docs: Add multilingual README files (Spanish, French, Korean, Russian, Vietnamese) (#1794)

* Initial plan

* Add multilingual README files (ES, FR, KO, RU, VI)

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

---------

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

.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

@@ -1,10 +1,9 @@
 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]
+  workflow_dispatch:
 jobs:
   publish-docker-image:
     runs-on: ubuntu-latest
@@ -41,5 +40,9 @@ jobs:
         run: docker login --username=${{ secrets.DOCKER_USERNAME }} --password ${{ secrets.DOCKER_PASSWORD }}
       - name: Create Buildx
         run: docker buildx create --name mybuilder --use
-      - name: Build  # image name: rockchin/langbot:<VERSION>
-        run: docker buildx build --platform linux/arm64,linux/amd64 -t rockchin/langbot:${{ steps.check_version.outputs.version }} -t rockchin/langbot:latest . --push
+      - name: Build for Release # only relase, exlude pre-release
+        if: ${{ github.event.release.prerelease == false }}
+        run: docker buildx build --platform linux/amd64 -t rockchin/langbot:${{ steps.check_version.outputs.version }} -t rockchin/langbot:latest . --push
+      - name: Build for Pre-release # no update for latest tag
+        if: ${{ github.event.release.prerelease == true }}
+        run: docker buildx build --platform linux/amd64 -t rockchin/langbot:${{ steps.check_version.outputs.version }} . --push

.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/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

@@ -44,5 +44,12 @@ test.py
 .venv/
 uv.lock
 /test
+plugins.bak
 coverage.xml
-.coverage
+.coverage
+src/langbot/web/
+
+# Build artifacts
+/dist
+/build
+*.egg-info

AGENTS.md

@@ -0,0 +1,86 @@
+# 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:
+
+- `./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.
+
+## 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

README.md

@@ -8,7 +8,7 @@
 
 <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)
+[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)
@@ -31,6 +31,16 @@ 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
 
 ## 📦 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 +71,10 @@ 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。
@@ -112,6 +126,7 @@ 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 +139,7 @@ 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 +162,9 @@ 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

@@ -5,7 +5,7 @@
 
 <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)
+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)
@@ -25,6 +25,16 @@ LangBot is an open-source LLM native instant messaging robot development platfor
 
 ## 📦 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 +65,10 @@ 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.
@@ -105,6 +119,7 @@ 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 +1,141 @@
+<p align="center">
+<a href="https://langbot.app">
+<img src="https://docs.langbot.app/social_en.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](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/guide.html">Despliegue</a> ｜
+<a href="https://docs.langbot.app/en/plugin/plugin-intro.html">Plugin</a> ｜
+<a href="https://github.com/langbot-app/LangBot/issues/new?assignees=&labels=%E7%8B%AC%E7%AB%8B%E6%8F%92%E4%BB%B6&projects=&template=submit-plugin.yml&title=%5BPlugin%5D%3A+%E8%AF%B7%E6%B1%82%E7%99%BB%E8%AE%B0%E6%96%B0%E6%8F%92%E4%BB%B6">Enviar Plugin</a>
+
+</div>
+
+</p>
+
+LangBot es una plataforma de desarrollo de robots de mensajería instantánea nativa de LLM de código abierto, con el objetivo de proporcionar una experiencia de desarrollo de robots de mensajería instantánea lista para usar, con funciones de aplicación LLM como Agent, RAG, MCP, adaptándose a plataformas de mensajería instantánea globales y proporcionando interfaces API ricas, compatible con desarrollo personalizado.
+
+## 📦 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
+
+- 💬 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).
+- 🤖 Soporte Multiplataforma: Actualmente compatible con QQ, QQ Channel, WeCom, WeChat personal, Lark, DingTalk, Discord, Telegram, etc.
