refactor: simplify sender_name extraction using tuple isinstance check

Co-authored-by: RockChinQ <45992437+RockChinQ@users.noreply.github.com>

.dockerignore

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

.github/ISSUE_TEMPLATE/bug-report.yml

@@ -19,7 +19,7 @@ body:
   - type: textarea
     attributes:
       label: 复现步骤
-      description: 提供越多信息，我们会越快解决问题，建议多提供配置截图；**如果涉及 Dify、n8n、Langflow 等外部平台，请提供应用的导出文件（如 Dify 应用的 DSL），我们将更快回复您。**
+      description: 提供越多信息，我们会越快解决问题，建议多提供配置截图；**如果你不认真填写（只一两句话概括），我们会很生气并且立即关闭 issue 或两年后才回复你**
     validations:
       required: false
   - type: textarea

.github/ISSUE_TEMPLATE/bug-report_en.yml

@@ -19,7 +19,7 @@ body:
   - type: textarea
     attributes:
       label: Reproduction steps
-      description: How to reproduce this problem, the more detailed the better; the more information you provide, the faster we will solve the problem.
+      description: How to reproduce this problem, the more detailed the better; the more information you provide, the faster we will solve the problem. 【注意】请务必认真填写此部分，若不提供完整信息（如只有一两句话的概括），我们将不会回复！
     validations:
       required: false
   - type: textarea

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

@@ -3,6 +3,7 @@ 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
@@ -41,7 +42,7 @@ jobs:
         run: docker buildx create --name mybuilder --use
       - name: Build for Release # only relase, exlude pre-release
         if: ${{ github.event.release.prerelease == false }}
-        run: docker buildx build --platform linux/arm64,linux/amd64 -t rockchin/langbot:${{ steps.check_version.outputs.version }} -t rockchin/langbot:latest . --push
+        run: docker buildx build --platform 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: ${{ github.event.release.prerelease == true }}
-        run: docker buildx build --platform linux/arm64,linux/amd64 -t rockchin/langbot:${{ steps.check_version.outputs.version }} . --push
+        run: docker buildx build --platform linux/amd64 -t rockchin/langbot:${{ steps.check_version.outputs.version }} . --push

.github/workflows/lint.yml

@@ -1,60 +0,0 @@
-name: Lint
-
-on:
-  push:
-    branches:
-      - main
-      - master
-      - dev
-  pull_request:
-    types: [opened, synchronize, reopened, ready_for_review]
-
-jobs:
-  ruff:
-    name: Ruff Lint & Format
-    runs-on: ubuntu-latest
-    steps:
-      - name: Checkout code
-        uses: actions/checkout@v4
-
-      - name: Set up Python
-        uses: actions/setup-python@v5
-        with:
-          python-version: '3.12'
-
-      - name: Install uv
-        uses: astral-sh/setup-uv@v4
-
-      - name: Install dependencies
-        run: uv sync --dev
-
-      - name: Run ruff check
-        run: uv run ruff check src
-
-      - name: Run ruff format
-        run: uv run ruff format src --check
-
-  frontend:
-    name: Frontend Lint
-    runs-on: ubuntu-latest
-    steps:
-      - name: Checkout code
-        uses: actions/checkout@v4
-
-      - name: Setup Node.js
-        uses: actions/setup-node@v4
-        with:
-          node-version: '25'
-
-      - name: Install pnpm
-        uses: pnpm/action-setup@v4
-        with:
-          version: 9
-
-      - name: Install dependencies
-        working-directory: web
-        run: pnpm install
-
-      - name: Run lint
-        working-directory: web
-        run: pnpm lint

.github/workflows/run-tests.yml

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

.gitignore

@@ -42,6 +42,7 @@ botpy.log*
 test.py
 /web_ui
 .venv/
+uv.lock
 /test
 plugins.bak
 coverage.xml

AGENTS.md

@@ -8,17 +8,16 @@ 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:
 
-- `./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.
+- `./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
 
@@ -70,7 +69,6 @@ Plugin Runtime automatically starts each installed plugin and interacts through
     - type: must be a specific type, such as feat (new feature), fix (bug fix), docs (documentation), style (code style), refactor (refactoring), perf (performance optimization), etc.
     - scope: the scope of the commit, such as the package name, the file name, the function name, the class name, the module name, etc.
     - subject: the subject of the commit, such as the description of the commit, the reason for the commit, the impact of the commit, etc.
-- If you changed the definition of database entities, please update the migration file in `src/langbot/pkg/persistence/migrations/` and update the constants.py file in `src/langbot/pkg/utils/constants.py` with the new migration number.
 
 ## Some Principles
 

Dockerfile

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

README.md

@@ -1,69 +1,47 @@
+
 <p align="center">
 <a href="https://langbot.app">
-<img width="130" src="res/logo-blue.png" alt="LangBot"/>
+<img src="https://docs.langbot.app/social_zh.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>
+<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>Production-grade platform for building agentic IM bots.</h3>
-<h4>Quickly build, debug, and ship AI bots to Slack, Discord, Telegram, WeChat, and more.</h4>
-
-English / [简体中文](README_CN.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)
+[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)
+[![QQ Group](https://img.shields.io/badge/%E7%A4%BE%E5%8C%BAQQ%E7%BE%A4-966235608-blue)](https://qm.qq.com/q/JLi38whHum)
 [![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/langbot-app/LangBot)
 [![GitHub release (latest by date)](https://img.shields.io/github/v/release/langbot-app/LangBot)](https://github.com/langbot-app/LangBot/releases/latest)
 <img src="https://img.shields.io/badge/python-3.10 ~ 3.13 -blue.svg" alt="python">
-[![GitHub stars](https://img.shields.io/github/stars/langbot-app/LangBot?style=social)](https://github.com/langbot-app/LangBot/stargazers)
+[![star](https://gitcode.com/RockChinQ/LangBot/star/badge.svg)](https://gitcode.com/RockChinQ/LangBot)
+
+<a href="https://langbot.app">项目主页</a> ｜
+<a href="https://docs.langbot.app/zh/insight/guide.html">部署文档</a> ｜
+<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>
 
-<a href="https://langbot.app">Website</a> ｜
-<a href="https://docs.langbot.app/en/insight/features">Features</a> ｜
-<a href="https://docs.langbot.app/en/insight/guide">Docs</a> ｜
-<a href="https://docs.langbot.app/en/tags/readme">API</a> ｜
-<a href="https://space.langbot.app/cloud">Cloud</a> ｜
-<a href="https://space.langbot.app">Plugin Market</a> ｜
-<a href="https://langbot.featurebase.app/roadmap">Roadmap</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。
 
-## What is LangBot?
+## 📦 开始使用
 
-LangBot is an **open-source, production-grade platform** for building AI-powered instant messaging bots. It connects Large Language Models (LLMs) to any chat platform, enabling you to create intelligent agents that can converse, execute tasks, and integrate with your existing workflows.
+#### 快速部署
 
-### Key Capabilities
-
-- **AI Conversations & Agents** — Multi-turn dialogues, tool calling, multi-modal support, streaming output. Built-in RAG (knowledge base) with deep integration to [Dify](https://dify.ai), [Coze](https://coze.com), [n8n](https://n8n.io), [Langflow](https://langflow.org).
-- **Universal IM Platform Support** — One codebase for Discord, Telegram, Slack, LINE, QQ, WeChat, WeCom, Lark, DingTalk, KOOK.
-- **Production-Ready** — Access control, rate limiting, sensitive word filtering, comprehensive monitoring, and exception handling. Trusted by enterprises.
-- **Plugin Ecosystem** — Hundreds of plugins, event-driven architecture, component extensions, and [MCP protocol](https://modelcontextprotocol.io/) support.
-- **Web Management Panel** — Configure, manage, and monitor your bots through an intuitive browser interface. No YAML editing required.
-- **Multi-Pipeline Architecture** — Different bots for different scenarios, with comprehensive monitoring and exception handling.
-
-[→ Learn more about all features](https://docs.langbot.app/en/insight/features)
-
----
-
-## Quick Start
-
-### ☁️ LangBot Cloud (Recommended)
-
-**[LangBot Cloud](https://space.langbot.app/cloud)** — Zero deployment, ready to use.
-
-### One-Line Launch
+使用 `uvx` 一键启动（需要先安装 [uv](https://docs.astral.sh/uv/getting-started/installation/)）：
 
 ```bash
 uvx langbot
 ```
 
-> Requires [uv](https://docs.astral.sh/uv/getting-started/installation/). Visit http://localhost:5300 — done.
+访问 http://localhost:5300 即可开始使用。
 
-### Docker Compose
+#### Docker Compose 部署
 
 ```bash
 git clone https://github.com/langbot-app/LangBot
@@ -71,102 +49,122 @@ cd LangBot/docker
 docker compose up -d
 ```
 
-### One-Click Cloud Deploy
+访问 http://localhost:5300 即可开始使用。
+
+详细文档[Docker 部署](https://docs.langbot.app/zh/deploy/langbot/docker.html)。
+
+#### 宝塔面板部署
+
+已上架宝塔面板，若您已安装宝塔面板，可以根据[文档](https://docs.langbot.app/zh/deploy/langbot/one-click/bt.html)使用。
+
+#### Zeabur 云部署
+
+社区贡献的 Zeabur 模板。
+
+[![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/zh-CN/templates/ZKTBDH)
+
+#### Railway 云部署
 
-[![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/en-US/templates/ZKTBDH)
 [![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF)
 
-**More options:** [Docker](https://docs.langbot.app/en/deploy/langbot/docker) · [Manual](https://docs.langbot.app/en/deploy/langbot/manual) · [BTPanel](https://docs.langbot.app/en/deploy/langbot/one-click/bt) · [Kubernetes](./docker/README_K8S.md)
+#### 手动部署
 
----
+直接使用发行版运行，查看文档[手动部署](https://docs.langbot.app/zh/deploy/langbot/manual.html)。
 
-## Supported Platforms
+#### Kubernetes 部署
 
-| Platform | Status | Notes |
-|----------|--------|-------|
+参考 [Kubernetes 部署](./docker/README_K8S.md) 文档。
+
+## 😎 保持更新
+
+点击仓库右上角 Star 和 Watch 按钮，获取最新动态。
+
+![star gif](https://docs.langbot.app/star.gif)
+
+## ✨ 特性
+
+- 💬 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 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。
+- 🧩 插件扩展、活跃社区：高稳定性、高安全性的生产级插件系统，支持事件驱动、组件扩展等插件机制；适配 Anthropic [MCP 协议](https://modelcontextprotocol.io/)；目前已有数百个插件。
+- 😻 Web 管理面板：支持通过浏览器管理 LangBot 实例，不再需要手动编写配置文件。
+
+详细规格特性请访问[文档](https://docs.langbot.app/zh/insight/features.html)。
+
+或访问 demo 环境：https://demo.langbot.dev/  
+  - 登录信息：邮箱：`demo@langbot.app` 密码：`langbot123456`
+  - 注意：仅展示 WebUI 效果，公开环境，请不要在其中填入您的任何敏感信息。
+
+### 消息平台
+
+| 平台 | 状态 | 备注 |
+| --- | --- | --- |
+| QQ 个人号 | ✅ | QQ 个人号私聊、群聊 |
+| QQ 官方机器人 | ✅ | QQ 官方机器人，支持频道、私聊、群聊 |
+| 企业微信 | ✅ |  |
+| 企微对外客服 | ✅ |  |
+| 企微智能机器人 | ✅ |  |
+| 个人微信 | ✅ |  |
+| 微信公众号 | ✅ |  |
+| 飞书 | ✅ |  |
+| 钉钉 | ✅ |  |
 | Discord | ✅ |  |
 | Telegram | ✅ |  |
 | Slack | ✅ |  |
 | LINE | ✅ |  |
-| QQ | ✅ | Personal & Official API |
-| WeCom | ✅ | Enterprise WeChat, External CS, AI Bot |
-| WeChat | ✅ | Personal & Official Account |
-| Lark | ✅ |  |
-| DingTalk | ✅ |  |
-| KOOK | ✅ |  |
-| Satori | ✅ |  |
 
----
+### 大模型能力
 
-## Supported LLMs & Integrations
+| 模型 | 状态 | 备注 |
+| --- | --- | --- |
+| [OpenAI](https://platform.openai.com/) | ✅ | 可接入任何 OpenAI 接口格式模型 |
+| [DeepSeek](https://www.deepseek.com/) | ✅ |  |
+| [Moonshot](https://www.moonshot.cn/) | ✅ |  |
+| [Anthropic](https://www.anthropic.com/) | ✅ |  |
+| [xAI](https://x.ai/) | ✅ |  |
+| [智谱AI](https://open.bigmodel.cn/) | ✅ |  |
+| [胜算云](https://www.shengsuanyun.com/?from=CH_KYIPP758) | ✅ | 全球大模型都可调用（友情推荐） |
+| [优云智算](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | ✅ | 大模型和 GPU 资源平台 |
+| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | ✅ | 大模型和 GPU 资源平台 |
+| [接口 AI](https://jiekou.ai/) | ✅ | 大模型聚合平台，专注全球大模型接入 |
+| [302.AI](https://share.302.ai/SuTG99) | ✅ | 大模型聚合平台 |
+| [Google Gemini](https://aistudio.google.com/prompts/new_chat) | ✅ | |
+| [Dify](https://dify.ai) | ✅ | LLMOps 平台 |
+| [Ollama](https://ollama.com/) | ✅ | 本地大模型运行平台 |
+| [LMStudio](https://lmstudio.ai/) | ✅ | 本地大模型运行平台 |
+| [GiteeAI](https://ai.gitee.com/) | ✅ | 大模型接口聚合平台 |
+| [SiliconFlow](https://siliconflow.cn/) | ✅ | 大模型聚合平台 |
+| [小马算力](https://www.tokenpony.cn/453z1) | ✅ | 大模型聚合平台 |
+| [阿里云百炼](https://bailian.console.aliyun.com/) | ✅ | 大模型聚合平台, LLMOps 平台 |
+| [火山方舟](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | ✅ | 大模型聚合平台, LLMOps 平台 |
+| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | ✅ | 大模型聚合平台 |
+| [MCP](https://modelcontextprotocol.io/) | ✅ | 支持通过 MCP 协议获取工具 |
+| [百宝箱Tbox](https://www.tbox.cn/open) | ✅ | 蚂蚁百宝箱智能体平台，每月免费10亿大模型Token |
 
-| Provider | Type | Status |
-|----------|------|--------|
-| [OpenAI](https://platform.openai.com/) | LLM | ✅ |
-| [Anthropic](https://www.anthropic.com/) | LLM | ✅ |
-| [DeepSeek](https://www.deepseek.com/) | LLM | ✅ |
-| [Google Gemini](https://aistudio.google.com/prompts/new_chat) | LLM | ✅ |
-| [xAI](https://x.ai/) | LLM | ✅ |
-| [Moonshot](https://www.moonshot.cn/) | LLM | ✅ |
-| [Zhipu AI](https://open.bigmodel.cn/) | LLM | ✅ |
-| [Ollama](https://ollama.com/) | Local LLM | ✅ |
-| [LM Studio](https://lmstudio.ai/) | Local LLM | ✅ |
-| [Dify](https://dify.ai) | LLMOps | ✅ |
-| [MCP](https://modelcontextprotocol.io/) | Protocol | ✅ |
-| [SiliconFlow](https://siliconflow.cn/) | Gateway | ✅ |
-| [Aliyun Bailian](https://bailian.console.aliyun.com/) | Gateway | ✅ |
-| [Volc Engine Ark](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | Gateway | ✅ |
-| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | Gateway | ✅ |
-| [GiteeAI](https://ai.gitee.com/) | Gateway | ✅ |
-| [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | GPU Platform | ✅ |
-| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | GPU Platform | ✅ |
-| [ShengSuanYun](https://www.shengsuanyun.com/?from=CH_KYIPP758) | GPU Platform | ✅ |
-| [接口 AI](https://jiekou.ai/) | Gateway | ✅ |
-| [302.AI](https://share.302.ai/SuTG99) | Gateway | ✅ |
+### TTS
 
-[→ View all integrations](https://docs.langbot.app/en/insight/features)
+| 平台/模型 | 备注 |
+| --- | --- |
+| [FishAudio](https://fish.audio/zh-CN/discovery/) | [插件](https://github.com/the-lazy-me/NewChatVoice) |
+| [海豚 AI](https://www.ttson.cn/?source=thelazy) | [插件](https://github.com/the-lazy-me/NewChatVoice) |
+| [AzureTTS](https://portal.azure.com/) | [插件](https://github.com/Ingnaryk/LangBot_AzureTTS) |
 
----
+### 文生图
 
-## Why LangBot?
+| 平台/模型 | 备注 |
+| --- | --- |
+| 阿里云百炼 | [插件](https://github.com/Thetail001/LangBot_BailianTextToImagePlugin)
 
-| Use Case | How LangBot Helps |
-|----------|-------------------|
-| **Customer Support** | Deploy AI agents to Slack/Discord/Telegram that answer questions using your knowledge base |
-| **Internal Tools** | Connect n8n/Dify workflows to WeCom/DingTalk for automated business processes |
-| **Community Management** | Moderate QQ/Discord groups with AI-powered content filtering and interaction |
-| **Multi-Platform Presence** | One bot, all platforms. Manage from a single dashboard |
+## 😘 社区贡献
 
----
-
-## Live Demo
-
-**Try it now:** https://demo.langbot.dev/
-- Email: `demo@langbot.app`
-- Password: `langbot123456`
-
-*Note: Public demo environment. Do not enter sensitive information.*
-
----
-
-## Community
-
-[![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&label=Discord)](https://discord.gg/wdNEHETs87)
-
-- [Discord Community](https://discord.gg/wdNEHETs87)
-
----
-
-## Star History
-
-[![Star History Chart](https://api.star-history.com/svg?repos=langbot-app/LangBot&type=Date)](https://star-history.com/#langbot-app/LangBot&Date)
-
----
-
-## Contributors
-
-Thanks to all [contributors](https://github.com/langbot-app/LangBot/graphs/contributors) who have helped make LangBot better:
+感谢以下[代码贡献者](https://github.com/langbot-app/LangBot/graphs/contributors)和社区里其他成员对 LangBot 的贡献：
 
 <a href="https://github.com/langbot-app/LangBot/graphs/contributors">
   <img src="https://contrib.rocks/image?repo=langbot-app/LangBot" />
 </a>
+
+<!--
+## For Code Agents
+
+If you're a code agent based on LLM, you should read [AGENTS.md](AGENTS.md) to understand the project structure and development process before you start any development.
+-->

README_CN.md

@@ -1,197 +0,0 @@
-<p align="center">
-<a href="https://langbot.app">
-<img width="130" src="res/logo-blue.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>生产级 AI 即时通信机器人开发平台。</h3>
-<h4>快速构建、调试和部署 AI 机器人到微信、QQ、飞书、Slack、Discord、Telegram 等平台。</h4>
-
-[English](README.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)
-[![QQ Group](https://img.shields.io/badge/%E7%A4%BE%E5%8C%BAQQ%E7%BE%A4-1030838208-blue)](https://qm.qq.com/q/DxZZcNxM1W)
-[![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/langbot-app/LangBot)
-[![GitHub release (latest by date)](https://img.shields.io/github/v/release/langbot-app/LangBot)](https://github.com/langbot-app/LangBot/releases/latest)
-<img src="https://img.shields.io/badge/python-3.10 ~ 3.13 -blue.svg" alt="python">
-[![GitHub stars](https://img.shields.io/github/stars/langbot-app/LangBot?style=social)](https://github.com/langbot-app/LangBot/stargazers)
-[![star](https://gitcode.com/RockChinQ/LangBot/star/badge.svg)](https://gitcode.com/RockChinQ/LangBot)
-
-<a href="https://langbot.app">官网</a> ｜
-<a href="https://docs.langbot.app/zh/insight/features.html">特性</a> ｜
-<a href="https://docs.langbot.app/zh/insight/guide.html">文档</a> ｜
-<a href="https://docs.langbot.app/zh/tags/readme.html">API</a> ｜
-<a href="https://space.langbot.app/cloud">Cloud</a> ｜
-<a href="https://space.langbot.app">插件市场</a> ｜
-<a href="https://langbot.featurebase.app/roadmap">路线图</a>
-
-</div>
-
-</p>
-
----
-
-## 什么是 LangBot？
-
-LangBot 是一个**开源的生产级平台**，用于构建 AI 驱动的即时通信机器人。它将大语言模型（LLM）连接到各种聊天平台，帮助你创建能够对话、执行任务、并集成到现有工作流程中的智能 Agent。
-
-### 核心能力
-
-- **AI 对话与 Agent** — 多轮对话、工具调用、多模态、流式输出。自带 RAG（知识库），深度集成 [Dify](https://dify.ai)、[Coze](https://coze.com)、[n8n](https://n8n.io)、[Langflow](https://langflow.org) 等 LLMOps 平台。
-- **全平台支持** — 一套代码，覆盖 QQ、微信、企业微信、飞书、钉钉、Discord、Telegram、Slack、LINE、KOOK 等平台。
-- **生产就绪** — 访问控制、限速、敏感词过滤、全面监控与异常处理，已被多家企业采用。
-- **插件生态** — 数百个插件，事件驱动架构，组件扩展，适配 [MCP 协议](https://modelcontextprotocol.io/)。
-- **Web 管理面板** — 通过浏览器直观地配置、管理和监控机器人，无需手动编辑配置文件。
-- **多流水线架构** — 不同机器人用于不同场景，具备全面的监控和异常处理能力。
-
-[→ 了解更多功能特性](https://docs.langbot.app/zh/insight/features.html)
-
----
-
-## 快速开始
-
-### ☁️ LangBot Cloud（推荐）
-
-**[LangBot Cloud](https://space.langbot.app/cloud)** — 免部署，开箱即用。
-
-### 一键启动
-
-```bash
-uvx langbot
-```
-
-> 需要安装 [uv](https://docs.astral.sh/uv/getting-started/installation/)。访问 http://localhost:5300 即可使用。
-
-### Docker Compose
-
-```bash
-git clone https://github.com/langbot-app/LangBot
-cd LangBot/docker
-docker compose up -d
-```
-
-### 一键云部署
-
-[![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/zh-CN/templates/ZKTBDH)
-[![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF)
-
-**更多方式：** [Docker](https://docs.langbot.app/zh/deploy/langbot/docker.html) · [手动部署](https://docs.langbot.app/zh/deploy/langbot/manual.html) · [宝塔面板](https://docs.langbot.app/zh/deploy/langbot/one-click/bt.html) · [Kubernetes](./docker/README_K8S.md)
-
----
-
-## 支持的平台
-
-| 平台 | 状态 | 备注 |
-|------|------|------|
-| QQ | ✅ | 个人号、官方机器人（频道、私聊、群聊） |
-| 微信 | ✅ | 个人微信、微信公众号 |
-| 企业微信 | ✅ | 应用消息、对外客服、智能机器人 |
-| 飞书 | ✅ |  |
-| 钉钉 | ✅ |  |
-| Discord | ✅ |  |
-| Telegram | ✅ |  |
-| Slack | ✅ |  |
-| LINE | ✅ |  |
-| KOOK | ✅ |  |
-
----
-
-## 支持的大模型与集成
-
-| 提供商 | 类型 | 状态 |
-|--------|------|------|
-| [OpenAI](https://platform.openai.com/) | LLM | ✅ |
-| [Anthropic](https://www.anthropic.com/) | LLM | ✅ |
-| [DeepSeek](https://www.deepseek.com/) | LLM | ✅ |
-| [Google Gemini](https://aistudio.google.com/prompts/new_chat) | LLM | ✅ |
-| [xAI](https://x.ai/) | LLM | ✅ |
-| [Moonshot](https://www.moonshot.cn/) | LLM | ✅ |
-| [智谱AI](https://open.bigmodel.cn/) | LLM | ✅ |
-| [Ollama](https://ollama.com/) | 本地 LLM | ✅ |
-| [LM Studio](https://lmstudio.ai/) | 本地 LLM | ✅ |
-| [Dify](https://dify.ai) | LLMOps | ✅ |
-| [MCP](https://modelcontextprotocol.io/) | 协议 | ✅ |
-| [SiliconFlow](https://siliconflow.cn/) | 聚合平台 | ✅ |
-| [阿里云百炼](https://bailian.console.aliyun.com/) | 聚合平台 | ✅ |
-| [火山方舟](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | 聚合平台 | ✅ |
-| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | 聚合平台 | ✅ |
-| [GiteeAI](https://ai.gitee.com/) | 聚合平台 | ✅ |
-| [胜算云](https://www.shengsuanyun.com/?from=CH_KYIPP758) | GPU 平台 | ✅ |
-| [优云智算](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | GPU 平台 | ✅ |
-| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | GPU 平台 | ✅ |
-| [接口 AI](https://jiekou.ai/) | 聚合平台 | ✅ |
-| [302.AI](https://share.302.ai/SuTG99) | 聚合平台 | ✅ |
-| [小马算力](https://www.tokenpony.cn/453z1) | 聚合平台 | ✅ |
-| [百宝箱Tbox](https://www.tbox.cn/open) | 智能体平台 | ✅ |
-
-[→ 查看完整集成列表](https://docs.langbot.app/zh/insight/features.html)
-
-### TTS（语音合成）
-
-| 平台/模型 | 备注 |
-|-----------|------|
-| [FishAudio](https://fish.audio/zh-CN/discovery/) | [插件](https://github.com/the-lazy-me/NewChatVoice) |
-| [海豚 AI](https://www.ttson.cn/?source=thelazy) | [插件](https://github.com/the-lazy-me/NewChatVoice) |
-| [AzureTTS](https://portal.azure.com/) | [插件](https://github.com/Ingnaryk/LangBot_AzureTTS) |
-
-### 文生图
-
-| 平台/模型 | 备注 |
-|-----------|------|
-| 阿里云百炼 | [插件](https://github.com/Thetail001/LangBot_BailianTextToImagePlugin) |
-
----
-
-## 为什么选择 LangBot？
-
-| 使用场景 | LangBot 如何帮助 |
-|----------|------------------|
-| **客户服务** | 将 AI Agent 部署到微信/企微/钉钉/飞书，基于知识库自动回答用户问题 |
-| **内部工具** | 将 n8n/Dify 工作流接入企微/钉钉，实现业务流程自动化 |
-| **社群运营** | 在 QQ/Discord 群中使用 AI 驱动的内容审核与智能互动 |
-| **多平台触达** | 一个机器人，覆盖所有平台。通过统一面板集中管理 |
-
----
-
-## 在线演示
-
-**立即体验：** https://demo.langbot.dev/
-- 邮箱：`demo@langbot.app`
-- 密码：`langbot123456`
-
-*注意：公开演示环境，请不要在其中填入任何敏感信息。*
-
----
-
-## 社区
-
-[![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&label=Discord)](https://discord.gg/wdNEHETs87)
-[![QQ Group](https://img.shields.io/badge/%E7%A4%BE%E5%8C%BAQQ%E7%BE%A4-1030838208-blue)](https://qm.qq.com/q/DxZZcNxM1W)
-
-- [Discord 社区](https://discord.gg/wdNEHETs87)
-- [QQ 社区群](https://qm.qq.com/q/DxZZcNxM1W)
-
----
-
-## Star 趋势
-
-[![Star History Chart](https://api.star-history.com/svg?repos=langbot-app/LangBot&type=Date)](https://star-history.com/#langbot-app/LangBot&Date)
-
----
-
-## 贡献者
-
-感谢所有[贡献者](https://github.com/langbot-app/LangBot/graphs/contributors)对 LangBot 的帮助：
-
-<a href="https://github.com/langbot-app/LangBot/graphs/contributors">
-  <img src="https://contrib.rocks/image?repo=langbot-app/LangBot" />
-</a>
-
-<!--
-## For Code Agents
-
-If you're a code agent based on LLM, you should read [AGENTS.md](AGENTS.md) to understand the project structure and development process before you start any development.
--->

README_EN.md

@@ -0,0 +1,143 @@
+<p align="center">
+<a href="https://langbot.app">
+<img src="https://docs.langbot.app/social_en.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>
+
+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)
+[![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/langbot-app/LangBot)
+[![GitHub release (latest by date)](https://img.shields.io/github/v/release/langbot-app/LangBot)](https://github.com/langbot-app/LangBot/releases/latest)
+<img src="https://img.shields.io/badge/python-3.10 ~ 3.13 -blue.svg" alt="python">
+
+<a href="https://langbot.app">Home</a> ｜
+<a href="https://docs.langbot.app/en/insight/guide.html">Deployment</a> ｜
+<a href="https://docs.langbot.app/en/plugin/plugin-intro.html">Plugin</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">Submit Plugin</a>
+
+</div>
+
+</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
+
+#### Quick Start
+
+Use `uvx` to start with one command (need to install [uv](https://docs.astral.sh/uv/getting-started/installation/)):
+
+```bash
+uvx langbot
+```
+
+Visit http://localhost:5300 to start using it.
+
+#### Docker Compose Deployment
+
+```bash
+git clone https://github.com/langbot-app/LangBot
+cd LangBot/docker
+docker compose up -d
+```
+
+Visit http://localhost:5300 to start using it.
+
+Detailed documentation [Docker Deployment](https://docs.langbot.app/en/deploy/langbot/docker.html).
+
+#### One-click Deployment on BTPanel
+
+LangBot has been listed on the BTPanel, if you have installed the BTPanel, you can use the [document](https://docs.langbot.app/en/deploy/langbot/one-click/bt.html) to use it.
+
+#### Zeabur Cloud Deployment
+
+Community contributed Zeabur template.
+
+[![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/en-US/templates/ZKTBDH)
+
+#### Railway Cloud Deployment
+
+[![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF)
+
+#### Other Deployment Methods
+
+Directly use the released version to run, see the [Manual Deployment](https://docs.langbot.app/en/deploy/langbot/manual.html) documentation.
+
+#### Kubernetes Deployment
+
+Refer to the [Kubernetes Deployment](./docker/README_K8S.md) documentation.
+
+## 😎 Stay Ahead
+
+Click the Star and Watch button in the upper right corner of the repository to get the latest updates.
+
+![star gif](https://docs.langbot.app/star.gif)
+
+## ✨ Features
+
+- 💬 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, 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.
+- 🧩 Plugin Extension, Active Community: High stability, high security production-level plugin system; Support event-driven, component extension, etc. plugin mechanisms; Integrate Anthropic [MCP protocol](https://modelcontextprotocol.io/); Currently has hundreds of plugins.
+- 😻 Web UI: Support management LangBot instance through the browser. No need to manually write configuration files.
+
+For more detailed specifications, please refer to the [documentation](https://docs.langbot.app/en/insight/features.html).
+
+Or visit the demo environment: https://demo.langbot.dev/
+  - Login information: Email: `demo@langbot.app` Password: `langbot123456`
+  - Note: For WebUI demo only, please do not fill in any sensitive information in the public environment.
+
+### Message Platform
+
+| Platform | Status | Remarks |
+| --- | --- | --- |
+| Discord | ✅ |  |
+| Telegram | ✅ |  |
+| Slack | ✅ |  |
+| LINE | ✅ |  |
+| Personal QQ | ✅ |  |
+| QQ Official API | ✅ |  |
+| WeCom | ✅ |  |
+| WeComCS | ✅ |  |
+| WeCom AI Bot | ✅ |  |
+| Personal WeChat | ✅ |  |
+| Lark | ✅ |  |
+| DingTalk | ✅ |  |
+
+### LLMs
+
+| LLM | Status | Remarks |
+| --- | --- | --- |
+| [OpenAI](https://platform.openai.com/) | ✅ | Available for any OpenAI interface format model |
+| [DeepSeek](https://www.deepseek.com/) | ✅ |  |
+| [Moonshot](https://www.moonshot.cn/) | ✅ |  |
+| [Anthropic](https://www.anthropic.com/) | ✅ |  |
+| [xAI](https://x.ai/) | ✅ |  |
+| [Zhipu AI](https://open.bigmodel.cn/) | ✅ |  |
+| [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | ✅ | LLM and GPU resource platform |
+| [Dify](https://dify.ai) | ✅ | LLMOps platform |
+| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | ✅ | LLM and GPU resource platform |
+| [接口 AI](https://jiekou.ai/) | ✅ | LLM aggregation platform, dedicated to global LLMs |
+| [ShengSuanYun](https://www.shengsuanyun.com/?from=CH_KYIPP758) | ✅ | LLM and GPU resource platform |
+| [302.AI](https://share.302.ai/SuTG99) | ✅ | LLM gateway(MaaS) |
+| [Google Gemini](https://aistudio.google.com/prompts/new_chat) | ✅ | |
+| [Ollama](https://ollama.com/) | ✅ | Local LLM running platform |
+| [LMStudio](https://lmstudio.ai/) | ✅ | Local LLM running platform |
+| [GiteeAI](https://ai.gitee.com/) | ✅ | LLM interface gateway(MaaS) |
+| [SiliconFlow](https://siliconflow.cn/) | ✅ | LLM gateway(MaaS) |
+| [Aliyun Bailian](https://bailian.console.aliyun.com/) | ✅ | LLM gateway(MaaS), LLMOps platform |
+| [Volc Engine Ark](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | ✅ | LLM gateway(MaaS), LLMOps platform |
+| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | ✅ | LLM gateway(MaaS) |
+| [MCP](https://modelcontextprotocol.io/) | ✅ | Support tool access through MCP protocol |
+
+## 🤝 Community Contribution
+
+Thank you for the following [code contributors](https://github.com/langbot-app/LangBot/graphs/contributors) and other members in the community for their contributions to LangBot:
+
+<a href="https://github.com/langbot-app/LangBot/graphs/contributors">
+  <img src="https://contrib.rocks/image?repo=langbot-app/LangBot" />
+</a>

README_ES.md

@@ -1,68 +1,43 @@
 <p align="center">
 <a href="https://langbot.app">
-<img width="130" src="res/logo-blue.png" alt="LangBot"/>
+<img src="https://docs.langbot.app/social_en.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>Plataforma de grado de producción para construir bots de mensajería instantánea con agentes de IA.</h3>
-<h4>Construya, depure y despliegue bots de IA rápidamente en Slack, Discord, Telegram, WeChat y más.</h4>
-
-[English](README.md) / [简体中文](README_CN.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)
+[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)
 [![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/langbot-app/LangBot)
 [![GitHub release (latest by date)](https://img.shields.io/github/v/release/langbot-app/LangBot)](https://github.com/langbot-app/LangBot/releases/latest)
 <img src="https://img.shields.io/badge/python-3.10 ~ 3.13 -blue.svg" alt="python">
-[![GitHub stars](https://img.shields.io/github/stars/langbot-app/LangBot?style=social)](https://github.com/langbot-app/LangBot/stargazers)
 
 <a href="https://langbot.app">Inicio</a> ｜
-<a href="https://docs.langbot.app/en/insight/features.html">Características</a> ｜
-<a href="https://docs.langbot.app/en/insight/guide.html">Documentación</a> ｜
-<a href="https://docs.langbot.app/en/tags/readme.html">API</a> ｜
-<a href="https://space.langbot.app">Mercado de Plugins</a> ｜
-<a href="https://langbot.featurebase.app/roadmap">Hoja de Ruta</a>
+<a href="https://docs.langbot.app/en/insight/guide.html">Despliegue</a> ｜
+<a href="https://docs.langbot.app/en/plugin/plugin-intro.html">Plugin</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">Enviar Plugin</a>
 
 </div>
 
 </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.
 
-## ¿Qué es LangBot?
+## 📦 Comenzar
 
-LangBot es una **plataforma de código abierto y grado de producción** para construir bots de mensajería instantánea impulsados por IA. Conecta modelos de lenguaje de gran escala (LLMs) con cualquier plataforma de chat, permitiéndole crear agentes inteligentes que pueden conversar, ejecutar tareas e integrarse con sus flujos de trabajo existentes.
+#### Inicio Rápido
 
-### Capacidades Clave
-
-- **Conversaciones e Agentes IA** — Diálogos de múltiples turnos, llamadas a herramientas, soporte multimodal, salida en streaming. RAG (base de conocimientos) incorporado con integración profunda con [Dify](https://dify.ai), [Coze](https://coze.com), [n8n](https://n8n.io), [Langflow](https://langflow.org).
-- **Soporte Universal de Plataformas de MI** — Un solo código base para Discord, Telegram, Slack, LINE, QQ, WeChat, WeCom, Lark, DingTalk, KOOK.
-- **Listo para Producción** — Control de acceso, limitación de velocidad, filtrado de palabras sensibles, monitoreo completo y manejo de excepciones. De confianza para empresas.
-- **Ecosistema de Plugins** — Cientos de plugins, arquitectura basada en eventos, extensiones de componentes y soporte del [protocolo MCP](https://modelcontextprotocol.io/).
-- **Panel de Gestión Web** — Configure, gestione y monitoree sus bots a través de una interfaz de navegador intuitiva. Sin necesidad de editar YAML.
-- **Arquitectura Multi-Pipeline** — Diferentes bots para diferentes escenarios, con monitoreo completo y manejo de excepciones.
-
-[→ Conocer más sobre todas las funcionalidades](https://docs.langbot.app/en/insight/features.html)
-
----
-
-## Inicio Rápido
-
-### ☁️ LangBot Cloud (Recomendado)
-
-**[LangBot Cloud](https://space.langbot.app/cloud)** — Sin despliegue, listo para usar.
-
-### Lanzamiento en una línea
+Use `uvx` para iniciar con un comando (necesita instalar [uv](https://docs.astral.sh/uv/getting-started/installation/)):
 
 ```bash
 uvx langbot
 ```
 
-> Requiere [uv](https://docs.astral.sh/uv/getting-started/installation/). Visite http://localhost:5300 — listo.
+Visite http://localhost:5300 para comenzar a usarlo.
 
-### Docker Compose
+#### Despliegue con Docker Compose
 
 ```bash
 git clone https://github.com/langbot-app/LangBot
@@ -70,101 +45,98 @@ cd LangBot/docker
 docker compose up -d
 ```
 
-### Despliegue en la Nube con un Clic
+Visite http://localhost:5300 para comenzar a usarlo.
+
+Documentación detallada [Despliegue con Docker](https://docs.langbot.app/en/deploy/langbot/docker.html).
+
+#### Despliegue con un clic en BTPanel
+
+LangBot ha sido listado en BTPanel. Si tiene BTPanel instalado, puede usar la [documentación](https://docs.langbot.app/en/deploy/langbot/one-click/bt.html) para usarlo.
+
+#### Despliegue en la Nube Zeabur
+
+Plantilla de Zeabur contribuida por la comunidad.
 
 [![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/en-US/templates/ZKTBDH)
+
+#### Despliegue en la Nube Railway
+
 [![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF)
 
-**Más opciones:** [Docker](https://docs.langbot.app/en/deploy/langbot/docker.html) · [Manual](https://docs.langbot.app/en/deploy/langbot/manual.html) · [BTPanel](https://docs.langbot.app/en/deploy/langbot/one-click/bt.html) · [Kubernetes](./docker/README_K8S.md)
+#### Otros Métodos de Despliegue
 
----
+Use directamente la versión publicada para ejecutar, consulte la documentación de [Despliegue Manual](https://docs.langbot.app/en/deploy/langbot/manual.html).
 
-## Plataformas Soportadas
+#### Despliegue en Kubernetes
 
-| Plataforma | Estado | Notas |
-|----------|--------|-------|
+Consulte la documentación de [Despliegue en Kubernetes](./docker/README_K8S.md).
+
+## 😎 Manténgase Actualizado
+
+Haga clic en los botones Star y Watch en la esquina superior derecha del repositorio para obtener las últimas actualizaciones.
+
+![star gif](https://docs.langbot.app/star.gif)
+
+## ✨ Características
+
+- 💬 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, 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.
+- 🧩 Extensión de Plugin, Comunidad Activa: Sistema de plugin de alta estabilidad, alta seguridad de nivel de producción; Compatible con mecanismos de plugin impulsados por eventos, extensión de componentes, etc.; Integración del protocolo [MCP](https://modelcontextprotocol.io/) de Anthropic; Actualmente cuenta con cientos de plugins.
+- 😻 Interfaz Web: Admite la gestión de instancias de LangBot a través del navegador. No es necesario escribir archivos de configuración manualmente.
+
+Para especificaciones más detalladas, consulte la [documentación](https://docs.langbot.app/en/insight/features.html).
+
+O visite el entorno de demostración: https://demo.langbot.dev/
+  - Información de inicio de sesión: Correo electrónico: `demo@langbot.app` Contraseña: `langbot123456`
+  - Nota: Solo para demostración de WebUI, por favor no ingrese información confidencial en el entorno público.
+
+### Plataformas de Mensajería
+
+| Plataforma | Estado | Observaciones |
+| --- | --- | --- |
 | Discord | ✅ |  |
 | Telegram | ✅ |  |
 | Slack | ✅ |  |
 | LINE | ✅ |  |
-| QQ | ✅ | Personal y API Oficial |
-| WeCom | ✅ | WeChat Empresarial, CS Externo, AI Bot |
-| WeChat | ✅ | Personal y Cuenta Oficial |
+| QQ Personal | ✅ |  |
+| QQ API Oficial | ✅ |  |
+| WeCom | ✅ |  |
+| WeComCS | ✅ |  |
+| WeCom AI Bot | ✅ |  |
+| WeChat Personal | ✅ |  |
 | Lark | ✅ |  |
 | DingTalk | ✅ |  |
-| KOOK | ✅ |  |
-| Satori | ✅ |  |
 
----
+### LLMs
 
-## LLMs e Integraciones Soportadas
+| LLM | Estado | Observaciones |
+| --- | --- | --- |
+| [OpenAI](https://platform.openai.com/) | ✅ | Disponible para cualquier modelo con formato de interfaz OpenAI |
+| [DeepSeek](https://www.deepseek.com/) | ✅ |  |
+| [Moonshot](https://www.moonshot.cn/) | ✅ |  |
+| [Anthropic](https://www.anthropic.com/) | ✅ |  |
+| [xAI](https://x.ai/) | ✅ |  |
+| [Zhipu AI](https://open.bigmodel.cn/) | ✅ |  |
+| [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | ✅ | Plataforma de recursos LLM y GPU |
+| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | ✅ | Plataforma de recursos LLM y GPU |
+| [接口 AI](https://jiekou.ai/) | ✅ | Plataforma de agregación LLM |
+| [ShengSuanYun](https://www.shengsuanyun.com/?from=CH_KYIPP758) | ✅ | Plataforma de recursos LLM y GPU |
+| [302.AI](https://share.302.ai/SuTG99) | ✅ | Gateway LLM (MaaS) |
+| [Google Gemini](https://aistudio.google.com/prompts/new_chat) | ✅ | |
+| [Dify](https://dify.ai) | ✅ | Plataforma LLMOps |
+| [Ollama](https://ollama.com/) | ✅ | Plataforma de ejecución de LLM local |
+| [LMStudio](https://lmstudio.ai/) | ✅ | Plataforma de ejecución de LLM local |
+| [GiteeAI](https://ai.gitee.com/) | ✅ | Gateway de interfaz LLM (MaaS) |
+| [SiliconFlow](https://siliconflow.cn/) | ✅ | Gateway LLM (MaaS) |
+| [Aliyun Bailian](https://bailian.console.aliyun.com/) | ✅ | Gateway LLM (MaaS), plataforma LLMOps |
+| [Volc Engine Ark](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | ✅ | Gateway LLM (MaaS), plataforma LLMOps |
+| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | ✅ | Gateway LLM (MaaS) |
+| [MCP](https://modelcontextprotocol.io/) | ✅ | Compatible con acceso a herramientas a través del protocolo MCP |
 
-| Proveedor | Tipo | Estado |
-|----------|------|--------|
-| [OpenAI](https://platform.openai.com/) | LLM | ✅ |
-| [Anthropic](https://www.anthropic.com/) | LLM | ✅ |
-| [DeepSeek](https://www.deepseek.com/) | LLM | ✅ |
-| [Google Gemini](https://aistudio.google.com/prompts/new_chat) | LLM | ✅ |
-| [xAI](https://x.ai/) | LLM | ✅ |
-| [Moonshot](https://www.moonshot.cn/) | LLM | ✅ |
-| [Zhipu AI](https://open.bigmodel.cn/) | LLM | ✅ |
-| [Ollama](https://ollama.com/) | LLM Local | ✅ |
-| [LM Studio](https://lmstudio.ai/) | LLM Local | ✅ |
-| [Dify](https://dify.ai) | LLMOps | ✅ |
-| [MCP](https://modelcontextprotocol.io/) | Protocolo | ✅ |
-| [SiliconFlow](https://siliconflow.cn/) | Pasarela | ✅ |
-| [Aliyun Bailian](https://bailian.console.aliyun.com/) | Pasarela | ✅ |
-| [Volc Engine Ark](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | Pasarela | ✅ |
-| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | Pasarela | ✅ |
-| [GiteeAI](https://ai.gitee.com/) | Pasarela | ✅ |
-| [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | Plataforma GPU | ✅ |
-| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | Plataforma GPU | ✅ |
-| [ShengSuanYun](https://www.shengsuanyun.com/?from=CH_KYIPP758) | Plataforma GPU | ✅ |
-| [接口 AI](https://jiekou.ai/) | Pasarela | ✅ |
-| [302.AI](https://share.302.ai/SuTG99) | Pasarela | ✅ |
+## 🤝 Contribución de la Comunidad
 
-[→ Ver todas las integraciones](https://docs.langbot.app/en/insight/features.html)
-
----
-
-## ¿Por qué LangBot?
-
-| Caso de Uso | Cómo Ayuda LangBot |
-|----------|-------------------|
-| **Atención al cliente** | Despliegue agentes de IA en Slack/Discord/Telegram que respondan preguntas usando su base de conocimientos |
-| **Herramientas internas** | Conecte flujos de trabajo de n8n/Dify a WeCom/DingTalk para procesos empresariales automatizados |
-| **Gestión de comunidades** | Modere grupos de QQ/Discord con filtrado de contenido e interacción impulsados por IA |
-| **Presencia multiplataforma** | Un solo bot, todas las plataformas. Gestione desde un único panel de control |
-
----
-
-## Demo en Vivo
-
-**Pruébelo ahora:** https://demo.langbot.dev/
-- Correo electrónico: `demo@langbot.app`
-- Contraseña: `langbot123456`
-
-*Nota: Entorno de demostración público. No ingrese información confidencial.*
-
----
-
-## Comunidad
-
-[![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&label=Discord)](https://discord.gg/wdNEHETs87)
-
-- [Comunidad de Discord](https://discord.gg/wdNEHETs87)
-
----
-
-## Historial de Stars
-
-[![Star History Chart](https://api.star-history.com/svg?repos=langbot-app/LangBot&type=Date)](https://star-history.com/#langbot-app/LangBot&Date)
-
----
-
-## Colaboradores
-
-Gracias a todos los [colaboradores](https://github.com/langbot-app/LangBot/graphs/contributors) que han ayudado a mejorar LangBot:
+Gracias a los siguientes [contribuidores de código](https://github.com/langbot-app/LangBot/graphs/contributors) y otros miembros de la comunidad por sus contribuciones a LangBot:
 
 <a href="https://github.com/langbot-app/LangBot/graphs/contributors">
   <img src="https://contrib.rocks/image?repo=langbot-app/LangBot" />

README_FR.md

@@ -1,68 +1,43 @@
 <p align="center">
 <a href="https://langbot.app">
-<img width="130" src="res/logo-blue.png" alt="LangBot"/>
+<img src="https://docs.langbot.app/social_en.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>Plateforme de niveau production pour construire des bots de messagerie instantanée avec agents IA.</h3>
-<h4>Créez, déboguez et déployez rapidement des bots IA sur Slack, Discord, Telegram, WeChat et plus.</h4>
-
-[English](README.md) / [简体中文](README_CN.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)
+[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)
 [![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/langbot-app/LangBot)
 [![GitHub release (latest by date)](https://img.shields.io/github/v/release/langbot-app/LangBot)](https://github.com/langbot-app/LangBot/releases/latest)
 <img src="https://img.shields.io/badge/python-3.10 ~ 3.13 -blue.svg" alt="python">
-[![GitHub stars](https://img.shields.io/github/stars/langbot-app/LangBot?style=social)](https://github.com/langbot-app/LangBot/stargazers)
 
 <a href="https://langbot.app">Accueil</a> ｜
-<a href="https://docs.langbot.app/en/insight/features.html">Fonctionnalités</a> ｜
-<a href="https://docs.langbot.app/en/insight/guide.html">Documentation</a> ｜
-<a href="https://docs.langbot.app/en/tags/readme.html">API</a> ｜
-<a href="https://space.langbot.app">Marché des Plugins</a> ｜
-<a href="https://langbot.featurebase.app/roadmap">Feuille de Route</a>
+<a href="https://docs.langbot.app/en/insight/guide.html">Déploiement</a> ｜
+<a href="https://docs.langbot.app/en/plugin/plugin-intro.html">Plugin</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">Soumettre un Plugin</a>
 
 </div>
 
 </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.
 
