chore: bump version to 4.8.3 in pyproject.toml and uv.lock

* Initial plan

* feat: add Telegram voice message receiving support

- Add filters.VOICE to Telegram message handler to capture voice messages
- Implement voice message processing in target2yiri converter
- Download voice files from Telegram API and convert to base64
- Create platform_message.Voice component with proper mime type and duration
- Maintain compatibility with existing text, photo, and command messages

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

* chore: format code

---------

Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
Co-authored-by: RockChinQ <45992437+RockChinQ@users.noreply.github.com>
Co-authored-by: Junyan Qin <rockchinq@gmail.com>

.dockerignore

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

.github/pull_request_template.md

@@ -2,6 +2,17 @@
 
 > 请在此部分填写你实现/解决/优化的内容:  
 > Summary of what you implemented/solved/optimized:
+> 
+
+### 更改前后对比截图 / Screenshots
+
+> 请在此部分粘贴更改前后对比截图（可以是界面截图、控制台输出、对话截图等）:  
+> Please paste the screenshots of changes before and after here (can be interface screenshots, console output, conversation screenshots, etc.):
+> 
+> 修改前 / Before:
+> 
+> 修改后 / After:
+> 
 
 ## 检查清单 / Checklist
 

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

@@ -1,7 +1,5 @@
 name: Build Docker Image
 on:
-  #防止fork乱用action设置只能手动触发构建
-  workflow_dispatch:
   ## 发布release的时候会自动构建
   release:
     types: [published]
@@ -41,5 +39,9 @@ jobs:
         run: docker login --username=${{ secrets.DOCKER_USERNAME }} --password ${{ secrets.DOCKER_PASSWORD }}
       - name: Create Buildx
         run: docker buildx create --name mybuilder --use
-      - name: Build  # image name: rockchin/langbot:<VERSION>
+      - 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
+      - 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

.github/workflows/lint.yml

@@ -0,0 +1,60 @@
+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/publish-to-pypi.yml

@@ -0,0 +1,46 @@
+name: Build and Publish to PyPI
+
+on:
+  workflow_dispatch:
+  release:
+    types: [published]
+
+jobs:
+  build-and-publish:
+    runs-on: ubuntu-latest
+    permissions:
+      contents: read
+      id-token: write  # Required for trusted publishing to PyPI
+    
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+        with:
+          persist-credentials: false
+
+      - name: Set up Node.js
+        uses: actions/setup-node@v4
+        with:
+          node-version: '22'
+
+      - name: Build frontend
+        run: |
+          cd web
+          npm install -g pnpm
+          pnpm install
+          pnpm build
+          mkdir -p ../src/langbot/web/out
+          cp -r out ../src/langbot/web/
+
+      - name: Install the latest version of uv
+        uses: astral-sh/setup-uv@v6
+        with:
+          version: "latest"
+
+      - name: Build package
+        run: |
+          uv build
+
+      - name: Publish to PyPI
+        run: |
+          uv publish --token ${{ secrets.PYPI_TOKEN }}

.github/workflows/run-tests.yml

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

.github/workflows/test-dev-image.yaml

@@ -0,0 +1,108 @@
+name: Test Dev Image
+
+on:
+  workflow_run:
+    workflows: ["Build Dev Image"]
+    types:
+      - completed
+    branches:
+      - master
+
+jobs:
+  test-dev-image:
+    runs-on: ubuntu-latest
+    # Only run if the build workflow succeeded
+    if: ${{ github.event.workflow_run.conclusion == 'success' }}
+    
+    permissions:
+      contents: read
+    
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v4
+
+      - name: Update Docker Compose to use master tag
+        working-directory: ./docker
+        run: |
+          # Replace 'latest' with 'master' tag for testing the dev image
+          sed -i 's/rockchin\/langbot:latest/rockchin\/langbot:master/g' docker-compose.yaml
+          echo "Updated docker-compose.yaml to use master tag:"
+          cat docker-compose.yaml
+
+      - name: Start Docker Compose
+        working-directory: ./docker
+        run: docker compose up -d
+
+      - name: Wait and Test API
+        run: |
+          # Function to test API endpoint
+          test_api() {
+            echo "Testing API endpoint..."
+            response=$(curl -s --connect-timeout 10 --max-time 30 -w "\n%{http_code}" http://localhost:5300/api/v1/system/info 2>&1)
+            curl_exit_code=$?
+            
+            if [ $curl_exit_code -ne 0 ]; then
+              echo "Curl failed with exit code: $curl_exit_code"
+              echo "Error: $response"
+              return 1
+            fi
+            
+            http_code=$(echo "$response" | tail -n 1)
+            response_body=$(echo "$response" | head -n -1)
+            
+            if [ "$http_code" = "200" ]; then
+              echo "API is healthy! Response code: $http_code"
+              echo "Response: $response_body"
+              return 0
+            else
+              echo "API returned non-200 response: $http_code"
+              echo "Response body: $response_body"
+              return 1
+            fi
+          }
+
+          # Wait 30 seconds before first attempt
+          echo "Waiting 30 seconds for services to start..."
+          sleep 30
+
+          # Try up to 3 times with 30-second intervals
+          max_attempts=3
+          attempt=1
+
+          while [ $attempt -le $max_attempts ]; do
+            echo "Attempt $attempt of $max_attempts"
+            
+            if test_api; then
+              echo "Success! API is responding correctly."
+              exit 0
+            fi
+            
+            if [ $attempt -lt $max_attempts ]; then
+              echo "Retrying in 30 seconds..."
+              sleep 30
+            fi
+            
+            attempt=$((attempt + 1))
+          done
+
+          # All attempts failed
+          echo "Failed to get healthy response after $max_attempts attempts"
+          exit 1
+
+      - name: Show Container Logs on Failure
+        if: failure()
+        working-directory: ./docker
+        run: |
+          echo "=== Docker Compose Status ==="
+          docker compose ps
+          echo ""
+          echo "=== LangBot Logs ==="
+          docker compose logs langbot
+          echo ""
+          echo "=== Plugin Runtime Logs ==="
+          docker compose logs langbot_plugin_runtime
+
+      - name: Cleanup
+        if: always()
+        working-directory: ./docker
+        run: docker compose down

.gitignore

@@ -42,7 +42,13 @@ botpy.log*
 test.py
 /web_ui
 .venv/
-uv.lock
 /test
+plugins.bak
 coverage.xml
-.coverage
+.coverage
+src/langbot/web/
+
+# Build artifacts
+/dist
+/build
+*.egg-info

.mcp.json

@@ -0,0 +1,37 @@
+{
+  "mcpServers": {
+    "shadcn": {
+      "command": "npx",
+      "args": [
+        "shadcn@latest",
+        "mcp"
+      ]
+    },
+    "sequential-thinking": {
+      "type": "stdio",
+      "command": "npx",
+      "args": ["-y", "@modelcontextprotocol/server-sequential-thinking"],
+      "env": {}
+    },
+    "github": {
+      "type": "stdio",
+      "command": "npx",
+      "args": ["-y", "@modelcontextprotocol/server-github"],
+      "env": {
+        "GITHUB_PERSONAL_ACCESS_TOKEN": "${GITHUB_PERSONAL_ACCESS_TOKEN}"
+      }
+    },
+    "fetch": {
+      "type": "stdio",
+      "command": "uvx",
+      "args": ["mcp-server-fetch"],
+      "env": {}
+    },
+    "playwright": {
+      "type": "stdio",
+      "command": "npx",
+      "args": ["-y", "@playwright/mcp@latest"],
+      "env": {}
+    }
+  }
+}

AGENTS.md

@@ -0,0 +1,88 @@
+# AGENTS.md
+
+This file is for guiding code agents (like Claude Code, GitHub Copilot, OpenAI Codex, etc.) to work in LangBot project.
+
+## Project Overview
+
+LangBot is a open-source LLM native instant messaging bot development platform, aiming to provide an out-of-the-box IM robot development experience, with Agent, RAG, MCP and other LLM application functions, supporting global instant messaging platforms, and providing rich API interfaces, supporting custom development.
+
+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.
+
+## Backend Development
+
+We use `uv` to manage dependencies.
+
+```bash
+pip install uv
+uv sync --dev
+```
+
+Start the backend and run the project in development mode.
+
+```bash
+uv run main.py
+```
+
+Then you can access the project at `http://127.0.0.1:5300`.
+
+## Frontend Development
+
+We use `pnpm` to manage dependencies.
+
+```bash
+cd web
+cp .env.example .env
+pnpm install
+pnpm dev
+```
+
+Then you can access the project at `http://127.0.0.1:3000`.
+
+## Plugin System Architecture
+
+LangBot is composed of various internal components such as Large Language Model tools, commands, messaging platform adapters, LLM requesters, and more. To meet extensibility and flexibility requirements, we have implemented a production-grade plugin system.
+
+Each plugin runs in an independent process, managed uniformly by the Plugin Runtime. It has two operating modes: `stdio` and `websocket`. When LangBot is started directly by users (not running in a container), it uses `stdio` mode, which is common for personal users or lightweight environments. When LangBot runs in a container, it uses `websocket` mode, designed specifically for production environments.
+
+Plugin Runtime automatically starts each installed plugin and interacts through stdio. In plugin development scenarios, developers can use the lbp command-line tool to start plugins and connect to the running Runtime via WebSocket for debugging.
+
+> Plugin SDK, CLI, Runtime, and entities definitions shared between LangBot and plugins are contained in the [`langbot-plugin-sdk`](https://github.com/langbot-app/langbot-plugin-sdk) repository.
+
+## Some Development Tips and Standards
+
+- LangBot is a global project, any comments in code should be in English, and user experience should be considered in all aspects.
+- Thus you should consider the i18n support in all aspects.
+- LangBot is widely adopted in both toC and toB scenarios, so you should consider the compatibility and security in all aspects.
+- If you were asked to make a commit, please follow the commit message format: 
+    - format: <type>(<scope>): <subject>
+    - 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
+
+- Keep it simple, stupid.
+- Entities should not be multiplied unnecessarily
+- 八荣八耻
+
+    以瞎猜接口为耻，以认真查询为荣。
+    以模糊执行为耻，以寻求确认为荣。
+    以臆想业务为耻，以人类确认为荣。
+    以创造接口为耻，以复用现有为荣。
+    以跳过验证为耻，以主动测试为荣。
+    以破坏架构为耻，以遵循规范为荣。
+    以假装理解为耻，以诚实无知为荣。
+    以盲目修改为耻，以谨慎重构为荣。

CLAUDE.md

@@ -0,0 +1 @@
+AGENTS.md

Dockerfile

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

README.md

@@ -1,36 +1,48 @@
 
 <p align="center">
 <a href="https://langbot.app">
-<img src="https://docs.langbot.app/social_zh.png" alt="LangBot"/>
+<img width="130" src="https://docs.langbot.app/langbot-logo.png" alt="LangBot"/>
 </a>
 
 <div align="center">
 
 <a href="https://hellogithub.com/repository/langbot-app/LangBot" target="_blank"><img src="https://abroad.hellogithub.com/v1/widgets/recommend.svg?rid=5ce8ae2aa4f74316bf393b57b952433c&claim_uid=gtmc6YWjMZkT21R" alt="Featured｜HelloGitHub" style="width: 250px; height: 54px;" width="250" height="54" /></a>
 
-[English](README_EN.md) / 简体中文 / [繁體中文](README_TW.md) / [日本語](README_JP.md) / (PR for your language)
+<h3>使用 LangBot 快速构建、调试、部署即时通信机器人。</h3>
+
+[English](README_EN.md) / 简体中文 / [繁體中文](README_TW.md) / [日本語](README_JP.md) / [Español](README_ES.md) / [Français](README_FR.md) / [한국어](README_KO.md) / [Русский](README_RU.md) / [Tiếng Việt](README_VI.md)
 
 [![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb)](https://discord.gg/wdNEHETs87)
-[![QQ Group](https://img.shields.io/badge/%E7%A4%BE%E5%8C%BAQQ%E7%BE%A4-966235608-blue)](https://qm.qq.com/q/JLi38whHum)
+[![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">
 [![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/features.html">规格特性</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://docs.langbot.app/zh/tags/readme.html">API 集成</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>
 
-LangBot 是一个开源的大语言模型原生即时通信机器人开发平台，旨在提供开箱即用的 IM 机器人开发体验，具有 Agent、RAG、MCP 等多种 LLM 应用功能，适配全球主流即时通信平台，并提供丰富的 API 接口，支持自定义开发。
 
 ## 📦 开始使用
 
+#### 快速部署
+
+使用 `uvx` 一键启动（需要先安装 [uv](https://docs.astral.sh/uv/getting-started/installation/)）：
+
+```bash
+uvx langbot
+```
+
+访问 http://localhost:5300 即可开始使用。
+
 #### Docker Compose 部署
 
 ```bash
@@ -61,6 +73,10 @@ docker compose up -d
 
 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)。
 
+#### Kubernetes 部署
+
+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。
@@ -69,11 +85,15 @@ docker compose up -d
 
 ## ✨ 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)。
-- 🤖 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：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。
+<img width="500" src="https://docs.langbot.app/ui/bot-page-zh-rounded.png" />
+
+
+- 💬 大模型对话、Agent：支持多种大模型，适配群聊和私聊；具有多轮对话、工具调用、多模态、流式输出能力，自带 RAG（知识库）实现，并深度适配 [Dify](https://dify.ai)、[Coze](https://coze.com)、[n8n](https://n8n.io)、[Langflow](https://langflow.org)等 LLMOps 平台。
+- 🤖 多平台支持：目前支持 QQ、QQ频道、企业微信、个人微信、飞书、Discord、Telegram、KOOK、Slack、LINE 等平台。
+- 🛠️ 高稳定性、功能完备：原生支持访问控制、限速、敏感词过滤等机制；配置简单，支持多种部署方式。
+- 🧩 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：提供先进的 WebUI 管理面板，用最直观的方式配置、管理、监控机器人。
+- 📊 生产级特性：支持多流水线配置，不同机器人用于不同应用场景。具有全面的监控和异常处理能力。已被多家企业采用。
 
 详细规格特性请访问[文档](https://docs.langbot.app/zh/insight/features.html)。
 
@@ -94,6 +114,7 @@ docker compose up -d
 | 微信公众号 | ✅ |  |
 | 飞书 | ✅ |  |
 | 钉钉 | ✅ |  |
+| KOOK | ✅ |  |
 | Discord | ✅ |  |
 | Telegram | ✅ |  |
 | Slack | ✅ |  |
@@ -112,6 +133,7 @@ docker compose up -d
 | [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 |
@@ -124,7 +146,7 @@ docker compose up -d
 | [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 |
+| [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 |
 
 ### TTS
 
@@ -147,3 +169,9 @@ docker compose up -d
 <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

@@ -1,11 +1,15 @@
 <p align="center">
 <a href="https://langbot.app">
-<img src="https://docs.langbot.app/social_en.png" alt="LangBot"/>
+<img width="130" src="https://docs.langbot.app/langbot-logo.png" alt="LangBot"/>
 </a>
 
 <div align="center">
 
-English / [简体中文](README.md) / [繁體中文](README_TW.md) / [日本語](README_JP.md) / (PR for your language)
+<a href="https://www.producthunt.com/products/langbot?utm_source=badge-follow&utm_medium=badge&utm_source=badge-langbot" target="_blank"><img src="https://api.producthunt.com/widgets/embed-image/v1/follow.svg?product_id=1077185&theme=light" alt="LangBot - Production&#0045;grade&#0032;IM&#0032;bot&#0032;made&#0032;easy&#0046; | Product Hunt" style="width: 250px; height: 54px;" width="250" height="54" /></a>
+
+<h3>Quickly build, debug, and ship IM bots with LangBot.</h3>
+
+English / [简体中文](README.md) / [繁體中文](README_TW.md) / [日本語](README_JP.md) / [Español](README_ES.md) / [Français](README_FR.md) / [한국어](README_KO.md) / [Русский](README_RU.md) / [Tiếng Việt](README_VI.md)
 
 [![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb)](https://discord.gg/wdNEHETs87)
 [![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/langbot-app/LangBot)
@@ -13,18 +17,29 @@ English / [简体中文](README.md) / [繁體中文](README_TW.md) / [日本語]
 <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/features.html">Features</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>
+<a href="https://docs.langbot.app/en/tags/readme.html">API Integration</a> ｜
+<a href="https://space.langbot.app">Plugin Market</a> ｜
+<a href="https://langbot.featurebase.app/roadmap">Roadmap</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
@@ -55,6 +70,10 @@ Community contributed Zeabur template.
 
 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.
@@ -63,11 +82,15 @@ Click the Star and Watch button in the upper right corner of the repository to g
 
 ## ✨ 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).
-- 🤖 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: Support event-driven, component extension, etc. plugin mechanisms; Integrate Anthropic [MCP protocol](https://modelcontextprotocol.io/); Currently has hundreds of plugins.
+<img width="500" src="https://docs.langbot.app/ui/bot-page-en-rounded.png" />
+
+
+- 💬 Chat with LLM / Agent: Supports multiple LLMs, adapt to group chats and private chats; Supports multi-round conversations, tool calls, multi-modal, and streaming output capabilities. Built-in RAG (knowledge base) implementation, and deeply integrates with [Dify](https://dify.ai), [Coze](https://coze.com), [n8n](https://n8n.io), [Langflow](https://langflow.org) etc. LLMOps platforms.
+- 🤖 Multi-platform Support: Currently supports QQ, QQ Channel, WeCom, personal WeChat, Lark, DingTalk, Discord, Telegram, KOOK, Slack, LINE, etc.
+- 🛠️ High Stability, Feature-rich: Native access control, rate limiting, sensitive word filtering, etc. mechanisms; Easy to use, supports multiple deployment methods.
+- 🧩 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.
+- 📊 Production-grade Features: Supports multiple pipeline configurations, different bots can be used for different scenarios. Has comprehensive monitoring and exception handling capabilities.
 
 For more detailed specifications, please refer to the [documentation](https://docs.langbot.app/en/insight/features.html).
 
@@ -91,6 +114,7 @@ Or visit the demo environment: https://demo.langbot.dev/
 | Personal WeChat | ✅ |  |
 | Lark | ✅ |  |
 | DingTalk | ✅ |  |
+| KOOK | ✅ |  |
 
 ### LLMs
 
@@ -105,6 +129,7 @@ Or visit the demo environment: https://demo.langbot.dev/
 | [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) | ✅ | |

README_ES.md

@@ -0,0 +1,151 @@
+<p align="center">
+<a href="https://langbot.app">
+<img width="130" src="https://docs.langbot.app/langbot-logo.png" alt="LangBot"/>
+</a>
+
+<div align="center">
+
+<a href="https://www.producthunt.com/products/langbot?utm_source=badge-follow&utm_medium=badge&utm_source=badge-langbot" target="_blank"><img src="https://api.producthunt.com/widgets/embed-image/v1/follow.svg?product_id=1077185&theme=light" alt="LangBot - Production&#0045;grade&#0032;IM&#0032;bot&#0032;made&#0032;easy&#0046; | Product Hunt" style="width: 250px; height: 54px;" width="250" height="54" /></a>
+
+<h3>Cree, depure y despliegue bots de mensajería instantánea rápidamente con LangBot.</h3>
+
+[English](README_EN.md) / [简体中文](README.md) / [繁體中文](README_TW.md) / [日本語](README_JP.md) / Español / [Français](README_FR.md) / [한국어](README_KO.md) / [Русский](README_RU.md) / [Tiếng Việt](README_VI.md)
+
+[![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb)](https://discord.gg/wdNEHETs87)
+[![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">Inicio</a> ｜
+<a href="https://docs.langbot.app/en/insight/features.html">Características</a> ｜
+<a href="https://docs.langbot.app/en/insight/guide.html">Despliegue</a> ｜
+<a href="https://docs.langbot.app/en/tags/readme.html">Integración API</a> ｜
+<a href="https://space.langbot.app">Mercado de Plugins</a> ｜
+<a href="https://langbot.featurebase.app/roadmap">Hoja de Ruta</a>
+
+</div>
+
+</p>
+
+
+## 📦 Comenzar
+
+#### Inicio Rápido
+
+Use `uvx` para iniciar con un comando (necesita instalar [uv](https://docs.astral.sh/uv/getting-started/installation/)):
+
+```bash
+uvx langbot
+```
+
+Visite http://localhost:5300 para comenzar a usarlo.
+
+#### Despliegue con Docker Compose
+
+```bash
+git clone https://github.com/langbot-app/LangBot
+cd LangBot/docker
+docker compose up -d
+```
+
+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)
+
+#### 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).
+
+#### Despliegue en Kubernetes
+
+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
+
+<img width="500" src="https://docs.langbot.app/ui/bot-page-en-rounded.png" />
+
+
+- 💬 Chat con LLM / Agent: Compatible con múltiples LLMs, adaptado para chats grupales y privados; Admite conversaciones de múltiples rondas, llamadas a herramientas, capacidades multimodales y de salida en streaming. Implementación RAG (base de conocimientos) incorporada, e integración profunda con [Dify](https://dify.ai), [Coze](https://coze.com), [n8n](https://n8n.io), [Langflow](https://langflow.org) etc. LLMOps platforms.
+- 🤖 Soporte Multiplataforma: Actualmente compatible con QQ, QQ Channel, WeCom, WeChat personal, Lark, DingTalk, Discord, Telegram, KOOK, Slack, LINE, etc.
+- 🛠️ Alta Estabilidad, Rico en Funciones: Control de acceso nativo, limitación de velocidad, filtrado de palabras sensibles, etc.; Fácil de usar, admite múltiples métodos de despliegue.
+- 🧩 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.
+- 📊 Características de Nivel de Producción: Compatible con múltiples configuraciones de pipeline, diferentes bots para diferentes escenarios. Cuenta con capacidades completas de monitoreo y manejo de excepciones.
+
+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 | ✅ |  |
+| QQ API Oficial | ✅ |  |
+| WeCom | ✅ |  |
+| WeComCS | ✅ |  |
+| WeCom AI Bot | ✅ |  |
+| WeChat Personal | ✅ |  |
+| Lark | ✅ |  |
+| DingTalk | ✅ |  |
+| KOOK | ✅ |  |
+
+### LLMs
+
+| 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 |
+
+## 🤝 Contribución de la Comunidad
+
+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" />
+</a>

README_FR.md

@@ -0,0 +1,150 @@
+<p align="center">
+<a href="https://langbot.app">
+<img width="130" src="https://docs.langbot.app/langbot-logo.png" alt="LangBot"/>
+</a>
+
+<div align="center">
+
+<a href="https://www.producthunt.com/products/langbot?utm_source=badge-follow&utm_medium=badge&utm_source=badge-langbot" target="_blank"><img src="https://api.producthunt.com/widgets/embed-image/v1/follow.svg?product_id=1077185&theme=light" alt="LangBot - Production&#0045;grade&#0032;IM&#0032;bot&#0032;made&#0032;easy&#0046; | Product Hunt" style="width: 250px; height: 54px;" width="250" height="54" /></a>
+
+<h3>Créez, déboguez et déployez rapidement des bots de messagerie instantanée avec LangBot.</h3>
+
+[English](README_EN.md) / [简体中文](README.md) / [繁體中文](README_TW.md) / [日本語](README_JP.md) / [Español](README_ES.md) / Français / [한국어](README_KO.md) / [Русский](README_RU.md) / [Tiếng Việt](README_VI.md)
+
+[![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb)](https://discord.gg/wdNEHETs87)
+[![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">Accueil</a> ｜
+<a href="https://docs.langbot.app/en/insight/features.html">Fonctionnalités</a> ｜
+<a href="https://docs.langbot.app/en/insight/guide.html">Déploiement</a> ｜
+<a href="https://docs.langbot.app/en/tags/readme.html">Intégration API</a> ｜
+<a href="https://space.langbot.app">Marché des Plugins</a> ｜
+<a href="https://langbot.featurebase.app/roadmap">Feuille de Route</a>
+
+</div>
+
+</p>
+
+## 📦 Commencer
+
+#### Démarrage Rapide
+
+Utilisez `uvx` pour démarrer avec une commande (besoin d'installer [uv](https://docs.astral.sh/uv/getting-started/installation/)) :
+
+```bash
+uvx langbot
+```
+
+Visitez http://localhost:5300 pour commencer à l'utiliser.
+
+#### Déploiement avec Docker Compose
+
+```bash
+git clone https://github.com/langbot-app/LangBot
+cd LangBot/docker
+docker compose up -d
+```
+
+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)
+
+#### 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).
+
+#### Déploiement Kubernetes
+
+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
+
+<img width="500" src="https://docs.langbot.app/ui/bot-page-en-rounded.png" />
+
+
+- 💬 Chat avec LLM / Agent : Prend en charge plusieurs LLM, adapté aux chats de groupe et privés ; Prend en charge les conversations multi-tours, les appels d'outils, les capacités multimodales et de sortie en streaming. Implémentation RAG (base de connaissances) intégrée, et intégration profonde avec [Dify](https://dify.ai), [Coze](https://coze.com), [n8n](https://n8n.io), [Langflow](https://langflow.org) etc. LLMOps platforms.
+- 🤖 Support Multi-plateforme : Actuellement compatible avec QQ, QQ Channel, WeCom, WeChat personnel, Lark, DingTalk, Discord, Telegram, KOOK, Slack, LINE, etc.
+- 🛠️ Haute Stabilité, Riche en Fonctionnalités : Contrôle d'accès natif, limitation de débit, filtrage de mots sensibles, etc. ; Facile à utiliser, prend en charge plusieurs méthodes de déploiement.
+- 🧩 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.
+- 📊 Fonctionnalités de Niveau Production : Prend en charge plusieurs configurations de pipeline, différents bots pour différents scénarios. Dispose de capacités complètes de surveillance et de gestion des exceptions.
+
+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 QQ | ✅ |  |
+| WeCom | ✅ |  |
+| WeComCS | ✅ |  |
+| WeCom AI Bot | ✅ |  |
+| WeChat Personnel | ✅ |  |
+| Lark | ✅ |  |
+| DingTalk | ✅ |  |
+| KOOK | ✅ |  |
+
+### LLMs
+
+| 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 |
+
+## 🤝 Contribution de la Communauté
+
+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" />
+</a>

README_JP.md

@@ -1,11 +1,15 @@
 <p align="center">
 <a href="https://langbot.app">
-<img src="https://docs.langbot.app/social_en.png" alt="LangBot"/>
+<img width="130" src="https://docs.langbot.app/langbot-logo.png" alt="LangBot"/>
 </a>
 
 <div align="center">
 
-[English](README_EN.md) / [简体中文](README.md) / [繁體中文](README_TW.md) / 日本語 / (PR for your language)
+<a href="https://www.producthunt.com/products/langbot?utm_source=badge-follow&utm_medium=badge&utm_source=badge-langbot" target="_blank"><img src="https://api.producthunt.com/widgets/embed-image/v1/follow.svg?product_id=1077185&theme=light" alt="LangBot - Production&#0045;grade&#0032;IM&#0032;bot&#0032;made&#0032;easy&#0046; | Product Hunt" style="width: 250px; height: 54px;" width="250" height="54" /></a>
+
+<h3>LangBotでIMボットを素早く構築、デバッグ、デプロイ。</h3>
+
+[English](README_EN.md) / [简体中文](README.md) / [繁體中文](README_TW.md) / 日本語 / [Español](README_ES.md) / [Français](README_FR.md) / [한국어](README_KO.md) / [Русский](README_RU.md) / [Tiếng Việt](README_VI.md)
 
 [![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb)](https://discord.gg/wdNEHETs87)
 [![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/langbot-app/LangBot)
@@ -13,18 +17,28 @@
 <img src="https://img.shields.io/badge/python-3.10 ~ 3.13 -blue.svg" alt="python">
 
 <a href="https://langbot.app">ホーム</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>
+<a href="https://docs.langbot.app/ja/insight/features.html">機能仕様</a> ｜
+<a href="https://docs.langbot.app/ja/insight/guide.html">デプロイ</a> ｜
+<a href="https://docs.langbot.app/ja/tags/readme.html">API統合</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>
 
 </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。
-
 ## 📦 始め方
 
+#### クイックスタート
+
+`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
+```
+
+http://localhost:5300 にアクセスして使用を開始します。
+
 #### Docker Compose デプロイ
 
 ```bash
@@ -55,6 +69,10 @@ LangBotはBTPanelにリストされています。BTPanelをインストール
 
 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。
 
+#### 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。
@@ -63,11 +81,15 @@ LangBotはBTPanelにリストされています。BTPanelをインストール
 
 ## ✨ 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) 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: 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。
+<img width="500" src="https://docs.langbot.app/ui/bot-page-en-rounded.png" />
+
+
+- 💬 LLM / エージェントとのチャット: 複数のLLMをサポートし、グループチャットとプライベートチャットに対応。マルチラウンドの会話、ツールの呼び出し、マルチモーダル、ストリーミング出力機能をサポート、RAG（知識ベース）を組み込み、[Dify](https://dify.ai)、[Coze](https://coze.com)、[n8n](https://n8n.io)、[Langflow](https://langflow.org)などの LLMOps プラットフォームと深く統合。
+- 🤖 多プラットフォーム対応: 現在、QQ、QQ チャンネル、WeChat、個人 WeChat、Lark、DingTalk、Discord、Telegram、KOOK、Slack、LINE など、複数のプラットフォームをサポートしています。
+- 🛠️ 高い安定性、豊富な機能: ネイティブのアクセス制御、レート制限、敏感な単語のフィルタリングなどのメカニズムをサポート。使いやすく、複数のデプロイ方法をサポート。
+- 🧩 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。
+- 📊 生産レベルの機能: 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。包括的な監視と例外処理機能を備えています。
 
 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。
 
@@ -91,6 +113,7 @@ LangBotはBTPanelにリストされています。BTPanelをインストール
 | 個人WeChat | ✅ | |
 | Lark | ✅ |  |
 | DingTalk | ✅ |  |
+| KOOK | ✅ |  |
 
 ### LLMs
 
@@ -104,6 +127,7 @@ LangBotはBTPanelにリストされています。BTPanelをインストール
 | [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) | ✅ | |