+- 🛠️ Alta Estabilidad, Rico en Funciones: Control de acceso nativo, limitación de velocidad, filtrado de palabras sensibles, etc.; Fácil de usar, admite múltiples métodos de despliegue. Compatible con múltiples configuraciones de pipeline, diferentes bots para diferentes escenarios.
+- 🧩 Extensión de Plugin, Comunidad Activa: Compatible con mecanismos de plugin impulsados por eventos, extensión de componentes, etc.; Integración del protocolo [MCP](https://modelcontextprotocol.io/) de Anthropic; Actualmente cuenta con cientos de plugins.
+- 😻 Interfaz Web: Admite la gestión de instancias de LangBot a través del navegador. No es necesario escribir archivos de configuración manualmente.
+
+Para especificaciones más detalladas, consulte la [documentación](https://docs.langbot.app/en/insight/features.html).
+
+O visite el entorno de demostración: https://demo.langbot.dev/
+  - Información de inicio de sesión: Correo electrónico: `demo@langbot.app` Contraseña: `langbot123456`
+  - Nota: Solo para demostración de WebUI, por favor no ingrese información confidencial en el entorno público.
+
+### Plataformas de Mensajería
+
+| Plataforma | Estado | Observaciones |
+| --- | --- | --- |
+| Discord | ✅ |  |
+| Telegram | ✅ |  |
+| Slack | ✅ |  |
+| LINE | ✅ |  |
+| QQ Personal | ✅ |  |
+| QQ API Oficial | ✅ |  |
+| WeCom | ✅ |  |
+| WeComCS | ✅ |  |
+| WeCom AI Bot | ✅ |  |
+| WeChat Personal | ✅ |  |
+| Lark | ✅ |  |
+| DingTalk | ✅ |  |
+
+### 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 +1,141 @@
+<p align="center">
+<a href="https://langbot.app">
+<img src="https://docs.langbot.app/social_en.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](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/guide.html">Déploiement</a> ｜
+<a href="https://docs.langbot.app/en/plugin/plugin-intro.html">Plugin</a> ｜
+<a href="https://github.com/langbot-app/LangBot/issues/new?assignees=&labels=%E7%8B%AC%E7%AB%8B%E6%8F%92%E4%BB%B6&projects=&template=submit-plugin.yml&title=%5BPlugin%5D%3A+%E8%AF%B7%E6%B1%82%E7%99%BB%E8%AE%B0%E6%96%B0%E6%8F%92%E4%BB%B6">Soumettre un Plugin</a>
+
+</div>
+
+</p>
+
+LangBot est une plateforme de développement de robots de messagerie instantanée native LLM open source, visant à fournir une expérience de développement de robots de messagerie instantanée prête à l'emploi, avec des fonctionnalités d'application LLM telles qu'Agent, RAG, MCP, s'adaptant aux plateformes de messagerie instantanée mondiales et fournissant des interfaces API riches, prenant en charge le développement personnalisé.
+
+## 📦 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
+
+- 💬 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).
+- 🤖 Support Multi-plateforme : Actuellement compatible avec QQ, QQ Channel, WeCom, WeChat personnel, Lark, DingTalk, Discord, Telegram, etc.
+- 🛠️ Haute Stabilité, Riche en Fonctionnalités : Contrôle d'accès natif, limitation de débit, filtrage de mots sensibles, etc. ; Facile à utiliser, prend en charge plusieurs méthodes de déploiement. Prend en charge plusieurs configurations de pipeline, différents bots pour différents scénarios.
+- 🧩 Extension de Plugin, Communauté Active : Prend en charge les mécanismes de plugin pilotés par événements, l'extension de composants, etc. ; Intégration du protocole [MCP](https://modelcontextprotocol.io/) d'Anthropic ; Dispose actuellement de centaines de plugins.
+- 😻 Interface Web : Prend en charge la gestion des instances LangBot via le navigateur. Pas besoin d'écrire manuellement les fichiers de configuration.
+
+Pour des spécifications plus détaillées, veuillez consulter la [documentation](https://docs.langbot.app/en/insight/features.html).
+
+Ou visitez l'environnement de démonstration : https://demo.langbot.dev/
+  - Informations de connexion : Email : `demo@langbot.app` Mot de passe : `langbot123456`
+  - Note : Pour la démonstration WebUI uniquement, veuillez ne pas entrer d'informations sensibles dans l'environnement public.
+
+### Plateformes de Messagerie
+
+| Plateforme | Statut | Remarques |
+| --- | --- | --- |
+| Discord | ✅ |  |
+| Telegram | ✅ |  |
+| Slack | ✅ |  |
+| LINE | ✅ |  |
+| QQ Personnel | ✅ |  |
+| API Officielle QQ | ✅ |  |
+| WeCom | ✅ |  |
+| WeComCS | ✅ |  |
+| WeCom AI Bot | ✅ |  |
+| WeChat Personnel | ✅ |  |
+| Lark | ✅ |  |
+| DingTalk | ✅ |  |
+
+### 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