-## Qu'est-ce que LangBot ?
+## 📦 Commencer
 
-LangBot est une **plateforme open-source de niveau production** pour créer des bots de messagerie instantanée alimentés par l'IA. Elle connecte les grands modèles de langage (LLMs) à n'importe quelle plateforme de chat, vous permettant de créer des agents intelligents capables de converser, d'exécuter des tâches et de s'intégrer à vos workflows existants.
+#### Démarrage Rapide
 
-### Capacités Clés
-
-- **Conversations IA & Agents** — Dialogues multi-tours, appels d'outils, support multimodal, sortie en streaming. RAG (base de connaissances) intégré avec intégration profonde de [Dify](https://dify.ai), [Coze](https://coze.com), [n8n](https://n8n.io), [Langflow](https://langflow.org).
-- **Support Universel des Plateformes de MI** — Un seul code pour Discord, Telegram, Slack, LINE, QQ, WeChat, WeCom, Lark, DingTalk, KOOK.
-- **Prêt pour la Production** — Contrôle d'accès, limitation de débit, filtrage de mots sensibles, surveillance complète et gestion des exceptions. Approuvé par les entreprises.
-- **Écosystème de Plugins** — Des centaines de plugins, architecture événementielle, extensions de composants, et support du [protocole MCP](https://modelcontextprotocol.io/).
-- **Panneau de Gestion Web** — Configurez, gérez et surveillez vos bots via une interface navigateur intuitive. Aucune édition de YAML requise.
-- **Architecture Multi-Pipeline** — Différents bots pour différents scénarios, avec surveillance complète et gestion des exceptions.
-
-[→ En savoir plus sur toutes les fonctionnalités](https://docs.langbot.app/en/insight/features.html)
-
----
-
-## Démarrage Rapide
-
-### ☁️ LangBot Cloud (Recommandé)
-
-**[LangBot Cloud](https://space.langbot.app/cloud)** — Sans déploiement, prêt à utiliser.
-
-### Lancement en une ligne
+Utilisez `uvx` pour démarrer avec une commande (besoin d'installer [uv](https://docs.astral.sh/uv/getting-started/installation/)) :
 
 ```bash
 uvx langbot
 ```
 
-> Nécessite [uv](https://docs.astral.sh/uv/getting-started/installation/). Visitez http://localhost:5300 — c'est prêt.
+Visitez http://localhost:5300 pour commencer à l'utiliser.
 
-### Docker Compose
+#### Déploiement avec Docker Compose
 
 ```bash
 git clone https://github.com/langbot-app/LangBot
@@ -70,101 +45,98 @@ cd LangBot/docker
 docker compose up -d
 ```
 
-### Déploiement Cloud en un Clic
+Visitez http://localhost:5300 pour commencer à l'utiliser.
+
+Documentation détaillée [Déploiement Docker](https://docs.langbot.app/en/deploy/langbot/docker.html).
+
+#### Déploiement en un clic sur BTPanel
+
+LangBot a été répertorié sur BTPanel. Si vous avez installé BTPanel, vous pouvez utiliser la [documentation](https://docs.langbot.app/en/deploy/langbot/one-click/bt.html) pour l'utiliser.
+
+#### Déploiement Cloud Zeabur
+
+Modèle Zeabur contribué par la communauté.
 
 [![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/en-US/templates/ZKTBDH)
+
+#### Déploiement Cloud Railway
+
 [![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF)
 
-**Plus d'options :** [Docker](https://docs.langbot.app/en/deploy/langbot/docker.html) · [Manuel](https://docs.langbot.app/en/deploy/langbot/manual.html) · [BTPanel](https://docs.langbot.app/en/deploy/langbot/one-click/bt.html) · [Kubernetes](./docker/README_K8S.md)
+#### Autres Méthodes de Déploiement
 
----
+Utilisez directement la version publiée pour exécuter, consultez la documentation de [Déploiement Manuel](https://docs.langbot.app/en/deploy/langbot/manual.html).
 
-## Plateformes Supportées
+#### Déploiement Kubernetes
 
-| Plateforme | Statut | Notes |
-|----------|--------|-------|
+Consultez la documentation de [Déploiement Kubernetes](./docker/README_K8S.md).
+
+## 😎 Restez à Jour
+
+Cliquez sur les boutons Star et Watch dans le coin supérieur droit du dépôt pour obtenir les dernières mises à jour.
+
+![star gif](https://docs.langbot.app/star.gif)
+
+## ✨ Fonctionnalités
+
+- 💬 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, 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.
+- 🧩 Extension de Plugin, Communauté Active : Système de plugin de haute stabilité, haute sécurité de niveau production; Prend en charge les mécanismes de plugin pilotés par événements, l'extension de composants, etc. ; Intégration du protocole [MCP](https://modelcontextprotocol.io/) d'Anthropic ; Dispose actuellement de centaines de plugins.
+- 😻 Interface Web : Prend en charge la gestion des instances LangBot via le navigateur. Pas besoin d'écrire manuellement les fichiers de configuration.
+
+Pour des spécifications plus détaillées, veuillez consulter la [documentation](https://docs.langbot.app/en/insight/features.html).
+
+Ou visitez l'environnement de démonstration : https://demo.langbot.dev/
+  - Informations de connexion : Email : `demo@langbot.app` Mot de passe : `langbot123456`
+  - Note : Pour la démonstration WebUI uniquement, veuillez ne pas entrer d'informations sensibles dans l'environnement public.
+
+### Plateformes de Messagerie
+
+| Plateforme | Statut | Remarques |
+| --- | --- | --- |
 | Discord | ✅ |  |
 | Telegram | ✅ |  |
 | Slack | ✅ |  |
 | LINE | ✅ |  |
-| QQ | ✅ | Personnel & API Officielle |
-| WeCom | ✅ | WeChat Entreprise, CS Externe, AI Bot |
-| WeChat | ✅ | Personnel & Compte Officiel |
+| QQ Personnel | ✅ |  |
+| API Officielle QQ | ✅ |  |
+| WeCom | ✅ |  |
+| WeComCS | ✅ |  |
+| WeCom AI Bot | ✅ |  |
+| WeChat Personnel | ✅ |  |
 | Lark | ✅ |  |
 | DingTalk | ✅ |  |
-| KOOK | ✅ |  |
-| Satori | ✅ |  |
 
----
+### LLMs
 
-## LLMs et Intégrations Supportés
+| LLM | Statut | Remarques |
+| --- | --- | --- |
+| [OpenAI](https://platform.openai.com/) | ✅ | Disponible pour tout modèle au format d'interface OpenAI |
+| [DeepSeek](https://www.deepseek.com/) | ✅ |  |
+| [Moonshot](https://www.moonshot.cn/) | ✅ |  |
+| [Anthropic](https://www.anthropic.com/) | ✅ |  |
+| [xAI](https://x.ai/) | ✅ |  |
+| [Zhipu AI](https://open.bigmodel.cn/) | ✅ |  |
+| [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | ✅ | Plateforme de ressources LLM et GPU |
+| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | ✅ | Plateforme de ressources LLM et GPU |
+| [接口 AI](https://jiekou.ai/) | ✅ | Plateforme d'agrégation LLM |
+| [ShengSuanYun](https://www.shengsuanyun.com/?from=CH_KYIPP758) | ✅ | Plateforme de ressources LLM et GPU |
+| [302.AI](https://share.302.ai/SuTG99) | ✅ | Passerelle LLM (MaaS) |
+| [Google Gemini](https://aistudio.google.com/prompts/new_chat) | ✅ | |
+| [Dify](https://dify.ai) | ✅ | Plateforme LLMOps |
+| [Ollama](https://ollama.com/) | ✅ | Plateforme d'exécution LLM locale |
+| [LMStudio](https://lmstudio.ai/) | ✅ | Plateforme d'exécution LLM locale |
+| [GiteeAI](https://ai.gitee.com/) | ✅ | Passerelle d'interface LLM (MaaS) |
+| [SiliconFlow](https://siliconflow.cn/) | ✅ | Passerelle LLM (MaaS) |
+| [Aliyun Bailian](https://bailian.console.aliyun.com/) | ✅ | Passerelle LLM (MaaS), plateforme LLMOps |
+| [Volc Engine Ark](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | ✅ | Passerelle LLM (MaaS), plateforme LLMOps |
+| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | ✅ | Passerelle LLM (MaaS) |
+| [MCP](https://modelcontextprotocol.io/) | ✅ | Prend en charge l'accès aux outils via le protocole MCP |
 
-| Fournisseur | Type | Statut |
-|----------|------|--------|
-| [OpenAI](https://platform.openai.com/) | LLM | ✅ |
-| [Anthropic](https://www.anthropic.com/) | LLM | ✅ |
-| [DeepSeek](https://www.deepseek.com/) | LLM | ✅ |
-| [Google Gemini](https://aistudio.google.com/prompts/new_chat) | LLM | ✅ |
-| [xAI](https://x.ai/) | LLM | ✅ |
-| [Moonshot](https://www.moonshot.cn/) | LLM | ✅ |
-| [Zhipu AI](https://open.bigmodel.cn/) | LLM | ✅ |
-| [Ollama](https://ollama.com/) | LLM Local | ✅ |
-| [LM Studio](https://lmstudio.ai/) | LLM Local | ✅ |
-| [Dify](https://dify.ai) | LLMOps | ✅ |
-| [MCP](https://modelcontextprotocol.io/) | Protocole | ✅ |
-| [SiliconFlow](https://siliconflow.cn/) | Passerelle | ✅ |
-| [Aliyun Bailian](https://bailian.console.aliyun.com/) | Passerelle | ✅ |
-| [Volc Engine Ark](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | Passerelle | ✅ |
-| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | Passerelle | ✅ |
-| [GiteeAI](https://ai.gitee.com/) | Passerelle | ✅ |
-| [接口 AI](https://jiekou.ai/) | Passerelle | ✅ |
-| [302.AI](https://share.302.ai/SuTG99) | Passerelle | ✅ |
-| [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | Plateforme GPU | ✅ |
-| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | Plateforme GPU | ✅ |
-| [ShengSuanYun](https://www.shengsuanyun.com/?from=CH_KYIPP758) | Plateforme GPU | ✅ |
+## 🤝 Contribution de la Communauté
 
-[→ Voir toutes les intégrations](https://docs.langbot.app/en/insight/features.html)
-
----
-
-## Pourquoi LangBot ?
-
-| Cas d'Usage | Comment LangBot Aide |
-|----------|-------------------|
-| **Support Client** | Déployez des agents IA sur Slack/Discord/Telegram qui répondent aux questions en utilisant votre base de connaissances |
-| **Outils Internes** | Connectez les workflows n8n/Dify à WeCom/DingTalk pour automatiser vos processus métier |
-| **Gestion de Communauté** | Modérez les groupes QQ/Discord avec un filtrage de contenu et des interactions alimentés par l'IA |
-| **Présence Multi-plateforme** | Un seul bot, toutes les plateformes. Gérez tout depuis un tableau de bord unique |
-
----
-
-## Démo en Ligne
-
-**Essayez maintenant :** https://demo.langbot.dev/
-- Email : `demo@langbot.app`
-- Mot de passe : `langbot123456`
-
-*Note : Environnement de démonstration public. Ne saisissez pas d'informations sensibles.*
-
----
-
-## Communauté
-
-[![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&label=Discord)](https://discord.gg/wdNEHETs87)
-
-- [Communauté Discord](https://discord.gg/wdNEHETs87)
-
----
-
-## Historique des Stars
-
-[![Star History Chart](https://api.star-history.com/svg?repos=langbot-app/LangBot&type=Date)](https://star-history.com/#langbot-app/LangBot&Date)
-
----
-
-## Contributeurs
-
-Merci à tous les [contributeurs](https://github.com/langbot-app/LangBot/graphs/contributors) qui ont aidé à améliorer LangBot :
+Merci aux [contributeurs de code](https://github.com/langbot-app/LangBot/graphs/contributors) suivants et aux autres membres de la communauté pour leurs contributions à LangBot :
 
 <a href="https://github.com/langbot-app/LangBot/graphs/contributors">
   <img src="https://contrib.rocks/image?repo=langbot-app/LangBot" />

README_JP.md

@@ -1,68 +1,43 @@
 <p align="center">
 <a href="https://langbot.app">
-<img width="130" src="res/logo-blue.png" alt="LangBot"/>
+<img src="https://docs.langbot.app/social_en.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>AIエージェント搭載IMボットを構築するための本番グレードプラットフォーム。</h3>
-<h4>Slack、Discord、Telegram、WeChat などに AI ボットを素早く構築、デバッグ、デプロイ。</h4>
-
-[English](README.md) / [简体中文](README_CN.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)
+[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)
 [![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/langbot-app/LangBot)
 [![GitHub release (latest by date)](https://img.shields.io/github/v/release/langbot-app/LangBot)](https://github.com/langbot-app/LangBot/releases/latest)
 <img src="https://img.shields.io/badge/python-3.10 ~ 3.13 -blue.svg" alt="python">
-[![GitHub stars](https://img.shields.io/github/stars/langbot-app/LangBot?style=social)](https://github.com/langbot-app/LangBot/stargazers)
 
 <a href="https://langbot.app">ホーム</a> ｜
-<a href="https://docs.langbot.app/ja/insight/features.html">機能</a> ｜
-<a href="https://docs.langbot.app/ja/insight/guide.html">ドキュメント</a> ｜
-<a href="https://docs.langbot.app/ja/tags/readme.html">API</a> ｜
-<a href="https://space.langbot.app">プラグインマーケット</a> ｜
-<a href="https://langbot.featurebase.app/roadmap">ロードマップ</a>
+<a href="https://docs.langbot.app/en/insight/guide.html">デプロイ</a> ｜
+<a href="https://docs.langbot.app/en/plugin/plugin-intro.html">プラグイン</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">プラグインの提出</a>
 
 </div>
 
 </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。
 
-## LangBot とは？
+## 📦 始め方
 
-LangBot は、AI搭載のインスタントメッセージングボットを構築するための**オープンソースの本番グレードプラットフォーム**です。大規模言語モデル（LLM）をあらゆるチャットプラットフォームに接続し、会話、タスク実行、既存のワークフローとの統合が可能なインテリジェントエージェントを作成できます。
+#### クイックスタート
 
-### 主な機能
-
-- **AI対話とエージェント** — マルチターン対話、ツール呼び出し、マルチモーダル対応、ストリーミング出力。RAG（ナレッジベース）を内蔵し、[Dify](https://dify.ai)、[Coze](https://coze.com)、[n8n](https://n8n.io)、[Langflow](https://langflow.org) と深く統合。
-- **ユニバーサルIMプラットフォーム対応** — 単一のコードベースで Discord、Telegram、Slack、LINE、QQ、WeChat、WeCom、Lark、DingTalk、KOOK に対応。
-- **本番環境対応** — アクセス制御、レート制限、センシティブワードフィルタリング、包括的な監視、例外処理を搭載。エンタープライズの信頼に応える品質。
-- **プラグインエコシステム** — 数百のプラグイン、イベント駆動アーキテクチャ、コンポーネント拡張、[MCPプロトコル](https://modelcontextprotocol.io/)対応。
-- **Web管理パネル** — 直感的なブラウザインターフェースからボットの設定、管理、監視が可能。YAML編集は不要。
-- **マルチパイプラインアーキテクチャ** — 異なるシナリオに異なるボットを配置し、包括的な監視と例外処理を実現。
-
-[→ すべての機能について詳しく見る](https://docs.langbot.app/ja/insight/features.html)
-
----
-
-## クイックスタート
-
-### ☁️ LangBot Cloud（推奨）
-
-**[LangBot Cloud](https://space.langbot.app/cloud)** — デプロイ不要、すぐに使えます。
-
-### ワンライン起動
+`uvx` を使用した迅速なデプロイ（[uv](https://docs.astral.sh/uv/getting-started/installation/) が必要です）：
 
 ```bash
 uvx langbot
 ```
 
-> [uv](https://docs.astral.sh/uv/getting-started/installation/) が必要です。http://localhost:5300 にアクセスして完了。
+http://localhost:5300 にアクセスして使用を開始します。
 
-### Docker Compose
+#### Docker Compose デプロイ
 
 ```bash
 git clone https://github.com/langbot-app/LangBot
@@ -70,101 +45,98 @@ cd LangBot/docker
 docker compose up -d
 ```
 
-### ワンクリッククラウドデプロイ
+http://localhost:5300 にアクセスして使用を開始します。
+
+詳細なドキュメントは[Dockerデプロイ](https://docs.langbot.app/en/deploy/langbot/docker.html)を参照してください。
+
+#### Panelでのワンクリックデプロイ
+
+LangBotはBTPanelにリストされています。BTPanelをインストールしている場合は、[ドキュメント](https://docs.langbot.app/en/deploy/langbot/one-click/bt.html)を使用して使用できます。
+
+#### Zeaburクラウドデプロイ
+
+コミュニティが提供するZeaburテンプレート。
 
 [![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/en-US/templates/ZKTBDH)
+
+#### Railwayクラウドデプロイ
+
 [![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF)
 
-**その他:** [Docker](https://docs.langbot.app/en/deploy/langbot/docker.html) · [手動デプロイ](https://docs.langbot.app/en/deploy/langbot/manual.html) · [BTPanel](https://docs.langbot.app/en/deploy/langbot/one-click/bt.html) · [Kubernetes](./docker/README_K8S.md)
+#### その他のデプロイ方法
 
----
+リリースバージョンを直接使用して実行します。[手動デプロイ](https://docs.langbot.app/en/deploy/langbot/manual.html)のドキュメントを参照してください。
 
-## 対応プラットフォーム
+#### Kubernetes デプロイ
+
+[Kubernetes デプロイ](./docker/README_K8S.md) ドキュメントを参照してください。
+
+## 😎 最新情報を入手
+
+リポジトリの右上にある Star と Watch ボタンをクリックして、最新の更新を取得してください。
+
+![star gif](https://docs.langbot.app/star.gif)
+
+## ✨ 機能
+
+- 💬 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 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。
+- 🧩 プラグイン拡張、活発なコミュニティ: 高い安定性、高いセキュリティの生産レベルのプラグインシステム；イベント駆動、コンポーネント拡張などのプラグインメカニズムをサポート。適配 Anthropic [MCP プロトコル](https://modelcontextprotocol.io/)；豊富なエコシステム、現在数百のプラグインが存在。
+- 😻 Web UI: ブラウザを通じてLangBotインスタンスを管理することをサポート。
+
+詳細な仕様については、[ドキュメント](https://docs.langbot.app/en/insight/features.html)を参照してください。
+
+または、デモ環境にアクセスしてください: https://demo.langbot.dev/
+  - ログイン情報: メール: `demo@langbot.app` パスワード: `langbot123456`
+  - 注意: WebUI のデモンストレーションのみの場合、公開環境では機密情報を入力しないでください。
+
+### メッセージプラットフォーム
 
 | プラットフォーム | ステータス | 備考 |
-|----------|--------|-------|
+| --- | --- | --- |
 | Discord | ✅ |  |
 | Telegram | ✅ |  |
 | Slack | ✅ |  |
 | LINE | ✅ |  |
-| QQ | ✅ | 個人 & 公式API |
-| WeCom | ✅ | 企業WeChat、外部CS、AIボット |
-| WeChat | ✅ | 個人 & 公式アカウント |
+| 個人QQ | ✅ |  |
+| QQ公式API | ✅ |  |
+| WeCom | ✅ |  |
+| WeComCS | ✅ |  |
+| WeCom AI Bot | ✅ |  |
+| 個人WeChat | ✅ | |
 | Lark | ✅ |  |
 | DingTalk | ✅ |  |
-| KOOK | ✅ |  |
-| Satori | ✅ |  |
 
----
+### LLMs
 
-## 対応LLMと統合
+| LLM | ステータス | 備考 |
+| --- | --- | --- |
+| [OpenAI](https://platform.openai.com/) | ✅ | 任意のOpenAIインターフェース形式モデルに対応 |
+| [DeepSeek](https://www.deepseek.com/) | ✅ |  |
+| [Moonshot](https://www.moonshot.cn/) | ✅ |  |
+| [Anthropic](https://www.anthropic.com/) | ✅ |  |
+| [xAI](https://x.ai/) | ✅ |  |
+| [Zhipu AI](https://open.bigmodel.cn/) | ✅ |  |
+| [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | ✅ | 大模型とGPUリソースプラットフォーム |
+| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | ✅ | 大模型とGPUリソースプラットフォーム |
+| [接口 AI](https://jiekou.ai/) | ✅ | LLMゲートウェイ(MaaS) |
+| [ShengSuanYun](https://www.shengsuanyun.com/?from=CH_KYIPP758) | ✅ | LLMとGPUリソースプラットフォーム |
+| [302.AI](https://share.302.ai/SuTG99) | ✅ | LLMゲートウェイ(MaaS) |
+| [Google Gemini](https://aistudio.google.com/prompts/new_chat) | ✅ | |
+| [Dify](https://dify.ai) | ✅ | LLMOpsプラットフォーム |
+| [Ollama](https://ollama.com/) | ✅ | ローカルLLM実行プラットフォーム |
+| [LMStudio](https://lmstudio.ai/) | ✅ | ローカルLLM実行プラットフォーム |
+| [GiteeAI](https://ai.gitee.com/) | ✅ | LLMインターフェースゲートウェイ(MaaS) |
+| [SiliconFlow](https://siliconflow.cn/) | ✅ | LLMゲートウェイ(MaaS) |
+| [Aliyun Bailian](https://bailian.console.aliyun.com/) | ✅ | LLMゲートウェイ(MaaS), LLMOpsプラットフォーム |
+| [Volc Engine Ark](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | ✅ | LLMゲートウェイ(MaaS), LLMOpsプラットフォーム |
+| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | ✅ | LLMゲートウェイ(MaaS) |
+| [MCP](https://modelcontextprotocol.io/) | ✅ | MCPプロトコルをサポート |
 
-| プロバイダー | タイプ | ステータス |
-|----------|------|--------|
-| [OpenAI](https://platform.openai.com/) | LLM | ✅ |
-| [Anthropic](https://www.anthropic.com/) | LLM | ✅ |
-| [DeepSeek](https://www.deepseek.com/) | LLM | ✅ |
-| [Google Gemini](https://aistudio.google.com/prompts/new_chat) | LLM | ✅ |
-| [xAI](https://x.ai/) | LLM | ✅ |
-| [Moonshot](https://www.moonshot.cn/) | LLM | ✅ |
-| [Zhipu AI](https://open.bigmodel.cn/) | LLM | ✅ |
-| [Ollama](https://ollama.com/) | ローカルLLM | ✅ |
-| [LM Studio](https://lmstudio.ai/) | ローカルLLM | ✅ |
-| [Dify](https://dify.ai) | LLMOps | ✅ |
-| [MCP](https://modelcontextprotocol.io/) | プロトコル | ✅ |
-| [SiliconFlow](https://siliconflow.cn/) | ゲートウェイ | ✅ |
-| [Aliyun Bailian](https://bailian.console.aliyun.com/) | ゲートウェイ | ✅ |
-| [Volc Engine Ark](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | ゲートウェイ | ✅ |
-| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | ゲートウェイ | ✅ |
-| [GiteeAI](https://ai.gitee.com/) | ゲートウェイ | ✅ |
-| [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | GPUプラットフォーム | ✅ |
-| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | GPUプラットフォーム | ✅ |
-| [ShengSuanYun](https://www.shengsuanyun.com/?from=CH_KYIPP758) | GPUプラットフォーム | ✅ |
-| [接口 AI](https://jiekou.ai/) | ゲートウェイ | ✅ |
-| [302.AI](https://share.302.ai/SuTG99) | ゲートウェイ | ✅ |
+## 🤝 コミュニティ貢献
 
-[→ すべての統合を表示](https://docs.langbot.app/en/insight/features.html)
-
----
-
-## なぜ LangBot？
-
-| ユースケース | LangBot の活用方法 |
-|----------|-------------------|
-| **カスタマーサポート** | ナレッジベースを活用して質問に回答するAIエージェントをSlack/Discord/Telegramにデプロイ |
-| **社内ツール** | n8n/Difyのワークフローを WeCom/DingTalk に接続し、業務プロセスを自動化 |
-| **コミュニティ管理** | AI搭載のコンテンツフィルタリングとインタラクションでQQ/Discordグループをモデレーション |
-| **マルチプラットフォーム展開** | 1つのボットで全プラットフォームに対応。単一のダッシュボードから管理 |
-
----
-
-## ライブデモ
-
-**今すぐ試す:** https://demo.langbot.dev/
-- メール: `demo@langbot.app`
-- パスワード: `langbot123456`
-
-*注意: 公開デモ環境です。機密情報を入力しないでください。*
-
----
-
-## コミュニティ
-
-[![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&label=Discord)](https://discord.gg/wdNEHETs87)
-
-- [Discord コミュニティ](https://discord.gg/wdNEHETs87)
-
----
-
-## Star 推移
-
-[![Star History Chart](https://api.star-history.com/svg?repos=langbot-app/LangBot&type=Date)](https://star-history.com/#langbot-app/LangBot&Date)
-
----
-
-## コントリビューター
-
-LangBot をより良くするために貢献してくださったすべての[コントリビューター](https://github.com/langbot-app/LangBot/graphs/contributors)に感謝します:
+LangBot への貢献に対して、以下の [コード貢献者](https://github.com/langbot-app/LangBot/graphs/contributors) とコミュニティの他のメンバーに感謝します。
 
 <a href="https://github.com/langbot-app/LangBot/graphs/contributors">
   <img src="https://contrib.rocks/image?repo=langbot-app/LangBot" />

README_KO.md

@@ -1,68 +1,43 @@
 <p align="center">
 <a href="https://langbot.app">
-<img width="130" src="res/logo-blue.png" alt="LangBot"/>
+<img src="https://docs.langbot.app/social_en.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>AI 에이전트 IM 봇 구축을 위한 프로덕션 등급 플랫폼.</h3>
-<h4>Slack, Discord, Telegram, WeChat 등에 AI 봇을 빠르게 구축, 디버그 및 배포.</h4>
-
-[English](README.md) / [简体中文](README_CN.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)
+[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)
 [![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/langbot-app/LangBot)
 [![GitHub release (latest by date)](https://img.shields.io/github/v/release/langbot-app/LangBot)](https://github.com/langbot-app/LangBot/releases/latest)
 <img src="https://img.shields.io/badge/python-3.10 ~ 3.13 -blue.svg" alt="python">
-[![GitHub stars](https://img.shields.io/github/stars/langbot-app/LangBot?style=social)](https://github.com/langbot-app/LangBot/stargazers)
 
 <a href="https://langbot.app">홈</a> ｜
-<a href="https://docs.langbot.app/en/insight/features.html">기능</a> ｜
-<a href="https://docs.langbot.app/en/insight/guide.html">문서</a> ｜
-<a href="https://docs.langbot.app/en/tags/readme.html">API</a> ｜
-<a href="https://space.langbot.app">플러그인 마켓</a> ｜
-<a href="https://langbot.featurebase.app/roadmap">로드맵</a>
+<a href="https://docs.langbot.app/en/insight/guide.html">배포</a> ｜
+<a href="https://docs.langbot.app/en/plugin/plugin-intro.html">플러그인</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">플러그인 제출</a>
 
 </div>
 
 </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.
 
-## LangBot이란?
+## 📦 시작하기
 
-LangBot은 AI 기반 인스턴트 메시징 봇을 구축하기 위한 **오픈소스 프로덕션 등급 플랫폼**입니다. 대규모 언어 모델(LLM)을 모든 채팅 플랫폼에 연결하여 대화, 작업 실행, 기존 워크플로우와의 통합이 가능한 지능형 에이전트를 만들 수 있습니다.
+#### 빠른 시작
 
-### 핵심 기능
-
-- **AI 대화 및 에이전트** — 멀티턴 대화, 도구 호출, 멀티모달 지원, 스트리밍 출력. 내장 RAG(지식 베이스)와 [Dify](https://dify.ai), [Coze](https://coze.com), [n8n](https://n8n.io), [Langflow](https://langflow.org) 심층 통합.
-- **유니버설 IM 플랫폼 지원** — 단일 코드베이스로 Discord, Telegram, Slack, LINE, QQ, WeChat, WeCom, Lark, DingTalk, KOOK 지원.
-- **프로덕션 레디** — 접근 제어, 속도 제한, 민감어 필터링, 종합 모니터링 및 예외 처리. 기업 환경에서 검증됨.
-- **플러그인 생태계** — 수백 개의 플러그인, 이벤트 기반 아키텍처, 컴포넌트 확장, [MCP 프로토콜](https://modelcontextprotocol.io/) 지원.
-- **웹 관리 패널** — 직관적인 브라우저 인터페이스로 봇을 구성, 관리 및 모니터링. YAML 편집 불필요.
-- **멀티 파이프라인 아키텍처** — 다양한 시나리오에 맞는 다양한 봇 구성, 종합 모니터링 및 예외 처리.
-
-[→ 모든 기능 자세히 보기](https://docs.langbot.app/en/insight/features.html)
-
----
-
-## 빠른 시작
-
-### ☁️ LangBot Cloud (추천)
-
-**[LangBot Cloud](https://space.langbot.app/cloud)** — 배포 없이 바로 사용.
-
-### 원라인 실행
+`uvx`를 사용하여 한 명령으로 시작하세요 ([uv](https://docs.astral.sh/uv/getting-started/installation/) 설치 필요):
 
 ```bash
 uvx langbot
 ```
 
-> [uv](https://docs.astral.sh/uv/getting-started/installation/) 설치 필요. http://localhost:5300 방문 — 완료.
+http://localhost:5300을 방문하여 사용을 시작하세요.
 
-### Docker Compose
+#### Docker Compose 배포
 
 ```bash
 git clone https://github.com/langbot-app/LangBot
@@ -70,101 +45,98 @@ cd LangBot/docker
 docker compose up -d
 ```
 
-### 원클릭 클라우드 배포
+http://localhost:5300을 방문하여 사용을 시작하세요.
+
+자세한 문서는 [Docker 배포](https://docs.langbot.app/en/deploy/langbot/docker.html)를 참조하세요.
+
+#### BTPanel 원클릭 배포
+
+LangBot은 BTPanel에 등록되어 있습니다. BTPanel을 설치한 경우 [문서](https://docs.langbot.app/en/deploy/langbot/one-click/bt.html)를 사용하여 사용할 수 있습니다.
+
+#### Zeabur 클라우드 배포
+
+커뮤니티에서 제공하는 Zeabur 템플릿입니다.
 
 [![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/en-US/templates/ZKTBDH)
+
+#### Railway 클라우드 배포
+
 [![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF)
 
-**더 많은 옵션:** [Docker](https://docs.langbot.app/en/deploy/langbot/docker.html) · [수동 배포](https://docs.langbot.app/en/deploy/langbot/manual.html) · [BTPanel](https://docs.langbot.app/en/deploy/langbot/one-click/bt.html) · [Kubernetes](./docker/README_K8S.md)
+#### 기타 배포 방법
 
----
+릴리스 버전을 직접 사용하여 실행하려면 [수동 배포](https://docs.langbot.app/en/deploy/langbot/manual.html) 문서를 참조하세요.
 
-## 지원 플랫폼
+#### Kubernetes 배포
+
+[Kubernetes 배포](./docker/README_K8S.md) 문서를 참조하세요.
+
+## 😎 최신 정보 받기
+
+리포지토리 오른쪽 상단의 Star 및 Watch 버튼을 클릭하여 최신 업데이트를 받으세요.
+
+![star gif](https://docs.langbot.app/star.gif)
+
+## ✨ 기능
+
+- 💬 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 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.
+- 🧩 플러그인 확장, 활발한 커뮤니티: 고안정성, 고보안 생산 수준의 플러그인 시스템; 이벤트 기반, 컴포넌트 확장 등의 플러그인 메커니즘을 지원; Anthropic [MCP 프로토콜](https://modelcontextprotocol.io/) 통합; 현재 수백 개의 플러그인이 있습니다.
+- 😻 웹 UI: 브라우저를 통해 LangBot 인스턴스 관리를 지원합니다. 구성 파일을 수동으로 작성할 필요가 없습니다.
+
+더 자세한 사양은 [문서](https://docs.langbot.app/en/insight/features.html)를 참조하세요.
+
+또는 데모 환경을 방문하세요: https://demo.langbot.dev/
+  - 로그인 정보: 이메일: `demo@langbot.app` 비밀번호: `langbot123456`
+  - 참고: WebUI 데모 전용이므로 공개 환경에서는 민감한 정보를 입력하지 마세요.
+
+### 메시징 플랫폼
 
 | 플랫폼 | 상태 | 비고 |
-|--------|------|------|
+| --- | --- | --- |
 | Discord | ✅ |  |
 | Telegram | ✅ |  |
 | Slack | ✅ |  |
 | LINE | ✅ |  |
-| QQ | ✅ | 개인 및 공식 API |
-| WeCom | ✅ | 기업 WeChat, 외부 CS, AI Bot |
-| WeChat | ✅ | 개인 및 공식 계정 |
+| 개인 QQ | ✅ |  |
+| QQ 공식 API | ✅ |  |
+| WeCom | ✅ |  |
+| WeComCS | ✅ |  |
+| WeCom AI Bot | ✅ |  |
+| 개인 WeChat | ✅ |  |
 | Lark | ✅ |  |
 | DingTalk | ✅ |  |
-| KOOK | ✅ |  |
-| Satori | ✅ |  |
 
----
+### LLMs
 
-## 지원 LLM 및 통합
+| LLM | 상태 | 비고 |
+| --- | --- | --- |
+| [OpenAI](https://platform.openai.com/) | ✅ | 모든 OpenAI 인터페이스 형식 모델에 사용 가능 |
+| [DeepSeek](https://www.deepseek.com/) | ✅ |  |
+| [Moonshot](https://www.moonshot.cn/) | ✅ |  |
+| [Anthropic](https://www.anthropic.com/) | ✅ |  |
+| [xAI](https://x.ai/) | ✅ |  |
+| [Zhipu AI](https://open.bigmodel.cn/) | ✅ |  |
+| [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | ✅ | LLM 및 GPU 리소스 플랫폼 |
+| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | ✅ | LLM 및 GPU 리소스 플랫폼 |
+| [接口 AI](https://jiekou.ai/) | ✅ | LLM 집계 플랫폼 |
+| [ShengSuanYun](https://www.shengsuanyun.com/?from=CH_KYIPP758) | ✅ | LLM 및 GPU 리소스 플랫폼 |
+| [302.AI](https://share.302.ai/SuTG99) | ✅ | LLM 게이트웨이(MaaS) |
+| [Google Gemini](https://aistudio.google.com/prompts/new_chat) | ✅ | |
+| [Dify](https://dify.ai) | ✅ | LLMOps 플랫폼 |
+| [Ollama](https://ollama.com/) | ✅ | 로컬 LLM 실행 플랫폼 |
+| [LMStudio](https://lmstudio.ai/) | ✅ | 로컬 LLM 실행 플랫폼 |
+| [GiteeAI](https://ai.gitee.com/) | ✅ | LLM 인터페이스 게이트웨이(MaaS) |
+| [SiliconFlow](https://siliconflow.cn/) | ✅ | LLM 게이트웨이(MaaS) |
+| [Aliyun Bailian](https://bailian.console.aliyun.com/) | ✅ | LLM 게이트웨이(MaaS), LLMOps 플랫폼 |
+| [Volc Engine Ark](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | ✅ | LLM 게이트웨이(MaaS), LLMOps 플랫폼 |
+| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | ✅ | LLM 게이트웨이(MaaS) |
+| [MCP](https://modelcontextprotocol.io/) | ✅ | MCP 프로토콜을 통한 도구 액세스 지원 |
 
-| 제공자 | 유형 | 상태 |
-|--------|------|------|
-| [OpenAI](https://platform.openai.com/) | LLM | ✅ |
-| [Anthropic](https://www.anthropic.com/) | LLM | ✅ |
-| [DeepSeek](https://www.deepseek.com/) | LLM | ✅ |
-| [Google Gemini](https://aistudio.google.com/prompts/new_chat) | LLM | ✅ |
-| [xAI](https://x.ai/) | LLM | ✅ |
-| [Moonshot](https://www.moonshot.cn/) | LLM | ✅ |
-| [Zhipu AI](https://open.bigmodel.cn/) | LLM | ✅ |
-| [Ollama](https://ollama.com/) | 로컬 LLM | ✅ |
-| [LM Studio](https://lmstudio.ai/) | 로컬 LLM | ✅ |
-| [Dify](https://dify.ai) | LLMOps | ✅ |
-| [MCP](https://modelcontextprotocol.io/) | 프로토콜 | ✅ |
-| [SiliconFlow](https://siliconflow.cn/) | 게이트웨이 | ✅ |
-| [Aliyun Bailian](https://bailian.console.aliyun.com/) | 게이트웨이 | ✅ |
-| [Volc Engine Ark](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | 게이트웨이 | ✅ |
-| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | 게이트웨이 | ✅ |
-| [GiteeAI](https://ai.gitee.com/) | 게이트웨이 | ✅ |
-| [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | GPU 플랫폼 | ✅ |
-| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | GPU 플랫폼 | ✅ |
-| [ShengSuanYun](https://www.shengsuanyun.com/?from=CH_KYIPP758) | GPU 플랫폼 | ✅ |
-| [接口 AI](https://jiekou.ai/) | 게이트웨이 | ✅ |
-| [302.AI](https://share.302.ai/SuTG99) | 게이트웨이 | ✅ |
+## 🤝 커뮤니티 기여
 
-[→ 모든 통합 보기](https://docs.langbot.app/en/insight/features.html)
-
----
-
-## 왜 LangBot인가?
-
-| 사용 사례 | LangBot 활용 방법 |
-|-----------|-------------------|
-| **고객 지원** | 지식 베이스를 활용하여 질문에 답변하는 AI 에이전트를 Slack/Discord/Telegram에 배포 |
-| **내부 도구** | n8n/Dify 워크플로우를 WeCom/DingTalk에 연결하여 비즈니스 프로세스 자동화 |
-| **커뮤니티 관리** | AI 기반 콘텐츠 필터링 및 상호작용으로 QQ/Discord 그룹 관리 |
-| **멀티 플랫폼** | 하나의 봇으로 모든 플랫폼 지원. 단일 대시보드에서 관리 |
-
----
-
-## 라이브 데모
-
-**지금 체험:** https://demo.langbot.dev/
-- 이메일: `demo@langbot.app`
-- 비밀번호: `langbot123456`
-
-*참고: 공개 데모 환경입니다. 민감한 정보를 입력하지 마세요.*
-
----
-
-## 커뮤니티
-
-[![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&label=Discord)](https://discord.gg/wdNEHETs87)
-
-- [Discord 커뮤니티](https://discord.gg/wdNEHETs87)
-
----
-
-## Star 추이
-
-[![Star History Chart](https://api.star-history.com/svg?repos=langbot-app/LangBot&type=Date)](https://star-history.com/#langbot-app/LangBot&Date)
-
----
-
-## 기여자
-
-LangBot을 더 나은 프로젝트로 만들어 주신 모든 [기여자](https://github.com/langbot-app/LangBot/graphs/contributors)분들께 감사드립니다:
+다음 [코드 기여자](https://github.com/langbot-app/LangBot/graphs/contributors) 및 커뮤니티의 다른 구성원들의 LangBot 기여에 감사드립니다:
 
 <a href="https://github.com/langbot-app/LangBot/graphs/contributors">
   <img src="https://contrib.rocks/image?repo=langbot-app/LangBot" />

README_RU.md

@@ -1,68 +1,43 @@
 <p align="center">
 <a href="https://langbot.app">
-<img width="130" src="res/logo-blue.png" alt="LangBot"/>
+<img src="https://docs.langbot.app/social_en.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>Платформа производственного уровня для создания агентных IM-ботов.</h3>
-<h4>Быстро создавайте, отлаживайте и развертывайте ИИ-ботов в Slack, Discord, Telegram, WeChat и других платформах.</h4>
-
-[English](README.md) / [简体中文](README_CN.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)
+[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)
 [![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/langbot-app/LangBot)
 [![GitHub release (latest by date)](https://img.shields.io/github/v/release/langbot-app/LangBot)](https://github.com/langbot-app/LangBot/releases/latest)
 <img src="https://img.shields.io/badge/python-3.10 ~ 3.13 -blue.svg" alt="python">
-[![GitHub stars](https://img.shields.io/github/stars/langbot-app/LangBot?style=social)](https://github.com/langbot-app/LangBot/stargazers)
 
 <a href="https://langbot.app">Главная</a> ｜
-<a href="https://docs.langbot.app/en/insight/features.html">Возможности</a> ｜
-<a href="https://docs.langbot.app/en/insight/guide.html">Документация</a> ｜
-<a href="https://docs.langbot.app/en/tags/readme.html">API</a> ｜
-<a href="https://space.langbot.app">Магазин плагинов</a> ｜
-<a href="https://langbot.featurebase.app/roadmap">Дорожная карта</a>
+<a href="https://docs.langbot.app/en/insight/guide.html">Развертывание</a> ｜
+<a href="https://docs.langbot.app/en/plugin/plugin-intro.html">Плагин</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">Отправить плагин</a>
 
 </div>
 
 </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.
 
-## Что такое LangBot?
+## 📦 Начало работы
 
-LangBot — это **платформа с открытым исходным кодом производственного уровня** для создания ИИ-ботов в мессенджерах. Она связывает большие языковые модели (LLM) с любой чат-платформой, позволяя создавать интеллектуальных агентов, которые могут вести диалоги, выполнять задачи и интегрироваться с вашими существующими рабочими процессами.
+#### Быстрый старт
 
-### Ключевые возможности
-
-- **ИИ-диалоги и агенты** — Многораундовые диалоги, вызов инструментов, мультимодальная поддержка, потоковый вывод. Встроенная реализация RAG (база знаний) с глубокой интеграцией в [Dify](https://dify.ai), [Coze](https://coze.com), [n8n](https://n8n.io), [Langflow](https://langflow.org).
-- **Универсальная поддержка IM-платформ** — Единая кодовая база для Discord, Telegram, Slack, LINE, QQ, WeChat, WeCom, Lark, DingTalk, KOOK.
-- **Готовность к продакшену** — Контроль доступа, ограничение скорости, фильтрация чувствительных слов, комплексный мониторинг и обработка исключений. Проверено в корпоративной среде.
-- **Экосистема плагинов** — Сотни плагинов, событийно-ориентированная архитектура, расширения компонентов и поддержка [протокола MCP](https://modelcontextprotocol.io/).
-- **Веб-панель управления** — Настраивайте, управляйте и мониторьте ваших ботов через интуитивный браузерный интерфейс. Ручное редактирование YAML не требуется.
-- **Мультиконвейерная архитектура** — Разные боты для разных сценариев с комплексным мониторингом и обработкой исключений.
-
-[→ Подробнее обо всех возможностях](https://docs.langbot.app/en/insight/features.html)
-
----
-
-## Быстрый старт
-
-### ☁️ LangBot Cloud (Рекомендуется)
-
-**[LangBot Cloud](https://space.langbot.app/cloud)** — Без развёртывания, готово к использованию.
-
-### Запуск одной командой
+Используйте `uvx` для запуска одной командой (требуется установка [uv](https://docs.astral.sh/uv/getting-started/installation/)):
 
 ```bash
 uvx langbot
 ```
 
-> Требуется [uv](https://docs.astral.sh/uv/getting-started/installation/). Откройте http://localhost:5300 — готово.
+Посетите http://localhost:5300, чтобы начать использование.
 
-### Docker Compose
+#### Развертывание с Docker Compose
 
 ```bash
 git clone https://github.com/langbot-app/LangBot
@@ -70,101 +45,98 @@ cd LangBot/docker
 docker compose up -d
 ```
 
-### Облачное развертывание одним кликом
+Посетите http://localhost:5300, чтобы начать использование.
+
+Подробная документация [Развертывание Docker](https://docs.langbot.app/en/deploy/langbot/docker.html).
+
+#### Развертывание одним кликом на BTPanel
+
+LangBot добавлен в BTPanel. Если у вас установлен BTPanel, вы можете использовать [документацию](https://docs.langbot.app/en/deploy/langbot/one-click/bt.html) для его использования.
+
+#### Облачное развертывание Zeabur
+
+Шаблон Zeabur, предоставленный сообществом.
 
 [![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/en-US/templates/ZKTBDH)
+
+#### Облачное развертывание Railway
+
 [![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF)
 
-**Другие варианты:** [Docker](https://docs.langbot.app/en/deploy/langbot/docker.html) · [Ручная установка](https://docs.langbot.app/en/deploy/langbot/manual.html) · [BTPanel](https://docs.langbot.app/en/deploy/langbot/one-click/bt.html) · [Kubernetes](./docker/README_K8S.md)
+#### Другие методы развертывания
 
----
+Используйте выпущенную версию напрямую для запуска, см. документацию [Ручное развертывание](https://docs.langbot.app/en/deploy/langbot/manual.html).
 