README_KO.md

@@ -0,0 +1,150 @@
+<p align="center">
+<a href="https://langbot.app">
+<img width="130" src="https://docs.langbot.app/langbot-logo.png" alt="LangBot"/>
+</a>
+
+<div align="center">
+
+<a href="https://www.producthunt.com/products/langbot?utm_source=badge-follow&utm_medium=badge&utm_source=badge-langbot" target="_blank"><img src="https://api.producthunt.com/widgets/embed-image/v1/follow.svg?product_id=1077185&theme=light" alt="LangBot - Production&#0045;grade&#0032;IM&#0032;bot&#0032;made&#0032;easy&#0046; | Product Hunt" style="width: 250px; height: 54px;" width="250" height="54" /></a>
+
+<h3>LangBot으로 IM 봇을 빠르게 구축, 디버그 및 배포하세요.</h3>
+
+[English](README_EN.md) / [简体中文](README.md) / [繁體中文](README_TW.md) / [日本語](README_JP.md) / [Español](README_ES.md) / [Français](README_FR.md) / 한국어 / [Русский](README_RU.md) / [Tiếng Việt](README_VI.md)
+
+[![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb)](https://discord.gg/wdNEHETs87)
+[![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">홈</a> ｜
+<a href="https://docs.langbot.app/en/insight/features.html">기능 사양</a> ｜
+<a href="https://docs.langbot.app/en/insight/guide.html">배포</a> ｜
+<a href="https://docs.langbot.app/en/tags/readme.html">API 통합</a> ｜
+<a href="https://space.langbot.app">플러그인 마켓</a> ｜
+<a href="https://langbot.featurebase.app/roadmap">로드맵</a>
+
+</div>
+
+</p>
+
+## 📦 시작하기
+
+#### 빠른 시작
+
+`uvx`를 사용하여 한 명령으로 시작하세요 ([uv](https://docs.astral.sh/uv/getting-started/installation/) 설치 필요):
+
+```bash
+uvx langbot
+```
+
+http://localhost:5300을 방문하여 사용을 시작하세요.
+
+#### Docker Compose 배포
+
+```bash
+git clone https://github.com/langbot-app/LangBot
+cd LangBot/docker
+docker compose up -d
+```
+
+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)
+
+#### 기타 배포 방법
+
+릴리스 버전을 직접 사용하여 실행하려면 [수동 배포](https://docs.langbot.app/en/deploy/langbot/manual.html) 문서를 참조하세요.
+
+#### 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
+
+<img width="500" src="https://docs.langbot.app/ui/bot-page-en-rounded.png" />
+
+
+- 💬 LLM / Agent와 채팅: 여러 LLM을 지원하며 그룹 채팅 및 개인 채팅에 적응; 멀티 라운드 대화, 도구 호출, 멀티모달, 스트리밍 출력 기능을 지원합니다. 내장된 RAG(지식 베이스) 구현 및 [Dify](https://dify.ai)、[Coze](https://coze.com)、[n8n](https://n8n.io)、[Langflow](https://langflow.org)등의 LLMOps 플랫폼과 깊이 통합됩니다.
+- 🤖 다중 플랫폼 지원: 현재 QQ, QQ Channel, WeCom, 개인 WeChat, Lark, DingTalk, Discord, Telegram, KOOK, Slack, LINE 등을 지원합니다.
+- 🛠️ 높은 안정성, 풍부한 기능: 네이티브 액세스 제어, 속도 제한, 민감한 단어 필터링 등의 메커니즘; 사용하기 쉽고 여러 배포 방법을 지원합니다.
+- 🧩 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.
+- 📊 생산 수준의 기능: 여러 파이프라인 구성을 지원하며 다양한 시나리오에 대해 다른 봇을 사용할 수 있습니다. 포괄적인 모니터링 및 예외 처리 기능을 갖추고 있습니다.
+
+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 | ✅ |  |
+| 개인 QQ | ✅ |  |
+| QQ 공식 API | ✅ |  |
+| WeCom | ✅ |  |
+| WeComCS | ✅ |  |
+| WeCom AI Bot | ✅ |  |
+| 개인 WeChat | ✅ |  |
+| KOOK | ✅ |  |
+| Lark | ✅ |  |
+| DingTalk | ✅ |  |
+
+### LLMs
+
+| 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 |
+
+## 🤝 커뮤니티 기여
+
+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" />
+</a>

README_RU.md

@@ -0,0 +1,150 @@
+<p align="center">
+<a href="https://langbot.app">
+<img width="130" src="https://docs.langbot.app/langbot-logo.png" alt="LangBot"/>
+</a>
+
+<div align="center">
+
+<a href="https://www.producthunt.com/products/langbot?utm_source=badge-follow&utm_medium=badge&utm_source=badge-langbot" target="_blank"><img src="https://api.producthunt.com/widgets/embed-image/v1/follow.svg?product_id=1077185&theme=light" alt="LangBot - Production&#0045;grade&#0032;IM&#0032;bot&#0032;made&#0032;easy&#0046; | Product Hunt" style="width: 250px; height: 54px;" width="250" height="54" /></a>
+
+<h3>Быстро создавайте, отлаживайте и развертывайте IM-ботов с LangBot.</h3>
+
+[English](README_EN.md) / [简体中文](README.md) / [繁體中文](README_TW.md) / [日本語](README_JP.md) / [Español](README_ES.md) / [Français](README_FR.md) / [한국어](README_KO.md) / Русский / [Tiếng Việt](README_VI.md)
+
+[![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb)](https://discord.gg/wdNEHETs87)
+[![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">Главная</a> ｜
+<a href="https://docs.langbot.app/en/insight/features.html">Характеристики</a> ｜
+<a href="https://docs.langbot.app/en/insight/guide.html">Развертывание</a> ｜
+<a href="https://docs.langbot.app/en/tags/readme.html">Интеграция API</a> ｜
+<a href="https://space.langbot.app">Магазин плагинов</a> ｜
+<a href="https://langbot.featurebase.app/roadmap">Дорожная карта</a>
+
+</div>
+
+</p>
+
+## 📦 Начало работы
+
+#### Быстрый старт
+
+Используйте `uvx` для запуска одной командой (требуется установка [uv](https://docs.astral.sh/uv/getting-started/installation/)):
+
+```bash
+uvx langbot
+```
+
+Посетите http://localhost:5300, чтобы начать использование.
+
+#### Развертывание с Docker Compose
+
+```bash
+git clone https://github.com/langbot-app/LangBot
+cd LangBot/docker
+docker compose up -d
+```
+
+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 методы развертывания
+
+Используйте выпущенную версию напрямую для запуска, см. документацию [Ручное развертывание](https://docs.langbot.app/en/deploy/langbot/manual.html).
+
+#### 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
+
+<img width="500" src="https://docs.langbot.app/ui/bot-page-en-rounded.png" />
+
+
+- 💬 Чат с LLM / Agent: Поддержка нескольких LLM, адаптация к групповым и личным чатам; Поддержка многораундовых разговоров, вызовов инструментов, мультимодальных возможностей и потоковой передачи. Встроенная реализация RAG (база знаний) и глубокая интеграция с [Dify](https://dify.ai), [Coze](https://coze.com), [n8n](https://n8n.io), [Langflow](https://langflow.org) и др. LLMOps платформами.
+- 🤖 Многоплатформенная поддержка: В настоящее время поддерживает QQ, QQ Channel, WeCom, личный WeChat, Lark, DingTalk, Discord, Telegram, KOOK, Slack, LINE и т.д.
+- 🛠️ Высокая стабильность, богатство функций: Нативный контроль доступа, ограничение скорости, фильтрация чувствительных слов и т.д.; Простота в использовании, поддержка нескольких методов развертывания.
+- 🧩 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.
+- 📊 Функции уровня производства: Поддержка нескольких конфигураций конвейера, разные боты для разных сценариев. Имеет комплексные возможности мониторинга и обработки исключений.
+
+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 | ✅ |  |
+| Личный QQ | ✅ |  |
+| Официальный API QQ | ✅ |  |
+| WeCom | ✅ |  |
+| WeComCS | ✅ |  |
+| WeCom AI Bot | ✅ |  |
+| Личный WeChat | ✅ |  |
+| KOOK | ✅ |  |
+| Lark | ✅ |  |
+| DingTalk | ✅ |  |
+
+### LLMs
+
+| 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 |
+
+## 🤝 Вклад сообщества
+
+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" />
+</a>

README_TW.md

@@ -1,11 +1,13 @@
 <p align="center">
 <a href="https://langbot.app">
-<img src="https://docs.langbot.app/social_zh.png" alt="LangBot"/>
+<img width="130" src="https://docs.langbot.app/langbot-logo.png" alt="LangBot"/>
 </a>
 
 <div align="center"><a href="https://hellogithub.com/repository/langbot-app/LangBot" target="_blank"><img src="https://abroad.hellogithub.com/v1/widgets/recommend.svg?rid=5ce8ae2aa4f74316bf393b57b952433c&claim_uid=gtmc6YWjMZkT21R" alt="Featured｜HelloGitHub" style="width: 250px; height: 54px;" width="250" height="54" /></a>
 
-[English](README_EN.md) / [简体中文](README.md) / 繁體中文 / [日本語](README_JP.md) / (PR for your language)
+<h3>使用 LangBot 快速建構、除錯和部署 IM 機器人。</h3>
+
+[English](README_EN.md) / [简体中文](README.md) / 繁體中文 / [日本語](README_JP.md) / [Español](README_ES.md) / [Français](README_FR.md) / [한국어](README_KO.md) / [Русский](README_RU.md) / [Tiếng Việt](README_VI.md)
 
 [![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb)](https://discord.gg/wdNEHETs87)
 [![QQ Group](https://img.shields.io/badge/%E7%A4%BE%E5%8C%BAQQ%E7%BE%A4-966235608-blue)](https://qm.qq.com/q/JLi38whHum)
@@ -15,18 +17,28 @@
 [![star](https://gitcode.com/RockChinQ/LangBot/star/badge.svg)](https://gitcode.com/RockChinQ/LangBot)
 
 <a href="https://langbot.app">主頁</a> ｜
+<a href="https://docs.langbot.app/zh/insight/features.html">規格特性</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>
+<a href="https://docs.langbot.app/zh/tags/readme.html">API 整合</a> ｜
+<a href="https://space.langbot.app">外掛市場</a> ｜
+<a href="https://langbot.featurebase.app/roadmap">路線圖</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。
-
 ## 📦 開始使用
 
