mirror of
https://github.com/langbot-app/LangBot.git
synced 2026-06-02 03:55:55 +00:00
Merge branch 'master' into master
This commit is contained in:
Typer_Body
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|
||||
- type: textarea
|
||||
attributes:
|
||||
label: 复现步骤
|
||||
description: 提供越多信息，我们会越快解决问题，建议多提供配置截图；**如果你不认真填写（只一两句话概括），我们会很生气并且立即关闭 issue 或两年后才回复你**
|
||||
description: 提供越多信息，我们会越快解决问题，建议多提供配置截图；**如果涉及 Dify、n8n、Langflow 等外部平台，请提供应用的导出文件（如 Dify 应用的 DSL），我们将更快回复您。**
|
||||
validations:
|
||||
required: false
|
||||
- type: textarea
|
||||
|
||||
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@@ -19,7 +19,7 @@ body:
|
||||
- type: textarea
|
||||
attributes:
|
||||
label: Reproduction steps
|
||||
description: How to reproduce this problem, the more detailed the better; the more information you provide, the faster we will solve the problem. 【注意】请务必认真填写此部分，若不提供完整信息（如只有一两句话的概括），我们将不会回复！
|
||||
description: How to reproduce this problem, the more detailed the better; the more information you provide, the faster we will solve the problem.
|
||||
validations:
|
||||
required: false
|
||||
- type: textarea
|
||||
|
||||
192
README_CN.md
Normal file
192
README_CN.md
Normal file
@@ -0,0 +1,192 @@
|
||||
<p align="center">
|
||||
<a href="https://langbot.app">
|
||||
<img width="130" src="https://docs.langbot.app/langbot-logo.png" alt="LangBot"/>
|
||||
</a>
|
||||
|
||||
<div align="center">
|
||||
|
||||
<a href="https://hellogithub.com/repository/langbot-app/LangBot" target="_blank"><img src="https://abroad.hellogithub.com/v1/widgets/recommend.svg?rid=5ce8ae2aa4f74316bf393b57b952433c&claim_uid=gtmc6YWjMZkT21R" alt="Featured｜HelloGitHub" style="width: 250px; height: 54px;" width="250" height="54" /></a>
|
||||
|
||||
<h3>生产级 AI 即时通信机器人开发平台。</h3>
|
||||
<h4>快速构建、调试和部署 AI 机器人到微信、QQ、飞书、Slack、Discord、Telegram 等平台。</h4>
|
||||
|
||||
[English](README.md) / 简体中文 / [繁體中文](README_TW.md) / [日本語](README_JP.md) / [Español](README_ES.md) / [Français](README_FR.md) / [한국어](README_KO.md) / [Русский](README_RU.md) / [Tiếng Việt](README_VI.md)
|
||||
|
||||
[](https://discord.gg/wdNEHETs87)
|
||||
[](https://qm.qq.com/q/DxZZcNxM1W)
|
||||
[](https://deepwiki.com/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">
|
||||
[](https://github.com/langbot-app/LangBot/stargazers)
|
||||
[](https://gitcode.com/RockChinQ/LangBot)
|
||||
|
||||
<a href="https://langbot.app">官网</a> ｜
|
||||
<a href="https://docs.langbot.app/zh/insight/features.html">特性</a> ｜
|
||||
<a href="https://docs.langbot.app/zh/insight/guide.html">文档</a> ｜
|
||||
<a href="https://docs.langbot.app/zh/tags/readme.html">API</a> ｜
|
||||
<a href="https://space.langbot.app">插件市场</a> ｜
|
||||
<a href="https://langbot.featurebase.app/roadmap">路线图</a>
|
||||
|
||||
</div>
|
||||
|
||||
</p>
|
||||
|
||||
---
|
||||
|
||||
## 🚀 什么是 LangBot？
|
||||
|
||||
LangBot 是一个**开源的生产级平台**，用于构建 AI 驱动的即时通信机器人。它将大语言模型（LLM）连接到各种聊天平台，帮助你创建能够对话、执行任务、并集成到现有工作流程中的智能 Agent。
|
||||
|
||||
### 核心能力
|
||||
|
||||
- **💬 AI 对话与 Agent** — 多轮对话、工具调用、多模态、流式输出。自带 RAG（知识库），深度集成 [Dify](https://dify.ai)、[Coze](https://coze.com)、[n8n](https://n8n.io)、[Langflow](https://langflow.org) 等 LLMOps 平台。
|
||||
- **🤖 全平台支持** — 一套代码，覆盖 QQ、微信、企业微信、飞书、钉钉、Discord、Telegram、Slack、LINE、KOOK 等平台。
|
||||
- **🛠️ 生产就绪** — 访问控制、限速、敏感词过滤、全面监控与异常处理，已被多家企业采用。
|
||||
- **🧩 插件生态** — 数百个插件，事件驱动架构，组件扩展，适配 [MCP 协议](https://modelcontextprotocol.io/)。
|
||||
- **😻 Web 管理面板** — 通过浏览器直观地配置、管理和监控机器人，无需手动编辑配置文件。
|
||||
- **📊 多流水线架构** — 不同机器人用于不同场景，具备全面的监控和异常处理能力。
|
||||
|
||||
[→ 了解更多功能特性](https://docs.langbot.app/zh/insight/features.html)
|
||||
|
||||
---
|
||||
|
||||
## 📦 快速开始
|
||||
|
||||
### 一键启动
|
||||
|
||||
```bash
|
||||
uvx langbot
|
||||
```
|
||||
|
||||
> 需要安装 [uv](https://docs.astral.sh/uv/getting-started/installation/)。访问 http://localhost:5300 即可使用。
|
||||
|
||||
### Docker Compose
|
||||
|
||||
```bash
|
||||
git clone https://github.com/langbot-app/LangBot
|
||||
cd LangBot/docker
|
||||
docker compose up -d
|
||||
```
|
||||
|
||||
### 一键云部署
|
||||
|
||||
[](https://zeabur.com/zh-CN/templates/ZKTBDH)
|
||||
[](https://railway.app/template/yRrAyL?referralCode=vogKPF)
|
||||
|
||||
**更多方式：** [Docker](https://docs.langbot.app/zh/deploy/langbot/docker.html) · [手动部署](https://docs.langbot.app/zh/deploy/langbot/manual.html) · [宝塔面板](https://docs.langbot.app/zh/deploy/langbot/one-click/bt.html) · [Kubernetes](./docker/README_K8S.md)
|
||||
|
||||
---
|
||||
|
||||
## ✨ 支持的平台
|
||||
|
||||
| 平台 | 状态 | 备注 |
|
||||
|------|------|------|
|
||||
| QQ | ✅ | 个人号、官方机器人（频道、私聊、群聊） |
|
||||
| 微信 | ✅ | 个人微信、微信公众号 |
|
||||
| 企业微信 | ✅ | 应用消息、对外客服、智能机器人 |
|
||||
| 飞书 | ✅ | |
|
||||
| 钉钉 | ✅ | |
|
||||
| Discord | ✅ | |
|
||||
| Telegram | ✅ | |
|
||||
| Slack | ✅ | |
|
||||
| LINE | ✅ | |
|
||||
| KOOK | ✅ | |
|
||||
|
||||
---
|
||||
|
||||
## 🤖 支持的大模型与集成
|
||||
|
||||
| 提供商 | 类型 | 状态 |
|
||||
|--------|------|------|
|
||||
| [OpenAI](https://platform.openai.com/) | LLM | ✅ |
|
||||
| [Anthropic](https://www.anthropic.com/) | LLM | ✅ |
|
||||
| [DeepSeek](https://www.deepseek.com/) | LLM | ✅ |
|
||||
| [Google Gemini](https://aistudio.google.com/prompts/new_chat) | LLM | ✅ |
|
||||
| [xAI](https://x.ai/) | LLM | ✅ |
|
||||
| [Moonshot](https://www.moonshot.cn/) | LLM | ✅ |
|
||||
| [智谱AI](https://open.bigmodel.cn/) | LLM | ✅ |
|
||||
| [Ollama](https://ollama.com/) | 本地 LLM | ✅ |
|
||||
| [LM Studio](https://lmstudio.ai/) | 本地 LLM | ✅ |
|
||||
| [Dify](https://dify.ai) | LLMOps | ✅ |
|
||||
| [MCP](https://modelcontextprotocol.io/) | 协议 | ✅ |
|
||||
| [SiliconFlow](https://siliconflow.cn/) | 聚合平台 | ✅ |
|
||||
| [阿里云百炼](https://bailian.console.aliyun.com/) | 聚合平台 | ✅ |
|
||||
| [火山方舟](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | 聚合平台 | ✅ |
|
||||
| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | 聚合平台 | ✅ |
|
||||
| [GiteeAI](https://ai.gitee.com/) | 聚合平台 | ✅ |
|
||||
| [胜算云](https://www.shengsuanyun.com/?from=CH_KYIPP758) | GPU 平台 | ✅ |
|
||||
| [优云智算](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | GPU 平台 | ✅ |
|
||||
| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | GPU 平台 | ✅ |
|
||||
| [接口 AI](https://jiekou.ai/) | 聚合平台 | ✅ |
|
||||
| [302.AI](https://share.302.ai/SuTG99) | 聚合平台 | ✅ |
|
||||
| [小马算力](https://www.tokenpony.cn/453z1) | 聚合平台 | ✅ |
|
||||
| [百宝箱Tbox](https://www.tbox.cn/open) | 智能体平台 | ✅ |
|
||||
|
||||
[→ 查看完整集成列表](https://docs.langbot.app/zh/insight/features.html)
|
||||
|
||||
### TTS（语音合成）
|
||||
|
||||
| 平台/模型 | 备注 |
|
||||
|-----------|------|
|
||||
| [FishAudio](https://fish.audio/zh-CN/discovery/) | [插件](https://github.com/the-lazy-me/NewChatVoice) |
|
||||
| [海豚 AI](https://www.ttson.cn/?source=thelazy) | [插件](https://github.com/the-lazy-me/NewChatVoice) |
|
||||
| [AzureTTS](https://portal.azure.com/) | [插件](https://github.com/Ingnaryk/LangBot_AzureTTS) |
|
||||
|
||||
### 文生图
|
||||
|
||||
| 平台/模型 | 备注 |
|
||||
|-----------|------|
|
||||
| 阿里云百炼 | [插件](https://github.com/Thetail001/LangBot_BailianTextToImagePlugin) |
|
||||
|
||||
---
|
||||
|
||||
## 🌟 为什么选择 LangBot？
|
||||
|
||||
| 使用场景 | LangBot 如何帮助 |
|
||||
|----------|------------------|
|
||||
| **客户服务** | 将 AI Agent 部署到微信/企微/钉钉/飞书，基于知识库自动回答用户问题 |
|
||||
| **内部工具** | 将 n8n/Dify 工作流接入企微/钉钉，实现业务流程自动化 |
|
||||
| **社群运营** | 在 QQ/Discord 群中使用 AI 驱动的内容审核与智能互动 |
|
||||
| **多平台触达** | 一个机器人，覆盖所有平台。通过统一面板集中管理 |
|
||||
|
||||
---
|
||||
|
||||
## 🎮 在线演示
|
||||
|
||||
**立即体验：** https://demo.langbot.dev/
|
||||
- 邮箱：`demo@langbot.app`
|
||||
- 密码：`langbot123456`
|
||||
|
||||
*注意：公开演示环境，请不要在其中填入任何敏感信息。*
|
||||
|
||||
---
|
||||
|
||||
## 🤝 社区
|
||||
|
||||
[](https://discord.gg/wdNEHETs87)
|
||||
[](https://qm.qq.com/q/DxZZcNxM1W)
|
||||
|
||||
- 💬 [Discord 社区](https://discord.gg/wdNEHETs87)
|
||||
- 💬 [QQ 社区群](https://qm.qq.com/q/DxZZcNxM1W)
|
||||
|
||||
---
|
||||
|
||||
## ⭐ Star 趋势
|
||||
|
||||
[](https://star-history.com/#langbot-app/LangBot&Date)
|
||||
|
||||
---
|
||||
|
||||
## 😘 贡献者
|
||||
|
||||
感谢所有[贡献者](https://github.com/langbot-app/LangBot/graphs/contributors)对 LangBot 的帮助：
|
||||
|
||||
<a href="https://github.com/langbot-app/LangBot/graphs/contributors">
|
||||
<img src="https://contrib.rocks/image?repo=langbot-app/LangBot" />
|
||||
</a>
|
||||
|
||||
<!--
|
||||
## For Code Agents
|
||||
|
||||
If you're a code agent based on LLM, you should read [AGENTS.md](AGENTS.md) to understand the project structure and development process before you start any development.