@@ -5,7 +5,7 @@
 
 <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)
+[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)
@@ -25,6 +25,16 @@ LangBot は、エージェント、RAG、MCP などの LLM アプリケーショ
 
 ## 📦 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 +65,10 @@ 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。
@@ -104,6 +118,7 @@ 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 +1,141 @@
+<p align="center">
+<a href="https://langbot.app">
+<img src="https://docs.langbot.app/social_en.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](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/guide.html">배포</a> ｜
+<a href="https://docs.langbot.app/en/plugin/plugin-intro.html">플러그인</a> ｜
+<a href="https://github.com/langbot-app/LangBot/issues/new?assignees=&labels=%E7%8B%AC%E7%AB%8B%E6%8F%92%E4%BB%B6&projects=&template=submit-plugin.yml&title=%5BPlugin%5D%3A+%E8%AF%B7%E6%B1%82%E7%99%BB%E8%AE%B0%E6%96%B0%E6%8F%92%E4%BB%B6">플러그인 제출</a>
+
+</div>
+
+</p>
+
+LangBot은 오픈 소스 LLM 네이티브 인스턴트 메시징 로봇 개발 플랫폼으로, Agent, RAG, MCP 등 다양한 LLM 애플리케이션 기능을 갖춘 즉시 사용 가능한 IM 로봇 개발 경험을 제공하며, 글로벌 인스턴트 메시징 플랫폼에 적응하고 풍부한 API 인터페이스를 제공하여 맞춤형 개발을 지원합니다.
+
+## 📦 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
+
+- 💬 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)와 깊이 통합됩니다.
+- 🤖 다중 플랫폼 지원: 현재 QQ, QQ Channel, WeCom, 개인 WeChat, Lark, DingTalk, Discord, Telegram 등을 지원합니다.
+- 🛠️ 높은 안정성, 풍부한 기능: 네이티브 액세스 제어, 속도 제한, 민감한 단어 필터링 등의 메커니즘; 사용하기 쉽고 여러 배포 방법을 지원합니다. 여러 파이프라인 구성을 지원하며 다양한 시나리오에 대해 다른 봇을 사용할 수 있습니다.
+- 🧩 플러그인 확장, 활발한 커뮤니티: 이벤트 기반, 컴포넌트 확장 등의 플러그인 메커니즘을 지원; Anthropic [MCP 프로토콜](https://modelcontextprotocol.io/) 통합; 현재 수백 개의 플러그인이 있습니다.
+- 😻 웹 UI: 브라우저를 통해 LangBot 인스턴스 관리를 지원합니다. 구성 파일을 수동으로 작성할 필요가 없습니다.
+
+더 자세한 사양은 [문서](https://docs.langbot.app/en/insight/features.html)를 참조하세요.
+
+또는 데모 환경을 방문하세요: https://demo.langbot.dev/
+  - 로그인 정보: 이메일: `demo@langbot.app` 비밀번호: `langbot123456`
+  - 참고: WebUI 데모 전용이므로 공개 환경에서는 민감한 정보를 입력하지 마세요.
+
+### 메시징 플랫폼
+
+| 플랫폼 | 상태 | 비고 |
+| --- | --- | --- |
+| Discord | ✅ |  |
+| Telegram | ✅ |  |
+| Slack | ✅ |  |
+| LINE | ✅ |  |
+| 개인 QQ | ✅ |  |
+| QQ 공식 API | ✅ |  |
+| WeCom | ✅ |  |
+| WeComCS | ✅ |  |
+| WeCom AI Bot | ✅ |  |
+| 개인 WeChat | ✅ |  |
+| 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 +1,141 @@
+<p align="center">
+<a href="https://langbot.app">
+<img src="https://docs.langbot.app/social_en.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](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/guide.html">Развертывание</a> ｜
+<a href="https://docs.langbot.app/en/plugin/plugin-intro.html">Плагин</a> ｜
+<a href="https://github.com/langbot-app/LangBot/issues/new?assignees=&labels=%E7%8B%AC%E7%AB%8B%E6%8F%92%E4%BB%B6&projects=&template=submit-plugin.yml&title=%5BPlugin%5D%3A+%E8%AF%B7%E6%B1%82%E7%99%BB%E8%AE%B0%E6%96%B0%E6%8F%92%E4%BB%B6">Отправить плагин</a>
+
+</div>
+
+</p>
+
+LangBot — это платформа разработки ботов для мгновенных сообщений на основе LLM с открытым исходным кодом, целью которой является предоставление готового к использованию опыта разработки ботов для IM, с функциями приложений LLM, такими как Agent, RAG, MCP, адаптацией к глобальным платформам мгновенных сообщений и предоставлением богатых API-интерфейсов, поддерживающих пользовательскую разработку.
+
+## 📦 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
+
+- 💬 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).
+- 🤖 Многоплатформенная поддержка: В настоящее время поддерживает QQ, QQ Channel, WeCom, личный WeChat, Lark, DingTalk, Discord, Telegram и т.д.
+- 🛠️ Высокая стабильность, богатство функций: Нативный контроль доступа, ограничение скорости, фильтрация чувствительных слов и т.д.; Простота в использовании, поддержка нескольких методов развертывания. Поддержка нескольких конфигураций конвейера, разные боты для разных сценариев.
+- 🧩 Расширение плагинов, активное сообщество: Поддержка механизмов плагинов, управляемых событиями, расширения компонентов и т.д.; Интеграция протокола [MCP](https://modelcontextprotocol.io/) от Anthropic; В настоящее время сотни плагинов.
+- 😻 Веб-интерфейс: Поддержка управления экземплярами LangBot через браузер. Нет необходимости вручную писать конфигурационные файлы.
+
+Для более подробных спецификаций обратитесь к [документации](https://docs.langbot.app/en/insight/features.html).
+
+Или посетите демонстрационную среду: https://demo.langbot.dev/
+  - Информация для входа: Email: `demo@langbot.app` Пароль: `langbot123456`
+  - Примечание: Только для демонстрации WebUI, пожалуйста, не вводите конфиденциальную информацию в общедоступной среде.
+
+### Платформы обмена сообщениями
+
+| Платформа | Статус | Примечания |
+| --- | --- | --- |
+| Discord | ✅ |  |
+| Telegram | ✅ |  |
+| Slack | ✅ |  |
+| LINE | ✅ |  |
+| Личный QQ | ✅ |  |
+| Официальный API QQ | ✅ |  |
+| WeCom | ✅ |  |
+| WeComCS | ✅ |  |
+| WeCom AI Bot | ✅ |  |
+| Личный WeChat | ✅ |  |
+| 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

@@ -5,7 +5,7 @@
 
 <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)
+[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)
@@ -27,6 +27,16 @@ 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
 