+#### 快速部署
+
+使用 `uvx` 一鍵啟動（需要先安裝 [uv](https://docs.astral.sh/uv/getting-started/installation/) ）：
+
+```bash
+uvx langbot
+```
+
+訪問 http://localhost:5300 即可開始使用。
+
 #### Docker Compose 部署
 
 ```bash
@@ -57,6 +69,10 @@ docker compose up -d
 
 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)。
 
+#### 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。
@@ -65,11 +81,15 @@ docker compose up -d
 
 ## ✨ 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)。
-- 🤖 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：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。
+<img width="500" src="https://docs.langbot.app/ui/bot-page-en-rounded.png" />
+
+
+- 💬 大模型對話、Agent：支援多種大模型，適配群聊和私聊；具有多輪對話、工具調用、多模態、流式輸出能力，自帶 RAG（知識庫）實現，並深度適配 [Dify](https://dify.ai)、[Coze](https://coze.com)、[n8n](https://n8n.io)、[Langflow](https://langflow.org)等 LLMOps 平台。
+- 🤖 多平台支援：目前支援 QQ、QQ頻道、企業微信、個人微信、飛書、Discord、Telegram、KOOK、Slack、LINE 等平台。
+- 🛠️ 高穩定性、功能完備：原生支援訪問控制、限速、敏感詞過濾等機制；配置簡單，支援多種部署方式。
+- 🧩 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：提供先進的 WebUI 管理面板，用最直觀的方式配置、管理、監控機器人。
+- 📊 生產級特性：支援多流水線配置，不同機器人用於不同應用場景。具有全面的監控和異常處理能力。
 
 詳細規格特性請訪問[文件](https://docs.langbot.app/zh/insight/features.html)。
 
@@ -91,6 +111,7 @@ docker compose up -d
 | 企微對外客服 | ✅ |  |
 | 企微智能機器人 | ✅ |  |
 | 微信公眾號 | ✅ |  |
+| KOOK | ✅ |  |
 | Lark | ✅ |  |
 | DingTalk | ✅ |  |
 
@@ -107,6 +128,7 @@ docker compose up -d
 | [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 |

README_VI.md

@@ -0,0 +1,150 @@
+<p align="center">
+<a href="https://langbot.app">
+<img width="130" src="https://docs.langbot.app/langbot-logo.png" alt="LangBot"/>
+</a>
+
+<div align="center">
+
+<a href="https://www.producthunt.com/products/langbot?utm_source=badge-follow&utm_medium=badge&utm_source=badge-langbot" target="_blank"><img src="https://api.producthunt.com/widgets/embed-image/v1/follow.svg?product_id=1077185&theme=light" alt="LangBot - Production&#0045;grade&#0032;IM&#0032;bot&#0032;made&#0032;easy&#0046; | Product Hunt" style="width: 250px; height: 54px;" width="250" height="54" /></a>
+
+<h3>Xây dựng, gỡ lỗi và triển khai bot IM nhanh chóng với LangBot.</h3>
+
+[English](README_EN.md) / [简体中文](README.md) / [繁體中文](README_TW.md) / [日本語](README_JP.md) / [Español](README_ES.md) / [Français](README_FR.md) / [한국어](README_KO.md) / [Русский](README_RU.md) / Tiếng Việt
+
+[![Discord](https://img.shields.io/discord/1335141740050649118?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb)](https://discord.gg/wdNEHETs87)
+[![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">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">Triển khai</a> ｜
+<a href="https://docs.langbot.app/en/tags/readme.html">Tích hợp API</a> ｜
+<a href="https://space.langbot.app">Chợ Plugin</a> ｜
+<a href="https://langbot.featurebase.app/roadmap">Lộ trình</a>
+
+</div>
+
+</p>
+
+## 📦 Bắt đầu
+
+#### Khởi động Nhanh
+
+Sử dụng `uvx` để khởi động bằng một lệnh (cần cài đặt [uv](https://docs.astral.sh/uv/getting-started/installation/)):
+
+```bash
+uvx langbot
+```
+
+Truy cập http://localhost:5300 để bắt đầu sử dụng.
+
+#### Triển khai Docker Compose
+
+```bash
+git clone https://github.com/langbot-app/LangBot
+cd LangBot/docker
+docker compose up -d
+```
+
+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)
+
+#### 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).
+
+#### 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
+
+<img width="500" src="https://docs.langbot.app/ui/bot-page-en-rounded.png" />
+
+
+- 💬 Chat với LLM / Agent: Hỗ trợ nhiều LLM, thích ứng với chat nhóm và chat riêng tư; Hỗ trợ các cuộc trò chuyện nhiều vòng, gọi công cụ, khả năng đa phương thức và đầu ra streaming. Triển khai RAG (cơ sở kiến thức) tích hợp sẵn và tích hợp sâu với [Dify](https://dify.ai), [Coze](https://coze.com), [n8n](https://n8n.io), [Langflow](https://langflow.org) v.v. LLMOps platforms.
+- 🤖 Hỗ trợ Đa nền tảng: Hiện hỗ trợ QQ, QQ Channel, WeCom, WeChat cá nhân, Lark, DingTalk, Discord, Telegram, KOOK, Slack, LINE, v.v.
+- 🛠️ Độ ổn định Cao, Tính năng Phong phú: Kiểm soát truy cập gốc, giới hạn tốc độ, lọc từ nhạy cảm, v.v.; Dễ sử dụng, hỗ trợ nhiều phương pháp triển khai.
+- 🧩 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.
+- 📊 Tính năng Cấp sản xuất: Hỗ trợ nhiều cấu hình pipeline, các bot khác nhau cho các kịch bản khác nhau. Có khả năng giám sát toàn diện và xử lý ngoại lệ.
+
+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 | ✅ |  |
+| QQ API Chính thức | ✅ |  |
+| WeCom | ✅ |  |
+| WeComCS | ✅ |  |
+| WeCom AI Bot | ✅ |  |
+| WeChat Cá nhân | ✅ |  |
+| KOOK | ✅ |  |
+| Lark | ✅ |  |
+| DingTalk | ✅ |  |
+
+### LLMs
+
+| 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 |
+
+## 🤝 Đóng góp Cộng đồng
+
+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" />
+</a>

codecov.yml

@@ -0,0 +1,4 @@
+coverage:
+  status:
+    project: off
+    patch: off

docker/README_K8S.md

@@ -0,0 +1,629 @@
+# LangBot Kubernetes 部署指南 / Kubernetes Deployment Guide
+
+[简体中文](#简体中文) | [English](#english)
+
+---
+
+## 简体中文
+
+### 概述
+
+本指南提供了在 Kubernetes 集群中部署 LangBot 的完整步骤。Kubernetes 部署配置基于 `docker-compose.yaml`，适用于生产环境的容器化部署。
+
+### 前置要求
+
+- Kubernetes 集群（版本 1.19+）
+- `kubectl` 命令行工具已配置并可访问集群
+- 集群中有可用的存储类（StorageClass）用于持久化存储（可选但推荐）
+- 至少 2 vCPU 和 4GB RAM 的可用资源
+
+### 架构说明
+
+Kubernetes 部署包含以下组件：
+
+1. **langbot**: 主应用服务
+   - 提供 Web UI（端口 5300）
+   - 处理平台 webhook（端口 2280-2290）
+   - 数据持久化卷
+   
+2. **langbot-plugin-runtime**: 插件运行时服务
+   - WebSocket 通信（端口 5400）
+   - 插件数据持久化卷
+
+3. **持久化存储**:
+   - `langbot-data`: LangBot 主数据
+   - `langbot-plugins`: 插件文件
+   - `langbot-plugin-runtime-data`: 插件运行时数据
+
+### 快速开始
+
+#### 1. 下载部署文件
+
+```bash
+# 克隆仓库
+git clone https://github.com/langbot-app/LangBot
+cd LangBot/docker
+
+# 或直接下载 kubernetes.yaml
+wget https://raw.githubusercontent.com/langbot-app/LangBot/main/docker/kubernetes.yaml
+```
+
+#### 2. 部署到 Kubernetes
+
+```bash
+# 应用所有配置
+kubectl apply -f kubernetes.yaml
+
+# 检查部署状态
+kubectl get all -n langbot
+
+# 查看 Pod 日志
+kubectl logs -n langbot -l app=langbot -f
+```
+
+#### 3. 访问 LangBot
+
+默认情况下，LangBot 服务使用 ClusterIP 类型，只能在集群内部访问。您可以选择以下方式之一来访问：
+
+**选项 A: 端口转发（推荐用于测试）**
+
+```bash
+kubectl port-forward -n langbot svc/langbot 5300:5300
+```
+
+然后访问 http://localhost:5300
+
+**选项 B: NodePort（适用于开发环境）**
+
+编辑 `kubernetes.yaml`，取消注释 NodePort Service 部分，然后：
+
+```bash
+kubectl apply -f kubernetes.yaml
+# 获取节点 IP
+kubectl get nodes -o wide
+# 访问 http://<NODE_IP>:30300
+```
+
+**选项 C: LoadBalancer（适用于云环境）**
+
+编辑 `kubernetes.yaml`，取消注释 LoadBalancer Service 部分，然后：
+
+```bash
+kubectl apply -f kubernetes.yaml
+# 获取外部 IP
+kubectl get svc -n langbot langbot-loadbalancer
+# 访问 http://<EXTERNAL_IP>
+```
+
+**选项 D: Ingress（推荐用于生产环境）**
+
+确保集群中已安装 Ingress Controller（如 nginx-ingress），然后：
+
+1. 编辑 `kubernetes.yaml` 中的 Ingress 配置
+2. 修改域名为您的实际域名
+3. 应用配置：
+
+```bash
+kubectl apply -f kubernetes.yaml
+# 访问 http://langbot.yourdomain.com
+```
+
+### 配置说明
+
+#### 环境变量
+
+在 `ConfigMap` 中配置环境变量：
+
+```yaml
+apiVersion: v1
+kind: ConfigMap
+metadata:
+  name: langbot-config
+  namespace: langbot
+data:
+  TZ: "Asia/Shanghai"  # 修改为您的时区
+```
+
+#### 存储配置
+
+默认使用动态存储分配。如果您有特定的 StorageClass，请在 PVC 中指定：
+
+```yaml
+spec:
+  storageClassName: your-storage-class-name
+  accessModes:
+    - ReadWriteOnce
+  resources:
+    requests:
+      storage: 10Gi
+```
+
+#### 资源限制
+
+根据您的需求调整资源限制：
+
+```yaml
+resources:
+  requests:
+    memory: "1Gi"
+    cpu: "500m"
+  limits:
+    memory: "4Gi"
+    cpu: "2000m"
+```
+
+### 常用操作
+
+#### 查看日志
+
+```bash
+# 查看 LangBot 主服务日志
+kubectl logs -n langbot -l app=langbot -f
+
+# 查看插件运行时日志
+kubectl logs -n langbot -l app=langbot-plugin-runtime -f
+```
+
+#### 重启服务
+
+```bash
+# 重启 LangBot
+kubectl rollout restart deployment/langbot -n langbot
+
+# 重启插件运行时
+kubectl rollout restart deployment/langbot-plugin-runtime -n langbot
+```
+
+#### 更新镜像
+
+```bash
+# 更新到最新版本
+kubectl set image deployment/langbot -n langbot langbot=rockchin/langbot:latest
+kubectl set image deployment/langbot-plugin-runtime -n langbot langbot-plugin-runtime=rockchin/langbot:latest
+
+# 检查更新状态
+kubectl rollout status deployment/langbot -n langbot
+```
+
+#### 扩容（不推荐）
+
+注意：由于 LangBot 使用 ReadWriteOnce 的持久化存储，不支持多副本扩容。如需高可用，请考虑使用 ReadWriteMany 存储或其他架构方案。
+
+#### 备份数据
+
+```bash
+# 备份 PVC 数据
+kubectl exec -n langbot -it <langbot-pod-name> -- tar czf /tmp/backup.tar.gz /app/data
+kubectl cp langbot/<langbot-pod-name>:/tmp/backup.tar.gz ./backup.tar.gz
+```
+
+### 卸载
+
+```bash
+# 删除所有资源（保留 PVC）
+kubectl delete deployment,service,configmap -n langbot --all
+
+# 删除 PVC（会删除数据）
+kubectl delete pvc -n langbot --all
+
+# 删除命名空间
+kubectl delete namespace langbot
+```
+
+### 故障排查
+
+#### Pod 无法启动
+
+```bash
+# 查看 Pod 状态
+kubectl get pods -n langbot
+
+# 查看详细信息
+kubectl describe pod -n langbot <pod-name>
+
+# 查看事件
+kubectl get events -n langbot --sort-by='.lastTimestamp'
+```
+
+#### 存储问题
+
+```bash
+# 检查 PVC 状态
+kubectl get pvc -n langbot
+
+# 检查 PV
+kubectl get pv
+```
+
+#### 网络访问问题
+
+```bash
+# 检查 Service
+kubectl get svc -n langbot
+
+# 检查端口转发
+kubectl port-forward -n langbot svc/langbot 5300:5300
+```
+
+### 生产环境建议
+
+1. **使用特定版本标签**：避免使用 `latest` 标签，使用具体版本号如 `rockchin/langbot:v1.0.0`
+2. **配置资源限制**：根据实际负载调整 CPU 和内存限制
+3. **使用 Ingress + TLS**：配置 HTTPS 访问和证书管理
+4. **配置监控和告警**：集成 Prometheus、Grafana 等监控工具
+5. **定期备份**：配置自动备份策略保护数据
+6. **使用专用 StorageClass**：为生产环境配置高性能存储
+7. **配置亲和性规则**：确保 Pod 调度到合适的节点
+
+### 高级配置
+
+#### 使用 Secrets 管理敏感信息
+
+如果需要配置 API 密钥等敏感信息：
+
+```yaml
+apiVersion: v1
+kind: Secret
+metadata:
+  name: langbot-secrets
+  namespace: langbot
+type: Opaque
+data:
+  api_key: <base64-encoded-value>
+```
+
+然后在 Deployment 中引用：
+
+```yaml
+env:
+- name: API_KEY
+  valueFrom:
+    secretKeyRef:
+      name: langbot-secrets
+      key: api_key
+```
+
+#### 配置水平自动扩缩容（HPA）
+
+注意：需要确保使用 ReadWriteMany 存储类型
+
+```yaml
+apiVersion: autoscaling/v2
+kind: HorizontalPodAutoscaler
+metadata:
+  name: langbot-hpa
+  namespace: langbot
+spec:
+  scaleTargetRef:
+    apiVersion: apps/v1
+    kind: Deployment
+    name: langbot
+  minReplicas: 1
+  maxReplicas: 3
+  metrics:
+  - type: Resource
+    resource:
+      name: cpu
+      target:
+        type: Utilization
+        averageUtilization: 70
+```
+
+### 参考资源
+
+- [LangBot 官方文档](https://docs.langbot.app)
+- [Docker 部署文档](https://docs.langbot.app/zh/deploy/langbot/docker.html)
+- [Kubernetes 官方文档](https://kubernetes.io/docs/)
+
+---
+
+## English
+
+### Overview
+
+This guide provides complete steps for deploying LangBot in a Kubernetes cluster. The Kubernetes deployment configuration is based on `docker-compose.yaml` and is suitable for production containerized deployments.
+
+### Prerequisites
+
+- Kubernetes cluster (version 1.19+)
+- `kubectl` command-line tool configured with cluster access
+- Available StorageClass in the cluster for persistent storage (optional but recommended)
+- At least 2 vCPU and 4GB RAM of available resources
+
+### Architecture
+
+The Kubernetes deployment includes the following components:
+
+1. **langbot**: Main application service
+   - Provides Web UI (port 5300)
+   - Handles platform webhooks (ports 2280-2290)
+   - Data persistence volume
+   
+2. **langbot-plugin-runtime**: Plugin runtime service
+   - WebSocket communication (port 5400)
+   - Plugin data persistence volume
+
+3. **Persistent Storage**:
+   - `langbot-data`: LangBot main data
+   - `langbot-plugins`: Plugin files
+   - `langbot-plugin-runtime-data`: Plugin runtime data
+
+### Quick Start
+
+#### 1. Download Deployment Files
+
+```bash
+# Clone repository
+git clone https://github.com/langbot-app/LangBot
+cd LangBot/docker
+
+# Or download kubernetes.yaml directly
+wget https://raw.githubusercontent.com/langbot-app/LangBot/main/docker/kubernetes.yaml
+```
+
+#### 2. Deploy to Kubernetes
+
+```bash
+# Apply all configurations
+kubectl apply -f kubernetes.yaml
+
+# Check deployment status
+kubectl get all -n langbot
+
+# View Pod logs
+kubectl logs -n langbot -l app=langbot -f
+```
+
+#### 3. Access LangBot
+
+By default, LangBot service uses ClusterIP type, accessible only within the cluster. Choose one of the following methods to access:
+
+**Option A: Port Forwarding (Recommended for testing)**
+
+```bash
+kubectl port-forward -n langbot svc/langbot 5300:5300
+```
+
+Then visit http://localhost:5300
+
+**Option B: NodePort (Suitable for development)**
+
+Edit `kubernetes.yaml`, uncomment the NodePort Service section, then:
+
+```bash
+kubectl apply -f kubernetes.yaml
+# Get node IP
+kubectl get nodes -o wide
+# Visit http://<NODE_IP>:30300
+```
+
+**Option C: LoadBalancer (Suitable for cloud environments)**
+
+Edit `kubernetes.yaml`, uncomment the LoadBalancer Service section, then:
+
+```bash
+kubectl apply -f kubernetes.yaml
+# Get external IP
+kubectl get svc -n langbot langbot-loadbalancer
+# Visit http://<EXTERNAL_IP>
+```
+
+**Option D: Ingress (Recommended for production)**
+
+Ensure an Ingress Controller (e.g., nginx-ingress) is installed in the cluster, then:
+
+1. Edit the Ingress configuration in `kubernetes.yaml`
+2. Change the domain to your actual domain
+3. Apply configuration:
+
+```bash
+kubectl apply -f kubernetes.yaml
+# Visit http://langbot.yourdomain.com
+```
+
+### Configuration
+
+#### Environment Variables
+
+Configure environment variables in ConfigMap:
+
+```yaml
+apiVersion: v1
+kind: ConfigMap
+metadata:
+  name: langbot-config
+  namespace: langbot
+data:
+  TZ: "Asia/Shanghai"  # Change to your timezone
+```
+
+#### Storage Configuration
+
+Uses dynamic storage provisioning by default. If you have a specific StorageClass, specify it in PVC:
+
+```yaml
+spec:
+  storageClassName: your-storage-class-name
+  accessModes:
+    - ReadWriteOnce
+  resources:
+    requests:
+      storage: 10Gi
+```
+
+#### Resource Limits
+
+Adjust resource limits based on your needs:
+
+```yaml
+resources:
+  requests:
+    memory: "1Gi"
+    cpu: "500m"
+  limits:
+    memory: "4Gi"
+    cpu: "2000m"
+```
+
+### Common Operations
+
+#### View Logs
+
+```bash
+# View LangBot main service logs
+kubectl logs -n langbot -l app=langbot -f
+
+# View plugin runtime logs
+kubectl logs -n langbot -l app=langbot-plugin-runtime -f
+```
+
+#### Restart Services
+
+```bash
+# Restart LangBot
+kubectl rollout restart deployment/langbot -n langbot
+
+# Restart plugin runtime
+kubectl rollout restart deployment/langbot-plugin-runtime -n langbot
+```
+
+#### Update Images
+
+```bash
+# Update to latest version
+kubectl set image deployment/langbot -n langbot langbot=rockchin/langbot:latest
+kubectl set image deployment/langbot-plugin-runtime -n langbot langbot-plugin-runtime=rockchin/langbot:latest
+
+# Check update status
+kubectl rollout status deployment/langbot -n langbot
+```
+
+#### Scaling (Not Recommended)
+
+Note: Due to LangBot using ReadWriteOnce persistent storage, multi-replica scaling is not supported. For high availability, consider using ReadWriteMany storage or alternative architectures.
+
+#### Backup Data
+
+```bash
+# Backup PVC data
+kubectl exec -n langbot -it <langbot-pod-name> -- tar czf /tmp/backup.tar.gz /app/data
+kubectl cp langbot/<langbot-pod-name>:/tmp/backup.tar.gz ./backup.tar.gz
+```
+
+### Uninstall
+
+```bash
+# Delete all resources (keep PVCs)
+kubectl delete deployment,service,configmap -n langbot --all
+
+# Delete PVCs (will delete data)
+kubectl delete pvc -n langbot --all
+
+# Delete namespace
+kubectl delete namespace langbot
+```
+
+### Troubleshooting
+
+#### Pods Not Starting
+
+```bash
+# Check Pod status
+kubectl get pods -n langbot
+
+# View detailed information
+kubectl describe pod -n langbot <pod-name>
+
+# View events
+kubectl get events -n langbot --sort-by='.lastTimestamp'
+```
+
+#### Storage Issues
+
+```bash
+# Check PVC status
+kubectl get pvc -n langbot
+
+# Check PV
+kubectl get pv
+```
+
+#### Network Access Issues
+
+```bash
+# Check Service
+kubectl get svc -n langbot
+
+# Test port forwarding
+kubectl port-forward -n langbot svc/langbot 5300:5300
+```
+
+### Production Recommendations
+
+1. **Use specific version tags**: Avoid using `latest` tag, use specific version like `rockchin/langbot:v1.0.0`
+2. **Configure resource limits**: Adjust CPU and memory limits based on actual load
+3. **Use Ingress + TLS**: Configure HTTPS access and certificate management
+4. **Configure monitoring and alerts**: Integrate monitoring tools like Prometheus, Grafana
+5. **Regular backups**: Configure automated backup strategy to protect data
+6. **Use dedicated StorageClass**: Configure high-performance storage for production
+7. **Configure affinity rules**: Ensure Pods are scheduled to appropriate nodes
+
+### Advanced Configuration
+
+#### Using Secrets for Sensitive Information
+
+If you need to configure sensitive information like API keys:
+
+```yaml
+apiVersion: v1
+kind: Secret
+metadata:
+  name: langbot-secrets
+  namespace: langbot
+type: Opaque
+data:
+  api_key: <base64-encoded-value>
+```
+
+Then reference in Deployment:
+
+```yaml
+env:
+- name: API_KEY
+  valueFrom:
+    secretKeyRef:
+      name: langbot-secrets
+      key: api_key
+```
+
+#### Configure Horizontal Pod Autoscaling (HPA)
+
+Note: Requires ReadWriteMany storage type
+
+```yaml
+apiVersion: autoscaling/v2
+kind: HorizontalPodAutoscaler
+metadata:
+  name: langbot-hpa
+  namespace: langbot
+spec:
+  scaleTargetRef:
+    apiVersion: apps/v1
+    kind: Deployment
+    name: langbot
+  minReplicas: 1
+  maxReplicas: 3
+  metrics:
+  - type: Resource
+    resource:
+      name: cpu
+      target:
+        type: Utilization
+        averageUtilization: 70
+```
+
+### References
+
+- [LangBot Official Documentation](https://docs.langbot.app)
+- [Docker Deployment Guide](https://docs.langbot.app/zh/deploy/langbot/docker.html)
+- [Kubernetes Official Documentation](https://kubernetes.io/docs/)

docker/deploy-k8s-test.sh

@@ -0,0 +1,74 @@
+#!/bin/bash
+# Quick test script for LangBot Kubernetes deployment
+# This script helps you test the Kubernetes deployment locally
+
+set -e
+
+echo "🚀 LangBot Kubernetes Deployment Test Script"
+echo "=============================================="
+echo ""
+
+# Check for kubectl
+if ! command -v kubectl &> /dev/null; then
+    echo "❌ kubectl is not installed. Please install kubectl first."
+    echo "Visit: https://kubernetes.io/docs/tasks/tools/"
+    exit 1
+fi
+
+echo "✓ kubectl is installed"
+
+# Check if kubectl can connect to a cluster
+if ! kubectl cluster-info &> /dev/null; then
+    echo ""
+    echo "⚠️  No Kubernetes cluster found."
+    echo ""
+    echo "To test locally, you can use:"
+    echo "  - kind: https://kind.sigs.k8s.io/"
+    echo "  - minikube: https://minikube.sigs.k8s.io/"
+    echo "  - k3s: https://k3s.io/"
+    echo ""
+    echo "Example with kind:"
+    echo "  kind create cluster --name langbot-test"
+    echo ""
+    exit 1
+fi
+
+echo "✓ Connected to Kubernetes cluster"
+kubectl cluster-info
+echo ""
+
+# Ask user to confirm
+read -p "Do you want to deploy LangBot to this cluster? (y/N) " -n 1 -r
+echo
+if [[ ! $REPLY =~ ^[Yy]$ ]]; then
+    echo "Deployment cancelled."
+    exit 0
+fi
+
+echo ""
+echo "📦 Deploying LangBot..."
+kubectl apply -f kubernetes.yaml
+
+echo ""
+echo "⏳ Waiting for pods to be ready..."
+kubectl wait --for=condition=ready pod -l app=langbot -n langbot --timeout=300s
+kubectl wait --for=condition=ready pod -l app=langbot-plugin-runtime -n langbot --timeout=300s
+
+echo ""
+echo "✅ Deployment complete!"
+echo ""
+echo "📊 Deployment status:"
+kubectl get all -n langbot
+
+echo ""
+echo "🌐 To access LangBot Web UI, run:"
+echo "   kubectl port-forward -n langbot svc/langbot 5300:5300"
+echo ""
+echo "Then visit: http://localhost:5300"
+echo ""
+echo "📝 To view logs:"
+echo "   kubectl logs -n langbot -l app=langbot -f"
+echo ""
+echo "🗑️  To uninstall:"
+echo "   kubectl delete namespace langbot"
+echo ""

docker/docker-compose.yaml

@@ -1,3 +1,5 @@
+# Docker Compose configuration for LangBot
+# For Kubernetes deployment, see kubernetes.yaml and README_K8S.md
 version: "3"
 
 services:
@@ -12,7 +14,7 @@ services:
     restart: on-failure
     environment:
       - TZ=Asia/Shanghai
-    command: ["uv", "run", "-m", "langbot_plugin.cli.__init__", "rt"]
+    command: ["uv", "run", "--no-sync", "-m", "langbot_plugin.cli.__init__", "rt"]
     networks:
       - langbot_network
 
@@ -21,13 +23,12 @@ services:
     container_name: langbot
     volumes:
       - ./data:/app/data
-      - ./plugins:/app/plugins
     restart: on-failure
     environment:
       - TZ=Asia/Shanghai
     ports:
-      - 5300:5300  # For web ui
-      - 2280-2290:2280-2290  # For platform webhook
+      - 5300:5300  # For web ui and webhook callback
+      - 2280-2285:2280-2285  # For platform reverse connection
     networks:
       - langbot_network
 

docker/kubernetes.yaml

@@ -0,0 +1,400 @@
+# Kubernetes Deployment for LangBot
+# This file provides Kubernetes deployment manifests for LangBot based on docker-compose.yaml
+# 
+# Usage:
+#   kubectl apply -f kubernetes.yaml
+#
+# Prerequisites:
+#   - A Kubernetes cluster (1.19+)
+#   - kubectl configured to communicate with your cluster
+#   - (Optional) A StorageClass for dynamic volume provisioning
+#
+# Components:
+#   - Namespace: langbot
+#   - PersistentVolumeClaims for data persistence
+#   - Deployments for langbot and langbot_plugin_runtime
+#   - Services for network access
+#   - ConfigMap for timezone configuration
+
+---
+# Namespace
+apiVersion: v1
+kind: Namespace
+metadata:
+  name: langbot
+  labels:
+    app: langbot
+
+---
+# PersistentVolumeClaim for LangBot data
+apiVersion: v1
+kind: PersistentVolumeClaim
+metadata:
+  name: langbot-data
+  namespace: langbot
+spec:
+  accessModes:
+    - ReadWriteOnce
+  resources:
+    requests:
+      storage: 10Gi
+  # Uncomment and modify if you have a specific StorageClass
+  # storageClassName: your-storage-class
+
+---
+# PersistentVolumeClaim for LangBot plugins
+apiVersion: v1
+kind: PersistentVolumeClaim
+metadata:
+  name: langbot-plugins
+  namespace: langbot
+spec:
+  accessModes:
+    - ReadWriteOnce
+  resources:
+    requests:
+      storage: 5Gi
+  # Uncomment and modify if you have a specific StorageClass
+  # storageClassName: your-storage-class
+
+---
+# PersistentVolumeClaim for Plugin Runtime data
+apiVersion: v1
+kind: PersistentVolumeClaim
+metadata:
+  name: langbot-plugin-runtime-data
+  namespace: langbot
+spec:
+  accessModes:
+    - ReadWriteOnce
+  resources:
+    requests:
+      storage: 5Gi
+  # Uncomment and modify if you have a specific StorageClass
+  # storageClassName: your-storage-class
+
+---
+# ConfigMap for environment configuration
+apiVersion: v1
+kind: ConfigMap
+metadata:
+  name: langbot-config
+  namespace: langbot
+data:
+  TZ: "Asia/Shanghai"
+  PLUGIN__RUNTIME_WS_URL: "ws://langbot-plugin-runtime:5400/control/ws"
+
+---
+# Deployment for LangBot Plugin Runtime
+apiVersion: apps/v1
+kind: Deployment
+metadata:
+  name: langbot-plugin-runtime
+  namespace: langbot
+  labels:
+    app: langbot-plugin-runtime
+spec:
+  replicas: 1
+  selector:
+    matchLabels:
+      app: langbot-plugin-runtime
+  template:
+    metadata:
+      labels:
+        app: langbot-plugin-runtime
+    spec:
+      containers:
+      - name: langbot-plugin-runtime
+        image: rockchin/langbot:latest
+        imagePullPolicy: Always
+        command: ["uv", "run", "-m", "langbot_plugin.cli.__init__", "rt"]
+        ports:
+        - containerPort: 5400
+          name: runtime
+          protocol: TCP
+        env:
+        - name: TZ
+          valueFrom:
+            configMapKeyRef:
+              name: langbot-config
+              key: TZ
+        volumeMounts:
+        - name: plugin-data
+          mountPath: /app/data/plugins
+        resources:
+          requests:
+            memory: "512Mi"
+            cpu: "250m"
+          limits:
+            memory: "2Gi"
+            cpu: "1000m"
+        # Liveness probe to restart container if it becomes unresponsive
+        livenessProbe:
+          tcpSocket:
+            port: 5400
+          initialDelaySeconds: 30
+          periodSeconds: 10
+          timeoutSeconds: 5
+          failureThreshold: 3
+        # Readiness probe to know when container is ready to accept traffic
+        readinessProbe:
+          tcpSocket:
+            port: 5400
+          initialDelaySeconds: 10
+          periodSeconds: 5
+          timeoutSeconds: 3
+          failureThreshold: 3
+      volumes:
+      - name: plugin-data
+        persistentVolumeClaim:
+          claimName: langbot-plugin-runtime-data
+      restartPolicy: Always
+
+---
+# Service for LangBot Plugin Runtime
+apiVersion: v1
+kind: Service
+metadata:
+  name: langbot-plugin-runtime
+  namespace: langbot
+  labels:
+    app: langbot-plugin-runtime
+spec:
+  type: ClusterIP
+  selector:
+    app: langbot-plugin-runtime
+  ports:
+  - port: 5400
+    targetPort: 5400
+    protocol: TCP
+    name: runtime
+
+---
+# Deployment for LangBot
+apiVersion: apps/v1
+kind: Deployment
+metadata:
+  name: langbot
+  namespace: langbot
+  labels:
+    app: langbot
+spec:
+  replicas: 1
+  selector:
+    matchLabels:
+      app: langbot
+  template:
+    metadata:
+      labels:
+        app: langbot
+    spec:
+      containers:
+      - name: langbot
+        image: rockchin/langbot:latest
+        imagePullPolicy: Always
+        ports:
+        - containerPort: 5300
+          name: web
+          protocol: TCP
+        - containerPort: 2280
+          name: webhook-start
+          protocol: TCP
+        # Note: Kubernetes doesn't support port ranges directly in container ports
+        # The webhook ports 2280-2290 are available, but we only expose the start of the range
+        # If you need all ports exposed, consider using a Service with multiple port definitions
+        env:
+        - name: TZ
+          valueFrom:
+            configMapKeyRef:
+              name: langbot-config
+              key: TZ
+        - name: PLUGIN__RUNTIME_WS_URL
+          valueFrom:
+            configMapKeyRef:
+              name: langbot-config
+              key: PLUGIN__RUNTIME_WS_URL
+        volumeMounts:
+        - name: data
+          mountPath: /app/data
+        - name: plugins
+          mountPath: /app/plugins
+        resources:
+          requests:
+            memory: "1Gi"
+            cpu: "500m"
+          limits:
+            memory: "4Gi"
+            cpu: "2000m"
+        # Liveness probe to restart container if it becomes unresponsive
+        livenessProbe:
+          httpGet:
+            path: /
+            port: 5300
+          initialDelaySeconds: 60
+          periodSeconds: 10
+          timeoutSeconds: 5
+          failureThreshold: 3
+        # Readiness probe to know when container is ready to accept traffic
+        readinessProbe:
+          httpGet:
+            path: /
+            port: 5300
+          initialDelaySeconds: 30
+          periodSeconds: 5
+          timeoutSeconds: 3
+          failureThreshold: 3
+      volumes:
+      - name: data
+        persistentVolumeClaim:
+          claimName: langbot-data
+      - name: plugins
+        persistentVolumeClaim:
+          claimName: langbot-plugins
+      restartPolicy: Always
+
+---
+# Service for LangBot (ClusterIP for internal access)
+apiVersion: v1
+kind: Service
+metadata:
+  name: langbot
+  namespace: langbot
+  labels:
+    app: langbot
+spec:
+  type: ClusterIP
+  selector:
+    app: langbot
+  ports:
+  - port: 5300
+    targetPort: 5300
+    protocol: TCP
+    name: web
+  - port: 2280
+    targetPort: 2280
+    protocol: TCP
+    name: webhook-2280
+  - port: 2281
+    targetPort: 2281
+    protocol: TCP
+    name: webhook-2281
+  - port: 2282
+    targetPort: 2282
+    protocol: TCP
+    name: webhook-2282
+  - port: 2283
+    targetPort: 2283
+    protocol: TCP
+    name: webhook-2283
+  - port: 2284
+    targetPort: 2284
+    protocol: TCP
+    name: webhook-2284
+  - port: 2285
+    targetPort: 2285
+    protocol: TCP
+    name: webhook-2285
+  - port: 2286
+    targetPort: 2286
+    protocol: TCP
+    name: webhook-2286
+  - port: 2287
+    targetPort: 2287
+    protocol: TCP
+    name: webhook-2287
+  - port: 2288
+    targetPort: 2288
+    protocol: TCP
+    name: webhook-2288
+  - port: 2289
+    targetPort: 2289
+    protocol: TCP
+    name: webhook-2289
+  - port: 2290
+    targetPort: 2290
+    protocol: TCP
+    name: webhook-2290
+
+---
+# Ingress for external access (Optional - requires Ingress Controller)
+# Uncomment and modify the following section if you want to expose LangBot via Ingress
+# apiVersion: networking.k8s.io/v1
+# kind: Ingress
+# metadata:
+#   name: langbot-ingress
+#   namespace: langbot
+#   annotations:
+#     # Uncomment and modify based on your ingress controller
+#     # nginx.ingress.kubernetes.io/rewrite-target: /
+#     # cert-manager.io/cluster-issuer: letsencrypt-prod
+# spec:
+#   ingressClassName: nginx  # Change based on your ingress controller
+#   rules:
+#   - host: langbot.yourdomain.com  # Change to your domain
+#     http:
+#       paths:
+#       - path: /
+#         pathType: Prefix
+#         backend:
+#           service:
+#             name: langbot
+#             port:
+#               number: 5300
+#   # Uncomment for TLS/HTTPS
+#   # tls:
+#   # - hosts:
+#   #   - langbot.yourdomain.com
+#   #   secretName: langbot-tls
+
+---
+# Service for LangBot with LoadBalancer (Alternative to Ingress)
+# Uncomment the following if you want to expose LangBot directly via LoadBalancer
+# This is useful in cloud environments (AWS, GCP, Azure, etc.)
+# apiVersion: v1
+# kind: Service
+# metadata:
+#   name: langbot-loadbalancer
+#   namespace: langbot
+#   labels:
+#     app: langbot
+# spec:
+#   type: LoadBalancer
+#   selector:
+#     app: langbot
+#   ports:
+#   - port: 80
+#     targetPort: 5300
+#     protocol: TCP
+#     name: web
+#   - port: 2280
+#     targetPort: 2280
+#     protocol: TCP
+#     name: webhook-start
+#   # Add more webhook ports as needed
+
+---
+# Service for LangBot with NodePort (Alternative for exposing service)
+# Uncomment if you want to expose LangBot via NodePort
+# This is useful for testing or when LoadBalancer is not available
+# apiVersion: v1
+# kind: Service
+# metadata:
+#   name: langbot-nodeport
+#   namespace: langbot
+#   labels:
+#     app: langbot
+# spec:
+#   type: NodePort
+#   selector:
+#     app: langbot
+#   ports:
+#   - port: 5300
+#     targetPort: 5300
+#     nodePort: 30300  # Must be in range 30000-32767
+#     protocol: TCP
+#     name: web
+#   - port: 2280
+#     targetPort: 2280
+#     nodePort: 30280  # Must be in range 30000-32767
+#     protocol: TCP
+#     name: webhook

docs/API_KEY_AUTH.md

@@ -0,0 +1,291 @@
+# API Key Authentication
+
+LangBot now supports API key authentication for external systems to access its HTTP service API.
+
+## Managing API Keys
+
+API keys can be managed through the web interface:
+
+1. Log in to the LangBot web interface
+2. Click the "API Keys" button at the bottom of the sidebar
+3. Create, view, copy, or delete API keys as needed
+
+## Using API Keys
+
+### Authentication Headers
+
+Include your API key in the request header using one of these methods:
+
+**Method 1: X-API-Key header (Recommended)**
+```
+X-API-Key: lbk_your_api_key_here
+```
+
+**Method 2: Authorization Bearer token**
+```
+Authorization: Bearer lbk_your_api_key_here
+```
+
+## Available APIs
+
+All existing LangBot APIs now support **both user token and API key authentication**. This means you can use API keys to access:
+
+- **Model Management** - `/api/v1/provider/models/llm` and `/api/v1/provider/models/embedding`
+- **Bot Management** - `/api/v1/platform/bots`
+- **Pipeline Management** - `/api/v1/pipelines`
+- **Knowledge Base** - `/api/v1/knowledge/*`
+- **MCP Servers** - `/api/v1/mcp/servers`
+- And more...
+
+### Authentication Methods
+
+Each endpoint accepts **either**:
+1. **User Token** (via `Authorization: Bearer <user_jwt_token>`) - for web UI and authenticated users
+2. **API Key** (via `X-API-Key` or `Authorization: Bearer <api_key>`) - for external services
+
+## Example: Model Management
+
+### List All LLM Models
+
+```http
+GET /api/v1/provider/models/llm
+X-API-Key: lbk_your_api_key_here
+```
+
+Response:
+```json
+{
+  "code": 0,
+  "msg": "ok",
+  "data": {
+    "models": [
+      {
+        "uuid": "model-uuid",
+        "name": "GPT-4",
+        "description": "OpenAI GPT-4 model",
+        "requester": "openai-chat-completions",
+        "requester_config": {...},
+        "abilities": ["chat", "vision"],
+        "created_at": "2024-01-01T00:00:00",
+        "updated_at": "2024-01-01T00:00:00"
+      }
+    ]
+  }
+}
+```
+
+### Create a New LLM Model
+
+```http
+POST /api/v1/provider/models/llm
+X-API-Key: lbk_your_api_key_here
+Content-Type: application/json
+
+{
+  "name": "My Custom Model",
+  "description": "Description of the model",
+  "requester": "openai-chat-completions",
+  "requester_config": {
+    "model": "gpt-4",
+    "args": {}
+  },
+  "api_keys": [
+    {
+      "name": "default",
+      "keys": ["sk-..."]
+    }
+  ],
+  "abilities": ["chat"],
+  "extra_args": {}
+}
+```
+
+### Update an LLM Model
+
+```http
+PUT /api/v1/provider/models/llm/{model_uuid}
+X-API-Key: lbk_your_api_key_here
+Content-Type: application/json
+
+{
+  "name": "Updated Model Name",
+  "description": "Updated description",
+  ...
+}
+```
+
+### Delete an LLM Model
+
+```http
+DELETE /api/v1/provider/models/llm/{model_uuid}