|
||||
-->
|
||||
191
README_ES.md
191
README_ES.md
@@ -7,19 +7,21 @@
|
||||
|
||||
<a href="https://www.producthunt.com/products/langbot?utm_source=badge-follow&utm_medium=badge&utm_source=badge-langbot" target="_blank"><img src="https://api.producthunt.com/widgets/embed-image/v1/follow.svg?product_id=1077185&theme=light" alt="LangBot - Production-grade IM bot made easy. | Product Hunt" style="width: 250px; height: 54px;" width="250" height="54" /></a>
|
||||
|
||||
<h3>Cree, depure y despliegue bots de mensajería instantánea rápidamente con LangBot.</h3>
|
||||
<h3>Plataforma de grado de producción para construir bots de mensajería instantánea con agentes de IA.</h3>
|
||||
<h4>Construya, depure y despliegue bots de IA rápidamente en Slack, Discord, Telegram, WeChat y más.</h4>
|
||||
|
||||
[English](README_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)
|
||||
[English](README.md) / [简体中文](README_CN.md) / [繁體中文](README_TW.md) / [日本語](README_JP.md) / Español / [Français](README_FR.md) / [한국어](README_KO.md) / [Русский](README_RU.md) / [Tiếng Việt](README_VI.md)
|
||||
|
||||
[](https://discord.gg/wdNEHETs87)
|
||||
[](https://deepwiki.com/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">
|
||||
[](https://github.com/langbot-app/LangBot/stargazers)
|
||||
|
||||
<a href="https://langbot.app">Inicio</a> ｜
|
||||
<a href="https://docs.langbot.app/en/insight/features.html">Características</a> ｜
|
||||
<a href="https://docs.langbot.app/en/insight/guide.html">Despliegue</a> ｜
|
||||
<a href="https://docs.langbot.app/en/tags/readme.html">Integración API</a> ｜
|
||||
<a href="https://docs.langbot.app/en/insight/guide.html">Documentación</a> ｜
|
||||
<a href="https://docs.langbot.app/en/tags/readme.html">API</a> ｜
|
||||
<a href="https://space.langbot.app">Mercado de Plugins</a> ｜
|
||||
<a href="https://langbot.featurebase.app/roadmap">Hoja de Ruta</a>
|
||||
|
||||
@@ -27,20 +29,36 @@
|
||||
|
||||
</p>
|
||||
|
||||
---
|
||||
|
||||
## 📦 Comenzar
|
||||
## 🚀 ¿Qué es LangBot?
|
||||
|
||||
#### Inicio Rápido
|
||||
LangBot es una **plataforma de código abierto y grado de producción** para construir bots de mensajería instantánea impulsados por IA. Conecta modelos de lenguaje de gran escala (LLMs) con cualquier plataforma de chat, permitiéndole crear agentes inteligentes que pueden conversar, ejecutar tareas e integrarse con sus flujos de trabajo existentes.
|
||||
|
||||
Use `uvx` para iniciar con un comando (necesita instalar [uv](https://docs.astral.sh/uv/getting-started/installation/)):
|
||||
### Capacidades Clave
|
||||
|
||||
- **💬 Conversaciones e Agentes IA** — Diálogos de múltiples turnos, llamadas a herramientas, soporte multimodal, salida en streaming. RAG (base de conocimientos) incorporado con integración profunda con [Dify](https://dify.ai), [Coze](https://coze.com), [n8n](https://n8n.io), [Langflow](https://langflow.org).
|
||||
- **🤖 Soporte Universal de Plataformas de MI** — Un solo código base para Discord, Telegram, Slack, LINE, QQ, WeChat, WeCom, Lark, DingTalk, KOOK.
|
||||
- **🛠️ Listo para Producción** — Control de acceso, limitación de velocidad, filtrado de palabras sensibles, monitoreo completo y manejo de excepciones. De confianza para empresas.
|
||||
- **🧩 Ecosistema de Plugins** — Cientos de plugins, arquitectura basada en eventos, extensiones de componentes y soporte del [protocolo MCP](https://modelcontextprotocol.io/).
|
||||
- **😻 Panel de Gestión Web** — Configure, gestione y monitoree sus bots a través de una interfaz de navegador intuitiva. Sin necesidad de editar YAML.
|
||||
- **📊 Arquitectura Multi-Pipeline** — Diferentes bots para diferentes escenarios, con monitoreo completo y manejo de excepciones.
|
||||
|
||||
[→ Conocer más sobre todas las funcionalidades](https://docs.langbot.app/en/insight/features.html)
|
||||
|
||||
---
|
||||
|
||||
## 📦 Inicio Rápido
|
||||
|
||||
### Lanzamiento en una línea
|
||||
|
||||
```bash
|
||||
uvx langbot
|
||||
```
|
||||
|
||||
Visite http://localhost:5300 para comenzar a usarlo.
|
||||
> Requiere [uv](https://docs.astral.sh/uv/getting-started/installation/). Visite http://localhost:5300 — listo.
|
||||
|
||||
#### Despliegue con Docker Compose
|
||||
### Docker Compose
|
||||
|
||||
```bash
|
||||
git clone https://github.com/langbot-app/LangBot
|
||||
@@ -48,104 +66,101 @@ 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.
|
||||
### Despliegue en la Nube con un Clic
|
||||
|
||||
[](https://zeabur.com/en-US/templates/ZKTBDH)
|
||||
|
||||
#### Despliegue en la Nube Railway
|
||||
|
||||
[](https://railway.app/template/yRrAyL?referralCode=vogKPF)
|
||||
|
||||
#### Otros Métodos de Despliegue
|
||||
**Más opciones:** [Docker](https://docs.langbot.app/en/deploy/langbot/docker.html) · [Manual](https://docs.langbot.app/en/deploy/langbot/manual.html) · [BTPanel](https://docs.langbot.app/en/deploy/langbot/one-click/bt.html) · [Kubernetes](./docker/README_K8S.md)
|
||||
|
||||
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
|
||||
## ✨ Plataformas Soportadas
|
||||
|
||||
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.
|
||||
|
||||
|
||||
|
||||
## ✨ Características
|
||||
|
||||
<img width="500" src="https://docs.langbot.app/ui/bot-page-en-rounded.png" />
|
||||
|
||||
|
||||
- 💬 Chat con LLM / Agent: Compatible con múltiples LLMs, adaptado para chats grupales y privados; Admite conversaciones de múltiples rondas, llamadas a herramientas, capacidades multimodales y de salida en streaming. Implementación RAG (base de conocimientos) incorporada, e integración profunda con [Dify](https://dify.ai), [Coze](https://coze.com), [n8n](https://n8n.io), [Langflow](https://langflow.org) etc. LLMOps platforms.
|
||||
- 🤖 Soporte Multiplataforma: Actualmente compatible con QQ, QQ Channel, WeCom, WeChat personal, Lark, DingTalk, Discord, Telegram, KOOK, Slack, LINE, etc.
|
||||
- 🛠️ Alta Estabilidad, Rico en Funciones: Control de acceso nativo, limitación de velocidad, filtrado de palabras sensibles, etc.; Fácil de usar, admite múltiples métodos de despliegue.
|
||||
- 🧩 Extensión de Plugin, Comunidad Activa: Sistema de plugin de alta estabilidad, alta seguridad de nivel de producción; Compatible con mecanismos de plugin impulsados por eventos, extensión de componentes, etc.; Integración del protocolo [MCP](https://modelcontextprotocol.io/) de Anthropic; Actualmente cuenta con cientos de plugins.
|
||||
- 😻 Interfaz Web: Admite la gestión de instancias de LangBot a través del navegador. No es necesario escribir archivos de configuración manualmente.
|
||||
- 📊 Características de Nivel de Producción: Compatible con múltiples configuraciones de pipeline, diferentes bots para diferentes escenarios. Cuenta con capacidades completas de monitoreo y manejo de excepciones.
|
||||
|
||||
Para especificaciones más detalladas, consulte la [documentación](https://docs.langbot.app/en/insight/features.html).
|
||||
|
||||
O visite el entorno de demostración: https://demo.langbot.dev/
|
||||
- Información de inicio de sesión: Correo electrónico: `demo@langbot.app` Contraseña: `langbot123456`
|
||||
- Nota: Solo para demostración de WebUI, por favor no ingrese información confidencial en el entorno público.
|
||||
|
||||
### Plataformas de Mensajería
|
||||
|
||||
| Plataforma | Estado | Observaciones |
|
||||
| --- | --- | --- |
|
||||
| Plataforma | Estado | Notas |
|
||||
|----------|--------|-------|
|
||||
| Discord | ✅ | |
|
||||
| Telegram | ✅ | |
|
||||
| Slack | ✅ | |
|
||||
| LINE | ✅ | |
|
||||
| QQ Personal | ✅ | |
|
||||
| QQ API Oficial | ✅ | |
|
||||
| WeCom | ✅ | |
|
||||
| WeComCS | ✅ | |
|
||||
| WeCom AI Bot | ✅ | |
|
||||
| WeChat Personal | ✅ | |
|
||||
| QQ | ✅ | Personal y API Oficial |
|
||||
| WeCom | ✅ | WeChat Empresarial, CS Externo, AI Bot |
|
||||
| WeChat | ✅ | Personal y Cuenta Oficial |
|
||||
| Lark | ✅ | |
|
||||
| DingTalk | ✅ | |
|
||||
| KOOK | ✅ | |
|
||||
| Satori | ✅ | |
|
||||
|
||||
### 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 |
|
||||
## 🤖 LLMs e Integraciones Soportadas
|
||||
|
||||
## 🤝 Contribución de la Comunidad
|
||||
| Proveedor | Tipo | Estado |
|
||||
|----------|------|--------|
|
||||
| [OpenAI](https://platform.openai.com/) | LLM | ✅ |
|
||||
| [Anthropic](https://www.anthropic.com/) | LLM | ✅ |
|
||||
| [DeepSeek](https://www.deepseek.com/) | LLM | ✅ |
|
||||
| [Google Gemini](https://aistudio.google.com/prompts/new_chat) | LLM | ✅ |
|
||||
| [xAI](https://x.ai/) | LLM | ✅ |
|
||||
| [Moonshot](https://www.moonshot.cn/) | LLM | ✅ |
|
||||
| [Zhipu AI](https://open.bigmodel.cn/) | LLM | ✅ |
|
||||
| [Ollama](https://ollama.com/) | LLM Local | ✅ |
|
||||
| [LM Studio](https://lmstudio.ai/) | LLM Local | ✅ |
|
||||
| [Dify](https://dify.ai) | LLMOps | ✅ |
|
||||
| [MCP](https://modelcontextprotocol.io/) | Protocolo | ✅ |
|
||||
| [SiliconFlow](https://siliconflow.cn/) | Pasarela | ✅ |
|
||||
| [Aliyun Bailian](https://bailian.console.aliyun.com/) | Pasarela | ✅ |
|
||||
| [Volc Engine Ark](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | Pasarela | ✅ |
|
||||
| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | Pasarela | ✅ |
|
||||
| [GiteeAI](https://ai.gitee.com/) | Pasarela | ✅ |
|
||||
| [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | Plataforma GPU | ✅ |
|
||||
| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | Plataforma GPU | ✅ |
|
||||
| [ShengSuanYun](https://www.shengsuanyun.com/?from=CH_KYIPP758) | Plataforma GPU | ✅ |
|
||||
| [接口 AI](https://jiekou.ai/) | Pasarela | ✅ |
|
||||
| [302.AI](https://share.302.ai/SuTG99) | Pasarela | ✅ |
|
||||
|
||||
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:
|
||||
[→ Ver todas las integraciones](https://docs.langbot.app/en/insight/features.html)