 ## 📦 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 +67,10 @@ 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。
@@ -107,6 +121,7 @@ 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 +1,141 @@
+<p align="center">
+<a href="https://langbot.app">
+<img src="https://docs.langbot.app/social_en.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](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/guide.html">Triển khai</a> ｜
+<a href="https://docs.langbot.app/en/plugin/plugin-intro.html">Plugin</a> ｜
+<a href="https://github.com/langbot-app/LangBot/issues/new?assignees=&labels=%E7%8B%AC%E7%AB%8B%E6%8F%92%E4%BB%B6&projects=&template=submit-plugin.yml&title=%5BPlugin%5D%3A+%E8%AF%B7%E6%B1%82%E7%99%BB%E8%AE%B0%E6%96%B0%E6%8F%92%E4%BB%B6">Gửi Plugin</a>
+
+</div>
+
+</p>
+
+LangBot là một nền tảng phát triển robot nhắn tin tức thời gốc LLM mã nguồn mở, nhằm mục đích cung cấp trải nghiệm phát triển robot IM sẵn sàng sử dụng, với các chức năng ứng dụng LLM như Agent, RAG, MCP, thích ứng với các nền tảng nhắn tin tức thời toàn cầu và cung cấp giao diện API phong phú, hỗ trợ phát triển tùy chỉnh.
+
+## 📦 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
+
+- 💬 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).
+- 🤖 Hỗ trợ Đa nền tảng: Hiện hỗ trợ QQ, QQ Channel, WeCom, WeChat cá nhân, Lark, DingTalk, Discord, Telegram, v.v.
+- 🛠️ Độ ổn định Cao, Tính năng Phong phú: Kiểm soát truy cập gốc, giới hạn tốc độ, lọc từ nhạy cảm, v.v.; Dễ sử dụng, hỗ trợ nhiều phương pháp triển khai. Hỗ trợ nhiều cấu hình pipeline, các bot khác nhau cho các kịch bản khác nhau.
+- 🧩 Mở rộng Plugin, Cộng đồng Hoạt động: Hỗ trợ các cơ chế plugin hướng sự kiện, mở rộng thành phần, v.v.; Tích hợp giao thức [MCP](https://modelcontextprotocol.io/) của Anthropic; Hiện có hàng trăm plugin.
+- 😻 Giao diện Web: Hỗ trợ quản lý các phiên bản LangBot thông qua trình duyệt. Không cần viết tệp cấu hình thủ công.
+
+Để biết thêm thông số kỹ thuật chi tiết, vui lòng tham khảo [tài liệu](https://docs.langbot.app/en/insight/features.html).
+
+Hoặc truy cập môi trường demo: https://demo.langbot.dev/
+  - Thông tin đăng nhập: Email: `demo@langbot.app` Mật khẩu: `langbot123456`
+  - Lưu ý: Chỉ dành cho demo WebUI, vui lòng không nhập bất kỳ thông tin nhạy cảm nào trong môi trường công cộng.
+
+### Nền tảng Nhắn tin
+
+| Nền tảng | Trạng thái | Ghi chú |
+| --- | --- | --- |
+| Discord | ✅ |  |
+| Telegram | ✅ |  |
+| Slack | ✅ |  |
+| LINE | ✅ |  |
+| QQ Cá nhân | ✅ |  |
+| QQ API Chính thức | ✅ |  |
+| WeCom | ✅ |  |
+| WeComCS | ✅ |  |
+| WeCom AI Bot | ✅ |  |
+| WeChat Cá nhân | ✅ |  |
+| 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:
@@ -5,6 +7,7 @@ services:
   langbot_plugin_runtime:
     image: rockchin/langbot:latest
     container_name: langbot_plugin_runtime
+    platform: linux/amd64 # For Apple Silicon compatibility
     volumes:
       - ./data/plugins:/app/data/plugins
     ports:
@@ -19,6 +22,7 @@ services:
   langbot:
     image: rockchin/langbot:latest
     container_name: langbot
+    platform: linux/amd64 # For Apple Silicon compatibility
     volumes:
       - ./data:/app/data
       - ./plugins:/app/plugins

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/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.

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)
-
-                
-    
-            
-

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/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/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/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/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/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

pyproject.toml

@@ -1,8 +1,9 @@
 [project]
 name = "langbot"
-version = "4.3.5"
+version = "4.5.4"
 description = "Easy-to-use global IM bot platform designed for LLM era"
 readme = "README.md"
+license-files = ["LICENSE"]
 requires-python = ">=3.10.1,<4.0"
 dependencies = [
     "aiocqhttp>=1.4.4",
@@ -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 +60,14 @@ 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",
+    "langbot-plugin==0.1.12",
     "asyncpg>=0.30.0",
     "line-bot-sdk>=3.19.0",
     "tboxsdk>=0.0.10",
+    "boto3>=1.35.0",
 ]
 keywords = [
     "bot",
@@ -83,11 +85,10 @@ 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 +99,16 @@ 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.pkg
 omit =
     */tests/*
     */test_*.py

src/langbot/__init__.py

@@ -0,0 +1,3 @@
+"""LangBot - Easy-to-use global IM bot platform designed for LLM era"""
+
+__version__ = '4.5.4'

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:
@@ -109,7 +111,23 @@ 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 +139,8 @@ class AsyncDifyServiceClient:
                 headers={'Authorization': f'Bearer {self.api_key}'},
                 files={
                     'file': file,
+                },
+                data={
                     'user': (None, user),
                 },
             )

src/langbot/libs/dingtalk_api/api.py

@@ -188,12 +188,69 @@ class DingTalkClient:
 