-## Поддерживаемые платформы
+#### Развертывание Kubernetes
+
+См. документацию [Развертывание Kubernetes](./docker/README_K8S.md).
+
+## 😎 Оставайтесь в курсе
+
+Нажмите кнопки Star и Watch в правом верхнем углу репозитория, чтобы получать последние обновления.
+
+![star gif](https://docs.langbot.app/star.gif)
+
+## ✨ Функции
+
+- 💬 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 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.
+- 🧩 Расширение плагинов, активное сообщество: Высокая стабильность, высокая безопасность уровня производства; Поддержка механизмов плагинов, управляемых событиями, расширения компонентов и т.д.; Интеграция протокола [MCP](https://modelcontextprotocol.io/) от Anthropic; В настоящее время сотни плагинов.
+- 😻 Веб-интерфейс: Поддержка управления экземплярами LangBot через браузер. Нет необходимости вручную писать конфигурационные файлы.
+
+Для более подробных спецификаций обратитесь к [документации](https://docs.langbot.app/en/insight/features.html).
+
+Или посетите демонстрационную среду: https://demo.langbot.dev/
+  - Информация для входа: Email: `demo@langbot.app` Пароль: `langbot123456`
+  - Примечание: Только для демонстрации WebUI, пожалуйста, не вводите конфиденциальную информацию в общедоступной среде.
+
+### Платформы обмена сообщениями
 
 | Платформа | Статус | Примечания |
-|-----------|--------|------------|
+| --- | --- | --- |
 | Discord | ✅ |  |
 | Telegram | ✅ |  |
 | Slack | ✅ |  |
 | LINE | ✅ |  |
-| QQ | ✅ | Личный и официальный API |
-| WeCom | ✅ | Корпоративный WeChat, внешний CS, AI-бот |
-| WeChat | ✅ | Личный и официальный аккаунт |
+| Личный QQ | ✅ |  |
+| Официальный API QQ | ✅ |  |
+| WeCom | ✅ |  |
+| WeComCS | ✅ |  |
+| WeCom AI Bot | ✅ |  |
+| Личный WeChat | ✅ |  |
 | Lark | ✅ |  |
 | DingTalk | ✅ |  |
-| KOOK | ✅ |  |
-| Satori | ✅ |  |
 
----
+### LLMs
 
-## Поддерживаемые LLM и интеграции
+| LLM | Статус | Примечания |
+| --- | --- | --- |
+| [OpenAI](https://platform.openai.com/) | ✅ | Доступна для любой модели формата интерфейса OpenAI |
+| [DeepSeek](https://www.deepseek.com/) | ✅ |  |
+| [Moonshot](https://www.moonshot.cn/) | ✅ |  |
+| [Anthropic](https://www.anthropic.com/) | ✅ |  |
+| [xAI](https://x.ai/) | ✅ |  |
+| [Zhipu AI](https://open.bigmodel.cn/) | ✅ |  |
+| [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | ✅ | Платформа ресурсов LLM и GPU |
+| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | ✅ | Платформа ресурсов LLM и GPU |
+| [接口 AI](https://jiekou.ai/) | ✅ | Платформа агрегации LLM |
+| [ShengSuanYun](https://www.shengsuanyun.com/?from=CH_KYIPP758) | ✅ | Платформа ресурсов LLM и GPU |
+| [302.AI](https://share.302.ai/SuTG99) | ✅ | Шлюз LLM (MaaS) |
+| [Google Gemini](https://aistudio.google.com/prompts/new_chat) | ✅ | |
+| [Dify](https://dify.ai) | ✅ | Платформа LLMOps |
+| [Ollama](https://ollama.com/) | ✅ | Платформа локального запуска LLM |
+| [LMStudio](https://lmstudio.ai/) | ✅ | Платформа локального запуска LLM |
+| [GiteeAI](https://ai.gitee.com/) | ✅ | Шлюз интерфейса LLM (MaaS) |
+| [SiliconFlow](https://siliconflow.cn/) | ✅ | Шлюз LLM (MaaS) |
+| [Aliyun Bailian](https://bailian.console.aliyun.com/) | ✅ | Шлюз LLM (MaaS), платформа LLMOps |
+| [Volc Engine Ark](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | ✅ | Шлюз LLM (MaaS), платформа LLMOps |
+| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | ✅ | Шлюз LLM (MaaS) |
+| [MCP](https://modelcontextprotocol.io/) | ✅ | Поддержка доступа к инструментам через протокол MCP |
 
-| Провайдер | Тип | Статус |
-|-----------|-----|--------|
-| [OpenAI](https://platform.openai.com/) | LLM | ✅ |
-| [Anthropic](https://www.anthropic.com/) | LLM | ✅ |
-| [DeepSeek](https://www.deepseek.com/) | LLM | ✅ |
-| [Google Gemini](https://aistudio.google.com/prompts/new_chat) | LLM | ✅ |
-| [xAI](https://x.ai/) | LLM | ✅ |
-| [Moonshot](https://www.moonshot.cn/) | LLM | ✅ |
-| [Zhipu AI](https://open.bigmodel.cn/) | LLM | ✅ |
-| [Ollama](https://ollama.com/) | Локальный LLM | ✅ |
-| [LM Studio](https://lmstudio.ai/) | Локальный LLM | ✅ |
-| [Dify](https://dify.ai) | LLMOps | ✅ |
-| [MCP](https://modelcontextprotocol.io/) | Протокол | ✅ |
-| [SiliconFlow](https://siliconflow.cn/) | Шлюз | ✅ |
-| [Aliyun Bailian](https://bailian.console.aliyun.com/) | Шлюз | ✅ |
-| [Volc Engine Ark](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | Шлюз | ✅ |
-| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | Шлюз | ✅ |
-| [GiteeAI](https://ai.gitee.com/) | Шлюз | ✅ |
-| [302.AI](https://share.302.ai/SuTG99) | Шлюз | ✅ |
-| [接口 AI](https://jiekou.ai/) | Шлюз | ✅ |
-| [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | Платформа GPU | ✅ |
-| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | Платформа GPU | ✅ |
-| [ShengSuanYun](https://www.shengsuanyun.com/?from=CH_KYIPP758) | Платформа GPU | ✅ |
+## 🤝 Вклад сообщества
 
-[→ Смотреть все интеграции](https://docs.langbot.app/en/insight/features.html)
-
----
-
-## Почему LangBot?
-
-| Сценарий использования | Как помогает LangBot |
-|------------------------|----------------------|
-| **Поддержка клиентов** | Разверните ИИ-агентов в Slack/Discord/Telegram, которые отвечают на вопросы, используя вашу базу знаний |
-| **Внутренние инструменты** | Подключите рабочие процессы n8n/Dify к WeCom/DingTalk для автоматизации бизнес-процессов |
-| **Управление сообществом** | Модерируйте группы QQ/Discord с помощью ИИ-фильтрации контента и взаимодействия |
-| **Мультиплатформенное присутствие** | Один бот — все платформы. Управляйте из единой панели |
-
----
-
-## Демо
-
-**Попробуйте прямо сейчас:** https://demo.langbot.dev/
-- Email: `demo@langbot.app`
-- Пароль: `langbot123456`
-
-*Примечание: Публичная демо-среда. Не вводите конфиденциальную информацию.*
-
----
-
-## Сообщество
-
-[![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&label=Discord)](https://discord.gg/wdNEHETs87)
-
-- [Сообщество Discord](https://discord.gg/wdNEHETs87)
-
----
-
-## История Stars
-
-[![Star History Chart](https://api.star-history.com/svg?repos=langbot-app/LangBot&type=Date)](https://star-history.com/#langbot-app/LangBot&Date)
-
----
-
-## Участники
-
-Спасибо всем [участникам](https://github.com/langbot-app/LangBot/graphs/contributors), которые помогли сделать LangBot лучше:
+Спасибо следующим [контрибьюторам кода](https://github.com/langbot-app/LangBot/graphs/contributors) и другим членам сообщества за их вклад в LangBot:
 
 <a href="https://github.com/langbot-app/LangBot/graphs/contributors">
   <img src="https://contrib.rocks/image?repo=langbot-app/LangBot" />

README_TW.md

@@ -1,70 +1,43 @@
 <p align="center">
 <a href="https://langbot.app">
-<img width="130" src="res/logo-blue.png" alt="LangBot"/>
+<img src="https://docs.langbot.app/social_zh.png" alt="LangBot"/>
 </a>
 
-<div align="center">
+<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>
 
-<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>生產級 AI 即時通訊機器人開發平台。</h3>
-<h4>快速建構、除錯和部署 AI 機器人到微信、QQ、飛書、Slack、Discord、Telegram 等平台。</h4>
-
-[English](README.md) / [简体中文](README_CN.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)
+[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)
 [![QQ Group](https://img.shields.io/badge/%E7%A4%BE%E5%8C%BAQQ%E7%BE%A4-966235608-blue)](https://qm.qq.com/q/JLi38whHum)
 [![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/langbot-app/LangBot)
 [![GitHub release (latest by date)](https://img.shields.io/github/v/release/langbot-app/LangBot)](https://github.com/langbot-app/LangBot/releases/latest)
 <img src="https://img.shields.io/badge/python-3.10 ~ 3.13 -blue.svg" alt="python">
-[![GitHub stars](https://img.shields.io/github/stars/langbot-app/LangBot?style=social)](https://github.com/langbot-app/LangBot/stargazers)
 [![star](https://gitcode.com/RockChinQ/LangBot/star/badge.svg)](https://gitcode.com/RockChinQ/LangBot)
 
-<a href="https://langbot.app">官網</a> ｜
-<a href="https://docs.langbot.app/zh/insight/features.html">特性</a> ｜
-<a href="https://docs.langbot.app/zh/insight/guide.html">文件</a> ｜
-<a href="https://docs.langbot.app/zh/tags/readme.html">API</a> ｜
-<a href="https://space.langbot.app">外掛市場</a> ｜
-<a href="https://langbot.featurebase.app/roadmap">路線圖</a>
+<a href="https://langbot.app">主頁</a> ｜
+<a href="https://docs.langbot.app/zh/insight/guide.html">部署文件</a> ｜
+<a href="https://docs.langbot.app/zh/plugin/plugin-intro.html">外掛介紹</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">提交外掛</a>
 
 </div>
 
 </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。
 
-## 什麼是 LangBot？
+## 📦 開始使用
 
-LangBot 是一個**開源的生產級平台**，用於建構 AI 驅動的即時通訊機器人。它將大語言模型（LLM）連接到各種聊天平台，幫助你創建能夠對話、執行任務、並整合到現有工作流程中的智能 Agent。
+#### 快速部署
 
-### 核心能力
-
-- **AI 對話與 Agent** — 多輪對話、工具調用、多模態、流式輸出。自帶 RAG（知識庫），深度整合 [Dify](https://dify.ai)、[Coze](https://coze.com)、[n8n](https://n8n.io)、[Langflow](https://langflow.org) 等 LLMOps 平台。
-- **全平台支援** — 一套程式碼，覆蓋 QQ、微信、企業微信、飛書、釘釘、Discord、Telegram、Slack、LINE、KOOK 等平台。
-- **生產就緒** — 存取控制、限速、敏感詞過濾、全面監控與異常處理，已被多家企業採用。
-- **外掛生態** — 數百個外掛，事件驅動架構，組件擴展，適配 [MCP 協議](https://modelcontextprotocol.io/)。
-- **Web 管理面板** — 透過瀏覽器直觀地配置、管理和監控機器人，無需手動編輯設定檔。
-- **多流水線架構** — 不同機器人用於不同場景，具備全面的監控和異常處理能力。
-
-[→ 了解更多功能特性](https://docs.langbot.app/zh/insight/features.html)
-
----
-
-## 快速開始
-
-### ☁️ LangBot Cloud（推薦）
-
-**[LangBot Cloud](https://space.langbot.app/cloud)** — 免部署，開箱即用。
-
-### 一鍵啟動
+使用 `uvx` 一鍵啟動（需要先安裝 [uv](https://docs.astral.sh/uv/getting-started/installation/) ）：
 
 ```bash
 uvx langbot
 ```
 
-> 需要安裝 [uv](https://docs.astral.sh/uv/getting-started/installation/)。訪問 http://localhost:5300 即可使用。
+訪問 http://localhost:5300 即可開始使用。
 
-### Docker Compose
+#### Docker Compose 部署
 
 ```bash
 git clone https://github.com/langbot-app/LangBot
@@ -72,63 +45,99 @@ cd LangBot/docker
 docker compose up -d
 ```
 
-### 一鍵雲端部署
+訪問 http://localhost:5300 即可開始使用。
+
+詳細文件[Docker 部署](https://docs.langbot.app/zh/deploy/langbot/docker.html)。
+
+#### 寶塔面板部署
+
+已上架寶塔面板，若您已安裝寶塔面板，可以根據[文件](https://docs.langbot.app/zh/deploy/langbot/one-click/bt.html)使用。
+
+#### Zeabur 雲端部署
+
+社群貢獻的 Zeabur 模板。
 
 [![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/zh-CN/templates/ZKTBDH)
+
+#### Railway 雲端部署
+
 [![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF)
 
-**更多方式：** [Docker](https://docs.langbot.app/zh/deploy/langbot/docker.html) · [手動部署](https://docs.langbot.app/zh/deploy/langbot/manual.html) · [寶塔面板](https://docs.langbot.app/zh/deploy/langbot/one-click/bt.html) · [Kubernetes](./docker/README_K8S.md)
+#### 手動部署
 
----
+直接使用發行版運行，查看文件[手動部署](https://docs.langbot.app/zh/deploy/langbot/manual.html)。
 
-## 支援的平台
+#### Kubernetes 部署
+
+參考 [Kubernetes 部署](./docker/README_K8S.md) 文件。
+
+## 😎 保持更新
+
+點擊倉庫右上角 Star 和 Watch 按鈕，獲取最新動態。
+
+![star gif](https://docs.langbot.app/star.gif)
+
+## ✨ 特性
+
+- 💬 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 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。
+- 🧩 外掛擴展、活躍社群：高穩定性、高安全性的生產級外掛系統；支援事件驅動、組件擴展等外掛機制；適配 Anthropic [MCP 協議](https://modelcontextprotocol.io/)；目前已有數百個外掛。
+- 😻 Web 管理面板：支援通過瀏覽器管理 LangBot 實例，不再需要手動編寫配置文件。
+
+詳細規格特性請訪問[文件](https://docs.langbot.app/zh/insight/features.html)。
+
+或訪問 demo 環境：https://demo.langbot.dev/  
+  - 登入資訊：郵箱：`demo@langbot.app` 密碼：`langbot123456`
+  - 注意：僅展示 WebUI 效果，公開環境，請不要在其中填入您的任何敏感資訊。
+
+### 訊息平台
 
 | 平台 | 狀態 | 備註 |
-|------|------|------|
-| QQ | ✅ | 個人號、官方機器人（頻道、私聊、群聊） |
-| 微信 | ✅ | 個人微信、微信公眾號 |
-| 企業微信 | ✅ | 應用訊息、對外客服、智能機器人 |
-| 飛書 | ✅ |  |
-| 釘釘 | ✅ |  |
+| --- | --- | --- |
 | Discord | ✅ |  |
 | Telegram | ✅ |  |
 | Slack | ✅ |  |
 | LINE | ✅ |  |
-| KOOK | ✅ |  |
-| Satori | ✅ |  |
+| QQ 個人號 | ✅ | QQ 個人號私聊、群聊 |
+| QQ 官方機器人 | ✅ | QQ 官方機器人，支援頻道、私聊、群聊 |
+| 微信 | ✅ |  |
+| 企微對外客服 | ✅ |  |
+| 企微智能機器人 | ✅ |  |
+| 微信公眾號 | ✅ |  |
+| Lark | ✅ |  |
+| DingTalk | ✅ |  |
 
----
+### 大模型能力
 
-## 支援的大模型與整合
+| 模型 | 狀態 | 備註 |
+| --- | --- | --- |
+| [OpenAI](https://platform.openai.com/) | ✅ | 可接入任何 OpenAI 介面格式模型 |
+| [DeepSeek](https://www.deepseek.com/) | ✅ |  |
+| [Moonshot](https://www.moonshot.cn/) | ✅ |  |
+| [Anthropic](https://www.anthropic.com/) | ✅ |  |
+| [xAI](https://x.ai/) | ✅ |  |
+| [智譜AI](https://open.bigmodel.cn/) | ✅ |  |
+| [勝算雲](https://www.shengsuanyun.com/?from=CH_KYIPP758) | ✅ | 大模型和 GPU 資源平台 |
+| [優雲智算](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | ✅ | 大模型和 GPU 資源平台 |
+| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | ✅ | 大模型和 GPU 資源平台 |
+| [接口 AI](https://jiekou.ai/) | ✅ | 大模型聚合平台，專注全球大模型接入 |
+| [302.AI](https://share.302.ai/SuTG99) | ✅ | 大模型聚合平台 |
+| [Google Gemini](https://aistudio.google.com/prompts/new_chat) | ✅ | |
+| [Dify](https://dify.ai) | ✅ | LLMOps 平台 |
+| [Ollama](https://ollama.com/) | ✅ | 本地大模型運行平台 |
+| [LMStudio](https://lmstudio.ai/) | ✅ | 本地大模型運行平台 |
+| [GiteeAI](https://ai.gitee.com/) | ✅ | 大模型介面聚合平台 |
+| [SiliconFlow](https://siliconflow.cn/) | ✅ | 大模型聚合平台 |
+| [阿里雲百煉](https://bailian.console.aliyun.com/) | ✅ | 大模型聚合平台, LLMOps 平台 |
+| [火山方舟](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | ✅ | 大模型聚合平台, LLMOps 平台 |
+| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | ✅ | 大模型聚合平台 |
+| [MCP](https://modelcontextprotocol.io/) | ✅ | 支援通過 MCP 協議獲取工具 |
 
-| 提供商 | 類型 | 狀態 |
-|--------|------|------|
-| [OpenAI](https://platform.openai.com/) | LLM | ✅ |
-| [Anthropic](https://www.anthropic.com/) | LLM | ✅ |
-| [DeepSeek](https://www.deepseek.com/) | LLM | ✅ |
-| [Google Gemini](https://aistudio.google.com/prompts/new_chat) | LLM | ✅ |
-| [xAI](https://x.ai/) | LLM | ✅ |
-| [Moonshot](https://www.moonshot.cn/) | LLM | ✅ |
-| [智譜AI](https://open.bigmodel.cn/) | LLM | ✅ |
-| [Ollama](https://ollama.com/) | 本地 LLM | ✅ |
-| [LM Studio](https://lmstudio.ai/) | 本地 LLM | ✅ |
-| [Dify](https://dify.ai) | LLMOps | ✅ |
-| [MCP](https://modelcontextprotocol.io/) | 協議 | ✅ |
-| [SiliconFlow](https://siliconflow.cn/) | 聚合平台 | ✅ |
-| [阿里雲百煉](https://bailian.console.aliyun.com/) | 聚合平台 | ✅ |
-| [火山方舟](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | 聚合平台 | ✅ |
-| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | 聚合平台 | ✅ |
-| [GiteeAI](https://ai.gitee.com/) | 聚合平台 | ✅ |
-| [勝算雲](https://www.shengsuanyun.com/?from=CH_KYIPP758) | GPU 平台 | ✅ |
-| [優雲智算](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | GPU 平台 | ✅ |
-| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | GPU 平台 | ✅ |
-| [接口 AI](https://jiekou.ai/) | 聚合平台 | ✅ |
-| [302.AI](https://share.302.ai/SuTG99) | 聚合平台 | ✅ |
-
-### TTS（語音合成）
+### TTS
 
 | 平台/模型 | 備註 |
-|-----------|------|
+| --- | --- |
 | [FishAudio](https://fish.audio/zh-CN/discovery/) | [外掛](https://github.com/the-lazy-me/NewChatVoice) |
 | [海豚 AI](https://www.ttson.cn/?source=thelazy) | [外掛](https://github.com/the-lazy-me/NewChatVoice) |
 | [AzureTTS](https://portal.azure.com/) | [外掛](https://github.com/Ingnaryk/LangBot_AzureTTS) |
@@ -136,54 +145,13 @@ docker compose up -d
 ### 文生圖
 
 | 平台/模型 | 備註 |
-|-----------|------|
-| 阿里雲百煉 | [外掛](https://github.com/Thetail001/LangBot_BailianTextToImagePlugin) |
+| --- | --- |
+| 阿里雲百煉 | [外掛](https://github.com/Thetail001/LangBot_BailianTextToImagePlugin)
 
-[→ 查看完整整合列表](https://docs.langbot.app/zh/insight/features.html)
+## 😘 社群貢獻
 
----
-
-## 為什麼選擇 LangBot？
-
-| 使用場景 | LangBot 如何幫助 |
-|----------|------------------|
-| **客戶服務** | 將 AI Agent 部署到微信/企微/釘釘/飛書，基於知識庫自動回答使用者問題 |
-| **內部工具** | 將 n8n/Dify 工作流接入企微/釘釘，實現業務流程自動化 |
-| **社群運營** | 在 QQ/Discord 群中使用 AI 驅動的內容審核與智能互動 |
-| **多平台觸達** | 一個機器人，覆蓋所有平台。透過統一面板集中管理 |
-
----
-
-## 線上演示
-
-**立即體驗：** https://demo.langbot.dev/
-- 信箱：`demo@langbot.app`
-- 密碼：`langbot123456`
-
-*注意：公開演示環境，請不要在其中填入任何敏感資訊。*
-
----
-
-## 社群
-
-[![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&label=Discord)](https://discord.gg/wdNEHETs87)
-[![QQ Group](https://img.shields.io/badge/%E7%A4%BE%E5%8C%BAQQ%E7%BE%A4-966235608-blue)](https://qm.qq.com/q/JLi38whHum)
-
-- [Discord 社群](https://discord.gg/wdNEHETs87)
-- [QQ 社群群](https://qm.qq.com/q/JLi38whHum)
-
----
-
-## Star 趨勢
-
-[![Star History Chart](https://api.star-history.com/svg?repos=langbot-app/LangBot&type=Date)](https://star-history.com/#langbot-app/LangBot&Date)
-
----
-
-## 貢獻者
-
-感謝所有[貢獻者](https://github.com/langbot-app/LangBot/graphs/contributors)對 LangBot 的幫助：
+感謝以下[程式碼貢獻者](https://github.com/langbot-app/LangBot/graphs/contributors)和社群裡其他成員對 LangBot 的貢獻：
 
 <a href="https://github.com/langbot-app/LangBot/graphs/contributors">
   <img src="https://contrib.rocks/image?repo=langbot-app/LangBot" />
-</a>
+</a> 

README_VI.md

@@ -1,68 +1,43 @@
 <p align="center">
 <a href="https://langbot.app">
-<img width="130" src="res/logo-blue.png" alt="LangBot"/>
+<img src="https://docs.langbot.app/social_en.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>Nền tảng cấp sản xuất để xây dựng bot IM với AI agent.</h3>
-<h4>Xây dựng, gỡ lỗi và triển khai bot AI nhanh chóng trên Slack, Discord, Telegram, WeChat và nhiều nền tảng khác.</h4>
-
-[English](README.md) / [简体中文](README_CN.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
+[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)
 [![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/langbot-app/LangBot)
 [![GitHub release (latest by date)](https://img.shields.io/github/v/release/langbot-app/LangBot)](https://github.com/langbot-app/LangBot/releases/latest)
 <img src="https://img.shields.io/badge/python-3.10 ~ 3.13 -blue.svg" alt="python">
-[![GitHub stars](https://img.shields.io/github/stars/langbot-app/LangBot?style=social)](https://github.com/langbot-app/LangBot/stargazers)
 
 <a href="https://langbot.app">Trang chủ</a> ｜
-<a href="https://docs.langbot.app/en/insight/features.html">Tính năng</a> ｜
-<a href="https://docs.langbot.app/en/insight/guide.html">Tài liệu</a> ｜
-<a href="https://docs.langbot.app/en/tags/readme.html">API</a> ｜
-<a href="https://space.langbot.app">Chợ Plugin</a> ｜
-<a href="https://langbot.featurebase.app/roadmap">Lộ trình</a>
+<a href="https://docs.langbot.app/en/insight/guide.html">Triển khai</a> ｜
+<a href="https://docs.langbot.app/en/plugin/plugin-intro.html">Plugin</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">Gửi Plugin</a>
 
 </div>
 
 </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.
 
-## LangBot là gì?
+## 📦 Bắt đầu
 
-LangBot là một **nền tảng mã nguồn mở, cấp sản xuất** để xây dựng bot nhắn tin tức thời được hỗ trợ bởi AI. Nó kết nối các Mô hình Ngôn ngữ Lớn (LLM) với bất kỳ nền tảng chat nào, cho phép bạn tạo các agent thông minh có thể trò chuyện, thực hiện tác vụ và tích hợp với quy trình làm việc hiện có của bạn.
+#### Khởi động Nhanh
 
-### Khả năng chính
-
-- **Hội thoại AI & Agent** — Đối thoại nhiều lượt, gọi công cụ, hỗ trợ đa phương thức, đầu ra streaming. RAG (cơ sở kiến thức) tích hợp sẵn với tích hợp sâu vào [Dify](https://dify.ai), [Coze](https://coze.com), [n8n](https://n8n.io), [Langflow](https://langflow.org).
-- **Hỗ trợ đa nền tảng IM** — Một mã nguồn cho Discord, Telegram, Slack, LINE, QQ, WeChat, WeCom, Lark, DingTalk, KOOK.
-- **Sẵn sàng cho sản xuất** — Kiểm soát truy cập, giới hạn tốc độ, lọc từ nhạy cảm, giám sát toàn diện và xử lý ngoại lệ. Được doanh nghiệp tin dùng.
-- **Hệ sinh thái Plugin** — Hàng trăm plugin, kiến trúc hướng sự kiện, mở rộng thành phần, và hỗ trợ [giao thức MCP](https://modelcontextprotocol.io/).
-- **Bảng quản lý Web** — Cấu hình, quản lý và giám sát bot thông qua giao diện trình duyệt trực quan. Không cần chỉnh sửa YAML.
-- **Kiến trúc đa Pipeline** — Các bot khác nhau cho các kịch bản khác nhau, với giám sát toàn diện và xử lý ngoại lệ.
-
-[→ Tìm hiểu thêm về tất cả tính năng](https://docs.langbot.app/en/insight/features.html)
-
----
-
-## Bắt đầu nhanh
-
-### ☁️ LangBot Cloud (Khuyên dùng)
-
-**[LangBot Cloud](https://space.langbot.app/cloud)** — Không cần triển khai, sẵn sàng sử dụng.
-
-### Khởi chạy một dòng
+Sử dụng `uvx` để khởi động bằng một lệnh (cần cài đặt [uv](https://docs.astral.sh/uv/getting-started/installation/)):
 
 ```bash
 uvx langbot
 ```
 
-> Yêu cầu [uv](https://docs.astral.sh/uv/getting-started/installation/). Truy cập http://localhost:5300 — xong.
+Truy cập http://localhost:5300 để bắt đầu sử dụng.
 
-### Docker Compose
+#### Triển khai Docker Compose
 
 ```bash
 git clone https://github.com/langbot-app/LangBot
@@ -70,101 +45,98 @@ cd LangBot/docker
 docker compose up -d
 ```
 
-### Triển khai đám mây một cú nhấp
+Truy cập http://localhost:5300 để bắt đầu sử dụng.
+
+Tài liệu chi tiết [Triển khai Docker](https://docs.langbot.app/en/deploy/langbot/docker.html).
+
+#### Triển khai Một cú nhấp chuột trên BTPanel
+
+LangBot đã được liệt kê trên BTPanel. Nếu bạn đã cài đặt BTPanel, bạn có thể sử dụng [tài liệu](https://docs.langbot.app/en/deploy/langbot/one-click/bt.html) để sử dụng nó.
+
+#### Triển khai Cloud Zeabur
+
+Mẫu Zeabur được đóng góp bởi cộng đồng.
 
 [![Deploy on Zeabur](https://zeabur.com/button.svg)](https://zeabur.com/en-US/templates/ZKTBDH)
+
+#### Triển khai Cloud Railway
+
 [![Deploy on Railway](https://railway.com/button.svg)](https://railway.app/template/yRrAyL?referralCode=vogKPF)
 
-**Thêm tùy chọn:** [Docker](https://docs.langbot.app/en/deploy/langbot/docker.html) · [Thủ công](https://docs.langbot.app/en/deploy/langbot/manual.html) · [BTPanel](https://docs.langbot.app/en/deploy/langbot/one-click/bt.html) · [Kubernetes](./docker/README_K8S.md)
+#### Các Phương pháp Triển khai Khác
 
----
+Sử dụng trực tiếp phiên bản phát hành để chạy, xem tài liệu [Triển khai Thủ công](https://docs.langbot.app/en/deploy/langbot/manual.html).
 
-## Nền tảng được hỗ trợ
+#### Triển khai Kubernetes
+
+Tham khảo tài liệu [Triển khai Kubernetes](./docker/README_K8S.md).
+
+## 😎 Cập nhật Mới nhất
+
+Nhấp vào các nút Star và Watch ở góc trên bên phải của kho lưu trữ để nhận các bản cập nhật mới nhất.
+
+![star gif](https://docs.langbot.app/star.gif)
+
+## ✨ Tính năng
+
+- 💬 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, 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.
+- 🧩 Mở rộng Plugin, Cộng đồng Hoạt động: Hỗ trợ các cơ chế plugin hướng sự kiện, mở rộng thành phần, v.v.; Tích hợp giao thức [MCP](https://modelcontextprotocol.io/) của Anthropic; Hiện có hàng trăng plugin.
+- 😻 Giao diện Web: Hỗ trợ quản lý các phiên bản LangBot thông qua trình duyệt. Không cần viết tệp cấu hình thủ công.
+
+Để biết thêm thông số kỹ thuật chi tiết, vui lòng tham khảo [tài liệu](https://docs.langbot.app/en/insight/features.html).
+
+Hoặc truy cập môi trường demo: https://demo.langbot.dev/
+  - Thông tin đăng nhập: Email: `demo@langbot.app` Mật khẩu: `langbot123456`
+  - Lưu ý: Chỉ dành cho demo WebUI, vui lòng không nhập bất kỳ thông tin nhạy cảm nào trong môi trường công cộng.
+
+### Nền tảng Nhắn tin
 
 | Nền tảng | Trạng thái | Ghi chú |
-|----------|--------|-------|
+| --- | --- | --- |
 | Discord | ✅ |  |
 | Telegram | ✅ |  |
 | Slack | ✅ |  |
 | LINE | ✅ |  |
-| QQ | ✅ | Cá nhân & API chính thức |
-| WeCom | ✅ | WeChat doanh nghiệp, CS bên ngoài, AI Bot |
-| WeChat | ✅ | Cá nhân & Tài khoản công khai |
+| QQ Cá nhân | ✅ |  |
+| QQ API Chính thức | ✅ |  |
+| WeCom | ✅ |  |
+| WeComCS | ✅ |  |
+| WeCom AI Bot | ✅ |  |
+| WeChat Cá nhân | ✅ |  |
 | Lark | ✅ |  |
 | DingTalk | ✅ |  |
-| KOOK | ✅ |  |
-| Satori | ✅ |  |
 
----
+### LLMs
 
-## LLM và tích hợp được hỗ trợ
+| LLM | Trạng thái | Ghi chú |
+| --- | --- | --- |
+| [OpenAI](https://platform.openai.com/) | ✅ | Có sẵn cho bất kỳ mô hình định dạng giao diện OpenAI nào |
+| [DeepSeek](https://www.deepseek.com/) | ✅ |  |
+| [Moonshot](https://www.moonshot.cn/) | ✅ |  |
+| [Anthropic](https://www.anthropic.com/) | ✅ |  |
+| [xAI](https://x.ai/) | ✅ |  |
+| [Zhipu AI](https://open.bigmodel.cn/) | ✅ |  |
+| [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | ✅ | Nền tảng tài nguyên LLM và GPU |
+| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | ✅ | Nền tảng tài nguyên LLM và GPU |
+| [接口 AI](https://jiekou.ai/) | ✅ | Nền tảng tổng hợp LLM |
+| [ShengSuanYun](https://www.shengsuanyun.com/?from=CH_KYIPP758) | ✅ | Nền tảng tài nguyên LLM và GPU |
+| [302.AI](https://share.302.ai/SuTG99) | ✅ | Cổng LLM (MaaS) |
+| [Google Gemini](https://aistudio.google.com/prompts/new_chat) | ✅ | |
+| [Dify](https://dify.ai) | ✅ | Nền tảng LLMOps |
+| [Ollama](https://ollama.com/) | ✅ | Nền tảng chạy LLM cục bộ |
+| [LMStudio](https://lmstudio.ai/) | ✅ | Nền tảng chạy LLM cục bộ |
+| [GiteeAI](https://ai.gitee.com/) | ✅ | Cổng giao diện LLM (MaaS) |
+| [SiliconFlow](https://siliconflow.cn/) | ✅ | Cổng LLM (MaaS) |
+| [Aliyun Bailian](https://bailian.console.aliyun.com/) | ✅ | Cổng LLM (MaaS), nền tảng LLMOps |
+| [Volc Engine Ark](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | ✅ | Cổng LLM (MaaS), nền tảng LLMOps |
+| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | ✅ | Cổng LLM (MaaS) |
+| [MCP](https://modelcontextprotocol.io/) | ✅ | Hỗ trợ truy cập công cụ qua giao thức MCP |
 
-| Nhà cung cấp | Loại | Trạng thái |
-|----------|------|--------|
-| [OpenAI](https://platform.openai.com/) | LLM | ✅ |
-| [Anthropic](https://www.anthropic.com/) | LLM | ✅ |
-| [DeepSeek](https://www.deepseek.com/) | LLM | ✅ |
-| [Google Gemini](https://aistudio.google.com/prompts/new_chat) | LLM | ✅ |
-| [xAI](https://x.ai/) | LLM | ✅ |
-| [Moonshot](https://www.moonshot.cn/) | LLM | ✅ |
-| [Zhipu AI](https://open.bigmodel.cn/) | LLM | ✅ |
-| [Ollama](https://ollama.com/) | LLM cục bộ | ✅ |
-| [LM Studio](https://lmstudio.ai/) | LLM cục bộ | ✅ |
-| [Dify](https://dify.ai) | LLMOps | ✅ |
-| [MCP](https://modelcontextprotocol.io/) | Giao thức | ✅ |
-| [SiliconFlow](https://siliconflow.cn/) | Cổng | ✅ |
-| [Aliyun Bailian](https://bailian.console.aliyun.com/) | Cổng | ✅ |
-| [Volc Engine Ark](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | Cổng | ✅ |
-| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | Cổng | ✅ |
-| [GiteeAI](https://ai.gitee.com/) | Cổng | ✅ |
-| [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | Nền tảng GPU | ✅ |
-| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | Nền tảng GPU | ✅ |
-| [ShengSuanYun](https://www.shengsuanyun.com/?from=CH_KYIPP758) | Nền tảng GPU | ✅ |
-| [接口 AI](https://jiekou.ai/) | Cổng | ✅ |
-| [302.AI](https://share.302.ai/SuTG99) | Cổng | ✅ |
+## 🤝 Đóng góp Cộng đồng
 
-[→ Xem tất cả tích hợp](https://docs.langbot.app/en/insight/features.html)
-
----
-
-## Tại sao chọn LangBot?
-
-| Trường hợp sử dụng | LangBot giúp như thế nào |
-|----------|-------------------|
-| **Hỗ trợ khách hàng** | Triển khai agent AI trên Slack/Discord/Telegram để trả lời câu hỏi bằng cơ sở kiến thức của bạn |
-| **Công cụ nội bộ** | Kết nối quy trình n8n/Dify với WeCom/DingTalk để tự động hóa quy trình kinh doanh |
-| **Quản lý cộng đồng** | Quản lý nhóm QQ/Discord với tính năng lọc nội dung và tương tác được hỗ trợ bởi AI |
-| **Đa nền tảng** | Một bot, tất cả nền tảng. Quản lý từ một bảng điều khiển duy nhất |
-
----
-
-## Demo trực tuyến
-
-**Thử ngay:** https://demo.langbot.dev/
-- Email: `demo@langbot.app`
-- Mật khẩu: `langbot123456`
-
-*Lưu ý: Môi trường demo công khai. Không nhập thông tin nhạy cảm.*
-
----
-
-## Cộng đồng
-
-[![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&label=Discord)](https://discord.gg/wdNEHETs87)
-
-- [Cộng đồng Discord](https://discord.gg/wdNEHETs87)
-
----
-
-## Lịch sử Star
-
-[![Star History Chart](https://api.star-history.com/svg?repos=langbot-app/LangBot&type=Date)](https://star-history.com/#langbot-app/LangBot&Date)
-
----
-
-## Người đóng góp
-
-Cảm ơn tất cả [người đóng góp](https://github.com/langbot-app/LangBot/graphs/contributors) đã giúp LangBot trở nên tốt hơn:
+Cảm ơn các [người đóng góp mã](https://github.com/langbot-app/LangBot/graphs/contributors) sau đây và các thành viên khác trong cộng đồng vì những đóng góp của họ cho LangBot:
 
 <a href="https://github.com/langbot-app/LangBot/graphs/contributors">
   <img src="https://contrib.rocks/image?repo=langbot-app/LangBot" />

docker/docker-compose.yaml

@@ -7,6 +7,7 @@ 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:
@@ -14,21 +15,23 @@ services:
     restart: on-failure
     environment:
       - TZ=Asia/Shanghai
-    command: ["uv", "run", "--no-sync", "-m", "langbot_plugin.cli.__init__", "rt"]
+    command: ["uv", "run", "-m", "langbot_plugin.cli.__init__", "rt"]
     networks:
       - langbot_network
 
   langbot:
     image: rockchin/langbot:latest
     container_name: langbot
+    platform: linux/amd64 # For Apple Silicon compatibility
     volumes:
       - ./data:/app/data
+      - ./plugins:/app/plugins
     restart: on-failure
     environment:
       - TZ=Asia/Shanghai
     ports:
-      - 5300:5300  # For web ui and webhook callback
-      - 2280-2285:2280-2285  # For platform reverse connection
+      - 5300:5300  # For web ui
+      - 2280-2290:2280-2290  # For platform webhook
     networks:
       - langbot_network
 

docs/SEEKDB_INTEGRATION.md

@@ -1,259 +0,0 @@
-# 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.

docs/service-api-openapi.json

@@ -9,7 +9,7 @@
       "url": "https://langbot.app"
     },
     "license": {
-      "name": "Apache-2.0",
+      "name": "AGPL-3.0",
       "url": "https://github.com/langbot-app/LangBot/blob/master/LICENSE"
     }
   },

pyproject.toml

@@ -1,10 +1,10 @@
 [project]
 name = "langbot"
-version = "4.9.0"
-description = "Production-grade platform for building agentic IM bots"
+version = "4.5.4"
+description = "Easy-to-use global IM bot platform designed for LLM era"
 readme = "README.md"
 license-files = ["LICENSE"]
-requires-python = ">=3.11,<4.0"
+requires-python = ">=3.10.1,<4.0"
 dependencies = [
     "aiocqhttp>=1.4.4",
     "aiofiles>=24.1.0",
@@ -17,13 +17,13 @@ dependencies = [
     "certifi>=2025.4.26",
     "colorlog~=6.6.0",
     "cryptography>=44.0.3",
-    "dashscope>=1.25.10",
+    "dashscope>=1.23.2",
     "dingtalk-stream>=0.24.0",
     "discord-py>=2.5.2",
     "pynacl>=1.5.0", # Required for Discord voice support
     "gewechat-client>=0.1.5",
     "lark-oapi>=1.4.15",
-    "mcp>=1.25.0",
+    "mcp>=1.8.1",
     "nakuru-project-idk>=0.0.2.1",
     "ollama>=0.4.8",
     "openai>1.0.0",
@@ -61,17 +61,13 @@ dependencies = [
     "html2text>=2024.2.26",
     "langchain>=0.2.0",
     "langchain-text-splitters>=0.0.1",
-    "chromadb>=1.0.0,<2.0.0",
+    "chromadb>=0.4.24",
     "qdrant-client (>=1.15.1,<2.0.0)",
-    "pyseekdb==1.1.0.post3",
-    "langbot-plugin==0.3.0",
+    "langbot-plugin==0.2.0b1",
     "asyncpg>=0.30.0",
     "line-bot-sdk>=3.19.0",
     "tboxsdk>=0.0.10",
     "boto3>=1.35.0",
-    "pymilvus>=2.6.4",
-    "pgvector>=0.4.1",
-    "botocore>=1.42.39",
 ]
 keywords = [
     "bot",

src/langbot/__init__.py

@@ -1,3 +1,3 @@
-"""LangBot - Production-grade platform for building agentic IM bots"""
+"""LangBot - Easy-to-use global IM bot platform designed for LLM era"""
 
-__version__ = '4.9.0'
+__version__ = '4.5.4'

src/langbot/libs/dingtalk_api/api.py

@@ -1,11 +1,8 @@
-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
@@ -39,7 +36,6 @@ 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'
@@ -174,9 +170,6 @@ 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]:
@@ -347,15 +340,10 @@ class DingTalkClient:
             raise Exception(f'failed to send proactive massage to group: {traceback.format_exc()}')
 
     async def create_and_card(
-        self,
-        temp_card_id: str,
-        incoming_message: dingtalk_stream.ChatbotMessage,
-        quote_origin: bool = False,
-        card_auto_layout: bool = False,
+        self, temp_card_id: str, incoming_message: dingtalk_stream.ChatbotMessage, quote_origin: bool = False
     ):
-        card_data = {}
-        card_data['config'] = json.dumps({'autoLayout': card_auto_layout})
-        card_data['content'] = ''
+        content_key = 'content'
+        card_data = {content_key: ''}
 
         card_instance = dingtalk_stream.AICardReplier(self.client, incoming_message)
         # print(card_instance)
@@ -390,70 +378,4 @@ class DingTalkClient:
 
     async def start(self):
         """启动 WebSocket 连接，监听消息"""
-        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': []}
+        await self.client.start()

src/langbot/libs/official_account_api/api.py

@@ -23,34 +23,20 @@ xml_template = """
 
 
 class OAClient:
-    def __init__(
-        self,
-        token: str,
-        EncodingAESKey: str,
-        AppID: str,
-        Appsecret: str,
-        logger: None,
-        unified_mode: bool = False,
-        api_base_url: str = 'https://api.weixin.qq.com',
-    ):
+    def __init__(self, token: str, EncodingAESKey: str, AppID: str, Appsecret: str, logger: None):
         self.token = token
         self.aes = EncodingAESKey
         self.appid = AppID
         self.appsecret = Appsecret
-        self.base_url = api_base_url
+        self.base_url = 'https://api.weixin.qq.com'
         self.access_token = ''
-        self.unified_mode = unified_mode
         self.app = Quart(__name__)
-
-        # 只有在非统一模式下才注册独立路由
-        if not self.unified_mode:
-            self.app.add_url_rule(
-                '/callback/command',
-                'handle_callback',
-                self.handle_callback_request,
-                methods=['GET', 'POST'],
-            )
-
+        self.app.add_url_rule(
+            '/callback/command',
+            'handle_callback',
+            self.handle_callback_request,
+            methods=['GET', 'POST'],
+        )
         self._message_handlers = {
             'example': [],
         }
@@ -60,39 +46,19 @@ class OAClient:
         self.logger = logger
 
     async def handle_callback_request(self):
-        """处理回调请求（独立端口模式，使用全局 request）。"""
-        return await self._handle_callback_internal(request)
-
-    async def handle_unified_webhook(self, req):
-        """处理回调请求（统一 webhook 模式，显式传递 request）。
-
-        Args:
-            req: Quart Request 对象
-
-        Returns:
-            响应数据
-        """
-        return await self._handle_callback_internal(req)
-
-    async def _handle_callback_internal(self, req):
-        """处理回调请求的内部实现，包括 GET 验证和 POST 消息接收。
-
-        Args:
-            req: Quart Request 对象
-        """
         try:
             # 每隔100毫秒查询是否生成ai回答
             start_time = time.time()
-            signature = req.args.get('signature', '')
-            timestamp = req.args.get('timestamp', '')
-            nonce = req.args.get('nonce', '')
-            echostr = req.args.get('echostr', '')
-            msg_signature = req.args.get('msg_signature', '')
+            signature = request.args.get('signature', '')
+            timestamp = request.args.get('timestamp', '')
+            nonce = request.args.get('nonce', '')
+            echostr = request.args.get('echostr', '')
+            msg_signature = request.args.get('msg_signature', '')
             if msg_signature is None:
                 await self.logger.error('msg_signature不在请求体中')
                 raise Exception('msg_signature不在请求体中')
 
-            if req.method == 'GET':
+            if request.method == 'GET':
                 # 校验签名
                 check_str = ''.join(sorted([self.token, timestamp, nonce]))
                 check_signature = hashlib.sha1(check_str.encode('utf-8')).hexdigest()
@@ -102,8 +68,8 @@ class OAClient:
                 else:
                     await self.logger.error('拒绝请求')
                     raise Exception('拒绝请求')
-            elif req.method == 'POST':
-                encryt_msg = await req.data
+            elif request.method == 'POST':
+                encryt_msg = await request.data
                 wxcpt = WXBizMsgCrypt(self.token, self.aes, self.appid)
                 ret, xml_msg = wxcpt.DecryptMsg(encryt_msg, msg_signature, timestamp, nonce)
                 xml_msg = xml_msg.decode('utf-8')
@@ -216,27 +182,20 @@ class OAClientForLongerResponse:
         Appsecret: str,
         LoadingMessage: str,
         logger: None,
-        unified_mode: bool = False,
-        api_base_url: str = 'https://api.weixin.qq.com',
     ):
         self.token = token
         self.aes = EncodingAESKey
         self.appid = AppID
         self.appsecret = Appsecret
-        self.base_url = api_base_url
+        self.base_url = 'https://api.weixin.qq.com'
         self.access_token = ''
-        self.unified_mode = unified_mode
         self.app = Quart(__name__)
-
-        # 只有在非统一模式下才注册独立路由
-        if not self.unified_mode:
-            self.app.add_url_rule(
-                '/callback/command',
-                'handle_callback',
-                self.handle_callback_request,
-                methods=['GET', 'POST'],
-            )
-
+        self.app.add_url_rule(
+            '/callback/command',
+            'handle_callback',
+            self.handle_callback_request,
+            methods=['GET', 'POST'],
+        )
         self._message_handlers = {
             'example': [],
         }
@@ -247,44 +206,24 @@ class OAClientForLongerResponse:
         self.logger = logger
 
     async def handle_callback_request(self):
-        """处理回调请求（独立端口模式，使用全局 request）。"""
-        return await self._handle_callback_internal(request)
-
-    async def handle_unified_webhook(self, req):
-        """处理回调请求（统一 webhook 模式，显式传递 request）。
-
-        Args:
-            req: Quart Request 对象
-
-        Returns:
-            响应数据
-        """
-        return await self._handle_callback_internal(req)
-
-    async def _handle_callback_internal(self, req):
-        """处理回调请求的内部实现，包括 GET 验证和 POST 消息接收。
-
-        Args:
-            req: Quart Request 对象
-        """
         try:
-            signature = req.args.get('signature', '')
-            timestamp = req.args.get('timestamp', '')
-            nonce = req.args.get('nonce', '')
-            echostr = req.args.get('echostr', '')
-            msg_signature = req.args.get('msg_signature', '')
+            signature = request.args.get('signature', '')
+            timestamp = request.args.get('timestamp', '')
+            nonce = request.args.get('nonce', '')
+            echostr = request.args.get('echostr', '')
+            msg_signature = request.args.get('msg_signature', '')
 
             if msg_signature is None:
                 await self.logger.error('msg_signature不在请求体中')
                 raise Exception('msg_signature不在请求体中')
 
-            if req.method == 'GET':
+            if request.method == 'GET':
                 check_str = ''.join(sorted([self.token, timestamp, nonce]))
                 check_signature = hashlib.sha1(check_str.encode('utf-8')).hexdigest()
                 return echostr if check_signature == signature else '拒绝请求'
 
-            elif req.method == 'POST':
-                encryt_msg = await req.data
+            elif request.method == 'POST':
+                encryt_msg = await request.data
                 wxcpt = WXBizMsgCrypt(self.token, self.aes, self.appid)
                 ret, xml_msg = wxcpt.DecryptMsg(encryt_msg, msg_signature, timestamp, nonce)
                 xml_msg = xml_msg.decode('utf-8')

src/langbot/libs/qq_official_api/api.py

@@ -10,20 +10,38 @@ import traceback
 from cryptography.hazmat.primitives.asymmetric import ed25519
 
 
+def handle_validation(body: dict, bot_secret: str):
+    # bot正确的secert是32位的，此处仅为了适配演示demo
+    while len(bot_secret) < 32:
+        bot_secret = bot_secret * 2
+    bot_secret = bot_secret[:32]
+    # 实际使用场景中以上三行内容可清除
+
+    seed_bytes = bot_secret.encode()
+
+    signing_key = ed25519.Ed25519PrivateKey.from_private_bytes(seed_bytes)
+
+    msg = body['d']['event_ts'] + body['d']['plain_token']
+    msg_bytes = msg.encode()
+
+    signature = signing_key.sign(msg_bytes)
+
+    signature_hex = signature.hex()
+
+    response = {'plain_token': body['d']['plain_token'], 'signature': signature_hex}
+
+    return response
+
+
 class QQOfficialClient:
-    def __init__(self, secret: str, token: str, app_id: str, logger: None, unified_mode: bool = False):
-        self.unified_mode = unified_mode
+    def __init__(self, secret: str, token: str, app_id: str, logger: None):
         self.app = Quart(__name__)
-
-        # 只有在非统一模式下才注册独立路由
-        if not self.unified_mode:
-            self.app.add_url_rule(
-                '/callback/command',
-                'handle_callback',
-                self.handle_callback_request,
-                methods=['GET', 'POST'],
-            )
-
+        self.app.add_url_rule(
+            '/callback/command',
+            'handle_callback',
+            self.handle_callback_request,
+            methods=['GET', 'POST'],
+        )
         self.secret = secret
         self.token = token
         self.app_id = app_id
@@ -64,43 +82,18 @@ class QQOfficialClient:
                 raise Exception(f'获取access_token失败: {e}')
 
     async def handle_callback_request(self):
-        """处理回调请求（独立端口模式，使用全局 request）"""
-        return await self._handle_callback_internal(request)
-
-    async def handle_unified_webhook(self, req):
-        """处理回调请求（统一 webhook 模式，显式传递 request）。
-
-        Args:
-            req: Quart Request 对象
-
-        Returns:
-            响应数据
-        """
-        return await self._handle_callback_internal(req)
-
-    async def _handle_callback_internal(self, req):
-        """处理回调请求的内部实现。
-
-        Args:
-            req: Quart Request 对象
-        """
+        """处理回调请求"""
         try:
-            body = await req.get_data()
-
-            print(f'[QQ Official] Received request, body length: {len(body)}')
-
-            if not body or len(body) == 0:
-                print('[QQ Official] Received empty body, might be health check or GET request')
-                return {'code': 0, 'message': 'ok'}, 200
-
+            # 读取请求数据
+            body = await request.get_data()
             payload = json.loads(body)
 
+            # 验证是否为回调验证请求
             if payload.get('op') == 13:
-                validation_data = payload.get('d')
-                if not validation_data:
-                    return {'error': "missing 'd' field"}, 400
-                response = await self.verify(validation_data)
-                return response, 200
+                # 生成签名
+                response = handle_validation(payload, self.secret)
+
+                return response
 
             if payload.get('op') == 0:
                 message_data = await self.get_message(payload)
@@ -111,7 +104,6 @@ class QQOfficialClient:
             return {'code': 0, 'message': 'success'}
 
         except Exception as e:
-            print(f'[QQ Official] ERROR: {traceback.format_exc()}')
             await self.logger.error(f'Error in handle_callback_request: {traceback.format_exc()}')
             return {'error': str(e)}, 400
 
@@ -269,26 +261,3 @@ class QQOfficialClient:
         if self.access_token_expiry_time is None:
             return True
         return time.time() > self.access_token_expiry_time
-
-    async def repeat_seed(self, bot_secret: str, target_size: int = 32) -> bytes:
-        seed = bot_secret
-        while len(seed) < target_size:
-            seed *= 2
-        return seed[:target_size].encode('utf-8')
-
-    async def verify(self, validation_payload: dict):
-        seed = await self.repeat_seed(self.secret)
-        private_key = ed25519.Ed25519PrivateKey.from_private_bytes(seed)
-
-        event_ts = validation_payload.get('event_ts', '')
-        plain_token = validation_payload.get('plain_token', '')
-        msg = event_ts + plain_token
-
-        # sign
-        signature = private_key.sign(msg.encode()).hex()
-
-        response = {
-            'plain_token': plain_token,
-            'signature': signature,
-        }
-        return response

src/langbot/libs/slack_api/api.py

@@ -8,19 +8,14 @@ import langbot_plugin.api.entities.builtin.platform.events as platform_events
 
 
 class SlackClient:
-    def __init__(self, bot_token: str, signing_secret: str, logger: None, unified_mode: bool = False):
+    def __init__(self, bot_token: str, signing_secret: str, logger: None):
         self.bot_token = bot_token
         self.signing_secret = signing_secret
-        self.unified_mode = unified_mode
         self.app = Quart(__name__)
         self.client = AsyncWebClient(self.bot_token)
-
-        # 只有在非统一模式下才注册独立路由
-        if not self.unified_mode:
-            self.app.add_url_rule(
-                '/callback/command', 'handle_callback', self.handle_callback_request, methods=['GET', 'POST']
-            )
-
+        self.app.add_url_rule(
+            '/callback/command', 'handle_callback', self.handle_callback_request, methods=['GET', 'POST']
+        )
         self._message_handlers = {
             'example': [],
         }
@@ -28,28 +23,8 @@ class SlackClient:
         self.logger = logger
 
     async def handle_callback_request(self):
-        """处理回调请求（独立端口模式，使用全局 request）"""
-        return await self._handle_callback_internal(request)
-
-    async def handle_unified_webhook(self, req):
-        """处理回调请求（统一 webhook 模式，显式传递 request）。
-
-        Args:
-            req: Quart Request 对象
-
-        Returns:
-            响应数据
-        """
-        return await self._handle_callback_internal(req)
-
-    async def _handle_callback_internal(self, req):
-        """处理回调请求的内部实现。
-
-        Args:
-            req: Quart Request 对象
-        """
         try:
-            body = await req.get_data()
+            body = await request.get_data()
             data = json.loads(body)
             if 'type' in data:
                 if data['type'] == 'url_verification':

src/langbot/libs/wechatpad_api/util/http_util.py

@@ -1,5 +1,5 @@
 import requests
-from langbot.pkg.utils import httpclient
+import aiohttp
 
 
 def post_json(base_url, token, data=None):
@@ -63,16 +63,16 @@ async def async_request(
     """
     headers = {'Content-Type': 'application/json'}
     url = f'{base_url}?key={token_key}'
-    session = httpclient.get_session()
-    async with session.request(
-        method=method, url=url, params=params, headers=headers, data=data, json=json
-    ) as response:
-        response.raise_for_status()  # 如果状态码不是200，抛出异常
-        result = await response.json()
-        # print(result)
-        return result
-        # if result.get('Code') == 200:
-        #
-        #     return await result
-        # else:
-        #     raise RuntimeError("请求失败",response.text)
+    async with aiohttp.ClientSession() as session:
+        async with session.request(
+            method=method, url=url, params=params, headers=headers, data=data, json=json
+        ) as response:
+            response.raise_for_status()  # 如果状态码不是200，抛出异常
+            result = await response.json()
+            # print(result)
+            return result
+            # if result.get('Code') == 200:
+            #
+            #     return await result
+            # else:
+            #     raise RuntimeError("请求失败",response.text)

src/langbot/libs/wecom_ai_bot_api/api.py

@@ -200,7 +200,7 @@ class StreamSessionManager:
 
 
 class WecomBotClient:
-    def __init__(self, Token: str, EnCodingAESKey: str, Corpid: str, logger: EventLogger, unified_mode: bool = False):
+    def __init__(self, Token: str, EnCodingAESKey: str, Corpid: str, logger: EventLogger):
         """企业微信智能机器人客户端。
 