+X-API-Key: lbk_your_api_key_here
+```
+
+## Example: Bot Management
+
+### List All Bots
+
+```http
+GET /api/v1/platform/bots
+X-API-Key: lbk_your_api_key_here
+```
+
+### Create a New Bot
+
+```http
+POST /api/v1/platform/bots
+X-API-Key: lbk_your_api_key_here
+Content-Type: application/json
+
+{
+  "name": "My Bot",
+  "adapter": "telegram",
+  "config": {...}
+}
+```
+
+## Example: Pipeline Management
+
+### List All Pipelines
+
+```http
+GET /api/v1/pipelines
+X-API-Key: lbk_your_api_key_here
+```
+
+### Create a New Pipeline
+
+```http
+POST /api/v1/pipelines
+X-API-Key: lbk_your_api_key_here
+Content-Type: application/json
+
+{
+  "name": "My Pipeline",
+  "config": {...}
+}
+```
+
+## Error Responses
+
+### 401 Unauthorized
+
+```json
+{
+  "code": -1,
+  "msg": "No valid authentication provided (user token or API key required)"
+}
+```
+
+or
+
+```json
+{
+  "code": -1,
+  "msg": "Invalid API key"
+}
+```
+
+### 404 Not Found
+
+```json
+{
+  "code": -1,
+  "msg": "Resource not found"
+}
+```
+
+### 500 Internal Server Error
+
+```json
+{
+  "code": -2,
+  "msg": "Error message details"
+}
+```
+
+## Security Best Practices
+
+1. **Keep API keys secure**: Store them securely and never commit them to version control
+2. **Use HTTPS**: Always use HTTPS in production to encrypt API key transmission
+3. **Rotate keys regularly**: Create new API keys periodically and delete old ones
+4. **Use descriptive names**: Give your API keys meaningful names to track their usage
+5. **Delete unused keys**: Remove API keys that are no longer needed
+6. **Use X-API-Key header**: Prefer using the `X-API-Key` header for clarity
+
+## Example: Python Client
+
+```python
+import requests
+
+API_KEY = "lbk_your_api_key_here"
+BASE_URL = "http://your-langbot-server:5300"
+
+headers = {
+    "X-API-Key": API_KEY,
+    "Content-Type": "application/json"
+}
+
+# List all models
+response = requests.get(f"{BASE_URL}/api/v1/provider/models/llm", headers=headers)
+models = response.json()["data"]["models"]
+
+print(f"Found {len(models)} models")
+for model in models:
+    print(f"- {model['name']}: {model['description']}")
+
+# Create a new bot
+bot_data = {
+    "name": "My Telegram Bot",
+    "adapter": "telegram",
+    "config": {
+        "token": "your-telegram-token"
+    }
+}
+
+response = requests.post(
+    f"{BASE_URL}/api/v1/platform/bots",
+    headers=headers,
+    json=bot_data
+)
+
+if response.status_code == 200:
+    bot_uuid = response.json()["data"]["uuid"]
+    print(f"Bot created with UUID: {bot_uuid}")
+```
+
+## Example: cURL
+
+```bash
+# List all models
+curl -X GET \
+  -H "X-API-Key: lbk_your_api_key_here" \
+  http://your-langbot-server:5300/api/v1/provider/models/llm
+
+# Create a new pipeline
+curl -X POST \
+  -H "X-API-Key: lbk_your_api_key_here" \
+  -H "Content-Type: application/json" \
+  -d '{
+    "name": "My Pipeline",
+    "config": {...}
+  }' \
+  http://your-langbot-server:5300/api/v1/pipelines
+
+# Get bot logs
+curl -X POST \
+  -H "X-API-Key: lbk_your_api_key_here" \
+  -H "Content-Type: application/json" \
+  -d '{
+    "from_index": -1,
+    "max_count": 10
+  }' \
+  http://your-langbot-server:5300/api/v1/platform/bots/{bot_uuid}/logs
+```
+
+## Notes
+
+- The same endpoints work for both the web UI (with user tokens) and external services (with API keys)
+- No need to learn different API paths - use the existing API documentation with API key authentication
+- All endpoints that previously required user authentication now also accept API keys
+

docs/MIGRATION_SUMMARY.md

@@ -0,0 +1,412 @@
+# WebChat 到 WebSocket 迁移总结
+
+## 概述
+
+已完全移除旧的基于SSE的WebChat系统，并替换为基于WebSocket的双向实时通信系统。这是一个内置在LangBot中的完整IM系统，支持流式输出。
+
+## 已删除的文件
+
+### 后端
+- ❌ `src/langbot/pkg/api/http/controller/groups/pipelines/webchat.py` - 旧的SSE路由
+- ❌ `src/langbot/pkg/platform/sources/webchat.py` - 旧的WebChat适配器
+- ❌ `src/langbot/pkg/platform/sources/webchat.yaml` - 旧的配置文件
+
+### 前端
+- ❌ BackendClient中所有SSE相关代码已完全移除
+- ❌ DebugDialog中所有SSE相关逻辑已完全替换
+
+## 新增的文件
+
+### 后端核心文件
+
+**1. WebSocket连接管理器**
+```
+src/langbot/pkg/platform/sources/websocket_manager.py
+```
+- 管理所有并发WebSocket连接
+- 线程安全的连接池
+- 按流水线、会话类型分组
+- 广播和单播消息功能
+- 连接统计和监控
+
+**2. WebSocket适配器**
+```
+src/langbot/pkg/platform/sources/websocket_adapter.py
+```
+- 实现平台适配器接口
+- **完整流式支持** (`reply_message_chunk` 方法)
+- 双向消息流处理
+- 消息历史管理
+- 会话管理
+
+**3. WebSocket路由控制器**
+```
+src/langbot/pkg/api/http/controller/groups/pipelines/websocket_chat.py
+```
+- WebSocket端点处理
+- REST API接口
+- 心跳机制
+- 连接生命周期管理
+
+**4. 配置文件**
+```
+src/langbot/pkg/platform/sources/websocket.yaml
+```
+- WebSocket适配器元数据
+
+### 前端核心文件
+
+**1. WebSocket客户端**
+```
+web/src/app/infra/websocket/WebSocketClient.ts
+```
+- WebSocket连接管理
+- 自动重连（最多5次）
+- 心跳机制（30秒）
+- 事件回调系统
+
+**2. 更新的组件**
+```
+web/src/app/home/pipelines/components/debug-dialog/DebugDialog.tsx
+```
+- 完全重写，使用WebSocket
+- 实时连接状态显示
+- 流式消息支持
+- 自动重连
+
+**3. HTTP客户端更新**
+```
+web/src/app/infra/http/BackendClient.ts
+```
+- 移除所有旧的WebChat API
+- 仅保留WebSocket API
+
+### 测试工具
+
+**Python测试客户端**
+```
+test_websocket_client.py
+```
+- 单连接交互测试
+- 多连接并发测试
+- 命令行工具
+
+### 文档
+
+**使用文档**
+```
+WEBSOCKET_README.md
+```
+- 完整的API文档
+- 架构说明
+- 使用示例
+- 故障排查
+
+## 核心变更
+
+### 后端变更
+
+**1. botmgr.py**
+- ❌ 移除 `webchat_proxy_bot`
+- ✅ 仅保留 `websocket_proxy_bot`
+- ✅ 更新适配器过滤逻辑（排除`websocket`而非`webchat`）
+
+**2. 适配器注册**
+```python
+# 旧代码（已删除）
+webchat_adapter_class = self.adapter_dict['webchat']
+self.webchat_proxy_bot = RuntimeBot(...)
+
+# 新代码
+websocket_adapter_class = self.adapter_dict['websocket']
+self.websocket_proxy_bot = RuntimeBot(
+    uuid='websocket-proxy-bot',
+    name='WebSocket',
+    adapter='websocket',
+    ...
+)
+```
+
+### 前端变更
+
+**1. API调用完全更换**
+
+旧代码（已删除）:
+```typescript
+// SSE流式请求
+await fetch(url, {
+  method: 'POST',
+  body: JSON.stringify({ is_stream: true })
+})
+// 手动解析 text/event-stream
+```
+
+新代码:
+```typescript
+// WebSocket实时通信
+const wsClient = new WebSocketClient(pipelineId, sessionType);
+await wsClient.connect();
+
+wsClient.onMessage((message) => {
+  // 流式消息自动处理
+  setMessages(prev => [...prev, message]);
+});
+
+wsClient.sendMessage(messageChain);
+```
+
+**2. 连接状态管理**
+
+新增功能:
+- ✅ 实时连接状态指示器（绿色/红色圆点）
+- ✅ 连接/断开toast提示
+- ✅ 自动重连逻辑
+- ✅ 心跳保活
+
+**3. 流式支持**
+
+完整的流式消息处理:
+```typescript
+wsClient.onMessage((message) => {
+  if (message.is_final) {
+    // 最终消息
+    finalizeBotMessage(message);
+  } else {
+    // 中间消息块，实时更新UI
+    updateBotMessage(message);
+  }
+});
+```
+
+## API对比
+
+### WebSocket端点
+
+**连接**
+```
+ws://localhost:8000/api/v1/pipelines/<pipeline_uuid>/ws/connect?session_type=<person|group>
+```
+
+**消息格式**
+
+客户端发送:
+```json
+{
+  "type": "message",
+  "message": [
+    {"type": "Plain", "text": "你好"}
+  ]
+}
+```
+
+服务器响应（流式）:
+```json
+{
+  "type": "response",
+  "data": {
+    "id": 1,
+    "role": "assistant",
+    "content": "你好，我是...",
+    "is_final": false,
+    "timestamp": "2025-01-28T..."
+  }
+}
+```
+
+### REST API
+
+| 端点 | 方法 | 说明 |
+|------|------|------|
+| `/api/v1/pipelines/<uuid>/ws/messages/<type>` | GET | 获取消息历史 |
+| `/api/v1/pipelines/<uuid>/ws/reset/<type>` | POST | 重置会话 |
+| `/api/v1/pipelines/<uuid>/ws/connections` | GET | 获取连接统计 |
+| `/api/v1/pipelines/<uuid>/ws/broadcast` | POST | 广播消息 |
+
+## 流式支持详解
+
+### 后端流式实现
+
+**WebSocket Adapter**
+```python
+async def reply_message_chunk(
+    self,
+    message_source: platform_events.MessageEvent,
+    bot_message,
+    message: platform_message.MessageChain,
+    quote_origin: bool = False,
+    is_final: bool = False,
+) -> dict:
+    """回复消息块 - 流式"""
+    message_data = WebSocketMessage(
+        id=-1,
+        role='assistant',
+        content=str(message),
+        message_chain=[component.__dict__ for component in message],
+        timestamp=datetime.now().isoformat(),
+        is_final=is_final and bot_message.tool_calls is None,
+    )
+
+    # 发送到队列，由WebSocket连接处理发送
+    await session.resp_queues[message_id].put(message_data)
+    return message_data.model_dump()
+
+async def is_stream_output_supported(self) -> bool:
+    """WebSocket始终支持流式输出"""
+    return True
+```
+
+### 前端流式处理
+
+**DebugDialog组件**
+```typescript
+wsClient.onMessage((message) => {
+  setMessages((prevMessages) => {
+    const existingIndex = prevMessages.findIndex(
+      (msg) => msg.role === 'assistant' && msg.content === 'Generating...'
+    );
+
+    if (existingIndex !== -1) {
+      // 更新正在生成的消息
+      const updatedMessages = [...prevMessages];
+      updatedMessages[existingIndex] = message;
+      return updatedMessages;
+    } else {
+      // 添加新消息
+      return [...prevMessages, message];
+    }
+  });
+});
+```
+
+## 兼容性说明
+
+### ⚠️ 不兼容旧版本
+
+此次迁移**完全不兼容**旧的WebChat系统：
+
+1. **API端点变更**
+   - 旧: `/api/v1/pipelines/<uuid>/chat/send`
+   - 新: `ws://.../<uuid>/ws/connect`
+
+2. **通信协议变更**
+   - 旧: HTTP + SSE (Server-Sent Events)
+   - 新: WebSocket (双向)
+
+3. **流式实现变更**
+   - 旧: `text/event-stream` 格式
+   - 新: WebSocket JSON消息
+
+### 迁移要求
+
+使用新系统需要:
+1. ✅ 前端必须支持WebSocket
+2. ✅ 后端必须运行新的WebSocket适配器
+3. ✅ 清除旧的WebChat相关配置
+
+## 优势对比
+
+| 特性 | 旧WebChat (SSE) | 新WebSocket |
+|------|----------------|-------------|
+| 双向通信 | ❌ 单向（服务器→客户端） | ✅ 双向 |
+| 主动推送 | ❌ 不支持 | ✅ 支持 |
+| 连接管理 | ❌ 无状态 | ✅ 有状态，完整生命周期 |
+| 流式输出 | ✅ 支持 | ✅ 支持（更优） |
+| 心跳机制 | ❌ 无 | ✅ 30秒心跳 |
+| 自动重连 | ❌ 无 | ✅ 最多5次 |
+| 多连接 | ⚠️ 难以管理 | ✅ 完整支持 |
+| 连接状态 | ❌ 不可见 | ✅ 实时显示 |
+| 广播功能 | ❌ 不支持 | ✅ 支持 |
+
+## 测试方式
+
+### 1. Python测试客户端
+
+```bash
+# 单连接测试
+python test_websocket_client.py <pipeline_uuid>
+
+# 指定会话类型
+python test_websocket_client.py <pipeline_uuid> --session-type group
+
+# 多连接并发测试（5个连接）
+python test_websocket_client.py <pipeline_uuid> --multi 5
+```
+
+### 2. 前端测试
+
+1. 启动LangBot服务器
+2. 访问前端界面
+3. 打开流水线调试对话框
+4. 观察连接状态指示器（左下角圆点）
+5. 发送消息测试流式响应
+
+### 3. 浏览器控制台测试
+
+```javascript
+const ws = new WebSocket('ws://localhost:8000/api/v1/pipelines/<uuid>/ws/connect?session_type=person');
+
+ws.onopen = () => {
+  console.log('已连接');
+  ws.send(JSON.stringify({
+    type: 'message',
+    message: [{type: 'Plain', text: '你好'}]
+  }));
+};
+
+ws.onmessage = (event) => {
+  console.log('收到:', JSON.parse(event.data));
+};
+```
+
+## 常见问题
+
+### Q: 为什么完全删除旧代码而不保留兼容性？
+A: 根据需求，不需要考虑任何对老版本的兼容性，彻底迁移可以避免代码冗余和维护负担。
+
+### Q: 流式输出如何工作？
+A:
+1. 后端通过`reply_message_chunk`发送消息块
+2. 消息块放入队列
+3. WebSocket连接从队列取出并发送
+4. 前端实时更新UI
+5. `is_final=true`表示最后一块
+
+### Q: 如何确保连接不断开？
+A:
+1. 客户端每30秒发送心跳（ping）
+2. 服务器响应pong
+3. 连接断开时自动重连（最多5次）
+
+### Q: 如何实现后端主动推送？
+A:
+1. 调用 `/api/v1/pipelines/<uuid>/ws/broadcast` API
+2. 消息会被推送到该流水线的所有连接
+3. 前端通过`onBroadcast`回调接收
+
+## 总结
+
+✅ **完成的工作**
+- 完全移除旧的WebChat/SSE系统
+- 实现完整的WebSocket双向通信系统
+- 支持流式输出
+- 支持多连接并发
+- 实现自动重连和心跳机制
+- 提供完整的测试工具和文档
+
+✅ **核心特性**
+- 双向实时通信
+- 流式消息支持
+- 多连接管理
+- 自动重连
+- 心跳保活
+- 连接状态可视化
+- 广播消息
+
+✅ **技术亮点**
+- 异步架构（asyncio）
+- 线程安全的连接管理
+- 独立的消息队列
+- 完整的错误处理
+- 模块化设计
+
+🎉 系统已完全迁移到WebSocket，无任何旧代码遗留！

docs/PYPI_INSTALLATION.md

@@ -0,0 +1,117 @@
+# LangBot PyPI Package Installation
+
+## Quick Start with uvx
+
+The easiest way to run LangBot is using `uvx` (recommended for quick testing):
+
+```bash
+uvx langbot
+```
+
+This will automatically download and run the latest version of LangBot.
+
+## Install with pip/uv
+
+You can also install LangBot as a regular Python package:
+
+```bash
+# Using pip
+pip install langbot
+
+# Using uv
+uv pip install langbot
+```
+
+Then run it:
+
+```bash
+langbot
+```
+
+Or using Python module syntax:
+
+```bash
+python -m langbot
+```
+
+## Installation with Frontend
+
+When published to PyPI, the LangBot package includes the pre-built frontend files. You don't need to build the frontend separately.
+
+## Data Directory
+
+When running LangBot as a package, it will create a `data/` directory in your current working directory to store configuration, logs, and other runtime data. You can run LangBot from any directory, and it will set up its data directory there.
+
+## Command Line Options
+
+LangBot supports the following command line options:
+
+- `--standalone-runtime`: Use standalone plugin runtime
+- `--debug`: Enable debug mode
+
+Example:
+
+```bash
+langbot --debug
+```
+
+## Comparison with Other Installation Methods
+
+### PyPI Package (uvx/pip)
+- **Pros**: Easy to install and update, no need to clone repository or build frontend
+- **Cons**: Less flexible for development/customization
+
+### Docker
+- **Pros**: Isolated environment, easy deployment
+- **Cons**: Requires Docker
+
+### Manual Source Installation
+- **Pros**: Full control, easy to customize and develop
+- **Cons**: Requires building frontend, managing dependencies manually
+
+## Development
+
+If you want to contribute or customize LangBot, you should still use the manual installation method by cloning the repository:
+
+```bash
+git clone https://github.com/langbot-app/LangBot
+cd LangBot
+uv sync
+cd web
+npm install
+npm run build
+cd ..
+uv run main.py
+```
+
+## Updating
+
+To update to the latest version:
+
+```bash
+# With pip
+pip install --upgrade langbot
+
+# With uv
+uv pip install --upgrade langbot
+
+# With uvx (automatically uses latest)
+uvx langbot
+```
+
+## System Requirements
+
+- Python 3.10.1 or higher
+- Operating System: Linux, macOS, or Windows
+
+## Differences from Source Installation
+
+When running LangBot from the PyPI package (via uvx or pip), there are a few behavioral differences compared to running from source:
+
+1. **Version Check**: The package version does not prompt for user input when the Python version is incompatible. It simply prints an error message and exits. This makes it compatible with non-interactive environments like containers and CI/CD.
+
+2. **Working Directory**: The package version does not require being run from the LangBot project root. You can run `langbot` from any directory, and it will create a `data/` directory in your current working directory.
+
+3. **Frontend Files**: The frontend is pre-built and included in the package, so you don't need to run `npm build` separately.
+
+These differences are intentional to make the package more user-friendly and suitable for various deployment scenarios.

docs/SEEKDB_INTEGRATION.md

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

docs/WEBSOCKET_README.md

@@ -0,0 +1,394 @@
+# LangBot WebSocket 双向通信系统
+
+## 概述
+
+这是一个内置在 LangBot 中的完整 IM (即时通讯) 系统，支持：
+
+- ✅ WebSocket 双向实时通信
+- ✅ 多个客户端并发连接
+- ✅ 前端到后端的消息发送
+- ✅ 后端到前端的主动推送
+- ✅ 流式响应支持
+- ✅ 连接管理和会话隔离
+- ✅ 心跳机制
+- ✅ 广播消息功能
+
+## 架构设计
+
+### 核心组件
+
+1. **WebSocketConnectionManager** (`websocket_manager.py`)
+   - 管理所有活跃的 WebSocket 连接
+   - 支持按流水线、会话类型查询连接
+   - 提供广播和单播功能
+   - 线程安全的并发访问控制
+
+2. **WebSocketAdapter** (`websocket_adapter.py`)
+   - 实现平台适配器接口
+   - 处理消息的接收和发送
+   - 支持流式输出
+   - 管理消息历史
+
+3. **WebSocketChatRouterGroup** (`websocket_chat.py`)
+   - WebSocket 路由控制器
+   - 处理连接建立、消息收发
+   - 实现心跳机制
+   - 提供 REST API 接口
+
+## API 接口
+
+### WebSocket 连接
+
+#### 建立连接
+
+```
+ws://localhost:8000/api/v1/pipelines/<pipeline_uuid>/ws/connect?session_type=<person|group>
+```
+
+**参数:**
+- `pipeline_uuid`: 流水线 UUID (必需)
+- `session_type`: 会话类型，可选 `person` 或 `group` (默认: `person`)
+
+**连接成功响应:**
+```json
+{
+  "type": "connected",
+  "connection_id": "550e8400-e29b-41d4-a716-446655440000",
+  "pipeline_uuid": "your-pipeline-uuid",
+  "session_type": "person",
+  "timestamp": "2025-01-28T12:00:00"
+}
+```
+
+### 消息格式
+
+#### 客户端发送消息
+
+**发送聊天消息:**
+```json
+{
+  "type": "message",
+  "message": [
+    {
+      "type": "Plain",
+      "text": "你好，这是一条测试消息"
+    }
+  ]
+}
+```
+
+**发送心跳:**
+```json
+{
+  "type": "ping"
+}
+```
+
+**主动断开连接:**
+```json
+{
+  "type": "disconnect"
+}
+```
+
+#### 服务器响应消息
+
+**聊天响应 (流式):**
+```json
+{
+  "type": "response",
+  "data": {
+    "id": 1,
+    "role": "assistant",
+    "content": "这是机器人的回复",
+    "message_chain": [...],
+    "timestamp": "2025-01-28T12:00:00",
+    "is_final": false,
+    "connection_id": "..."
+  }
+}
+```
+
+**心跳响应:**
+```json
+{
+  "type": "pong",
+  "timestamp": "2025-01-28T12:00:00"
+}
+```
+
+**广播消息:**
+```json
+{
+  "type": "broadcast",
+  "message": "这是一条广播消息",
+  "timestamp": "2025-01-28T12:00:00"
+}
+```
+
+**错误消息:**
+```json
+{
+  "type": "error",
+  "message": "错误描述"
+}
+```
+
+### REST API 接口
+
+#### 1. 获取消息历史
+
+```http
+GET /api/v1/pipelines/<pipeline_uuid>/ws/messages/<session_type>
+```
+
+**响应:**
+```json
+{
+  "code": 0,
+  "msg": "ok",
+  "data": {
+    "messages": [...]
+  }
+}
+```
+
+#### 2. 重置会话
+
+```http
+POST /api/v1/pipelines/<pipeline_uuid>/ws/reset/<session_type>
+```
+
+**响应:**
+```json
+{
+  "code": 0,
+  "msg": "ok",
+  "data": {
+    "message": "Session reset successfully"
+  }
+}
+```
+
+#### 3. 获取连接统计
+
+```http
+GET /api/v1/pipelines/<pipeline_uuid>/ws/connections
+```
+
+**响应:**
+```json
+{
+  "code": 0,
+  "msg": "ok",
+  "data": {
+    "stats": {
+      "total_connections": 5,
+      "pipelines": 2,
+      "connections_by_pipeline": {
+        "pipeline-1": 3,
+        "pipeline-2": 2
+      },
+      "connections_by_session_type": {
+        "person": 4,
+        "group": 1
+      }
+    },
+    "connections": [
+      {
+        "connection_id": "...",
+        "session_type": "person",
+        "created_at": "2025-01-28T12:00:00",
+        "last_active": "2025-01-28T12:05:00",
+        "is_active": true
+      }
+    ]
+  }
+}
+```
+
+#### 4. 广播消息 (后端主动推送)
+
+```http
+POST /api/v1/pipelines/<pipeline_uuid>/ws/broadcast
+Content-Type: application/json
+
+{
+  "message": "这是一条广播消息"
+}
+```
+
+**响应:**
+```json
+{
+  "code": 0,
+  "msg": "ok",
+  "data": {
+    "message": "Broadcast sent successfully"
+  }
+}
+```
+
+## 使用示例
+
+### Python 客户端示例
+
+使用提供的测试客户端：
+
+```bash
+# 安装依赖
+pip install websockets
+
+# 单个连接测试
+python test_websocket_client.py <pipeline_uuid>
+
+# 指定会话类型
+python test_websocket_client.py <pipeline_uuid> --session-type group
+
+# 多连接并发测试
+python test_websocket_client.py <pipeline_uuid> --multi 5
+```
+
+### JavaScript 客户端示例
+
+```javascript
+// 建立 WebSocket 连接
+const ws = new WebSocket('ws://localhost:8000/api/v1/pipelines/your-pipeline-uuid/ws/connect?session_type=person');
+
+// 连接建立
+ws.onopen = () => {
+  console.log('WebSocket 连接已建立');
+
+  // 发送消息
+  ws.send(JSON.stringify({
+    type: 'message',
+    message: [
+      {
+        type: 'Plain',
+        text: '你好'
+      }
+    ]
+  }));
+};
+
+// 接收消息
+ws.onmessage = (event) => {
+  const data = JSON.parse(event.data);
+
+  if (data.type === 'connected') {
+    console.log('连接成功:', data.connection_id);
+  } else if (data.type === 'response') {
+    console.log('机器人回复:', data.data.content);
+    if (data.data.is_final) {
+      console.log('响应完成');
+    }
+  } else if (data.type === 'broadcast') {
+    console.log('收到广播:', data.message);
+  }
+};
+
+// 连接关闭
+ws.onclose = () => {
+  console.log('WebSocket 连接已关闭');
+};
+
+// 错误处理
+ws.onerror = (error) => {
+  console.error('WebSocket 错误:', error);
+};
+
+// 发送心跳
+setInterval(() => {
+  if (ws.readyState === WebSocket.OPEN) {
+    ws.send(JSON.stringify({ type: 'ping' }));
+  }
+}, 30000); // 每 30 秒发送一次心跳
+```
+
+## 特性说明
+
+### 1. 多连接支持
+
+系统支持同时建立多个 WebSocket 连接，每个连接都有唯一的 `connection_id`。连接按照流水线和会话类型进行分组管理。
+
+### 2. 双向通信
+
+- **前端 → 后端**: 客户端可以主动发送消息给服务器
+- **后端 → 前端**: 服务器可以通过广播 API 主动推送消息给客户端
+
+### 3. 流式响应
+
+支持流式输出，机器人的响应会分块发送，客户端可以实时显示部分响应内容。
+
+### 4. 会话隔离
+
+支持 `person` 和 `group` 两种会话类型，不同类型的会话消息历史互不影响。
+
+### 5. 连接管理
+
+- 自动追踪连接状态
+- 记录最后活跃时间
+- 支持连接统计查询
+- 连接断开时自动清理资源
+
+### 6. 心跳机制
+
+客户端可以定期发送 `ping` 消息，服务器会响应 `pong`，用于保持连接活跃和检测连接状态。
+
+## 架构优势
+
+1. **高并发**: 使用 asyncio 异步架构，支持大量并发连接
+2. **可扩展**: 模块化设计，易于扩展新功能
+3. **线程安全**: 连接管理器使用锁机制保证并发安全
+4. **消息队列**: 每个连接独立的发送队列，避免消息混乱
+5. **灵活路由**: 支持按流水线、会话类型灵活路由消息
+
+## 注意事项
+
+1. **认证**: 当前 WebSocket 连接不需要认证，生产环境建议添加认证机制
+2. **心跳**: 建议客户端实现心跳机制，避免连接超时
+3. **重连**: 客户端应实现断线重连逻辑
+4. **消息大小**: 注意控制单条消息大小，避免内存溢出
+5. **连接数限制**: 生产环境建议设置最大连接数限制
+
+## 故障排查
+
+### 连接失败
+
+1. 检查流水线 UUID 是否正确
+2. 检查服务器是否正常运行
+3. 检查防火墙设置
+
+### 消息发送失败
+
+1. 检查消息格式是否正确
+2. 检查连接是否仍然活跃
+3. 查看服务器日志获取详细错误信息
+
+### 性能问题
+
+1. 检查并发连接数是否过多
+2. 检查消息处理速度
+3. 考虑使用连接池或负载均衡
+
+## 开发调试
+
+启用详细日志：
+
+```python
+import logging
+logging.getLogger('langbot.pkg.platform.sources.websocket_adapter').setLevel(logging.DEBUG)
+logging.getLogger('langbot.pkg.platform.sources.websocket_manager').setLevel(logging.DEBUG)
+logging.getLogger('langbot.pkg.api.http.controller.groups.pipelines.websocket_chat').setLevel(logging.DEBUG)
+```
+
+## 后续改进建议
+
+1. 添加用户认证和授权机制
+2. 实现消息持久化
+3. 添加消息加密
+4. 实现更丰富的消息类型 (图片、文件等)
+5. 添加消息已读/未读状态
+6. 实现群组聊天功能
+7. 添加在线状态显示
+8. 实现消息撤回功能

libs/dify_service_api/test.py

@@ -1,45 +0,0 @@
-from v1 import client  # type: ignore
-
-import asyncio
-
-import os
-import json
-
-
-class TestDifyClient:
-    async def test_chat_messages(self):
-        cln = client.AsyncDifyServiceClient(api_key=os.getenv('DIFY_API_KEY'), base_url=os.getenv('DIFY_BASE_URL'))
-
-        async for chunk in cln.chat_messages(inputs={}, query='调用工具查看现在几点？', user='test'):
-            print(json.dumps(chunk, ensure_ascii=False, indent=4))
-
-    async def test_upload_file(self):
-        cln = client.AsyncDifyServiceClient(api_key=os.getenv('DIFY_API_KEY'), base_url=os.getenv('DIFY_BASE_URL'))
-
-        file_bytes = open('img.png', 'rb').read()
-
-        print(type(file_bytes))
-
-        file = ('img2.png', file_bytes, 'image/png')
-
-        resp = await cln.upload_file(file=file, user='test')
-        print(json.dumps(resp, ensure_ascii=False, indent=4))
-
-    async def test_workflow_run(self):
-        cln = client.AsyncDifyServiceClient(api_key=os.getenv('DIFY_API_KEY'), base_url=os.getenv('DIFY_BASE_URL'))
-
-        # resp = await cln.workflow_run(inputs={}, user="test")
-        # # print(json.dumps(resp, ensure_ascii=False, indent=4))
-        # print(resp)
-        chunks = []
-
-        ignored_events = ['text_chunk']
-        async for chunk in cln.workflow_run(inputs={}, user='test'):
-            if chunk['event'] in ignored_events:
-                continue
-            chunks.append(chunk)
-        print(json.dumps(chunks, ensure_ascii=False, indent=4))
-
-
-if __name__ == '__main__':
-    asyncio.run(TestDifyClient().test_chat_messages())

libs/wecom_ai_bot_api/api.py

@@ -1,290 +0,0 @@
-import json
-import time
-import uuid
-import xml.etree.ElementTree as ET
-from urllib.parse import unquote
-import hashlib
-import traceback
-
-import httpx
-from libs.wecom_ai_bot_api.WXBizMsgCrypt3 import WXBizMsgCrypt
-from quart import Quart, request, Response, jsonify
-import langbot_plugin.api.entities.builtin.platform.message as platform_message
-import asyncio
-from libs.wecom_ai_bot_api import wecombotevent
-from typing import Callable
-import base64
-from Crypto.Cipher import AES
-from pkg.platform.logger import EventLogger
-
-
-
-class WecomBotClient:
-    def __init__(self,Token:str,EnCodingAESKey:str,Corpid:str,logger:EventLogger):
-        self.Token=Token
-        self.EnCodingAESKey=EnCodingAESKey
-        self.Corpid=Corpid
-        self.ReceiveId = ''
-        self.app = Quart(__name__)
-        self.app.add_url_rule(
-            '/callback/command',
-            'handle_callback',
-            self.handle_callback_request,
-            methods=['POST','GET']
-        )
-        self._message_handlers = {
-            'example': [],
-        }
-        self.user_stream_map = {}
-        self.logger = logger
-        self.generated_content = {}
-        self.msg_id_map = {}
-
-    async def sha1_signature(token: str, timestamp: str, nonce: str, encrypt: str) -> str:
-        raw = "".join(sorted([token, timestamp, nonce, encrypt]))
-        return hashlib.sha1(raw.encode("utf-8")).hexdigest()
-    
-    async def handle_callback_request(self):
-        try:
-            self.wxcpt=WXBizMsgCrypt(self.Token,self.EnCodingAESKey,'')
-
-            if request.method == "GET":
-
-                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")
-                    return Response("缺少参数", status=400)
-
-                ret, decrypted_str = self.wxcpt.VerifyURL(msg_signature, timestamp, nonce, echostr)
-                if ret != 0:
-                    
-                    await self.logger.error("验证URL失败")
-                    return Response("验证失败", status=403)
-
-                return Response(decrypted_str, mimetype="text/plain")
-
-            elif request.method == "POST":
-                msg_signature = unquote(request.args.get("msg_signature", ""))
-                timestamp     = unquote(request.args.get("timestamp", ""))
-                nonce         = unquote(request.args.get("nonce", ""))
-
-                try:
-                    timeout = 3
-                    interval = 0.1
-                    start_time = time.monotonic()
-                    encrypted_json  = await request.get_json()
-                    encrypted_msg   = encrypted_json.get("encrypt", "")
-                    if not encrypted_msg:
-                        await self.logger.error("请求体中缺少 'encrypt' 字段")
-
-                    xml_post_data = f"<xml><Encrypt><![CDATA[{encrypted_msg}]]></Encrypt></xml>"
-                    ret, decrypted_xml = self.wxcpt.DecryptMsg(xml_post_data, msg_signature, timestamp, nonce)
-                    if ret != 0:
-                        await self.logger.error("解密失败")
-
-
-                    msg_json = json.loads(decrypted_xml)
-                    
-                    from_user_id = msg_json.get("from", {}).get("userid")
-                    chatid = msg_json.get("chatid", "")
-                    
-                    message_data = await self.get_message(msg_json)
-                    
-                    
-
-                    if message_data:
-                        try:
-                            event = wecombotevent.WecomBotEvent(message_data)
-                            if event:
-                                await self._handle_message(event)
-                        except Exception as e:
-                            await self.logger.error(traceback.format_exc())
-                            print(traceback.format_exc())
-
-                    start_time = time.time()
-                    try:
-                        if msg_json.get('chattype','') == 'single':
-                            if from_user_id in self.user_stream_map:
-                                stream_id = self.user_stream_map[from_user_id]
-                            else:
-                                stream_id =str(uuid.uuid4())
-                                self.user_stream_map[from_user_id] = stream_id
-                            
-
-                        else:
-                            
-                            if chatid in self.user_stream_map:
-                                stream_id = self.user_stream_map[chatid]
-                            else:
-                                stream_id = str(uuid.uuid4())
-                                self.user_stream_map[chatid] = stream_id
-                    except Exception as e:
-                        await self.logger.error(traceback.format_exc())
-                        print(traceback.format_exc())
-                    while True:
-                        content = self.generated_content.pop(msg_json['msgid'],None)
-                        if content:
-                            reply_plain = {
-                                "msgtype": "stream",
-                                "stream": {
-                                    "id": stream_id,
-                                    "finish": True,
-                                    "content": content
-                                }
-                            }
-                            reply_plain_str = json.dumps(reply_plain, ensure_ascii=False)
-
-                            reply_timestamp = str(int(time.time()))
-                            ret, encrypt_text = self.wxcpt.EncryptMsg(reply_plain_str, nonce, reply_timestamp)
-                            if ret != 0:
-                                
-                                await self.logger.error("加密失败"+str(ret))
-                            
-
-                            root = ET.fromstring(encrypt_text)
-                            encrypt = root.find("Encrypt").text
-                            resp = {
-                                "encrypt": encrypt,
-                            }
-                            return jsonify(resp), 200
-
-                        if time.time() - start_time > timeout:
-                            break
-
-                        await asyncio.sleep(interval)
-
-                    if self.msg_id_map.get(message_data['msgid'], 1) == 3:
-                        await self.logger.error('请求失效：暂不支持智能机器人超过7秒的请求，如有需求，请联系 LangBot 团队。')
-                        return ''
-
-                except Exception as e:
-                    await self.logger.error(traceback.format_exc())
-                    print(traceback.format_exc())
-
-        except Exception as e:
-            await self.logger.error(traceback.format_exc())
-            print(traceback.format_exc())
-
-    
-    async def get_message(self,msg_json):
-        message_data = {}
-
-        if msg_json.get('chattype','') == 'single':
-            message_data['type'] = 'single'
-        elif msg_json.get('chattype','') == 'group':
-            message_data['type'] = 'group'
-
-        if msg_json.get('msgtype') == 'text':
-            message_data['content'] = msg_json.get('text',{}).get('content')
-        elif msg_json.get('msgtype') == 'image':
-            picurl = msg_json.get('image', {}).get('url','')
-            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 = []
-            picurl = None
-            for item in items:
-                if item.get('msgtype') == 'text':
-                    texts.append(item.get('text', {}).get('content', ''))
-                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 picurl:
-                base64 = await self.download_url_to_base64(picurl,self.EnCodingAESKey)
-                message_data['picurl'] = base64          # 只保留第一个 image
-
-        message_data['userid'] = msg_json.get('from', {}).get('userid', '')
-        message_data['msgid'] = msg_json.get('msgid', '')
-
-        if msg_json.get('aibotid'):
-            message_data['aibotid'] = msg_json.get('aibotid', '')
-
-        return message_data
-    
-    async def _handle_message(self, event: wecombotevent.WecomBotEvent):
-        """
-        处理消息事件。
-        """
-        try:
-            message_id = event.message_id
-            if message_id in self.msg_id_map.keys():
-                self.msg_id_map[message_id] += 1
-                return
-            self.msg_id_map[message_id] = 1
-            msg_type = event.type
-            if msg_type in self._message_handlers:
-                for handler in self._message_handlers[msg_type]:
-                    await handler(event)
-        except Exception:
-                print(traceback.format_exc())
-
-    async def set_message(self, msg_id: str, content: str):
-        self.generated_content[msg_id] = content
-
-    def on_message(self, msg_type: str):
-        def decorator(func: Callable[[wecombotevent.WecomBotEvent], None]):
-            if msg_type not in self._message_handlers:
-                self._message_handlers[msg_type] = []
-            self._message_handlers[msg_type].append(func)
-            return func
-
-        return decorator
-
-
-    async def download_url_to_base64(self, download_url, encoding_aes_key):
-        async with httpx.AsyncClient() as client:
-            response = await client.get(download_url)
-            if response.status_code != 200:
-                await self.logger.error(f'failed to get file: {response.text}')
-                return None
-
-            encrypted_bytes = response.content
-
-        
-        aes_key = base64.b64decode(encoding_aes_key + "=")  # base64 补齐
-        iv = aes_key[:16]
-
-        
-        cipher = AES.new(aes_key, AES.MODE_CBC, iv)
-        decrypted = cipher.decrypt(encrypted_bytes)
-
-        
-        pad_len = decrypted[-1]
-        decrypted = decrypted[:-pad_len]
-
-        
-        if decrypted.startswith(b"\xff\xd8"):   # JPEG
-            mime_type = "image/jpeg"
-        elif decrypted.startswith(b"\x89PNG"):  # PNG
-            mime_type = "image/png"
-        elif decrypted.startswith((b"GIF87a", b"GIF89a")):  # GIF
-            mime_type = "image/gif"
-        elif decrypted.startswith(b"BM"):       # BMP
-            mime_type = "image/bmp"
-        elif decrypted.startswith(b"II*\x00") or decrypted.startswith(b"MM\x00*"):  # TIFF
-            mime_type = "image/tiff"
-        else:
-            mime_type = "application/octet-stream"
-
-        # 转 base64
-        base64_str = base64.b64encode(decrypted).decode("utf-8")
-        return f"data:{mime_type};base64,{base64_str}"
-    
-
-    async def run_task(self, host: str, port: int, *args, **kwargs):
-        """
-        启动 Quart 应用。
-        """
-        await self.app.run_task(host=host, port=port, *args, **kwargs)
-
-                
-    
-            
-

libs/wecom_ai_bot_api/wecombotevent.py

@@ -1,60 +0,0 @@
-from typing import Dict, Any, Optional
-
-
-class WecomBotEvent(dict):
-    @staticmethod
-    def from_payload(payload: Dict[str, Any]) -> Optional['WecomBotEvent']:
-        try:
-            event = WecomBotEvent(payload)
-            return event
-        except KeyError:
-            return None
-
-    @property
-    def type(self) -> str:
-        """
-        事件类型
-        """
-        return self.get('type', '')
-
-    @property