             if incoming_message.message_type == 'richText':
                 data = incoming_message.rich_text_content.to_dict()
+
+                # 使用统一的结构化数据格式，保持顺序
+                rich_content = {
+                    'Type': 'richText',
+                    'Elements': [],  # 按顺序存储所有元素
+                    'SimpleContent': '',  # 兼容字段：纯文本内容
+                    'SimplePicture': '',  # 兼容字段：第一张图片
+                }
+
+                # 先收集所有文本和图片占位符
+                text_elements = []
+
+                # 解析富文本内容，保持原始顺序
                 for item in data['richText']:
-                    if 'text' in item:
-                        message_data['Content'] = item['text']
-                    if incoming_message.get_image_list()[0]:
-                        message_data['Picture'] = await self.download_image(incoming_message.get_image_list()[0])
-                message_data['Type'] = 'text'
+                    # 处理文本内容
+                    if 'text' in item and item['text'] != '\n':
+                        element = {'Type': 'text', 'Content': item['text']}
+                        rich_content['Elements'].append(element)
+                        text_elements.append(item['text'])
+
+                    # 检查是否是图片元素 - 根据钉钉API的实际结构调整
+                    # 钉钉富文本中的图片通常有特定标识，可能需要根据实际返回调整
+                    elif item.get('type') == 'picture':
+                        # 创建图片占位符
+                        element = {
+                            'Type': 'image_placeholder',
+                        }
+                        rich_content['Elements'].append(element)
+
+                # 获取并下载所有图片
+                image_list = incoming_message.get_image_list()
+                if image_list:
+                    new_elements = []
+                    image_index = 0
+
+                    for element in rich_content['Elements']:
+                        if element['Type'] == 'image_placeholder':
+                            if image_index < len(image_list) and image_list[image_index]:
+                                image_url = await self.download_image(image_list[image_index])
+                                new_elements.append({'Type': 'image', 'Picture': image_url})
+                                image_index += 1
+                            else:
+                                # 如果没有对应的图片，保留占位符或跳过
+                                continue
+                        else:
+                            new_elements.append(element)
+
+                    rich_content['Elements'] = new_elements
+
+                # 设置兼容字段
+                all_texts = [elem['Content'] for elem in rich_content['Elements'] if elem.get('Type') == 'text']
+                rich_content['SimpleContent'] = '\n'.join(all_texts) if all_texts else ''
+
+                all_images = [elem['Picture'] for elem in rich_content['Elements'] if elem.get('Type') == 'image']
+                if all_images:
+                    rich_content['SimplePicture'] = all_images[0]
+                    rich_content['AllImages'] = all_images  # 所有图片的列表
+
+                # 设置原始的 content 和 picture 字段以保持兼容
+                message_data['Content'] = rich_content['SimpleContent']
+                message_data['Rich_Content'] = rich_content
+                if all_images:
+                    message_data['Picture'] = all_images[0]
 
             elif incoming_message.message_type == 'text':
                 message_data['Content'] = incoming_message.get_text_list()[0]

src/langbot/libs/dingtalk_api/dingtalkevent.py

@@ -15,6 +15,10 @@ class DingTalkEvent(dict):
     def content(self):
         return self.get('Content', '')
 
+    @property
+    def rich_content(self):
+        return self.get('Rich_Content', '')
+
     @property
     def incoming_message(self) -> Optional['dingtalk_stream.chatbot.ChatbotMessage']:
         return self.get('IncomingMessage')
@@ -39,7 +43,6 @@ class DingTalkEvent(dict):
     def name(self):
         return self.get('Name', '')
 
-
     @property
     def conversation(self):
         return self.get('conversation_type', '')

src/langbot/libs/official_account_api/api.py

@@ -1,12 +1,12 @@
 # 微信公众号的加解密算法与企业微信一样，所以直接使用企业微信的加解密算法文件
 import time
 import traceback
-from libs.wecom_api.WXBizMsgCrypt3 import WXBizMsgCrypt
+from langbot.libs.wecom_api.WXBizMsgCrypt3 import WXBizMsgCrypt
 import xml.etree.ElementTree as ET
 from quart import Quart, request
 import hashlib
 from typing import Callable
-from .oaevent import OAEvent
+from langbot.libs.official_account_api.oaevent import OAEvent
 
 import asyncio
 

src/langbot/libs/wechatpad_api/api/chatroom.py

@@ -1,4 +1,4 @@
-from libs.wechatpad_api.util.http_util import post_json
+from langbot.libs.wechatpad_api.util.http_util import post_json
 
 
 class ChatRoomApi:

src/langbot/libs/wechatpad_api/api/downloadpai.py

@@ -1,4 +1,4 @@
-from libs.wechatpad_api.util.http_util import post_json
+from langbot.libs.wechatpad_api.util.http_util import post_json
 import httpx
 import base64
 

src/langbot/libs/wechatpad_api/api/login.py

@@ -1,4 +1,4 @@
-from libs.wechatpad_api.util.http_util import post_json, get_json
+from langbot.libs.wechatpad_api.util.http_util import post_json, get_json
 
 
 class LoginApi:

src/langbot/libs/wechatpad_api/api/message.py

@@ -1,4 +1,4 @@
-from libs.wechatpad_api.util.http_util import post_json
+from langbot.libs.wechatpad_api.util.http_util import post_json
 
 
 class MessageApi:

src/langbot/libs/wechatpad_api/api/user.py

@@ -1,4 +1,4 @@
-from libs.wechatpad_api.util.http_util import post_json, async_request, get_json
+from langbot.libs.wechatpad_api.util.http_util import post_json, async_request, get_json
 
 
 class UserApi:

src/langbot/libs/wechatpad_api/client.py

@@ -1,9 +1,9 @@
-from libs.wechatpad_api.api.login import LoginApi
-from libs.wechatpad_api.api.friend import FriendApi
-from libs.wechatpad_api.api.message import MessageApi
-from libs.wechatpad_api.api.user import UserApi
-from libs.wechatpad_api.api.downloadpai import DownloadApi
-from libs.wechatpad_api.api.chatroom import ChatRoomApi
+from langbot.libs.wechatpad_api.api.login import LoginApi
+from langbot.libs.wechatpad_api.api.friend import FriendApi
+from langbot.libs.wechatpad_api.api.message import MessageApi
+from langbot.libs.wechatpad_api.api.user import UserApi
+from langbot.libs.wechatpad_api.api.downloadpai import DownloadApi
+from langbot.libs.wechatpad_api.api.chatroom import ChatRoomApi
 
 
 class WeChatPadClient:

src/langbot/libs/wecom_ai_bot_api/WXBizMsgCrypt3.py

@@ -16,7 +16,7 @@ import struct
 from Crypto.Cipher import AES
 import xml.etree.cElementTree as ET
 import socket
-from libs.wecom_ai_bot_api import ierror
+from langbot.libs.wecom_ai_bot_api import ierror
 