|
||||
|
||||
---
|
||||
|
||||
## 🌟 ¿Por qué LangBot?
|
||||
|
||||
| Caso de Uso | Cómo Ayuda LangBot |
|
||||
|----------|-------------------|
|
||||
| **Atención al cliente** | Despliegue agentes de IA en Slack/Discord/Telegram que respondan preguntas usando su base de conocimientos |
|
||||
| **Herramientas internas** | Conecte flujos de trabajo de n8n/Dify a WeCom/DingTalk para procesos empresariales automatizados |
|
||||
| **Gestión de comunidades** | Modere grupos de QQ/Discord con filtrado de contenido e interacción impulsados por IA |
|
||||
| **Presencia multiplataforma** | Un solo bot, todas las plataformas. Gestione desde un único panel de control |
|
||||
|
||||
---
|
||||
|
||||
## 🎮 Demo en Vivo
|
||||
|
||||
**Pruébelo ahora:** https://demo.langbot.dev/
|
||||
- Correo electrónico: `demo@langbot.app`
|
||||
- Contraseña: `langbot123456`
|
||||
|
||||
*Nota: Entorno de demostración público. No ingrese información confidencial.*
|
||||
|
||||
---
|
||||
|
||||
## 🤝 Comunidad
|
||||
|
||||
[](https://discord.gg/wdNEHETs87)
|
||||
|
||||
- 💬 [Comunidad de Discord](https://discord.gg/wdNEHETs87)
|
||||
|
||||
---
|
||||
|
||||
## ⭐ Historial de Stars
|
||||
|
||||
[](https://star-history.com/#langbot-app/LangBot&Date)
|
||||
|
||||
---
|
||||
|
||||
## 😘 Colaboradores
|
||||
|
||||
Gracias a todos los [colaboradores](https://github.com/langbot-app/LangBot/graphs/contributors) que han ayudado a mejorar LangBot:
|
||||
|
||||
<a href="https://github.com/langbot-app/LangBot/graphs/contributors">
|
||||
<img src="https://contrib.rocks/image?repo=langbot-app/LangBot" />
|
||||
|
||||
192
README_FR.md
192
README_FR.md
@@ -7,19 +7,21 @@
|
||||
|
||||
<a href="https://www.producthunt.com/products/langbot?utm_source=badge-follow&utm_medium=badge&utm_source=badge-langbot" target="_blank"><img src="https://api.producthunt.com/widgets/embed-image/v1/follow.svg?product_id=1077185&theme=light" alt="LangBot - Production-grade IM bot made easy. | Product Hunt" style="width: 250px; height: 54px;" width="250" height="54" /></a>
|
||||
|
||||
<h3>Créez, déboguez et déployez rapidement des bots de messagerie instantanée avec LangBot.</h3>
|
||||
<h3>Plateforme de niveau production pour construire des bots de messagerie instantanée avec agents IA.</h3>
|
||||
<h4>Créez, déboguez et déployez rapidement des bots IA sur Slack, Discord, Telegram, WeChat et plus.</h4>
|
||||
|
||||
[English](README_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)
|
||||
[English](README.md) / [简体中文](README_CN.md) / [繁體中文](README_TW.md) / [日本語](README_JP.md) / [Español](README_ES.md) / Français / [한국어](README_KO.md) / [Русский](README_RU.md) / [Tiếng Việt](README_VI.md)
|
||||
|
||||
[](https://discord.gg/wdNEHETs87)
|
||||
[](https://deepwiki.com/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">
|
||||
[](https://github.com/langbot-app/LangBot/stargazers)
|
||||
|
||||
<a href="https://langbot.app">Accueil</a> ｜
|
||||
<a href="https://docs.langbot.app/en/insight/features.html">Fonctionnalités</a> ｜
|
||||
<a href="https://docs.langbot.app/en/insight/guide.html">Déploiement</a> ｜
|
||||
<a href="https://docs.langbot.app/en/tags/readme.html">Intégration API</a> ｜
|
||||
<a href="https://docs.langbot.app/en/insight/guide.html">Documentation</a> ｜
|
||||
<a href="https://docs.langbot.app/en/tags/readme.html">API</a> ｜
|
||||
<a href="https://space.langbot.app">Marché des Plugins</a> ｜
|
||||
<a href="https://langbot.featurebase.app/roadmap">Feuille de Route</a>
|
||||
|
||||
@@ -27,19 +29,36 @@
|
||||
|
||||
</p>
|
||||
|
||||
## 📦 Commencer
|
||||
---
|
||||
|
||||
#### Démarrage Rapide
|
||||
## 🚀 Qu'est-ce que LangBot ?
|
||||
|
||||
Utilisez `uvx` pour démarrer avec une commande (besoin d'installer [uv](https://docs.astral.sh/uv/getting-started/installation/)) :
|
||||
LangBot est une **plateforme open-source de niveau production** pour créer des bots de messagerie instantanée alimentés par l'IA. Elle connecte les grands modèles de langage (LLMs) à n'importe quelle plateforme de chat, vous permettant de créer des agents intelligents capables de converser, d'exécuter des tâches et de s'intégrer à vos workflows existants.
|
||||
|
||||
### Capacités Clés
|
||||
|
||||
- **💬 Conversations IA & Agents** — Dialogues multi-tours, appels d'outils, support multimodal, sortie en streaming. RAG (base de connaissances) intégré avec intégration profonde de [Dify](https://dify.ai), [Coze](https://coze.com), [n8n](https://n8n.io), [Langflow](https://langflow.org).
|
||||
- **🤖 Support Universel des Plateformes de MI** — Un seul code pour Discord, Telegram, Slack, LINE, QQ, WeChat, WeCom, Lark, DingTalk, KOOK.
|
||||
- **🛠️ Prêt pour la Production** — Contrôle d'accès, limitation de débit, filtrage de mots sensibles, surveillance complète et gestion des exceptions. Approuvé par les entreprises.
|
||||
- **🧩 Écosystème de Plugins** — Des centaines de plugins, architecture événementielle, extensions de composants, et support du [protocole MCP](https://modelcontextprotocol.io/).
|
||||
- **😻 Panneau de Gestion Web** — Configurez, gérez et surveillez vos bots via une interface navigateur intuitive. Aucune édition de YAML requise.
|
||||
- **📊 Architecture Multi-Pipeline** — Différents bots pour différents scénarios, avec surveillance complète et gestion des exceptions.
|
||||
|
||||
[→ En savoir plus sur toutes les fonctionnalités](https://docs.langbot.app/en/insight/features.html)
|
||||
|
||||
---
|
||||
|
||||
## 📦 Démarrage Rapide
|
||||
|
||||
### Lancement en une ligne
|
||||
|
||||
```bash
|
||||
uvx langbot
|
||||
```
|
||||
|
||||
Visitez http://localhost:5300 pour commencer à l'utiliser.
|
||||
> Nécessite [uv](https://docs.astral.sh/uv/getting-started/installation/). Visitez http://localhost:5300 — c'est prêt.
|
||||
|
||||
#### Déploiement avec Docker Compose
|
||||
### Docker Compose
|
||||
|
||||
```bash
|
||||
git clone https://github.com/langbot-app/LangBot
|
||||
@@ -47,104 +66,101 @@ 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.
|
||||
### Déploiement Cloud en un Clic
|
||||
|
||||
[](https://zeabur.com/en-US/templates/ZKTBDH)
|
||||
|
||||
#### Déploiement Cloud Railway
|
||||
|
||||
[](https://railway.app/template/yRrAyL?referralCode=vogKPF)
|
||||
|
||||
#### Autres Méthodes de Déploiement
|
||||
**Plus d'options :** [Docker](https://docs.langbot.app/en/deploy/langbot/docker.html) · [Manuel](https://docs.langbot.app/en/deploy/langbot/manual.html) · [BTPanel](https://docs.langbot.app/en/deploy/langbot/one-click/bt.html) · [Kubernetes](./docker/README_K8S.md)
|
||||
|
||||
Utilisez directement la version publiée pour exécuter, consultez la documentation de [Déploiement Manuel](https://docs.langbot.app/en/deploy/langbot/manual.html).
|
||||
---
|
||||
|
||||
#### Déploiement Kubernetes
|
||||
## ✨ Plateformes Supportées
|
||||
|
||||
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.
|
||||
|
||||
|
||||
|
||||
## ✨ Fonctionnalités
|
||||
|
||||
<img width="500" src="https://docs.langbot.app/ui/bot-page-en-rounded.png" />
|
||||
|
||||
|
||||
- 💬 Chat avec LLM / Agent : Prend en charge plusieurs LLM, adapté aux chats de groupe et privés ; Prend en charge les conversations multi-tours, les appels d'outils, les capacités multimodales et de sortie en streaming. Implémentation RAG (base de connaissances) intégrée, et intégration profonde avec [Dify](https://dify.ai), [Coze](https://coze.com), [n8n](https://n8n.io), [Langflow](https://langflow.org) etc. LLMOps platforms.
|
||||
- 🤖 Support Multi-plateforme : Actuellement compatible avec QQ, QQ Channel, WeCom, WeChat personnel, Lark, DingTalk, Discord, Telegram, KOOK, Slack, LINE, etc.
|
||||
- 🛠️ Haute Stabilité, Riche en Fonctionnalités : Contrôle d'accès natif, limitation de débit, filtrage de mots sensibles, etc. ; Facile à utiliser, prend en charge plusieurs méthodes de déploiement.
|
||||
- 🧩 Extension de Plugin, Communauté Active : Système de plugin de haute stabilité, haute sécurité de niveau production; Prend en charge les mécanismes de plugin pilotés par événements, l'extension de composants, etc. ; Intégration du protocole [MCP](https://modelcontextprotocol.io/) d'Anthropic ; Dispose actuellement de centaines de plugins.
|
||||
- 😻 Interface Web : Prend en charge la gestion des instances LangBot via le navigateur. Pas besoin d'écrire manuellement les fichiers de configuration.
|
||||
- 📊 Fonctionnalités de Niveau Production : Prend en charge plusieurs configurations de pipeline, différents bots pour différents scénarios. Dispose de capacités complètes de surveillance et de gestion des exceptions.