-    def userid(self) -> str:
-        """
-        用户id
-        """
-        return self.get('from', {}).get('userid', '')
-
-    @property
-    def content(self) -> str:
-        """
-        内容
-        """
-        return self.get('content', '')
-
-    @property
-    def picurl(self) -> str:
-        """
-        图片url
-        """
-        return self.get('picurl', '')
-
-    @property
-    def chatid(self) -> str:
-        """
-        群组id
-        """
-        return self.get('chatid', {})
-
-    @property
-    def message_id(self) -> str:
-        """
-        消息id
-        """
-        return self.get('msgid', '')
-    
-    @property
-    def ai_bot_id(self) -> str:
-        """
-        AI Bot ID
-        """
-        return self.get('aibotid', '')

main.py

@@ -1,117 +1,3 @@
-import asyncio
-import argparse
-# LangBot 终端启动入口
-# 在此层级解决依赖项检查。
-# LangBot/main.py
+import langbot.__main__
 
-asciiart = r"""
- _                   ___      _   
-| |   __ _ _ _  __ _| _ ) ___| |_ 
-| |__/ _` | ' \/ _` | _ \/ _ \  _|
-|____\__,_|_||_\__, |___/\___/\__|
-               |___/              
-
-⭐️ Open Source 开源地址: https://github.com/langbot-app/LangBot
-📖 Documentation 文档地址: https://docs.langbot.app
-"""
-
-
-async def main_entry(loop: asyncio.AbstractEventLoop):
-    parser = argparse.ArgumentParser(description='LangBot')
-    parser.add_argument(
-        '--standalone-runtime',
-        action='store_true',
-        help='Use standalone plugin runtime / 使用独立插件运行时',
-        default=False,
-    )
-    parser.add_argument('--debug', action='store_true', help='Debug mode / 调试模式', default=False)
-    args = parser.parse_args()
-
-    if args.standalone_runtime:
-        from pkg.utils import platform
-
-        platform.standalone_runtime = True
-
-    if args.debug:
-        from pkg.utils import constants
-
-        constants.debug_mode = True
-
-    print(asciiart)
-
-    import sys
-
-    # 检查依赖
-
-    from pkg.core.bootutils import deps
-
-    missing_deps = await deps.check_deps()
-
-    if missing_deps:
-        print('以下依赖包未安装，将自动安装，请完成后重启程序：')
-        print(
-            'These dependencies are missing, they will be installed automatically, please restart the program after completion:'
-        )
-        for dep in missing_deps:
-            print('-', dep)
-        await deps.install_deps(missing_deps)
-        print('已自动安装缺失的依赖包，请重启程序。')
-        print('The missing dependencies have been installed automatically, please restart the program.')
-        sys.exit(0)
-
-    # # 检查pydantic版本，如果没有 pydantic.v1，则把 pydantic 映射为 v1
-    # import pydantic.version
-
-    # if pydantic.version.VERSION < '2.0':
-    #     import pydantic
-
-    #     sys.modules['pydantic.v1'] = pydantic
-
-    # 检查配置文件
-
-    from pkg.core.bootutils import files
-
-    generated_files = await files.generate_files()
-
-    if generated_files:
-        print('以下文件不存在，已自动生成：')
-        print('Following files do not exist and have been automatically generated:')
-        for file in generated_files:
-            print('-', file)
-
-    from pkg.core import boot
-
-    await boot.main(loop)
-
-
-if __name__ == '__main__':
-    import os
-    import sys
-
-    # 必须大于 3.10.1
-    if sys.version_info < (3, 10, 1):
-        print('需要 Python 3.10.1 及以上版本，当前 Python 版本为：', sys.version)
-        input('按任意键退出...')
-        print('Your Python version is not supported. Please exit the program by pressing any key.')
-        exit(1)
-
-    # Check if the current directory is the LangBot project root directory
-    invalid_pwd = False
-
-    if not os.path.exists('main.py'):
-        invalid_pwd = True
-    else:
-        with open('main.py', 'r', encoding='utf-8') as f:
-            content = f.read()
-            if 'LangBot/main.py' not in content:
-                invalid_pwd = True
-    if invalid_pwd:
-        print('请在 LangBot 项目根目录下以命令形式运行此程序。')
-        input('按任意键退出...')
-        print('Please run this program in the LangBot project root directory in command form.')
-        print('Press any key to exit...')
-        exit(1)
-
-    loop = asyncio.new_event_loop()
-
-    loop.run_until_complete(main_entry(loop))
+langbot.__main__.main()

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

@@ -1,53 +0,0 @@
-from __future__ import annotations
-
-import quart
-import mimetypes
-import uuid
-import asyncio
-
-import quart.datastructures
-
-from .. import group
-
-
-@group.group_class('files', '/api/v1/files')
-class FilesRouterGroup(group.RouterGroup):
-    async def initialize(self) -> None:
-        @self.route('/image/<image_key>', methods=['GET'], auth_type=group.AuthType.NONE)
-        async def _(image_key: str) -> quart.Response:
-            if '/' in image_key or '\\' in image_key:
-                return quart.Response(status=404)
-
-            if not await self.ap.storage_mgr.storage_provider.exists(image_key):
-                return quart.Response(status=404)
-
-            image_bytes = await self.ap.storage_mgr.storage_provider.load(image_key)
-            mime_type = mimetypes.guess_type(image_key)[0]
-            if mime_type is None:
-                mime_type = 'image/jpeg'
-
-            return quart.Response(image_bytes, mimetype=mime_type)
-
-        @self.route('/documents', methods=['POST'], auth_type=group.AuthType.USER_TOKEN)
-        async def _() -> quart.Response:
-            request = quart.request
-            # get file bytes from 'file'
-            file = (await request.files)['file']
-            assert isinstance(file, quart.datastructures.FileStorage)
-
-            file_bytes = await asyncio.to_thread(file.stream.read)
-            extension = file.filename.split('.')[-1]
-            file_name = file.filename.split('.')[0]
-
-            # check if file name contains '/' or '\'
-            if '/' in file_name or '\\' in file_name:
-                return self.fail(400, 'File name contains invalid characters')
-
-            file_key = file_name + '_' + str(uuid.uuid4())[:8] + '.' + extension
-            # save file to storage
-            await self.ap.storage_mgr.storage_provider.save(file_key, file_bytes)
-            return self.success(
-                data={
-                    'file_id': file_key,
-                }
-            )

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

@@ -1,48 +0,0 @@
-from __future__ import annotations
-
-import quart
-
-from ... import group
-
-
-@group.group_class('pipelines', '/api/v1/pipelines')
-class PipelinesRouterGroup(group.RouterGroup):
-    async def initialize(self) -> None:
-        @self.route('', methods=['GET', 'POST'])
-        async def _() -> str:
-            if quart.request.method == 'GET':
-                sort_by = quart.request.args.get('sort_by', 'created_at')
-                sort_order = quart.request.args.get('sort_order', 'DESC')
-                return self.success(
-                    data={'pipelines': await self.ap.pipeline_service.get_pipelines(sort_by, sort_order)}
-                )
-            elif quart.request.method == 'POST':
-                json_data = await quart.request.json
-
-                pipeline_uuid = await self.ap.pipeline_service.create_pipeline(json_data)
-
-                return self.success(data={'uuid': pipeline_uuid})
-
-        @self.route('/_/metadata', methods=['GET'])
-        async def _() -> str:
-            return self.success(data={'configs': await self.ap.pipeline_service.get_pipeline_metadata()})
-
-        @self.route('/<pipeline_uuid>', methods=['GET', 'PUT', 'DELETE'])
-        async def _(pipeline_uuid: str) -> str:
-            if quart.request.method == 'GET':
-                pipeline = await self.ap.pipeline_service.get_pipeline(pipeline_uuid)
-
-                if pipeline is None:
-                    return self.http_status(404, -1, 'pipeline not found')
-
-                return self.success(data={'pipeline': pipeline})
-            elif quart.request.method == 'PUT':
-                json_data = await quart.request.json
-
-                await self.ap.pipeline_service.update_pipeline(pipeline_uuid, json_data)
-
-                return self.success()
-            elif quart.request.method == 'DELETE':
-                await self.ap.pipeline_service.delete_pipeline(pipeline_uuid)
-
-                return self.success()

pkg/api/http/controller/groups/pipelines/webchat.py

@@ -1,109 +0,0 @@
-import json
-
-import quart
-
-from ... import group
-
-
-@group.group_class('webchat', '/api/v1/pipelines/<pipeline_uuid>/chat')
-class WebChatDebugRouterGroup(group.RouterGroup):
-    async def initialize(self) -> None:
-        @self.route('/send', methods=['POST'])
-        async def send_message(pipeline_uuid: str) -> str:
-            """Send a message to the pipeline for debugging"""
-
-            async def stream_generator(generator):
-                yield 'data: {"type": "start"}\n\n'
-                async for message in generator:
-                    yield f'data: {json.dumps({"message": message})}\n\n'
-                yield 'data: {"type": "end"}\n\n'
-
-            try:
-                data = await quart.request.get_json()
-                session_type = data.get('session_type', 'person')
-                message_chain_obj = data.get('message', [])
-                is_stream = data.get('is_stream', False)
-
-                if not message_chain_obj:
-                    return self.http_status(400, -1, 'message is required')
-
-                if session_type not in ['person', 'group']:
-                    return self.http_status(400, -1, 'session_type must be person or group')
-
-                webchat_adapter = self.ap.platform_mgr.webchat_proxy_bot.adapter
-
-                if not webchat_adapter:
-                    return self.http_status(404, -1, 'WebChat adapter not found')
-
-                if is_stream:
-                    generator = webchat_adapter.send_webchat_message(
-                        pipeline_uuid, session_type, message_chain_obj, is_stream
-                    )
-                    # 设置正确的响应头
-                    headers = {
-                        'Content-Type': 'text/event-stream',
-                        'Transfer-Encoding': 'chunked',
-                        'Cache-Control': 'no-cache',
-                        'Connection': 'keep-alive',
-                    }
-                    return quart.Response(stream_generator(generator), mimetype='text/event-stream', headers=headers)
-
-                else:  # non-stream
-                    result = None
-                    async for message in webchat_adapter.send_webchat_message(
-                        pipeline_uuid, session_type, message_chain_obj
-                    ):
-                        result = message
-                    if result is not None:
-                        return self.success(
-                            data={
-                                'message': result,
-                            }
-                        )
-                    else:
-                        return self.http_status(400, -1, 'message is required')
-
-            except Exception as e:
-                return self.http_status(500, -1, f'Internal server error: {str(e)}')
-
-        @self.route('/messages/<session_type>', methods=['GET'])
-        async def get_messages(pipeline_uuid: str, session_type: str) -> str:
-            """Get the message history of the pipeline for debugging"""
-            try:
-                if session_type not in ['person', 'group']:
-                    return self.http_status(400, -1, 'session_type must be person or group')
-
-                webchat_adapter = self.ap.platform_mgr.webchat_proxy_bot.adapter
-
-                if not webchat_adapter:
-                    return self.http_status(404, -1, 'WebChat adapter not found')
-
-                messages = webchat_adapter.get_webchat_messages(pipeline_uuid, session_type)
-
-                return self.success(data={'messages': messages})
-
-            except Exception as e:
-                return self.http_status(500, -1, f'Internal server error: {str(e)}')
-
-        @self.route('/reset/<session_type>', methods=['POST'])
-        async def reset_session(session_type: str) -> str:
-            """Reset the debug session"""
-            try:
-                if session_type not in ['person', 'group']:
-                    return self.http_status(400, -1, 'session_type must be person or group')
-
-                webchat_adapter = None
-                for bot in self.ap.platform_mgr.bots:
-                    if hasattr(bot.adapter, '__class__') and bot.adapter.__class__.__name__ == 'WebChatAdapter':
-                        webchat_adapter = bot.adapter
-                        break
-
-                if not webchat_adapter:
-                    return self.http_status(404, -1, 'WebChat adapter not found')
-
-                webchat_adapter.reset_debug_session(session_type)
-
-                return self.success(data={'message': 'Session reset successfully'})
-
-            except Exception as e:
-                return self.http_status(500, -1, f'Internal server error: {str(e)}')

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

@@ -1,44 +0,0 @@
-import quart
-
-from ... import group
-
-
-@group.group_class('bots', '/api/v1/platform/bots')
-class BotsRouterGroup(group.RouterGroup):
-    async def initialize(self) -> None:
-        @self.route('', methods=['GET', 'POST'])
-        async def _() -> str:
-            if quart.request.method == 'GET':
-                return self.success(data={'bots': await self.ap.bot_service.get_bots()})
-            elif quart.request.method == 'POST':
-                json_data = await quart.request.json
-                bot_uuid = await self.ap.bot_service.create_bot(json_data)
-                return self.success(data={'uuid': bot_uuid})
-
-        @self.route('/<bot_uuid>', methods=['GET', 'PUT', 'DELETE'])
-        async def _(bot_uuid: str) -> str:
-            if quart.request.method == 'GET':
-                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})
-            elif quart.request.method == 'PUT':
-                json_data = await quart.request.json
-                await self.ap.bot_service.update_bot(bot_uuid, json_data)
-                return self.success()
-            elif quart.request.method == 'DELETE':
-                await self.ap.bot_service.delete_bot(bot_uuid)
-                return self.success()
-
-        @self.route('/<bot_uuid>/logs', methods=['POST'])
-        async def _(bot_uuid: str) -> str:
-            json_data = await quart.request.json
-            from_index = json_data.get('from_index', -1)
-            max_count = json_data.get('max_count', 10)
-            logs, total_count = await self.ap.bot_service.list_event_logs(bot_uuid, from_index, max_count)
-            return self.success(
-                data={
-                    'logs': logs,
-                    'total_count': total_count,
-                }
-            )

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

@@ -1,144 +0,0 @@
-from __future__ import annotations
-
-import base64
-import quart
-
-from .....core import taskmgr
-from .. import group
-from langbot_plugin.runtime.plugin.mgr import PluginInstallSource
-
-
-@group.group_class('plugins', '/api/v1/plugins')
-class PluginsRouterGroup(group.RouterGroup):
-    async def initialize(self) -> None:
-        @self.route('', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
-        async def _() -> str:
-            plugins = await self.ap.plugin_connector.list_plugins()
-
-            return self.success(data={'plugins': plugins})
-
-        @self.route(
-            '/<author>/<plugin_name>/upgrade',
-            methods=['POST'],
-            auth_type=group.AuthType.USER_TOKEN,
-        )
-        async def _(author: str, plugin_name: str) -> str:
-            ctx = taskmgr.TaskContext.new()
-            wrapper = self.ap.task_mgr.create_user_task(
-                self.ap.plugin_connector.upgrade_plugin(author, plugin_name, task_context=ctx),
-                kind='plugin-operation',
-                name=f'plugin-upgrade-{plugin_name}',
-                label=f'Upgrading plugin {plugin_name}',
-                context=ctx,
-            )
-            return self.success(data={'task_id': wrapper.id})
-
-        @self.route(
-            '/<author>/<plugin_name>',
-            methods=['GET', 'DELETE'],
-            auth_type=group.AuthType.USER_TOKEN,
-        )
-        async def _(author: str, plugin_name: str) -> str:
-            if quart.request.method == 'GET':
-                plugin = await self.ap.plugin_connector.get_plugin_info(author, plugin_name)
-                if plugin is None:
-                    return self.http_status(404, -1, 'plugin not found')
-                return self.success(data={'plugin': plugin})
-            elif quart.request.method == 'DELETE':
-                ctx = taskmgr.TaskContext.new()
-                wrapper = self.ap.task_mgr.create_user_task(
-                    self.ap.plugin_connector.delete_plugin(author, plugin_name, task_context=ctx),
-                    kind='plugin-operation',
-                    name=f'plugin-remove-{plugin_name}',
-                    label=f'Removing plugin {plugin_name}',
-                    context=ctx,
-                )
-
-                return self.success(data={'task_id': wrapper.id})
-
-        @self.route(
-            '/<author>/<plugin_name>/config',
-            methods=['GET', 'PUT'],
-            auth_type=group.AuthType.USER_TOKEN,
-        )
-        async def _(author: str, plugin_name: str) -> quart.Response:
-            plugin = await self.ap.plugin_connector.get_plugin_info(author, plugin_name)
-            if plugin is None:
-                return self.http_status(404, -1, 'plugin not found')
-
-            if quart.request.method == 'GET':
-                return self.success(data={'config': plugin['plugin_config']})
-            elif quart.request.method == 'PUT':
-                data = await quart.request.json
-
-                await self.ap.plugin_connector.set_plugin_config(author, plugin_name, data)
-
-                return self.success(data={})
-
-        @self.route(
-            '/<author>/<plugin_name>/icon',
-            methods=['GET'],
-            auth_type=group.AuthType.NONE,
-        )
-        async def _(author: str, plugin_name: str) -> quart.Response:
-            icon_data = await self.ap.plugin_connector.get_plugin_icon(author, plugin_name)
-            icon_base64 = icon_data['plugin_icon_base64']
-            mime_type = icon_data['mime_type']
-
-            icon_data = base64.b64decode(icon_base64)
-
-            return quart.Response(icon_data, mimetype=mime_type)
-
-        @self.route('/install/github', methods=['POST'], auth_type=group.AuthType.USER_TOKEN)
-        async def _() -> str:
-            data = await quart.request.json
-
-            ctx = taskmgr.TaskContext.new()
-            short_source_str = data['source'][-8:]
-            wrapper = self.ap.task_mgr.create_user_task(
-                self.ap.plugin_mgr.install_plugin(data['source'], task_context=ctx),
-                kind='plugin-operation',
-                name='plugin-install-github',
-                label=f'Installing plugin from github ...{short_source_str}',
-                context=ctx,
-            )
-
-            return self.success(data={'task_id': wrapper.id})
-
-        @self.route('/install/marketplace', methods=['POST'], auth_type=group.AuthType.USER_TOKEN)
-        async def _() -> str:
-            data = await quart.request.json
-
-            ctx = taskmgr.TaskContext.new()
-            wrapper = self.ap.task_mgr.create_user_task(
-                self.ap.plugin_connector.install_plugin(PluginInstallSource.MARKETPLACE, data, task_context=ctx),
-                kind='plugin-operation',
-                name='plugin-install-marketplace',
-                label=f'Installing plugin from marketplace ...{data}',
-                context=ctx,
-            )
-
-            return self.success(data={'task_id': wrapper.id})
-
-        @self.route('/install/local', methods=['POST'], auth_type=group.AuthType.USER_TOKEN)
-        async def _() -> str:
-            file = (await quart.request.files).get('file')
-            if file is None:
-                return self.http_status(400, -1, 'file is required')
-
-            file_bytes = file.read()
-
-            data = {
-                'plugin_file': file_bytes,
-            }
-
-            ctx = taskmgr.TaskContext.new()
-            wrapper = self.ap.task_mgr.create_user_task(
-                self.ap.plugin_connector.install_plugin(PluginInstallSource.LOCAL, data, task_context=ctx),
-                kind='plugin-operation',
-                name='plugin-install-local',
-                label=f'Installing plugin from local ...{file.filename}',
-                context=ctx,
-            )
-
-            return self.success(data={'task_id': wrapper.id})

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

@@ -1,85 +0,0 @@
-import quart
-import argon2
-import asyncio
-
-from .. import group
-
-
-@group.group_class('user', '/api/v1/user')
-class UserRouterGroup(group.RouterGroup):
-    async def initialize(self) -> None:
-        @self.route('/init', methods=['GET', 'POST'], auth_type=group.AuthType.NONE)
-        async def _() -> str:
-            if quart.request.method == 'GET':
-                return self.success(data={'initialized': await self.ap.user_service.is_initialized()})
-
-            if await self.ap.user_service.is_initialized():
-                return self.fail(1, 'System already initialized')
-
-            json_data = await quart.request.json
-
-            user_email = json_data['user']
-            password = json_data['password']
-
-            await self.ap.user_service.create_user(user_email, password)
-
-            return self.success()
-
-        @self.route('/auth', methods=['POST'], auth_type=group.AuthType.NONE)
-        async def _() -> str:
-            json_data = await quart.request.json
-
-            try:
-                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')
-
-            return self.success(data={'token': token})
-
-        @self.route('/check-token', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
-        async def _(user_email: str) -> str:
-            token = await self.ap.user_service.generate_jwt_token(user_email)
-
-            return self.success(data={'token': token})
-
-        @self.route('/reset-password', methods=['POST'], auth_type=group.AuthType.NONE)
-        async def _() -> str:
-            json_data = await quart.request.json
-
-            user_email = json_data['user']
-            recovery_key = json_data['recovery_key']
-            new_password = json_data['new_password']
-
-            # hard sleep 3s for security
-            await asyncio.sleep(3)
-
-            if not await self.ap.user_service.is_initialized():
-                return self.http_status(400, -1, 'System not initialized')
-
-            user_obj = await self.ap.user_service.get_user_by_email(user_email)
-
-            if user_obj is None:
-                return self.http_status(400, -1, 'User not found')
-
-            if recovery_key != self.ap.instance_config.data['system']['recovery_key']:
-                return self.http_status(403, -1, 'Invalid recovery key')
-
-            await self.ap.user_service.reset_password(user_email, new_password)
-
-            return self.success(data={'user': user_email})
-
-        @self.route('/change-password', methods=['POST'], auth_type=group.AuthType.USER_TOKEN)
-        async def _(user_email: str) -> str:
-            json_data = await quart.request.json
-
-            current_password = json_data['current_password']
-            new_password = json_data['new_password']
-
-            try:
-                await self.ap.user_service.change_password(user_email, current_password, new_password)
-            except argon2.exceptions.VerifyMismatchError:
-                return self.http_status(400, -1, 'Current password is incorrect')
-            except ValueError as e:
-                return self.http_status(400, -1, str(e))
-
-            return self.success(data={'user': user_email})

pkg/api/http/service/model.py

@@ -1,199 +0,0 @@
-from __future__ import annotations
-
-import uuid
-import sqlalchemy
-
-from ....core import app
-from ....entity.persistence import model as persistence_model
-from ....entity.persistence import pipeline as persistence_pipeline
-from ....provider.modelmgr import requester as model_requester
-from langbot_plugin.api.entities.builtin.provider import message as provider_message
-
-
-class LLMModelsService:
-    ap: app.Application
-
-    def __init__(self, ap: app.Application) -> None:
-        self.ap = ap
-
-    async def get_llm_models(self, include_secret: bool = True) -> list[dict]:
-        result = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_model.LLMModel))
-
-        models = result.all()
-
-        masked_columns = []
-        if not include_secret:
-            masked_columns = ['api_keys']
-
-        return [
-            self.ap.persistence_mgr.serialize_model(persistence_model.LLMModel, model, masked_columns)
-            for model in models
-        ]
-
-    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))
-
-        llm_model = await self.get_llm_model(model_data['uuid'])
-
-        await self.ap.model_mgr.load_llm_model(llm_model)
-
-        # 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)
-
-        return model_data['uuid']
-
-    async def get_llm_model(self, model_uuid: str) -> dict | None:
-        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
-
-        return self.ap.persistence_mgr.serialize_model(persistence_model.LLMModel, model)
-
-    async def update_llm_model(self, model_uuid: str, model_data: dict) -> None:
-        if 'uuid' in model_data:
-            del model_data['uuid']
-
-        await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.update(persistence_model.LLMModel)
-            .where(persistence_model.LLMModel.uuid == model_uuid)
-            .values(**model_data)
-        )
-
-        await self.ap.model_mgr.remove_llm_model(model_uuid)
-
-        llm_model = await self.get_llm_model(model_uuid)
-
-        await self.ap.model_mgr.load_llm_model(llm_model)
-
-    async def delete_llm_model(self, model_uuid: str) -> None:
-        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:
-        runtime_llm_model: model_requester.RuntimeLLMModel | None = None
-
-        if model_uuid != '_':
-            for model in self.ap.model_mgr.llm_models:
-                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_runtime_llm_model(model_data)
-
-        await runtime_llm_model.requester.invoke_llm(
-            query=None,
-            model=runtime_llm_model,
-            messages=[provider_message.Message(role='user', content='Hello, world!')],
-            funcs=[],
-            extra_args=model_data.get('extra_args', {}),
-        )
-
-
-class EmbeddingModelsService:
-    ap: app.Application
-
-    def __init__(self, ap: app.Application) -> None:
-        self.ap = ap
-
-    async def get_embedding_models(self) -> list[dict]:
-        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]
-
-    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)
-        )
-
-        embedding_model = await self.get_embedding_model(model_data['uuid'])
-
-        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:
-        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
-
-        return self.ap.persistence_mgr.serialize_model(persistence_model.EmbeddingModel, model)
-
-    async def update_embedding_model(self, model_uuid: str, model_data: dict) -> None:
-        if 'uuid' in model_data:
-            del model_data['uuid']
-
-        await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.update(persistence_model.EmbeddingModel)
-            .where(persistence_model.EmbeddingModel.uuid == model_uuid)
-            .values(**model_data)
-        )
-
-        await self.ap.model_mgr.remove_embedding_model(model_uuid)
-
-        embedding_model = await self.get_embedding_model(model_uuid)
-
-        await self.ap.model_mgr.load_embedding_model(embedding_model)
-
-    async def delete_embedding_model(self, model_uuid: str) -> None:
-        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:
-        runtime_embedding_model: model_requester.RuntimeEmbeddingModel | None = None
-
-        if model_uuid != '_':
-            for model in self.ap.model_mgr.embedding_models:
-                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_runtime_embedding_model(model_data)
-
-        await runtime_embedding_model.requester.invoke_embedding(
-            model=runtime_embedding_model,
-            input_text=['Hello, world!'],
-            extra_args={},
-        )

pkg/api/http/service/user.py

@@ -1,99 +0,0 @@
-from __future__ import annotations
-
-import sqlalchemy
-import argon2
-import jwt
-import datetime
-
-from ....core import app
-from ....entity.persistence import user
-from ....utils import constants
-
-
-class UserService:
-    ap: app.Application
-
-    def __init__(self, ap: app.Application) -> None:
-        self.ap = ap
-
-    async def is_initialized(self) -> bool:
-        result = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(user.User).limit(1))
-
-        result_list = result.all()
-        return result_list is not None and len(result_list) > 0
-
-    async def create_user(self, user_email: str, password: str) -> None:
-        ph = argon2.PasswordHasher()
-
-        hashed_password = ph.hash(password)
-
-        await self.ap.persistence_mgr.execute_async(
-            sqlalchemy.insert(user.User).values(user=user_email, password=hashed_password)
-        )
-
-    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 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)
-        )
-
-        result_list = result.all()
-
-        if result_list is None or len(result_list) == 0:
-            raise ValueError('用户不存在')
-
-        user_obj = result_list[0]
-
-        ph = argon2.PasswordHasher()
-
-        ph.verify(user_obj.password, password)
-
-        return await self.generate_jwt_token(user_email)
-
-    async def generate_jwt_token(self, user_email: str) -> str:
-        jwt_secret = self.ap.instance_config.data['system']['jwt']['secret']
-        jwt_expire = self.ap.instance_config.data['system']['jwt']['expire']
-
-        payload = {
-            'user': user_email,
-            'iss': 'LangBot-' + constants.edition,
-            'exp': datetime.datetime.now() + datetime.timedelta(seconds=jwt_expire),
-        }
-
-        return jwt.encode(payload, jwt_secret, algorithm='HS256')
-
-    async def verify_jwt_token(self, token: str) -> str:
-        jwt_secret = self.ap.instance_config.data['system']['jwt']['secret']
-
-        return jwt.decode(token, jwt_secret, algorithms=['HS256'])['user']
-
-    async def reset_password(self, user_email: str, new_password: str) -> None:
-        ph = argon2.PasswordHasher()
-
-        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 change_password(self, user_email: str, current_password: str, new_password: str) -> None:
-        ph = argon2.PasswordHasher()
-
-        user_obj = await self.get_user_by_email(user_email)
-        if user_obj is None:
-            raise ValueError('User not found')
-
-        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)
-        )

pkg/core/stages/load_config.py

@@ -1,79 +0,0 @@
-from __future__ import annotations
-
-import os
-
-from .. import stage, app
-from ..bootutils import config
-
-
-@stage.stage_class('LoadConfigStage')
-class LoadConfigStage(stage.BootingStage):
-    """Load config file stage"""
-
-    async def run(self, ap: app.Application):
-        """Load config file"""
-
-        # ======= deprecated =======
-        if os.path.exists('data/config/command.json'):
-            ap.command_cfg = await config.load_json_config(
-                'data/config/command.json',
-                'templates/legacy/command.json',
-                completion=False,
-            )
-
-        if os.path.exists('data/config/pipeline.json'):
-            ap.pipeline_cfg = await config.load_json_config(
-                'data/config/pipeline.json',
-                'templates/legacy/pipeline.json',
-                completion=False,
-            )
-
-        if os.path.exists('data/config/platform.json'):
-            ap.platform_cfg = await config.load_json_config(
-                'data/config/platform.json',
-                'templates/legacy/platform.json',
-                completion=False,
-            )
-
-        if os.path.exists('data/config/provider.json'):
-            ap.provider_cfg = await config.load_json_config(
-                'data/config/provider.json',
-                'templates/legacy/provider.json',
-                completion=False,
-            )
-
-        if os.path.exists('data/config/system.json'):
-            ap.system_cfg = await config.load_json_config(
-                'data/config/system.json',
-                'templates/legacy/system.json',
-                completion=False,
-            )
-
-        # ======= deprecated =======
-
-        ap.instance_config = await config.load_yaml_config(
-            'data/config.yaml', 'templates/config.yaml', completion=False
-        )