 
 """

src/langbot/libs/wecom_ai_bot_api/api.py

@@ -0,0 +1,587 @@
+import asyncio
+import base64
+import json
+import time
+import traceback
+import uuid
+import xml.etree.ElementTree as ET
+from dataclasses import dataclass, field
+from typing import Any, Callable, Optional
+from urllib.parse import unquote
+
+import httpx
+from Crypto.Cipher import AES
+from quart import Quart, request, Response, jsonify
+
+from langbot.libs.wecom_ai_bot_api import wecombotevent
+from langbot.libs.wecom_ai_bot_api.WXBizMsgCrypt3 import WXBizMsgCrypt
+from langbot.pkg.platform.logger import EventLogger
+
+
+@dataclass
+class StreamChunk:
+    """描述单次推送给企业微信的流式片段。"""
+
+    # 需要返回给企业微信的文本内容
+    content: str
+
+    # 标记是否为最终片段，对应企业微信协议里的 finish 字段
+    is_final: bool = False
+
+    # 预留额外元信息，未来支持多模态扩展时可使用
+    meta: dict[str, Any] = field(default_factory=dict)
+
+
+@dataclass
+class StreamSession:
+    """维护一次企业微信流式会话的上下文。"""
+
+    # 企业微信要求的 stream_id，用于标识后续刷新请求
+    stream_id: str
+
+    # 原始消息的 msgid，便于与流水线消息对应
+    msg_id: str
+
+    # 群聊会话标识（单聊时为空）
+    chat_id: Optional[str]
+
+    # 触发消息的发送者
+    user_id: Optional[str]
+
+    # 会话创建时间
+    created_at: float = field(default_factory=time.time)
+
+    # 最近一次被访问的时间，cleanup 依据该值判断过期
+    last_access: float = field(default_factory=time.time)
+
+    # 将流水线增量结果缓存到队列，刷新请求逐条消费
+    queue: asyncio.Queue = field(default_factory=asyncio.Queue)
+
+    # 是否已经完成（收到最终片段）
+    finished: bool = False
+
+    # 缓存最近一次片段，处理重试或超时兜底
+    last_chunk: Optional[StreamChunk] = None
+
+
+class StreamSessionManager:
+    """管理 stream 会话的生命周期，并负责队列的生产消费。"""
+
+    def __init__(self, logger: EventLogger, ttl: int = 60) -> None:
+        self.logger = logger
+
+        self.ttl = ttl  # 超时时间（秒），超过该时间未被访问的会话会被清理由 cleanup
+        self._sessions: dict[str, StreamSession] = {}  # stream_id -> StreamSession 映射
+        self._msg_index: dict[str, str] = {}  # msgid -> stream_id 映射，便于流水线根据消息 ID 找到会话
+
+    def get_stream_id_by_msg(self, msg_id: str) -> Optional[str]:
+        if not msg_id:
+            return None
+        return self._msg_index.get(msg_id)
+
+    def get_session(self, stream_id: str) -> Optional[StreamSession]:
+        return self._sessions.get(stream_id)
+
+    def create_or_get(self, msg_json: dict[str, Any]) -> tuple[StreamSession, bool]:
+        """根据企业微信回调创建或获取会话。
+
+        Args:
+            msg_json: 企业微信解密后的回调 JSON。
+
+        Returns:
+            Tuple[StreamSession, bool]: `StreamSession` 为会话实例，`bool` 指示是否为新建会话。
+
+        Example:
+            在首次回调中调用，得到 `is_new=True` 后再触发流水线。
+        """
+        msg_id = msg_json.get('msgid', '')
+        if msg_id and msg_id in self._msg_index:
+            stream_id = self._msg_index[msg_id]
+            session = self._sessions.get(stream_id)
+            if session:
+                session.last_access = time.time()
+                return session, False
+
+        stream_id = str(uuid.uuid4())
+        session = StreamSession(
+            stream_id=stream_id,
+            msg_id=msg_id,
+            chat_id=msg_json.get('chatid'),
+            user_id=msg_json.get('from', {}).get('userid'),
+        )
+
+        if msg_id:
+            self._msg_index[msg_id] = stream_id
+        self._sessions[stream_id] = session
+        return session, True
+
+    async def publish(self, stream_id: str, chunk: StreamChunk) -> bool:
+        """向 stream 队列写入新的增量片段。
+
+        Args:
+            stream_id: 企业微信分配的流式会话 ID。
+            chunk: 待发送的增量片段。
+
+        Returns:
+            bool: 当流式队列存在并成功入队时返回 True。
+
+        Example:
+            在收到模型增量后调用 `await manager.publish('sid', StreamChunk('hello'))`。
+        """
+        session = self._sessions.get(stream_id)
+        if not session:
+            return False
+
+        session.last_access = time.time()
+        session.last_chunk = chunk
+
+        try:
+            session.queue.put_nowait(chunk)
+        except asyncio.QueueFull:
+            # 默认无界队列，此处兜底防御
+            await session.queue.put(chunk)
+
+        if chunk.is_final:
+            session.finished = True
+
+        return True
+
+    async def consume(self, stream_id: str, timeout: float = 0.5) -> Optional[StreamChunk]:
+        """从队列中取出一个片段，若超时返回 None。
+
+        Args:
+            stream_id: 企业微信流式会话 ID。
+            timeout: 取片段的最长等待时间（秒）。
+
+        Returns:
+            Optional[StreamChunk]: 成功时返回片段，超时或会话不存在时返回 None。
+
+        Example:
+            企业微信刷新到达时调用，若队列有数据则立即返回 `StreamChunk`。
+        """
+        session = self._sessions.get(stream_id)
+        if not session:
+            return None
+
+        session.last_access = time.time()
+
+        try:
+            chunk = await asyncio.wait_for(session.queue.get(), timeout)
+            session.last_access = time.time()
+            if chunk.is_final:
+                session.finished = True
+            return chunk
+        except asyncio.TimeoutError:
+            if session.finished and session.last_chunk:
+                return session.last_chunk
+            return None
+