         Args:
@@ -208,7 +208,6 @@ class WecomBotClient:
             EnCodingAESKey: 企业微信消息加解密密钥。
             Corpid: 企业 ID。
             logger: 日志记录器。
-            unified_mode: 是否使用统一 webhook 模式（默认 False）。
 
         Example:
             >>> client = WecomBotClient(Token='token', EnCodingAESKey='aeskey', Corpid='corp', logger=logger)
@@ -218,15 +217,10 @@ class WecomBotClient:
         self.EnCodingAESKey = EnCodingAESKey
         self.Corpid = Corpid
         self.ReceiveId = ''
-        self.unified_mode = unified_mode
         self.app = Quart(__name__)
-
-        # 只有在非统一模式下才注册独立路由
-        if not self.unified_mode:
-            self.app.add_url_rule(
-                '/callback/command', 'handle_callback', self.handle_callback_request, methods=['POST', 'GET']
-            )
-
+        self.app.add_url_rule(
+            '/callback/command', 'handle_callback', self.handle_callback_request, methods=['POST', 'GET']
+        )
         self._message_handlers = {
             'example': [],
         }
@@ -365,7 +359,7 @@ class WecomBotClient:
         return await self._encrypt_and_reply(payload, nonce)
 
     async def handle_callback_request(self):
-        """企业微信回调入口（独立端口模式，使用全局 request）。
+        """企业微信回调入口。
 
         Returns:
             Quart Response: 根据请求类型返回验证、首包或刷新结果。
@@ -373,33 +367,15 @@ class WecomBotClient:
         Example:
             作为 Quart 路由处理函数直接注册并使用。
         """
-        return await self._handle_callback_internal(request)
-
-    async def handle_unified_webhook(self, req):
-        """处理回调请求（统一 webhook 模式，显式传递 request）。
-
-        Args:
-            req: Quart Request 对象
-
-        Returns:
-            响应数据
-        """
-        return await self._handle_callback_internal(req)
-
-    async def _handle_callback_internal(self, req):
-        """处理回调请求的内部实现，包括 GET 验证和 POST 消息接收。
-
-        Args:
-            req: Quart Request 对象
-        """
         try:
             self.wxcpt = WXBizMsgCrypt(self.Token, self.EnCodingAESKey, '')
+            await self.logger.info(f'{request.method} {request.url} {str(request.args)}')
 
-            if req.method == 'GET':
-                return await self._handle_get_callback(req)
+            if request.method == 'GET':
+                return await self._handle_get_callback()
 
-            if req.method == 'POST':
-                return await self._handle_post_callback(req)
+            if request.method == 'POST':
+                return await self._handle_post_callback()
 
             return Response('', status=405)
 
@@ -407,13 +383,13 @@ class WecomBotClient:
             await self.logger.error(traceback.format_exc())
             return Response('Internal Server Error', status=500)
 
-    async def _handle_get_callback(self, req) -> tuple[Response, int] | Response:
+    async def _handle_get_callback(self) -> tuple[Response, int] | Response:
         """处理企业微信的 GET 验证请求。"""
 
-        msg_signature = unquote(req.args.get('msg_signature', ''))
-        timestamp = unquote(req.args.get('timestamp', ''))
-        nonce = unquote(req.args.get('nonce', ''))
-        echostr = unquote(req.args.get('echostr', ''))
+        msg_signature = unquote(request.args.get('msg_signature', ''))
+        timestamp = unquote(request.args.get('timestamp', ''))
+        nonce = unquote(request.args.get('nonce', ''))
+        echostr = unquote(request.args.get('echostr', ''))
 
         if not all([msg_signature, timestamp, nonce, echostr]):
             await self.logger.error('请求参数缺失')
@@ -426,16 +402,16 @@ class WecomBotClient:
 
         return Response(decrypted_str, mimetype='text/plain')
 
-    async def _handle_post_callback(self, req) -> tuple[Response, int] | Response:
+    async def _handle_post_callback(self) -> tuple[Response, int] | Response:
         """处理企业微信的 POST 回调请求。"""
 
         self.stream_sessions.cleanup()
 
-        msg_signature = unquote(req.args.get('msg_signature', ''))
-        timestamp = unquote(req.args.get('timestamp', ''))
-        nonce = unquote(req.args.get('nonce', ''))
+        msg_signature = unquote(request.args.get('msg_signature', ''))
+        timestamp = unquote(request.args.get('timestamp', ''))
+        nonce = unquote(request.args.get('nonce', ''))
 
-        encrypted_json = await req.get_json()
+        encrypted_json = await request.get_json()
         encrypted_msg = (encrypted_json or {}).get('encrypt', '')
         if not encrypted_msg:
             await self.logger.error("请求体中缺少 'encrypt' 字段")
@@ -457,174 +433,32 @@ class WecomBotClient:
     async def get_message(self, msg_json):
         message_data = {}
 
-        msg_type = msg_json.get('msgtype', '')
-        if msg_type:
-            message_data['msgtype'] = msg_type
-
         if msg_json.get('chattype', '') == 'single':
             message_data['type'] = 'single'
         elif msg_json.get('chattype', '') == 'group':
             message_data['type'] = 'group'
 
-        max_inline_file_size = 5 * 1024 * 1024  # avoid decoding very large payloads by default
-
-        async def _safe_download(url: str):
-            if not url:
-                return None
-            return await self.download_url_to_base64(url, self.EnCodingAESKey)
-
-        if msg_type == 'text':
+        if msg_json.get('msgtype') == 'text':
             message_data['content'] = msg_json.get('text', {}).get('content')
-        elif msg_type == 'markdown':
-            message_data['content'] = msg_json.get('markdown', {}).get('content') or msg_json.get('text', {}).get(
-                'content', ''
-            )
-        elif msg_type == 'image':
+        elif msg_json.get('msgtype') == 'image':
             picurl = msg_json.get('image', {}).get('url', '')
-            base64_data = await _safe_download(picurl)
-            if base64_data:
-                message_data['picurl'] = base64_data
-                message_data['images'] = [base64_data]
-        elif msg_type == 'voice':
-            voice_info = msg_json.get('voice', {}) or {}
-            download_url = voice_info.get('url')
-            message_data['voice'] = {
-                'url': download_url,
-                'md5sum': voice_info.get('md5sum') or voice_info.get('md5'),
-                'filesize': voice_info.get('filesize') or voice_info.get('size'),
-                'sdkfileid': voice_info.get('sdkfileid') or voice_info.get('fileid'),
-            }
-            # 企业微信智能转写文本（如果已有）直接复用，避免重复转写
-            if voice_info.get('content'):
-                message_data['content'] = voice_info.get('content')
-            if (message_data['voice'].get('filesize') or 0) <= max_inline_file_size:
-                voice_base64 = await _safe_download(download_url)
-                if voice_base64:
-                    message_data['voice']['base64'] = voice_base64
-        elif msg_type == 'video':
-            video_info = msg_json.get('video', {}) or {}
-            download_url = video_info.get('url')
-            video_data = {
-                'url': download_url,
-                'filesize': video_info.get('filesize') or video_info.get('size'),
-                'sdkfileid': video_info.get('sdkfileid') or video_info.get('fileid'),
-                'md5sum': video_info.get('md5sum') or video_info.get('md5'),
-                'filename': video_info.get('filename') or video_info.get('name'),
-            }
-            if (video_data.get('filesize') or 0) <= max_inline_file_size:
-                video_base64 = await _safe_download(download_url)
-                if video_base64:
-                    video_data['base64'] = video_base64
-            message_data['video'] = video_data
-        elif msg_type == 'file':
-            file_info = msg_json.get('file', {}) or {}
-            download_url = file_info.get('url') or file_info.get('fileurl')
-            file_data = {
-                'filename': file_info.get('filename') or file_info.get('name'),
-                'filesize': file_info.get('filesize') or file_info.get('size'),
-                'md5sum': file_info.get('md5sum') or file_info.get('md5'),
-                'sdkfileid': file_info.get('sdkfileid') or file_info.get('fileid'),
-                'download_url': download_url,
-                'extra': file_info,
-            }
-            if (file_data.get('filesize') or 0) <= max_inline_file_size:
-                file_base64 = await _safe_download(download_url)
-                if file_base64:
-                    file_data['base64'] = file_base64
-            message_data['file'] = file_data
-        elif msg_type == 'link':
-            message_data['link'] = msg_json.get('link', {})
-            if not message_data.get('content'):
-                title = message_data['link'].get('title', '')
-                desc = message_data['link'].get('description') or message_data['link'].get('digest', '')
-                message_data['content'] = '\n'.join(filter(None, [title, desc]))
-        elif msg_type == 'mixed':
+            base64 = await self.download_url_to_base64(picurl, self.EnCodingAESKey)
+            message_data['picurl'] = base64
+        elif msg_json.get('msgtype') == 'mixed':
             items = msg_json.get('mixed', {}).get('msg_item', [])
             texts = []
-            images = []
-            files = []
-            voices = []
-            videos = []
-            links = []
+            picurl = None
             for item in items:
-                item_type = item.get('msgtype')
-                if item_type == 'text':
+                if item.get('msgtype') == 'text':
                     texts.append(item.get('text', {}).get('content', ''))
-                elif item_type == 'image':
-                    img_url = item.get('image', {}).get('url')
-                    base64_data = await _safe_download(img_url)
-                    if base64_data:
-                        images.append(base64_data)
-                elif item_type == 'file':
-                    file_info = item.get('file', {}) or {}
-                    download_url = file_info.get('url') or file_info.get('fileurl')
-                    file_data = {
-                        'filename': file_info.get('filename') or file_info.get('name'),
-                        'filesize': file_info.get('filesize') or file_info.get('size'),
-                        'md5sum': file_info.get('md5sum') or file_info.get('md5'),
-                        'sdkfileid': file_info.get('sdkfileid') or file_info.get('fileid'),
-                        'download_url': download_url,
-                        'extra': file_info,
-                    }
-                    if (file_data.get('filesize') or 0) <= max_inline_file_size:
-                        file_base64 = await _safe_download(download_url)
-                        if file_base64:
-                            file_data['base64'] = file_base64
-                    files.append(file_data)
-                elif item_type == 'voice':
-                    voice_info = item.get('voice', {}) or {}
-                    download_url = voice_info.get('url')
-                    voice_data = {
-                        'url': download_url,
-                        'md5sum': voice_info.get('md5sum') or voice_info.get('md5'),
-                        'filesize': voice_info.get('filesize') or voice_info.get('size'),
-                        'sdkfileid': voice_info.get('sdkfileid') or voice_info.get('fileid'),
-                    }
-                    if voice_info.get('content'):
-                        texts.append(voice_info.get('content'))
-                    if (voice_data.get('filesize') or 0) <= max_inline_file_size:
-                        voice_base64 = await _safe_download(download_url)
-                        if voice_base64:
-                            voice_data['base64'] = voice_base64
-                    voices.append(voice_data)
-                elif item_type == 'video':
-                    video_info = item.get('video', {}) or {}
-                    download_url = video_info.get('url')
-                    video_data = {
-                        'url': download_url,
-                        'filesize': video_info.get('filesize') or video_info.get('size'),
-                        'sdkfileid': video_info.get('sdkfileid') or video_info.get('fileid'),
-                        'md5sum': video_info.get('md5sum') or video_info.get('md5'),
-                        'filename': video_info.get('filename') or video_info.get('name'),
-                    }
-                    if (video_data.get('filesize') or 0) <= max_inline_file_size:
-                        video_base64 = await _safe_download(download_url)
-                        if video_base64:
-                            video_data['base64'] = video_base64
-                    videos.append(video_data)
-                elif item_type == 'link':
-                    links.append(item.get('link', {}))
+                elif item.get('msgtype') == 'image' and picurl is None:
+                    picurl = item.get('image', {}).get('url')
 
             if texts:
-                message_data['content'] = ' '.join(texts)  # 拼接所有 text
-            if images:
-                message_data['images'] = images
-                message_data['picurl'] = images[0]  # 只保留第一个 image
-            if files:
-                message_data['files'] = files
-                message_data['file'] = files[0]
-            if voices:
-                message_data['voices'] = voices
-                message_data['voice'] = voices[0]
-            if videos:
-                message_data['videos'] = videos
-                message_data['video'] = videos[0]
-            if links:
-                message_data['link'] = links[0]
-            if items:
-                message_data['attachments'] = items
-        else:
-            message_data['raw_msg'] = msg_json
+                message_data['content'] = ''.join(texts)  # 拼接所有 text
+            if picurl:
+                base64 = await self.download_url_to_base64(picurl, self.EnCodingAESKey)
+                message_data['picurl'] = base64  # 只保留第一个 image
 
         # Extract user information
         from_info = msg_json.get('from', {})

src/langbot/libs/wecom_ai_bot_api/wecombotevent.py

@@ -17,13 +17,6 @@ class WecomBotEvent(dict):
         """
         return self.get('type', '')
 
-    @property
-    def msgtype(self) -> str:
-        """
-        消息 msgtype
-        """
-        return self.get('msgtype', '')
-
     @property
     def userid(self) -> str:
         """
@@ -64,55 +57,6 @@ class WecomBotEvent(dict):
         """
         return self.get('picurl', '')
 
-    @property
-    def images(self):
-        """
-        图片列表（兼容 mixed）
-        """
-        return self.get('images', [])
-
-    @property
-    def file(self):
-        """
-        文件信息
-        """
-        return self.get('file', {})
-
-    @property
-    def voice(self):
-        """
-        语音信息
-        """
-        return self.get('voice', {})
-
-    @property
-    def video(self):
-        """
-        视频信息
-        """
-        return self.get('video', {})
-
-    @property
-    def link(self):
-        """
-        链接消息信息
-        """
-        return self.get('link', {})
-
-    @property
-    def location(self):
-        """
-        位置信息
-        """
-        return self.get('location', {})
-
-    @property
-    def attachments(self):
-        """
-        原始 mixed 中的附件项
-        """
-        return self.get('attachments', [])
-
     @property
     def chatid(self) -> str:
         """

src/langbot/libs/wecom_api/api.py

@@ -21,30 +21,23 @@ class WecomClient:
         EncodingAESKey: str,
         contacts_secret: str,
         logger: None,
-        unified_mode: bool = False,
-        api_base_url: str = 'https://qyapi.weixin.qq.com/cgi-bin',
     ):
         self.corpid = corpid
         self.secret = secret
         self.access_token_for_contacts = ''
         self.token = token
         self.aes = EncodingAESKey
-        self.base_url = api_base_url
+        self.base_url = 'https://qyapi.weixin.qq.com/cgi-bin'
         self.access_token = ''
         self.secret_for_contacts = contacts_secret
         self.logger = logger
-        self.unified_mode = unified_mode
         self.app = Quart(__name__)
-
-        # 只有在非统一模式下才注册独立路由
-        if not self.unified_mode:
-            self.app.add_url_rule(
-                '/callback/command',
-                'handle_callback',
-                self.handle_callback_request,
-                methods=['GET', 'POST'],
-            )
-
+        self.app.add_url_rule(
+            '/callback/command',
+            'handle_callback',
+            self.handle_callback_request,
+            methods=['GET', 'POST'],
+        )
         self._message_handlers = {
             'example': [],
         }
@@ -57,7 +50,7 @@ class WecomClient:
         return bool(self.access_token_for_contacts and self.access_token_for_contacts.strip())
 
     async def get_access_token(self, secret):
-        url = f'{self.base_url}/gettoken?corpid={self.corpid}&corpsecret={secret}'
+        url = f'https://qyapi.weixin.qq.com/cgi-bin/gettoken?corpid={self.corpid}&corpsecret={secret}'
         async with httpx.AsyncClient() as client:
             response = await client.get(url)
             data = response.json()
@@ -140,64 +133,12 @@ class WecomClient:
                 await self.logger.error(f'发送图片失败:{data}')
                 raise Exception('Failed to send image: ' + str(data))
 
-    async def send_voice(self, user_id: str, agent_id: int, media_id: str):
-        if not await self.check_access_token():
-            self.access_token = await self.get_access_token(self.secret)
-        url = self.base_url + '/message/send?access_token=' + self.access_token
-        async with httpx.AsyncClient() as client:
-            params = {
-                'touser': user_id,
-                'msgtype': 'voice',
-                'agentid': agent_id,
-                'voice': {
-                    'media_id': media_id,
-                },
-                'safe': 0,
-                'enable_id_trans': 0,
-                'enable_duplicate_check': 0,
-                'duplicate_check_interval': 1800,
-            }
-            response = await client.post(url, json=params)
-            data = response.json()
-            if data['errcode'] == 40014 or data['errcode'] == 42001:
-                self.access_token = await self.get_access_token(self.secret)
-                return await self.send_voice(user_id, agent_id, media_id)
-            if data['errcode'] != 0:
-                await self.logger.error(f'发送语音失败:{data}')
-                raise Exception('Failed to send voice: ' + str(data))
-
-    async def send_file(self, user_id: str, agent_id: int, media_id: str):
-        if not await self.check_access_token():
-            self.access_token = await self.get_access_token(self.secret)
-        url = self.base_url + '/message/send?access_token=' + self.access_token
-        async with httpx.AsyncClient() as client:
-            params = {
-                'touser': user_id,
-                'msgtype': 'file',
-                'agentid': agent_id,
-                'file': {
-                    'media_id': media_id,
-                },
-                'safe': 0,
-                'enable_id_trans': 0,
-                'enable_duplicate_check': 0,
-                'duplicate_check_interval': 1800,
-            }
-            response = await client.post(url, json=params)
-            data = response.json()
-            if data['errcode'] == 40014 or data['errcode'] == 42001:
-                self.access_token = await self.get_access_token(self.secret)
-                return await self.send_file(user_id, agent_id, media_id)
-            if data['errcode'] != 0:
-                await self.logger.error(f'发送文件失败:{data}')
-                raise Exception('Failed to send file: ' + str(data))
-
     async def send_private_msg(self, user_id: str, agent_id: int, content: str):
         if not await self.check_access_token():
             self.access_token = await self.get_access_token(self.secret)
 
         url = self.base_url + '/message/send?access_token=' + self.access_token
-        async with httpx.AsyncClient(timeout=None) as client:
+        async with httpx.AsyncClient() as client:
             params = {
                 'touser': user_id,
                 'msgtype': 'text',
@@ -220,43 +161,25 @@ class WecomClient:
                 raise Exception('Failed to send message: ' + str(data))
 
     async def handle_callback_request(self):
-        """处理回调请求（独立端口模式，使用全局 request）。"""
-        return await self._handle_callback_internal(request)
-
-    async def handle_unified_webhook(self, req):
-        """处理回调请求（统一 webhook 模式，显式传递 request）。
-
-        Args:
-            req: Quart Request 对象
-
-        Returns:
-            响应数据
         """
-        return await self._handle_callback_internal(req)
-
-    async def _handle_callback_internal(self, req):
-        """
-        处理回调请求的内部实现，包括 GET 验证和 POST 消息接收。
-
-        Args:
-            req: Quart Request 对象
+        处理回调请求，包括 GET 验证和 POST 消息接收。
         """
         try:
-            msg_signature = req.args.get('msg_signature')
-            timestamp = req.args.get('timestamp')
-            nonce = req.args.get('nonce')
+            msg_signature = request.args.get('msg_signature')
+            timestamp = request.args.get('timestamp')
+            nonce = request.args.get('nonce')
 
             wxcpt = WXBizMsgCrypt(self.token, self.aes, self.corpid)
-            if req.method == 'GET':
-                echostr = req.args.get('echostr')
+            if request.method == 'GET':
+                echostr = request.args.get('echostr')
                 ret, reply_echo_str = wxcpt.VerifyURL(msg_signature, timestamp, nonce, echostr)
                 if ret != 0:
                     await self.logger.error('验证失败')
                     raise Exception(f'验证失败，错误码: {ret}')
                 return reply_echo_str
 
-            elif req.method == 'POST':
-                encrypt_msg = await req.data
+            elif request.method == 'POST':
+                encrypt_msg = await request.data
                 ret, xml_msg = wxcpt.DecryptMsg(encrypt_msg, msg_signature, timestamp, nonce)
                 if ret != 0:
                     await self.logger.error('消息解密失败')
@@ -340,7 +263,7 @@ class WecomClient:
                 return ext
         return 'jpg'  # 默认返回jpg
 
-    async def upload_image_to_work(self, image: platform_message.Image):
+    async def upload_to_work(self, image: platform_message.Image):
         """
         获取 media_id
         """
@@ -357,7 +280,7 @@ class WecomClient:
                 file_bytes = await f.read()
                 file_name = image.path.split('/')[-1]
         elif image.url:
-            file_bytes = await self.download_media_to_bytes(image.url)
+            file_bytes = await self.download_image_to_bytes(image.url)
             file_name = image.url.split('/')[-1]
         elif image.base64:
             try:
@@ -392,7 +315,7 @@ class WecomClient:
             data = response.json()
             if data['errcode'] == 40014 or data['errcode'] == 42001:
                 self.access_token = await self.get_access_token(self.secret)
-                media_id = await self.upload_image_to_work(image)
+                media_id = await self.upload_to_work(image)
             if data.get('errcode', 0) != 0:
                 await self.logger.error(f'上传图片失败:{data}')
                 raise Exception('failed to upload file')
@@ -400,128 +323,13 @@ class WecomClient:
             media_id = data.get('media_id')
             return media_id
 
-    async def upload_voice_to_work(self, voice: platform_message.Voice):
-        """
-        上传语音文件到企业微信
-        """
-        if not await self.check_access_token():
-            self.access_token = await self.get_access_token(self.secret)
-        url = self.base_url + '/media/upload?access_token=' + self.access_token + '&type=file'
-        file_bytes = None
-        file_name = 'voice.mp3'
-
-        if voice.path:
-            async with aiofiles.open(voice.path, 'rb') as f:
-                file_bytes = await f.read()
-                file_name = voice.path.split('/')[-1]
-        elif voice.url:
-            file_bytes = await self.download_media_to_bytes(voice.url)
-            file_name = voice.url.split('/')[-1]
-        elif voice.base64:
-            try:
-                base64_data = voice.base64
-                if ',' in base64_data:
-                    base64_data = base64_data.split(',', 1)[1]
-                padding = 4 - (len(base64_data) % 4) if len(base64_data) % 4 else 0
-                padded_base64 = base64_data + '=' * padding
-                file_bytes = base64.b64decode(padded_base64)
-            except binascii.Error as e:
-                raise ValueError(f'Invalid base64 string: {str(e)}')
-        else:
-            await self.logger.error('Voice对象出错')
-            raise ValueError('voice对象出错')
-
-        boundary = '-------------------------acebdf13572468'
-        headers = {'Content-Type': f'multipart/form-data; boundary={boundary}'}
-        body = (
-            (
-                f'--{boundary}\r\n'
-                f'Content-Disposition: form-data; name="media"; filename="{file_name}"; filelength={len(file_bytes)}\r\n'
-                f'Content-Type: application/octet-stream\r\n\r\n'
-            ).encode('utf-8')
-            + file_bytes
-            + f'\r\n--{boundary}--\r\n'.encode('utf-8')
-        )
-
-        # print(body)
-        async with httpx.AsyncClient() as client:
-            response = await client.post(url, headers=headers, content=body)
-            data = response.json()
-            if data['errcode'] == 40014 or data['errcode'] == 42001:
-                self.access_token = await self.get_access_token(self.secret)
-                media_id = await self.upload_voice_to_work(voice)
-            if data.get('errcode', 0) != 0:
-                await self.logger.error(f'上传语音文件失败:{data}')
-                raise Exception('failed to upload file')
-            media_id = data.get('media_id')
-            return media_id
-
-    async def upload_file_to_work(self, file: platform_message.File):
-        """
-        上传文件到企业微信
-        """
-        if not await self.check_access_token():
-            self.access_token = await self.get_access_token(self.secret)
-        url = self.base_url + '/media/upload?access_token=' + self.access_token + '&type=file'
-        file_bytes = None
-        file_name = 'file.txt'
-        if file.path:
-            async with aiofiles.open(file.path, 'rb') as f:
-                file_bytes = await f.read()
-                file_name = file.path.split('/')[-1]
-        elif file.url:
-            file_bytes = await self.download_media_to_bytes(file.url)
-            file_name = file.url.split('/')[-1]
-        elif file.base64:
-            try:
-                base64_data = file.base64
-                if ',' in base64_data:
-                    base64_data = base64_data.split(',', 1)[1]
-                padding = 4 - (len(base64_data) % 4) if len(base64_data) % 4 else 0
-                padded_base64 = base64_data + '=' * padding
-                file_bytes = base64.b64decode(padded_base64)
-            except binascii.Error as e:
-                raise ValueError(f'Invalid base64 string: {str(e)}')
-        else:
-            await self.logger.error('File对象出错')
-            raise ValueError('file对象出错')
-        boundary = '-------------------------acebdf13572468'
-        headers = {'Content-Type': f'multipart/form-data; boundary={boundary}'}
-        body = (
-            (
-                f'--{boundary}\r\n'
-                f'Content-Disposition: form-data; name="media"; filename="{file_name}"; filelength={len(file_bytes)}\r\n'
-                f'Content-Type: application/octet-stream\r\n\r\n'
-            ).encode('utf-8')
-            + file_bytes
-            + f'\r\n--{boundary}--\r\n'.encode('utf-8')
-        )
-        async with httpx.AsyncClient() as client:
-            response = await client.post(url, headers=headers, content=body)
-            data = response.json()
-            if data['errcode'] == 40014 or data['errcode'] == 42001:
-                self.access_token = await self.get_access_token(self.secret)
-                media_id = await self.upload_file_to_work(file)
-            if data.get('errcode', 0) != 0:
-                await self.logger.error(f'上传文件失败:{data}')
-                raise Exception('failed to upload file')
-            media_id = data.get('media_id')
-            return media_id
-
-    async def download_media_to_bytes(self, url: str) -> bytes:
+    async def download_image_to_bytes(self, url: str) -> bytes:
         async with httpx.AsyncClient() as client:
             response = await client.get(url)
             response.raise_for_status()
             return response.content
 
     # 进行media_id的获取
-    async def get_media_id(self, media: platform_message.Image | platform_message.Voice | platform_message.File):
-        if isinstance(media, platform_message.Image):
-            media_id = await self.upload_image_to_work(image=media)
-        elif isinstance(media, platform_message.Voice):
-            media_id = await self.upload_voice_to_work(voice=media)
-        elif isinstance(media, platform_message.File):
-            media_id = await self.upload_file_to_work(file=media)
-        else:
-            raise ValueError('Unsupported media type')
+    async def get_media_id(self, image: platform_message.Image):
+        media_id = await self.upload_to_work(image=image)
         return media_id

src/langbot/libs/wecom_customer_service_api/api.py

@@ -10,41 +10,22 @@ from typing import Callable
 from .wecomcsevent import WecomCSEvent
 import langbot_plugin.api.entities.builtin.platform.message as platform_message
 import aiofiles
-import time
 
 
 class WecomCSClient:
-    def __init__(
-        self,
-        corpid: str,
-        secret: str,
-        token: str,
-        EncodingAESKey: str,
-        logger: None,
-        unified_mode: bool = False,
-        api_base_url: str = 'https://qyapi.weixin.qq.com/cgi-bin',
-    ):
+    def __init__(self, corpid: str, secret: str, token: str, EncodingAESKey: str, logger: None):
         self.corpid = corpid
         self.secret = secret
         self.access_token_for_contacts = ''
         self.token = token
         self.aes = EncodingAESKey
-        self.base_url = api_base_url
+        self.base_url = 'https://qyapi.weixin.qq.com/cgi-bin'
         self.access_token = ''
         self.logger = logger
-        self.unified_mode = unified_mode
         self.app = Quart(__name__)
-
-        # Customer info cache: {external_userid: (info_dict, timestamp)}
-        self._customer_cache: dict[str, tuple[dict, float]] = {}
-        self._cache_ttl = 60  # Cache TTL in seconds (1 minute)
-
-        # 只有在非统一模式下才注册独立路由
-        if not self.unified_mode:
-            self.app.add_url_rule(
-                '/callback/command', 'handle_callback', self.handle_callback_request, methods=['GET', 'POST']
-            )
-
+        self.app.add_url_rule(
+            '/callback/command', 'handle_callback', self.handle_callback_request, methods=['GET', 'POST']
+        )
         self._message_handlers = {
             'example': [],
         }
@@ -80,7 +61,7 @@ class WecomCSClient:
         return bool(self.access_token_for_contacts and self.access_token_for_contacts.strip())
 
     async def get_access_token(self, secret):
-        url = f'{self.base_url}/gettoken?corpid={self.corpid}&corpsecret={secret}'
+        url = f'https://qyapi.weixin.qq.com/cgi-bin/gettoken?corpid={self.corpid}&corpsecret={secret}'
         async with httpx.AsyncClient() as client:
             response = await client.get(url)
             data = response.json()
@@ -186,7 +167,7 @@ class WecomCSClient:
         if not await self.check_access_token():
             self.access_token = await self.get_access_token(self.secret)
 
-        url = f'{self.base_url}/kf/send_msg?access_token={self.access_token}'
+        url = f'https://qyapi.weixin.qq.com/cgi-bin/kf/send_msg?access_token={self.access_token}'
 
         payload = {
             'touser': external_userid,
@@ -211,45 +192,27 @@ class WecomCSClient:
             return data
 
     async def handle_callback_request(self):
-        """处理回调请求（独立端口模式，使用全局 request）。"""
-        return await self._handle_callback_internal(request)
-
-    async def handle_unified_webhook(self, req):
-        """处理回调请求（统一 webhook 模式，显式传递 request）。
-
-        Args:
-            req: Quart Request 对象
-
-        Returns:
-            响应数据
         """
-        return await self._handle_callback_internal(req)
-
-    async def _handle_callback_internal(self, req):
-        """
-        处理回调请求的内部实现，包括 GET 验证和 POST 消息接收。
-
-        Args:
-            req: Quart Request 对象
+        处理回调请求，包括 GET 验证和 POST 消息接收。
         """
         try:
-            msg_signature = req.args.get('msg_signature')
-            timestamp = req.args.get('timestamp')
-            nonce = req.args.get('nonce')
+            msg_signature = request.args.get('msg_signature')
+            timestamp = request.args.get('timestamp')
+            nonce = request.args.get('nonce')
             try:
                 wxcpt = WXBizMsgCrypt(self.token, self.aes, self.corpid)
             except Exception as e:
                 raise Exception(f'初始化失败，错误码: {e}')
 
-            if req.method == 'GET':
-                echostr = req.args.get('echostr')
+            if request.method == 'GET':
+                echostr = request.args.get('echostr')
                 ret, reply_echo_str = wxcpt.VerifyURL(msg_signature, timestamp, nonce, echostr)
                 if ret != 0:
                     raise Exception(f'验证失败，错误码: {ret}')
                 return reply_echo_str
 
-            elif req.method == 'POST':
-                encrypt_msg = await req.data
+            elif request.method == 'POST':
+                encrypt_msg = await request.data
                 ret, xml_msg = wxcpt.DecryptMsg(encrypt_msg, msg_signature, timestamp, nonce)
                 if ret != 0:
                     raise Exception(f'消息解密失败，错误码: {ret}')
@@ -383,53 +346,3 @@ class WecomCSClient:
     async def get_media_id(self, image: platform_message.Image):
         media_id = await self.upload_to_work(image=image)
         return media_id
-
-    async def get_customer_info(self, external_userid: str) -> dict | None:
-        """
-        Get customer information by external_userid with caching.
-
-        Uses a 1-minute cache to avoid repeated API calls for the same user.
-
-        Args:
-            external_userid: The external user ID of the customer.
-
-        Returns:
-            Customer info dict with 'nickname', 'avatar', etc., or None if not found.
-        """
-        # Check cache first
-        current_time = time.time()
-        if external_userid in self._customer_cache:
-            cached_info, cached_time = self._customer_cache[external_userid]
-            if current_time - cached_time < self._cache_ttl:
-                return cached_info
-
-        # Cache miss or expired, fetch from API
-        if not await self.check_access_token():
-            self.access_token = await self.get_access_token(self.secret)
-
-        url = f'{self.base_url}/kf/customer/batchget?access_token={self.access_token}'
-
-        payload = {
-            'external_userid_list': [external_userid],
-        }
-
-        async with httpx.AsyncClient() as client:
-            response = await client.post(url, json=payload)
-            data = response.json()
-
-            if data.get('errcode') in [40014, 42001]:
-                self.access_token = await self.get_access_token(self.secret)
-                return await self.get_customer_info(external_userid)
-
-            if data.get('errcode', 0) != 0:
-                if self.logger:
-                    await self.logger.warning(f'Failed to get customer info: {data}')
-                return None
-
-            customer_list = data.get('customer_list', [])
-            if customer_list:
-                customer_info = customer_list[0]
-                # Store in cache
-                self._customer_cache[external_userid] = (customer_info, current_time)
-                return customer_info
-            return None

src/langbot/pkg/api/http/controller/groups/knowledge/base.py

@@ -13,10 +13,7 @@ class KnowledgeBaseRouterGroup(group.RouterGroup):
 
             elif quart.request.method == 'POST':
                 json_data = await quart.request.json
-                try:
-                    knowledge_base_uuid = await self.ap.knowledge_service.create_knowledge_base(json_data)
-                except ValueError as e:
-                    return self.http_status(400, -1, str(e))
+                knowledge_base_uuid = await self.ap.knowledge_service.create_knowledge_base(json_data)
                 return self.success(data={'uuid': knowledge_base_uuid})
 
             return self.http_status(405, -1, 'Method not allowed')
@@ -42,7 +39,7 @@ class KnowledgeBaseRouterGroup(group.RouterGroup):
             elif quart.request.method == 'PUT':
                 json_data = await quart.request.json
                 await self.ap.knowledge_service.update_knowledge_base(knowledge_base_uuid, json_data)
-                return self.success(data={'uuid': knowledge_base_uuid})
+                return self.success({})
 
             elif quart.request.method == 'DELETE':
                 await self.ap.knowledge_service.delete_knowledge_base(knowledge_base_uuid)
@@ -68,12 +65,8 @@ class KnowledgeBaseRouterGroup(group.RouterGroup):
                 if not file_id:
                     return self.http_status(400, -1, 'File ID is required')
 
-                parser_plugin_id = json_data.get('parser_plugin_id')
-
                 # 调用服务层方法将文件与知识库关联
-                task_id = await self.ap.knowledge_service.store_file(
-                    knowledge_base_uuid, file_id, parser_plugin_id=parser_plugin_id
-                )
+                task_id = await self.ap.knowledge_service.store_file(knowledge_base_uuid, file_id)
                 return self.success(
                     {
                         'task_id': task_id,
@@ -97,13 +90,5 @@ class KnowledgeBaseRouterGroup(group.RouterGroup):
         async def retrieve_knowledge_base(knowledge_base_uuid: str) -> str:
             json_data = await quart.request.json
             query = json_data.get('query')
-
-            if not query or not query.strip():
-                return self.http_status(400, -1, 'Query is required and cannot be empty')
-
-            # Extract retrieval_settings to allow dynamic control over Knowledge Engine behavior (e.g. top_k, filters)
-            retrieval_settings = json_data.get('retrieval_settings', {})
-            results = await self.ap.knowledge_service.retrieve_knowledge_base(
-                knowledge_base_uuid, query, retrieval_settings
-            )
+            results = await self.ap.knowledge_service.retrieve_knowledge_base(knowledge_base_uuid, query)
             return self.success(data={'results': results})

src/langbot/pkg/api/http/controller/groups/knowledge/engines.py

@@ -1,45 +0,0 @@
-import quart
-from urllib.parse import unquote
-from ... import group
-
-
-@group.group_class('knowledge_engines', '/api/v1/knowledge/engines')
-class KnowledgeEnginesRouterGroup(group.RouterGroup):
-    async def initialize(self) -> None:
-        @self.route('', methods=['GET'], auth_type=group.AuthType.USER_TOKEN_OR_API_KEY)
-        async def list_knowledge_engines() -> quart.Response:
-            """List all available Knowledge Engines from plugins.
-
-            Returns a list of Knowledge Engines with their capabilities and configuration schemas.
-            This is used by the frontend to render the knowledge base creation wizard.
-            """
-            engines = await self.ap.knowledge_service.list_knowledge_engines()
-            return self.success(data={'engines': engines})
-
-        @self.route(
-            '/<path:plugin_id>/creation-schema', methods=['GET'], auth_type=group.AuthType.USER_TOKEN_OR_API_KEY
-        )
-        async def get_engine_creation_schema(plugin_id: str) -> quart.Response:
-            """Get creation settings schema for a specific Knowledge Engine.
-
-            plugin_id is in 'author/name' format, captured via <path:> converter.
-            """
-            plugin_id = unquote(plugin_id)
-            if '/' not in plugin_id:
-                return self.http_status(400, -1, 'Invalid plugin_id format. Expected author/name.')
-            schema = await self.ap.knowledge_service.get_engine_creation_schema(plugin_id)
-            return self.success(data={'schema': schema})
-
-        @self.route(
-            '/<path:plugin_id>/retrieval-schema', methods=['GET'], auth_type=group.AuthType.USER_TOKEN_OR_API_KEY
-        )
-        async def get_engine_retrieval_schema(plugin_id: str) -> quart.Response:
-            """Get retrieval settings schema for a specific Knowledge Engine.
-
-            plugin_id is in 'author/name' format, captured via <path:> converter.
-            """
-            plugin_id = unquote(plugin_id)
-            if '/' not in plugin_id:
-                return self.http_status(400, -1, 'Invalid plugin_id format. Expected author/name.')
-            schema = await self.ap.knowledge_service.get_engine_retrieval_schema(plugin_id)
-            return self.success(data={'schema': schema})

src/langbot/pkg/api/http/controller/groups/knowledge/external.py

@@ -0,0 +1,61 @@
+import quart
+from ... import group
+
+
+@group.group_class('external_knowledge_base', '/api/v1/knowledge/external-bases')
+class ExternalKnowledgeBaseRouterGroup(group.RouterGroup):
+    async def initialize(self) -> None:
+        @self.route('/retrievers', methods=['GET'])
+        async def list_knowledge_retrievers() -> quart.Response:
+            """List all available knowledge retrievers from plugins."""
+            retrievers = await self.ap.plugin_connector.list_knowledge_retrievers()
+            return self.success(data={'retrievers': retrievers})
+
+        @self.route('', methods=['POST', 'GET'])
+        async def handle_external_knowledge_bases() -> quart.Response:
+            if quart.request.method == 'GET':
+                external_kbs = await self.ap.external_kb_service.get_external_knowledge_bases()
+                return self.success(data={'bases': external_kbs})
+
+            elif quart.request.method == 'POST':
+                json_data = await quart.request.json
+                kb_uuid = await self.ap.external_kb_service.create_external_knowledge_base(json_data)
+                return self.success(data={'uuid': kb_uuid})
+
+            return self.http_status(405, -1, 'Method not allowed')
+
+        @self.route(
+            '/<kb_uuid>',
+            methods=['GET', 'DELETE', 'PUT'],
+        )
+        async def handle_specific_external_knowledge_base(kb_uuid: str) -> quart.Response:
+            if quart.request.method == 'GET':
+                external_kb = await self.ap.external_kb_service.get_external_knowledge_base(kb_uuid)
+
+                if external_kb is None:
+                    return self.http_status(404, -1, 'external knowledge base not found')
+
+                return self.success(
+                    data={
+                        'base': external_kb,
+                    }
+                )
+
+            elif quart.request.method == 'PUT':
+                json_data = await quart.request.json
+                await self.ap.external_kb_service.update_external_knowledge_base(kb_uuid, json_data)
+                return self.success({})
+
+            elif quart.request.method == 'DELETE':
+                await self.ap.external_kb_service.delete_external_knowledge_base(kb_uuid)
+                return self.success({})
+
+        @self.route(
+            '/<kb_uuid>/retrieve',
+            methods=['POST'],
+        )
+        async def retrieve_external_knowledge_base(kb_uuid: str) -> str:
+            json_data = await quart.request.json
+            query = json_data.get('query')
+            results = await self.ap.external_kb_service.retrieve_external_knowledge_base(kb_uuid, query)
+            return self.success(data={'results': results})

src/langbot/pkg/api/http/controller/groups/knowledge/migration.py

@@ -1,372 +0,0 @@
-import asyncio
-import json
-
-import httpx
-import quart
-import sqlalchemy
-
-from ... import group
-from ......core import taskmgr
-from ......entity.persistence import metadata as persistence_metadata
-from langbot_plugin.runtime.plugin.mgr import PluginInstallSource
-
-LANGRAG_PLUGIN_AUTHOR = 'langbot-team'
-LANGRAG_PLUGIN_NAME = 'LangRAG'
-LANGRAG_PLUGIN_ID = f'{LANGRAG_PLUGIN_AUTHOR}/{LANGRAG_PLUGIN_NAME}'
-DEFAULT_SPACE_URL = 'https://space.langbot.app'
-
-# Old Retriever plugin_name -> New Connector plugin_name
-EXTERNAL_PLUGIN_NAME_MAPPING = {
-    'DifyDatasetsRetriever': 'DifyDatasetsConnector',
-    'RAGFlowRetriever': 'RAGFlowConnector',
-    'FastGPTRetriever': 'FastGPTConnector',
-}
-
-# Per-plugin: which old retriever_config fields belong to creation_settings.
-# Remaining fields go to retrieval_settings.
-# None means ALL fields go to creation_settings (no retrieval_schema).
-EXTERNAL_PLUGIN_CREATION_FIELDS: dict[str, set[str] | None] = {
-    'langbot-team/DifyDatasetsConnector': {'api_base_url', 'dify_apikey', 'dataset_id'},
-    'langbot-team/RAGFlowConnector': {'api_base_url', 'api_key', 'dataset_ids'},
-    'langbot-team/FastGPTConnector': None,  # all fields -> creation_settings
-}
-
-
-@group.group_class('knowledge/migration', '/api/v1/knowledge/migration')
-class KnowledgeMigrationRouterGroup(group.RouterGroup):
-    async def _get_migration_flag(self) -> bool:
-        """Check if rag_plugin_migration_needed flag is set."""
-        result = await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.select(persistence_metadata.Metadata).where(
-                persistence_metadata.Metadata.key == 'rag_plugin_migration_needed'
-            )
-        )
-        row = result.first()
-        return row is not None and row.value == 'true'
-
-    async def _set_migration_flag(self, value: str):
-        """Set rag_plugin_migration_needed flag."""
-        await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.update(persistence_metadata.Metadata)
-            .where(persistence_metadata.Metadata.key == 'rag_plugin_migration_needed')
-            .values(value=value)
-        )
-
-    async def _table_exists(self, table_name: str) -> bool:
-        """Check if a table exists."""
-        if self.ap.persistence_mgr.db.name == 'postgresql':
-            result = await self.ap.persistence_mgr.execute_async(
-                sqlalchemy.text(
-                    'SELECT EXISTS (SELECT FROM information_schema.tables WHERE table_name = :table_name);'
-                ).bindparams(table_name=table_name)
-            )
-            return result.scalar()
-        else:
-            result = await self.ap.persistence_mgr.execute_async(
-                sqlalchemy.text("SELECT name FROM sqlite_master WHERE type='table' AND name=:table_name;").bindparams(
-                    table_name=table_name
-                )
-            )
-            return result.first() is not None
-
-    async def _install_plugin_from_marketplace(
-        self, plugin_id: str, task_context: taskmgr.TaskContext, space_url: str
-    ) -> None:
-        """Install a single plugin from the marketplace."""
-        p_author, p_name = plugin_id.split('/', 1)
-        self.ap.logger.info(f'RAG migration: installing plugin {plugin_id} from marketplace...')
-        task_context.trace(f'Installing plugin {plugin_id} from marketplace...')
-
-        async with httpx.AsyncClient(trust_env=True, timeout=15) as client:
-            resp = await client.get(f'{space_url}/api/v1/marketplace/plugins/{p_author}/{p_name}')
-            resp.raise_for_status()
-            p_data = resp.json().get('data', {}).get('plugin', {})
-            p_version = p_data.get('latest_version')
-            if not p_version:
-                raise Exception(f'Could not determine latest version for {plugin_id}')
-
-        await self.ap.plugin_connector.install_plugin(
-            PluginInstallSource.MARKETPLACE,
-            {
-                'plugin_author': p_author,
-                'plugin_name': p_name,
-                'plugin_version': p_version,
-            },
-            task_context=task_context,
-        )
-        self.ap.logger.info(f'RAG migration: plugin {plugin_id} install request sent.')
-
-    async def _execute_rag_migration(self, task_context: taskmgr.TaskContext, install_plugin: bool = True):
-        """Execute RAG migration: install required plugins and restore backup data."""
-        warnings = []
-
-        # Collect all plugins we need: LangRAG (always) + connector plugins (from external KBs)
-        needed_plugins: dict[str, str] = {
-            LANGRAG_PLUGIN_ID: LANGRAG_PLUGIN_NAME,
-        }
-
-        has_external = await self._table_exists('external_knowledge_bases')
-        if has_external:
-            result = await self.ap.persistence_mgr.execute_async(
-                sqlalchemy.text('SELECT DISTINCT plugin_author, plugin_name FROM external_knowledge_bases;')
-            )
-            for row in result.fetchall():
-                plugin_author = row[0] or ''
-                plugin_name = row[1] or ''
-                mapped_name = EXTERNAL_PLUGIN_NAME_MAPPING.get(plugin_name, plugin_name)
-                plugin_id = f'{plugin_author}/{mapped_name}'
-                if plugin_id not in needed_plugins:
-                    needed_plugins[plugin_id] = mapped_name
-
-        self.ap.logger.info(f'RAG migration: plugins needed: {list(needed_plugins.keys())}')
-
-        if install_plugin:
-            # Step 1: Install all required plugins from marketplace
-            task_context.trace('Installing required plugins...', action='install-plugin')
-            space_url = self.ap.instance_config.data.get('space', {}).get('url', DEFAULT_SPACE_URL).rstrip('/')
-
-            for plugin_id in needed_plugins:
-                try:
-                    await self._install_plugin_from_marketplace(plugin_id, task_context, space_url)
-                except Exception as e:
-                    self.ap.logger.warning(f'RAG migration: plugin {plugin_id} install returned: {e}')
-                    task_context.trace(f'Plugin install note ({plugin_id}): {e}')
-
-            # Step 2: Wait for all plugins to become available as knowledge engines
-            task_context.trace(
-                f'Waiting for plugins to become available: {list(needed_plugins.keys())}...',
-                action='wait-plugin',
-            )
-            max_retries = 30
-            engine_id_set: set[str] = set()
-            for i in range(max_retries):
-                try:
-                    engines = await self.ap.plugin_connector.list_knowledge_engines()
-                    engine_id_set = {e.get('plugin_id') for e in engines}
-                except Exception:
-                    pass
-                if all(pid in engine_id_set for pid in needed_plugins):
-                    self.ap.logger.info(f'RAG migration: all plugins ready: {engine_id_set}')
-                    task_context.trace('All required plugins are ready.')
-                    break
-                if i == max_retries - 1:
-                    still_missing = [pid for pid in needed_plugins if pid not in engine_id_set]
-                    warning = f'Plugin(s) {still_missing} did not become available after {max_retries} retries'
-                    self.ap.logger.warning(f'RAG migration: {warning}')
-                    warnings.append(warning)
-                    task_context.trace(warning)
-                await asyncio.sleep(2)
-        else:
-            try:
-                engines = await self.ap.plugin_connector.list_knowledge_engines()
-                engine_id_set = {e.get('plugin_id') for e in engines}
-            except Exception:
-                engine_id_set = set()
-
-        # Step 3: Restore internal knowledge bases from backup
-        task_context.trace('Restoring internal knowledge bases...', action='restore-internal')
-        if await self._table_exists('knowledge_bases_backup'):
-            result = await self.ap.persistence_mgr.execute_async(
-                sqlalchemy.text('SELECT * FROM knowledge_bases_backup;')
-            )
-            rows = result.fetchall()
-            columns = result.keys()
-
-            for row in rows:
-                row_dict = dict(zip(columns, row))
-                kb_uuid = row_dict.get('uuid')
-                name = row_dict.get('name', 'Untitled')
-                description = row_dict.get('description', '')
-                emoji = row_dict.get('emoji', '\U0001f4da')
-                embedding_model_uuid = row_dict.get('embedding_model_uuid', '')
-                top_k = row_dict.get('top_k', 5)
-                created_at = row_dict.get('created_at')
-                updated_at = row_dict.get('updated_at')
-
-                creation_settings = json.dumps({'embedding_model_uuid': embedding_model_uuid})
-                retrieval_settings = json.dumps({'top_k': top_k})
-
-                await self.ap.persistence_mgr.execute_async(
-                    sqlalchemy.text(
-                        'INSERT INTO knowledge_bases '
-                        '(uuid, name, description, emoji, created_at, updated_at, '
-                        'knowledge_engine_plugin_id, collection_id, creation_settings, retrieval_settings) '
-                        'VALUES (:uuid, :name, :description, :emoji, :created_at, :updated_at, '
-                        ':plugin_id, :collection_id, :creation_settings, :retrieval_settings);'
-                    ).bindparams(
-                        uuid=kb_uuid,
-                        name=name,
-                        description=description,
-                        emoji=emoji,
-                        created_at=created_at,
-                        updated_at=updated_at,
-                        plugin_id=LANGRAG_PLUGIN_ID,
-                        collection_id=kb_uuid,
-                        creation_settings=creation_settings,
-                        retrieval_settings=retrieval_settings,
-                    )
-                )
-
-                try:
-                    config = {'embedding_model_uuid': embedding_model_uuid}
-                    await self.ap.plugin_connector.rag_on_kb_create(LANGRAG_PLUGIN_ID, kb_uuid, config)
-                    task_context.trace(f'Restored internal KB: {name} ({kb_uuid})')
-                except Exception as e:
-                    warning = f'Failed to notify plugin for KB {name} ({kb_uuid}): {e}'
-                    warnings.append(warning)
-                    task_context.trace(warning)
-
-            await self.ap.rag_mgr.load_knowledge_bases_from_db()
-
-        # Step 4: Restore external knowledge bases
-        task_context.trace('Restoring external knowledge bases...', action='restore-external')
-        if has_external:
-            result = await self.ap.persistence_mgr.execute_async(
-                sqlalchemy.text('SELECT * FROM external_knowledge_bases;')
-            )
-            rows = result.fetchall()
-            columns = result.keys()
-
-            self.ap.logger.info(
-                f'RAG migration: {len(rows)} external KB(s) to restore. Available engines: {engine_id_set}'
-            )
-            task_context.trace(f'Found {len(rows)} external KB(s). Available engines: {engine_id_set}')
-
-            for row in rows:
-                row_dict = dict(zip(columns, row))
-                kb_uuid = row_dict.get('uuid')
-                name = row_dict.get('name', 'Untitled')
-                description = row_dict.get('description', '')
-                emoji = row_dict.get('emoji', '\U0001f517')
-                plugin_author = row_dict.get('plugin_author', '')
-                plugin_name = row_dict.get('plugin_name', '')
-                retriever_config = row_dict.get('retriever_config', {})
-                created_at = row_dict.get('created_at')
-
-                mapped_plugin_name = EXTERNAL_PLUGIN_NAME_MAPPING.get(plugin_name, plugin_name)
-                external_plugin_id = f'{plugin_author}/{mapped_plugin_name}'
-
-                self.ap.logger.info(
-                    f'RAG migration: processing external KB "{name}" ({kb_uuid}), '
-                    f'plugin: {plugin_author}/{plugin_name} -> {external_plugin_id}'
-                )
-
-                if isinstance(retriever_config, str):
-                    try:
-                        retriever_config = json.loads(retriever_config)
-                    except (json.JSONDecodeError, TypeError):
-                        retriever_config = {}
-
-                creation_fields = EXTERNAL_PLUGIN_CREATION_FIELDS.get(external_plugin_id)
-                if creation_fields is None:
-                    creation_settings_dict = retriever_config
-                    retrieval_settings_dict = {}
-                else:
-                    creation_settings_dict = {k: v for k, v in retriever_config.items() if k in creation_fields}
-                    retrieval_settings_dict = {k: v for k, v in retriever_config.items() if k not in creation_fields}
-
-                await self.ap.persistence_mgr.execute_async(
-                    sqlalchemy.text(
-                        'INSERT INTO knowledge_bases '
-                        '(uuid, name, description, emoji, created_at, updated_at, '
-                        'knowledge_engine_plugin_id, collection_id, creation_settings, retrieval_settings) '
-                        'VALUES (:uuid, :name, :description, :emoji, :created_at, :updated_at, '
-                        ':plugin_id, :collection_id, :creation_settings, :retrieval_settings);'
-                    ).bindparams(
-                        uuid=kb_uuid,
-                        name=name,
-                        description=description,
-                        emoji=emoji,
-                        created_at=created_at,
-                        updated_at=created_at,
-                        plugin_id=external_plugin_id,
-                        collection_id=kb_uuid,
-                        creation_settings=json.dumps(creation_settings_dict),
-                        retrieval_settings=json.dumps(retrieval_settings_dict),
-                    )
-                )
-
-                if external_plugin_id not in engine_id_set:
-                    warning = (
-                        f'External KB "{name}" ({kb_uuid}) record saved, but plugin {external_plugin_id} '
-                        f'is not installed yet. Install the connector plugin to use it.'
-                    )
-                    warnings.append(warning)
-                    task_context.trace(warning)
-                else:
-                    try:
-                        await self.ap.plugin_connector.rag_on_kb_create(
-                            external_plugin_id, kb_uuid, creation_settings_dict
-                        )
-                        task_context.trace(f'Restored external KB: {name} ({kb_uuid})')
-                    except Exception as e:
-                        warning = f'Failed to notify plugin for external KB {name} ({kb_uuid}): {e}'
-                        warnings.append(warning)
-                        task_context.trace(warning)
-
-            await self.ap.rag_mgr.load_knowledge_bases_from_db()
-
-        # Step 5: Clear migration flag
-        await self._set_migration_flag('false')
-        task_context.trace('RAG migration completed.', action='done')
-
-        if warnings:
-            task_context.trace(f'Completed with {len(warnings)} warning(s).')
-
-    async def initialize(self) -> None:
-        @self.route('/status', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
-        async def _() -> str:
-            needed = await self._get_migration_flag()
-
-            internal_kb_count = 0
-            external_kb_count = 0
-
-            if needed:
-                if await self._table_exists('knowledge_bases_backup'):
-                    result = await self.ap.persistence_mgr.execute_async(
-                        sqlalchemy.text('SELECT COUNT(*) FROM knowledge_bases_backup;')
-                    )
-                    internal_kb_count = result.scalar() or 0
-
-                if await self._table_exists('external_knowledge_bases'):
-                    result = await self.ap.persistence_mgr.execute_async(
-                        sqlalchemy.text('SELECT COUNT(*) FROM external_knowledge_bases;')
-                    )
-                    external_kb_count = result.scalar() or 0
-
-            return self.success(
-                data={
-                    'needed': needed,
-                    'internal_kb_count': internal_kb_count,
-                    'external_kb_count': external_kb_count,
-                }
-            )
-
-        @self.route('/execute', methods=['POST'], auth_type=group.AuthType.USER_TOKEN)
-        async def _() -> str:
-            needed = await self._get_migration_flag()
-            if not needed:
-                return self.http_status(400, -1, 'RAG migration is not needed')
-
-            data = await quart.request.get_json(silent=True) or {}
-            install_plugin = data.get('install_plugin', True)
-
-            ctx = taskmgr.TaskContext.new()
-            wrapper = self.ap.task_mgr.create_user_task(
-                self._execute_rag_migration(task_context=ctx, install_plugin=install_plugin),
-                kind='rag-migration',
-                name='rag-migration-execute',
-                label='Migrating knowledge bases to plugin architecture',
-                context=ctx,
-            )
-
-            return self.success(data={'task_id': wrapper.id})
-
-        @self.route('/dismiss', methods=['POST'], auth_type=group.AuthType.USER_TOKEN)
-        async def _() -> str:
-            needed = await self._get_migration_flag()
-            if not needed:
-                return self.http_status(400, -1, 'RAG migration is not needed')
-
-            await self._set_migration_flag('false')
-            return self.success()

src/langbot/pkg/api/http/controller/groups/knowledge/parsers.py

@@ -1,16 +0,0 @@
-import quart
-from ... import group
-
-
-@group.group_class('parsers', '/api/v1/knowledge/parsers')
-class ParsersRouterGroup(group.RouterGroup):
-    async def initialize(self) -> None:
-        @self.route('', methods=['GET'], auth_type=group.AuthType.USER_TOKEN_OR_API_KEY)
-        async def list_parsers() -> quart.Response:
-            """List all available parsers from plugins.
-
-            Optional query parameter `mime_type` to filter parsers by supported MIME type.
-            """
-            mime_type = quart.request.args.get('mime_type')
-            parsers = await self.ap.knowledge_service.list_parsers(mime_type)
-            return self.success(data={'parsers': parsers})