|
||||
|
||||
Pour des spécifications plus détaillées, veuillez consulter la [documentation](https://docs.langbot.app/en/insight/features.html).
|
||||
|
||||
Ou visitez l'environnement de démonstration : https://demo.langbot.dev/
|
||||
- Informations de connexion : Email : `demo@langbot.app` Mot de passe : `langbot123456`
|
||||
- Note : Pour la démonstration WebUI uniquement, veuillez ne pas entrer d'informations sensibles dans l'environnement public.
|
||||
|
||||
### Plateformes de Messagerie
|
||||
|
||||
| Plateforme | Statut | Remarques |
|
||||
| --- | --- | --- |
|
||||
| Plateforme | Statut | Notes |
|
||||
|----------|--------|-------|
|
||||
| Discord | ✅ | |
|
||||
| Telegram | ✅ | |
|
||||
| Slack | ✅ | |
|
||||
| LINE | ✅ | |
|
||||
| QQ Personnel | ✅ | |
|
||||
| API Officielle QQ | ✅ | |
|
||||
| WeCom | ✅ | |
|
||||
| WeComCS | ✅ | |
|
||||
| WeCom AI Bot | ✅ | |
|
||||
| WeChat Personnel | ✅ | |
|
||||
| QQ | ✅ | Personnel & API Officielle |
|
||||
| WeCom | ✅ | WeChat Entreprise, CS Externe, AI Bot |
|
||||
| WeChat | ✅ | Personnel & Compte Officiel |
|
||||
| Lark | ✅ | |
|
||||
| DingTalk | ✅ | |
|
||||
| KOOK | ✅ | |
|
||||
| Satori | ✅ | |
|
||||
|
||||
### 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 |
|
||||
## 🤖 LLMs et Intégrations Supportés
|
||||
|
||||
## 🤝 Contribution de la Communauté
|
||||
| Fournisseur | Type | Statut |
|
||||
|----------|------|--------|
|
||||
| [OpenAI](https://platform.openai.com/) | LLM | ✅ |
|
||||
| [Anthropic](https://www.anthropic.com/) | LLM | ✅ |
|
||||
| [DeepSeek](https://www.deepseek.com/) | LLM | ✅ |
|
||||
| [Google Gemini](https://aistudio.google.com/prompts/new_chat) | LLM | ✅ |
|
||||
| [xAI](https://x.ai/) | LLM | ✅ |
|
||||
| [Moonshot](https://www.moonshot.cn/) | LLM | ✅ |
|
||||
| [Zhipu AI](https://open.bigmodel.cn/) | LLM | ✅ |
|
||||
| [Ollama](https://ollama.com/) | LLM Local | ✅ |
|
||||
| [LM Studio](https://lmstudio.ai/) | LLM Local | ✅ |
|
||||
| [Dify](https://dify.ai) | LLMOps | ✅ |
|
||||
| [MCP](https://modelcontextprotocol.io/) | Protocole | ✅ |
|
||||
| [SiliconFlow](https://siliconflow.cn/) | Passerelle | ✅ |
|
||||
| [Aliyun Bailian](https://bailian.console.aliyun.com/) | Passerelle | ✅ |
|
||||
| [Volc Engine Ark](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | Passerelle | ✅ |
|
||||
| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | Passerelle | ✅ |
|
||||
| [GiteeAI](https://ai.gitee.com/) | Passerelle | ✅ |
|
||||
| [接口 AI](https://jiekou.ai/) | Passerelle | ✅ |
|
||||
| [302.AI](https://share.302.ai/SuTG99) | Passerelle | ✅ |
|
||||
| [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | Plateforme GPU | ✅ |
|
||||
| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | Plateforme GPU | ✅ |
|
||||
| [ShengSuanYun](https://www.shengsuanyun.com/?from=CH_KYIPP758) | Plateforme GPU | ✅ |
|
||||
|
||||
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 :
|
||||
[→ Voir toutes les intégrations](https://docs.langbot.app/en/insight/features.html)
|
||||
|
||||
---
|
||||
|
||||
## 🌟 Pourquoi LangBot ?
|
||||
|
||||
| Cas d'Usage | Comment LangBot Aide |
|
||||
|----------|-------------------|
|
||||
| **Support Client** | Déployez des agents IA sur Slack/Discord/Telegram qui répondent aux questions en utilisant votre base de connaissances |
|
||||
| **Outils Internes** | Connectez les workflows n8n/Dify à WeCom/DingTalk pour automatiser vos processus métier |
|
||||
| **Gestion de Communauté** | Modérez les groupes QQ/Discord avec un filtrage de contenu et des interactions alimentés par l'IA |
|
||||
| **Présence Multi-plateforme** | Un seul bot, toutes les plateformes. Gérez tout depuis un tableau de bord unique |
|
||||
|
||||
---
|
||||
|
||||
## 🎮 Démo en Ligne
|
||||
|
||||
**Essayez maintenant :** https://demo.langbot.dev/
|
||||
- Email : `demo@langbot.app`
|
||||
- Mot de passe : `langbot123456`
|
||||
|
||||
*Note : Environnement de démonstration public. Ne saisissez pas d'informations sensibles.*
|
||||
|
||||
---
|
||||
|
||||
## 🤝 Communauté
|
||||
|
||||
[](https://discord.gg/wdNEHETs87)
|
||||
|
||||
- 💬 [Communauté Discord](https://discord.gg/wdNEHETs87)
|
||||
|
||||
---
|
||||
|
||||
## ⭐ Historique des Stars
|
||||
|
||||
[](https://star-history.com/#langbot-app/LangBot&Date)
|
||||
|
||||
---
|
||||
|
||||
## 😘 Contributeurs
|
||||
|
||||
Merci à tous les [contributeurs](https://github.com/langbot-app/LangBot/graphs/contributors) qui ont aidé à améliorer LangBot :
|
||||
|
||||
<a href="https://github.com/langbot-app/LangBot/graphs/contributors">
|
||||
<img src="https://contrib.rocks/image?repo=langbot-app/LangBot" />
|
||||
|
||||
192
README_JP.md
192
README_JP.md
@@ -7,19 +7,21 @@
|
||||
|
||||
<a href="https://www.producthunt.com/products/langbot?utm_source=badge-follow&utm_medium=badge&utm_source=badge-langbot" target="_blank"><img src="https://api.producthunt.com/widgets/embed-image/v1/follow.svg?product_id=1077185&theme=light" alt="LangBot - Production-grade IM bot made easy. | Product Hunt" style="width: 250px; height: 54px;" width="250" height="54" /></a>
|
||||
|
||||
<h3>LangBotでIMボットを素早く構築、デバッグ、デプロイ。</h3>
|
||||
<h3>AIエージェント搭載IMボットを構築するための本番グレードプラットフォーム。</h3>
|
||||
<h4>Slack、Discord、Telegram、WeChat などに AI ボットを素早く構築、デバッグ、デプロイ。</h4>
|
||||
|
||||
[English](README_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)
|
||||
[English](README.md) / [简体中文](README_CN.md) / [繁體中文](README_TW.md) / 日本語 / [Español](README_ES.md) / [Français](README_FR.md) / [한국어](README_KO.md) / [Русский](README_RU.md) / [Tiếng Việt](README_VI.md)
|
||||
|
||||
[](https://discord.gg/wdNEHETs87)
|
||||
[](https://deepwiki.com/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">
|
||||
[](https://github.com/langbot-app/LangBot/stargazers)
|
||||
|
||||
<a href="https://langbot.app">ホーム</a> ｜
|
||||
<a href="https://docs.langbot.app/ja/insight/features.html">機能仕様</a> ｜
|
||||
<a href="https://docs.langbot.app/ja/insight/guide.html">デプロイ</a> ｜
|
||||
<a href="https://docs.langbot.app/ja/tags/readme.html">API統合</a> ｜
|
||||
<a href="https://docs.langbot.app/ja/insight/features.html">機能</a> ｜
|
||||
<a href="https://docs.langbot.app/ja/insight/guide.html">ドキュメント</a> ｜
|
||||
<a href="https://docs.langbot.app/ja/tags/readme.html">API</a> ｜
|
||||
<a href="https://space.langbot.app">プラグインマーケット</a> ｜
|
||||
<a href="https://langbot.featurebase.app/roadmap">ロードマップ</a>
|
||||
|
||||
@@ -27,19 +29,36 @@
|
||||
|
||||
</p>
|
||||
|
||||
## 📦 始め方
|
||||
---
|
||||
|
||||
#### クイックスタート
|
||||
## 🚀 LangBot とは？
|
||||
|
||||
`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）：
|
||||
LangBot は、AI搭載のインスタントメッセージングボットを構築するための**オープンソースの本番グレードプラットフォーム**です。大規模言語モデル（LLM）をあらゆるチャットプラットフォームに接続し、会話、タスク実行、既存のワークフローとの統合が可能なインテリジェントエージェントを作成できます。
|
||||
|
||||
### 主な機能
|
||||
|
||||
- **💬 AI対話とエージェント** — マルチターン対話、ツール呼び出し、マルチモーダル対応、ストリーミング出力。RAG（ナレッジベース）を内蔵し、[Dify](https://dify.ai)、[Coze](https://coze.com)、[n8n](https://n8n.io)、[Langflow](https://langflow.org) と深く統合。
|
||||
- **🤖 ユニバーサルIMプラットフォーム対応** — 単一のコードベースで Discord、Telegram、Slack、LINE、QQ、WeChat、WeCom、Lark、DingTalk、KOOK に対応。
|
||||
- **🛠️ 本番環境対応** — アクセス制御、レート制限、センシティブワードフィルタリング、包括的な監視、例外処理を搭載。エンタープライズの信頼に応える品質。
|
||||
- **🧩 プラグインエコシステム** — 数百のプラグイン、イベント駆動アーキテクチャ、コンポーネント拡張、[MCPプロトコル](https://modelcontextprotocol.io/)対応。
|
||||
- **😻 Web管理パネル** — 直感的なブラウザインターフェースからボットの設定、管理、監視が可能。YAML編集は不要。
|
||||
- **📊 マルチパイプラインアーキテクチャ** — 異なるシナリオに異なるボットを配置し、包括的な監視と例外処理を実現。
|
||||
|
||||
[→ すべての機能について詳しく見る](https://docs.langbot.app/ja/insight/features.html)
|
||||
|
||||
---
|
||||
|
||||
## 📦 クイックスタート
|
||||
|
||||
### ワンライン起動
|
||||
|
||||
```bash
|
||||
uvx langbot
|
||||
```
|
||||
|
||||
http://localhost:5300 にアクセスして使用を開始します。
|
||||
> [uv](https://docs.astral.sh/uv/getting-started/installation/) が必要です。http://localhost:5300 にアクセスして完了。
|
||||
|
||||
#### Docker Compose デプロイ
|
||||
### Docker Compose
|
||||
|
||||
```bash
|
||||
git clone https://github.com/langbot-app/LangBot
|
||||
@@ -47,104 +66,101 @@ cd LangBot/docker
|
||||
docker compose up -d
|
||||
```
|
||||
|
||||
http://localhost:5300 にアクセスして使用を開始します。
|
||||
|
||||
詳細なドキュメントは[Dockerデプロイ](https://docs.langbot.app/en/deploy/langbot/docker.html)を参照してください。
|
||||
|
||||
#### Panelでのワンクリックデプロイ
|
||||
|
||||
LangBotはBTPanelにリストされています。BTPanelをインストールしている場合は、[ドキュメント](https://docs.langbot.app/en/deploy/langbot/one-click/bt.html)を使用して使用できます。
|
||||
|
||||
#### Zeaburクラウドデプロイ
|
||||
|
||||
コミュニティが提供するZeaburテンプレート。
|
||||
### ワンクリッククラウドデプロイ
|
||||
|
||||
[](https://zeabur.com/en-US/templates/ZKTBDH)
|
||||
|
||||
#### Railwayクラウドデプロイ
|
||||
|
||||
[](https://railway.app/template/yRrAyL?referralCode=vogKPF)
|
||||
|
||||
#### その他のデプロイ方法
|
||||