+    def mark_finished(self, stream_id: str) -> None:
+        session = self._sessions.get(stream_id)
+        if session:
+            session.finished = True
+            session.last_access = time.time()
+
+    def cleanup(self) -> None:
+        """定期清理过期会话，防止队列与映射无上限累积。"""
+        now = time.time()
+        expired: list[str] = []
+        for stream_id, session in self._sessions.items():
+            if now - session.last_access > self.ttl:
+                expired.append(stream_id)
+
+        for stream_id in expired:
+            session = self._sessions.pop(stream_id, None)
+            if not session:
+                continue
+            msg_id = session.msg_id
+            if msg_id and self._msg_index.get(msg_id) == stream_id:
+                self._msg_index.pop(msg_id, None)
+
+
+class WecomBotClient:
+    def __init__(self, Token: str, EnCodingAESKey: str, Corpid: str, logger: EventLogger):
+        """企业微信智能机器人客户端。
+
+        Args:
+            Token: 企业微信回调验证使用的 token。
+            EnCodingAESKey: 企业微信消息加解密密钥。
+            Corpid: 企业 ID。
+            logger: 日志记录器。
+
+        Example:
+            >>> client = WecomBotClient(Token='token', EnCodingAESKey='aeskey', Corpid='corp', logger=logger)
+        """
+
+        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.logger = logger
+        self.generated_content: dict[str, str] = {}
+        self.msg_id_map: dict[str, int] = {}
+        self.stream_sessions = StreamSessionManager(logger=logger)
+        self.stream_poll_timeout = 0.5
+
+    @staticmethod
+    def _build_stream_payload(stream_id: str, content: str, finish: bool) -> dict[str, Any]:
+        """按照企业微信协议拼装返回报文。
+
+        Args:
+            stream_id: 企业微信会话 ID。
+            content: 推送的文本内容。
+            finish: 是否为最终片段。
+
+        Returns:
+            dict[str, Any]: 可直接加密返回的 payload。
+
+        Example:
+            组装 `{'msgtype': 'stream', 'stream': {'id': 'sid', ...}}` 结构。
+        """
+        return {
+            'msgtype': 'stream',
+            'stream': {
+                'id': stream_id,
+                'finish': finish,
+                'content': content,
+            },
+        }
+
+    async def _encrypt_and_reply(self, payload: dict[str, Any], nonce: str) -> tuple[Response, int]:
+        """对响应进行加密封装并返回给企业微信。
+
+        Args:
+            payload: 待加密的响应内容。
+            nonce: 企业微信回调参数中的 nonce。
+
+        Returns:
+            Tuple[Response, int]: Quart Response 对象及状态码。
+
+        Example:
+            在首包或刷新场景中调用以生成加密响应。
+        """
+        reply_plain_str = json.dumps(payload, 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(f'加密失败: {ret}')
+            return jsonify({'error': 'encrypt_failed'}), 500
+
+        root = ET.fromstring(encrypt_text)
+        encrypt = root.find('Encrypt').text
+        resp = {
+            'encrypt': encrypt,
+        }
+        return jsonify(resp), 200
+
+    async def _dispatch_event(self, event: wecombotevent.WecomBotEvent) -> None:
+        """异步触发流水线处理，避免阻塞首包响应。
+
+        Args:
+            event: 由企业微信消息转换的内部事件对象。
+        """
+        try:
+            await self._handle_message(event)
+        except Exception:
+            await self.logger.error(traceback.format_exc())
+
+    async def _handle_post_initial_response(self, msg_json: dict[str, Any], nonce: str) -> tuple[Response, int]:
+        """处理企业微信首次推送的消息，返回 stream_id 并开启流水线。
+
+        Args:
+            msg_json: 解密后的企业微信消息 JSON。
+            nonce: 企业微信回调参数 nonce。
+
+        Returns:
+            Tuple[Response, int]: Quart Response 及状态码。
+
+        Example:
+            首次回调时调用，立即返回带 `stream_id` 的响应。
+        """
+        session, is_new = self.stream_sessions.create_or_get(msg_json)
+
+        message_data = await self.get_message(msg_json)
+        if message_data:
+            message_data['stream_id'] = session.stream_id
+            try:
+                event = wecombotevent.WecomBotEvent(message_data)
+            except Exception:
+                await self.logger.error(traceback.format_exc())
+            else:
+                if is_new:
+                    asyncio.create_task(self._dispatch_event(event))
+
+        payload = self._build_stream_payload(session.stream_id, '', False)
+        return await self._encrypt_and_reply(payload, nonce)
+
+    async def _handle_post_followup_response(self, msg_json: dict[str, Any], nonce: str) -> tuple[Response, int]:
+        """处理企业微信的流式刷新请求，按需返回增量片段。
+
+        Args:
+            msg_json: 解密后的企业微信刷新请求。
+            nonce: 企业微信回调参数 nonce。
+
+        Returns:
+            Tuple[Response, int]: Quart Response 及状态码。
+
+        Example:
+            在刷新请求中调用，按需返回增量片段。
+        """
+        stream_info = msg_json.get('stream', {})
+        stream_id = stream_info.get('id', '')
+        if not stream_id:
+            await self.logger.error('刷新请求缺少 stream.id')
+            return await self._encrypt_and_reply(self._build_stream_payload('', '', True), nonce)
+
+        session = self.stream_sessions.get_session(stream_id)