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

@@ -1,488 +0,0 @@
-from __future__ import annotations
-
-import datetime
-import quart
-
-from .. import group
-
-
-def parse_iso_datetime(datetime_str: str | None) -> datetime.datetime | None:
-    """Parse ISO 8601 datetime string, handling 'Z' suffix for UTC timezone"""
-    if not datetime_str:
-        return None
-    # Replace 'Z' with '+00:00' for Python 3.10 compatibility
-    if datetime_str.endswith('Z'):
-        datetime_str = datetime_str[:-1] + '+00:00'
-    dt = datetime.datetime.fromisoformat(datetime_str)
-    # Convert to UTC and remove timezone info to match database storage (which stores UTC as naive datetime)
-    if dt.tzinfo is not None:
-        # Convert to UTC and remove timezone info
-        dt = dt.astimezone(datetime.timezone.utc).replace(tzinfo=None)
-    return dt
-
-
-@group.group_class('monitoring', '/api/v1/monitoring')
-class MonitoringRouterGroup(group.RouterGroup):
-    async def initialize(self) -> None:
-        @self.route('/overview', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
-        async def get_overview() -> str:
-            """Get overview metrics"""
-            # Parse query parameters
-            bot_ids = quart.request.args.getlist('botId')
-            pipeline_ids = quart.request.args.getlist('pipelineId')
-            start_time_str = quart.request.args.get('startTime')
-            end_time_str = quart.request.args.get('endTime')
-
-            # Parse datetime
-            start_time = parse_iso_datetime(start_time_str)
-            end_time = parse_iso_datetime(end_time_str)
-
-            metrics = await self.ap.monitoring_service.get_overview_metrics(
-                bot_ids=bot_ids if bot_ids else None,
-                pipeline_ids=pipeline_ids if pipeline_ids else None,
-                start_time=start_time,
-                end_time=end_time,
-            )
-
-            return self.success(data=metrics)
-
-        @self.route('/messages', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
-        async def get_messages() -> str:
-            """Get message logs"""
-            # Parse query parameters
-            bot_ids = quart.request.args.getlist('botId')
-            pipeline_ids = quart.request.args.getlist('pipelineId')
-            session_ids = quart.request.args.getlist('sessionId')
-            start_time_str = quart.request.args.get('startTime')
-            end_time_str = quart.request.args.get('endTime')
-            limit = int(quart.request.args.get('limit', 100))
-            offset = int(quart.request.args.get('offset', 0))
-
-            # Parse datetime
-            start_time = parse_iso_datetime(start_time_str)
-            end_time = parse_iso_datetime(end_time_str)
-
-            messages, total = await self.ap.monitoring_service.get_messages(
-                bot_ids=bot_ids if bot_ids else None,
-                pipeline_ids=pipeline_ids if pipeline_ids else None,
-                session_ids=session_ids if session_ids else None,
-                start_time=start_time,
-                end_time=end_time,
-                limit=limit,
-                offset=offset,
-            )
-
-            return self.success(
-                data={
-                    'messages': messages,
-                    'total': total,
-                    'limit': limit,
-                    'offset': offset,
-                }
-            )
-
-        @self.route('/llm-calls', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
-        async def get_llm_calls() -> str:
-            """Get LLM call records"""
-            # Parse query parameters
-            bot_ids = quart.request.args.getlist('botId')
-            pipeline_ids = quart.request.args.getlist('pipelineId')
-            start_time_str = quart.request.args.get('startTime')
-            end_time_str = quart.request.args.get('endTime')
-            limit = int(quart.request.args.get('limit', 100))
-            offset = int(quart.request.args.get('offset', 0))
-
-            # Parse datetime
-            start_time = parse_iso_datetime(start_time_str)
-            end_time = parse_iso_datetime(end_time_str)
-
-            llm_calls, total = await self.ap.monitoring_service.get_llm_calls(
-                bot_ids=bot_ids if bot_ids else None,
-                pipeline_ids=pipeline_ids if pipeline_ids else None,
-                start_time=start_time,
-                end_time=end_time,
-                limit=limit,
-                offset=offset,
-            )
-
-            return self.success(
-                data={
-                    'llm_calls': llm_calls,
-                    'total': total,
-                    'limit': limit,
-                    'offset': offset,
-                }
-            )
-
-        @self.route('/embedding-calls', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
-        async def get_embedding_calls() -> str:
-            """Get embedding call records"""
-            # Parse query parameters
-            start_time_str = quart.request.args.get('startTime')
-            end_time_str = quart.request.args.get('endTime')
-            knowledge_base_id = quart.request.args.get('knowledgeBaseId')
-            limit = int(quart.request.args.get('limit', 100))
-            offset = int(quart.request.args.get('offset', 0))
-
-            # Parse datetime
-            start_time = parse_iso_datetime(start_time_str)
-            end_time = parse_iso_datetime(end_time_str)
-
-            embedding_calls, total = await self.ap.monitoring_service.get_embedding_calls(
-                start_time=start_time,
-                end_time=end_time,
-                knowledge_base_id=knowledge_base_id if knowledge_base_id else None,
-                limit=limit,
-                offset=offset,
-            )
-
-            return self.success(
-                data={
-                    'embedding_calls': embedding_calls,
-                    'total': total,
-                    'limit': limit,
-                    'offset': offset,
-                }
-            )
-
-        @self.route('/sessions', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
-        async def get_sessions() -> str:
-            """Get session information"""
-            # Parse query parameters
-            bot_ids = quart.request.args.getlist('botId')
-            pipeline_ids = quart.request.args.getlist('pipelineId')
-            start_time_str = quart.request.args.get('startTime')
-            end_time_str = quart.request.args.get('endTime')
-            is_active_str = quart.request.args.get('isActive')
-            limit = int(quart.request.args.get('limit', 100))
-            offset = int(quart.request.args.get('offset', 0))
-
-            # Parse datetime
-            start_time = parse_iso_datetime(start_time_str)
-            end_time = parse_iso_datetime(end_time_str)
-
-            # Parse is_active
-            is_active = None
-            if is_active_str:
-                is_active = is_active_str.lower() == 'true'
-
-            sessions, total = await self.ap.monitoring_service.get_sessions(
-                bot_ids=bot_ids if bot_ids else None,
-                pipeline_ids=pipeline_ids if pipeline_ids else None,
-                start_time=start_time,
-                end_time=end_time,
-                is_active=is_active,
-                limit=limit,
-                offset=offset,
-            )
-
-            return self.success(
-                data={
-                    'sessions': sessions,
-                    'total': total,
-                    'limit': limit,
-                    'offset': offset,
-                }
-            )
-
-        @self.route('/errors', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
-        async def get_errors() -> str:
-            """Get error logs"""
-            # Parse query parameters
-            bot_ids = quart.request.args.getlist('botId')
-            pipeline_ids = quart.request.args.getlist('pipelineId')
-            start_time_str = quart.request.args.get('startTime')
-            end_time_str = quart.request.args.get('endTime')
-            limit = int(quart.request.args.get('limit', 100))
-            offset = int(quart.request.args.get('offset', 0))
-
-            # Parse datetime
-            start_time = parse_iso_datetime(start_time_str)
-            end_time = parse_iso_datetime(end_time_str)
-
-            errors, total = await self.ap.monitoring_service.get_errors(
-                bot_ids=bot_ids if bot_ids else None,
-                pipeline_ids=pipeline_ids if pipeline_ids else None,
-                start_time=start_time,
-                end_time=end_time,
-                limit=limit,
-                offset=offset,
-            )
-
-            return self.success(
-                data={
-                    'errors': errors,
-                    'total': total,
-                    'limit': limit,
-                    'offset': offset,
-                }
-            )
-
-        @self.route('/data', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
-        async def get_all_data() -> str:
-            """Get all monitoring data in a single request"""
-            # Parse query parameters
-            bot_ids = quart.request.args.getlist('botId')
-            pipeline_ids = quart.request.args.getlist('pipelineId')
-            start_time_str = quart.request.args.get('startTime')
-            end_time_str = quart.request.args.get('endTime')
-            limit = int(quart.request.args.get('limit', 50))
-
-            # Parse datetime
-            start_time = parse_iso_datetime(start_time_str)
-            end_time = parse_iso_datetime(end_time_str)
-
-            # Get overview metrics
-            overview = await self.ap.monitoring_service.get_overview_metrics(
-                bot_ids=bot_ids if bot_ids else None,
-                pipeline_ids=pipeline_ids if pipeline_ids else None,
-                start_time=start_time,
-                end_time=end_time,
-            )
-
-            # Get messages
-            messages, messages_total = await self.ap.monitoring_service.get_messages(
-                bot_ids=bot_ids if bot_ids else None,
-                pipeline_ids=pipeline_ids if pipeline_ids else None,
-                start_time=start_time,
-                end_time=end_time,
-                limit=limit,
-                offset=0,
-            )
-
-            # Get LLM calls
-            llm_calls, llm_calls_total = await self.ap.monitoring_service.get_llm_calls(
-                bot_ids=bot_ids if bot_ids else None,
-                pipeline_ids=pipeline_ids if pipeline_ids else None,
-                start_time=start_time,
-                end_time=end_time,
-                limit=limit,
-                offset=0,
-            )
-
-            # Get sessions
-            sessions, sessions_total = await self.ap.monitoring_service.get_sessions(
-                bot_ids=bot_ids if bot_ids else None,
-                pipeline_ids=pipeline_ids if pipeline_ids else None,
-                start_time=start_time,
-                end_time=end_time,
-                is_active=None,
-                limit=limit,
-                offset=0,
-            )
-
-            # Get errors
-            errors, errors_total = await self.ap.monitoring_service.get_errors(
-                bot_ids=bot_ids if bot_ids else None,
-                pipeline_ids=pipeline_ids if pipeline_ids else None,
-                start_time=start_time,
-                end_time=end_time,
-                limit=limit,
-                offset=0,
-            )
-
-            # Get embedding calls
-            embedding_calls, embedding_calls_total = await self.ap.monitoring_service.get_embedding_calls(
-                start_time=start_time,
-                end_time=end_time,
-                limit=limit,
-                offset=0,
-            )
-
-            return self.success(
-                data={
-                    'overview': overview,
-                    'messages': messages,
-                    'llmCalls': llm_calls,
-                    'embeddingCalls': embedding_calls,
-                    'sessions': sessions,
-                    'errors': errors,
-                    'totalCount': {
-                        'messages': messages_total,
-                        'llmCalls': llm_calls_total,
-                        'embeddingCalls': embedding_calls_total,
-                        'sessions': sessions_total,
-                        'errors': errors_total,
-                    },
-                }
-            )
-
-        @self.route('/sessions/<session_id>/analysis', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
-        async def get_session_analysis(session_id: str) -> str:
-            """Get detailed analysis for a specific session"""
-            analysis = await self.ap.monitoring_service.get_session_analysis(session_id)
-
-            # Always return success with the analysis data
-            # The frontend will handle the 'found: false' case
-            return self.success(data=analysis)
-
-        @self.route('/messages/<message_id>/details', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
-        async def get_message_details(message_id: str) -> str:
-            """Get detailed information for a specific message"""
-            details = await self.ap.monitoring_service.get_message_details(message_id)
-
-            if not details.get('found'):
-                return self.error(message=f'Message {message_id} not found', code=404)
-
-            return self.success(data=details)
-
-        @self.route('/export', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
-        async def export_data() -> tuple[str, int]:
-            """Export monitoring data as CSV"""
-            # Parse query parameters
-            export_type = quart.request.args.get('type', 'messages')
-            bot_ids = quart.request.args.getlist('botId')
-            pipeline_ids = quart.request.args.getlist('pipelineId')
-            start_time_str = quart.request.args.get('startTime')
-            end_time_str = quart.request.args.get('endTime')
-            limit = int(quart.request.args.get('limit', 100000))
-
-            # Parse datetime
-            start_time = parse_iso_datetime(start_time_str)
-            end_time = parse_iso_datetime(end_time_str)
-
-            # Get data based on export type
-            if export_type == 'messages':
-                data = await self.ap.monitoring_service.export_messages(
-                    bot_ids=bot_ids if bot_ids else None,
-                    pipeline_ids=pipeline_ids if pipeline_ids else None,
-                    start_time=start_time,
-                    end_time=end_time,
-                    limit=limit,
-                )
-                headers = [
-                    'id',
-                    'timestamp',
-                    'bot_id',
-                    'bot_name',
-                    'pipeline_id',
-                    'pipeline_name',
-                    'runner_name',
-                    'message_content',
-                    'message_text',
-                    'session_id',
-                    'status',
-                    'level',
-                    'platform',
-                    'user_id',
-                ]
-            elif export_type == 'llm-calls':
-                data = await self.ap.monitoring_service.export_llm_calls(
-                    bot_ids=bot_ids if bot_ids else None,
-                    pipeline_ids=pipeline_ids if pipeline_ids else None,
-                    start_time=start_time,
-                    end_time=end_time,
-                    limit=limit,
-                )
-                headers = [
-                    'id',
-                    'timestamp',
-                    'model_name',
-                    'input_tokens',
-                    'output_tokens',
-                    'total_tokens',
-                    'duration_ms',
-                    'cost',
-                    'status',
-                    'bot_id',
-                    'bot_name',
-                    'pipeline_id',
-                    'pipeline_name',
-                    'session_id',
-                    'message_id',
-                    'error_message',
-                ]
-            elif export_type == 'embedding-calls':
-                data = await self.ap.monitoring_service.export_embedding_calls(
-                    start_time=start_time,
-                    end_time=end_time,
-                    limit=limit,
-                )
-                headers = [
-                    'id',
-                    'timestamp',
-                    'model_name',
-                    'prompt_tokens',
-                    'total_tokens',
-                    'duration_ms',
-                    'input_count',
-                    'status',
-                    'error_message',
-                    'knowledge_base_id',
-                    'query_text',
-                    'session_id',
-                    'message_id',
-                    'call_type',
-                ]
-            elif export_type == 'errors':
-                data = await self.ap.monitoring_service.export_errors(
-                    bot_ids=bot_ids if bot_ids else None,
-                    pipeline_ids=pipeline_ids if pipeline_ids else None,
-                    start_time=start_time,
-                    end_time=end_time,
-                    limit=limit,
-                )
-                headers = [
-                    'id',
-                    'timestamp',
-                    'error_type',
-                    'error_message',
-                    'bot_id',
-                    'bot_name',
-                    'pipeline_id',
-                    'pipeline_name',
-                    'session_id',
-                    'message_id',
-                    'stack_trace',
-                ]
-            elif export_type == 'sessions':
-                data = await self.ap.monitoring_service.export_sessions(
-                    bot_ids=bot_ids if bot_ids else None,
-                    pipeline_ids=pipeline_ids if pipeline_ids else None,
-                    start_time=start_time,
-                    end_time=end_time,
-                    limit=limit,
-                )
-                headers = [
-                    'session_id',
-                    'bot_id',
-                    'bot_name',
-                    'pipeline_id',
-                    'pipeline_name',
-                    'message_count',
-                    'start_time',
-                    'last_activity',
-                    'is_active',
-                    'platform',
-                    'user_id',
-                ]
-            else:
-                return self.error(message=f'Invalid export type: {export_type}', code=400)
-
-            # Generate CSV content with UTF-8 BOM for Excel compatibility
-            import io
-
-            output = io.StringIO()
-            # Write UTF-8 BOM for Excel
-            output.write('\ufeff')
-            # Write header
-            output.write(','.join(headers) + '\n')
-
-            # Escape and write each row
-            for row in data:
-                escaped_values = []
-                for header in headers:
-                    value = row.get(header, '')
-                    escaped_values.append(self.ap.monitoring_service._escape_csv_field(value))
-                output.write(','.join(escaped_values) + '\n')
-
-            csv_content = output.getvalue()
-
-            # Return as file download
-            response = await quart.make_response(csv_content)
-            response.headers['Content-Type'] = 'text/csv; charset=utf-8'
-            response.headers['Content-Disposition'] = (
-                f'attachment; filename="monitoring-{export_type}-{int(datetime.datetime.now().timestamp())}.csv"'
-            )
-
-            return response, 200

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

@@ -49,14 +49,6 @@ 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
         )
@@ -68,7 +60,7 @@ class PipelinesRouterGroup(group.RouterGroup):
                     return self.http_status(404, -1, 'pipeline not found')
 
                 # Only include plugins with pipeline-related components (Command, EventListener, Tool)
-                # Plugins that only have KnowledgeEngine components are not suitable for pipeline extensions
+                # Plugins that only have KnowledgeRetriever components are not suitable for pipeline extensions
                 pipeline_component_kinds = ['Command', 'EventListener', 'Tool']
                 plugins = await self.ap.plugin_connector.list_plugins(component_kinds=pipeline_component_kinds)
                 mcp_servers = await self.ap.mcp_service.get_mcp_servers(contain_runtime_info=True)

src/langbot/pkg/api/http/controller/groups/platform/bots.py

@@ -18,8 +18,7 @@ class BotsRouterGroup(group.RouterGroup):
         @self.route('/<bot_uuid>', methods=['GET', 'PUT', 'DELETE'], auth_type=group.AuthType.USER_TOKEN_OR_API_KEY)
         async def _(bot_uuid: str) -> str:
             if quart.request.method == 'GET':
-                # 返回运行时信息，包括webhook地址等
-                bot = await self.ap.bot_service.get_runtime_bot_info(bot_uuid)
+                bot = await self.ap.bot_service.get_bot(bot_uuid)
                 if bot is None:
                     return self.http_status(404, -1, 'bot not found')
                 return self.success(data={'bot': bot})

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

@@ -14,18 +14,6 @@ from langbot_plugin.runtime.plugin.mgr import PluginInstallSource
 
 @group.group_class('plugins', '/api/v1/plugins')
 class PluginsRouterGroup(group.RouterGroup):
-    async def _check_extensions_limit(self) -> str | None:
-        """Check if extensions limit is reached. Returns error response if limit exceeded, None otherwise."""
-        limitation = self.ap.instance_config.data.get('system', {}).get('limitation', {})
-        max_extensions = limitation.get('max_extensions', -1)
-        if max_extensions >= 0:
-            plugins = await self.ap.plugin_connector.list_plugins()
-            mcp_servers = await self.ap.mcp_service.get_mcp_servers()
-            total_extensions = len(plugins) + len(mcp_servers)
-            if total_extensions >= max_extensions:
-                return self.http_status(400, -1, f'Maximum number of extensions ({max_extensions}) reached')
-        return None
-
     async def initialize(self) -> None:
         @self.route('', methods=['GET'], auth_type=group.AuthType.USER_TOKEN_OR_API_KEY)
         async def _() -> str:
@@ -33,22 +21,6 @@ class PluginsRouterGroup(group.RouterGroup):
 
             return self.success(data={'plugins': plugins})
 
-        @self.route('/debug-info', methods=['GET'], auth_type=group.AuthType.USER_TOKEN_OR_API_KEY)
-        async def _() -> str:
-            """Get plugin debug information including debug URL and key"""
-            debug_info = await self.ap.plugin_connector.get_debug_info()
-
-            # Get debug URL from config
-            plugin_config = self.ap.instance_config.data.get('plugin', {})
-            debug_url = plugin_config.get('display_plugin_debug_url', 'http://localhost:5401')
-
-            return self.success(
-                data={
-                    'debug_url': debug_url,
-                    'plugin_debug_key': debug_info.get('plugin_debug_key', ''),
-                }
-            )
-
         @self.route(
             '/<author>/<plugin_name>/upgrade',
             methods=['POST'],
@@ -251,10 +223,6 @@ class PluginsRouterGroup(group.RouterGroup):
         @self.route('/install/github', methods=['POST'], auth_type=group.AuthType.USER_TOKEN_OR_API_KEY)
         async def _() -> str:
             """Install plugin from GitHub release asset"""
-            limit_error = await self._check_extensions_limit()
-            if limit_error is not None:
-                return limit_error
-
             data = await quart.request.json
             asset_url = data.get('asset_url', '')
             owner = data.get('owner', '')
@@ -289,10 +257,6 @@ class PluginsRouterGroup(group.RouterGroup):
             auth_type=group.AuthType.USER_TOKEN_OR_API_KEY,
         )
         async def _() -> str:
-            limit_error = await self._check_extensions_limit()
-            if limit_error is not None:
-                return limit_error
-
             data = await quart.request.json
 
             ctx = taskmgr.TaskContext.new()
@@ -308,10 +272,6 @@ class PluginsRouterGroup(group.RouterGroup):
 
         @self.route('/install/local', methods=['POST'], auth_type=group.AuthType.USER_TOKEN_OR_API_KEY)
         async def _() -> str:
-            limit_error = await self._check_extensions_limit()
-            if limit_error is not None:
-                return limit_error
-
             file = (await quart.request.files).get('file')
             if file is None:
                 return self.http_status(400, -1, 'file is required')

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

@@ -9,15 +9,12 @@ class LLMModelsRouterGroup(group.RouterGroup):
         @self.route('', methods=['GET', 'POST'], auth_type=group.AuthType.USER_TOKEN_OR_API_KEY)
         async def _() -> str:
             if quart.request.method == 'GET':
-                provider_uuid = quart.request.args.get('provider_uuid')
-                if provider_uuid:
-                    return self.success(
-                        data={'models': await self.ap.llm_model_service.get_llm_models_by_provider(provider_uuid)}
-                    )
                 return self.success(data={'models': await self.ap.llm_model_service.get_llm_models()})
             elif quart.request.method == 'POST':
                 json_data = await quart.request.json
+
                 model_uuid = await self.ap.llm_model_service.create_llm_model(json_data)
+
                 return self.success(data={'uuid': model_uuid})
 
         @self.route('/<model_uuid>', methods=['GET', 'PUT', 'DELETE'], auth_type=group.AuthType.USER_TOKEN_OR_API_KEY)
@@ -55,19 +52,12 @@ class EmbeddingModelsRouterGroup(group.RouterGroup):
         @self.route('', methods=['GET', 'POST'], auth_type=group.AuthType.USER_TOKEN_OR_API_KEY)
         async def _() -> str:
             if quart.request.method == 'GET':
-                provider_uuid = quart.request.args.get('provider_uuid')
-                if provider_uuid:
-                    return self.success(
-                        data={
-                            'models': await self.ap.embedding_models_service.get_embedding_models_by_provider(
-                                provider_uuid
-                            )
-                        }
-                    )
                 return self.success(data={'models': await self.ap.embedding_models_service.get_embedding_models()})
             elif quart.request.method == 'POST':
                 json_data = await quart.request.json
+
                 model_uuid = await self.ap.embedding_models_service.create_embedding_model(json_data)
+
                 return self.success(data={'uuid': model_uuid})
 
         @self.route('/<model_uuid>', methods=['GET', 'PUT', 'DELETE'], auth_type=group.AuthType.USER_TOKEN_OR_API_KEY)

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

@@ -1,45 +0,0 @@
-import quart
-
-from ... import group
-
-
-@group.group_class('models/providers', '/api/v1/provider/providers')
-class ModelProvidersRouterGroup(group.RouterGroup):
-    async def initialize(self) -> None:
-        @self.route('', methods=['GET', 'POST'], auth_type=group.AuthType.USER_TOKEN_OR_API_KEY)
-        async def _() -> str:
-            if quart.request.method == 'GET':
-                providers = await self.ap.provider_service.get_providers()
-                # Add model counts
-                for provider in providers:
-                    counts = await self.ap.provider_service.get_provider_model_counts(provider['uuid'])
-                    provider['llm_count'] = counts['llm_count']
-                    provider['embedding_count'] = counts['embedding_count']
-                return self.success(data={'providers': providers})
-            elif quart.request.method == 'POST':
-                json_data = await quart.request.json
-                provider_uuid = await self.ap.provider_service.create_provider(json_data)
-                return self.success(data={'uuid': provider_uuid})
-
-        @self.route(
-            '/<provider_uuid>', methods=['GET', 'PUT', 'DELETE'], auth_type=group.AuthType.USER_TOKEN_OR_API_KEY
-        )
-        async def _(provider_uuid: str) -> str:
-            if quart.request.method == 'GET':
-                provider = await self.ap.provider_service.get_provider(provider_uuid)
-                if provider is None:
-                    return self.http_status(404, -1, 'provider not found')
-                counts = await self.ap.provider_service.get_provider_model_counts(provider_uuid)
-                provider['llm_count'] = counts['llm_count']
-                provider['embedding_count'] = counts['embedding_count']
-                return self.success(data={'provider': provider})
-            elif quart.request.method == 'PUT':
-                json_data = await quart.request.json
-                await self.ap.provider_service.update_provider(provider_uuid, json_data)
-                return self.success()
-            elif quart.request.method == 'DELETE':
-                try:
-                    await self.ap.provider_service.delete_provider(provider_uuid)
-                    return self.success()
-                except ValueError as e:
-                    return self.http_status(400, -1, str(e))

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

@@ -1,47 +0,0 @@
-import quart
-
-from .. import group
-
-
-@group.group_class('survey', '/api/v1/survey')
-class SurveyRouterGroup(group.RouterGroup):
-    async def initialize(self) -> None:
-        @self.route('/pending', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
-        async def _get_pending() -> str:
-            """Get pending survey for the frontend to display."""
-            survey = self.ap.survey.get_pending_survey() if self.ap.survey else None
-            return self.success(data={'survey': survey})
-
-        @self.route('/respond', methods=['POST'], auth_type=group.AuthType.USER_TOKEN)
-        async def _respond() -> str:
-            """Submit survey response."""
-            json_data = await quart.request.json
-            survey_id = json_data.get('survey_id')
-            answers = json_data.get('answers', {})
-            completed = json_data.get('completed', True)
-
-            if not survey_id:
-                return self.fail(1, 'survey_id required')
-
-            if self.ap.survey:
-                ok = await self.ap.survey.submit_response(survey_id, answers, completed)
-                if ok:
-                    return self.success()
-                return self.fail(2, 'Failed to submit response')
-            return self.fail(3, 'Survey not available')
-
-        @self.route('/dismiss', methods=['POST'], auth_type=group.AuthType.USER_TOKEN)
-        async def _dismiss() -> str:
-            """Dismiss survey."""
-            json_data = await quart.request.json
-            survey_id = json_data.get('survey_id')
-
-            if not survey_id:
-                return self.fail(1, 'survey_id required')
-
-            if self.ap.survey:
-                ok = await self.ap.survey.dismiss_survey(survey_id)
-                if ok:
-                    return self.success()
-                return self.fail(2, 'Failed to dismiss')
-            return self.fail(3, 'Survey not available')

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

@@ -13,20 +13,16 @@ class SystemRouterGroup(group.RouterGroup):
                 data={
                     'version': constants.semantic_version,
                     'debug': constants.debug_mode,
-                    'edition': constants.edition,
                     'enable_marketplace': self.ap.instance_config.data.get('plugin', {}).get(
                         'enable_marketplace', True
                     ),
                     'cloud_service_url': (
-                        self.ap.instance_config.data.get('space', {}).get('url', 'https://space.langbot.app')
+                        self.ap.instance_config.data.get('plugin', {}).get(
+                            'cloud_service_url', 'https://space.langbot.app'
+                        )
+                        if 'cloud_service_url' in self.ap.instance_config.data.get('plugin', {})
+                        else 'https://space.langbot.app'
                     ),
-                    'allow_modify_login_info': self.ap.instance_config.data.get('system', {}).get(
-                        'allow_modify_login_info', True
-                    ),
-                    'disable_models_service': self.ap.instance_config.data.get('space', {}).get(
-                        'disable_models_service', False
-                    ),
-                    'limitation': self.ap.instance_config.data.get('system', {}).get('limitation', {}),
                 }
             )
 

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

@@ -1,10 +1,8 @@
 import quart
 import argon2
 import asyncio
-import traceback
 
 from .. import group
-from .....entity.errors import account as account_errors
 
 
 @group.group_class('user', '/api/v1/user')
@@ -35,8 +33,6 @@ class UserRouterGroup(group.RouterGroup):
                 token = await self.ap.user_service.authenticate(json_data['user'], json_data['password'])
             except argon2.exceptions.VerifyMismatchError:
                 return self.fail(1, 'Invalid username or password')
-            except ValueError as e:
-                return self.fail(1, str(e))
 
             return self.success(data={'token': token})
 
@@ -74,13 +70,6 @@ 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_modify_login_info = self.ap.instance_config.data.get('system', {}).get(
-                'allow_modify_login_info', True
-            )
-            if not allow_modify_login_info:
-                return self.http_status(403, -1, 'Modifying login info is disabled')
-
             json_data = await quart.request.json
 
             current_password = json_data['current_password']
@@ -94,169 +83,3 @@ class UserRouterGroup(group.RouterGroup):
                 return self.http_status(400, -1, str(e))
 
             return self.success(data={'user': user_email})
-
-        # Space OAuth endpoints (redirect flow)
-
-        @self.route('/space/authorize-url', methods=['GET'], auth_type=group.AuthType.NONE)
-        async def _() -> str:
-            """Get Space OAuth authorization URL for redirect"""
-            redirect_uri = quart.request.args.get('redirect_uri', '')
-            state = quart.request.args.get('state', '')
-
-            if not redirect_uri:
-                return self.fail(1, 'Missing redirect_uri parameter')
-
-            try:
-                authorize_url = self.ap.space_service.get_oauth_authorize_url(redirect_uri, state)
-                return self.success(data={'authorize_url': authorize_url})
-            except Exception as e:
-                return self.fail(1, str(e))
-
-        @self.route('/space/callback', methods=['POST'], auth_type=group.AuthType.NONE)
-        async def _() -> str:
-            """Handle OAuth callback - exchange code for tokens and authenticate"""
-            json_data = await quart.request.json
-            code = json_data.get('code')
-
-            if not code:
-                return self.fail(1, 'Missing authorization code')
-
-            try:
-                # Exchange code for tokens
-                token_data = await self.ap.space_service.exchange_oauth_code(code)
-                access_token = token_data.get('access_token')
-                refresh_token = token_data.get('refresh_token')
-                expires_in = token_data.get('expires_in', 0)
-
-                if not access_token:
-                    return self.fail(1, 'Failed to get access token from Space')
-
-                # Authenticate and create/update local user
-                jwt_token, user_obj = await self.ap.user_service.authenticate_space_user(
-                    access_token, refresh_token, expires_in
-                )
-
-                return self.success(
-                    data={
-                        'token': jwt_token,
-                        'user': user_obj.user,
-                    }
-                )
-            except account_errors.AccountEmailMismatchError as e:
-                return self.fail(3, str(e))
-            except ValueError as e:
-                traceback.print_exc()
-                return self.fail(1, str(e))
-            except Exception as e:
-                traceback.print_exc()
-                return self.fail(2, f'OAuth callback failed: {str(e)}')
-
-        @self.route('/info', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
-        async def _(user_email: str) -> str:
-            """Get current user information including account type"""
-            user_obj = await self.ap.user_service.get_user_by_email(user_email)
-
-            if user_obj is None:
-                return self.http_status(404, -1, 'User not found')
-
-            return self.success(
-                data={
-                    'user': user_obj.user,
-                    'account_type': user_obj.account_type,
-                    'has_password': bool(user_obj.password and user_obj.password.strip()),
-                }
-            )
-
-        @self.route('/space-credits', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
-        async def _(user_email: str) -> str:
-            """Get Space credits balance for current user"""
-            credits = await self.ap.space_service.get_credits(user_email)
-            return self.success(data={'credits': credits})
-
-        @self.route('/account-info', methods=['GET'], auth_type=group.AuthType.NONE)
-        async def _() -> str:
-            """Get account info for login page (account type and has_password)"""
-            if not await self.ap.user_service.is_initialized():
-                return self.success(data={'initialized': False})
-
-            user_obj = await self.ap.user_service.get_first_user()
-            if user_obj is None:
-                return self.success(data={'initialized': False})
-
-            return self.success(
-                data={
-                    'initialized': True,
-                    'account_type': user_obj.account_type,
-                    'has_password': bool(user_obj.password and user_obj.password.strip()),
-                }
-            )
-
-        @self.route('/set-password', methods=['POST'], auth_type=group.AuthType.USER_TOKEN)
-        async def _(user_email: str) -> str:
-            """Set password for Space account (first time) or change password"""
-            json_data = await quart.request.json
-            new_password = json_data.get('new_password')
-            current_password = json_data.get('current_password')
-
-            if not new_password:
-                return self.http_status(400, -1, 'New password is required')
-
-            user_obj = await self.ap.user_service.get_user_by_email(user_email)
-            if user_obj is None:
-                return self.http_status(404, -1, 'User not found')
-
-            try:
-                await self.ap.user_service.set_password(user_email, new_password, current_password)
-                return self.success(data={'user': user_email})
-            except ValueError as e:
-                return self.http_status(400, -1, str(e))
-            except argon2.exceptions.VerifyMismatchError:
-                return self.http_status(400, -1, 'Current password is incorrect')
-
-        @self.route('/bind-space', methods=['POST'], auth_type=group.AuthType.NONE)
-        async def _() -> str:
-            """Bind Space account to existing local account"""
-            # Check if modifying login info is allowed
-            allow_modify_login_info = self.ap.instance_config.data.get('system', {}).get(
-                'allow_modify_login_info', True
-            )
-            if not allow_modify_login_info:
-                return self.http_status(403, -1, 'Modifying login info is disabled')
-
-            json_data = await quart.request.json
-            code = json_data.get('code')
-            state = json_data.get('state')  # JWT token passed as state
-
-            if not code:
-                return self.http_status(400, -1, 'Missing authorization code')
-
-            if not state:
-                return self.http_status(400, -1, 'Missing state parameter')
-
-            # Verify state is a valid JWT token
-            try:
-                user_email = await self.ap.user_service.verify_jwt_token(state)
-            except Exception:
-                return self.http_status(401, -1, 'Invalid or expired state')
-
-            user_obj = await self.ap.user_service.get_user_by_email(user_email)
-            if user_obj is None:
-                return self.http_status(404, -1, 'User not found')
-
-            if user_obj.account_type != 'local':
-                return self.http_status(400, -1, 'Only local accounts can bind to Space')
-
-            try:
-                updated_user = await self.ap.user_service.bind_space_account(user_email, code)
-                jwt_token = await self.ap.user_service.generate_jwt_token(updated_user.user)
-                return self.success(
-                    data={
-                        'token': jwt_token,
-                        'user': updated_user.user,
-                        'account_type': updated_user.account_type,
-                    }
-                )
-            except ValueError as e:
-                return self.http_status(400, -1, str(e))
-            except Exception as e:
-                return self.http_status(500, -1, f'Failed to bind Space account: {str(e)}')

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

@@ -1,49 +0,0 @@
-import quart
-
-from .. import group
-
-
-@group.group_class('webhook_mgmt', '/api/v1/webhooks')
-class WebhookManagementRouterGroup(group.RouterGroup):
-    async def initialize(self) -> None:
-        @self.route('', methods=['GET', 'POST'])
-        async def _() -> str:
-            if quart.request.method == 'GET':
-                webhooks = await self.ap.webhook_service.get_webhooks()
-                return self.success(data={'webhooks': webhooks})
-            elif quart.request.method == 'POST':
-                json_data = await quart.request.json
-                name = json_data.get('name', '')
-                url = json_data.get('url', '')
-                description = json_data.get('description', '')
-                enabled = json_data.get('enabled', True)
-
-                if not name:
-                    return self.http_status(400, -1, 'Name is required')
-                if not url:
-                    return self.http_status(400, -1, 'URL is required')
-
-                webhook = await self.ap.webhook_service.create_webhook(name, url, description, enabled)
-                return self.success(data={'webhook': webhook})
-
-        @self.route('/<int:webhook_id>', methods=['GET', 'PUT', 'DELETE'])
-        async def _(webhook_id: int) -> str:
-            if quart.request.method == 'GET':
-                webhook = await self.ap.webhook_service.get_webhook(webhook_id)
-                if webhook is None:
-                    return self.http_status(404, -1, 'Webhook not found')
-                return self.success(data={'webhook': webhook})
-
-            elif quart.request.method == 'PUT':
-                json_data = await quart.request.json
-                name = json_data.get('name')
-                url = json_data.get('url')
-                description = json_data.get('description')
-                enabled = json_data.get('enabled')
-
-                await self.ap.webhook_service.update_webhook(webhook_id, name, url, description, enabled)
-                return self.success()
-
-            elif quart.request.method == 'DELETE':
-                await self.ap.webhook_service.delete_webhook(webhook_id)
-                return self.success()

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

@@ -1,54 +1,49 @@
-from __future__ import annotations
-
 import quart
-import traceback
 
 from .. import group
 
 
-@group.group_class('webhooks', '/bots')
-class WebhookRouterGroup(group.RouterGroup):
+@group.group_class('webhooks', '/api/v1/webhooks')
+class WebhooksRouterGroup(group.RouterGroup):
     async def initialize(self) -> None:
-        @self.route('/<bot_uuid>', methods=['GET', 'POST'], auth_type=group.AuthType.NONE)
-        async def handle_webhook(bot_uuid: str):
-            """处理 bot webhook 回调（无子路径）"""
-            return await self._dispatch_webhook(bot_uuid, '')
+        @self.route('', methods=['GET', 'POST'])
+        async def _() -> str:
+            if quart.request.method == 'GET':
+                webhooks = await self.ap.webhook_service.get_webhooks()
+                return self.success(data={'webhooks': webhooks})
+            elif quart.request.method == 'POST':
+                json_data = await quart.request.json
+                name = json_data.get('name', '')
+                url = json_data.get('url', '')
+                description = json_data.get('description', '')
+                enabled = json_data.get('enabled', True)
 
-        @self.route('/<bot_uuid>/<path:path>', methods=['GET', 'POST'], auth_type=group.AuthType.NONE)
-        async def handle_webhook_with_path(bot_uuid: str, path: str):
-            """处理 bot webhook 回调（带子路径）"""
-            return await self._dispatch_webhook(bot_uuid, path)
+                if not name:
+                    return self.http_status(400, -1, 'Name is required')
+                if not url:
+                    return self.http_status(400, -1, 'URL is required')
 
-    async def _dispatch_webhook(self, bot_uuid: str, path: str):
-        """分发 webhook 请求到对应的 bot adapter
+                webhook = await self.ap.webhook_service.create_webhook(name, url, description, enabled)
+                return self.success(data={'webhook': webhook})
 
-        Args:
-            bot_uuid: Bot 的 UUID
-            path: 子路径（如果有的话）
+        @self.route('/<int:webhook_id>', methods=['GET', 'PUT', 'DELETE'])
+        async def _(webhook_id: int) -> str:
+            if quart.request.method == 'GET':
+                webhook = await self.ap.webhook_service.get_webhook(webhook_id)
+                if webhook is None:
+                    return self.http_status(404, -1, 'Webhook not found')
+                return self.success(data={'webhook': webhook})
 
-        Returns:
-            适配器返回的响应
-        """
-        try:
-            runtime_bot = await self.ap.platform_mgr.get_bot_by_uuid(bot_uuid)
+            elif quart.request.method == 'PUT':
+                json_data = await quart.request.json
+                name = json_data.get('name')
+                url = json_data.get('url')
+                description = json_data.get('description')
+                enabled = json_data.get('enabled')
 
-            if not runtime_bot:
-                return quart.jsonify({'error': 'Bot not found'}), 404
+                await self.ap.webhook_service.update_webhook(webhook_id, name, url, description, enabled)
+                return self.success()
 
-            if not runtime_bot.enable:
-                return quart.jsonify({'error': 'Bot is disabled'}), 403
-
-            if not hasattr(runtime_bot.adapter, 'handle_unified_webhook'):
-                return quart.jsonify({'error': 'Adapter does not support unified webhook'}), 501
-
-            response = await runtime_bot.adapter.handle_unified_webhook(
-                bot_uuid=bot_uuid,
-                path=path,
-                request=quart.request,
-            )
-
-            return response
-
-        except Exception as e:
-            self.ap.logger.error(f'Webhook dispatch error for bot {bot_uuid}: {traceback.format_exc()}')
-            return quart.jsonify({'error': str(e)}), 500
+            elif quart.request.method == 'DELETE':
+                await self.ap.webhook_service.delete_webhook(webhook_id)
+                return self.success()

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

@@ -92,11 +92,7 @@ class HTTPController:
 
         @self.quart_app.route('/')
         async def index():
-            response = await quart.send_from_directory(frontend_path, 'index.html', mimetype='text/html')
-            response.headers['Cache-Control'] = 'no-cache, no-store, must-revalidate'
-            response.headers['Pragma'] = 'no-cache'
-            response.headers['Expires'] = '0'
-            return response
+            return await quart.send_from_directory(frontend_path, 'index.html', mimetype='text/html')
 
         @self.quart_app.route('/<path:path>')
         async def static_file(path: str):

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

@@ -58,39 +58,12 @@ class BotService:
         if runtime_bot is not None:
             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',
-            '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
-            adapter_runtime_values['webhook_full_url'] = f'{webhook_prefix}{webhook_url}'
-        else:
-            adapter_runtime_values['webhook_url'] = None
-            adapter_runtime_values['webhook_full_url'] = None
-
         persistence_bot['adapter_runtime_values'] = adapter_runtime_values
 
         return persistence_bot
 
     async def create_bot(self, bot_data: dict) -> str:
         """Create bot"""
-        # Check limitation
-        limitation = self.ap.instance_config.data.get('system', {}).get('limitation', {})
-        max_bots = limitation.get('max_bots', -1)
-        if max_bots >= 0:
-            existing_bots = await self.get_bots()
-            if len(existing_bots) >= max_bots:
-                raise ValueError(f'Maximum number of bots ({max_bots}) reached')
-
         # TODO: 检查配置信息格式
         bot_data['uuid'] = str(uuid.uuid4())
 