**その他:** [Docker](https://docs.langbot.app/en/deploy/langbot/docker.html) · [手動デプロイ](https://docs.langbot.app/en/deploy/langbot/manual.html) · [BTPanel](https://docs.langbot.app/en/deploy/langbot/one-click/bt.html) · [Kubernetes](./docker/README_K8S.md)
|
||||
|
||||
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。
|
||||
|
||||
|
||||
|
||||
## ✨ 機能
|
||||
|
||||
<img width="500" src="https://docs.langbot.app/ui/bot-page-en-rounded.png" />
|
||||
|
||||
|
||||
- 💬 LLM / エージェントとのチャット: 複数のLLMをサポートし、グループチャットとプライベートチャットに対応。マルチラウンドの会話、ツールの呼び出し、マルチモーダル、ストリーミング出力機能をサポート、RAG（知識ベース）を組み込み、[Dify](https://dify.ai)、[Coze](https://coze.com)、[n8n](https://n8n.io)、[Langflow](https://langflow.org)などの LLMOps プラットフォームと深く統合。
|
||||
- 🤖 多プラットフォーム対応: 現在、QQ、QQ チャンネル、WeChat、個人 WeChat、Lark、DingTalk、Discord、Telegram、KOOK、Slack、LINE など、複数のプラットフォームをサポートしています。
|
||||
- 🛠️ 高い安定性、豊富な機能: ネイティブのアクセス制御、レート制限、敏感な単語のフィルタリングなどのメカニズムをサポート。使いやすく、複数のデプロイ方法をサポート。
|
||||
- 🧩 プラグイン拡張、活発なコミュニティ: 高い安定性、高いセキュリティの生産レベルのプラグインシステム；イベント駆動、コンポーネント拡張などのプラグインメカニズムをサポート。適配 Anthropic [MCP プロトコル](https://modelcontextprotocol.io/)；豊富なエコシステム、現在数百のプラグインが存在。
|
||||
- 😻 Web UI: ブラウザを通じてLangBotインスタンスを管理することをサポート。
|
||||
- 📊 生産レベルの機能: 複数のパイプライン設定をサポートし、異なるボットを異なる用途に使用できます。包括的な監視と例外処理機能を備えています。
|
||||
|
||||
詳細な仕様については、[ドキュメント](https://docs.langbot.app/en/insight/features.html)を参照してください。
|
||||
|
||||
または、デモ環境にアクセスしてください: https://demo.langbot.dev/
|
||||
- ログイン情報: メール: `demo@langbot.app` パスワード: `langbot123456`
|
||||
- 注意: WebUI のデモンストレーションのみの場合、公開環境では機密情報を入力しないでください。
|
||||
|
||||
### メッセージプラットフォーム
|
||||
## ✨ 対応プラットフォーム
|
||||
|
||||
| プラットフォーム | ステータス | 備考 |
|
||||
| --- | --- | --- |
|
||||
|----------|--------|-------|
|
||||
| Discord | ✅ | |
|
||||
| Telegram | ✅ | |
|
||||
| Slack | ✅ | |
|
||||
| LINE | ✅ | |
|
||||
| 個人QQ | ✅ | |
|
||||
| QQ公式API | ✅ | |
|
||||
| WeCom | ✅ | |
|
||||
| WeComCS | ✅ | |
|
||||
| WeCom AI Bot | ✅ | |
|
||||
| 個人WeChat | ✅ | |
|
||||
| QQ | ✅ | 個人 & 公式API |
|
||||
| WeCom | ✅ | 企業WeChat、外部CS、AIボット |
|
||||
| WeChat | ✅ | 個人 & 公式アカウント |
|
||||
| Lark | ✅ | |
|
||||
| DingTalk | ✅ | |
|
||||
| KOOK | ✅ | |
|
||||
| Satori | ✅ | |
|
||||
|
||||
### LLMs
|
||||
---
|
||||
|
||||
| LLM | ステータス | 備考 |
|
||||
| --- | --- | --- |
|
||||
| [OpenAI](https://platform.openai.com/) | ✅ | 任意のOpenAIインターフェース形式モデルに対応 |
|
||||
| [DeepSeek](https://www.deepseek.com/) | ✅ | |
|
||||
| [Moonshot](https://www.moonshot.cn/) | ✅ | |
|
||||
| [Anthropic](https://www.anthropic.com/) | ✅ | |
|
||||
| [xAI](https://x.ai/) | ✅ | |
|
||||
| [Zhipu AI](https://open.bigmodel.cn/) | ✅ | |
|
||||
| [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | ✅ | 大模型とGPUリソースプラットフォーム |
|
||||
| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | ✅ | 大模型とGPUリソースプラットフォーム |
|
||||
| [接口 AI](https://jiekou.ai/) | ✅ | LLMゲートウェイ(MaaS) |
|
||||
| [ShengSuanYun](https://www.shengsuanyun.com/?from=CH_KYIPP758) | ✅ | LLMとGPUリソースプラットフォーム |
|
||||
| [302.AI](https://share.302.ai/SuTG99) | ✅ | LLMゲートウェイ(MaaS) |
|
||||
| [Google Gemini](https://aistudio.google.com/prompts/new_chat) | ✅ | |
|
||||
| [Dify](https://dify.ai) | ✅ | LLMOpsプラットフォーム |
|
||||
| [Ollama](https://ollama.com/) | ✅ | ローカルLLM実行プラットフォーム |
|
||||
| [LMStudio](https://lmstudio.ai/) | ✅ | ローカルLLM実行プラットフォーム |
|
||||
| [GiteeAI](https://ai.gitee.com/) | ✅ | LLMインターフェースゲートウェイ(MaaS) |
|
||||
| [SiliconFlow](https://siliconflow.cn/) | ✅ | LLMゲートウェイ(MaaS) |
|
||||
| [Aliyun Bailian](https://bailian.console.aliyun.com/) | ✅ | LLMゲートウェイ(MaaS), LLMOpsプラットフォーム |
|
||||
| [Volc Engine Ark](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | ✅ | LLMゲートウェイ(MaaS), LLMOpsプラットフォーム |
|
||||
| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | ✅ | LLMゲートウェイ(MaaS) |
|
||||
| [MCP](https://modelcontextprotocol.io/) | ✅ | MCPプロトコルをサポート |
|
||||
## 🤖 対応LLMと統合
|
||||
|
||||
## 🤝 コミュニティ貢献
|
||||
| プロバイダー | タイプ | ステータス |
|
||||
|----------|------|--------|
|
||||
| [OpenAI](https://platform.openai.com/) | LLM | ✅ |
|
||||
| [Anthropic](https://www.anthropic.com/) | LLM | ✅ |
|
||||
| [DeepSeek](https://www.deepseek.com/) | LLM | ✅ |
|
||||
| [Google Gemini](https://aistudio.google.com/prompts/new_chat) | LLM | ✅ |
|
||||
| [xAI](https://x.ai/) | LLM | ✅ |
|
||||
| [Moonshot](https://www.moonshot.cn/) | LLM | ✅ |
|
||||
| [Zhipu AI](https://open.bigmodel.cn/) | LLM | ✅ |
|
||||
| [Ollama](https://ollama.com/) | ローカルLLM | ✅ |
|
||||
| [LM Studio](https://lmstudio.ai/) | ローカルLLM | ✅ |
|
||||
| [Dify](https://dify.ai) | LLMOps | ✅ |
|
||||
| [MCP](https://modelcontextprotocol.io/) | プロトコル | ✅ |
|
||||
| [SiliconFlow](https://siliconflow.cn/) | ゲートウェイ | ✅ |
|
||||
| [Aliyun Bailian](https://bailian.console.aliyun.com/) | ゲートウェイ | ✅ |
|
||||
| [Volc Engine Ark](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | ゲートウェイ | ✅ |
|
||||
| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | ゲートウェイ | ✅ |
|
||||
| [GiteeAI](https://ai.gitee.com/) | ゲートウェイ | ✅ |
|
||||
| [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | GPUプラットフォーム | ✅ |
|
||||
| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | GPUプラットフォーム | ✅ |
|
||||
| [ShengSuanYun](https://www.shengsuanyun.com/?from=CH_KYIPP758) | GPUプラットフォーム | ✅ |
|
||||
| [接口 AI](https://jiekou.ai/) | ゲートウェイ | ✅ |
|
||||
| [302.AI](https://share.302.ai/SuTG99) | ゲートウェイ | ✅ |
|
||||
|
||||
LangBot への貢献に対して、以下の [コード貢献者](https://github.com/langbot-app/LangBot/graphs/contributors) とコミュニティの他のメンバーに感謝します。
|
||||
[→ すべての統合を表示](https://docs.langbot.app/en/insight/features.html)
|
||||
|
||||
---
|
||||
|
||||
## 🌟 なぜ LangBot？
|
||||
|
||||
| ユースケース | LangBot の活用方法 |
|
||||
|----------|-------------------|
|
||||
| **カスタマーサポート** | ナレッジベースを活用して質問に回答するAIエージェントをSlack/Discord/Telegramにデプロイ |
|
||||
| **社内ツール** | n8n/Difyのワークフローを WeCom/DingTalk に接続し、業務プロセスを自動化 |
|
||||
| **コミュニティ管理** | AI搭載のコンテンツフィルタリングとインタラクションでQQ/Discordグループをモデレーション |
|
||||
| **マルチプラットフォーム展開** | 1つのボットで全プラットフォームに対応。単一のダッシュボードから管理 |
|
||||
|
||||
---
|
||||
|
||||
## 🎮 ライブデモ
|
||||
|
||||
**今すぐ試す:** https://demo.langbot.dev/
|
||||
- メール: `demo@langbot.app`
|
||||
- パスワード: `langbot123456`
|
||||
|
||||
*注意: 公開デモ環境です。機密情報を入力しないでください。*
|
||||
|
||||
---
|
||||
|
||||
## 🤝 コミュニティ
|
||||
|
||||
[](https://discord.gg/wdNEHETs87)
|
||||
|
||||
- 💬 [Discord コミュニティ](https://discord.gg/wdNEHETs87)
|
||||
|
||||
---
|
||||
|
||||
## ⭐ Star 推移
|
||||
|
||||
[](https://star-history.com/#langbot-app/LangBot&Date)
|
||||
|
||||
---
|
||||
|
||||
## 😘 コントリビューター
|
||||
|
||||
LangBot をより良くするために貢献してくださったすべての[コントリビューター](https://github.com/langbot-app/LangBot/graphs/contributors)に感謝します:
|
||||
|
||||
<a href="https://github.com/langbot-app/LangBot/graphs/contributors">
|
||||
<img src="https://contrib.rocks/image?repo=langbot-app/LangBot" />
|
||||
|
||||
@@ -323,3 +323,164 @@ class MonitoringRouterGroup(group.RouterGroup):
|
||||
return self.error(message=f'Message {message_id} not found', code=404)
|
||||
|
||||
return self.success(data=details)
|
||||
|
||||
@self.route('/export', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
|
||||
async def export_data() -> tuple[str, int]:
|
||||
"""Export monitoring data as CSV"""
|
||||
# Parse query parameters
|
||||
export_type = quart.request.args.get('type', 'messages')
|
||||
bot_ids = quart.request.args.getlist('botId')
|
||||
pipeline_ids = quart.request.args.getlist('pipelineId')
|
||||
start_time_str = quart.request.args.get('startTime')
|
||||
end_time_str = quart.request.args.get('endTime')
|
||||
limit = int(quart.request.args.get('limit', 100000))
|
||||
|
||||
# Parse datetime
|
||||
start_time = parse_iso_datetime(start_time_str)
|
||||
end_time = parse_iso_datetime(end_time_str)
|
||||
|
||||
# Get data based on export type
|
||||
if export_type == 'messages':
|
||||
data = await self.ap.monitoring_service.export_messages(
|
||||
bot_ids=bot_ids if bot_ids else None,
|
||||
pipeline_ids=pipeline_ids if pipeline_ids else None,
|
||||
start_time=start_time,
|
||||
end_time=end_time,
|
||||
limit=limit,
|
||||
)
|
||||
headers = [
|
||||
'id',
|
||||
'timestamp',
|
||||
'bot_id',
|
||||
'bot_name',
|
||||
'pipeline_id',
|
||||
'pipeline_name',
|
||||
'runner_name',
|
||||
'message_content',
|
||||
'message_text',
|
||||
'session_id',
|
||||
'status',
|
||||
'level',
|
||||
'platform',
|
||||
'user_id',
|
||||
]
|
||||
elif export_type == 'llm-calls':
|
||||
data = await self.ap.monitoring_service.export_llm_calls(
|
||||
bot_ids=bot_ids if bot_ids else None,
|
||||
pipeline_ids=pipeline_ids if pipeline_ids else None,
|
||||
start_time=start_time,
|
||||
end_time=end_time,
|
||||
limit=limit,
|
||||
)
|
||||
headers = [
|
||||
'id',
|
||||
'timestamp',
|
||||
'model_name',
|
||||
'input_tokens',
|
||||
'output_tokens',
|
||||
'total_tokens',
|
||||
'duration_ms',
|
||||
'cost',
|
||||
'status',
|
||||
'bot_id',
|
||||
'bot_name',
|
||||
'pipeline_id',
|
||||
'pipeline_name',
|
||||
'session_id',
|
||||
'message_id',