+        chunk = await self.stream_sessions.consume(stream_id, timeout=self.stream_poll_timeout)
+
+        if not chunk:
+            cached_content = None
+            if session and session.msg_id:
+                cached_content = self.generated_content.pop(session.msg_id, None)
+            if cached_content is not None:
+                chunk = StreamChunk(content=cached_content, is_final=True)
+            else:
+                payload = self._build_stream_payload(stream_id, '', False)
+                return await self._encrypt_and_reply(payload, nonce)
+
+        payload = self._build_stream_payload(stream_id, chunk.content, chunk.is_final)
+        if chunk.is_final:
+            self.stream_sessions.mark_finished(stream_id)
+        return await self._encrypt_and_reply(payload, nonce)
+
+    async def handle_callback_request(self):
+        """企业微信回调入口。
+
+        Returns:
+            Quart Response: 根据请求类型返回验证、首包或刷新结果。
+
+        Example:
+            作为 Quart 路由处理函数直接注册并使用。
+        """
+        try:
+            self.wxcpt = WXBizMsgCrypt(self.Token, self.EnCodingAESKey, '')
+            await self.logger.info(f'{request.method} {request.url} {str(request.args)}')
+
+            if request.method == 'GET':
+                return await self._handle_get_callback()
+
+            if request.method == 'POST':
+                return await self._handle_post_callback()
+
+            return Response('', status=405)
+
+        except Exception:
+            await self.logger.error(traceback.format_exc())
+            return Response('Internal Server Error', status=500)
+
+    async def _handle_get_callback(self) -> tuple[Response, int] | Response:
+        """处理企业微信的 GET 验证请求。"""
+
+        msg_signature = unquote(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')
+
+    async def _handle_post_callback(self) -> tuple[Response, int] | Response:
+        """处理企业微信的 POST 回调请求。"""
+
+        self.stream_sessions.cleanup()
+
+        msg_signature = unquote(request.args.get('msg_signature', ''))
+        timestamp = unquote(request.args.get('timestamp', ''))
+        nonce = unquote(request.args.get('nonce', ''))
+
+        encrypted_json = await request.get_json()
+        encrypted_msg = (encrypted_json or {}).get('encrypt', '')
+        if not encrypted_msg:
+            await self.logger.error("请求体中缺少 'encrypt' 字段")
+            return Response('Bad Request', status=400)
+
+        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')
+            return Response('解密失败', status=400)
+
+        msg_json = json.loads(decrypted_xml)
+
+        if msg_json.get('msgtype') == 'stream':
+            return await self._handle_post_followup_response(msg_json, nonce)
+
+        return await self._handle_post_initial_response(msg_json, nonce)
+
+    async def 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
+
+        # Extract user information
+        from_info = msg_json.get('from', {})
+        message_data['userid'] = from_info.get('userid', '')
+        message_data['username'] = (
+            from_info.get('alias', '') or from_info.get('name', '') or from_info.get('userid', '')
+        )
+
+        # Extract chat/group information
+        if msg_json.get('chattype', '') == 'group':
+            message_data['chatid'] = msg_json.get('chatid', '')
+            # Try to get group name if available
+            message_data['chatname'] = msg_json.get('chatname', '') or msg_json.get('chatid', '')
+
+        message_data['msgid'] = msg_json.get('msgid', '')
+
+        if msg_json.get('aibotid'):
+            message_data['aibotid'] = msg_json.get('aibotid', '')
+
+        return message_data
+
+    async def _handle_message(self, event: wecombotevent.WecomBotEvent):
+        """
+        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 push_stream_chunk(self, msg_id: str, content: str, is_final: bool = False) -> bool:
+        """将流水线片段推送到 stream 会话。
+
+        Args:
+            msg_id: 原始企业微信消息 ID。
+            content: 模型产生的片段内容。
+            is_final: 是否为最终片段。
+
+        Returns:
+            bool: 当成功写入流式队列时返回 True。
+
+        Example:
+            在流水线 `reply_message_chunk` 中调用，将增量推送至企业微信。
+        """
+        # 根据 msg_id 找到对应 stream 会话，如果不存在说明当前消息非流式
+        stream_id = self.stream_sessions.get_stream_id_by_msg(msg_id)
+        if not stream_id:
+            return False
+
+        chunk = StreamChunk(content=content, is_final=is_final)
+        await self.stream_sessions.publish(stream_id, chunk)
+        if is_final:
+            self.stream_sessions.mark_finished(stream_id)
+        return True
+
+    async def set_message(self, msg_id: str, content: str):
+        """兼容旧逻辑：若无法流式返回则缓存最终结果。
+
+        Args:
+            msg_id: 企业微信消息 ID。
+            content: 最终回复的文本内容。
+
+        Example:
+            在非流式场景下缓存最终结果以备刷新时返回。
+        """
+        handled = await self.push_stream_chunk(msg_id, content, is_final=True)
+        if not handled:
+            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)