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

@@ -0,0 +1,80 @@
+from __future__ import annotations
+
+from ....core import app
+import sqlalchemy
+from langbot.pkg.entity.persistence import rag as persistence_rag
+import uuid
+
+
+class ExternalKBService:
+    """External KB service"""
+
+    ap: app.Application
+
+    def __init__(self, ap: app.Application) -> None:
+        self.ap = ap
+
+    # External Knowledge Base methods
+    async def get_external_knowledge_bases(self) -> list[dict]:
+        result = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_rag.ExternalKnowledgeBase))
+        external_kbs = result.all()
+        return [
+            self.ap.persistence_mgr.serialize_model(persistence_rag.ExternalKnowledgeBase, external_kb)
+            for external_kb in external_kbs
+        ]
+
+    async def get_external_knowledge_base(self, kb_uuid: str) -> dict | None:
+        result = await self.ap.persistence_mgr.execute_async(
+            sqlalchemy.select(persistence_rag.ExternalKnowledgeBase).where(
+                persistence_rag.ExternalKnowledgeBase.uuid == kb_uuid
+            )
+        )
+        external_kb = result.first()
+        if external_kb is None:
+            return None
+        return self.ap.persistence_mgr.serialize_model(persistence_rag.ExternalKnowledgeBase, external_kb)
+
+    async def create_external_knowledge_base(self, kb_data: dict) -> str:
+        kb_data['uuid'] = str(uuid.uuid4())
+        await self.ap.persistence_mgr.execute_async(
+            sqlalchemy.insert(persistence_rag.ExternalKnowledgeBase).values(kb_data)
+        )
+
+        kb = await self.get_external_knowledge_base(kb_data['uuid'])
+
+        await self.ap.rag_mgr.load_external_knowledge_base(kb)
+
+        return kb_data['uuid']
+
+    async def retrieve_external_knowledge_base(self, kb_uuid: str, query: str) -> list[dict]:
+        """Retrieve external knowledge base"""
+        runtime_kb = await self.ap.rag_mgr.get_knowledge_base_by_uuid(kb_uuid)
+        if runtime_kb is None:
+            raise Exception('Knowledge base not found')
+        return [
+            result.model_dump() for result in await runtime_kb.retrieve(query, 5)
+        ]  # top_k is just a placeholder for external knowledge base
+
+    async def update_external_knowledge_base(self, kb_uuid: str, kb_data: dict) -> None:
+        if 'uuid' in kb_data:
+            del kb_data['uuid']
+
+        await self.ap.persistence_mgr.execute_async(
+            sqlalchemy.update(persistence_rag.ExternalKnowledgeBase)
+            .values(kb_data)
+            .where(persistence_rag.ExternalKnowledgeBase.uuid == kb_uuid)
+        )
+        await self.ap.rag_mgr.remove_knowledge_base_from_runtime(kb_uuid)
+
+        kb = await self.get_external_knowledge_base(kb_uuid)
+
+        await self.ap.rag_mgr.load_external_knowledge_base(kb)
+
+    async def delete_external_knowledge_base(self, kb_uuid: str) -> None:
+        await self.ap.persistence_mgr.execute_async(
+            sqlalchemy.delete(persistence_rag.ExternalKnowledgeBase).where(
+                persistence_rag.ExternalKnowledgeBase.uuid == kb_uuid
+            )
+        )
+
+        await self.ap.rag_mgr.delete_knowledge_base(kb_uuid)

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

@@ -1,5 +1,6 @@
 from __future__ import annotations
 
+import uuid
 import sqlalchemy
 
 from ....core import app
@@ -16,99 +17,73 @@ class KnowledgeService:
 
     async def get_knowledge_bases(self) -> list[dict]:
         """获取所有知识库"""
-        return await self.ap.rag_mgr.get_all_knowledge_base_details()
+        result = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_rag.KnowledgeBase))
+        knowledge_bases = result.all()
+        return [
+            self.ap.persistence_mgr.serialize_model(persistence_rag.KnowledgeBase, knowledge_base)
+            for knowledge_base in knowledge_bases
+        ]
 
     async def get_knowledge_base(self, kb_uuid: str) -> dict | None:
         """获取知识库"""
-        return await self.ap.rag_mgr.get_knowledge_base_details(kb_uuid)
+        result = await self.ap.persistence_mgr.execute_async(
+            sqlalchemy.select(persistence_rag.KnowledgeBase).where(persistence_rag.KnowledgeBase.uuid == kb_uuid)
+        )
+        knowledge_base = result.first()
+        if knowledge_base is None:
+            return None
+        return self.ap.persistence_mgr.serialize_model(persistence_rag.KnowledgeBase, knowledge_base)
 
     async def create_knowledge_base(self, kb_data: dict) -> str:
         """创建知识库"""
-        # In new architecture, we delegate entirely to RAGManager which uses plugins.
-        # Legacy internal KB creation is removed.
+        kb_data['uuid'] = str(uuid.uuid4())
+        await self.ap.persistence_mgr.execute_async(sqlalchemy.insert(persistence_rag.KnowledgeBase).values(kb_data))
 
-        knowledge_engine_plugin_id = kb_data.get('knowledge_engine_plugin_id')
-        if not knowledge_engine_plugin_id:
-            raise ValueError('knowledge_engine_plugin_id is required')
+        kb = await self.get_knowledge_base(kb_data['uuid'])
 
-        kb = await self.ap.rag_mgr.create_knowledge_base(
-            name=kb_data.get('name', 'Untitled'),
-            knowledge_engine_plugin_id=knowledge_engine_plugin_id,
-            creation_settings=kb_data.get('creation_settings', {}),
-            retrieval_settings=kb_data.get('retrieval_settings', {}),
-            description=kb_data.get('description', ''),
-        )
-        return kb.uuid
+        await self.ap.rag_mgr.load_knowledge_base(kb)
+
+        return kb_data['uuid']
 
     async def update_knowledge_base(self, kb_uuid: str, kb_data: dict) -> None:
         """更新知识库"""
-        # Filter to only mutable fields
-        filtered_data = {k: v for k, v in kb_data.items() if k in persistence_rag.KnowledgeBase.MUTABLE_FIELDS}
+        if 'uuid' in kb_data:
+            del kb_data['uuid']
 
-        if not filtered_data:
-            return
+        if 'embedding_model_uuid' in kb_data:
+            del kb_data['embedding_model_uuid']
 
         await self.ap.persistence_mgr.execute_async(
             sqlalchemy.update(persistence_rag.KnowledgeBase)
-            .values(filtered_data)
+            .values(kb_data)
             .where(persistence_rag.KnowledgeBase.uuid == kb_uuid)
         )
         await self.ap.rag_mgr.remove_knowledge_base_from_runtime(kb_uuid)
 
         kb = await self.get_knowledge_base(kb_uuid)
-        if kb is None:
-            raise Exception('Knowledge base not found after update')
 
         await self.ap.rag_mgr.load_knowledge_base(kb)
 
-    async def _check_doc_capability(self, kb_uuid: str, operation: str) -> None:
-        """Check if the KB's Knowledge Engine supports document operations.
-
-        Args:
-            kb_uuid: Knowledge base UUID.
-            operation: Human-readable operation name for error messages.
-
-        Raises:
-            Exception: If the KB does not support doc_ingestion.
-        """
-        kb_info = await self.ap.rag_mgr.get_knowledge_base_details(kb_uuid)
-        if not kb_info:
-            raise Exception('Knowledge base not found')
-        capabilities = kb_info.get('knowledge_engine', {}).get('capabilities', [])
-        if 'doc_ingestion' not in capabilities:
-            raise Exception(f'This knowledge base does not support {operation}')
-
-    async def store_file(self, kb_uuid: str, file_id: str, parser_plugin_id: str | None = None) -> str:
+    async def store_file(self, kb_uuid: str, file_id: str) -> int:
         """存储文件"""
+        # await self.ap.persistence_mgr.execute_async(sqlalchemy.insert(persistence_rag.File).values(kb_id=kb_uuid, file_id=file_id))
+        # await self.ap.rag_mgr.store_file(file_id)
         runtime_kb = await self.ap.rag_mgr.get_knowledge_base_by_uuid(kb_uuid)
         if runtime_kb is None:
             raise Exception('Knowledge base not found')
+        # Only internal KBs support file storage
+        if runtime_kb.get_type() != 'internal':
+            raise Exception('Only internal knowledge bases support file storage')
+        return await runtime_kb.store_file(file_id)
 
-        await self._check_doc_capability(kb_uuid, 'document upload')
-
-        result = await runtime_kb.store_file(file_id, parser_plugin_id=parser_plugin_id)
-
-        # Update the KB's updated_at timestamp
-        await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.update(persistence_rag.KnowledgeBase)
-            .values(updated_at=sqlalchemy.func.now())
-            .where(persistence_rag.KnowledgeBase.uuid == kb_uuid)
-        )
-
-        return result
-
-    async def retrieve_knowledge_base(
-        self, kb_uuid: str, query: str, retrieval_settings: dict | None = None
-    ) -> list[dict]:
+    async def retrieve_knowledge_base(self, kb_uuid: str, query: str) -> list[dict]:
         """检索知识库"""
         runtime_kb = await self.ap.rag_mgr.get_knowledge_base_by_uuid(kb_uuid)
         if runtime_kb is None:
             raise Exception('Knowledge base not found')
-
-        # Pass retrieval_settings
-        results = await runtime_kb.retrieve(query, settings=retrieval_settings)
-
-        return [result.model_dump() for result in results]
+        return [
+            result.model_dump() for result in await runtime_kb.retrieve(query, runtime_kb.knowledge_base_entity.top_k)
+        ]
 
     async def get_files_by_knowledge_base(self, kb_uuid: str) -> list[dict]:
         """获取知识库文件"""
@@ -123,28 +98,20 @@ class KnowledgeService:
         runtime_kb = await self.ap.rag_mgr.get_knowledge_base_by_uuid(kb_uuid)
         if runtime_kb is None:
             raise Exception('Knowledge base not found')
-
-        await self._check_doc_capability(kb_uuid, 'document deletion')
-
+        # Only internal KBs support file deletion
+        if runtime_kb.get_type() != 'internal':
+            raise Exception('Only internal knowledge bases support file deletion')
         await runtime_kb.delete_file(file_id)
 
-        # Update the KB's updated_at timestamp
-        await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.update(persistence_rag.KnowledgeBase)
-            .values(updated_at=sqlalchemy.func.now())
-            .where(persistence_rag.KnowledgeBase.uuid == kb_uuid)
-        )
-
     async def delete_knowledge_base(self, kb_uuid: str) -> None:
         """删除知识库"""
-        # Delete from DB first to commit the deletion, then clean up runtime/plugin (best-effort)
+        await self.ap.rag_mgr.delete_knowledge_base(kb_uuid)
+
         await self.ap.persistence_mgr.execute_async(
             sqlalchemy.delete(persistence_rag.KnowledgeBase).where(persistence_rag.KnowledgeBase.uuid == kb_uuid)
         )
 
         # delete files
-        # NOTE: Chunk cleanup is for legacy (pre-plugin) KBs that stored chunks locally.
-        # For plugin-based Knowledge Engines, the Chunk table is not populated, so this is a no-op.
         files = await self.ap.persistence_mgr.execute_async(
             sqlalchemy.select(persistence_rag.File).where(persistence_rag.File.kb_id == kb_uuid)
         )
@@ -157,53 +124,3 @@ class KnowledgeService:
             await self.ap.persistence_mgr.execute_async(
                 sqlalchemy.delete(persistence_rag.File).where(persistence_rag.File.uuid == file.uuid)
             )
-
-        # Remove from runtime and notify plugin (best-effort, DB is already cleaned up)
-        await self.ap.rag_mgr.delete_knowledge_base(kb_uuid)
-
-    # ================= Knowledge Engine Discovery =================
-
-    async def list_knowledge_engines(self) -> list[dict]:
-        """List all available Knowledge Engines from plugins."""
-        engines = []
-
-        if not self.ap.plugin_connector.is_enable_plugin:
-            return engines
-
-        # Get KnowledgeEngine plugins
-        try:
-            knowledge_engines = await self.ap.plugin_connector.list_knowledge_engines()
-            engines.extend(knowledge_engines)
-        except Exception as e:
-            self.ap.logger.warning(f'Failed to list Knowledge Engines from plugins: {e}')
-
-        return engines
-
-    async def list_parsers(self, mime_type: str | None = None) -> list[dict]:
-        """List available parsers, optionally filtered by MIME type."""
-        if not self.ap.plugin_connector.is_enable_plugin:
-            return []
-        try:
-            parsers = await self.ap.plugin_connector.list_parsers()
-            if mime_type:
-                parsers = [p for p in parsers if mime_type in p.get('supported_mime_types', [])]
-            return parsers
-        except Exception as e:
-            self.ap.logger.warning(f'Failed to list parsers: {e}')
-            return []
-
-    async def get_engine_creation_schema(self, plugin_id: str) -> dict:
-        """Get creation settings schema for a specific Knowledge Engine."""
-        try:
-            return await self.ap.plugin_connector.get_rag_creation_schema(plugin_id)
-        except Exception as e:
-            self.ap.logger.warning(f'Failed to get creation schema for {plugin_id}: {e}')
-            return {}
-
-    async def get_engine_retrieval_schema(self, plugin_id: str) -> dict:
-        """Get retrieval settings schema for a specific Knowledge Engine."""
-        try:
-            return await self.ap.plugin_connector.get_rag_retrieval_schema(plugin_id)
-        except Exception as e:
-            self.ap.logger.warning(f'Failed to get retrieval schema for {plugin_id}: {e}')
-            return {}

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

@@ -38,16 +38,6 @@ class MCPService:
         return serialized_servers
 
     async def create_mcp_server(self, server_data: dict) -> str:
-        # Check limitation (extensions = MCP servers + plugins)
-        limitation = self.ap.instance_config.data.get('system', {}).get('limitation', {})
-        max_extensions = limitation.get('max_extensions', -1)
-        if max_extensions >= 0:
-            existing_mcp_servers = await self.get_mcp_servers()
-            plugins = await self.ap.plugin_connector.list_plugins()
-            total_extensions = len(existing_mcp_servers) + len(plugins)
-            if total_extensions >= max_extensions:
-                raise ValueError(f'Maximum number of extensions ({max_extensions}) reached')
-
         server_data['uuid'] = str(uuid.uuid4())
         await self.ap.persistence_mgr.execute_async(sqlalchemy.insert(persistence_mcp.MCPServer).values(server_data))
 

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

@@ -11,18 +11,6 @@ from ....entity.persistence import pipeline as persistence_pipeline
 from ....provider.modelmgr import requester as model_requester
 
 
-def _parse_provider_api_keys(provider_dict: dict) -> dict:
-    """Parse api_keys if it's a JSON string"""
-    if isinstance(provider_dict.get('api_keys'), str):
-        import json
-
-        try:
-            provider_dict['api_keys'] = json.loads(provider_dict['api_keys'])
-        except Exception:
-            provider_dict['api_keys'] = []
-    return provider_dict
-
-
 class LLMModelsService:
     ap: app.Application
 
@@ -30,131 +18,59 @@ class LLMModelsService:
         self.ap = ap
 
     async def get_llm_models(self, include_secret: bool = True) -> list[dict]:
-        """Get all LLM models with provider info"""
         result = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_model.LLMModel))
+
         models = result.all()
 
-        # Get all providers for lookup
-        providers_result = await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.select(persistence_model.ModelProvider)
-        )
-        providers = {p.uuid: p for p in providers_result.all()}
+        masked_columns = []
+        if not include_secret:
+            masked_columns = ['api_keys']
 
-        models_list = []
-        for model in models:
-            model_dict = self.ap.persistence_mgr.serialize_model(persistence_model.LLMModel, model)
-            provider = providers.get(model.provider_uuid)
-            if provider:
-                provider_dict = self.ap.persistence_mgr.serialize_model(persistence_model.ModelProvider, provider)
-                provider_dict = _parse_provider_api_keys(provider_dict)
-                if not include_secret:
-                    provider_dict['api_keys'] = ['***'] * len(provider_dict.get('api_keys', []))
-                model_dict['provider'] = provider_dict
-            models_list.append(model_dict)
+        return [
+            self.ap.persistence_mgr.serialize_model(persistence_model.LLMModel, model, masked_columns)
+            for model in models
+        ]
 
-        return models_list
-
-    async def get_llm_models_by_provider(self, provider_uuid: str) -> list[dict]:
-        """Get LLM models by provider UUID"""
-        result = await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.select(persistence_model.LLMModel).where(
-                persistence_model.LLMModel.provider_uuid == provider_uuid
-            )
-        )
-        models = result.all()
-        return [self.ap.persistence_mgr.serialize_model(persistence_model.LLMModel, m) for m in models]
-
-    async def create_llm_model(
-        self, model_data: dict, preserve_uuid: bool = False, auto_set_to_default_pipeline: bool = True
-    ) -> str:
-        """Create a new LLM model"""
-        if not preserve_uuid:
-            model_data['uuid'] = str(uuid.uuid4())
-
-        # Handle provider creation if needed
-        if 'provider' in model_data:
-            provider_data = model_data.pop('provider')
-            if provider_data.get('uuid'):
-                model_data['provider_uuid'] = provider_data['uuid']
-            else:
-                # Create new provider
-                provider_uuid = await self.ap.provider_service.find_or_create_provider(
-                    requester=provider_data.get('requester', ''),
-                    base_url=provider_data.get('base_url', ''),
-                    api_keys=provider_data.get('api_keys', []),
-                )
-                model_data['provider_uuid'] = provider_uuid
+    async def create_llm_model(self, model_data: dict) -> str:
+        model_data['uuid'] = str(uuid.uuid4())
 
         await self.ap.persistence_mgr.execute_async(sqlalchemy.insert(persistence_model.LLMModel).values(**model_data))
 
-        runtime_provider = self.ap.model_mgr.provider_dict.get(model_data['provider_uuid'])
-        if runtime_provider is None:
-            raise Exception('provider not found')
+        llm_model = await self.get_llm_model(model_data['uuid'])
 
-        runtime_llm_model = await self.ap.model_mgr.load_llm_model_with_provider(
-            persistence_model.LLMModel(**model_data),
-            runtime_provider,
-        )
-        self.ap.model_mgr.llm_models.append(runtime_llm_model)
+        await self.ap.model_mgr.load_llm_model(llm_model)
 
-        if auto_set_to_default_pipeline:
-            # set the default pipeline model to this model
-            result = await self.ap.persistence_mgr.execute_async(
-                sqlalchemy.select(persistence_pipeline.LegacyPipeline).where(
-                    persistence_pipeline.LegacyPipeline.is_default == True
-                )
+        # check if default pipeline has no model bound
+        result = await self.ap.persistence_mgr.execute_async(
+            sqlalchemy.select(persistence_pipeline.LegacyPipeline).where(
+                persistence_pipeline.LegacyPipeline.is_default == True
             )
-            pipeline = result.first()
-            if pipeline is not None and pipeline.config['ai']['local-agent']['model'] == '':
-                pipeline_config = pipeline.config
-                pipeline_config['ai']['local-agent']['model'] = model_data['uuid']
-                pipeline_data = {'config': pipeline_config}
-                await self.ap.pipeline_service.update_pipeline(pipeline.uuid, pipeline_data)
+        )
+        pipeline = result.first()
+        if pipeline is not None and pipeline.config['ai']['local-agent']['model'] == '':
+            pipeline_config = pipeline.config
+            pipeline_config['ai']['local-agent']['model'] = model_data['uuid']
+            pipeline_data = {'config': pipeline_config}
+            await self.ap.pipeline_service.update_pipeline(pipeline.uuid, pipeline_data)
 
         return model_data['uuid']
 
     async def get_llm_model(self, model_uuid: str) -> dict | None:
-        """Get a single LLM model with provider info"""
         result = await self.ap.persistence_mgr.execute_async(
             sqlalchemy.select(persistence_model.LLMModel).where(persistence_model.LLMModel.uuid == model_uuid)
         )
+
         model = result.first()
+
         if model is None:
             return None
 
-        model_dict = self.ap.persistence_mgr.serialize_model(persistence_model.LLMModel, model)
-
-        # Get provider
-        provider_result = await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.select(persistence_model.ModelProvider).where(
-                persistence_model.ModelProvider.uuid == model.provider_uuid
-            )
-        )
-        provider = provider_result.first()
-        if provider:
-            provider_dict = self.ap.persistence_mgr.serialize_model(persistence_model.ModelProvider, provider)
-            model_dict['provider'] = _parse_provider_api_keys(provider_dict)
-
-        return model_dict
+        return self.ap.persistence_mgr.serialize_model(persistence_model.LLMModel, model)
 
     async def update_llm_model(self, model_uuid: str, model_data: dict) -> None:
-        """Update an existing LLM model"""
         if 'uuid' in model_data:
             del model_data['uuid']
 
-        # Handle provider update if needed
-        if 'provider' in model_data:
-            provider_data = model_data.pop('provider')
-            if provider_data.get('uuid'):
-                model_data['provider_uuid'] = provider_data['uuid']
-            else:
-                provider_uuid = await self.ap.provider_service.find_or_create_provider(
-                    requester=provider_data.get('requester', ''),
-                    base_url=provider_data.get('base_url', ''),
-                    api_keys=provider_data.get('api_keys', []),
-                )
-                model_data['provider_uuid'] = provider_uuid
-
         await self.ap.persistence_mgr.execute_async(
             sqlalchemy.update(persistence_model.LLMModel)
             .where(persistence_model.LLMModel.uuid == model_uuid)
@@ -163,25 +79,18 @@ class LLMModelsService:
 
         await self.ap.model_mgr.remove_llm_model(model_uuid)
 
-        runtime_provider = self.ap.model_mgr.provider_dict.get(model_data['provider_uuid'])
-        if runtime_provider is None:
-            raise Exception('provider not found')
+        llm_model = await self.get_llm_model(model_uuid)
 
-        runtime_llm_model = await self.ap.model_mgr.load_llm_model_with_provider(
-            persistence_model.LLMModel(**model_data),
-            runtime_provider,
-        )
-        self.ap.model_mgr.llm_models.append(runtime_llm_model)
+        await self.ap.model_mgr.load_llm_model(llm_model)
 
     async def delete_llm_model(self, model_uuid: str) -> None:
-        """Delete an LLM model"""
         await self.ap.persistence_mgr.execute_async(
             sqlalchemy.delete(persistence_model.LLMModel).where(persistence_model.LLMModel.uuid == model_uuid)
         )
+
         await self.ap.model_mgr.remove_llm_model(model_uuid)
 
     async def test_llm_model(self, model_uuid: str, model_data: dict) -> None:
-        """Test an LLM model"""
         runtime_llm_model: model_requester.RuntimeLLMModel | None = None
 
         if model_uuid != '_':
@@ -189,18 +98,25 @@ class LLMModelsService:
                 if model.model_entity.uuid == model_uuid:
                     runtime_llm_model = model
                     break
+
             if runtime_llm_model is None:
                 raise Exception('model not found')
-        else:
-            runtime_llm_model = await self.ap.model_mgr.init_temporary_runtime_llm_model(model_data)
 
-        extra_args = model_data.get('extra_args', {})
-        await runtime_llm_model.provider.invoke_llm(
+        else:
+            runtime_llm_model = await self.ap.model_mgr.init_runtime_llm_model(model_data)
+
+        # Mon Nov 10 2025: Commented for some providers may not support thinking parameter
+        # # 有些模型厂商默认开启了思考功能，测试容易延迟
+        # extra_args = model_data.get('extra_args', {})
+        # if not extra_args or 'thinking' not in extra_args:
+        #     extra_args['thinking'] = {'type': 'disabled'}
+
+        await runtime_llm_model.requester.invoke_llm(
             query=None,
             model=runtime_llm_model,
             messages=[provider_message.Message(role='user', content='Hello, world! Please just reply a "Hello".')],
             funcs=[],
-            extra_args=extra_args,
+            # extra_args=extra_args,
         )
 
 
@@ -211,111 +127,42 @@ class EmbeddingModelsService:
         self.ap = ap
 
     async def get_embedding_models(self) -> list[dict]:
-        """Get all embedding models with provider info"""
         result = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_model.EmbeddingModel))
+
         models = result.all()
+        return [self.ap.persistence_mgr.serialize_model(persistence_model.EmbeddingModel, model) for model in models]
 
-        providers_result = await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.select(persistence_model.ModelProvider)
-        )
-        providers = {p.uuid: p for p in providers_result.all()}
-
-        models_list = []
-        for model in models:
-            model_dict = self.ap.persistence_mgr.serialize_model(persistence_model.EmbeddingModel, model)
-            provider = providers.get(model.provider_uuid)
-            if provider:
-                provider_dict = self.ap.persistence_mgr.serialize_model(persistence_model.ModelProvider, provider)
-                model_dict['provider'] = _parse_provider_api_keys(provider_dict)
-            models_list.append(model_dict)
-
-        return models_list
-
-    async def get_embedding_models_by_provider(self, provider_uuid: str) -> list[dict]:
-        """Get embedding models by provider UUID"""
-        result = await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.select(persistence_model.EmbeddingModel).where(
-                persistence_model.EmbeddingModel.provider_uuid == provider_uuid
-            )
-        )
-        models = result.all()
-        return [self.ap.persistence_mgr.serialize_model(persistence_model.EmbeddingModel, m) for m in models]
-
-    async def create_embedding_model(self, model_data: dict, preserve_uuid: bool = False) -> str:
-        """Create a new embedding model"""
-        if not preserve_uuid:
-            model_data['uuid'] = str(uuid.uuid4())
-
-        if 'provider' in model_data:
-            provider_data = model_data.pop('provider')
-            if provider_data.get('uuid'):
-                model_data['provider_uuid'] = provider_data['uuid']
-            else:
-                provider_uuid = await self.ap.provider_service.find_or_create_provider(
-                    requester=provider_data.get('requester', ''),
-                    base_url=provider_data.get('base_url', ''),
-                    api_keys=provider_data.get('api_keys', []),
-                )
-                model_data['provider_uuid'] = provider_uuid
+    async def create_embedding_model(self, model_data: dict) -> str:
+        model_data['uuid'] = str(uuid.uuid4())
 
         await self.ap.persistence_mgr.execute_async(
             sqlalchemy.insert(persistence_model.EmbeddingModel).values(**model_data)
         )
 
-        runtime_provider = self.ap.model_mgr.provider_dict.get(model_data['provider_uuid'])
-        if runtime_provider is None:
-            raise Exception('provider not found')
+        embedding_model = await self.get_embedding_model(model_data['uuid'])
 
-        runtime_embedding_model = await self.ap.model_mgr.load_embedding_model_with_provider(
-            persistence_model.EmbeddingModel(**model_data),
-            runtime_provider,
-        )
-        self.ap.model_mgr.embedding_models.append(runtime_embedding_model)
+        await self.ap.model_mgr.load_embedding_model(embedding_model)
 
         return model_data['uuid']
 
     async def get_embedding_model(self, model_uuid: str) -> dict | None:
-        """Get a single embedding model with provider info"""
         result = await self.ap.persistence_mgr.execute_async(
             sqlalchemy.select(persistence_model.EmbeddingModel).where(
                 persistence_model.EmbeddingModel.uuid == model_uuid
             )
         )
+
         model = result.first()
+
         if model is None:
             return None
 
-        model_dict = self.ap.persistence_mgr.serialize_model(persistence_model.EmbeddingModel, model)
-
-        provider_result = await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.select(persistence_model.ModelProvider).where(
-                persistence_model.ModelProvider.uuid == model.provider_uuid
-            )
-        )
-        provider = provider_result.first()
-        if provider:
-            provider_dict = self.ap.persistence_mgr.serialize_model(persistence_model.ModelProvider, provider)
-            model_dict['provider'] = _parse_provider_api_keys(provider_dict)
-
-        return model_dict
+        return self.ap.persistence_mgr.serialize_model(persistence_model.EmbeddingModel, model)
 
     async def update_embedding_model(self, model_uuid: str, model_data: dict) -> None:
-        """Update an existing embedding model"""
         if 'uuid' in model_data:
             del model_data['uuid']
 
-        if 'provider' in model_data:
-            provider_data = model_data.pop('provider')
-            if provider_data.get('uuid'):
-                model_data['provider_uuid'] = provider_data['uuid']
-            else:
-                provider_uuid = await self.ap.provider_service.find_or_create_provider(
-                    requester=provider_data.get('requester', ''),
-                    base_url=provider_data.get('base_url', ''),
-                    api_keys=provider_data.get('api_keys', []),
-                )
-                model_data['provider_uuid'] = provider_uuid
-
         await self.ap.persistence_mgr.execute_async(
             sqlalchemy.update(persistence_model.EmbeddingModel)
             .where(persistence_model.EmbeddingModel.uuid == model_uuid)
@@ -324,27 +171,20 @@ class EmbeddingModelsService:
 
         await self.ap.model_mgr.remove_embedding_model(model_uuid)
 
-        runtime_provider = self.ap.model_mgr.provider_dict.get(model_data['provider_uuid'])
-        if runtime_provider is None:
-            raise Exception('provider not found')
+        embedding_model = await self.get_embedding_model(model_uuid)
 
-        runtime_embedding_model = await self.ap.model_mgr.load_embedding_model_with_provider(
-            persistence_model.EmbeddingModel(**model_data),
-            runtime_provider,
-        )
-        self.ap.model_mgr.embedding_models.append(runtime_embedding_model)
+        await self.ap.model_mgr.load_embedding_model(embedding_model)
 
     async def delete_embedding_model(self, model_uuid: str) -> None:
-        """Delete an embedding model"""
         await self.ap.persistence_mgr.execute_async(
             sqlalchemy.delete(persistence_model.EmbeddingModel).where(
                 persistence_model.EmbeddingModel.uuid == model_uuid
             )
         )
+
         await self.ap.model_mgr.remove_embedding_model(model_uuid)
 
     async def test_embedding_model(self, model_uuid: str, model_data: dict) -> None:
-        """Test an embedding model"""
         runtime_embedding_model: model_requester.RuntimeEmbeddingModel | None = None
 
         if model_uuid != '_':
@@ -352,12 +192,14 @@ class EmbeddingModelsService:
                 if model.model_entity.uuid == model_uuid:
                     runtime_embedding_model = model
                     break
+
             if runtime_embedding_model is None:
                 raise Exception('model not found')
-        else:
-            runtime_embedding_model = await self.ap.model_mgr.init_temporary_runtime_embedding_model(model_data)
 
-        await runtime_embedding_model.provider.invoke_embedding(
+        else:
+            runtime_embedding_model = await self.ap.model_mgr.init_runtime_embedding_model(model_data)
+
+        await runtime_embedding_model.requester.invoke_embedding(
             model=runtime_embedding_model,
             input_text=['Hello, world!'],
             extra_args={},

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

@@ -76,14 +76,6 @@ class PipelineService:
     async def create_pipeline(self, pipeline_data: dict, default: bool = False) -> str:
         from ....utils import paths as path_utils
 
-        # Check limitation
-        limitation = self.ap.instance_config.data.get('system', {}).get('limitation', {})
-        max_pipelines = limitation.get('max_pipelines', -1)
-        if max_pipelines >= 0:
-            existing_pipelines = await self.get_pipelines()
-            if len(existing_pipelines) >= max_pipelines:
-                raise ValueError(f'Maximum number of pipelines ({max_pipelines}) reached')
-
         pipeline_data['uuid'] = str(uuid.uuid4())
         pipeline_data['for_version'] = self.ap.ver_mgr.get_current_version()
         pipeline_data['stages'] = default_stage_order.copy()
@@ -159,60 +151,6 @@ 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"""
-        # Check limitation
-        limitation = self.ap.instance_config.data.get('system', {}).get('limitation', {})
-        max_pipelines = limitation.get('max_pipelines', -1)
-        if max_pipelines >= 0:
-            existing_pipelines = await self.get_pipelines()
-            if len(existing_pipelines) >= max_pipelines:
-                raise ValueError(f'Maximum number of pipelines ({max_pipelines}) reached')
-
-        # 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/api/http/service/provider.py

@@ -1,166 +0,0 @@
-from __future__ import annotations
-
-import uuid
-
-import sqlalchemy
-
-from ....core import app
-from ....entity.persistence import model as persistence_model
-
-
-class ModelProviderService:
-    """Service for managing model providers"""
-
-    ap: app.Application
-
-    def __init__(self, ap: app.Application) -> None:
-        self.ap = ap
-
-    async def get_providers(self) -> list[dict]:
-        """Get all providers"""
-        result = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_model.ModelProvider))
-        providers = result.all()
-        providers_list = []
-        for p in providers:
-            provider_dict = self.ap.persistence_mgr.serialize_model(persistence_model.ModelProvider, p)
-            # Parse api_keys if it's a JSON string
-            if isinstance(provider_dict.get('api_keys'), str):
-                import json
-
-                try:
-                    provider_dict['api_keys'] = json.loads(provider_dict['api_keys'])
-                except Exception:
-                    provider_dict['api_keys'] = []
-            providers_list.append(provider_dict)
-        return providers_list
-
-    async def get_provider(self, provider_uuid: str) -> dict | None:
-        """Get a single provider by UUID"""
-        result = await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.select(persistence_model.ModelProvider).where(
-                persistence_model.ModelProvider.uuid == provider_uuid
-            )
-        )
-        provider = result.first()
-        if provider is None:
-            return None
-        provider_dict = self.ap.persistence_mgr.serialize_model(persistence_model.ModelProvider, provider)
-        # Parse api_keys if it's a JSON string
-        if isinstance(provider_dict.get('api_keys'), str):
-            import json
-
-            try:
-                provider_dict['api_keys'] = json.loads(provider_dict['api_keys'])
-            except Exception:
-                provider_dict['api_keys'] = []
-        return provider_dict
-
-    async def create_provider(self, provider_data: dict) -> str:
-        """Create a new provider"""
-        provider_data['uuid'] = str(uuid.uuid4())
-        await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.insert(persistence_model.ModelProvider).values(**provider_data)
-        )
-
-        # load to runtime
-        runtime_provider = await self.ap.model_mgr.load_provider(provider_data)
-        self.ap.model_mgr.provider_dict[runtime_provider.provider_entity.uuid] = runtime_provider
-        return provider_data['uuid']
-
-    async def update_provider(self, provider_uuid: str, provider_data: dict) -> None:
-        """Update an existing provider"""
-        if 'uuid' in provider_data:
-            del provider_data['uuid']
-        await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.update(persistence_model.ModelProvider)
-            .where(persistence_model.ModelProvider.uuid == provider_uuid)
-            .values(**provider_data)
-        )
-        await self.ap.model_mgr.reload_provider(provider_uuid)
-
-    async def delete_provider(self, provider_uuid: str) -> None:
-        """Delete a provider (only if no models reference it)"""
-        # Check if any models use this provider
-        llm_result = await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.select(persistence_model.LLMModel).where(
-                persistence_model.LLMModel.provider_uuid == provider_uuid
-            )
-        )
-        if llm_result.first() is not None:
-            raise ValueError('Cannot delete provider: LLM models still reference it')
-
-        embedding_result = await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.select(persistence_model.EmbeddingModel).where(
-                persistence_model.EmbeddingModel.provider_uuid == provider_uuid
-            )
-        )
-        if embedding_result.first() is not None:
-            raise ValueError('Cannot delete provider: Embedding models still reference it')
-
-        await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.delete(persistence_model.ModelProvider).where(
-                persistence_model.ModelProvider.uuid == provider_uuid
-            )
-        )
-
-        await self.ap.model_mgr.remove_provider(provider_uuid)
-
-    async def get_provider_model_counts(self, provider_uuid: str) -> dict:
-        """Get count of models using this provider"""
-        llm_result = await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.select(sqlalchemy.func.count())
-            .select_from(persistence_model.LLMModel)
-            .where(persistence_model.LLMModel.provider_uuid == provider_uuid)
-        )
-        llm_count = llm_result.scalar() or 0
-
-        embedding_result = await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.select(sqlalchemy.func.count())
-            .select_from(persistence_model.EmbeddingModel)
-            .where(persistence_model.EmbeddingModel.provider_uuid == provider_uuid)
-        )
-        embedding_count = embedding_result.scalar() or 0
-
-        return {'llm_count': llm_count, 'embedding_count': embedding_count}
-
-    async def find_or_create_provider(self, requester: str, base_url: str, api_keys: list) -> str:
-        """Find existing provider or create new one"""
-        # Try to find existing provider with same config
-        result = await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.select(persistence_model.ModelProvider).where(
-                persistence_model.ModelProvider.requester == requester,
-                persistence_model.ModelProvider.base_url == base_url,
-            )
-        )
-        for provider in result.all():
-            if sorted(provider.api_keys or []) == sorted(api_keys or []):
-                return provider.uuid
-
-        # Create new provider
-        provider_name = requester
-        if base_url:
-            try:
-                from urllib.parse import urlparse
-
-                parsed = urlparse(base_url)
-                provider_name = parsed.netloc or requester
-            except Exception:
-                pass
-
-        return await self.create_provider(
-            {
-                'name': provider_name,
-                'requester': requester,
-                'base_url': base_url,
-                'api_keys': api_keys or [],
-            }
-        )
-
-    async def update_space_model_provider_api_keys(self, api_key: str) -> None:
-        """Update Space model provider API keys"""
-        await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.update(persistence_model.ModelProvider)
-            .where(persistence_model.ModelProvider.uuid == '00000000-0000-0000-0000-000000000000')
-            .values(api_keys=[api_key])
-        )
-        await self.ap.model_mgr.reload_provider('00000000-0000-0000-0000-000000000000')

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

@@ -1,189 +0,0 @@
-from __future__ import annotations
-
-from langbot.pkg.utils import httpclient
-import typing
-import datetime
-import time
-import sqlalchemy
-
-from ....core import app
-from ....entity.persistence import user
-from ....entity.dto.space_model import SpaceModel
-
-
-class SpaceService:
-    """Service for interacting with LangBot Space API"""
-
-    ap: app.Application
-    _credits_cache: typing.Dict[str, typing.Tuple[int, float]]  # {user_email: (credits, timestamp)}
-
-    def __init__(self, ap: app.Application) -> None:
-        self.ap = ap
-        self._credits_cache = {}
-
-    def _get_space_config(self) -> typing.Dict[str, str]:
-        """Get Space configuration from config file"""
-        space_config = self.ap.instance_config.data.get('space', {})
-        return {
-            'url': space_config.get('url', 'https://space.langbot.app'),
-            'oauth_authorize_url': space_config.get('oauth_authorize_url', 'https://space.langbot.app/auth/authorize'),
-        }
-
-    async def _get_user_by_email(self, user_email: str) -> user.User | None:
-        result = await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.select(user.User).where(user.User.user == user_email)
-        )
-        result_list = result.all()
-        return result_list[0] if result_list else None
-
-    async def _ensure_valid_token(self, user_email: str) -> str | None:
-        """Ensure access token is valid, refresh if expired. Returns valid access_token or None."""
-        user_obj = await self._get_user_by_email(user_email)
-        if not user_obj or user_obj.account_type != 'space':
-            return None
-
-        if not user_obj.space_access_token:
-            return None
-
-        # Check if token is expired (with 60s buffer)
-        if user_obj.space_access_token_expires_at:
-            if datetime.datetime.now() >= user_obj.space_access_token_expires_at - datetime.timedelta(seconds=60):
-                # Token expired, try to refresh
-                if user_obj.space_refresh_token:
-                    try:
-                        new_token = await self._refresh_and_save_token(user_obj)
-                        return new_token
-                    except Exception:
-                        return None
-                return None
-
-        return user_obj.space_access_token
-
-    async def _refresh_and_save_token(self, user_obj: user.User) -> str:
-        """Refresh token and save to database"""
-        token_data = await self.refresh_token(user_obj.space_refresh_token)
-        access_token = token_data.get('access_token')
-        expires_in = token_data.get('expires_in', 0)
-
-        if not access_token:
-            raise ValueError('Failed to refresh token')
-
-        expires_at = datetime.datetime.now() + datetime.timedelta(seconds=expires_in) if expires_in > 0 else None
-
-        await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.update(user.User)
-            .where(user.User.user == user_obj.user)
-            .values(
-                space_access_token=access_token,
-                space_access_token_expires_at=expires_at,
-            )
-        )
-
-        return access_token
-
-    # === Raw API calls (no token validation) ===
-
-    def get_oauth_authorize_url(self, redirect_uri: str, state: str = '') -> str:
-        """Get the Space OAuth authorization URL for redirect"""
-        space_config = self._get_space_config()
-        authorize_url = space_config['oauth_authorize_url']
-        params = f'redirect_uri={redirect_uri}'
-        if state:
-            params += f'&state={state}'
-        return f'{authorize_url}?{params}'
-
-    async def exchange_oauth_code(self, code: str) -> typing.Dict:
-        """Exchange OAuth authorization code for tokens"""
-        from langbot.pkg.utils import constants
-
-        space_config = self._get_space_config()
-        space_url = space_config['url']
-
-        session = httpclient.get_session()
-        async with session.post(
-            f'{space_url}/api/v1/accounts/oauth/token',
-            json={'code': code, 'instance_id': constants.instance_id},
-        ) as response:
-            if response.status != 200:
-                raise ValueError(f'Failed to exchange OAuth code: {await response.text()}')
-            data = await response.json()
-            if data.get('code') != 0:
-                raise ValueError(f'Failed to exchange OAuth code: {data.get("msg")}')
-            return data.get('data', {})
-
-    async def refresh_token(self, refresh_token: str) -> typing.Dict:
-        """Refresh Space access token"""
-        space_config = self._get_space_config()
-        space_url = space_config['url']
-
-        session = httpclient.get_session()
-        async with session.post(
-            f'{space_url}/api/v1/accounts/token/refresh', json={'refresh_token': refresh_token}
-        ) as response:
-            if response.status != 200:
-                raise ValueError(f'Failed to refresh token: {await response.text()}')
-            data = await response.json()
-            if data.get('code') != 0:
-                raise ValueError(f'Failed to refresh token: {data.get("msg")}')
-            return data.get('data', {})
-
-    async def get_user_info_raw(self, access_token: str) -> typing.Dict:
-        """Get user info from Space using access token (no validation)"""
-        space_config = self._get_space_config()
-        space_url = space_config['url']
-
-        session = httpclient.get_session()
-        async with session.get(
-            f'{space_url}/api/v1/accounts/me', headers={'Authorization': f'Bearer {access_token}'}
-        ) as response:
-            if response.status != 200:
-                raise ValueError(f'Failed to get user info: {await response.text()}')
-            data = await response.json()
-            if data.get('code') != 0:
-                raise ValueError(f'Failed to get user info: {data.get("msg")}')
-            return data.get('data', {})
-
-    # === API calls with token validation ===
-
-    async def get_user_info(self, user_email: str) -> typing.Dict | None:
-        """Get user info from Space (with token validation)"""
-        access_token = await self._ensure_valid_token(user_email)
-        if not access_token:
-            return None
-        return await self.get_user_info_raw(access_token)
-
-    async def get_credits(self, user_email: str, force_refresh: bool = False) -> int | None:
-        """Get Space credits for user with caching (60s TTL)"""
-        cache_ttl = 60
-
-        if not force_refresh and user_email in self._credits_cache:
-            credits, ts = self._credits_cache[user_email]
-            if time.time() - ts < cache_ttl:
-                return credits
-
-        try:
-            info = await self.get_user_info(user_email)
-            if info is None:
-                return None
-            credits = info.get('credits')
-            if credits is not None:
-                self._credits_cache[user_email] = (credits, time.time())
-            return credits
-        except Exception:
-            return self._credits_cache.get(user_email, (None, 0))[0]
-
-    async def get_models(self) -> typing.List[SpaceModel]:
-        """Get models from Space"""
-
-        space_config = self._get_space_config()
-        space_url = space_config['url']
-
-        session = httpclient.get_session()
-        async with session.get(f'{space_url}/api/v1/models') as response:
-            if response.status != 200:
-                raise ValueError(f'Failed to get models: {await response.text()}')
-            data = await response.json()
-            if data.get('code') != 0:
-                raise ValueError(f'Failed to get models: {data.get("msg")}')
-            models_data = data.get('data', {}).get('models', [])
-            return [SpaceModel.model_validate(model_dict) for model_dict in models_data]

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

@@ -4,22 +4,17 @@ import sqlalchemy
 import argon2
 import jwt
 import datetime
-import typing
-import asyncio
 
 from ....core import app
 from ....entity.persistence import user
 from ....utils import constants
-from ....entity.errors import account as account_errors
 
 
 class UserService:
     ap: app.Application
-    _create_user_lock: asyncio.Lock
 
     def __init__(self, ap: app.Application) -> None:
         self.ap = ap
-        self._create_user_lock = asyncio.Lock()
 
     async def is_initialized(self) -> bool:
         result = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(user.User).limit(1))
@@ -33,7 +28,7 @@ class UserService:
         hashed_password = ph.hash(password)
 
         await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.insert(user.User).values(user=user_email, password=hashed_password, account_type='local')
+            sqlalchemy.insert(user.User).values(user=user_email, password=hashed_password)
         )
 
     async def get_user_by_email(self, user_email: str) -> user.User | None:
@@ -44,15 +39,6 @@ class UserService:
         result_list = result.all()
         return result_list[0] if result_list is not None and len(result_list) > 0 else None
 
-    async def get_user_by_space_account_uuid(self, space_account_uuid: str) -> user.User | None:
-        """Get user by Space account UUID"""
-        result = await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.select(user.User).where(user.User.space_account_uuid == space_account_uuid)
-        )
-
-        result_list = result.all()
-        return result_list[0] if result_list is not None and len(result_list) > 0 else None
-
     async def authenticate(self, user_email: str, password: str) -> str | None:
         result = await self.ap.persistence_mgr.execute_async(
             sqlalchemy.select(user.User).where(user.User.user == user_email)
@@ -65,10 +51,6 @@ class UserService:
 
         user_obj = result_list[0]
 
-        # Check if this is a Space account
-        if user_obj.account_type == 'space':
-            raise ValueError('请使用 Space 账户登录')
-
         ph = argon2.PasswordHasher()
 
         ph.verify(user_obj.password, password)
@@ -108,10 +90,6 @@ class UserService:
         if user_obj is None:
             raise ValueError('User not found')
 
-        # Space accounts cannot change password locally
-        if user_obj.account_type == 'space':
-            raise ValueError('Space account cannot change password locally')
-
         ph.verify(user_obj.password, current_password)
 
         hashed_password = ph.hash(new_password)
@@ -119,183 +97,3 @@ class UserService:
         await self.ap.persistence_mgr.execute_async(
             sqlalchemy.update(user.User).where(user.User.user == user_email).values(password=hashed_password)
         )
-
-    # Space user management
-
-    async def create_or_update_space_user(
-        self,
-        space_account_uuid: str,
-        email: str,
-        access_token: str,
-        refresh_token: str,
-        api_key: str,
-        expires_in: int = 0,
-    ) -> user.User:
-        """Create or update a Space user account (only if system not initialized or user exists)"""
-        expires_at = datetime.datetime.now() + datetime.timedelta(seconds=expires_in) if expires_in > 0 else None
-
-        async with self._create_user_lock:
-            # Check if user with this Space UUID already exists
-            existing_user = await self.get_user_by_space_account_uuid(space_account_uuid)
-
-            if existing_user:
-                # Update existing user's tokens
-                await self.ap.persistence_mgr.execute_async(
-                    sqlalchemy.update(user.User)
-                    .where(user.User.space_account_uuid == space_account_uuid)
-                    .values(
-                        space_access_token=access_token,
-                        space_refresh_token=refresh_token,
-                        space_api_key=api_key,
-                        space_access_token_expires_at=expires_at,
-                    )
-                )
-                await self.ap.provider_service.update_space_model_provider_api_keys(api_key)
-                return await self.get_user_by_space_account_uuid(space_account_uuid)
-
-            # Check if user with same email exists
-            existing_email_user = await self.get_user_by_email(email)
-            if existing_email_user:
-                # Update existing user to link with Space account
-                await self.ap.persistence_mgr.execute_async(
-                    sqlalchemy.update(user.User)
-                    .where(user.User.user == email)
-                    .values(
-                        account_type='space',
-                        space_account_uuid=space_account_uuid,
-                        space_access_token=access_token,
-                        space_refresh_token=refresh_token,
-                        space_api_key=api_key,
-                        space_access_token_expires_at=expires_at,
-                    )
-                )
-                await self.ap.provider_service.update_space_model_provider_api_keys(api_key)
-                return await self.get_user_by_email(email)
-
-            # Check if system is already initialized
-            is_initialized = await self.is_initialized()
-            if is_initialized:
-                raise account_errors.AccountEmailMismatchError()
-
-            # Create new Space user (first time initialization)
-            await self.ap.persistence_mgr.execute_async(
-                sqlalchemy.insert(user.User).values(
-                    user=email,
-                    password='',  # Space users don't have local password
-                    account_type='space',
-                    space_account_uuid=space_account_uuid,
-                    space_access_token=access_token,
-                    space_refresh_token=refresh_token,
-                    space_api_key=api_key,
-                    space_access_token_expires_at=expires_at,
-                )
-            )
-            await self.ap.provider_service.update_space_model_provider_api_keys(api_key)
-
-            return await self.get_user_by_space_account_uuid(space_account_uuid)
-
-    async def authenticate_space_user(
-        self, access_token: str, refresh_token: str, expires_in: int = 0
-    ) -> typing.Tuple[str, user.User]:
-        """Authenticate with Space and return JWT token"""
-        # Get user info from Space using raw API (token just obtained, no need to validate)
-        user_info = await self.ap.space_service.get_user_info_raw(access_token)
-
-        account = user_info.get('account', {})
-        api_key = user_info.get('api_key', '')
-
-        space_account_uuid = account.get('uuid')
-        email = account.get('email')
-
-        if not space_account_uuid or not email:
-            raise ValueError('Invalid Space user info')
-
-        # Create or update Space user in local database
-        user_obj = await self.create_or_update_space_user(
-            space_account_uuid=space_account_uuid,
-            email=email,
-            access_token=access_token,
-            refresh_token=refresh_token,
-            api_key=api_key,
-            expires_in=expires_in,
-        )
-
-        # Generate JWT token
-        jwt_token = await self.generate_jwt_token(email)
-
-        return jwt_token, user_obj
-
-    async def get_first_user(self) -> user.User | None:
-        """Get the first user (for single-user mode)"""
-        result = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(user.User).limit(1))
-        result_list = result.all()
-        return result_list[0] if result_list else None
-
-    async def set_password(self, user_email: str, new_password: str, current_password: str | None = None) -> None:
-        """Set or change password for a user"""
-        ph = argon2.PasswordHasher()
-        user_obj = await self.get_user_by_email(user_email)
-
-        if user_obj is None:
-            raise ValueError('User not found')
-
-        # If user already has a password, verify current password
-        has_password = bool(user_obj.password and user_obj.password.strip())
-        if has_password:
-            if not current_password:
-                raise ValueError('Current password is required')
-            ph.verify(user_obj.password, current_password)
-
-        hashed_password = ph.hash(new_password)
-        await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.update(user.User).where(user.User.user == user_email).values(password=hashed_password)
-        )
-
-    async def bind_space_account(self, user_email: str, code: str) -> user.User:
-        """Bind Space account to existing local account"""
-        # Exchange code for tokens
-        token_data = await self.ap.space_service.exchange_oauth_code(code)
-        access_token = token_data.get('access_token')
-        refresh_token = token_data.get('refresh_token')
-        expires_in = token_data.get('expires_in', 0)
-
-        if not access_token:
-            raise ValueError('Failed to get access token from Space')
-
-        expires_at = datetime.datetime.now() + datetime.timedelta(seconds=expires_in) if expires_in > 0 else None
-
-        # Get Space user info (token just obtained, use raw API)
-        user_info = await self.ap.space_service.get_user_info_raw(access_token)
-        account = user_info.get('account', {})
-        api_key = user_info.get('api_key', '')
-
-        space_account_uuid = account.get('uuid')
-        space_email = account.get('email')
-
-        if not space_account_uuid or not space_email:
-            raise ValueError('Invalid Space user info')
-
-        # Check if this Space account is already bound to another user
-        existing_space_user = await self.get_user_by_space_account_uuid(space_account_uuid)
-        if existing_space_user and existing_space_user.user != user_email:
-            raise ValueError('This Space account is already bound to another user')
-
-        # Update local account to Space account
-        await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.update(user.User)
-            .where(user.User.user == user_email)
-            .values(
-                user=space_email,  # Update email to Space email
-                account_type='space',
-                space_account_uuid=space_account_uuid,
-                space_access_token=access_token,
-                space_refresh_token=refresh_token,
-                space_api_key=api_key,
-                space_access_token_expires_at=expires_at,
-            )
-        )
-
-        # Update Space model provider API keys
-        await self.ap.provider_service.update_space_model_provider_api_keys(api_key)
-
-        return await self.get_user_by_email(space_email)

src/langbot/pkg/core/app.py

@@ -9,39 +9,31 @@ from ..platform import botmgr as im_mgr
 from ..platform.webhook_pusher import WebhookPusher
 from ..provider.session import sessionmgr as llm_session_mgr
 from ..provider.modelmgr import modelmgr as llm_model_mgr
-
 from langbot.pkg.provider.tools import toolmgr as llm_tool_mgr
 from ..config import manager as config_mgr
 from ..command import cmdmgr
 from ..plugin import connector as plugin_connector
 from ..pipeline import pool
 from ..pipeline import controller, pipelinemgr
-from ..pipeline import aggregator as message_aggregator
 from ..utils import version as version_mgr, proxy as proxy_mgr
 from ..persistence import mgr as persistencemgr
 from ..api.http.controller import main as http_controller
 from ..api.http.service import user as user_service
-from ..api.http.service import space as space_service
 from ..api.http.service import model as model_service
-from ..api.http.service import provider as provider_service
 from ..api.http.service import pipeline as pipeline_service
 from ..api.http.service import bot as bot_service
 from ..api.http.service import knowledge as knowledge_service
 from ..api.http.service import mcp as mcp_service
 from ..api.http.service import apikey as apikey_service
 from ..api.http.service import webhook as webhook_service
-from ..api.http.service import monitoring as monitoring_service
-
+from ..api.http.service import external_kb as external_kb_service
 from ..discover import engine as discover_engine
 from ..storage import mgr as storagemgr
 from ..utils import logcache
 from . import taskmgr
 from . import entities as core_entities
 from ..rag.knowledge import kbmgr as rag_mgr
-from ..rag.service import RAGRuntimeService
 from ..vector import mgr as vectordb_mgr
-from ..telemetry import telemetry as telemetry_module
-from ..survey import manager as survey_module
 
 
 class Application:
@@ -65,7 +57,6 @@ class Application:
     model_mgr: llm_model_mgr.ModelManager = None
 
     rag_mgr: rag_mgr.RAGManager = None
-    rag_runtime_service: RAGRuntimeService = None
 