|
||||
'error_message',
|
||||
]
|
||||
elif export_type == 'embedding-calls':
|
||||
data = await self.ap.monitoring_service.export_embedding_calls(
|
||||
start_time=start_time,
|
||||
end_time=end_time,
|
||||
limit=limit,
|
||||
)
|
||||
headers = [
|
||||
'id',
|
||||
'timestamp',
|
||||
'model_name',
|
||||
'prompt_tokens',
|
||||
'total_tokens',
|
||||
'duration_ms',
|
||||
'input_count',
|
||||
'status',
|
||||
'error_message',
|
||||
'knowledge_base_id',
|
||||
'query_text',
|
||||
'session_id',
|
||||
'message_id',
|
||||
'call_type',
|
||||
]
|
||||
elif export_type == 'errors':
|
||||
data = await self.ap.monitoring_service.export_errors(
|
||||
bot_ids=bot_ids if bot_ids else None,
|
||||
pipeline_ids=pipeline_ids if pipeline_ids else None,
|
||||
start_time=start_time,
|
||||
end_time=end_time,
|
||||
limit=limit,
|
||||
)
|
||||
headers = [
|
||||
'id',
|
||||
'timestamp',
|
||||
'error_type',
|
||||
'error_message',
|
||||
'bot_id',
|
||||
'bot_name',
|
||||
'pipeline_id',
|
||||
'pipeline_name',
|
||||
'session_id',
|
||||
'message_id',
|
||||
'stack_trace',
|
||||
]
|
||||
elif export_type == 'sessions':
|
||||
data = await self.ap.monitoring_service.export_sessions(
|
||||
bot_ids=bot_ids if bot_ids else None,
|
||||
pipeline_ids=pipeline_ids if pipeline_ids else None,
|
||||
start_time=start_time,
|
||||
end_time=end_time,
|
||||
limit=limit,
|
||||
)
|
||||
headers = [
|
||||
'session_id',
|
||||
'bot_id',
|
||||
'bot_name',
|
||||
'pipeline_id',
|
||||
'pipeline_name',
|
||||
'message_count',
|
||||
'start_time',
|
||||
'last_activity',
|
||||
'is_active',
|
||||
'platform',
|
||||
'user_id',
|
||||
]
|
||||
else:
|
||||
return self.error(message=f'Invalid export type: {export_type}', code=400)
|
||||
|
||||
# Generate CSV content with UTF-8 BOM for Excel compatibility
|
||||
import io
|
||||
|
||||
output = io.StringIO()
|
||||
# Write UTF-8 BOM for Excel
|
||||
output.write('\ufeff')
|
||||
# Write header
|
||||
output.write(','.join(headers) + '\n')
|
||||
|
||||
# Escape and write each row
|
||||
for row in data:
|
||||
escaped_values = []
|
||||
for header in headers:
|
||||
value = row.get(header, '')
|
||||
escaped_values.append(self.ap.monitoring_service._escape_csv_field(value))
|
||||
output.write(','.join(escaped_values) + '\n')
|
||||
|
||||
csv_content = output.getvalue()
|
||||
|
||||
# Return as file download
|
||||
response = await quart.make_response(csv_content)
|
||||
response.headers['Content-Type'] = 'text/csv; charset=utf-8'
|
||||
response.headers['Content-Disposition'] = (
|
||||
f'attachment; filename="monitoring-{export_type}-{int(datetime.datetime.now().timestamp())}.csv"'
|
||||
)
|
||||
|
||||
return response, 200
|
||||
|
||||
@@ -794,3 +794,332 @@ class MonitoringService:
|
||||
},
|
||||
'errors': errors,
|
||||
}
|
||||
|
||||
# ========== Export Methods ==========
|
||||
|
||||
def _escape_csv_field(self, field: str | None) -> str:
|
||||
"""Escape a field for CSV output"""
|
||||
if field is None:
|
||||
return ''
|
||||
# Convert non-string types to string first
|
||||
if not isinstance(field, str):
|
||||
field = str(field)
|
||||
# Replace common escape sequences
|
||||
field = field.replace('\r\n', '\n').replace('\r', '\n')
|
||||
# If field contains comma, double quote, or newline, wrap in quotes
|
||||
if ',' in field or '"' in field or '\n' in field:
|
||||
# Escape double quotes by doubling them
|
||||
field = '"' + field.replace('"', '""') + '"'
|
||||
return field
|
||||
|
||||
def _format_timestamp(self, dt: datetime.datetime) -> str:
|
||||
"""Format datetime to ISO format string"""
|
||||
return dt.strftime('%Y-%m-%d %H:%M:%S')
|
||||
|
||||
def _extract_message_text(self, message_content: str) -> str:
|
||||
"""Extract plain text from message chain JSON"""
|
||||
if not message_content:
|
||||
return ''
|
||||
|
||||
try:
|
||||
import json
|
||||
|
||||
message_chain = json.loads(message_content)
|
||||
if not isinstance(message_chain, list):
|
||||
return message_content
|
||||
|
||||
text_parts = []
|
||||
for component in message_chain:
|
||||
if not isinstance(component, dict):
|
||||
continue
|
||||
component_type = component.get('type')
|
||||
if component_type == 'Plain':
|
||||
text = component.get('text', '')
|
||||
text_parts.append(text)
|
||||
elif component_type == 'At':
|
||||
display = component.get('display', '')
|
||||
target = component.get('target', '')
|
||||
if display:
|
||||
text_parts.append(f'@{display}')
|
||||
elif target:
|
||||
text_parts.append(f'@{target}')
|
||||
elif component_type == 'AtAll':
|
||||
text_parts.append('@All')
|
||||
elif component_type == 'Image':
|
||||
text_parts.append('[Image]')
|
||||
elif component_type == 'File':
|
||||
name = component.get('name', 'File')
|
||||
text_parts.append(f'[File: {name}]')
|
||||
elif component_type == 'Voice':
|
||||
length = component.get('length', 0)
|
||||
text_parts.append(f'[Voice {length}s]')
|
||||
elif component_type == 'Quote':
|
||||
# Quote content is in 'origin' field
|
||||
origin = component.get('origin', [])
|
||||
if isinstance(origin, list):
|
||||
for item in origin:
|
||||
if isinstance(item, dict) and item.get('type') == 'Plain':
|
||||
text_parts.append(f'> {item.get("text", "")}')
|
||||
elif component_type == 'Source':
|
||||
# Skip Source component
|
||||
continue
|
||||
else:
|
||||
# Other unknown types
|
||||
text_parts.append(f'[{component_type}]')
|
||||
|
||||
return ''.join(text_parts)
|
||||
except (json.JSONDecodeError, TypeError, KeyError):
|
||||
# If not valid JSON, return as-is
|
||||
return message_content
|
||||
|
||||
async def export_messages(
|
||||
self,
|
||||
bot_ids: list[str] | None = None,
|
||||
pipeline_ids: list[str] | None = None,
|
||||
start_time: datetime.datetime | None = None,
|
||||
end_time: datetime.datetime | None = None,
|
||||
limit: int = 100000,
|
||||
) -> list[dict]:
|
||||
"""Export messages as list of dictionaries for CSV conversion"""
|
||||
conditions = []
|
||||
|
||||
if bot_ids:
|
||||
conditions.append(persistence_monitoring.MonitoringMessage.bot_id.in_(bot_ids))
|
||||
if pipeline_ids:
|
||||
conditions.append(persistence_monitoring.MonitoringMessage.pipeline_id.in_(pipeline_ids))
|
||||
if start_time:
|
||||
conditions.append(persistence_monitoring.MonitoringMessage.timestamp >= start_time)
|
||||
if end_time:
|
||||
conditions.append(persistence_monitoring.MonitoringMessage.timestamp <= end_time)
|
||||
|
||||
query = sqlalchemy.select(persistence_monitoring.MonitoringMessage).order_by(
|
||||
persistence_monitoring.MonitoringMessage.timestamp.desc()
|
||||
)
|
||||
if conditions:
|
||||
query = query.where(sqlalchemy.and_(*conditions))
|
||||
|
||||
query = query.limit(limit)
|
||||
|
||||
result = await self.ap.persistence_mgr.execute_async(query)
|
||||
rows = result.all()
|
||||
|
||||
return [
|
||||
{
|
||||
'id': row[0].id if isinstance(row, tuple) else row.id,
|
||||
'timestamp': self._format_timestamp(row[0].timestamp if isinstance(row, tuple) else row.timestamp),
|
||||
'bot_id': row[0].bot_id if isinstance(row, tuple) else row.bot_id,
|
||||
'bot_name': row[0].bot_name if isinstance(row, tuple) else row.bot_name,
|
||||
'pipeline_id': row[0].pipeline_id if isinstance(row, tuple) else row.pipeline_id,
|
||||
'pipeline_name': row[0].pipeline_name if isinstance(row, tuple) else row.pipeline_name,
|
||||
'runner_name': row[0].runner_name if isinstance(row, tuple) else row.runner_name,
|
||||
'message_content': row[0].message_content if isinstance(row, tuple) else row.message_content,
|
||||
'message_text': self._extract_message_text(
|
||||
row[0].message_content if isinstance(row, tuple) else row.message_content
|
||||
),
|
||||
'session_id': row[0].session_id if isinstance(row, tuple) else row.session_id,
|
||||
'status': row[0].status if isinstance(row, tuple) else row.status,
|
||||
'level': row[0].level if isinstance(row, tuple) else row.level,
|
||||
'platform': row[0].platform if isinstance(row, tuple) else row.platform,
|
||||
'user_id': row[0].user_id if isinstance(row, tuple) else row.user_id,
|
||||
}
|
||||
for row in rows
|
||||
]
|
||||
|
||||
async def export_llm_calls(
|
||||
self,
|
||||
bot_ids: list[str] | None = None,
|
||||
pipeline_ids: list[str] | None = None,
|
||||
start_time: datetime.datetime | None = None,
|
||||
end_time: datetime.datetime | None = None,
|
||||
limit: int = 100000,
|
||||
) -> list[dict]:
|
||||
"""Export LLM calls as list of dictionaries for CSV conversion"""
|
||||
conditions = []
|
||||
|
||||
if bot_ids:
|
||||
conditions.append(persistence_monitoring.MonitoringLLMCall.bot_id.in_(bot_ids))
|
||||
if pipeline_ids:
|
||||
conditions.append(persistence_monitoring.MonitoringLLMCall.pipeline_id.in_(pipeline_ids))
|
||||
if start_time:
|
||||