-        await ap.instance_config.dump_config()
-
-        ap.sensitive_meta = await config.load_json_config(
-            'data/metadata/sensitive-words.json',
-            'templates/metadata/sensitive-words.json',
-        )
-        await ap.sensitive_meta.dump_config()
-
-        ap.pipeline_config_meta_trigger = await config.load_yaml_config(
-            'templates/metadata/pipeline/trigger.yaml',
-            'templates/metadata/pipeline/trigger.yaml',
-        )
-        ap.pipeline_config_meta_safety = await config.load_yaml_config(
-            'templates/metadata/pipeline/safety.yaml',
-            'templates/metadata/pipeline/safety.yaml',
-        )
-        ap.pipeline_config_meta_ai = await config.load_yaml_config(
-            'templates/metadata/pipeline/ai.yaml', 'templates/metadata/pipeline/ai.yaml'
-        )
-        ap.pipeline_config_meta_output = await config.load_yaml_config(
-            'templates/metadata/pipeline/output.yaml',
-            'templates/metadata/pipeline/output.yaml',
-        )

pkg/entity/persistence/user.py

@@ -1,18 +0,0 @@
-import sqlalchemy
-
-from .base import Base
-
-
-class User(Base):
-    __tablename__ = 'users'
-
-    id = sqlalchemy.Column(sqlalchemy.Integer, primary_key=True)
-    user = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
-    password = sqlalchemy.Column(sqlalchemy.String(255), nullable=False)
-    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(),
-    )

pkg/entity/rag/retriever.py

@@ -1,13 +0,0 @@
-from __future__ import annotations
-
-import pydantic
-
-from typing import Any
-
-
-class RetrieveResultEntry(pydantic.BaseModel):
-    id: str
-
-    metadata: dict[str, Any]
-
-    distance: float

pkg/persistence/migrations/dbm002_combine_quote_msg_config.py

@@ -1,41 +0,0 @@
-from .. import migration
-
-import sqlalchemy
-
-from ...entity.persistence import pipeline as persistence_pipeline
-
-
-@migration.migration_class(2)
-class DBMigrateCombineQuoteMsgConfig(migration.DBMigration):
-    """Combine quote message config"""
-
-    async def upgrade(self):
-        """Upgrade"""
-        # read all pipelines
-        pipelines = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_pipeline.LegacyPipeline))
-
-        for pipeline in pipelines:
-            serialized_pipeline = self.ap.persistence_mgr.serialize_model(persistence_pipeline.LegacyPipeline, pipeline)
-
-            config = serialized_pipeline['config']
-
-            if 'misc' not in config['trigger']:
-                config['trigger']['misc'] = {}
-
-            if 'combine-quote-message' not in config['trigger']['misc']:
-                config['trigger']['misc']['combine-quote-message'] = False
-
-            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"""
-        pass

pkg/persistence/migrations/dbm003_n8n_config.py

@@ -1,49 +0,0 @@
-from .. import migration
-
-import sqlalchemy
-
-from ...entity.persistence import pipeline as persistence_pipeline
-
-
-@migration.migration_class(3)
-class DBMigrateN8nConfig(migration.DBMigration):
-    """N8n config"""
-
-    async def upgrade(self):
-        """Upgrade"""
-        # read all pipelines
-        pipelines = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_pipeline.LegacyPipeline))
-
-        for pipeline in pipelines:
-            serialized_pipeline = self.ap.persistence_mgr.serialize_model(persistence_pipeline.LegacyPipeline, pipeline)
-
-            config = serialized_pipeline['config']
-
-            if 'n8n-service-api' not in config['ai']:
-                config['ai']['n8n-service-api'] = {
-                    'webhook-url': 'http://your-n8n-webhook-url',
-                    'auth-type': 'none',
-                    'basic-username': '',
-                    'basic-password': '',
-                    'jwt-secret': '',
-                    'jwt-algorithm': 'HS256',
-                    'header-name': '',
-                    'header-value': '',
-                    'timeout': 120,
-                    'output-key': 'response',
-                }
-
-            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"""
-        pass

pkg/persistence/migrations/dbm004_rag_kb_uuid.py

@@ -1,38 +0,0 @@
-from .. import migration
-
-import sqlalchemy
-
-from ...entity.persistence import pipeline as persistence_pipeline
-
-
-@migration.migration_class(4)
-class DBMigrateRAGKBUUID(migration.DBMigration):
-    """RAG知识库UUID"""
-
-    async def upgrade(self):
-        """升级"""
-        # read all pipelines
-        pipelines = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_pipeline.LegacyPipeline))
-
-        for pipeline in pipelines:
-            serialized_pipeline = self.ap.persistence_mgr.serialize_model(persistence_pipeline.LegacyPipeline, pipeline)
-
-            config = serialized_pipeline['config']
-
-            if 'knowledge-base' not in config['ai']['local-agent']:
-                config['ai']['local-agent']['knowledge-base'] = ''
-
-            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"""
-        pass

pkg/persistence/migrations/dbm005_pipeline_remove_cot_config.py

@@ -1,38 +0,0 @@
-from .. import migration
-
-import sqlalchemy
-
-from ...entity.persistence import pipeline as persistence_pipeline
-
-
-@migration.migration_class(5)
-class DBMigratePipelineRemoveCotConfig(migration.DBMigration):
-    """Pipeline remove cot config"""
-
-    async def upgrade(self):
-        """Upgrade"""
-        # read all pipelines
-        pipelines = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_pipeline.LegacyPipeline))
-
-        for pipeline in pipelines:
-            serialized_pipeline = self.ap.persistence_mgr.serialize_model(persistence_pipeline.LegacyPipeline, pipeline)
-
-            config = serialized_pipeline['config']
-
-            if 'remove-think' not in config['output']['misc']:
-                config['output']['misc']['remove-think'] = False
-
-            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"""
-        pass

pkg/persistence/migrations/dbm006_langflow_api_config.py

@@ -1,45 +0,0 @@
-from .. import migration
-
-import sqlalchemy
-
-from ...entity.persistence import pipeline as persistence_pipeline
-
-
-@migration.migration_class(6)
-class DBMigrateLangflowApiConfig(migration.DBMigration):
-    """Langflow API config"""
-
-    async def upgrade(self):
-        """Upgrade"""
-        # read all pipelines
-        pipelines = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_pipeline.LegacyPipeline))
-
-        for pipeline in pipelines:
-            serialized_pipeline = self.ap.persistence_mgr.serialize_model(persistence_pipeline.LegacyPipeline, pipeline)
-
-            config = serialized_pipeline['config']
-
-            if 'langflow-api' not in config['ai']:
-                config['ai']['langflow-api'] = {
-                    'base-url': 'http://localhost:7860',
-                    'api-key': 'your-api-key',
-                    'flow-id': 'your-flow-id',
-                    'input-type': 'chat',
-                    'output-type': 'chat',
-                    'tweaks': '{}',
-                }
-
-            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"""
-        pass

pkg/pipeline/process/handlers/chat.py

@@ -1,126 +0,0 @@
-from __future__ import annotations
-
-import uuid
-import typing
-import traceback
-
-
-from .. import handler
-from ... import entities
-from ....provider import runner as runner_module
-
-import langbot_plugin.api.entities.builtin.platform.message as platform_message
-import langbot_plugin.api.entities.events as events
-from ....utils import importutil
-from ....provider import runners
-import langbot_plugin.api.entities.builtin.provider.session as provider_session
-import langbot_plugin.api.entities.builtin.pipeline.query as pipeline_query
-
-
-importutil.import_modules_in_pkg(runners)
-
-
-class ChatMessageHandler(handler.MessageHandler):
-    async def handle(
-        self,
-        query: pipeline_query.Query,
-    ) -> typing.AsyncGenerator[entities.StageProcessResult, None]:
-        """处理"""
-        # 调API
-        #   生成器
-
-        # 触发插件事件
-        event_class = (
-            events.PersonNormalMessageReceived
-            if query.launcher_type == provider_session.LauncherTypes.PERSON
-            else events.GroupNormalMessageReceived
-        )
-
-        event = event_class(
-            launcher_type=query.launcher_type.value,
-            launcher_id=query.launcher_id,
-            sender_id=query.sender_id,
-            text_message=str(query.message_chain),
-            query=query,
-        )
-
-        event_ctx = await self.ap.plugin_connector.emit_event(event)
-
-        is_create_card = False  # 判断下是否需要创建流式卡片
-        if event_ctx.is_prevented_default():
-            if event_ctx.event.reply is not None:
-                mc = platform_message.MessageChain(event_ctx.event.reply)
-                query.resp_messages.append(mc)
-
-                yield entities.StageProcessResult(result_type=entities.ResultType.CONTINUE, new_query=query)
-            else:
-                yield entities.StageProcessResult(result_type=entities.ResultType.INTERRUPT, new_query=query)
-        else:
-            if event_ctx.event.alter is not None:
-                # if isinstance(event_ctx.event, str):  # 现在暂时不考虑多模态alter
-                query.user_message.content = event_ctx.event.alter
-
-            text_length = 0
-            try:
-                is_stream = await query.adapter.is_stream_output_supported()
-            except AttributeError:
-                is_stream = False
-
-            try:
-                for r in runner_module.preregistered_runners:
-                    if r.name == query.pipeline_config['ai']['runner']['runner']:
-                        runner = r(self.ap, query.pipeline_config)
-                        break
-                else:
-                    raise ValueError(f'未找到请求运行器: {query.pipeline_config["ai"]["runner"]["runner"]}')
-                if is_stream:
-                    resp_message_id = uuid.uuid4()
-
-                    async for result in runner.run(query):
-                        result.resp_message_id = str(resp_message_id)
-                        if query.resp_messages:
-                            query.resp_messages.pop()
-                        if query.resp_message_chain:
-                            query.resp_message_chain.pop()
-                        # 此时连接外部 AI 服务正常,创建卡片
-                        if not is_create_card:  # 只有不是第一次才创建卡片
-                            await query.adapter.create_message_card(str(resp_message_id), query.message_event)
-                            is_create_card = True
-                        query.resp_messages.append(result)
-                        self.ap.logger.info(f'对话({query.query_id})流式响应: {self.cut_str(result.readable_str())}')
-
-                        if result.content is not None:
-                            text_length += len(result.content)
-
-                        yield entities.StageProcessResult(result_type=entities.ResultType.CONTINUE, new_query=query)
-
-                else:
-                    async for result in runner.run(query):
-                        query.resp_messages.append(result)
-
-                        self.ap.logger.info(f'对话({query.query_id})响应: {self.cut_str(result.readable_str())}')
-
-                        if result.content is not None:
-                            text_length += len(result.content)
-
-                        yield entities.StageProcessResult(result_type=entities.ResultType.CONTINUE, new_query=query)
-
-                query.session.using_conversation.messages.append(query.user_message)
-
-                query.session.using_conversation.messages.extend(query.resp_messages)
-            except Exception as e:
-                self.ap.logger.error(f'对话({query.query_id})请求失败: {type(e).__name__} {str(e)}')
-                traceback.print_exc()
-
-                hide_exception_info = query.pipeline_config['output']['misc']['hide-exception']
-
-                yield entities.StageProcessResult(
-                    result_type=entities.ResultType.INTERRUPT,
-                    new_query=query,
-                    user_notice='请求失败' if hide_exception_info else f'{e}',
-                    error_notice=f'{e}',
-                    debug_notice=traceback.format_exc(),
-                )
-            finally:
-                # TODO statistics
-                pass

pkg/platform/sources/webchat.py

@@ -1,304 +0,0 @@
-import asyncio
-import logging
-import typing
-from datetime import datetime
-
-import pydantic
-
-import langbot_plugin.api.definition.abstract.platform.adapter as abstract_platform_adapter
-import langbot_plugin.api.entities.builtin.platform.message as platform_message
-import langbot_plugin.api.entities.builtin.platform.events as platform_events
-import langbot_plugin.api.entities.builtin.platform.entities as platform_entities
-import langbot_plugin.api.definition.abstract.platform.event_logger as abstract_platform_logger
-from ...core import app
-
-logger = logging.getLogger(__name__)
-
-
-class WebChatMessage(pydantic.BaseModel):
-    id: int
-    role: str
-    content: str
-    message_chain: list[dict]
-    timestamp: str
-    is_final: bool = False
-
-
-class WebChatSession:
-    id: str
-    message_lists: dict[str, list[WebChatMessage]] = {}
-    resp_waiters: dict[int, asyncio.Future[WebChatMessage]]
-    resp_queues: dict[int, asyncio.Queue[WebChatMessage]]
-
-    def __init__(self, id: str):
-        self.id = id
-        self.message_lists = {}
-        self.resp_waiters = {}
-        self.resp_queues = {}
-
-    def get_message_list(self, pipeline_uuid: str) -> list[WebChatMessage]:
-        if pipeline_uuid not in self.message_lists:
-            self.message_lists[pipeline_uuid] = []
-
-        return self.message_lists[pipeline_uuid]
-
-
-class WebChatAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
-    """WebChat调试适配器，用于流水线调试"""
-
-    webchat_person_session: WebChatSession = pydantic.Field(exclude=True, default_factory=WebChatSession)
-    webchat_group_session: WebChatSession = pydantic.Field(exclude=True, default_factory=WebChatSession)
-
-    listeners: dict[
-        typing.Type[platform_events.Event],
-        typing.Callable[[platform_events.Event, abstract_platform_adapter.AbstractMessagePlatformAdapter], None],
-    ] = pydantic.Field(default_factory=dict, exclude=True)
-
-    is_stream: bool = pydantic.Field(exclude=True)
-    debug_messages: dict[str, list[dict]] = pydantic.Field(default_factory=dict, exclude=True)
-
-    ap: app.Application = pydantic.Field(exclude=True)
-
-    def __init__(self, config: dict, logger: abstract_platform_logger.AbstractEventLogger, **kwargs):
-        super().__init__(
-            config=config,
-            logger=logger,
-            **kwargs,
-        )
-
-        self.webchat_person_session = WebChatSession(id='webchatperson')
-        self.webchat_group_session = WebChatSession(id='webchatgroup')
-
-        self.bot_account_id = 'webchatbot'
-
-        self.debug_messages = {}
-
-    async def send_message(
-        self,
-        target_type: str,
-        target_id: str,
-        message: platform_message.MessageChain,
-    ) -> dict:
-        """发送消息到调试会话"""
-        session_key = target_id
-
-        if session_key not in self.debug_messages:
-            self.debug_messages[session_key] = []
-
-        message_data = {
-            'id': len(self.debug_messages[session_key]) + 1,
-            'type': 'bot',
-            'content': str(message),
-            'timestamp': datetime.now().isoformat(),
-            'message_chain': [component.__dict__ for component in message],
-        }
-
-        self.debug_messages[session_key].append(message_data)
-
-        await self.logger.info(f'Send message to {session_key}: {message}')
-
-        return message_data
-
-    async def reply_message(
-        self,
-        message_source: platform_events.MessageEvent,
-        message: platform_message.MessageChain,
-        quote_origin: bool = False,
-    ) -> dict:
-        """回复消息"""
-        message_data = WebChatMessage(
-            id=-1,
-            role='assistant',
-            content=str(message),
-            message_chain=[component.__dict__ for component in message],
-            timestamp=datetime.now().isoformat(),
-        )
-
-        # notify waiter
-        if isinstance(message_source, platform_events.FriendMessage):
-            await self.webchat_person_session.resp_queues[message_source.message_chain.message_id].put(message_data)
-        elif isinstance(message_source, platform_events.GroupMessage):
-            await self.webchat_group_session.resp_queues[message_source.message_chain.message_id].put(message_data)
-
-        return message_data.model_dump()
-
-    async def reply_message_chunk(
-        self,
-        message_source: platform_events.MessageEvent,
-        bot_message,
-        message: platform_message.MessageChain,
-        quote_origin: bool = False,
-        is_final: bool = False,
-    ) -> dict:
-        """回复消息"""
-        message_data = WebChatMessage(
-            id=-1,
-            role='assistant',
-            content=str(message),
-            message_chain=[component.__dict__ for component in message],
-            timestamp=datetime.now().isoformat(),
-        )
-
-        # notify waiter
-        session = (
-            self.webchat_group_session
-            if isinstance(message_source, platform_events.GroupMessage)
-            else self.webchat_person_session
-        )
-        if message_source.message_chain.message_id not in session.resp_waiters:
-            # session.resp_waiters[message_source.message_chain.message_id] = asyncio.Queue()
-            queue = session.resp_queues[message_source.message_chain.message_id]
-
-        # if isinstance(message_source, platform_events.FriendMessage):
-        #     queue = self.webchat_person_session.resp_queues[message_source.message_chain.message_id]
-        # elif isinstance(message_source, platform_events.GroupMessage):
-        #     queue = self.webchat_group_session.resp_queues[message_source.message_chain.message_id]
-        if is_final and bot_message.tool_calls is None:
-            message_data.is_final = True
-        # print(message_data)
-        await queue.put(message_data)
-
-        return message_data.model_dump()
-
-    async def is_stream_output_supported(self) -> bool:
-        return self.is_stream
-
-    def register_listener(
-        self,
-        event_type: typing.Type[platform_events.Event],
-        func: typing.Callable[
-            [platform_events.Event, abstract_platform_adapter.AbstractMessagePlatformAdapter], typing.Awaitable[None]
-        ],
-    ):
-        """注册事件监听器"""
-        self.listeners[event_type] = func
-
-    def unregister_listener(
-        self,
-        event_type: typing.Type[platform_events.Event],
-        func: typing.Callable[
-            [platform_events.Event, abstract_platform_adapter.AbstractMessagePlatformAdapter], typing.Awaitable[None]
-        ],
-    ):
-        """取消注册事件监听器"""
-        del self.listeners[event_type]
-
-    async def is_muted(self, group_id: int) -> bool:
-        return False
-
-    async def run_async(self):
-        """运行适配器"""
-        await self.logger.info('WebChat调试适配器已启动')
-
-        try:
-            while True:
-                await asyncio.sleep(1)
-        except asyncio.CancelledError:
-            await self.logger.info('WebChat调试适配器已停止')
-            raise
-
-    async def kill(self):
-        """停止适配器"""
-        await self.logger.info('WebChat调试适配器正在停止')
-
-    async def send_webchat_message(
-        self,
-        pipeline_uuid: str,
-        session_type: str,
-        message_chain_obj: typing.List[dict],
-        is_stream: bool = False,
-    ) -> dict:
-        self.is_stream = is_stream
-        """发送调试消息到流水线"""
-        if session_type == 'person':
-            use_session = self.webchat_person_session
-        else:
-            use_session = self.webchat_group_session
-
-        message_chain = platform_message.MessageChain.parse_obj(message_chain_obj)
-
-        message_id = len(use_session.get_message_list(pipeline_uuid)) + 1
-
-        use_session.resp_queues[message_id] = asyncio.Queue()
-        logger.debug(f'Initialized queue for message_id: {message_id}')
-
-        use_session.get_message_list(pipeline_uuid).append(
-            WebChatMessage(
-                id=message_id,
-                role='user',
-                content=str(message_chain),
-                message_chain=message_chain_obj,
-                timestamp=datetime.now().isoformat(),
-            )
-        )
-
-        message_chain.insert(0, platform_message.Source(id=message_id, time=datetime.now().timestamp()))
-
-        if session_type == 'person':
-            sender = platform_entities.Friend(id='webchatperson', nickname='User', remark='User')
-            event = platform_events.FriendMessage(
-                sender=sender, message_chain=message_chain, time=datetime.now().timestamp()
-            )
-        else:
-            group = platform_entities.Group(
-                id='webchatgroup', name='Group', permission=platform_entities.Permission.Member
-            )
-            sender = platform_entities.GroupMember(
-                id='webchatperson',
-                member_name='User',
-                group=group,
-                permission=platform_entities.Permission.Member,
-            )
-            event = platform_events.GroupMessage(
-                sender=sender, message_chain=message_chain, time=datetime.now().timestamp()
-            )
-
-        self.ap.platform_mgr.webchat_proxy_bot.bot_entity.use_pipeline_uuid = pipeline_uuid
-
-        # trigger pipeline
-        if event.__class__ in self.listeners:
-            await self.listeners[event.__class__](event, self)
-
-        if is_stream:
-            queue = use_session.resp_queues[message_id]
-            msg_id = len(use_session.get_message_list(pipeline_uuid)) + 1
-            while True:
-                resp_message = await queue.get()
-                resp_message.id = msg_id
-                if resp_message.is_final:
-                    resp_message.id = msg_id
-                    use_session.get_message_list(pipeline_uuid).append(resp_message)
-                    yield resp_message.model_dump()
-                    break
-                yield resp_message.model_dump()
-            use_session.resp_queues.pop(message_id)
-
-        else:  # non-stream
-            # set waiter
-            # waiter = asyncio.Future[WebChatMessage]()
-            # use_session.resp_waiters[message_id] = waiter
-            # # waiter.add_done_callback(lambda future: use_session.resp_waiters.pop(message_id))
-            #
-            # resp_message = await waiter
-            #
-            # resp_message.id = len(use_session.get_message_list(pipeline_uuid)) + 1
-            #
-            # use_session.get_message_list(pipeline_uuid).append(resp_message)
-            #
-            # yield resp_message.model_dump()
-            msg_id = len(use_session.get_message_list(pipeline_uuid)) + 1
-
-            queue = use_session.resp_queues[message_id]
-            resp_message = await queue.get()
-            use_session.get_message_list(pipeline_uuid).append(resp_message)
-            resp_message.id = msg_id
-            resp_message.is_final = True
-
-            yield resp_message.model_dump()
-
-    def get_webchat_messages(self, pipeline_uuid: str, session_type: str) -> list[dict]:
-        """获取调试消息历史"""
-        if session_type == 'person':
-            return [message.model_dump() for message in self.webchat_person_session.get_message_list(pipeline_uuid)]
-        else:
-            return [message.model_dump() for message in self.webchat_group_session.get_message_list(pipeline_uuid)]

pkg/platform/sources/webchat.yaml

@@ -1,17 +0,0 @@
-apiVersion: v1
-kind: MessagePlatformAdapter
-metadata:
-  name: webchat
-  label:
-    en_US: "WebChat Debug"
-    zh_Hans: "网页聊天调试"
-  description:
-    en_US: "WebChat adapter for pipeline debugging"
-    zh_Hans: "用于流水线调试的网页聊天适配器"
-  icon: ""
-spec:
-  config: []
-execution:
-  python:
-    path: "webchat.py"
-    attr: "WebChatAdapter"

pkg/platform/sources/wecombot.py

@@ -1,167 +0,0 @@
-from __future__ import annotations
-import typing
-import asyncio
-import traceback
-
-import datetime
-import langbot_plugin.api.definition.abstract.platform.adapter as abstract_platform_adapter
-import langbot_plugin.api.entities.builtin.platform.message as platform_message
-import langbot_plugin.api.entities.builtin.platform.events as platform_events
-import langbot_plugin.api.entities.builtin.platform.entities as platform_entities
-import pydantic
-from ..logger import  EventLogger
-from libs.wecom_ai_bot_api.wecombotevent import WecomBotEvent
-from libs.wecom_ai_bot_api.api import WecomBotClient
-from ...core import app
-
-class WecomBotMessageConverter(abstract_platform_adapter.AbstractMessageConverter):
-    @staticmethod
-    async def yiri2target(message_chain: platform_message.MessageChain):
-        content = ''
-        for msg in message_chain:
-            if type(msg) is platform_message.Plain:
-                content += msg.text
-        return content
-
-    @staticmethod
-    async def target2yiri(event: WecomBotEvent):
-        yiri_msg_list = []
-        if event.type == 'group':
-            yiri_msg_list.append(platform_message.At(target=event.ai_bot_id))
-        yiri_msg_list.append(platform_message.Source(id=event.message_id, time=datetime.datetime.now()))
-        yiri_msg_list.append(platform_message.Plain(text=event.content))
-        if event.picurl != '':
-            yiri_msg_list.append(platform_message.Image(base64=event.picurl))
-        chain = platform_message.MessageChain(yiri_msg_list)
-
-        return chain
-
-class WecomBotEventConverter(abstract_platform_adapter.AbstractEventConverter):
-
-    @staticmethod
-    async def yiri2target(event:platform_events.MessageEvent):
-        return event.source_platform_object
-    
-    @staticmethod
-    async def target2yiri(event:WecomBotEvent):
-        message_chain = await WecomBotMessageConverter.target2yiri(event)
-        if event.type == 'single':
-            return platform_events.FriendMessage(
-                sender=platform_entities.Friend(
-                    id=event.userid,
-                    nickname='',
-                    remark='',
-                ),
-                message_chain=message_chain,
-                time=datetime.datetime.now().timestamp(),
-                source_platform_object=event,
-            )
-        elif event.type == 'group':
-            try:
-                sender = platform_entities.GroupMember(
-                    id=event.userid,
-                    permission='MEMBER',
-                    member_name=event.userid,
-                    group=platform_entities.Group(
-                        id=str(event.chatid),
-                        name='',
-                        permission=platform_entities.Permission.Member,
-                    ),
-                    special_title='',
-                    join_timestamp=0,
-                    last_speak_timestamp=0,
-                    mute_time_remaining=0,
-                )
-                time = datetime.datetime.now().timestamp()
-                return platform_events.GroupMessage(
-                    sender=sender,
-                    message_chain=message_chain,
-                    time=time,
-                    source_platform_object=event,
-                )
-            except Exception:
-                print(traceback.format_exc())
-
-class WecomBotAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
-    bot: WecomBotClient
-    bot_account_id: str
-    message_converter: WecomBotMessageConverter = WecomBotMessageConverter()
-    event_converter: WecomBotEventConverter = WecomBotEventConverter()
-    config: dict
-
-    def __init__(self, config: dict, logger: EventLogger):
-        required_keys = ['Token', 'EncodingAESKey', 'Corpid', 'BotId', 'port']
-        missing_keys = [key for key in required_keys if key not in config]
-        if missing_keys:
-            raise Exception(f'WecomBot 缺少配置项: {missing_keys}')
-
-        # 创建运行时 bot 对象
-        bot = WecomBotClient(
-            Token=config['Token'],
-            EnCodingAESKey=config['EncodingAESKey'],
-            Corpid=config['Corpid'],
-            logger=logger,
-        )
-        bot_account_id = config['BotId']
-
-        super().__init__(
-            config=config,
-            logger=logger,
-            bot=bot,
-            bot_account_id=bot_account_id,
-        )
-
-
-    async def reply_message(self, message_source:platform_events.MessageEvent, message:platform_message.MessageChain,quote_origin: bool = False):
-
-        content = await self.message_converter.yiri2target(message)
-        await self.bot.set_message(message_source.source_platform_object.message_id, content)
-
-    async def send_message(self, target_type, target_id, message):
-        pass
-
-    def register_listener(
-        self,
-        event_type: typing.Type[platform_events.Event],
-        callback: typing.Callable[[platform_events.Event, abstract_platform_adapter.AbstractMessagePlatformAdapter], None],
-    ):
-        async def on_message(event: WecomBotEvent):
-            try:
-                return await callback(await self.event_converter.target2yiri(event), self)
-            except Exception:
-                await self.logger.error(f'Error in wecombot callback: {traceback.format_exc()}')
-                print(traceback.format_exc())
-        try:
-            if event_type == platform_events.FriendMessage:
-                self.bot.on_message('single')(on_message)
-            elif event_type == platform_events.GroupMessage:
-                self.bot.on_message('group')(on_message)
-        except Exception:
-            print(traceback.format_exc())
-            
-
-    async def run_async(self):
-        async def shutdown_trigger_placeholder():
-            while True:
-                await asyncio.sleep(1)
-
-        await self.bot.run_task(
-            host='0.0.0.0',
-            port=self.config['port'],
-            shutdown_trigger=shutdown_trigger_placeholder,
-        )
-
-    async def kill(self) -> bool:
-        return False
-
-    async def unregister_listener(
-        self,
-        event_type: type,
-        callback: typing.Callable[[platform_events.Event, abstract_platform_adapter.AbstractMessagePlatformAdapter], None],
-    ):
-        return super().unregister_listener(event_type, callback)
-    
-    async def is_muted(self, group_id: int) -> bool:
-        pass
-
-    

pkg/plugin/connector.py

@@ -1,250 +0,0 @@
-# For connect to plugin runtime.
-from __future__ import annotations
-
-import asyncio
-from typing import Any
-import typing
-import os
-import sys
-
-from async_lru import alru_cache
-
-from ..core import app
-from . import handler
-from ..utils import platform
-from langbot_plugin.runtime.io.controllers.stdio import client as stdio_client_controller
-from langbot_plugin.runtime.io.controllers.ws import client as ws_client_controller
-from langbot_plugin.api.entities import events
-from langbot_plugin.api.entities import context
-import langbot_plugin.runtime.io.connection as base_connection
-from langbot_plugin.api.definition.components.manifest import ComponentManifest
-from langbot_plugin.api.entities.builtin.command import context as command_context
-from langbot_plugin.runtime.plugin.mgr import PluginInstallSource
-from ..core import taskmgr
-
-
-class PluginRuntimeConnector:
-    """Plugin runtime connector"""
-
-    ap: app.Application
-
-    handler: handler.RuntimeConnectionHandler
-
-    handler_task: asyncio.Task
-
-    heartbeat_task: asyncio.Task | None = None
-
-    stdio_client_controller: stdio_client_controller.StdioClientController
-
-    ctrl: stdio_client_controller.StdioClientController | ws_client_controller.WebSocketClientController
-
-    runtime_disconnect_callback: typing.Callable[
-        [PluginRuntimeConnector], typing.Coroutine[typing.Any, typing.Any, None]
-    ]
-
-    is_enable_plugin: bool = True
-    """Mark if the plugin system is enabled"""
-
-    def __init__(
-        self,
-        ap: app.Application,
-        runtime_disconnect_callback: typing.Callable[
-            [PluginRuntimeConnector], typing.Coroutine[typing.Any, typing.Any, None]
-        ],
-    ):
-        self.ap = ap
-        self.runtime_disconnect_callback = runtime_disconnect_callback
-        self.is_enable_plugin = self.ap.instance_config.data.get('plugin', {}).get('enable', True)
-
-    async def heartbeat_loop(self):
-        while True:
-            await asyncio.sleep(10)
-            try:
-                await self.ping_plugin_runtime()
-                self.ap.logger.debug('Heartbeat to plugin runtime success.')
-            except Exception as e:
-                self.ap.logger.debug(f'Failed to heartbeat to plugin runtime: {e}')
-
-    async def initialize(self):
-        if not self.is_enable_plugin:
-            self.ap.logger.info('Plugin system is disabled.')
-            return
-
-        async def new_connection_callback(connection: base_connection.Connection):
-            async def disconnect_callback(rchandler: handler.RuntimeConnectionHandler) -> bool:
-                if platform.get_platform() == 'docker' or platform.use_websocket_to_connect_plugin_runtime():
-                    self.ap.logger.error('Disconnected from plugin runtime, trying to reconnect...')
-                    await self.runtime_disconnect_callback(self)
-                    return False
-                else:
-                    self.ap.logger.error(
-                        'Disconnected from plugin runtime, cannot automatically reconnect while LangBot connects to plugin runtime via stdio, please restart LangBot.'
-                    )
-                    return False
-
-            self.handler = handler.RuntimeConnectionHandler(connection, disconnect_callback, self.ap)
-
-            self.handler_task = asyncio.create_task(self.handler.run())
-            _ = await self.handler.ping()
-            self.ap.logger.info('Connected to plugin runtime.')
-            await self.handler_task
-
-        task: asyncio.Task | None = None
-
-        if platform.get_platform() == 'docker' or platform.use_websocket_to_connect_plugin_runtime():  # use websocket
-            self.ap.logger.info('use websocket to connect to plugin runtime')
-            ws_url = self.ap.instance_config.data.get('plugin', {}).get(
-                'runtime_ws_url', 'ws://langbot_plugin_runtime:5400/control/ws'
-            )
-
-            async def make_connection_failed_callback(
-                ctrl: ws_client_controller.WebSocketClientController, exc: Exception = None
-            ) -> None:
-                if exc is not None:
-                    self.ap.logger.error(f'Failed to connect to plugin runtime({ws_url}): {exc}')
-                else:
-                    self.ap.logger.error(f'Failed to connect to plugin runtime({ws_url}), trying to reconnect...')
-                await self.runtime_disconnect_callback(self)
-
-            self.ctrl = ws_client_controller.WebSocketClientController(
-                ws_url=ws_url,
-                make_connection_failed_callback=make_connection_failed_callback,
-            )
-            task = self.ctrl.run(new_connection_callback)
-        else:  # stdio
-            self.ap.logger.info('use stdio to connect to plugin runtime')
-            # cmd: lbp rt -s
-            python_path = sys.executable
-            env = os.environ.copy()
-            self.ctrl = stdio_client_controller.StdioClientController(
-                command=python_path,
-                args=['-m', 'langbot_plugin.cli.__init__', 'rt', '-s'],
-                env=env,
-            )
-            task = self.ctrl.run(new_connection_callback)
-
-        if self.heartbeat_task is None:
-            self.heartbeat_task = asyncio.create_task(self.heartbeat_loop())
-
-        asyncio.create_task(task)
-
-    async def initialize_plugins(self):
-        pass
-
-    async def ping_plugin_runtime(self):
-        if not hasattr(self, 'handler'):
-            raise Exception('Plugin runtime is not connected')
-
-        return await self.handler.ping()
-
-    async def install_plugin(
-        self,
-        install_source: PluginInstallSource,
-        install_info: dict[str, Any],
-        task_context: taskmgr.TaskContext | None = None,
-    ):
-        if install_source == PluginInstallSource.LOCAL:
-            # transfer file before install
-            file_bytes = install_info['plugin_file']
-            file_key = await self.handler.send_file(file_bytes, 'lbpkg')
-            install_info['plugin_file_key'] = file_key
-            del install_info['plugin_file']
-            self.ap.logger.info(f'Transfered file {file_key} to plugin runtime')
-
-        async for ret in self.handler.install_plugin(install_source.value, install_info):
-            current_action = ret.get('current_action', None)
-            if current_action is not None:
-                if task_context is not None:
-                    task_context.set_current_action(current_action)
-
-            trace = ret.get('trace', None)
-            if trace is not None:
-                if task_context is not None:
-                    task_context.trace(trace)
-
-    async def upgrade_plugin(
-        self, plugin_author: str, plugin_name: str, task_context: taskmgr.TaskContext | None = None
-    ) -> dict[str, Any]:
-        async for ret in self.handler.upgrade_plugin(plugin_author, plugin_name):
-            current_action = ret.get('current_action', None)
-            if current_action is not None:
-                if task_context is not None:
-                    task_context.set_current_action(current_action)
-
-            trace = ret.get('trace', None)
-            if trace is not None:
-                if task_context is not None:
-                    task_context.trace(trace)
-
-    async def delete_plugin(
-        self, plugin_author: str, plugin_name: str, task_context: taskmgr.TaskContext | None = None
-    ) -> dict[str, Any]:
-        async for ret in self.handler.delete_plugin(plugin_author, plugin_name):
-            current_action = ret.get('current_action', None)
-            if current_action is not None:
-                if task_context is not None:
-                    task_context.set_current_action(current_action)
-
-            trace = ret.get('trace', None)
-            if trace is not None:
-                if task_context is not None:
-                    task_context.trace(trace)
-
-    async def list_plugins(self) -> list[dict[str, Any]]:
-        return await self.handler.list_plugins()
-
-    async def get_plugin_info(self, author: str, plugin_name: str) -> dict[str, Any]:
-        return await self.handler.get_plugin_info(author, plugin_name)
-
-    async def set_plugin_config(self, plugin_author: str, plugin_name: str, config: dict[str, Any]) -> dict[str, Any]:
-        return await self.handler.set_plugin_config(plugin_author, plugin_name, config)
-
-    @alru_cache(ttl=5 * 60)  # 5 minutes
-    async def get_plugin_icon(self, plugin_author: str, plugin_name: str) -> dict[str, Any]:
-        return await self.handler.get_plugin_icon(plugin_author, plugin_name)
-
-    async def emit_event(
-        self,
-        event: events.BaseEventModel,
-    ) -> context.EventContext:
-        event_ctx = context.EventContext.from_event(event)
-
-        if not self.is_enable_plugin:
-            return event_ctx
-        event_ctx_result = await self.handler.emit_event(event_ctx.model_dump(serialize_as_any=True))
-
-        event_ctx = context.EventContext.model_validate(event_ctx_result['event_context'])
-
-        return event_ctx
-
-    async def list_tools(self) -> list[ComponentManifest]:
-        list_tools_data = await self.handler.list_tools()
-
-        return [ComponentManifest.model_validate(tool) for tool in list_tools_data]
-
-    async def call_tool(self, tool_name: str, parameters: dict[str, Any]) -> dict[str, Any]:
-        return await self.handler.call_tool(tool_name, parameters)
-
-    async def list_commands(self) -> list[ComponentManifest]:
-        list_commands_data = await self.handler.list_commands()
-
-        return [ComponentManifest.model_validate(command) for command in list_commands_data]
-
-    async def execute_command(
-        self, command_ctx: command_context.ExecuteContext
-    ) -> typing.AsyncGenerator[command_context.CommandReturn, None]:
-        gen = self.handler.execute_command(command_ctx.model_dump(serialize_as_any=True))
-
-        async for ret in gen:
-            cmd_ret = command_context.CommandReturn.model_validate(ret)
-
-            yield cmd_ret
-
-    def dispose(self):
-        if self.is_enable_plugin and isinstance(self.ctrl, stdio_client_controller.StdioClientController):
-            self.ap.logger.info('Terminating plugin runtime process...')
-            self.ctrl.process.terminate()
-
-        if self.heartbeat_task is not None:
-            self.heartbeat_task.cancel()
-            self.heartbeat_task = None

pkg/provider/modelmgr/modelmgr.py

@@ -1,192 +0,0 @@
-from __future__ import annotations
-
-import sqlalchemy
-import traceback
-
-from . import requester
-from ...core import app
-from ...discover import engine
-from . import token
-from ...entity.persistence import model as persistence_model
-from ...entity.errors import provider as provider_errors
-
-FETCH_MODEL_LIST_URL = 'https://api.qchatgpt.rockchin.top/api/v2/fetch/model_list'
-
-
-class ModelManager:
-    """模型管理器"""
-
-    ap: app.Application
-
-    llm_models: list[requester.RuntimeLLMModel]
-
-    embedding_models: list[requester.RuntimeEmbeddingModel]
-
-    requester_components: list[engine.Component]
-
-    requester_dict: dict[str, type[requester.ProviderAPIRequester]]  # cache
-
-    def __init__(self, ap: app.Application):
-        self.ap = ap
-        self.llm_models = []
-        self.embedding_models = []
-        self.requester_components = []
-        self.requester_dict = {}
-
-    async def initialize(self):
-        self.requester_components = self.ap.discover.get_components_by_kind('LLMAPIRequester')
-
-        # forge requester class dict
-        requester_dict: dict[str, type[requester.ProviderAPIRequester]] = {}
-        for component in self.requester_components:
-            requester_dict[component.metadata.name] = component.get_python_component_class()
-
-        self.requester_dict = requester_dict
-
-        await self.load_models_from_db()
-
-    async def load_models_from_db(self):
-        """从数据库加载模型"""
-        self.ap.logger.info('Loading models from db...')
-
-        self.llm_models = []
-        self.embedding_models = []
-
-        # llm models
-        result = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_model.LLMModel))
-        llm_models = result.all()
-        for llm_model in llm_models:
-            try:
-                await self.load_llm_model(llm_model)
-            except provider_errors.RequesterNotFoundError as e:
-                self.ap.logger.warning(f'Requester {e.requester_name} not found, skipping model {llm_model.uuid}')
-            except Exception as e:
-                self.ap.logger.error(f'Failed to load model {llm_model.uuid}: {e}\n{traceback.format_exc()}')
-
-        # embedding models
-        result = await self.ap.persistence_mgr.execute_async(sqlalchemy.select(persistence_model.EmbeddingModel))
-        embedding_models = result.all()
-        for embedding_model in embedding_models:
-            await self.load_embedding_model(embedding_model)
-
-    async def init_runtime_llm_model(
-        self,
-        model_info: persistence_model.LLMModel | sqlalchemy.Row[persistence_model.LLMModel] | dict,
-    ):
-        """初始化运行时 LLM 模型"""
-        if isinstance(model_info, sqlalchemy.Row):
-            model_info = persistence_model.LLMModel(**model_info._mapping)
-        elif isinstance(model_info, dict):
-            model_info = persistence_model.LLMModel(**model_info)
-
-        if model_info.requester not in self.requester_dict:
-            raise provider_errors.RequesterNotFoundError(model_info.requester)
-
-        requester_inst = self.requester_dict[model_info.requester](ap=self.ap, config=model_info.requester_config)
-
-        await requester_inst.initialize()
-
-        runtime_llm_model = requester.RuntimeLLMModel(
-            model_entity=model_info,
-            token_mgr=token.TokenManager(
-                name=model_info.uuid,
-                tokens=model_info.api_keys,
-            ),
-            requester=requester_inst,
-        )
-
-        return runtime_llm_model
-
-    async def init_runtime_embedding_model(
-        self,
-        model_info: persistence_model.EmbeddingModel | sqlalchemy.Row[persistence_model.EmbeddingModel] | dict,
-    ):
-        """初始化运行时 Embedding 模型"""
-        if isinstance(model_info, sqlalchemy.Row):
-            model_info = persistence_model.EmbeddingModel(**model_info._mapping)
-        elif isinstance(model_info, dict):
-            model_info = persistence_model.EmbeddingModel(**model_info)
-
-        requester_inst = self.requester_dict[model_info.requester](ap=self.ap, config=model_info.requester_config)
-
-        await requester_inst.initialize()
-
-        runtime_embedding_model = requester.RuntimeEmbeddingModel(
-            model_entity=model_info,
-            token_mgr=token.TokenManager(
-                name=model_info.uuid,
-                tokens=model_info.api_keys,
-            ),
-            requester=requester_inst,
-        )
-
-        return runtime_embedding_model
-
-    async def load_llm_model(
-        self,
-        model_info: persistence_model.LLMModel | sqlalchemy.Row[persistence_model.LLMModel] | dict,
-    ):
-        """加载 LLM 模型"""
-        runtime_llm_model = await self.init_runtime_llm_model(model_info)
-        self.llm_models.append(runtime_llm_model)
-
-    async def load_embedding_model(
-        self,
-        model_info: persistence_model.EmbeddingModel | sqlalchemy.Row[persistence_model.EmbeddingModel] | dict,
-    ):
-        """加载 Embedding 模型"""
-        runtime_embedding_model = await self.init_runtime_embedding_model(model_info)
-        self.embedding_models.append(runtime_embedding_model)
-
-    async def get_model_by_uuid(self, uuid: str) -> requester.RuntimeLLMModel:
-        """通过uuid获取 LLM 模型"""
-        for model in self.llm_models:
-            if model.model_entity.uuid == uuid:
-                return model
-        raise ValueError(f'LLM model {uuid} not found')
-
-    async def get_embedding_model_by_uuid(self, uuid: str) -> requester.RuntimeEmbeddingModel:
-        """通过uuid获取 Embedding 模型"""
-        for model in self.embedding_models:
-            if model.model_entity.uuid == uuid:
-                return model
-        raise ValueError(f'Embedding model {uuid} not found')
-
-    async def remove_llm_model(self, model_uuid: str):
-        """移除 LLM 模型"""
-        for model in self.llm_models:
-            if model.model_entity.uuid == model_uuid:
-                self.llm_models.remove(model)
-                return
-
-    async def remove_embedding_model(self, model_uuid: str):
-        """移除 Embedding 模型"""
-        for model in self.embedding_models:
-            if model.model_entity.uuid == model_uuid:
-                self.embedding_models.remove(model)
-                return
-
-    def get_available_requesters_info(self, model_type: str) -> list[dict]:
-        """获取所有可用的请求器"""
-        if model_type != '':
-            return [
-                component.to_plain_dict()
-                for component in self.requester_components
-                if model_type in component.spec['support_type']
-            ]
-        else:
-            return [component.to_plain_dict() for component in self.requester_components]
-
-    def get_available_requester_info_by_name(self, name: str) -> dict | None:
-        """通过名称获取请求器信息"""
-        for component in self.requester_components:
-            if component.metadata.name == name:
-                return component.to_plain_dict()
-        return None
-
-    def get_available_requester_manifest_by_name(self, name: str) -> engine.Component | None:
-        """通过名称获取请求器清单"""
-        for component in self.requester_components:
-            if component.metadata.name == name:
-                return component
-        return None

pkg/provider/modelmgr/requester.py

@@ -1,142 +0,0 @@
-from __future__ import annotations
-
-import abc
-import typing
-
-from ...core import app
-from ...entity.persistence import model as persistence_model
-import langbot_plugin.api.entities.builtin.resource.tool as resource_tool
-from . import token
-import langbot_plugin.api.entities.builtin.pipeline.query as pipeline_query
-import langbot_plugin.api.entities.builtin.provider.message as provider_message
-
-
-class RuntimeLLMModel:
-    """运行时模型"""
-
-    model_entity: persistence_model.LLMModel
-    """模型数据"""
-
-    token_mgr: token.TokenManager
-    """api key管理器"""
-
-    requester: ProviderAPIRequester
-    """请求器实例"""
-
-    def __init__(
-        self,
-        model_entity: persistence_model.LLMModel,
-        token_mgr: token.TokenManager,
-        requester: ProviderAPIRequester,
-    ):
-        self.model_entity = model_entity
-        self.token_mgr = token_mgr
-        self.requester = requester
-
-
-class RuntimeEmbeddingModel:
-    """运行时 Embedding 模型"""
-
-    model_entity: persistence_model.EmbeddingModel
-    """模型数据"""
-
-    token_mgr: token.TokenManager
-    """api key管理器"""
-
-    requester: ProviderAPIRequester
-    """请求器实例"""
-
-    def __init__(
-        self,
-        model_entity: persistence_model.EmbeddingModel,
-        token_mgr: token.TokenManager,
-        requester: ProviderAPIRequester,
-    ):
-        self.model_entity = model_entity
-        self.token_mgr = token_mgr
-        self.requester = requester
-
-
-class ProviderAPIRequester(metaclass=abc.ABCMeta):
-    """Provider API请求器"""
-
-    name: str = None
-
-    ap: app.Application
-
-    default_config: dict[str, typing.Any] = {}
-
-    requester_cfg: dict[str, typing.Any] = {}
-
-    def __init__(self, ap: app.Application, config: dict[str, typing.Any]):
-        self.ap = ap
-        self.requester_cfg = {**self.default_config}
-        self.requester_cfg.update(config)
-
-    async def initialize(self):
-        pass
-
-    @abc.abstractmethod
-    async def invoke_llm(
-        self,
-        query: pipeline_query.Query,
-        model: RuntimeLLMModel,
-        messages: typing.List[provider_message.Message],
-        funcs: typing.List[resource_tool.LLMTool] = None,
-        extra_args: dict[str, typing.Any] = {},
-        remove_think: bool = False,
-    ) -> provider_message.Message:
-        """调用API
-
-        Args:
-            model (RuntimeLLMModel): 使用的模型信息
-            messages (typing.List[llm_entities.Message]): 消息对象列表
-            funcs (typing.List[tools_entities.LLMFunction], optional): 使用的工具函数列表. Defaults to None.
-            extra_args (dict[str, typing.Any], optional): 额外的参数. Defaults to {}.
-            remove_think (bool, optional): 是否移思考中的消息. Defaults to False.
-
-        Returns:
-            llm_entities.Message: 返回消息对象
-        """
-        pass
-
-    async def invoke_llm_stream(
-        self,
-        query: pipeline_query.Query,
-        model: RuntimeLLMModel,
-        messages: typing.List[provider_message.Message],
-        funcs: typing.List[resource_tool.LLMTool] = None,
-        extra_args: dict[str, typing.Any] = {},
-        remove_think: bool = False,
-    ) -> provider_message.MessageChunk:
-        """调用API
-
-        Args:
-            model (RuntimeLLMModel): 使用的模型信息
-            messages (typing.List[provider_message.Message]): 消息对象列表
-            funcs (typing.List[resource_tool.LLMTool], optional): 使用的工具函数列表. Defaults to None.
-            extra_args (dict[str, typing.Any], optional): 额外的参数. Defaults to {}.
-            remove_think (bool, optional): 是否移除思考中的消息. Defaults to False.
-
-        Returns:
-            typing.AsyncGenerator[provider_message.MessageChunk]: 返回消息对象
-        """
-        pass
-
-    async def invoke_embedding(
-        self,
-        model: RuntimeEmbeddingModel,
-        input_text: typing.List[str],
-        extra_args: dict[str, typing.Any] = {},
-    ) -> typing.List[typing.List[float]]:
-        """调用 Embedding API
-
-        Args:
-            model (RuntimeEmbeddingModel): 使用的模型信息
-            input_text (typing.List[str]): 输入文本
-            extra_args (dict[str, typing.Any], optional): 额外的参数. Defaults to {}.
-
-        Returns:
-            typing.List[typing.List[float]]: 返回的 embedding 向量
-        """
-        pass

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

@@ -1,31 +0,0 @@
-apiVersion: v1
-kind: LLMAPIRequester
-metadata:
-  name: 302-ai-chat-completions
-  label:
-    en_US: 302.AI
-    zh_Hans: 302.AI
-  icon: 302ai.png
-spec:
-  config:
-    - name: base_url
-      label:
-        en_US: Base URL
-        zh_Hans: 基础 URL
-      type: string
-      required: true
-      default: "https://api.302.ai/v1"
-    - name: timeout
-      label:
-        en_US: Timeout
-        zh_Hans: 超时时间
-      type: integer
-      required: true
-      default: 120
-  support_type:
-    - llm
-    - text-embedding
-execution:
-  python:
-    path: ./302aichatcmpl.py
-    attr: AI302ChatCompletions

pkg/provider/modelmgr/requesters/anthropicmsgs.yaml

@@ -1,30 +0,0 @@
-apiVersion: v1
-kind: LLMAPIRequester
-metadata:
-  name: anthropic-messages
-  label:
-    en_US: Anthropic
-    zh_Hans: Anthropic
-  icon: anthropic.svg
-spec:
-  config:
-    - name: base_url
-      label:
-        en_US: Base URL
-        zh_Hans: 基础 URL
-      type: string
-      required: true
-      default: "https://api.anthropic.com"
-    - name: timeout
-      label:
-        en_US: Timeout
-        zh_Hans: 超时时间
-      type: integer
-      required: true
-      default: 120
-  support_type:
-    - llm
-execution:
-  python:
-    path: ./anthropicmsgs.py
-    attr: AnthropicMessages

pkg/provider/modelmgr/requesters/bailianchatcmpl.yaml

@@ -1,30 +0,0 @@
-apiVersion: v1
-kind: LLMAPIRequester
-metadata:
-  name: bailian-chat-completions
-  label:
-    en_US: Aliyun Bailian
-    zh_Hans: 阿里云百炼
-  icon: bailian.png
-spec:
-  config:
-    - name: base_url
-      label:
-        en_US: Base URL
-        zh_Hans: 基础 URL
-      type: string
-      required: true
-      default: "https://dashscope.aliyuncs.com/compatible-mode/v1"
-    - name: timeout
-      label:
-        en_US: Timeout
-        zh_Hans: 超时时间
-      type: integer
-      required: true
-      default: 120
-  support_type:
-    - llm
-execution:
-  python:
-    path: ./bailianchatcmpl.py
-    attr: BailianChatCompletions

pkg/provider/modelmgr/requesters/chatcmpl.yaml

@@ -1,31 +0,0 @@
-apiVersion: v1
-kind: LLMAPIRequester
-metadata:
-  name: openai-chat-completions
-  label:
-    en_US: OpenAI
-    zh_Hans: OpenAI
-  icon: openai.svg
-spec:
-  config:
-    - name: base_url
-      label:
-        en_US: Base URL
-        zh_Hans: 基础 URL
-      type: string
-      required: true
-      default: "https://api.openai.com/v1"
-    - name: timeout
-      label:
-        en_US: Timeout
-        zh_Hans: 超时时间
-      type: integer
-      required: true
-      default: 120
-  support_type:
-    - llm
-    - text-embedding
-execution:
-  python:
-    path: ./chatcmpl.py
-    attr: OpenAIChatCompletions

pkg/provider/modelmgr/requesters/compsharechatcmpl.yaml

@@ -1,30 +0,0 @@
-apiVersion: v1
-kind: LLMAPIRequester
-metadata:
-  name: compshare-chat-completions
-  label:
-    en_US: CompShare
-    zh_Hans: 优云智算
-  icon: compshare.png
-spec:
-  config:
-    - name: base_url
-      label:
-        en_US: Base URL
-        zh_Hans: 基础 URL
-      type: string
-      required: true
-      default: "https://api.modelverse.cn/v1"
-    - name: timeout
-      label:
-        en_US: Timeout
-        zh_Hans: 超时时间
-      type: integer
-      required: true
-      default: 120
-  support_type:
-    - llm
-execution:
-  python:
-    path: ./compsharechatcmpl.py
-    attr: CompShareChatCompletions

pkg/provider/modelmgr/requesters/deepseekchatcmpl.yaml

@@ -1,30 +0,0 @@
-apiVersion: v1
-kind: LLMAPIRequester
-metadata:
-  name: deepseek-chat-completions
-  label:
-    en_US: DeepSeek
-    zh_Hans: DeepSeek
-  icon: deepseek.svg
-spec:
-  config:
-    - name: base_url
-      label:
-        en_US: Base URL
-        zh_Hans: 基础 URL
-      type: string
-      required: true
-      default: "https://api.deepseek.com"
-    - name: timeout
-      label:
-        en_US: Timeout
-        zh_Hans: 超时时间
-      type: integer
-      required: true
-      default: 120
-  support_type:
-    - llm
-execution:
-  python:
-    path: ./deepseekchatcmpl.py
-    attr: DeepseekChatCompletions

pkg/provider/modelmgr/requesters/geminichatcmpl.yaml

@@ -1,30 +0,0 @@
-apiVersion: v1
-kind: LLMAPIRequester
-metadata:
-  name: gemini-chat-completions
-  label:
-    en_US: Google Gemini
-    zh_Hans: Google Gemini
-  icon: gemini.svg
-spec:
-  config:
-    - name: base_url
-      label:
-        en_US: Base URL
-        zh_Hans: 基础 URL
-      type: string
-      required: true
-      default: "https://generativelanguage.googleapis.com/v1beta/openai"
-    - name: timeout
-      label:
-        en_US: Timeout
-        zh_Hans: 超时时间
-      type: integer
-      required: true
-      default: 120
-  support_type:
-    - llm
-execution:
-  python:
-    path: ./geminichatcmpl.py
-    attr: GeminiChatCompletions

pkg/provider/modelmgr/requesters/giteeaichatcmpl.yaml

@@ -1,31 +0,0 @@
-apiVersion: v1
-kind: LLMAPIRequester
-metadata:
-  name: gitee-ai-chat-completions
-  label:
-    en_US: Gitee AI
-    zh_Hans: Gitee AI
-  icon: giteeai.svg
-spec:
-  config:
-    - name: base_url
-      label:
-        en_US: Base URL
-        zh_Hans: 基础 URL
-      type: string
-      required: true
-      default: "https://ai.gitee.com/v1"
-    - name: timeout
-      label:
-        en_US: Timeout
-        zh_Hans: 超时时间
-      type: integer
-      required: true
-      default: 120
-  support_type:
-    - llm
-    - text-embedding
-execution:
-  python:
-    path: ./giteeaichatcmpl.py
-    attr: GiteeAIChatCompletions

pkg/provider/modelmgr/requesters/lmstudiochatcmpl.yaml

@@ -1,31 +0,0 @@
-apiVersion: v1
-kind: LLMAPIRequester
-metadata:
-  name: lmstudio-chat-completions
-  label:
-    en_US: LM Studio
-    zh_Hans: LM Studio
-  icon: lmstudio.webp
-spec:
-  config:
-    - name: base_url
-      label:
-        en_US: Base URL
-        zh_Hans: 基础 URL
-      type: string
-      required: true
-      default: "http://127.0.0.1:1234/v1"
-    - name: timeout
-      label:
-        en_US: Timeout
-        zh_Hans: 超时时间
-      type: integer
-      required: true
-      default: 120
-  support_type:
-    - llm
-    - text-embedding
-execution:
-  python:
-    path: ./lmstudiochatcmpl.py
-    attr: LmStudioChatCompletions

pkg/provider/modelmgr/requesters/modelscopechatcmpl.yaml

@@ -1,37 +0,0 @@
-apiVersion: v1
-kind: LLMAPIRequester
-metadata:
-  name: modelscope-chat-completions
-  label:
-    en_US: ModelScope
-    zh_Hans: 魔搭社区
-  icon: modelscope.svg
-spec:
-  config:
-    - name: base_url
-      label:
-        en_US: Base URL
-        zh_Hans: 基础 URL
-      type: string
-      required: true
-      default: "https://api-inference.modelscope.cn/v1"
-    - name: args
-      label:
-        en_US: Args
-        zh_Hans: 附加参数
-      type: object
-      required: true
-      default: {}
-    - name: timeout
-      label:
-        en_US: Timeout
-        zh_Hans: 超时时间
-      type: int
-      required: true
-      default: 120
-  support_type:
-    - llm
-execution:
-  python:
-    path: ./modelscopechatcmpl.py
-    attr: ModelScopeChatCompletions

pkg/provider/modelmgr/requesters/moonshotchatcmpl.yaml

@@ -1,30 +0,0 @@
-apiVersion: v1
-kind: LLMAPIRequester
-metadata:
-  name: moonshot-chat-completions
-  label:
-    en_US: Moonshot
-    zh_Hans: 月之暗面
-  icon: moonshot.png
-spec:
-  config:
-    - name: base_url
-      label:
-        en_US: Base URL
-        zh_Hans: 基础 URL
-      type: string
-      required: true
-      default: "https://api.moonshot.ai/v1"
-    - name: timeout
-      label:
-        en_US: Timeout
-        zh_Hans: 超时时间
-      type: integer
-      required: true
-      default: 120
-  support_type:
-    - llm
-execution:
-  python:
-    path: ./moonshotchatcmpl.py
-    attr: MoonshotChatCompletions

pkg/provider/modelmgr/requesters/newapichatcmpl.yaml

@@ -1,31 +0,0 @@
-apiVersion: v1
-kind: LLMAPIRequester
-metadata:
-  name: new-api-chat-completions
-  label:
-    en_US: New API
-    zh_Hans: New API
-  icon: newapi.png
-spec:
-  config:
-    - name: base_url
-      label:
-        en_US: Base URL
-        zh_Hans: 基础 URL
-      type: string
-      required: true
-      default: "http://localhost:3000/v1"
-    - name: timeout
-      label:
-        en_US: Timeout
-        zh_Hans: 超时时间
-      type: integer
-      required: true
-      default: 120
-  support_type:
-    - llm
-    - text-embedding
-execution:
-  python:
-    path: ./newapichatcmpl.py
-    attr: NewAPIChatCompletions

pkg/provider/modelmgr/requesters/ollamachat.yaml

@@ -1,31 +0,0 @@
-apiVersion: v1
-kind: LLMAPIRequester
-metadata:
-  name: ollama-chat
-  label:
-    en_US: Ollama
-    zh_Hans: Ollama
-  icon: ollama.svg
-spec:
-  config:
-    - name: base_url
-      label:
-        en_US: Base URL
-        zh_Hans: 基础 URL
-      type: string
-      required: true
-      default: "http://127.0.0.1:11434"
-    - name: timeout
-      label:
-        en_US: Timeout
-        zh_Hans: 超时时间
-      type: integer
-      required: true
-      default: 120
-  support_type:
-    - llm
-    - text-embedding
-execution:
-  python:
-    path: ./ollamachat.py
-    attr: OllamaChatCompletions

pkg/provider/modelmgr/requesters/openrouterchatcmpl.yaml

@@ -1,31 +0,0 @@
-apiVersion: v1
-kind: LLMAPIRequester
-metadata:
-  name: openrouter-chat-completions
-  label:
-    en_US: OpenRouter
-    zh_Hans: OpenRouter
-  icon: openrouter.svg
-spec:
-  config:
-    - name: base_url
-      label:
-        en_US: Base URL
-        zh_Hans: 基础 URL
-      type: string
-      required: true
-      default: "https://openrouter.ai/api/v1"
-    - name: timeout
-      label:
-        en_US: Timeout
-        zh_Hans: 超时时间
-      type: integer
-      required: true
-      default: 120
-  support_type:
-    - llm
-    - text-embedding
-execution:
-  python:
-    path: ./openrouterchatcmpl.py
-    attr: OpenRouterChatCompletions

pkg/provider/modelmgr/requesters/ppiochatcmpl.yaml

@@ -1,38 +0,0 @@
-apiVersion: v1
-kind: LLMAPIRequester
-metadata:
-  name: ppio-chat-completions
-  label:
-    en_US: ppio 
-    zh_Hans: 派欧云
-  icon: ppio.svg
-spec:
-  config:
-    - name: base_url
-      label:
-        en_US: Base URL
-        zh_Hans: 基础 URL
-      type: string
-      required: true
-      default: "https://api.ppinfra.com/v3/openai"
-    - name: args
-      label:
-        en_US: Args
-        zh_Hans: 附加参数
-      type: object
-      required: true
-      default: {}
-    - name: timeout
-      label:
-        en_US: Timeout
-        zh_Hans: 超时时间
-      type: int
-      required: true
-      default: 120
-  support_type:
-    - llm
-    - text-embedding
-execution:
-  python:
-    path: ./ppiochatcmpl.py
-    attr: PPIOChatCompletions

pkg/provider/modelmgr/requesters/qhaigcchatcmpl.yaml

@@ -1,38 +0,0 @@
-apiVersion: v1
-kind: LLMAPIRequester
-metadata:
-  name: qhaigc-chat-completions
-  label:
-    en_US: QH AI
-    zh_Hans: 启航 AI
-  icon: qhaigc.png
-spec:
-  config:
-    - name: base_url
-      label:
-        en_US: Base URL
-        zh_Hans: 基础 URL
-      type: string
-      required: true
-      default: "https://api.qhaigc.net/v1"
-    - name: args
-      label:
-        en_US: Args
-        zh_Hans: 附加参数
-      type: object
-      required: true
-      default: {}
-    - name: timeout
-      label:
-        en_US: Timeout
-        zh_Hans: 超时时间
-      type: int
-      required: true
-      default: 120
-  support_type:
-    - llm
-    - text-embedding
-execution:
-  python:
-    path: ./qhaigcchatcmpl.py
-    attr: QHAIGCChatCompletions

pkg/provider/modelmgr/requesters/shengsuanyun.yaml

@@ -1,38 +0,0 @@
-apiVersion: v1
-kind: LLMAPIRequester
-metadata:
-  name: shengsuanyun-chat-completions
-  label:
-    en_US: ShengSuanYun
-    zh_Hans: 胜算云
-  icon: shengsuanyun.svg
-spec:
-  config:
-    - name: base_url
-      label:
-        en_US: Base URL
-        zh_Hans: 基础 URL
-      type: string
-      required: true
-      default: "https://router.shengsuanyun.com/api/v1"
-    - name: args
-      label:
-        en_US: Args
-        zh_Hans: 附加参数
-      type: object
-      required: true
-      default: {}
-    - name: timeout
-      label:
-        en_US: Timeout
-        zh_Hans: 超时时间
-      type: int
-      required: true
-      default: 120
-  support_type:
-    - llm
-    - text-embedding
-execution:
-  python:
-    path: ./shengsuanyun.py
-    attr: ShengSuanYunChatCompletions

pkg/provider/modelmgr/requesters/siliconflowchatcmpl.yaml

@@ -1,31 +0,0 @@
-apiVersion: v1
-kind: LLMAPIRequester
-metadata:
-  name: siliconflow-chat-completions
-  label:
-    en_US: SiliconFlow
-    zh_Hans: 硅基流动
-  icon: siliconflow.svg
-spec:
-  config:
-    - name: base_url
-      label:
-        en_US: Base URL
-        zh_Hans: 基础 URL
-      type: string
-      required: true
-      default: "https://api.siliconflow.cn/v1"
-    - name: timeout
-      label:
-        en_US: Timeout
-        zh_Hans: 超时时间
-      type: integer
-      required: true
-      default: 120
-  support_type:
-    - llm
-    - text-embedding
-execution:
-  python:
-    path: ./siliconflowchatcmpl.py
-    attr: SiliconFlowChatCompletions

pkg/provider/modelmgr/requesters/tokenpony.yaml

@@ -1,31 +0,0 @@
-apiVersion: v1
-kind: LLMAPIRequester
-metadata:
-  name: tokenpony-chat-completions
-  label:
-    en_US: TokenPony
-    zh_Hans: 小马算力
-  icon: tokenpony.svg
-spec:
-  config:
-    - name: base_url
-      label:
-        en_US: Base URL
-        zh_Hans: 基础 URL
-      type: string
-      required: true
-      default: "https://api.tokenpony.cn/v1"
-    - name: timeout
-      label:
-        en_US: Timeout
-        zh_Hans: 超时时间
-      type: integer
-      required: true
-      default: 120
-  support_type:
-    - llm
-    - text-embedding
-execution:
-  python:
-    path: ./tokenponychatcmpl.py
-    attr: TokenPonyChatCompletions

pkg/provider/modelmgr/requesters/volcarkchatcmpl.yaml

@@ -1,30 +0,0 @@
-apiVersion: v1
-kind: LLMAPIRequester