     # TODO move to pipeline
     tool_mgr: llm_tool_mgr.ToolManager = None
@@ -84,8 +75,6 @@ class Application:
 
     instance_config: config_mgr.ConfigManager = None
 
-    instance_id: config_mgr.ConfigManager = None  # used to identify the instance
-
     # ======= Metadata config manager =======
 
     sensitive_meta: config_mgr.ConfigManager = None
@@ -101,8 +90,6 @@ class Application:
 
     query_pool: pool.QueryPool = None
 
-    msg_aggregator: message_aggregator.MessageAggregator = None
-
     ctrl: controller.Controller = None
 
     pipeline_mgr: pipelinemgr.PipelineManager = None
@@ -127,32 +114,24 @@ class Application:
 
     user_service: user_service.UserService = None
 
-    space_service: space_service.SpaceService = None
-
     llm_model_service: model_service.LLMModelsService = None
 
     embedding_models_service: model_service.EmbeddingModelsService = None
 
-    provider_service: provider_service.ModelProviderService = None
-
     pipeline_service: pipeline_service.PipelineService = None
 
     bot_service: bot_service.BotService = None
 
     knowledge_service: knowledge_service.KnowledgeService = None
 
+    external_kb_service: external_kb_service.ExternalKBService = None
+
     mcp_service: mcp_service.MCPService = None
 
     apikey_service: apikey_service.ApiKeyService = None
 
     webhook_service: webhook_service.WebhookService = None
 
-    telemetry: telemetry_module.TelemetryManager = None
-
-    survey: survey_module.SurveyManager = None
-
-    monitoring_service: monitoring_service.MonitoringService = None
-
     def __init__(self):
         pass
 

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

@@ -1,4 +1,3 @@
-import importlib.util
 import pip
 import os
 from ...utils import pkgmgr
@@ -50,10 +49,9 @@ async def check_deps() -> list[str]:
 
     missing_deps = []
     for dep in required_deps:
-        # Use find_spec instead of __import__ to avoid actually loading
-        # all modules into memory. find_spec only checks if the module
-        # can be found, without executing module-level code.
-        if importlib.util.find_spec(dep) is None:
+        try:
+            __import__(dep)
+        except ImportError:
             missing_deps.append(dep)
     return missing_deps
 

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

@@ -1,5 +1,4 @@
 import logging
-import logging.handlers
 import sys
 import time
 
@@ -16,10 +15,6 @@ 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
@@ -48,17 +43,9 @@ 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,
-        rotating_file_handler,
+        logging.FileHandler(log_file_name, encoding='utf-8'),
     ]
     log_handlers += extra_handlers if extra_handlers is not None else []
 

src/langbot/pkg/core/migrations/m041_dingtalk_card_autolayout_config.py

@@ -1,17 +0,0 @@
-from __future__ import annotations
-
-from .. import migration
-
-
-@migration.migration_class('dingtalk_card_auto_layout', 41)
-class DingTalkCardAutoLayoutMigration(migration.Migration):
-    """迁移"""
-
-    async def need_migrate(self) -> bool:
-        """判断当前环境是否需要运行此迁移"""
-        return True
-
-    async def run(self):
-        """执行迁移"""
-        self.ap.platform_cfg.data['platform-adapters']['app']['dingtalk']['card_auto_layout'] = False
-        await self.ap.platform_cfg.dump_config()

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

@@ -5,36 +5,30 @@ import asyncio
 from .. import stage, app
 from ...utils import version, proxy
 from ...pipeline import pool, controller, pipelinemgr
-from ...pipeline import aggregator as message_aggregator
 from ...plugin import connector as plugin_connector
 from ...command import cmdmgr
 from ...provider.session import sessionmgr as llm_session_mgr
 from ...provider.modelmgr import modelmgr as llm_model_mgr
 from ...provider.tools import toolmgr as llm_tool_mgr
 from ...rag.knowledge import kbmgr as rag_mgr
-from ...rag.service import RAGRuntimeService
 from ...platform import botmgr as im_mgr
 from ...platform.webhook_pusher import WebhookPusher
 from ...persistence import mgr as persistencemgr
 from ...api.http.controller import main as http_controller
 from ...api.http.service import user as user_service
-from ...api.http.service import space as space_service
 from ...api.http.service import model as model_service
-from ...api.http.service import provider as provider_service
 from ...api.http.service import pipeline as pipeline_service
 from ...api.http.service import bot as bot_service
 from ...api.http.service import knowledge as knowledge_service
 from ...api.http.service import mcp as mcp_service
 from ...api.http.service import apikey as apikey_service
 from ...api.http.service import webhook as webhook_service
-from ...api.http.service import monitoring as monitoring_service
+from ...api.http.service import external_kb as external_kb_service
 from ...discover import engine as discover_engine
 from ...storage import mgr as storagemgr
 from ...utils import logcache
 from ...vector import mgr as vectordb_mgr
 from .. import taskmgr
-from ...telemetry import telemetry as telemetry_module
-from ...survey import manager as survey_module
 
 
 @stage.stage_class('BuildAppStage')
@@ -49,39 +43,6 @@ class BuildAppStage(stage.BootingStage):
         discover.discover_blueprint('templates/components.yaml')
         ap.discover = discover
 
-        user_service_inst = user_service.UserService(ap)
-        ap.user_service = user_service_inst
-
-        space_service_inst = space_service.SpaceService(ap)
-        ap.space_service = space_service_inst
-
-        llm_model_service_inst = model_service.LLMModelsService(ap)
-        ap.llm_model_service = llm_model_service_inst
-
-        embedding_models_service_inst = model_service.EmbeddingModelsService(ap)
-        ap.embedding_models_service = embedding_models_service_inst
-
-        provider_service_inst = provider_service.ModelProviderService(ap)
-        ap.provider_service = provider_service_inst
-
-        pipeline_service_inst = pipeline_service.PipelineService(ap)
-        ap.pipeline_service = pipeline_service_inst
-
-        bot_service_inst = bot_service.BotService(ap)
-        ap.bot_service = bot_service_inst
-
-        knowledge_service_inst = knowledge_service.KnowledgeService(ap)
-        ap.knowledge_service = knowledge_service_inst
-
-        mcp_service_inst = mcp_service.MCPService(ap)
-        ap.mcp_service = mcp_service_inst
-
-        apikey_service_inst = apikey_service.ApiKeyService(ap)
-        ap.apikey_service = apikey_service_inst
-
-        webhook_service_inst = webhook_service.WebhookService(ap)
-        ap.webhook_service = webhook_service_inst
-
         proxy_mgr = proxy.ProxyManager(ap)
         await proxy_mgr.initialize()
         ap.proxy_mgr = proxy_mgr
@@ -103,23 +64,13 @@ class BuildAppStage(stage.BootingStage):
         ap.persistence_mgr = persistence_mgr_inst
         await persistence_mgr_inst.initialize()
 
-        # Telemetry manager: attach to app so other components can call via self.ap.telemetry
-        telemetry_inst = telemetry_module.TelemetryManager(ap)
-        await telemetry_inst.initialize()
-        ap.telemetry = telemetry_inst
-
-        # Survey manager
-        survey_inst = survey_module.SurveyManager(ap)
-        await survey_inst.initialize()
-        ap.survey = survey_inst
-
         cmd_mgr_inst = cmdmgr.CommandManager(ap)
         await cmd_mgr_inst.initialize()
         ap.cmd_mgr = cmd_mgr_inst
 
         llm_model_mgr_inst = llm_model_mgr.ModelManager(ap)
-        ap.model_mgr = llm_model_mgr_inst
         await llm_model_mgr_inst.initialize()
+        ap.model_mgr = llm_model_mgr_inst
 
         llm_session_mgr_inst = llm_session_mgr.SessionManager(ap)
         await llm_session_mgr_inst.initialize()
@@ -141,17 +92,10 @@ class BuildAppStage(stage.BootingStage):
         await pipeline_mgr.initialize()
         ap.pipeline_mgr = pipeline_mgr
 
-        # Initialize message aggregator (after pipeline_mgr, as it needs pipeline config)
-        msg_aggregator_inst = message_aggregator.MessageAggregator(ap)
-        ap.msg_aggregator = msg_aggregator_inst
-
         rag_mgr_inst = rag_mgr.RAGManager(ap)
         await rag_mgr_inst.initialize()
         ap.rag_mgr = rag_mgr_inst
 
-        # Initialize RAG Runtime Service for plugins
-        ap.rag_runtime_service = RAGRuntimeService(ap)
-
         # 初始化向量数据库管理器
         vectordb_mgr_inst = vectordb_mgr.VectorDBManager(ap)
         await vectordb_mgr_inst.initialize()
@@ -161,8 +105,35 @@ class BuildAppStage(stage.BootingStage):
         await http_ctrl.initialize()
         ap.http_ctrl = http_ctrl
 
-        monitoring_service_inst = monitoring_service.MonitoringService(ap)
-        ap.monitoring_service = monitoring_service_inst
+        user_service_inst = user_service.UserService(ap)
+        ap.user_service = user_service_inst
+
+        llm_model_service_inst = model_service.LLMModelsService(ap)
+        ap.llm_model_service = llm_model_service_inst
+
+        embedding_models_service_inst = model_service.EmbeddingModelsService(ap)
+        ap.embedding_models_service = embedding_models_service_inst
+
+        pipeline_service_inst = pipeline_service.PipelineService(ap)
+        ap.pipeline_service = pipeline_service_inst
+
+        bot_service_inst = bot_service.BotService(ap)
+        ap.bot_service = bot_service_inst
+
+        knowledge_service_inst = knowledge_service.KnowledgeService(ap)
+        ap.knowledge_service = knowledge_service_inst
+
+        external_kb_service_inst = external_kb_service.ExternalKBService(ap)
+        ap.external_kb_service = external_kb_service_inst
+
+        mcp_service_inst = mcp_service.MCPService(ap)
+        ap.mcp_service = mcp_service_inst
+
+        apikey_service_inst = apikey_service.ApiKeyService(ap)
+        ap.apikey_service = apikey_service_inst
+
+        webhook_service_inst = webhook_service.WebhookService(ap)
+        ap.webhook_service = webhook_service_inst
 
         async def runtime_disconnect_callback(connector: plugin_connector.PluginRuntimeConnector) -> None:
             await asyncio.sleep(3)

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

@@ -2,11 +2,8 @@ from __future__ import annotations
 
 import os
 from typing import Any
-from langbot.pkg.utils import constants
 import yaml
 import importlib.resources as resources
-import uuid
-import time
 
 from .. import stage, app
 from ..bootutils import config
@@ -145,24 +142,6 @@ class LoadConfigStage(stage.BootingStage):
 
         await ap.instance_config.dump_config()
 
-        # load or generate instance id
-        ap.instance_id = await config.load_json_config(
-            'data/labels/instance_id.json',
-            template_data={
-                'instance_id': f'instance_{str(uuid.uuid4())}',
-                'instance_create_ts': int(time.time()),
-            },
-            completion=False,
-        )
-
-        constants.instance_id = ap.instance_id.data['instance_id']
-        constants.edition = ap.instance_config.data.get('system', {}).get('edition', 'community')
-
-        print(f'LangBot instance id: {constants.instance_id}')
-        print(f'LangBot edition: {constants.edition}')
-
-        await ap.instance_id.dump_config()
-
         ap.sensitive_meta = await config.load_json_config(
             'data/metadata/sensitive-words.json',
             'metadata/sensitive-words.json',

src/langbot/pkg/entity/dto/space_model.py

@@ -1,49 +0,0 @@
-# [
-#   {
-#     "uuid": "7652ebdb-54dc-412c-a830-e9268ac88471",
-#     "model_id": "claude-opus-4-5-20251101",
-#     "display_name": {
-#       "en_US": "claude-opus-4-5-20251101",
-#       "zh_Hans": "claude-opus-4-5-20251101"
-#     },
-#     "description": {},
-#     "provider": "anthropic",
-#     "category": "chat",
-#     "icon_url": "Claude.Color",
-#     "tags": {},
-#     "is_featured": true,
-#     "featured_order": 999,
-#     "model_ratio": 2.5,
-#     "completion_ratio": 5,
-#     "quota_type": 0,
-#     "model_price": 0,
-#     "input_credits": 500,
-#     "output_credits": 2500,
-#     "vendor_id": 1,
-#     "vendor_name": "Anthropic",
-#     "vendor_icon": "Claude.Color",
-#     "supported_endpoints": [
-#       "anthropic",
-#       "openai"
-#     ],
-#     "status": "active",
-#     "metadata": null,
-#     "created_at": "2025-12-30T22:23:38.337207+08:00",
-#     "updated_at": "2025-12-30T22:23:38.337207+08:00"
-#   }
-# ]
-
-import pydantic
-
-
-class SpaceModel(pydantic.BaseModel):
-    uuid: str
-    model_id: str
-    provider: str
-    category: str  # chat / embedding
-    llm_abilities: list[str] | None = None
-    is_featured: bool = False
-    featured_order: int = 0
-    status: str
-    created_at: str | None = None
-    updated_at: str | None = None

src/langbot/pkg/entity/errors/account.py

@@ -1,6 +0,0 @@
-from __future__ import annotations
-
-
-class AccountEmailMismatchError(Exception):
-    def __str__(self):
-        return 'Account email mismatch'

src/langbot/pkg/entity/errors/provider.py

@@ -7,11 +7,3 @@ class RequesterNotFoundError(Exception):
 
     def __str__(self):
         return f'Requester {self.requester_name} not found'
-
-
-class ProviderNotFoundError(Exception):
-    def __init__(self, provider_name: str):
-        self.provider_name = provider_name
-
-    def __str__(self):
-        return f'Provider {self.provider_name} not found'

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

@@ -9,7 +9,7 @@ class MCPServer(Base):
     uuid = sqlalchemy.Column(sqlalchemy.String(255), primary_key=True, unique=True)
     name = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
     enable = sqlalchemy.Column(sqlalchemy.Boolean, nullable=False, default=False)
-    mode = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)  # stdio, sse, http
+    mode = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)  # stdio, sse
     extra_args = sqlalchemy.Column(sqlalchemy.JSON, nullable=False, default={})
     created_at = sqlalchemy.Column(sqlalchemy.DateTime, nullable=False, server_default=sqlalchemy.func.now())
     updated_at = sqlalchemy.Column(

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

@@ -3,25 +3,6 @@ import sqlalchemy
 from .base import Base
 
 
-class ModelProvider(Base):
-    """Model provider"""
-
-    __tablename__ = 'model_providers'
-
-    uuid = sqlalchemy.Column(sqlalchemy.String(255), primary_key=True, unique=True)
-    name = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
-    requester = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
-    base_url = sqlalchemy.Column(sqlalchemy.String(512), nullable=False)
-    api_keys = sqlalchemy.Column(sqlalchemy.JSON, nullable=False, default=[])
-    created_at = sqlalchemy.Column(sqlalchemy.DateTime, nullable=False, server_default=sqlalchemy.func.now())
-    updated_at = sqlalchemy.Column(
-        sqlalchemy.DateTime,
-        nullable=False,
-        server_default=sqlalchemy.func.now(),
-        onupdate=sqlalchemy.func.now(),
-    )
-
-
 class LLMModel(Base):
     """LLM model"""
 
@@ -29,10 +10,12 @@ class LLMModel(Base):
 
     uuid = sqlalchemy.Column(sqlalchemy.String(255), primary_key=True, unique=True)
     name = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
-    provider_uuid = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
+    description = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
+    requester = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
+    requester_config = sqlalchemy.Column(sqlalchemy.JSON, nullable=False, default={})
+    api_keys = sqlalchemy.Column(sqlalchemy.JSON, nullable=False)
     abilities = sqlalchemy.Column(sqlalchemy.JSON, nullable=False, default=[])
     extra_args = sqlalchemy.Column(sqlalchemy.JSON, nullable=False, default={})
-    prefered_ranking = sqlalchemy.Column(sqlalchemy.Integer, nullable=False, default=0)
     created_at = sqlalchemy.Column(sqlalchemy.DateTime, nullable=False, server_default=sqlalchemy.func.now())
     updated_at = sqlalchemy.Column(
         sqlalchemy.DateTime,
@@ -43,15 +26,17 @@ class LLMModel(Base):
 
 
 class EmbeddingModel(Base):
-    """Embedding model"""
+    """Embedding 模型"""
 
     __tablename__ = 'embedding_models'
 
     uuid = sqlalchemy.Column(sqlalchemy.String(255), primary_key=True, unique=True)
     name = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
-    provider_uuid = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
+    description = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
+    requester = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
+    requester_config = sqlalchemy.Column(sqlalchemy.JSON, nullable=False, default={})
+    api_keys = sqlalchemy.Column(sqlalchemy.JSON, nullable=False)
     extra_args = sqlalchemy.Column(sqlalchemy.JSON, nullable=False, default={})
-    prefered_ranking = sqlalchemy.Column(sqlalchemy.Integer, nullable=False, default=0)
     created_at = sqlalchemy.Column(sqlalchemy.DateTime, nullable=False, server_default=sqlalchemy.func.now())
     updated_at = sqlalchemy.Column(
         sqlalchemy.DateTime,

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

@@ -1,108 +0,0 @@
-import sqlalchemy
-
-from .base import Base
-
-
-class MonitoringMessage(Base):
-    """Monitoring message records"""
-
-    __tablename__ = 'monitoring_messages'
-
-    id = sqlalchemy.Column(sqlalchemy.String(255), primary_key=True)
-    timestamp = sqlalchemy.Column(sqlalchemy.DateTime, nullable=False, index=True)
-    bot_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=False, index=True)
-    bot_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
-    pipeline_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=False, index=True)
-    pipeline_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
-    message_content = sqlalchemy.Column(sqlalchemy.Text, nullable=False)
-    session_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=False, index=True)
-    status = sqlalchemy.Column(sqlalchemy.String(50), nullable=False)  # success, error, pending
-    level = sqlalchemy.Column(sqlalchemy.String(50), nullable=False)  # info, warning, error, debug
-    platform = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
-    user_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
-    user_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)  # User display name
-    runner_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)  # Runner name for this query
-    variables = sqlalchemy.Column(sqlalchemy.Text, nullable=True)  # Query variables as JSON string
-    role = sqlalchemy.Column(sqlalchemy.String(50), nullable=True, default='user')  # user, assistant
-
-
-class MonitoringLLMCall(Base):
-    """LLM call records"""
-
-    __tablename__ = 'monitoring_llm_calls'
-
-    id = sqlalchemy.Column(sqlalchemy.String(255), primary_key=True)
-    timestamp = sqlalchemy.Column(sqlalchemy.DateTime, nullable=False, index=True)
-    model_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
-    input_tokens = sqlalchemy.Column(sqlalchemy.Integer, nullable=False)
-    output_tokens = sqlalchemy.Column(sqlalchemy.Integer, nullable=False)
-    total_tokens = sqlalchemy.Column(sqlalchemy.Integer, nullable=False)
-    duration = sqlalchemy.Column(sqlalchemy.Integer, nullable=False)  # milliseconds
-    cost = sqlalchemy.Column(sqlalchemy.Float, nullable=True)
-    status = sqlalchemy.Column(sqlalchemy.String(50), nullable=False)  # success, error
-    bot_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=False, index=True)
-    bot_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
-    pipeline_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=False, index=True)
-    pipeline_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
-    session_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
-    error_message = sqlalchemy.Column(sqlalchemy.Text, nullable=True)
-    message_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True, index=True)  # Associated message ID
-
-
-class MonitoringSession(Base):
-    """Session tracking records"""
-
-    __tablename__ = 'monitoring_sessions'
-
-    session_id = sqlalchemy.Column(sqlalchemy.String(255), primary_key=True)
-    bot_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=False, index=True)
-    bot_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
-    pipeline_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=False, index=True)
-    pipeline_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
-    message_count = sqlalchemy.Column(sqlalchemy.Integer, nullable=False, default=0)
-    start_time = sqlalchemy.Column(sqlalchemy.DateTime, nullable=False, index=True)
-    last_activity = sqlalchemy.Column(sqlalchemy.DateTime, nullable=False, index=True)
-    is_active = sqlalchemy.Column(sqlalchemy.Boolean, nullable=False, default=True, index=True)
-    platform = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
-    user_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
-    user_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)  # User display name
-
-
-class MonitoringError(Base):
-    """Error log records"""
-
-    __tablename__ = 'monitoring_errors'
-
-    id = sqlalchemy.Column(sqlalchemy.String(255), primary_key=True)
-    timestamp = sqlalchemy.Column(sqlalchemy.DateTime, nullable=False, index=True)
-    error_type = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
-    error_message = sqlalchemy.Column(sqlalchemy.Text, nullable=False)
-    bot_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=False, index=True)
-    bot_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
-    pipeline_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=False, index=True)
-    pipeline_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
-    session_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
-    stack_trace = sqlalchemy.Column(sqlalchemy.Text, nullable=True)
-    message_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True, index=True)  # Associated message ID
-
-
-class MonitoringEmbeddingCall(Base):
-    """Embedding call records"""
-
-    __tablename__ = 'monitoring_embedding_calls'
-
-    id = sqlalchemy.Column(sqlalchemy.String(255), primary_key=True)
-    timestamp = sqlalchemy.Column(sqlalchemy.DateTime, nullable=False, index=True)
-    model_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
-    prompt_tokens = sqlalchemy.Column(sqlalchemy.Integer, nullable=False)
-    total_tokens = sqlalchemy.Column(sqlalchemy.Integer, nullable=False)
-    duration = sqlalchemy.Column(sqlalchemy.Integer, nullable=False)  # milliseconds
-    input_count = sqlalchemy.Column(sqlalchemy.Integer, nullable=False)  # Number of input texts
-    status = sqlalchemy.Column(sqlalchemy.String(50), nullable=False)  # success, error
-    error_message = sqlalchemy.Column(sqlalchemy.Text, nullable=True)
-    # Optional context fields
-    knowledge_base_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True, index=True)
-    query_text = sqlalchemy.Column(sqlalchemy.Text, nullable=True)  # For retrieval calls
-    session_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True, index=True)
-    message_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True, index=True)
-    call_type = sqlalchemy.Column(sqlalchemy.String(50), nullable=True)  # embedding, retrieve

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

@@ -11,7 +11,6 @@ class LegacyPipeline(Base):
     uuid = sqlalchemy.Column(sqlalchemy.String(255), primary_key=True, unique=True)
     name = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
     description = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
-    emoji = sqlalchemy.Column(sqlalchemy.String(10), nullable=True, default='⚙️')
     created_at = sqlalchemy.Column(sqlalchemy.DateTime, nullable=False, server_default=sqlalchemy.func.now())
     updated_at = sqlalchemy.Column(
         sqlalchemy.DateTime,

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

@@ -7,24 +7,9 @@ class KnowledgeBase(Base):
     uuid = sqlalchemy.Column(sqlalchemy.String(255), primary_key=True, unique=True)
     name = sqlalchemy.Column(sqlalchemy.String, index=True)
     description = sqlalchemy.Column(sqlalchemy.Text)
-    emoji = sqlalchemy.Column(sqlalchemy.String(10), nullable=True, default='📚')
     created_at = sqlalchemy.Column(sqlalchemy.DateTime, default=sqlalchemy.func.now())
-    updated_at = sqlalchemy.Column(sqlalchemy.DateTime, default=sqlalchemy.func.now(), onupdate=sqlalchemy.func.now())
-    # New fields for plugin-based RAG
-    knowledge_engine_plugin_id = sqlalchemy.Column(sqlalchemy.String, nullable=True)
-    collection_id = sqlalchemy.Column(sqlalchemy.String, nullable=True)
-    creation_settings = sqlalchemy.Column(sqlalchemy.JSON, nullable=True, default=None)
-    retrieval_settings = sqlalchemy.Column(sqlalchemy.JSON, nullable=True, default=None)
-
-    # Field sets for different operations
-    MUTABLE_FIELDS = {'name', 'description', 'retrieval_settings'}
-    """Fields that can be updated after creation."""
-
-    CREATE_FIELDS = MUTABLE_FIELDS | {'uuid', 'knowledge_engine_plugin_id', 'collection_id', 'creation_settings'}
-    """Fields used when creating a new knowledge base."""
-
-    ALL_DB_FIELDS = CREATE_FIELDS | {'emoji', 'created_at', 'updated_at'}
-    """All fields stored in database (for loading from DB row)."""
+    embedding_model_uuid = sqlalchemy.Column(sqlalchemy.String, default='')
+    top_k = sqlalchemy.Column(sqlalchemy.Integer, default=5)
 
 
 class File(Base):
@@ -42,3 +27,15 @@ class Chunk(Base):
     uuid = sqlalchemy.Column(sqlalchemy.String(255), primary_key=True, unique=True)
     file_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
     text = sqlalchemy.Column(sqlalchemy.Text)
+
+
+class ExternalKnowledgeBase(Base):
+    __tablename__ = 'external_knowledge_bases'
+    uuid = sqlalchemy.Column(sqlalchemy.String(255), primary_key=True, unique=True)
+    name = sqlalchemy.Column(sqlalchemy.String, index=True)
+    description = sqlalchemy.Column(sqlalchemy.Text)
+    plugin_author = sqlalchemy.Column(sqlalchemy.String, nullable=False)
+    plugin_name = sqlalchemy.Column(sqlalchemy.String, nullable=False)
+    retriever_name = sqlalchemy.Column(sqlalchemy.String, nullable=False)
+    retriever_config = sqlalchemy.Column(sqlalchemy.JSON, nullable=False, default={})
+    created_at = sqlalchemy.Column(sqlalchemy.DateTime, default=sqlalchemy.func.now())

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

@@ -9,17 +9,6 @@ class User(Base):
     id = sqlalchemy.Column(sqlalchemy.Integer, primary_key=True)
     user = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
     password = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
-
-    # Account type: 'local' (default) or 'space'
-    account_type = sqlalchemy.Column(sqlalchemy.String(32), nullable=False, server_default='local')
-
-    # Space account fields (nullable, only used when account_type='space')
-    space_account_uuid = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
-    space_access_token = sqlalchemy.Column(sqlalchemy.Text, nullable=True)
-    space_refresh_token = sqlalchemy.Column(sqlalchemy.Text, nullable=True)
-    space_access_token_expires_at = sqlalchemy.Column(sqlalchemy.DateTime, nullable=True)
-    space_api_key = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
-
     created_at = sqlalchemy.Column(sqlalchemy.DateTime, nullable=False, server_default=sqlalchemy.func.now())
     updated_at = sqlalchemy.Column(
         sqlalchemy.DateTime,

src/langbot/pkg/persistence/mgr.py

@@ -9,7 +9,7 @@ import sqlalchemy.ext.asyncio as sqlalchemy_asyncio
 import sqlalchemy
 
 from . import database, migration
-from ..entity.persistence import base, pipeline, metadata, model as persistence_model
+from ..entity.persistence import base, pipeline, metadata
 from ..entity import persistence
 from ..core import app
 from ..utils import constants, importutil
@@ -79,7 +79,6 @@ class PersistenceManager:
             self.ap.logger.info(f'Successfully upgraded database to version {last_migration_number}.')
 
         await self.write_default_pipeline()
-        await self.write_space_model_providers()
 
     async def create_tables(self):
         # create tables
@@ -124,42 +123,7 @@ class PersistenceManager:
 
             await self.execute_async(sqlalchemy.insert(pipeline.LegacyPipeline).values(pipeline_data))
 
-    async def write_space_model_providers(self):
-        space_models_gateway_api_url = self.ap.instance_config.data.get('space', {}).get(
-            'models_gateway_api_url', 'https://api.langbot.cloud/v1'
-        )
-
-        # write space model providers
-        result = await self.execute_async(
-            sqlalchemy.select(persistence_model.ModelProvider).where(
-                persistence_model.ModelProvider.requester == 'space-chat-completions'
-            )
-        )
-        exists_space_chat_completions_model_provider = result.first()
-
-        # api keys will be set/updated when the oauth callback
-        if exists_space_chat_completions_model_provider is None:
-            self.ap.logger.info('Creating space model providers...')
-            space_chat_completions_model_provider = {
-                'uuid': '00000000-0000-0000-0000-000000000000',
-                'name': 'LangBot Models',
-                'requester': 'space-chat-completions',
-                'base_url': space_models_gateway_api_url,
-                'api_keys': [],
-            }
-
-            await self.execute_async(
-                sqlalchemy.insert(persistence_model.ModelProvider).values(space_chat_completions_model_provider)
-            )
-        else:
-            if exists_space_chat_completions_model_provider.base_url != space_models_gateway_api_url:
-                await self.execute_async(
-                    sqlalchemy.update(persistence_model.ModelProvider)
-                    .where(persistence_model.ModelProvider.uuid == exists_space_chat_completions_model_provider.uuid)
-                    .values({'base_url': space_models_gateway_api_url})
-                )
-
-    # =================================
+        # =================================
 
     async def execute_async(self, *args, **kwargs) -> sqlalchemy.engine.cursor.CursorResult:
         async with self.get_db_engine().connect() as conn:

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

@@ -1,7 +1,8 @@
 from .. import migration
 
 import sqlalchemy
-import json
+
+from ...entity.persistence import pipeline as persistence_pipeline
 
 
 @migration.migration_class(2)
@@ -10,45 +11,30 @@ class DBMigrateCombineQuoteMsgConfig(migration.DBMigration):
 
     async def upgrade(self):
         """Upgrade"""
-        # Read all pipelines using raw SQL
-        result = await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.text('SELECT uuid, config FROM legacy_pipelines')
-        )
-        pipelines = result.fetchall()
+        # read all pipelines
+        pipelines = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_pipeline.LegacyPipeline))
 
-        current_version = self.ap.ver_mgr.get_current_version()
+        for pipeline in pipelines:
+            serialized_pipeline = self.ap.persistence_mgr.serialize_model(persistence_pipeline.LegacyPipeline, pipeline)
 
-        for pipeline_row in pipelines:
-            uuid = pipeline_row[0]
-            config = json.loads(pipeline_row[1]) if isinstance(pipeline_row[1], str) else pipeline_row[1]
+            config = serialized_pipeline['config']
 
-            # Ensure 'trigger' exists
-            if 'trigger' not in config:
-                config['trigger'] = {}
-
-            # Ensure 'misc' exists in 'trigger'
             if 'misc' not in config['trigger']:
                 config['trigger']['misc'] = {}
 
-            # Add 'combine-quote-message' if not exists
             if 'combine-quote-message' not in config['trigger']['misc']:
                 config['trigger']['misc']['combine-quote-message'] = False
 
-            # Update using raw SQL with compatibility for both SQLite and PostgreSQL
-            if self.ap.persistence_mgr.db.name == 'postgresql':
-                await self.ap.persistence_mgr.execute_async(
-                    sqlalchemy.text(
-                        'UPDATE legacy_pipelines SET config = :config::jsonb, for_version = :for_version WHERE uuid = :uuid'
-                    ),
-                    {'config': json.dumps(config), 'for_version': current_version, 'uuid': uuid},
-                )
-            else:
-                await self.ap.persistence_mgr.execute_async(
-                    sqlalchemy.text(
-                        'UPDATE legacy_pipelines SET config = :config, for_version = :for_version WHERE uuid = :uuid'
-                    ),
-                    {'config': json.dumps(config), 'for_version': current_version, 'uuid': uuid},
+            await self.ap.persistence_mgr.execute_async(
+                sqlalchemy.update(persistence_pipeline.LegacyPipeline)
+                .where(persistence_pipeline.LegacyPipeline.uuid == serialized_pipeline['uuid'])
+                .values(
+                    {
+                        'config': config,
+                        'for_version': self.ap.ver_mgr.get_current_version(),
+                    }
                 )
+            )
 
     async def downgrade(self):
         """Downgrade"""

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

@@ -1,7 +1,8 @@
 from .. import migration
 
 import sqlalchemy
-import json
+
+from ...entity.persistence import pipeline as persistence_pipeline
 
 
 @migration.migration_class(3)
@@ -10,23 +11,14 @@ class DBMigrateN8nConfig(migration.DBMigration):
 
     async def upgrade(self):
         """Upgrade"""
-        # Read all pipelines using raw SQL
-        result = await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.text('SELECT uuid, config FROM legacy_pipelines')
-        )
-        pipelines = result.fetchall()
+        # read all pipelines
+        pipelines = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_pipeline.LegacyPipeline))
 
-        current_version = self.ap.ver_mgr.get_current_version()
+        for pipeline in pipelines:
+            serialized_pipeline = self.ap.persistence_mgr.serialize_model(persistence_pipeline.LegacyPipeline, pipeline)
 
-        for pipeline_row in pipelines:
-            uuid = pipeline_row[0]
-            config = json.loads(pipeline_row[1]) if isinstance(pipeline_row[1], str) else pipeline_row[1]
+            config = serialized_pipeline['config']
 
-            # Ensure 'ai' exists
-            if 'ai' not in config:
-                config['ai'] = {}
-
-            # Add 'n8n-service-api' if not exists
             if 'n8n-service-api' not in config['ai']:
                 config['ai']['n8n-service-api'] = {
                     'webhook-url': 'http://your-n8n-webhook-url',
@@ -41,21 +33,16 @@ class DBMigrateN8nConfig(migration.DBMigration):
                     'output-key': 'response',
                 }
 
-            # Update using raw SQL with compatibility for both SQLite and PostgreSQL
-            if self.ap.persistence_mgr.db.name == 'postgresql':
-                await self.ap.persistence_mgr.execute_async(
-                    sqlalchemy.text(
-                        'UPDATE legacy_pipelines SET config = :config::jsonb, for_version = :for_version WHERE uuid = :uuid'
-                    ),
-                    {'config': json.dumps(config), 'for_version': current_version, 'uuid': uuid},
-                )
-            else:
-                await self.ap.persistence_mgr.execute_async(
-                    sqlalchemy.text(
-                        'UPDATE legacy_pipelines SET config = :config, for_version = :for_version WHERE uuid = :uuid'
-                    ),
-                    {'config': json.dumps(config), 'for_version': current_version, 'uuid': uuid},
+            await self.ap.persistence_mgr.execute_async(
+                sqlalchemy.update(persistence_pipeline.LegacyPipeline)
+                .where(persistence_pipeline.LegacyPipeline.uuid == serialized_pipeline['uuid'])
+                .values(
+                    {
+                        'config': config,
+                        'for_version': self.ap.ver_mgr.get_current_version(),
+                    }
                 )
+            )
 
     async def downgrade(self):
         """Downgrade"""

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

@@ -1,7 +1,8 @@
 from .. import migration
 
 import sqlalchemy
-import json
+
+from ...entity.persistence import pipeline as persistence_pipeline
 
 
 @migration.migration_class(4)
@@ -10,43 +11,27 @@ class DBMigrateRAGKBUUID(migration.DBMigration):
 
     async def upgrade(self):
         """升级"""
-        # Read all pipelines using raw SQL
-        result = await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.text('SELECT uuid, config FROM legacy_pipelines')
-        )
-        pipelines = result.fetchall()
+        # read all pipelines
+        pipelines = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_pipeline.LegacyPipeline))
 
-        current_version = self.ap.ver_mgr.get_current_version()
+        for pipeline in pipelines:
+            serialized_pipeline = self.ap.persistence_mgr.serialize_model(persistence_pipeline.LegacyPipeline, pipeline)
 
-        for pipeline_row in pipelines:
-            uuid = pipeline_row[0]
-            config = json.loads(pipeline_row[1]) if isinstance(pipeline_row[1], str) else pipeline_row[1]
+            config = serialized_pipeline['config']
 
-            # Ensure nested structure exists
-            if 'ai' not in config:
-                config['ai'] = {}
-            if 'local-agent' not in config['ai']:
-                config['ai']['local-agent'] = {}
-
-            # Add 'knowledge-base' if not exists
             if 'knowledge-base' not in config['ai']['local-agent']:
                 config['ai']['local-agent']['knowledge-base'] = ''
 
-            # Update using raw SQL with compatibility for both SQLite and PostgreSQL
-            if self.ap.persistence_mgr.db.name == 'postgresql':
-                await self.ap.persistence_mgr.execute_async(
-                    sqlalchemy.text(
-                        'UPDATE legacy_pipelines SET config = :config::jsonb, for_version = :for_version WHERE uuid = :uuid'
-                    ),
-                    {'config': json.dumps(config), 'for_version': current_version, 'uuid': uuid},
-                )
-            else:
-                await self.ap.persistence_mgr.execute_async(
-                    sqlalchemy.text(
-                        'UPDATE legacy_pipelines SET config = :config, for_version = :for_version WHERE uuid = :uuid'
-                    ),
-                    {'config': json.dumps(config), 'for_version': current_version, 'uuid': uuid},
+            await self.ap.persistence_mgr.execute_async(
+                sqlalchemy.update(persistence_pipeline.LegacyPipeline)
+                .where(persistence_pipeline.LegacyPipeline.uuid == serialized_pipeline['uuid'])
+                .values(
+                    {
+                        'config': config,
+                        'for_version': self.ap.ver_mgr.get_current_version(),
+                    }
                 )
+            )
 
     async def downgrade(self):
         """降级"""

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

@@ -1,7 +1,8 @@
 from .. import migration
 
 import sqlalchemy
-import json
+
+from ...entity.persistence import pipeline as persistence_pipeline
 
 
 @migration.migration_class(5)
@@ -10,43 +11,27 @@ class DBMigratePipelineRemoveCotConfig(migration.DBMigration):
 
     async def upgrade(self):
         """Upgrade"""
-        # Read all pipelines using raw SQL
-        result = await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.text('SELECT uuid, config FROM legacy_pipelines')
-        )
-        pipelines = result.fetchall()
+        # read all pipelines
+        pipelines = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_pipeline.LegacyPipeline))
 
-        current_version = self.ap.ver_mgr.get_current_version()
+        for pipeline in pipelines:
+            serialized_pipeline = self.ap.persistence_mgr.serialize_model(persistence_pipeline.LegacyPipeline, pipeline)
 
-        for pipeline_row in pipelines:
-            uuid = pipeline_row[0]
-            config = json.loads(pipeline_row[1]) if isinstance(pipeline_row[1], str) else pipeline_row[1]
+            config = serialized_pipeline['config']
 
-            # Ensure nested structure exists
-            if 'output' not in config:
-                config['output'] = {}
-            if 'misc' not in config['output']:
-                config['output']['misc'] = {}
-
-            # Add 'remove-think' if not exists
             if 'remove-think' not in config['output']['misc']:
                 config['output']['misc']['remove-think'] = False
 
-            # Update using raw SQL with compatibility for both SQLite and PostgreSQL
-            if self.ap.persistence_mgr.db.name == 'postgresql':
-                await self.ap.persistence_mgr.execute_async(
-                    sqlalchemy.text(
-                        'UPDATE legacy_pipelines SET config = :config::jsonb, for_version = :for_version WHERE uuid = :uuid'
-                    ),
-                    {'config': json.dumps(config), 'for_version': current_version, 'uuid': uuid},
-                )
-            else:
-                await self.ap.persistence_mgr.execute_async(
-                    sqlalchemy.text(
-                        'UPDATE legacy_pipelines SET config = :config, for_version = :for_version WHERE uuid = :uuid'
-                    ),
-                    {'config': json.dumps(config), 'for_version': current_version, 'uuid': uuid},
+            await self.ap.persistence_mgr.execute_async(
+                sqlalchemy.update(persistence_pipeline.LegacyPipeline)
+                .where(persistence_pipeline.LegacyPipeline.uuid == serialized_pipeline['uuid'])
+                .values(
+                    {
+                        'config': config,
+                        'for_version': self.ap.ver_mgr.get_current_version(),
+                    }
                 )
+            )
 
     async def downgrade(self):
         """Downgrade"""

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

@@ -1,7 +1,8 @@
 from .. import migration
 
 import sqlalchemy
-import json
+
+from ...entity.persistence import pipeline as persistence_pipeline
 
 
 @migration.migration_class(6)
@@ -10,23 +11,14 @@ class DBMigrateLangflowApiConfig(migration.DBMigration):
 
     async def upgrade(self):
         """Upgrade"""
-        # Read all pipelines using raw SQL
-        result = await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.text('SELECT uuid, config FROM legacy_pipelines')
-        )
-        pipelines = result.fetchall()
+        # read all pipelines
+        pipelines = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_pipeline.LegacyPipeline))
 
-        current_version = self.ap.ver_mgr.get_current_version()
+        for pipeline in pipelines:
+            serialized_pipeline = self.ap.persistence_mgr.serialize_model(persistence_pipeline.LegacyPipeline, pipeline)
 
-        for pipeline_row in pipelines:
-            uuid = pipeline_row[0]
-            config = json.loads(pipeline_row[1]) if isinstance(pipeline_row[1], str) else pipeline_row[1]
+            config = serialized_pipeline['config']
 
-            # Ensure 'ai' exists
-            if 'ai' not in config:
-                config['ai'] = {}
-
-            # Add 'langflow-api' if not exists
             if 'langflow-api' not in config['ai']:
                 config['ai']['langflow-api'] = {
                     'base-url': 'http://localhost:7860',
@@ -37,21 +29,16 @@ class DBMigrateLangflowApiConfig(migration.DBMigration):
                     'tweaks': '{}',
                 }
 
-            # Update using raw SQL with compatibility for both SQLite and PostgreSQL
-            if self.ap.persistence_mgr.db.name == 'postgresql':
-                await self.ap.persistence_mgr.execute_async(
-                    sqlalchemy.text(
-                        'UPDATE legacy_pipelines SET config = :config::jsonb, for_version = :for_version WHERE uuid = :uuid'
-                    ),
-                    {'config': json.dumps(config), 'for_version': current_version, 'uuid': uuid},
-                )
-            else:
-                await self.ap.persistence_mgr.execute_async(
-                    sqlalchemy.text(
-                        'UPDATE legacy_pipelines SET config = :config, for_version = :for_version WHERE uuid = :uuid'
-                    ),
-                    {'config': json.dumps(config), 'for_version': current_version, 'uuid': uuid},
+            await self.ap.persistence_mgr.execute_async(
+                sqlalchemy.update(persistence_pipeline.LegacyPipeline)
+                .where(persistence_pipeline.LegacyPipeline.uuid == serialized_pipeline['uuid'])
+                .values(
+                    {
+                        'config': config,
+                        'for_version': self.ap.ver_mgr.get_current_version(),
+                    }
                 )
+            )
 
     async def downgrade(self):
         """Downgrade"""

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

@@ -1,7 +1,8 @@
 from .. import migration
 
 import sqlalchemy
-import json
+
+from ...entity.persistence import pipeline as persistence_pipeline
 
 
 @migration.migration_class(10)
@@ -10,20 +11,16 @@ class DBMigratePipelineMultiKnowledgeBase(migration.DBMigration):
 
     async def upgrade(self):
         """Upgrade"""
-        # Read all pipelines using raw SQL
-        result = await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.text('SELECT uuid, config FROM legacy_pipelines')
-        )
-        pipelines = result.fetchall()
+        # read all pipelines
+        pipelines = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_pipeline.LegacyPipeline))
 
-        current_version = self.ap.ver_mgr.get_current_version()
+        for pipeline in pipelines:
+            serialized_pipeline = self.ap.persistence_mgr.serialize_model(persistence_pipeline.LegacyPipeline, pipeline)
 
-        for pipeline_row in pipelines:
-            uuid = pipeline_row[0]
-            config = json.loads(pipeline_row[1]) if isinstance(pipeline_row[1], str) else pipeline_row[1]
+            config = serialized_pipeline['config']
 
             # Convert knowledge-base from string to array
-            if 'ai' in config and 'local-agent' in config['ai']:
+            if 'local-agent' in config['ai']:
                 current_kb = config['ai']['local-agent'].get('knowledge-base', '')
 
                 # If it's already a list, skip
@@ -40,38 +37,29 @@ class DBMigratePipelineMultiKnowledgeBase(migration.DBMigration):
                 if 'knowledge-base' in config['ai']['local-agent']:
                     del config['ai']['local-agent']['knowledge-base']
 
-                # Update using raw SQL with compatibility for both SQLite and PostgreSQL
-                if self.ap.persistence_mgr.db.name == 'postgresql':
-                    await self.ap.persistence_mgr.execute_async(
-                        sqlalchemy.text(
-                            'UPDATE legacy_pipelines SET config = :config::jsonb, for_version = :for_version WHERE uuid = :uuid'
-                        ),
-                        {'config': json.dumps(config), 'for_version': current_version, 'uuid': uuid},
-                    )
-                else:
-                    await self.ap.persistence_mgr.execute_async(
-                        sqlalchemy.text(
-                            'UPDATE legacy_pipelines SET config = :config, for_version = :for_version WHERE uuid = :uuid'
-                        ),
-                        {'config': json.dumps(config), 'for_version': current_version, 'uuid': uuid},
-                    )
+            await self.ap.persistence_mgr.execute_async(
+                sqlalchemy.update(persistence_pipeline.LegacyPipeline)
+                .where(persistence_pipeline.LegacyPipeline.uuid == serialized_pipeline['uuid'])
+                .values(
+                    {
+                        'config': config,
+                        'for_version': self.ap.ver_mgr.get_current_version(),
+                    }
+                )
+            )
 
     async def downgrade(self):
         """Downgrade"""
-        # Read all pipelines using raw SQL
-        result = await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.text('SELECT uuid, config FROM legacy_pipelines')
-        )
-        pipelines = result.fetchall()
+        # read all pipelines
+        pipelines = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_pipeline.LegacyPipeline))
 
-        current_version = self.ap.ver_mgr.get_current_version()
+        for pipeline in pipelines:
+            serialized_pipeline = self.ap.persistence_mgr.serialize_model(persistence_pipeline.LegacyPipeline, pipeline)
 
-        for pipeline_row in pipelines:
-            uuid = pipeline_row[0]
-            config = json.loads(pipeline_row[1]) if isinstance(pipeline_row[1], str) else pipeline_row[1]
+            config = serialized_pipeline['config']
 
             # Convert knowledge-bases from array back to string
-            if 'ai' in config and 'local-agent' in config['ai']:
+            if 'local-agent' in config['ai']:
                 current_kbs = config['ai']['local-agent'].get('knowledge-bases', [])
 
                 # If it's already a string, skip
@@ -88,18 +76,13 @@ class DBMigratePipelineMultiKnowledgeBase(migration.DBMigration):
                 if 'knowledge-bases' in config['ai']['local-agent']:
                     del config['ai']['local-agent']['knowledge-bases']
 