conditions.append(persistence_monitoring.MonitoringLLMCall.timestamp >= start_time)
|
||||
if end_time:
|
||||
conditions.append(persistence_monitoring.MonitoringLLMCall.timestamp <= end_time)
|
||||
|
||||
query = sqlalchemy.select(persistence_monitoring.MonitoringLLMCall).order_by(
|
||||
persistence_monitoring.MonitoringLLMCall.timestamp.desc()
|
||||
)
|
||||
if conditions:
|
||||
query = query.where(sqlalchemy.and_(*conditions))
|
||||
|
||||
query = query.limit(limit)
|
||||
|
||||
result = await self.ap.persistence_mgr.execute_async(query)
|
||||
rows = result.all()
|
||||
|
||||
return [
|
||||
{
|
||||
'id': row[0].id if isinstance(row, tuple) else row.id,
|
||||
'timestamp': self._format_timestamp(row[0].timestamp if isinstance(row, tuple) else row.timestamp),
|
||||
'model_name': row[0].model_name if isinstance(row, tuple) else row.model_name,
|
||||
'input_tokens': row[0].input_tokens if isinstance(row, tuple) else row.input_tokens,
|
||||
'output_tokens': row[0].output_tokens if isinstance(row, tuple) else row.output_tokens,
|
||||
'total_tokens': row[0].total_tokens if isinstance(row, tuple) else row.total_tokens,
|
||||
'duration_ms': row[0].duration if isinstance(row, tuple) else row.duration,
|
||||
'cost': row[0].cost if isinstance(row, tuple) else row.cost,
|
||||
'status': row[0].status if isinstance(row, tuple) else row.status,
|
||||
'bot_id': row[0].bot_id if isinstance(row, tuple) else row.bot_id,
|
||||
'bot_name': row[0].bot_name if isinstance(row, tuple) else row.bot_name,
|
||||
'pipeline_id': row[0].pipeline_id if isinstance(row, tuple) else row.pipeline_id,
|
||||
'pipeline_name': row[0].pipeline_name if isinstance(row, tuple) else row.pipeline_name,
|
||||
'session_id': row[0].session_id if isinstance(row, tuple) else row.session_id,
|
||||
'message_id': row[0].message_id if isinstance(row, tuple) else row.message_id,
|
||||
'error_message': row[0].error_message if isinstance(row, tuple) else row.error_message,
|
||||
}
|
||||
for row in rows
|
||||
]
|
||||
|
||||
async def export_embedding_calls(
|
||||
self,
|
||||
start_time: datetime.datetime | None = None,
|
||||
end_time: datetime.datetime | None = None,
|
||||
knowledge_base_id: str | None = None,
|
||||
limit: int = 100000,
|
||||
) -> list[dict]:
|
||||
"""Export embedding calls as list of dictionaries for CSV conversion"""
|
||||
conditions = []
|
||||
|
||||
if start_time:
|
||||
conditions.append(persistence_monitoring.MonitoringEmbeddingCall.timestamp >= start_time)
|
||||
if end_time:
|
||||
conditions.append(persistence_monitoring.MonitoringEmbeddingCall.timestamp <= end_time)
|
||||
if knowledge_base_id:
|
||||
conditions.append(persistence_monitoring.MonitoringEmbeddingCall.knowledge_base_id == knowledge_base_id)
|
||||
|
||||
query = sqlalchemy.select(persistence_monitoring.MonitoringEmbeddingCall).order_by(
|
||||
persistence_monitoring.MonitoringEmbeddingCall.timestamp.desc()
|
||||
)
|
||||
if conditions:
|
||||
query = query.where(sqlalchemy.and_(*conditions))
|
||||
|
||||
query = query.limit(limit)
|
||||
|
||||
result = await self.ap.persistence_mgr.execute_async(query)
|
||||
rows = result.all()
|
||||
|
||||
return [
|
||||
{
|
||||
'id': row[0].id if isinstance(row, tuple) else row.id,
|
||||
'timestamp': self._format_timestamp(row[0].timestamp if isinstance(row, tuple) else row.timestamp),
|
||||
'model_name': row[0].model_name if isinstance(row, tuple) else row.model_name,
|
||||
'prompt_tokens': row[0].prompt_tokens if isinstance(row, tuple) else row.prompt_tokens,
|
||||
'total_tokens': row[0].total_tokens if isinstance(row, tuple) else row.total_tokens,
|
||||
'duration_ms': row[0].duration if isinstance(row, tuple) else row.duration,
|
||||
'input_count': row[0].input_count if isinstance(row, tuple) else row.input_count,
|
||||
'status': row[0].status if isinstance(row, tuple) else row.status,
|
||||
'error_message': row[0].error_message if isinstance(row, tuple) else row.error_message,
|
||||
'knowledge_base_id': row[0].knowledge_base_id if isinstance(row, tuple) else row.knowledge_base_id,
|
||||
'query_text': row[0].query_text if isinstance(row, tuple) else row.query_text,
|
||||
'session_id': row[0].session_id if isinstance(row, tuple) else row.session_id,
|
||||
'message_id': row[0].message_id if isinstance(row, tuple) else row.message_id,
|
||||
'call_type': row[0].call_type if isinstance(row, tuple) else row.call_type,
|
||||
}
|
||||
for row in rows
|
||||
]
|
||||
|
||||
async def export_errors(
|
||||
self,
|
||||
bot_ids: list[str] | None = None,
|
||||
pipeline_ids: list[str] | None = None,
|
||||
start_time: datetime.datetime | None = None,
|
||||
end_time: datetime.datetime | None = None,
|
||||
limit: int = 100000,
|
||||
) -> list[dict]:
|
||||
"""Export errors as list of dictionaries for CSV conversion"""
|
||||
conditions = []
|
||||
|
||||
if bot_ids:
|
||||
conditions.append(persistence_monitoring.MonitoringError.bot_id.in_(bot_ids))
|
||||
if pipeline_ids:
|
||||
conditions.append(persistence_monitoring.MonitoringError.pipeline_id.in_(pipeline_ids))
|
||||
if start_time:
|
||||
conditions.append(persistence_monitoring.MonitoringError.timestamp >= start_time)
|
||||
if end_time:
|
||||
conditions.append(persistence_monitoring.MonitoringError.timestamp <= end_time)
|
||||
|
||||
query = sqlalchemy.select(persistence_monitoring.MonitoringError).order_by(
|
||||
persistence_monitoring.MonitoringError.timestamp.desc()
|
||||
)
|
||||
if conditions:
|
||||
query = query.where(sqlalchemy.and_(*conditions))
|
||||
|
||||
query = query.limit(limit)
|
||||
|
||||
result = await self.ap.persistence_mgr.execute_async(query)
|
||||
rows = result.all()
|
||||
|
||||
return [
|
||||
{
|
||||
'id': row[0].id if isinstance(row, tuple) else row.id,
|
||||
'timestamp': self._format_timestamp(row[0].timestamp if isinstance(row, tuple) else row.timestamp),
|
||||
'error_type': row[0].error_type if isinstance(row, tuple) else row.error_type,
|
||||
'error_message': row[0].error_message if isinstance(row, tuple) else row.error_message,
|
||||
'bot_id': row[0].bot_id if isinstance(row, tuple) else row.bot_id,
|
||||
'bot_name': row[0].bot_name if isinstance(row, tuple) else row.bot_name,
|
||||
'pipeline_id': row[0].pipeline_id if isinstance(row, tuple) else row.pipeline_id,
|
||||
'pipeline_name': row[0].pipeline_name if isinstance(row, tuple) else row.pipeline_name,
|
||||
'session_id': row[0].session_id if isinstance(row, tuple) else row.session_id,
|
||||
'message_id': row[0].message_id if isinstance(row, tuple) else row.message_id,
|
||||
'stack_trace': row[0].stack_trace if isinstance(row, tuple) else row.stack_trace,
|
||||
}
|
||||
for row in rows
|
||||
]
|
||||
|
||||
async def export_sessions(
|
||||
self,
|
||||
bot_ids: list[str] | None = None,
|
||||
pipeline_ids: list[str] | None = None,
|
||||
start_time: datetime.datetime | None = None,
|
||||
end_time: datetime.datetime | None = None,
|
||||
limit: int = 100000,
|
||||
) -> list[dict]:
|
||||
"""Export sessions as list of dictionaries for CSV conversion"""
|
||||
conditions = []
|
||||
|
||||
if bot_ids:
|
||||
conditions.append(persistence_monitoring.MonitoringSession.bot_id.in_(bot_ids))
|
||||
if pipeline_ids:
|
||||
conditions.append(persistence_monitoring.MonitoringSession.pipeline_id.in_(pipeline_ids))
|
||||
if start_time:
|
||||
conditions.append(persistence_monitoring.MonitoringSession.start_time >= start_time)
|
||||
if end_time:
|
||||
conditions.append(persistence_monitoring.MonitoringSession.start_time <= end_time)
|
||||
|
||||
query = sqlalchemy.select(persistence_monitoring.MonitoringSession).order_by(
|
||||
persistence_monitoring.MonitoringSession.last_activity.desc()
|
||||
)
|
||||
if conditions:
|
||||
query = query.where(sqlalchemy.and_(*conditions))
|
||||
|
||||
query = query.limit(limit)
|
||||
|
||||
result = await self.ap.persistence_mgr.execute_async(query)
|
||||
rows = result.all()
|
||||
|
||||
return [
|
||||
{
|
||||
'session_id': row[0].session_id if isinstance(row, tuple) else row.session_id,
|
||||
'bot_id': row[0].bot_id if isinstance(row, tuple) else row.bot_id,
|
||||
'bot_name': row[0].bot_name if isinstance(row, tuple) else row.bot_name,
|
||||
'pipeline_id': row[0].pipeline_id if isinstance(row, tuple) else row.pipeline_id,
|
||||
'pipeline_name': row[0].pipeline_name if isinstance(row, tuple) else row.pipeline_name,
|
||||
'message_count': row[0].message_count if isinstance(row, tuple) else row.message_count,
|
||||
'start_time': self._format_timestamp(row[0].start_time if isinstance(row, tuple) else row.start_time),
|
||||
'last_activity': self._format_timestamp(
|
||||
row[0].last_activity if isinstance(row, tuple) else row.last_activity
|
||||
),
|
||||
'is_active': str(row[0].is_active if isinstance(row, tuple) else row.is_active),