-metadata:
-  name: volcark-chat-completions
-  label:
-    en_US: Volc Engine Ark
-    zh_Hans: 火山方舟
-  icon: volcark.svg
-spec:
-  config:
-    - name: base_url
-      label:
-        en_US: Base URL
-        zh_Hans: 基础 URL
-      type: string
-      required: true
-      default: "https://ark.cn-beijing.volces.com/api/v3"
-    - name: timeout
-      label:
-        en_US: Timeout
-        zh_Hans: 超时时间
-      type: integer
-      required: true
-      default: 120
-  support_type:
-    - llm
-execution:
-  python:
-    path: ./volcarkchatcmpl.py
-    attr: VolcArkChatCompletions

pkg/provider/modelmgr/requesters/xaichatcmpl.yaml

@@ -1,30 +0,0 @@
-apiVersion: v1
-kind: LLMAPIRequester
-metadata:
-  name: xai-chat-completions
-  label:
-    en_US: xAI
-    zh_Hans: xAI
-  icon: xai.svg
-spec:
-  config:
-    - name: base_url
-      label:
-        en_US: Base URL
-        zh_Hans: 基础 URL
-      type: string
-      required: true
-      default: "https://api.x.ai/v1"
-    - name: timeout
-      label:
-        en_US: Timeout
-        zh_Hans: 超时时间
-      type: integer
-      required: true
-      default: 120
-  support_type:
-    - llm
-execution:
-  python:
-    path: ./xaichatcmpl.py
-    attr: XaiChatCompletions

pkg/provider/modelmgr/requesters/zhipuaichatcmpl.yaml

@@ -1,30 +0,0 @@
-apiVersion: v1
-kind: LLMAPIRequester
-metadata:
-  name: zhipuai-chat-completions
-  label:
-    en_US: ZhipuAI
-    zh_Hans: 智谱 AI
-  icon: zhipuai.svg
-spec:
-  config:
-    - name: base_url
-      label:
-        en_US: Base URL
-        zh_Hans: 基础 URL
-      type: string
-      required: true
-      default: "https://open.bigmodel.cn/api/paas/v4"
-    - name: timeout
-      label:
-        en_US: Timeout
-        zh_Hans: 超时时间
-      type: integer
-      required: true
-      default: 120
-  support_type:
-    - llm
-execution:
-  python:
-    path: ./zhipuaichatcmpl.py
-    attr: ZhipuAIChatCompletions

pkg/provider/runners/n8nsvapi.py

@@ -1,160 +0,0 @@
-from __future__ import annotations
-
-import typing
-import json
-import uuid
-import aiohttp
-
-from .. import runner
-from ...core import app
-import langbot_plugin.api.entities.builtin.pipeline.query as pipeline_query
-import langbot_plugin.api.entities.builtin.provider.message as provider_message
-
-
-class N8nAPIError(Exception):
-    """N8n API 请求失败"""
-
-    def __init__(self, message: str):
-        self.message = message
-        super().__init__(self.message)
-
-
-@runner.runner_class('n8n-service-api')
-class N8nServiceAPIRunner(runner.RequestRunner):
-    """N8n Service API 工作流请求器"""
-
-    def __init__(self, ap: app.Application, pipeline_config: dict):
-        self.ap = ap
-        self.pipeline_config = pipeline_config
-
-        # 获取webhook URL
-        self.webhook_url = self.pipeline_config['ai']['n8n-service-api']['webhook-url']
-
-        # 获取超时设置，默认为120秒
-        self.timeout = self.pipeline_config['ai']['n8n-service-api'].get('timeout', 120)
-
-        # 获取输出键名，默认为response
-        self.output_key = self.pipeline_config['ai']['n8n-service-api'].get('output-key', 'response')
-
-        # 获取认证类型，默认为none
-        self.auth_type = self.pipeline_config['ai']['n8n-service-api'].get('auth-type', 'none')
-
-        # 根据认证类型获取相应的认证信息
-        if self.auth_type == 'basic':
-            self.basic_username = self.pipeline_config['ai']['n8n-service-api'].get('basic-username', '')
-            self.basic_password = self.pipeline_config['ai']['n8n-service-api'].get('basic-password', '')
-        elif self.auth_type == 'jwt':
-            self.jwt_secret = self.pipeline_config['ai']['n8n-service-api'].get('jwt-secret', '')
-            self.jwt_algorithm = self.pipeline_config['ai']['n8n-service-api'].get('jwt-algorithm', 'HS256')
-        elif self.auth_type == 'header':
-            self.header_name = self.pipeline_config['ai']['n8n-service-api'].get('header-name', '')
-            self.header_value = self.pipeline_config['ai']['n8n-service-api'].get('header-value', '')
-
-    async def _preprocess_user_message(self, query: pipeline_query.Query) -> str:
-        """预处理用户消息，提取纯文本
-
-        Returns:
-            str: 纯文本消息
-        """
-        plain_text = ''
-
-        if isinstance(query.user_message.content, list):
-            for ce in query.user_message.content:
-                if ce.type == 'text':
-                    plain_text += ce.text
-                # 注意：n8n webhook目前不支持直接处理图片，如需支持可在此扩展
-        elif isinstance(query.user_message.content, str):
-            plain_text = query.user_message.content
-
-        return plain_text
-
-    async def _call_webhook(self, query: pipeline_query.Query) -> typing.AsyncGenerator[provider_message.Message, None]:
-        """调用n8n webhook"""
-        # 生成会话ID（如果不存在）
-        if not query.session.using_conversation.uuid:
-            query.session.using_conversation.uuid = str(uuid.uuid4())
-
-        # 预处理用户消息
-        plain_text = await self._preprocess_user_message(query)
-
-        # 准备请求数据
-        payload = {
-            # 基本消息内容
-            'message': plain_text,
-            'user_message_text': plain_text,
-            'conversation_id': query.session.using_conversation.uuid,
-            'session_id': query.variables.get('session_id', ''),
-            'user_id': f'{query.session.launcher_type.value}_{query.session.launcher_id}',
-            'msg_create_time': query.variables.get('msg_create_time', ''),
-        }
-
-        # 添加所有变量到payload
-        payload.update(query.variables)
-
-        try:
-            # 准备请求头和认证信息
-            headers = {}
-            auth = None
-
-            # 根据认证类型设置相应的认证信息
-            if self.auth_type == 'basic':
-                # 使用Basic认证
-                auth = aiohttp.BasicAuth(self.basic_username, self.basic_password)
-                self.ap.logger.debug(f'using basic auth: {self.basic_username}')
-            elif self.auth_type == 'jwt':
-                # 使用JWT认证
-                import jwt
-                import time
-
-                # 创建JWT令牌
-                payload_jwt = {
-                    'exp': int(time.time()) + 3600,  # 1小时过期
-                    'iat': int(time.time()),
-                    'sub': 'n8n-webhook',
-                }
-                token = jwt.encode(payload_jwt, self.jwt_secret, algorithm=self.jwt_algorithm)
-
-                # 添加到Authorization头
-                headers['Authorization'] = f'Bearer {token}'
-                self.ap.logger.debug('using jwt auth')
-            elif self.auth_type == 'header':
-                # 使用自定义请求头认证
-                headers[self.header_name] = self.header_value
-                self.ap.logger.debug(f'using header auth: {self.header_name}')
-            else:
-                self.ap.logger.debug('no auth')
-
-            # 调用webhook
-            async with aiohttp.ClientSession() as session:
-                async with session.post(
-                    self.webhook_url, json=payload, headers=headers, auth=auth, timeout=self.timeout
-                ) as response:
-                    if response.status != 200:
-                        error_text = await response.text()
-                        self.ap.logger.error(f'n8n webhook call failed: {response.status}, {error_text}')
-                        raise Exception(f'n8n webhook call failed: {response.status}, {error_text}')
-
-                    # 解析响应
-                    response_data = await response.json()
-                    self.ap.logger.debug(f'n8n webhook response: {response_data}')
-
-                    # 从响应中提取输出
-                    if self.output_key in response_data:
-                        output_content = response_data[self.output_key]
-                    else:
-                        # 如果没有指定的输出键，则使用整个响应
-                        output_content = json.dumps(response_data, ensure_ascii=False)
-
-                    # 返回消息
-                    yield provider_message.Message(
-                        role='assistant',
-                        content=output_content,
-                    )
-        except Exception as e:
-            self.ap.logger.error(f'n8n webhook call exception: {str(e)}')
-            raise N8nAPIError(f'n8n webhook call exception: {str(e)}')
-
-    async def run(self, query: pipeline_query.Query) -> typing.AsyncGenerator[provider_message.Message, None]:
-        """运行请求"""
-        async for msg in self._call_webhook(query):
-            yield msg

pkg/provider/tools/loaders/mcp.py

@@ -1,158 +0,0 @@
-from __future__ import annotations
-
-import typing
-from contextlib import AsyncExitStack
-
-from mcp import ClientSession, StdioServerParameters
-from mcp.client.stdio import stdio_client
-from mcp.client.sse import sse_client
-
-from .. import loader
-from ....core import app
-import langbot_plugin.api.entities.builtin.resource.tool as resource_tool
-
-
-class RuntimeMCPSession:
-    """运行时 MCP 会话"""
-
-    ap: app.Application
-
-    server_name: str
-
-    server_config: dict
-
-    session: ClientSession
-
-    exit_stack: AsyncExitStack
-
-    functions: list[resource_tool.LLMTool] = []
-
-    def __init__(self, server_name: str, server_config: dict, ap: app.Application):
-        self.server_name = server_name
-        self.server_config = server_config
-        self.ap = ap
-
-        self.session = None
-
-        self.exit_stack = AsyncExitStack()
-        self.functions = []
-
-    async def _init_stdio_python_server(self):
-        server_params = StdioServerParameters(
-            command=self.server_config['command'],
-            args=self.server_config['args'],
-            env=self.server_config['env'],
-        )
-
-        stdio_transport = await self.exit_stack.enter_async_context(stdio_client(server_params))
-
-        stdio, write = stdio_transport
-
-        self.session = await self.exit_stack.enter_async_context(ClientSession(stdio, write))
-
-        await self.session.initialize()
-
-    async def _init_sse_server(self):
-        sse_transport = await self.exit_stack.enter_async_context(
-            sse_client(
-                self.server_config['url'],
-                headers=self.server_config.get('headers', {}),
-                timeout=self.server_config.get('timeout', 10),
-            )
-        )
-
-        sseio, write = sse_transport
-
-        self.session = await self.exit_stack.enter_async_context(ClientSession(sseio, write))
-
-        await self.session.initialize()
-
-    async def initialize(self):
-        self.ap.logger.debug(f'初始化 MCP 会话: {self.server_name} {self.server_config}')
-
-        if self.server_config['mode'] == 'stdio':
-            await self._init_stdio_python_server()
-        elif self.server_config['mode'] == 'sse':
-            await self._init_sse_server()
-        else:
-            raise ValueError(f'无法识别 MCP 服务器类型: {self.server_name}: {self.server_config}')
-
-        tools = await self.session.list_tools()
-
-        self.ap.logger.debug(f'获取 MCP 工具: {tools}')
-
-        for tool in tools.tools:
-
-            async def func(*, _tool=tool, **kwargs):
-                result = await self.session.call_tool(_tool.name, kwargs)
-                if result.isError:
-                    raise Exception(result.content[0].text)
-                return result.content[0].text
-
-            func.__name__ = tool.name
-
-            self.functions.append(
-                resource_tool.LLMTool(
-                    name=tool.name,
-                    human_desc=tool.description,
-                    description=tool.description,
-                    parameters=tool.inputSchema,
-                    func=func,
-                )
-            )
-
-    async def shutdown(self):
-        """关闭工具"""
-        await self.session._exit_stack.aclose()
-
-
-@loader.loader_class('mcp')
-class MCPLoader(loader.ToolLoader):
-    """MCP 工具加载器。
-
-    在此加载器中管理所有与 MCP Server 的连接。
-    """
-
-    sessions: dict[str, RuntimeMCPSession] = {}
-
-    _last_listed_functions: list[resource_tool.LLMTool] = []
-
-    def __init__(self, ap: app.Application):
-        super().__init__(ap)
-        self.sessions = {}
-        self._last_listed_functions = []
-
-    async def initialize(self):
-        for server_config in self.ap.instance_config.data.get('mcp', {}).get('servers', []):
-            if not server_config['enable']:
-                continue
-            session = RuntimeMCPSession(server_config['name'], server_config, self.ap)
-            await session.initialize()
-            # self.ap.event_loop.create_task(session.initialize())
-            self.sessions[server_config['name']] = session
-
-    async def get_tools(self) -> list[resource_tool.LLMTool]:
-        all_functions = []
-
-        for session in self.sessions.values():
-            all_functions.extend(session.functions)
-
-        self._last_listed_functions = all_functions
-
-        return all_functions
-
-    async def has_tool(self, name: str) -> bool:
-        return name in [f.name for f in self._last_listed_functions]
-
-    async def invoke_tool(self, name: str, parameters: dict) -> typing.Any:
-        for server_name, session in self.sessions.items():
-            for function in session.functions:
-                if function.name == name:
-                    return await function.func(**parameters)
-
-        raise ValueError(f'未找到工具: {name}')
-
-    async def shutdown(self):
-        """关闭工具"""
-        for session in self.sessions.values():
-            await session.shutdown()

pkg/storage/mgr.py

@@ -1,21 +0,0 @@
-from __future__ import annotations
-
-
-from ..core import app
-from . import provider
-from .providers import localstorage
-
-
-class StorageMgr:
-    """存储管理器"""
-
-    ap: app.Application
-
-    storage_provider: provider.StorageProvider
-
-    def __init__(self, ap: app.Application):
-        self.ap = ap
-        self.storage_provider = localstorage.LocalStorageProvider(ap)
-
-    async def initialize(self):
-        await self.storage_provider.initialize()

pkg/utils/announce.py

@@ -1,115 +0,0 @@
-from __future__ import annotations
-
-import json
-import typing
-import os
-import base64
-import logging
-
-import pydantic
-import requests
-
-from ..core import app
-
-
-class Announcement(pydantic.BaseModel):
-    """公告"""
-
-    id: int
-
-    time: str
-
-    timestamp: int
-
-    content: str
-
-    enabled: typing.Optional[bool] = True
-
-    def to_dict(self) -> dict:
-        return {
-            'id': self.id,
-            'time': self.time,
-            'timestamp': self.timestamp,
-            'content': self.content,
-            'enabled': self.enabled,
-        }
-
-
-class AnnouncementManager:
-    """公告管理器"""
-
-    ap: app.Application = None
-
-    def __init__(self, ap: app.Application):
-        self.ap = ap
-
-    async def fetch_all(self) -> list[Announcement]:
-        """获取所有公告"""
-        try:
-            resp = requests.get(
-                url='https://api.github.com/repos/langbot-app/LangBot/contents/res/announcement.json',
-                proxies=self.ap.proxy_mgr.get_forward_proxies(),
-                timeout=5,
-            )
-            resp.raise_for_status()  # 检查请求是否成功
-            obj_json = resp.json()
-            b64_content = obj_json['content']
-            # 解码
-            content = base64.b64decode(b64_content).decode('utf-8')
-
-            return [Announcement(**item) for item in json.loads(content)]
-        except (requests.RequestException, json.JSONDecodeError, KeyError) as e:
-            self.ap.logger.warning(f'获取公告失败: {e}')
-            pass
-        return []  # 请求失败时返回空列表
-
-    async def fetch_saved(self) -> list[Announcement]:
-        if not os.path.exists('data/labels/announcement_saved.json'):
-            with open('data/labels/announcement_saved.json', 'w', encoding='utf-8') as f:
-                f.write('[]')
-
-        with open('data/labels/announcement_saved.json', 'r', encoding='utf-8') as f:
-            content = f.read()
-
-        if not content:
-            content = '[]'
-
-        return [Announcement(**item) for item in json.loads(content)]
-
-    async def write_saved(self, content: list[Announcement]):
-        with open('data/labels/announcement_saved.json', 'w', encoding='utf-8') as f:
-            f.write(json.dumps([item.to_dict() for item in content], indent=4, ensure_ascii=False))
-
-    async def fetch_new(self) -> list[Announcement]:
-        """获取新公告"""
-        all = await self.fetch_all()
-        saved = await self.fetch_saved()
-
-        to_show: list[Announcement] = []
-
-        for item in all:
-            # 遍历saved检查是否有相同id的公告
-            for saved_item in saved:
-                if saved_item.id == item.id:
-                    break
-            else:
-                if item.enabled:
-                    # 没有相同id的公告
-                    to_show.append(item)
-
-        await self.write_saved(all)
-        return to_show
-
-    async def show_announcements(self) -> typing.Tuple[str, int]:
-        """显示公告"""
-        try:
-            announcements = await self.fetch_new()
-            ann_text = ''
-            for ann in announcements:
-                ann_text += f'[公告] {ann.time}: {ann.content}\n'
-
-            # TODO statistics
-
-            return ann_text, logging.INFO
-        except Exception as e:
-            return f'获取公告时出错: {e}', logging.WARNING

pkg/vector/mgr.py

@@ -1,30 +0,0 @@
-from __future__ import annotations
-
-from ..core import app
-from .vdb import VectorDatabase
-from .vdbs.chroma import ChromaVectorDatabase
-from .vdbs.qdrant import QdrantVectorDatabase
-
-
-class VectorDBManager:
-    ap: app.Application
-    vector_db: VectorDatabase = None
-
-    def __init__(self, ap: app.Application):
-        self.ap = ap
-
-    async def initialize(self):
-        kb_config = self.ap.instance_config.data.get('vdb')
-        if kb_config:
-            if kb_config.get('use') == 'chroma':
-                self.vector_db = ChromaVectorDatabase(self.ap)
-                self.ap.logger.info('Initialized Chroma vector database backend.')
-            elif kb_config.get('use') == 'qdrant':
-                self.vector_db = QdrantVectorDatabase(self.ap)
-                self.ap.logger.info('Initialized Qdrant vector database backend.')
-            else:
-                self.vector_db = ChromaVectorDatabase(self.ap)
-                self.ap.logger.warning('No valid vector database backend configured, defaulting to Chroma.')
-        else:
-            self.vector_db = ChromaVectorDatabase(self.ap)
-            self.ap.logger.warning('No vector database backend configured, defaulting to Chroma.')

pyproject.toml

@@ -1,9 +1,10 @@
 [project]
 name = "langbot"
-version = "4.3.5"
-description = "Easy-to-use global IM bot platform designed for LLM era"
+version = "4.8.3"
+description = "Production-grade platform for building agentic IM bots"
 readme = "README.md"
-requires-python = ">=3.10.1,<4.0"
+license-files = ["LICENSE"]
+requires-python = ">=3.11,<4.0"
 dependencies = [
     "aiocqhttp>=1.4.4",
     "aiofiles>=24.1.0",
@@ -16,13 +17,13 @@ dependencies = [
     "certifi>=2025.4.26",
     "colorlog~=6.6.0",
     "cryptography>=44.0.3",
-    "dashscope>=1.23.2",
+    "dashscope>=1.25.10",
     "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>=1.8.1",
+    "mcp>=1.25.0",
     "nakuru-project-idk>=0.0.2.1",
     "ollama>=0.4.8",
     "openai>1.0.0",
@@ -45,7 +46,6 @@ dependencies = [
     "urllib3>=2.4.0",
     "websockets>=15.0.1",
     "python-socks>=2.7.1", # dingtalk missing dependency
-    "taskgroup==0.0.0a4", # graingert/taskgroup#20
     "pip>=25.1.1",
     "ruff>=0.11.9",
     "pre-commit>=4.2.0",
@@ -60,12 +60,17 @@ dependencies = [
     "ebooklib>=0.18",
     "html2text>=2024.2.26",
     "langchain>=0.2.0",
+    "langchain-text-splitters>=0.0.1",
     "chromadb>=0.4.24",
     "qdrant-client (>=1.15.1,<2.0.0)",
-    "langbot-plugin==0.1.3",
+    "pyseekdb==1.0.0b7",
+    "langbot-plugin==0.2.5",
     "asyncpg>=0.30.0",
     "line-bot-sdk>=3.19.0",
     "tboxsdk>=0.0.10",
+    "boto3>=1.35.0",
+    "pymilvus>=2.6.4",
+    "pgvector>=0.4.1",
 ]
 keywords = [
     "bot",
@@ -83,11 +88,10 @@ keywords = [
     "onebot",
 ]
 classifiers = [
-    "Development Status :: 3 - Alpha",
+    "Development Status :: 5 - Production/Stable",
     "Framework :: AsyncIO",
     "Framework :: Robot Framework",
     "Framework :: Robot Framework :: Library",
-    "License :: OSI Approved :: AGPL-3 License",
     "Operating System :: OS Independent",
     "Programming Language :: Python :: 3",
     "Topic :: Communications :: Chat",
@@ -98,6 +102,16 @@ Homepage = "https://langbot.app"
 Documentation = "https://docs.langbot.app"
 Repository = "https://github.com/langbot-app/LangBot"
 
+[project.scripts]
+langbot = "langbot.__main__:main"
+
+[build-system]
+requires = ["setuptools>=61.0", "wheel"]
+build-backend = "setuptools.build_meta"
+
+[tool.setuptools]
+package-data = { "langbot" = ["templates/**", "pkg/provider/modelmgr/requesters/*", "pkg/platform/sources/*", "web/out/**"] }
+
 [dependency-groups]
 dev = [
     "pre-commit>=4.2.0",

pytest.ini

@@ -26,7 +26,7 @@ markers =
 
 # Coverage options (when using pytest-cov)
 [coverage:run]
-source = pkg
+source = langbot
 omit =
     */tests/*
     */test_*.py

run_tests.sh

@@ -22,7 +22,7 @@ echo "Running all unit tests..."
 
 # Run tests with coverage
 pytest tests/unit_tests/ -v --tb=short \
-    --cov=pkg \
+    --cov=langbot \
     --cov-report=xml \
     "$@"
 

src/langbot/__init__.py

@@ -0,0 +1,3 @@
+"""LangBot - Production-grade platform for building agentic IM bots"""
+
+__version__ = '4.8.3'

src/langbot/__main__.py

@@ -0,0 +1,104 @@
+"""LangBot entry point for package execution"""
+
+import asyncio
+import argparse
+import sys
+import os
+
+# ASCII art banner
+asciiart = r"""
+ _                   ___      _   
+| |   __ _ _ _  __ _| _ ) ___| |_ 
+| |__/ _` | ' \/ _` | _ \/ _ \  _|
+|____\__,_|_||_\__, |___/\___/\__|
+               |___/              
+
+⭐️ Open Source 开源地址: https://github.com/langbot-app/LangBot
+📖 Documentation 文档地址: https://docs.langbot.app
+"""
+
+
+async def main_entry(loop: asyncio.AbstractEventLoop):
+    """Main entry point for LangBot"""
+    parser = argparse.ArgumentParser(description='LangBot')
+    parser.add_argument(
+        '--standalone-runtime',
+        action='store_true',
+        help='Use standalone plugin runtime / 使用独立插件运行时',
+        default=False,
+    )
+    parser.add_argument('--debug', action='store_true', help='Debug mode / 调试模式', default=False)
+    args = parser.parse_args()
+
+    if args.standalone_runtime:
+        from langbot.pkg.utils import platform
+
+        platform.standalone_runtime = True
+
+    if args.debug:
+        from langbot.pkg.utils import constants
+
+        constants.debug_mode = True
+
+    print(asciiart)
+
+    # Check dependencies
+    from langbot.pkg.core.bootutils import deps
+
+    missing_deps = await deps.check_deps()
+
+    if missing_deps:
+        print('以下依赖包未安装，将自动安装，请完成后重启程序：')
+        print(
+            'These dependencies are missing, they will be installed automatically, please restart the program after completion:'
+        )
+        for dep in missing_deps:
+            print('-', dep)
+        await deps.install_deps(missing_deps)
+        print('已自动安装缺失的依赖包，请重启程序。')
+        print('The missing dependencies have been installed automatically, please restart the program.')
+        sys.exit(0)
+
+    # Check configuration files
+    from langbot.pkg.core.bootutils import files
+
+    generated_files = await files.generate_files()
+
+    if generated_files:
+        print('以下文件不存在，已自动生成：')
+        print('Following files do not exist and have been automatically generated:')
+        for file in generated_files:
+            print('-', file)
+
+    from langbot.pkg.core import boot
+
+    await boot.main(loop)
+
+
+def main():
+    """Main function to be called by console script entry point"""
+    # Check Python version
+    if sys.version_info < (3, 10, 1):
+        print('需要 Python 3.10.1 及以上版本，当前 Python 版本为：', sys.version)
+        print('Your Python version is not supported.')
+        print('Python 3.10.1 or higher is required. Current version:', sys.version)
+        sys.exit(1)
+
+    # Set up the working directory
+    # When installed as a package, we need to handle the working directory differently
+    # We'll create data directory in current working directory if not exists
+    os.makedirs('data', exist_ok=True)
+
+    loop = asyncio.new_event_loop()
+
+    try:
+        loop.run_until_complete(main_entry(loop))
+    except KeyboardInterrupt:
+        print('\n正在退出...')
+        print('Exiting...')
+    finally:
+        loop.close()
+
+
+if __name__ == '__main__':
+    main()

src/langbot/libs/coze_server_api/client.py

@@ -0,0 +1,177 @@
+import json
+import asyncio
+import aiohttp
+import io
+from typing import Dict, List, Any, AsyncGenerator
+import os
+from pathlib import Path
+
+
+class AsyncCozeAPIClient:
+    def __init__(self, api_key: str, api_base: str = 'https://api.coze.cn'):
+        self.api_key = api_key
+        self.api_base = api_base
+        self.session = None
+
+    async def __aenter__(self):
+        """支持异步上下文管理器"""
+        await self.coze_session()
+        return self
+
+    async def __aexit__(self, exc_type, exc_val, exc_tb):
+        """退出时自动关闭会话"""
+        await self.close()
+
+    async def coze_session(self):
+        """确保HTTP session存在"""
+        if self.session is None:
+            connector = aiohttp.TCPConnector(
+                ssl=False if self.api_base.startswith('http://') else True,
+                limit=100,
+                limit_per_host=30,
+                keepalive_timeout=30,
+                enable_cleanup_closed=True,
+            )
+            timeout = aiohttp.ClientTimeout(
+                total=120,  # 默认超时时间
+                connect=30,
+                sock_read=120,
+            )
+            headers = {
+                'Authorization': f'Bearer {self.api_key}',
+                'Accept': 'text/event-stream',
+            }
+            self.session = aiohttp.ClientSession(headers=headers, timeout=timeout, connector=connector)
+        return self.session
+
+    async def close(self):
+        """显式关闭会话"""
+        if self.session and not self.session.closed:
+            await self.session.close()
+            self.session = None
+
+    async def upload(
+        self,
+        file,
+    ) -> str:
+        # 处理 Path 对象
+        if isinstance(file, Path):
+            if not file.exists():
+                raise ValueError(f'File not found: {file}')
+            with open(file, 'rb') as f:
+                file = f.read()
+
+        # 处理文件路径字符串
+        elif isinstance(file, str):
+            if not os.path.isfile(file):
+                raise ValueError(f'File not found: {file}')
+            with open(file, 'rb') as f:
+                file = f.read()
+
+        # 处理文件对象
+        elif hasattr(file, 'read'):
+            file = file.read()
+
+        session = await self.coze_session()
+        url = f'{self.api_base}/v1/files/upload'
+
+        try:
+            file_io = io.BytesIO(file)
+            async with session.post(
+                url,
+                data={
+                    'file': file_io,
+                },
+                timeout=aiohttp.ClientTimeout(total=60),
+            ) as response:
+                if response.status == 401:
+                    raise Exception('Coze API 认证失败，请检查 API Key 是否正确')
+
+                response_text = await response.text()
+
+                if response.status != 200:
+                    raise Exception(f'文件上传失败，状态码: {response.status}, 响应: {response_text}')
+                try:
+                    result = await response.json()
+                except json.JSONDecodeError:
+                    raise Exception(f'文件上传响应解析失败: {response_text}')
+
+                if result.get('code') != 0:
+                    raise Exception(f'文件上传失败: {result.get("msg", "未知错误")}')
+
+                file_id = result['data']['id']
+                return file_id
+
+        except asyncio.TimeoutError:
+            raise Exception('文件上传超时')
+        except Exception as e:
+            raise Exception(f'文件上传失败: {str(e)}')
+
+    async def chat_messages(
+        self,
+        bot_id: str,
+        user_id: str,
+        additional_messages: List[Dict] | None = None,
+        conversation_id: str | None = None,
+        auto_save_history: bool = True,
+        stream: bool = True,
+        timeout: float = 120,
+    ) -> AsyncGenerator[Dict[str, Any], None]:
+        """发送聊天消息并返回流式响应
+
+        Args:
+            bot_id: Bot ID
+            user_id: 用户ID
+            additional_messages: 额外消息列表
+            conversation_id: 会话ID
+            auto_save_history: 是否自动保存历史
+            stream: 是否流式响应
+            timeout: 超时时间
+        """
+        session = await self.coze_session()
+        url = f'{self.api_base}/v3/chat'
+
+        payload = {
+            'bot_id': bot_id,
+            'user_id': user_id,
+            'stream': stream,
+            'auto_save_history': auto_save_history,
+        }
+
+        if additional_messages:
+            payload['additional_messages'] = additional_messages
+
+        params = {}
+        if conversation_id:
+            params['conversation_id'] = conversation_id
+
+        try:
+            async with session.post(
+                url,
+                json=payload,
+                params=params,
+                timeout=aiohttp.ClientTimeout(total=timeout),
+            ) as response:
+                if response.status == 401:
+                    raise Exception('Coze API 认证失败，请检查 API Key 是否正确')
+
+                if response.status != 200:
+                    raise Exception(f'Coze API 流式请求失败，状态码: {response.status}')
+
+                async for chunk in response.content:
+                    chunk = chunk.decode('utf-8')
+                    if chunk != '\n':
+                        if chunk.startswith('event:'):
+                            chunk_type = chunk.replace('event:', '', 1).strip()
+                        elif chunk.startswith('data:'):
+                            chunk_data = chunk.replace('data:', '', 1).strip()
+                    else:
+                        yield {
+                            'event': chunk_type,
+                            'data': json.loads(chunk_data) if chunk_data else {},
+                        }  # 处理本地部署时，接口返回的data为空值
+
+        except asyncio.TimeoutError:
+            raise Exception(f'Coze API 流式请求超时 ({timeout}秒)')
+        except Exception as e:
+            raise Exception(f'Coze API 流式请求失败: {str(e)}')

src/langbot/libs/dify_service_api/v1/client.py

@@ -5,6 +5,8 @@ import typing
 import json
 
 from .errors import DifyAPIError
+from pathlib import Path
+import os
 
 
 class AsyncDifyServiceClient:
@@ -30,6 +32,7 @@ class AsyncDifyServiceClient:
         conversation_id: str = '',
         files: list[dict[str, typing.Any]] = [],
         timeout: float = 30.0,
+        model_config: dict[str, typing.Any] | None = None,
     ) -> typing.AsyncGenerator[dict[str, typing.Any], None]:
         """发送消息"""
         if response_mode != 'streaming':
@@ -40,6 +43,16 @@ class AsyncDifyServiceClient:
             trust_env=True,
             timeout=timeout,
         ) as client:
+            payload = {
+                'inputs': inputs,
+                'query': query,
+                'user': user,
+                'response_mode': response_mode,
+                'conversation_id': conversation_id,
+                'files': files,
+                'model_config': model_config or {},
+            }
+
             async with client.stream(
                 'POST',
                 '/chat-messages',
@@ -47,14 +60,7 @@ class AsyncDifyServiceClient:
                     'Authorization': f'Bearer {self.api_key}',
                     'Content-Type': 'application/json',
                 },
-                json={
-                    'inputs': inputs,
-                    'query': query,
-                    'user': user,
-                    'response_mode': response_mode,
-                    'conversation_id': conversation_id,
-                    'files': files,
-                },
+                json=payload,
             ) as r:
                 async for chunk in r.aiter_lines():
                     if r.status_code != 200:
@@ -109,7 +115,23 @@ class AsyncDifyServiceClient:
         user: str,
         timeout: float = 30.0,
     ) -> str:
-        """上传文件"""
+        # 处理 Path 对象
+        if isinstance(file, Path):
+            if not file.exists():
+                raise ValueError(f'File not found: {file}')
+            with open(file, 'rb') as f:
+                file = f.read()
+
+        # 处理文件路径字符串
+        elif isinstance(file, str):
+            if not os.path.isfile(file):
+                raise ValueError(f'File not found: {file}')
+            with open(file, 'rb') as f:
+                file = f.read()
+
+        # 处理文件对象
+        elif hasattr(file, 'read'):
+            file = file.read()
         async with httpx.AsyncClient(
             base_url=self.base_url,
             trust_env=True,
@@ -121,6 +143,8 @@ class AsyncDifyServiceClient:
                 headers={'Authorization': f'Bearer {self.api_key}'},
                 files={
                     'file': file,
+                },
+                data={
                     'user': (None, user),
                 },
             )