-                # Update using raw SQL with compatibility for both SQLite and PostgreSQL
-                if self.ap.persistence_mgr.db.name == 'postgresql':
-                    await self.ap.persistence_mgr.execute_async(
-                        sqlalchemy.text(
-                            'UPDATE legacy_pipelines SET config = :config::jsonb, for_version = :for_version WHERE uuid = :uuid'
-                        ),
-                        {'config': json.dumps(config), 'for_version': current_version, 'uuid': uuid},
-                    )
-                else:
-                    await self.ap.persistence_mgr.execute_async(
-                        sqlalchemy.text(
-                            'UPDATE legacy_pipelines SET config = :config, for_version = :for_version WHERE uuid = :uuid'
-                        ),
-                        {'config': json.dumps(config), 'for_version': current_version, 'uuid': uuid},
-                    )
+            await self.ap.persistence_mgr.execute_async(
+                sqlalchemy.update(persistence_pipeline.LegacyPipeline)
+                .where(persistence_pipeline.LegacyPipeline.uuid == serialized_pipeline['uuid'])
+                .values(
+                    {
+                        'config': config,
+                        'for_version': self.ap.ver_mgr.get_current_version(),
+                    }
+                )
+            )

src/langbot/pkg/persistence/migrations/dbm011_dify_base_prompt_config.py

@@ -1,7 +1,8 @@
 from .. import migration
 
 import sqlalchemy
-import json
+
+from ...entity.persistence import pipeline as persistence_pipeline
 
 
 @migration.migration_class(11)
@@ -10,45 +11,29 @@ class DBMigrateDifyApiConfig(migration.DBMigration):
 
     async def upgrade(self):
         """Upgrade"""
-        # Read all pipelines using raw SQL
-        result = await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.text('SELECT uuid, config FROM legacy_pipelines')
-        )
-        pipelines = result.fetchall()
+        # read all pipelines
+        pipelines = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_pipeline.LegacyPipeline))
 
-        current_version = self.ap.ver_mgr.get_current_version()
+        for pipeline in pipelines:
+            serialized_pipeline = self.ap.persistence_mgr.serialize_model(persistence_pipeline.LegacyPipeline, pipeline)
 
-        for pipeline_row in pipelines:
-            uuid = pipeline_row[0]
-            config = json.loads(pipeline_row[1]) if isinstance(pipeline_row[1], str) else pipeline_row[1]
+            config = serialized_pipeline['config']
 
-            # Ensure nested structure exists
-            if 'ai' not in config:
-                config['ai'] = {}
-            if 'dify-service-api' not in config['ai']:
-                config['ai']['dify-service-api'] = {}
-
-            # Add 'base-prompt' if not exists
             if 'base-prompt' not in config['ai']['dify-service-api']:
                 config['ai']['dify-service-api']['base-prompt'] = (
                     'When the file content is readable, please read the content of this file. When the file is an image, describe the content of this image.',
                 )
 
-            # Update using raw SQL with compatibility for both SQLite and PostgreSQL
-            if self.ap.persistence_mgr.db.name == 'postgresql':
-                await self.ap.persistence_mgr.execute_async(
-                    sqlalchemy.text(
-                        'UPDATE legacy_pipelines SET config = :config::jsonb, for_version = :for_version WHERE uuid = :uuid'
-                    ),
-                    {'config': json.dumps(config), 'for_version': current_version, 'uuid': uuid},
-                )
-            else:
-                await self.ap.persistence_mgr.execute_async(
-                    sqlalchemy.text(
-                        'UPDATE legacy_pipelines SET config = :config, for_version = :for_version WHERE uuid = :uuid'
-                    ),
-                    {'config': json.dumps(config), 'for_version': current_version, 'uuid': uuid},
+            await self.ap.persistence_mgr.execute_async(
+                sqlalchemy.update(persistence_pipeline.LegacyPipeline)
+                .where(persistence_pipeline.LegacyPipeline.uuid == serialized_pipeline['uuid'])
+                .values(
+                    {
+                        'config': config,
+                        'for_version': self.ap.ver_mgr.get_current_version(),
+                    }
                 )
+            )
 
     async def downgrade(self):
         """Downgrade"""

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

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

src/langbot/pkg/persistence/migrations/dbm013_knowledge_base_updated_at.py

@@ -1,49 +0,0 @@
-import sqlalchemy
-from .. import migration
-
-
-@migration.migration_class(13)
-class DBMigrateKnowledgeBaseUpdatedAt(migration.DBMigration):
-    """Add updated_at field to knowledge_bases table"""
-
-    async def upgrade(self):
-        """Upgrade"""
-        # Get all column names from the table
-        columns = []
-
-        if self.ap.persistence_mgr.db.name == 'postgresql':
-            result = await self.ap.persistence_mgr.execute_async(
-                sqlalchemy.text(
-                    "SELECT column_name FROM information_schema.columns WHERE table_name = 'knowledge_bases';"
-                )
-            )
-            all_result = result.fetchall()
-            columns = [row[0] for row in all_result]
-        else:
-            result = await self.ap.persistence_mgr.execute_async(sqlalchemy.text('PRAGMA table_info(knowledge_bases);'))
-            all_result = result.fetchall()
-            columns = [row[1] for row in all_result]
-
-        # Check and add updated_at column
-        if 'updated_at' not in columns:
-            if self.ap.persistence_mgr.db.name == 'postgresql':
-                await self.ap.persistence_mgr.execute_async(
-                    sqlalchemy.text(
-                        'ALTER TABLE knowledge_bases ADD COLUMN updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP'
-                    )
-                )
-            else:
-                # SQLite doesn't support DEFAULT CURRENT_TIMESTAMP in ALTER TABLE
-                # Add column without default first
-                await self.ap.persistence_mgr.execute_async(
-                    sqlalchemy.text('ALTER TABLE knowledge_bases ADD COLUMN updated_at DATETIME')
-                )
-
-            # Set initial updated_at values to created_at for existing records
-            await self.ap.persistence_mgr.execute_async(
-                sqlalchemy.text('UPDATE knowledge_bases SET updated_at = created_at WHERE updated_at IS NULL')
-            )
-
-    async def downgrade(self):
-        """Downgrade"""
-        pass

src/langbot/pkg/persistence/migrations/dbm014_space_account_support.py

@@ -1,94 +0,0 @@
-import sqlalchemy
-from .. import migration
-
-
-@migration.migration_class(14)
-class DBMigrateSpaceAccountSupport(migration.DBMigration):
-    """Add Space account support fields to users table"""
-
-    async def upgrade(self):
-        """Upgrade"""
-        # Get all column names from the users table
-        columns = []
-
-        if self.ap.persistence_mgr.db.name == 'postgresql':
-            result = await self.ap.persistence_mgr.execute_async(
-                sqlalchemy.text("SELECT column_name FROM information_schema.columns WHERE table_name = 'users';")
-            )
-            all_result = result.fetchall()
-            columns = [row[0] for row in all_result]
-        else:
-            result = await self.ap.persistence_mgr.execute_async(sqlalchemy.text('PRAGMA table_info(users);'))
-            all_result = result.fetchall()
-            columns = [row[1] for row in all_result]
-
-        # Add account_type column
-        if 'account_type' not in columns:
-            if self.ap.persistence_mgr.db.name == 'postgresql':
-                await self.ap.persistence_mgr.execute_async(
-                    sqlalchemy.text("ALTER TABLE users ADD COLUMN account_type VARCHAR(32) DEFAULT 'local' NOT NULL")
-                )
-            else:
-                await self.ap.persistence_mgr.execute_async(
-                    sqlalchemy.text("ALTER TABLE users ADD COLUMN account_type VARCHAR(32) DEFAULT 'local' NOT NULL")
-                )
-
-        # Add space_account_uuid column
-        if 'space_account_uuid' not in columns:
-            if self.ap.persistence_mgr.db.name == 'postgresql':
-                await self.ap.persistence_mgr.execute_async(
-                    sqlalchemy.text('ALTER TABLE users ADD COLUMN space_account_uuid VARCHAR(255)')
-                )
-            else:
-                await self.ap.persistence_mgr.execute_async(
-                    sqlalchemy.text('ALTER TABLE users ADD COLUMN space_account_uuid VARCHAR(255)')
-                )
-
-        # Add space_access_token column
-        if 'space_access_token' not in columns:
-            if self.ap.persistence_mgr.db.name == 'postgresql':
-                await self.ap.persistence_mgr.execute_async(
-                    sqlalchemy.text('ALTER TABLE users ADD COLUMN space_access_token TEXT')
-                )
-            else:
-                await self.ap.persistence_mgr.execute_async(
-                    sqlalchemy.text('ALTER TABLE users ADD COLUMN space_access_token TEXT')
-                )
-
-        # Add space_refresh_token column
-        if 'space_refresh_token' not in columns:
-            if self.ap.persistence_mgr.db.name == 'postgresql':
-                await self.ap.persistence_mgr.execute_async(
-                    sqlalchemy.text('ALTER TABLE users ADD COLUMN space_refresh_token TEXT')
-                )
-            else:
-                await self.ap.persistence_mgr.execute_async(
-                    sqlalchemy.text('ALTER TABLE users ADD COLUMN space_refresh_token TEXT')
-                )
-
-        # Add space_access_token_expires_at column
-        if 'space_access_token_expires_at' not in columns:
-            if self.ap.persistence_mgr.db.name == 'postgresql':
-                await self.ap.persistence_mgr.execute_async(
-                    sqlalchemy.text('ALTER TABLE users ADD COLUMN space_access_token_expires_at TIMESTAMP')
-                )
-
-            else:
-                await self.ap.persistence_mgr.execute_async(
-                    sqlalchemy.text('ALTER TABLE users ADD COLUMN space_access_token_expires_at DATETIME')
-                )
-
-        # Add space_api_key column
-        if 'space_api_key' not in columns:
-            if self.ap.persistence_mgr.db.name == 'postgresql':
-                await self.ap.persistence_mgr.execute_async(
-                    sqlalchemy.text('ALTER TABLE users ADD COLUMN space_api_key VARCHAR(255)')
-                )
-            else:
-                await self.ap.persistence_mgr.execute_async(
-                    sqlalchemy.text('ALTER TABLE users ADD COLUMN space_api_key VARCHAR(255)')
-                )
-
-    async def downgrade(self):
-        """Downgrade"""
-        pass

src/langbot/pkg/persistence/migrations/dbm015_model_source_tracking.py

@@ -1,15 +0,0 @@
-from .. import migration
-
-
-# this is a deprecated migration
-@migration.migration_class(15)
-class DBMigrateModelSourceTracking(migration.DBMigration):
-    """Add source tracking fields to models tables for Space integration"""
-
-    async def upgrade(self):
-        """Upgrade"""
-        pass
-
-    async def downgrade(self):
-        """Downgrade"""
-        pass

src/langbot/pkg/persistence/migrations/dbm016_model_provider_refactor.py

@@ -1,305 +0,0 @@
-import uuid as uuid_lib
-
-import sqlalchemy
-from .. import migration
-
-
-@migration.migration_class(16)
-class DBMigrateModelProviderRefactor(migration.DBMigration):
-    """Refactor model structure: create providers from existing models and update references"""
-
-    async def upgrade(self):
-        """Upgrade"""
-        # Step 1: Create model_providers table if not exists
-        await self._create_providers_table()
-
-        # Step 2: Migrate existing models to use providers
-        await self._migrate_llm_models()
-        await self._migrate_embedding_models()
-
-        # Step 3: Remove deprecated columns
-        await self._cleanup_columns()
-
-    async def _create_providers_table(self):
-        """Create model_providers table"""
-        if self.ap.persistence_mgr.db.name == 'postgresql':
-            await self.ap.persistence_mgr.execute_async(
-                sqlalchemy.text("""
-                    CREATE TABLE IF NOT EXISTS model_providers (
-                        uuid VARCHAR(255) PRIMARY KEY,
-                        name VARCHAR(255) NOT NULL,
-                        requester VARCHAR(255) NOT NULL,
-                        base_url VARCHAR(512) NOT NULL,
-                        api_keys JSONB NOT NULL DEFAULT '[]',
-                        created_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP,
-                        updated_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
-                    )
-                """)
-            )
-        else:
-            await self.ap.persistence_mgr.execute_async(
-                sqlalchemy.text("""
-                    CREATE TABLE IF NOT EXISTS model_providers (
-                        uuid VARCHAR(255) PRIMARY KEY,
-                        name VARCHAR(255) NOT NULL,
-                        requester VARCHAR(255) NOT NULL,
-                        base_url VARCHAR(512) NOT NULL,
-                        api_keys JSON NOT NULL DEFAULT '[]',
-                        created_at DATETIME NOT NULL DEFAULT CURRENT_TIMESTAMP,
-                        updated_at DATETIME NOT NULL DEFAULT CURRENT_TIMESTAMP
-                    )
-                """)
-            )
-
-    async def _migrate_llm_models(self):
-        """Migrate LLM models to use providers"""
-        llm_columns = await self._get_columns('llm_models')
-
-        # Add provider_uuid column if not exists
-        if 'provider_uuid' not in llm_columns:
-            await self.ap.persistence_mgr.execute_async(
-                sqlalchemy.text('ALTER TABLE llm_models ADD COLUMN provider_uuid VARCHAR(255)')
-            )
-
-        # Add prefered_ranking column if not exists
-        if 'prefered_ranking' not in llm_columns:
-            await self.ap.persistence_mgr.execute_async(
-                sqlalchemy.text('ALTER TABLE llm_models ADD COLUMN prefered_ranking INTEGER NOT NULL DEFAULT 0')
-            )
-
-        # Only migrate if old columns exist
-        if 'requester' not in llm_columns:
-            return
-
-        # Get all LLM models with old structure
-        result = await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.text('SELECT uuid, name, requester, requester_config, api_keys FROM llm_models')
-        )
-        models = result.fetchall()
-
-        # Create providers and update models
-        provider_cache = {}  # (requester, base_url, api_keys_str) -> provider_uuid
-
-        for model in models:
-            model_uuid, model_name, requester, requester_config, api_keys = model
-
-            # Extract base_url from requester_config
-            base_url = ''
-            if requester_config:
-                if isinstance(requester_config, str):
-                    import json
-
-                    requester_config = json.loads(requester_config)
-                base_url = requester_config.get('base_url', '') or requester_config.get('base-url', '')
-
-            # Parse api_keys if it's a string
-            if isinstance(api_keys, str):
-                import json
-
-                try:
-                    api_keys = json.loads(api_keys)
-                except Exception:
-                    api_keys = []
-            if not api_keys:
-                api_keys = []
-
-            # Create cache key
-            api_keys_str = str(sorted(api_keys)) if api_keys else '[]'
-            cache_key = (requester, base_url, api_keys_str)
-
-            if cache_key in provider_cache:
-                provider_uuid = provider_cache[cache_key]
-            else:
-                # Create new provider
-                provider_uuid = str(uuid_lib.uuid4())
-                provider_name = f'{requester}'
-                if base_url:
-                    # Extract domain for name
-                    try:
-                        from urllib.parse import urlparse
-
-                        parsed = urlparse(base_url)
-                        provider_name = parsed.netloc or requester
-                    except Exception:
-                        pass
-
-                import json
-
-                api_keys_json = json.dumps(api_keys) if api_keys else '[]'
-
-                await self.ap.persistence_mgr.execute_async(
-                    sqlalchemy.text("""
-                        INSERT INTO model_providers (uuid, name, requester, base_url, api_keys)
-                        VALUES (:uuid, :name, :requester, :base_url, :api_keys)
-                    """),
-                    {
-                        'uuid': provider_uuid,
-                        'name': provider_name,
-                        'requester': requester,
-                        'base_url': base_url,
-                        'api_keys': api_keys_json,
-                    },
-                )
-                provider_cache[cache_key] = provider_uuid
-
-            # Update model with provider_uuid
-            await self.ap.persistence_mgr.execute_async(
-                sqlalchemy.text('UPDATE llm_models SET provider_uuid = :provider_uuid WHERE uuid = :uuid'),
-                {'provider_uuid': provider_uuid, 'uuid': model_uuid},
-            )
-
-    async def _migrate_embedding_models(self):
-        """Migrate embedding models to use providers"""
-        embedding_columns = await self._get_columns('embedding_models')
-
-        # Add provider_uuid column if not exists
-        if 'provider_uuid' not in embedding_columns:
-            await self.ap.persistence_mgr.execute_async(
-                sqlalchemy.text('ALTER TABLE embedding_models ADD COLUMN provider_uuid VARCHAR(255)')
-            )
-
-        # Add prefered_ranking column if not exists
-        if 'prefered_ranking' not in embedding_columns:
-            await self.ap.persistence_mgr.execute_async(
-                sqlalchemy.text('ALTER TABLE embedding_models ADD COLUMN prefered_ranking INTEGER NOT NULL DEFAULT 0')
-            )
-
-        # Only migrate if old columns exist
-        if 'requester' not in embedding_columns:
-            return
-
-        # Get all embedding models with old structure
-        result = await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.text('SELECT uuid, name, requester, requester_config, api_keys FROM embedding_models')
-        )
-        models = result.fetchall()
-
-        # Get existing providers
-        provider_result = await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.text('SELECT uuid, requester, base_url, api_keys FROM model_providers')
-        )
-        existing_providers = provider_result.fetchall()
-
-        provider_cache = {}
-        for p in existing_providers:
-            p_uuid, p_requester, p_base_url, p_api_keys = p
-            api_keys_str = str(sorted(p_api_keys)) if p_api_keys else '[]'
-            provider_cache[(p_requester, p_base_url, api_keys_str)] = p_uuid
-
-        for model in models:
-            model_uuid, model_name, requester, requester_config, api_keys = model
-
-            base_url = ''
-            if requester_config:
-                if isinstance(requester_config, str):
-                    import json
-
-                    requester_config = json.loads(requester_config)
-                base_url = requester_config.get('base_url', '') or requester_config.get('base-url', '')
-
-            # Parse api_keys if it's a string
-            if isinstance(api_keys, str):
-                import json
-
-                try:
-                    api_keys = json.loads(api_keys)
-                except Exception:
-                    api_keys = []
-            if not api_keys:
-                api_keys = []
-
-            api_keys_str = str(sorted(api_keys)) if api_keys else '[]'
-            cache_key = (requester, base_url, api_keys_str)
-
-            if cache_key in provider_cache:
-                provider_uuid = provider_cache[cache_key]
-            else:
-                provider_uuid = str(uuid_lib.uuid4())
-                provider_name = f'{requester}'
-                if base_url:
-                    try:
-                        from urllib.parse import urlparse
-
-                        parsed = urlparse(base_url)
-                        provider_name = parsed.netloc or requester
-                    except Exception:
-                        pass
-
-                import json
-
-                api_keys_json = json.dumps(api_keys) if api_keys else '[]'
-
-                await self.ap.persistence_mgr.execute_async(
-                    sqlalchemy.text("""
-                        INSERT INTO model_providers (uuid, name, requester, base_url, api_keys)
-                        VALUES (:uuid, :name, :requester, :base_url, :api_keys)
-                    """),
-                    {
-                        'uuid': provider_uuid,
-                        'name': provider_name,
-                        'requester': requester,
-                        'base_url': base_url,
-                        'api_keys': api_keys_json,
-                    },
-                )
-                provider_cache[cache_key] = provider_uuid
-
-            await self.ap.persistence_mgr.execute_async(
-                sqlalchemy.text('UPDATE embedding_models SET provider_uuid = :provider_uuid WHERE uuid = :uuid'),
-                {'provider_uuid': provider_uuid, 'uuid': model_uuid},
-            )
-
-    async def _cleanup_columns(self):
-        """Remove deprecated columns from model tables"""
-
-        llm_columns = await self._get_columns('llm_models')
-        deprecated_llm_cols = ['requester', 'requester_config', 'api_keys', 'description', 'source', 'space_model_id']
-        for col in deprecated_llm_cols:
-            if col in llm_columns:
-                if self.ap.persistence_mgr.db.name == 'postgresql':
-                    await self.ap.persistence_mgr.execute_async(
-                        sqlalchemy.text(f'ALTER TABLE llm_models DROP COLUMN IF EXISTS {col}')
-                    )
-                else:
-                    await self.ap.persistence_mgr.execute_async(
-                        sqlalchemy.text(f'ALTER TABLE llm_models DROP COLUMN {col}')
-                    )
-
-        embedding_columns = await self._get_columns('embedding_models')
-        deprecated_embedding_cols = [
-            'requester',
-            'requester_config',
-            'api_keys',
-            'description',
-            'source',
-            'space_model_id',
-        ]
-        for col in deprecated_embedding_cols:
-            if col in embedding_columns:
-                if self.ap.persistence_mgr.db.name == 'postgresql':
-                    await self.ap.persistence_mgr.execute_async(
-                        sqlalchemy.text(f'ALTER TABLE embedding_models DROP COLUMN IF EXISTS {col}')
-                    )
-                else:
-                    await self.ap.persistence_mgr.execute_async(
-                        sqlalchemy.text(f'ALTER TABLE embedding_models DROP COLUMN {col}')
-                    )
-
-    async def _get_columns(self, table_name: str) -> list:
-        """Get column names for a table"""
-        if self.ap.persistence_mgr.db.name == 'postgresql':
-            result = await self.ap.persistence_mgr.execute_async(
-                sqlalchemy.text(
-                    f"SELECT column_name FROM information_schema.columns WHERE table_name = '{table_name}';"
-                )
-            )
-            all_result = result.fetchall()
-            return [row[0] for row in all_result]
-        else:
-            result = await self.ap.persistence_mgr.execute_async(sqlalchemy.text(f'PRAGMA table_info({table_name});'))
-            all_result = result.fetchall()
-            return [row[1] for row in all_result]
-
-    async def downgrade(self):
-        """Downgrade"""
-        pass

src/langbot/pkg/persistence/migrations/dbm017_move_cloud_service_url.py

@@ -1,25 +0,0 @@
-from .. import migration
-
-
-@migration.migration_class(17)
-class MoveCloudServiceUrl(migration.DBMigration):
-    """迁移云服务 URL 配置"""
-
-    async def upgrade(self):
-        """升级"""
-        if 'space' not in self.ap.instance_config.data:
-            self.ap.instance_config.data['space'] = {
-                'url': 'https://space.langbot.app',
-                'models_gateway_api_url': 'https://api.langbot.cloud/v1',
-                'oauth_authorize_url': 'https://space.langbot.app/auth/authorize',
-                'disable_models_service': False,
-            }
-
-        if 'plugin' in self.ap.instance_config.data:
-            self.ap.instance_config.data['plugin'].pop('cloud_service_url', None)
-
-        await self.ap.instance_config.dump_config()
-
-    async def downgrade(self):
-        """降级"""
-        pass

src/langbot/pkg/persistence/migrations/dbm018_add_emoji_support.py

@@ -1,58 +0,0 @@
-import sqlalchemy
-from .. import migration
-
-
-@migration.migration_class(18)
-class DBMigrateAddEmojiSupport(migration.DBMigration):
-    """Add emoji field to knowledge_bases, external_knowledge_bases and legacy_pipelines tables"""
-
-    async def upgrade(self):
-        """Upgrade"""
-        # Add emoji field to knowledge_bases
-        await self._add_emoji_to_table('knowledge_bases', '📚')
-
-        # Add emoji field to external_knowledge_bases
-        await self._add_emoji_to_table('external_knowledge_bases', '🔗')
-
-        # Add emoji field to legacy_pipelines
-        await self._add_emoji_to_table('legacy_pipelines', '⚙️')
-
-    async def _add_emoji_to_table(self, table_name: str, default_emoji: str):
-        """Add emoji column to specified table if it doesn't exist"""
-        # Get all column names from the table
-        columns = []
-
-        if self.ap.persistence_mgr.db.name == 'postgresql':
-            result = await self.ap.persistence_mgr.execute_async(
-                sqlalchemy.text(
-                    f"SELECT column_name FROM information_schema.columns WHERE table_name = '{table_name}';"
-                )
-            )
-            all_result = result.fetchall()
-            columns = [row[0] for row in all_result]
-        else:
-            result = await self.ap.persistence_mgr.execute_async(sqlalchemy.text(f'PRAGMA table_info({table_name});'))
-            all_result = result.fetchall()
-            columns = [row[1] for row in all_result]
-
-        # Check and add emoji column
-        if 'emoji' not in columns:
-            if self.ap.persistence_mgr.db.name == 'postgresql':
-                await self.ap.persistence_mgr.execute_async(
-                    sqlalchemy.text(f"ALTER TABLE {table_name} ADD COLUMN emoji VARCHAR(10) DEFAULT '{default_emoji}'")
-                )
-            else:
-                # SQLite doesn't support DEFAULT with emoji directly in ALTER TABLE
-                # Add column without default first
-                await self.ap.persistence_mgr.execute_async(
-                    sqlalchemy.text(f'ALTER TABLE {table_name} ADD COLUMN emoji VARCHAR(10)')
-                )
-
-            # Set default emoji value for existing records
-            await self.ap.persistence_mgr.execute_async(
-                sqlalchemy.text(f"UPDATE {table_name} SET emoji = '{default_emoji}' WHERE emoji IS NULL")
-            )
-
-    async def downgrade(self):
-        """Downgrade"""
-        pass

src/langbot/pkg/persistence/migrations/dbm019_monitoring_message_role.py

@@ -1,24 +0,0 @@
-import sqlalchemy
-from .. import migration
-
-
-@migration.migration_class(19)
-class DBMigrateMonitoringMessageRole(migration.DBMigration):
-    """Add role column to monitoring_messages table"""
-
-    async def upgrade(self):
-        """Upgrade"""
-        try:
-            sql_text = sqlalchemy.text("ALTER TABLE monitoring_messages ADD COLUMN role VARCHAR(50) DEFAULT 'user'")
-            await self.ap.persistence_mgr.execute_async(sql_text)
-        except Exception:
-            # Column may already exist
-            pass
-
-    async def downgrade(self):
-        """Downgrade"""
-        try:
-            sql_text = sqlalchemy.text('ALTER TABLE monitoring_messages DROP COLUMN role')
-            await self.ap.persistence_mgr.execute_async(sql_text)
-        except Exception:
-            pass

src/langbot/pkg/persistence/migrations/dbm020_knowledge_engine_plugin_architecture.py

@@ -1,161 +0,0 @@
-import sqlalchemy
-from .. import migration
-
-
-@migration.migration_class(20)
-class DBMigrateKnowledgeEnginePluginArchitecture(migration.DBMigration):
-    """Migrate to unified Knowledge Engine plugin architecture.
-
-    Changes:
-    - Backup existing knowledge_bases data to knowledge_bases_backup
-    - Clear knowledge_bases table and add new plugin architecture columns
-    - Drop old columns (PostgreSQL only; SQLite leaves them unmapped)
-    - Preserve external_knowledge_bases table as-is for future migration
-    - Set rag_plugin_migration_needed flag in metadata if old data exists
-    """
-
-    async def upgrade(self):
-        """Upgrade"""
-        has_internal_data = await self._backup_knowledge_bases()
-        has_external_data = await self._check_external_knowledge_bases()
-        await self._clear_knowledge_bases()
-        await self._add_columns_to_knowledge_bases()
-        await self._drop_old_columns()
-        if has_internal_data or has_external_data:
-            await self._set_migration_flag()
-
-    async def _get_table_columns(self, table_name: str) -> list[str]:
-        """Get column names from a table (works for both SQLite and PostgreSQL)."""
-        if self.ap.persistence_mgr.db.name == 'postgresql':
-            result = await self.ap.persistence_mgr.execute_async(
-                sqlalchemy.text(
-                    'SELECT column_name FROM information_schema.columns WHERE table_name = :table_name;'
-                ).bindparams(table_name=table_name)
-            )
-            return [row[0] for row in result.fetchall()]
-        else:
-            # SQLite PRAGMA does not support bind parameters; validate identifier.
-            if not table_name.isidentifier():
-                raise ValueError(f'Invalid table name: {table_name}')
-            result = await self.ap.persistence_mgr.execute_async(sqlalchemy.text(f'PRAGMA table_info({table_name});'))
-            return [row[1] for row in result.fetchall()]
-
-    async def _table_exists(self, table_name: str) -> bool:
-        """Check if a table exists."""
-        if self.ap.persistence_mgr.db.name == 'postgresql':
-            result = await self.ap.persistence_mgr.execute_async(
-                sqlalchemy.text(
-                    'SELECT EXISTS (SELECT FROM information_schema.tables WHERE table_name = :table_name);'
-                ).bindparams(table_name=table_name)
-            )
-            return result.scalar()
-        else:
-            result = await self.ap.persistence_mgr.execute_async(
-                sqlalchemy.text("SELECT name FROM sqlite_master WHERE type='table' AND name=:table_name;").bindparams(
-                    table_name=table_name
-                )
-            )
-            return result.first() is not None
-
-    async def _backup_knowledge_bases(self) -> bool:
-        """Backup knowledge_bases data. Returns True if data was backed up."""
-        result = await self.ap.persistence_mgr.execute_async(sqlalchemy.text('SELECT COUNT(*) FROM knowledge_bases;'))
-        count = result.scalar()
-        if count == 0:
-            return False
-
-        # Drop backup table if it already exists (from a previous failed migration)
-        if await self._table_exists('knowledge_bases_backup'):
-            await self.ap.persistence_mgr.execute_async(sqlalchemy.text('DROP TABLE knowledge_bases_backup;'))
-
-        await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.text('CREATE TABLE knowledge_bases_backup AS SELECT * FROM knowledge_bases;')
-        )
-        self.ap.logger.info(
-            'Backed up %d knowledge base(s) to knowledge_bases_backup table.',
-            count,
-        )
-        return True
-
-    async def _check_external_knowledge_bases(self) -> bool:
-        """Check if external_knowledge_bases table exists and has data.
-
-        The table is preserved as-is (not dropped) for future migration.
-        """
-        if not await self._table_exists('external_knowledge_bases'):
-            return False
-
-        result = await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.text('SELECT COUNT(*) FROM external_knowledge_bases;')
-        )
-        count = result.scalar()
-        if count > 0:
-            self.ap.logger.info(
-                'Found %d external knowledge base(s) in external_knowledge_bases table. '
-                'Table preserved for future migration.',
-                count,
-            )
-        return count > 0
-
-    async def _clear_knowledge_bases(self):
-        """Clear all rows from knowledge_bases table (preserve table structure)."""
-        await self.ap.persistence_mgr.execute_async(sqlalchemy.text('DELETE FROM knowledge_bases;'))
-
-    async def _add_columns_to_knowledge_bases(self):
-        """Add new RAG plugin architecture columns to knowledge_bases table."""
-        columns = await self._get_table_columns('knowledge_bases')
-
-        new_columns = {
-            'knowledge_engine_plugin_id': 'VARCHAR',
-            'collection_id': 'VARCHAR',
-            'creation_settings': 'TEXT',  # JSON stored as TEXT for SQLite compatibility
-            'retrieval_settings': 'TEXT',
-        }
-
-        for col_name, col_type in new_columns.items():
-            if col_name not in columns:
-                await self.ap.persistence_mgr.execute_async(
-                    sqlalchemy.text(f'ALTER TABLE knowledge_bases ADD COLUMN {col_name} {col_type};')
-                )
-
-    async def _drop_old_columns(self):
-        """Drop embedding_model_uuid and top_k columns (PostgreSQL only).
-
-        SQLite does not support DROP COLUMN in older versions, so we leave the
-        columns in place — the SQLAlchemy entity simply won't map them.
-        """
-        if self.ap.persistence_mgr.db.name != 'postgresql':
-            return
-
-        columns = await self._get_table_columns('knowledge_bases')
-
-        if 'embedding_model_uuid' in columns:
-            await self.ap.persistence_mgr.execute_async(
-                sqlalchemy.text('ALTER TABLE knowledge_bases DROP COLUMN embedding_model_uuid;')
-            )
-
-        if 'top_k' in columns:
-            await self.ap.persistence_mgr.execute_async(
-                sqlalchemy.text('ALTER TABLE knowledge_bases DROP COLUMN top_k;')
-            )
-
-    async def _set_migration_flag(self):
-        """Set rag_plugin_migration_needed flag in metadata table."""
-        # Check if the key already exists
-        result = await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.text("SELECT value FROM metadata WHERE key = 'rag_plugin_migration_needed';")
-        )
-        row = result.first()
-        if row is not None:
-            await self.ap.persistence_mgr.execute_async(
-                sqlalchemy.text("UPDATE metadata SET value = 'true' WHERE key = 'rag_plugin_migration_needed';")
-            )
-        else:
-            await self.ap.persistence_mgr.execute_async(
-                sqlalchemy.text("INSERT INTO metadata (key, value) VALUES ('rag_plugin_migration_needed', 'true');")
-            )
-        self.ap.logger.info('Set rag_plugin_migration_needed=true in metadata.')
-
-    async def downgrade(self):
-        """Downgrade"""
-        pass

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

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

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

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

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

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

src/langbot/pkg/pipeline/aggregator.py

@@ -1,289 +0,0 @@
-"""Message Aggregator Module
-
-This module provides message aggregation/debounce functionality.
-When users send multiple messages consecutively, the aggregator will wait
-for a configurable delay period and merge them into a single message
-before processing.
-"""
-
-from __future__ import annotations
-
-import asyncio
-import time
-import typing
-from dataclasses import dataclass, field
-
-import langbot_plugin.api.entities.builtin.platform.message as platform_message
-import langbot_plugin.api.entities.builtin.platform.events as platform_events
-import langbot_plugin.api.entities.builtin.provider.session as provider_session
-import langbot_plugin.api.definition.abstract.platform.adapter as abstract_platform_adapter
-
-if typing.TYPE_CHECKING:
-    from ..core import app
-
-# Maximum number of messages to buffer before forcing a flush
-MAX_BUFFER_MESSAGES = 10
-
-
-@dataclass
-class PendingMessage:
-    """A pending message waiting to be aggregated"""
-
-    bot_uuid: str
-    launcher_type: provider_session.LauncherTypes
-    launcher_id: typing.Union[int, str]
-    sender_id: typing.Union[int, str]
-    message_event: platform_events.MessageEvent
-    message_chain: platform_message.MessageChain
-    adapter: abstract_platform_adapter.AbstractMessagePlatformAdapter
-    pipeline_uuid: typing.Optional[str]
-    timestamp: float = field(default_factory=time.time)
-
-
-@dataclass
-class SessionBuffer:
-    """Buffer for a single session's pending messages"""
-
-    session_id: str
-    messages: list[PendingMessage] = field(default_factory=list)
-    timer_task: typing.Optional[asyncio.Task] = None
-    last_message_time: float = field(default_factory=time.time)
-
-
-class MessageAggregator:
-    """Message aggregator that buffers and merges consecutive messages
-
-    This class implements a debounce mechanism for incoming messages.
-    When a message arrives, it starts a timer. If more messages arrive
-    before the timer expires, they are buffered. When the timer expires,
-    all buffered messages are merged and sent to the query pool.
-    """
-
-    ap: app.Application
-
-    buffers: dict[str, SessionBuffer]
-    """Session ID -> SessionBuffer mapping"""
-
-    lock: asyncio.Lock
-    """Lock for thread-safe buffer operations"""
-
-    def __init__(self, ap: app.Application):
-        self.ap = ap
-        self.buffers = {}
-        self.lock = asyncio.Lock()
-
-    def _get_session_id(
-        self,
-        bot_uuid: str,
-        launcher_type: provider_session.LauncherTypes,
-        launcher_id: typing.Union[int, str],
-    ) -> str:
-        """Generate a unique session ID"""
-        return f'{bot_uuid}:{launcher_type.value}:{launcher_id}'
-
-    async def _get_aggregation_config(self, pipeline_uuid: typing.Optional[str]) -> tuple[bool, float]:
-        """Get aggregation configuration for a pipeline
-
-        Returns:
-            tuple: (enabled, delay_seconds)
-        """
-        default_enabled = False
-        default_delay = 1.5
-
-        if pipeline_uuid is None:
-            return default_enabled, default_delay
-
-        # Get pipeline from pipeline manager
-        pipeline = await self.ap.pipeline_mgr.get_pipeline_by_uuid(pipeline_uuid)
-        if pipeline is None:
-            return default_enabled, default_delay
-
-        config = pipeline.pipeline_entity.config or {}
-        trigger_config = config.get('trigger', {})
-        aggregation_config = trigger_config.get('message-aggregation', {})
-
-        enabled = aggregation_config.get('enabled', default_enabled)
-
-        delay_raw = aggregation_config.get('delay', default_delay)
-        try:
-            delay = float(delay_raw)
-        except (TypeError, ValueError):
-            delay = default_delay
-
-        # Clamp delay to valid range
-        delay = max(1.0, min(10.0, delay))
-
-        return enabled, delay
-
-    async def add_message(
-        self,
-        bot_uuid: str,
-        launcher_type: provider_session.LauncherTypes,
-        launcher_id: typing.Union[int, str],
-        sender_id: typing.Union[int, str],
-        message_event: platform_events.MessageEvent,
-        message_chain: platform_message.MessageChain,
-        adapter: abstract_platform_adapter.AbstractMessagePlatformAdapter,
-        pipeline_uuid: typing.Optional[str] = None,
-    ) -> None:
-        """Add a message to the aggregation buffer
-
-        If aggregation is disabled for the pipeline, the message is sent
-        directly to the query pool. Otherwise, it's buffered and will be
-        merged with other messages from the same session.
-        """
-        enabled, delay = await self._get_aggregation_config(pipeline_uuid)
-
-        if not enabled:
-            # Aggregation disabled, send directly to query pool
-            await self.ap.query_pool.add_query(
-                bot_uuid=bot_uuid,
-                launcher_type=launcher_type,
-                launcher_id=launcher_id,
-                sender_id=sender_id,
-                message_event=message_event,
-                message_chain=message_chain,
-                adapter=adapter,
-                pipeline_uuid=pipeline_uuid,
-            )
-            return
-
-        session_id = self._get_session_id(bot_uuid, launcher_type, launcher_id)
-
-        pending_msg = PendingMessage(
-            bot_uuid=bot_uuid,
-            launcher_type=launcher_type,
-            launcher_id=launcher_id,
-            sender_id=sender_id,
-            message_event=message_event,
-            message_chain=message_chain,
-            adapter=adapter,
-            pipeline_uuid=pipeline_uuid,
-        )
-
-        force_flush = False
-        async with self.lock:
-            if session_id in self.buffers:
-                buffer = self.buffers[session_id]
-                # Cancel existing timer (just cancel, don't await inside lock)
-                if buffer.timer_task and not buffer.timer_task.done():
-                    buffer.timer_task.cancel()
-                buffer.messages.append(pending_msg)
-            else:
-                buffer = SessionBuffer(
-                    session_id=session_id,
-                    messages=[pending_msg],
-                )
-                self.buffers[session_id] = buffer
-
-            buffer.last_message_time = time.time()
-
-            # Check if buffer reached max capacity
-            if len(buffer.messages) >= MAX_BUFFER_MESSAGES:
-                force_flush = True
-            else:
-                # Start new timer
-                buffer.timer_task = asyncio.create_task(self._delayed_flush(session_id, delay))
-
-        if force_flush:
-            await self._flush_buffer(session_id)
-
-    async def _delayed_flush(self, session_id: str, delay: float) -> None:
-        """Wait for delay then flush the buffer"""
-        try:
-            await asyncio.sleep(delay)
-            await self._flush_buffer(session_id)
-        except asyncio.CancelledError:
-            # Timer was cancelled, new message arrived
-            pass
-
-    async def _flush_buffer(self, session_id: str) -> None:
-        """Flush the buffer for a session, merging all messages"""
-        async with self.lock:
-            buffer = self.buffers.pop(session_id, None)
-
-        if buffer is None or not buffer.messages:
-            return
-
-        if len(buffer.messages) == 1:
-            # Only one message, no need to merge
-            msg = buffer.messages[0]
-            await self.ap.query_pool.add_query(
-                bot_uuid=msg.bot_uuid,
-                launcher_type=msg.launcher_type,
-                launcher_id=msg.launcher_id,
-                sender_id=msg.sender_id,
-                message_event=msg.message_event,
-                message_chain=msg.message_chain,
-                adapter=msg.adapter,
-                pipeline_uuid=msg.pipeline_uuid,
-            )
-            return
-
-        # Merge multiple messages
-        merged_msg = self._merge_messages(buffer.messages)
-        await self.ap.query_pool.add_query(
-            bot_uuid=merged_msg.bot_uuid,
-            launcher_type=merged_msg.launcher_type,
-            launcher_id=merged_msg.launcher_id,
-            sender_id=merged_msg.sender_id,
-            message_event=merged_msg.message_event,
-            message_chain=merged_msg.message_chain,
-            adapter=merged_msg.adapter,
-            pipeline_uuid=merged_msg.pipeline_uuid,
-        )
-
-    def _merge_messages(self, messages: list[PendingMessage]) -> PendingMessage:
-        """Merge multiple messages into one
-
-        The merged message uses the first message as base and combines
-        all message chains with newline separators.
-        The original message_event is kept unmodified to preserve
-        message metadata (message_id, etc.) for reply/quote.
-        """
-        if len(messages) == 1:
-            return messages[0]
-
-        base_msg = messages[0]
-
-        # Build merged message chain
-        merged_chain = platform_message.MessageChain([])
-
-        for i, msg in enumerate(messages):
-            if i > 0:
-                # Add newline separator between messages
-                merged_chain.append(platform_message.Plain(text='\n'))
-
-            # Copy all components from this message
-            for component in msg.message_chain:
-                merged_chain.append(component)
-
-        # Keep message_event unmodified (preserves original message_id and
-        # metadata for reply/quote), only pass merged chain separately
-        return PendingMessage(
-            bot_uuid=base_msg.bot_uuid,
-            launcher_type=base_msg.launcher_type,
-            launcher_id=base_msg.launcher_id,
-            sender_id=base_msg.sender_id,
-            message_event=base_msg.message_event,
-            message_chain=merged_chain,
-            adapter=base_msg.adapter,
-            pipeline_uuid=base_msg.pipeline_uuid,
-        )
-
-    async def flush_all(self) -> None:
-        """Flush all pending buffers immediately
-
-        This is useful during shutdown to ensure no messages are lost.
-        """
-        # Snapshot session IDs and cancel all timers under lock
-        async with self.lock:
-            session_ids = list(self.buffers.keys())
-            for sid in session_ids:
-                buffer = self.buffers.get(sid)
-                if buffer and buffer.timer_task and not buffer.timer_task.done():
-                    buffer.timer_task.cancel()
-
-        # Flush each buffer outside the lock
-        for session_id in session_ids:
-            await self._flush_buffer(session_id)

src/langbot/pkg/pipeline/cntfilter/filters/baiduexamine.py

@@ -1,9 +1,10 @@
 from __future__ import annotations
 
+import aiohttp
+
 from .. import entities
 from .. import filter as filter_model
 import langbot_plugin.api.entities.builtin.pipeline.query as pipeline_query
-from langbot.pkg.utils import httpclient
 
 BAIDU_EXAMINE_URL = 'https://aip.baidubce.com/rest/2.0/solution/v1/text_censor/v2/user_defined?access_token={}'
 BAIDU_EXAMINE_TOKEN_URL = 'https://aip.baidubce.com/oauth/2.0/token'
@@ -14,50 +15,50 @@ class BaiduCloudExamine(filter_model.ContentFilter):
     """百度云内容审核"""
 
     async def _get_token(self) -> str:
-        session = httpclient.get_session()
-        async with session.post(
-            BAIDU_EXAMINE_TOKEN_URL,
-            params={
-                'grant_type': 'client_credentials',
-                'client_id': self.ap.pipeline_cfg.data['baidu-cloud-examine']['api-key'],
-                'client_secret': self.ap.pipeline_cfg.data['baidu-cloud-examine']['api-secret'],
-            },
-        ) as resp:
-            return (await resp.json())['access_token']
+        async with aiohttp.ClientSession() as session:
+            async with session.post(
+                BAIDU_EXAMINE_TOKEN_URL,
+                params={
+                    'grant_type': 'client_credentials',
+                    'client_id': self.ap.pipeline_cfg.data['baidu-cloud-examine']['api-key'],
+                    'client_secret': self.ap.pipeline_cfg.data['baidu-cloud-examine']['api-secret'],
+                },
+            ) as resp:
+                return (await resp.json())['access_token']
 
     async def process(self, query: pipeline_query.Query, message: str) -> entities.FilterResult:
-        session = httpclient.get_session()
-        async with session.post(
-            BAIDU_EXAMINE_URL.format(await self._get_token()),
-            headers={
-                'Content-Type': 'application/x-www-form-urlencoded',
-                'Accept': 'application/json',
-            },
-            data=f'text={message}'.encode('utf-8'),
-        ) as resp:
-            result = await resp.json()
+        async with aiohttp.ClientSession() as session:
+            async with session.post(
+                BAIDU_EXAMINE_URL.format(await self._get_token()),
+                headers={
+                    'Content-Type': 'application/x-www-form-urlencoded',
+                    'Accept': 'application/json',
+                },
+                data=f'text={message}'.encode('utf-8'),
+            ) as resp:
+                result = await resp.json()
 
-            if 'error_code' in result:
-                return entities.FilterResult(
-                    level=entities.ResultLevel.BLOCK,
-                    replacement=message,
-                    user_notice='',
-                    console_notice=f'百度云判定出错，错误信息：{result["error_msg"]}',
-                )
-            else:
-                conclusion = result['conclusion']
-
-                if conclusion in ('合规'):
-                    return entities.FilterResult(
-                        level=entities.ResultLevel.PASS,
-                        replacement=message,
-                        user_notice='',
-                        console_notice=f'百度云判定结果：{conclusion}',
-                    )
-                else:
+                if 'error_code' in result:
                     return entities.FilterResult(
                         level=entities.ResultLevel.BLOCK,
                         replacement=message,
-                        user_notice='消息中存在不合适的内容, 请修改',
-                        console_notice=f'百度云判定结果：{conclusion}',
+                        user_notice='',
+                        console_notice=f'百度云判定出错，错误信息：{result["error_msg"]}',
                     )
+                else:
+                    conclusion = result['conclusion']
+
+                    if conclusion in ('合规'):
+                        return entities.FilterResult(
+                            level=entities.ResultLevel.PASS,
+                            replacement=message,
+                            user_notice='',
+                            console_notice=f'百度云判定结果：{conclusion}',
+                        )
+                    else:
+                        return entities.FilterResult(
+                            level=entities.ResultLevel.BLOCK,
+                            replacement=message,
+                            user_notice='消息中存在不合适的内容, 请修改',
+                            console_notice=f'百度云判定结果：{conclusion}',
+                        )

src/langbot/pkg/pipeline/config_coercion.py

@@ -1,105 +0,0 @@
-from __future__ import annotations
-
-import logging
-
-logger = logging.getLogger(__name__)
-
-# metadata type -> coercion function
-_COERCE_MAP = {
-    'integer': lambda v: int(v),
-    'number': lambda v: float(v),
-    'float': lambda v: float(v),
-}
-
-
-def _coerce_bool(v):
-    if isinstance(v, bool):
-        return v
-    if isinstance(v, str):
-        if v.lower() == 'true':
-            return True
-        if v.lower() == 'false':
-            return False
-        raise ValueError(f'Cannot convert string {v!r} to bool')
-    return bool(v)
-
-
-def _coerce_value(value, expected_type: str):
-    """Convert a single value to the expected type.
-
-    Returns the converted value, or the original value if no conversion needed.
-    """
-    if value is None:
-        return value
-
-    if expected_type == 'boolean':
-        if isinstance(value, bool):
-            return value
-        return _coerce_bool(value)
-
-    coerce_fn = _COERCE_MAP.get(expected_type)
-    if coerce_fn is None:
-        return value
-
-    # Already the correct type
-    if expected_type == 'integer' and isinstance(value, int) and not isinstance(value, bool):
-        return value
-    if expected_type in ('number', 'float') and isinstance(value, (int, float)) and not isinstance(value, bool):
-        return float(value)
-
-    return coerce_fn(value)
-
-
-def coerce_pipeline_config(
-    config: dict,
-    *metadata_list: dict,
-) -> None:
-    """Coerce pipeline config values according to metadata type definitions.
-
-    Walks each metadata dict (trigger, safety, ai, output) and converts
-    config values in-place so that strings coming from the JSON column are
-    cast to their declared types (integer, number/float, boolean).
-
-    Args:
-        config: The pipeline config dict to modify in-place.
-        *metadata_list: Metadata dicts loaded from the YAML templates.
-    """
-    for meta in metadata_list:
-        section_name = meta.get('name')
-        if not section_name or section_name not in config:
-            continue
-
-        section = config[section_name]
-        if not isinstance(section, dict):
-            continue
-
-        for stage_def in meta.get('stages', []):
-            stage_name = stage_def.get('name')
-            if not stage_name or stage_name not in section:
-                continue
-
-            stage_config = section[stage_name]
-            if not isinstance(stage_config, dict):
-                continue
-
-            for field_def in stage_def.get('config', []):
-                field_name = field_def.get('name')
-                field_type = field_def.get('type')
-                if not field_name or not field_type or field_name not in stage_config:
-                    continue
-
-                old_value = stage_config[field_name]
-                try:
-                    new_value = _coerce_value(old_value, field_type)
-                    if new_value is not old_value:
-                        stage_config[field_name] = new_value
-                except (ValueError, TypeError) as e:
-                    logger.warning(
-                        'Failed to coerce config %s.%s.%s (%r) to %s: %s',
-                        section_name,
-                        stage_name,
-                        field_name,
-                        old_value,
-                        field_type,
-                        e,
-                    )

src/langbot/pkg/pipeline/controller.py

@@ -33,14 +33,11 @@ class Controller:
 
                     for query in queries:
                         session = await self.ap.sess_mgr.get_session(query)
-                        # Debug logging removed from tight loop to prevent excessive log generation
-                        # that can cause memory overflow in high-traffic scenarios
+                        self.ap.logger.debug(f'Checking query {query} session {session}')
 
                         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