|
||||
'platform': row[0].platform if isinstance(row, tuple) else row.platform,
|
||||
'user_id': row[0].user_id if isinstance(row, tuple) else row.user_id,
|
||||
}
|
||||
for row in rows
|
||||
]
|
||||
|
||||
262
uv.lock
generated
262
uv.lock
generated
@@ -907,61 +907,61 @@ toml = [
|
||||
|
||||
[[package]]
|
||||
name = "cryptography"
|
||||
version = "46.0.4"
|
||||
version = "46.0.5"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "cffi", marker = "platform_python_implementation != 'PyPy'" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/78/19/f748958276519adf6a0c1e79e7b8860b4830dda55ccdf29f2719b5fc499c/cryptography-46.0.4.tar.gz", hash = "sha256:bfd019f60f8abc2ed1b9be4ddc21cfef059c841d86d710bb69909a688cbb8f59", size = 749301, upload-time = "2026-01-28T00:24:37.379Z" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/60/04/ee2a9e8542e4fa2773b81771ff8349ff19cdd56b7258a0cc442639052edb/cryptography-46.0.5.tar.gz", hash = "sha256:abace499247268e3757271b2f1e244b36b06f8515cf27c4d49468fc9eb16e93d", size = 750064, upload-time = "2026-02-10T19:18:38.255Z" }
|
||||
wheels = [
|
||||
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||||
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{ url = "https://files.pythonhosted.org/packages/00/98/fc53ab36da80b88df0967896b6c4b4cd948a0dc5aa40a754266aa3ae48b3/pillow-12.1.1-pp311-pypy311_pp73-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:f975aa7ef9684ce7e2c18a3aa8f8e2106ce1e46b94ab713d156b2898811651d3", size = 5313850, upload-time = "2026-02-11T04:23:00.554Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/30/02/00fa585abfd9fe9d73e5f6e554dc36cc2b842898cbfc46d70353dae227f8/pillow-12.1.1-pp311-pypy311_pp73-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:8089c852a56c2966cf18835db62d9b34fef7ba74c726ad943928d494fa7f4735", size = 5963343, upload-time = "2026-02-11T04:23:02.934Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/f2/26/c56ce33ca856e358d27fda9676c055395abddb82c35ac0f593877ed4562e/pillow-12.1.1-pp311-pypy311_pp73-win_amd64.whl", hash = "sha256:cb9bb857b2d057c6dfc72ac5f3b44836924ba15721882ef103cecb40d002d80e", size = 7029880, upload-time = "2026-02-11T04:23:04.783Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
|
||||
@@ -15,7 +15,6 @@ const config = {
|
||||
singleQuote: true,
|
||||
// 大括号前后空格
|
||||
bracketSpacing: true,
|
||||
attributeVerticalAlignment: 'auto',
|
||||
trailingComma: 'all',
|
||||
};
|
||||
|
||||
|
||||
@@ -44,7 +44,7 @@
|
||||
"@radix-ui/react-tooltip": "^1.2.7",
|
||||
"@tailwindcss/postcss": "^4.1.5",
|
||||
"@tanstack/react-table": "^8.21.3",
|
||||
"axios": "^1.12.0",
|
||||
"axios": "^1.13.5",
|
||||
"class-variance-authority": "^0.7.1",
|
||||
"clsx": "^2.1.1",
|
||||
"highlight.js": "^11.11.1",
|
||||
|
||||
8
web/pnpm-lock.yaml
generated
8
web/pnpm-lock.yaml
generated
@@ -78,8 +78,8 @@ dependencies:
|
||||
specifier: ^8.21.3
|
||||
version: 8.21.3(react-dom@19.2.1)(react@19.2.1)
|
||||
axios:
|
||||
specifier: ^1.12.0
|
||||
version: 1.13.4
|
||||
specifier: ^1.13.5
|
||||
version: 1.13.5
|
||||
class-variance-authority:
|
||||
specifier: ^0.7.1
|
||||
version: 0.7.1
|
||||
@@ -2608,8 +2608,8 @@ packages:
|
||||
engines: {node: '>=4'}
|
||||
dev: true
|
||||
|
||||
/axios@1.13.4:
|
||||
resolution: {integrity: sha512-1wVkUaAO6WyaYtCkcYCOx12ZgpGf9Zif+qXa4n+oYzK558YryKqiL6UWwd5DqiH3VRW0GYhTZQ/vlgJrCoNQlg==}
|
||||
/axios@1.13.5:
|
||||
resolution: {integrity: sha512-cz4ur7Vb0xS4/KUN0tPWe44eqxrIu31me+fbang3ijiNscE129POzipJJA6zniq2C/Z6sJCjMimjS8Lc/GAs8Q==}
|
||||
dependencies:
|
||||
follow-redirects: 1.15.11
|
||||
form-data: 4.0.5
|
||||
|
||||
227
web/src/app/home/monitoring/components/ExportDropdown.tsx
Normal file
227
web/src/app/home/monitoring/components/ExportDropdown.tsx
Normal file
@@ -0,0 +1,227 @@
|
||||
'use client';
|
||||
|
||||
import React, { useState } from 'react';
|
||||
import { useTranslation } from 'react-i18next';
|
||||
import {
|
||||
Download,
|
||||
FileText,
|
||||
Database,
|
||||
AlertCircle,
|
||||
Users,
|
||||
Layers,
|
||||
} from 'lucide-react';
|
||||
import { Button } from '@/components/ui/button';
|
||||
import {
|
||||
DropdownMenu,
|
||||
DropdownMenuContent,
|
||||
DropdownMenuItem,
|
||||
DropdownMenuLabel,
|
||||
DropdownMenuSeparator,
|
||||
DropdownMenuTrigger,
|
||||
} from '@/components/ui/dropdown-menu';
|
||||
import { backendClient } from '@/app/infra/http';
|
||||
import { FilterState } from '../types/monitoring';
|
||||
|
||||
export type ExportType =
|
||||
| 'messages'
|
||||
| 'llm-calls'
|
||||
| 'embedding-calls'
|
||||
| 'errors'
|
||||
| 'sessions';
|
||||
|
||||
interface ExportDropdownProps {
|
||||
filterState: FilterState;
|
||||
}
|
||||
|
||||
export function ExportDropdown({ filterState }: ExportDropdownProps) {
|
||||
const { t } = useTranslation();
|
||||
const [exporting, setExporting] = useState<ExportType | null>(null);
|
||||
|
||||
const getDateRangeParams = (): { startTime: string; endTime: string } => {
|
||||
const now = new Date();
|
||||
let startTime: Date;
|
||||
let endTime: Date = now;
|
||||
|
||||
switch (filterState.timeRange) {
|
||||
case 'lastHour':
|
||||
startTime = new Date(now.getTime() - 60 * 60 * 1000);
|
||||
break;
|
||||
case 'last6Hours':
|
||||
startTime = new Date(now.getTime() - 6 * 60 * 60 * 1000);
|
||||
break;
|
||||
case 'last24Hours':
|
||||
startTime = new Date(now.getTime() - 24 * 60 * 60 * 1000);
|
||||
break;
|
||||
case 'last7Days':
|
||||
startTime = new Date(now.getTime() - 7 * 24 * 60 * 60 * 1000);
|
||||
break;
|
||||
case 'last30Days':
|
||||
startTime = new Date(now.getTime() - 30 * 24 * 60 * 60 * 1000);
|
||||
break;
|
||||
case 'custom':
|
||||
if (filterState.customDateRange) {
|
||||
startTime = filterState.customDateRange.from;
|
||||
endTime = filterState.customDateRange.to;
|
||||
} else {
|
||||
startTime = new Date(now.getTime() - 24 * 60 * 60 * 1000);
|
||||
}
|
||||
break;
|
||||
default:
|
||||
startTime = new Date(now.getTime() - 24 * 60 * 60 * 1000);
|
||||
}
|
||||
|
||||
return {
|
||||
startTime: startTime.toISOString(),
|
||||
endTime: endTime.toISOString(),
|
||||
};
|
||||
};
|
||||
|
||||
const handleExport = async (type: ExportType) => {
|
||||
setExporting(type);
|
||||
try {
|
||||
const { startTime, endTime } = getDateRangeParams();
|
||||
const params = new URLSearchParams({
|
||||
type,
|
||||
startTime,
|
||||
endTime,
|
||||
});
|
||||
|
||||
if (filterState.selectedBots.length > 0) {
|
||||
filterState.selectedBots.forEach((botId) => {
|
||||
params.append('botId', botId);
|
||||
});
|
||||
}
|
||||
|
||||
if (filterState.selectedPipelines.length > 0) {
|
||||
filterState.selectedPipelines.forEach((pipelineId) => {
|
||||
params.append('pipelineId', pipelineId);
|
||||
});
|
||||
}
|
||||
|
||||
// Use backendClient's downloadFile method for blob response
|
||||
const response = await backendClient.downloadFile(
|
||||
`/api/v1/monitoring/export?${params.toString()}`,
|
||||
);
|
||||
|
||||
// Get filename from content-disposition header
|
||||
const contentDisposition = response.headers['content-disposition'];
|
||||
let filename = `monitoring-${type}-${Date.now()}.csv`;
|
||||
if (contentDisposition) {
|
||||
const filenameMatch = contentDisposition.match(
|
||||
/filename="?([^";\n]+)"?/,
|
||||
);
|
||||
if (filenameMatch) {
|
||||
filename = filenameMatch[1];
|
||||
}
|
||||
}
|
||||
|
||||
// Create download link
|
||||
const blob = new Blob([response.data], {
|
||||
type: 'text/csv;charset=utf-8;',
|
||||
});
|
||||
const url = window.URL.createObjectURL(blob);
|
||||
const link = document.createElement('a');
|
||||
link.href = url;
|
||||
link.setAttribute('download', filename);
|
||||
document.body.appendChild(link);
|
||||
link.click();
|
||||
document.body.removeChild(link);
|
||||
window.URL.revokeObjectURL(url);
|
||||
} catch (error) {
|
||||
console.error('Failed to export data:', error);
|
||||
} finally {
|
||||
setExporting(null);
|
||||
}
|
||||
};
|
||||
|
||||
const exportOptions: {
|
||||
type: ExportType;
|
||||
label: string;
|
||||
icon: React.ReactNode;
|
||||
}[] = [
|
||||
{
|
||||
type: 'messages',
|
||||
label: t('monitoring.export.messages'),
|
||||
icon: <FileText className="w-4 h-4 mr-2" />,
|
||||
},
|
||||
{
|
||||
type: 'llm-calls',
|
||||
label: t('monitoring.export.llmCalls'),
|
||||
icon: <Database className="w-4 h-4 mr-2" />,
|
||||
},
|
||||
{
|
||||
type: 'embedding-calls',
|
||||
label: t('monitoring.export.embeddingCalls'),
|
||||
icon: <Layers className="w-4 h-4 mr-2" />,
|
||||
},
|
||||
{
|
||||
type: 'errors',
|
||||
label: t('monitoring.export.errors'),
|
||||
icon: <AlertCircle className="w-4 h-4 mr-2" />,
|
||||
},
|
||||
{
|
||||
type: 'sessions',
|
||||
label: t('monitoring.export.sessions'),
|
||||
icon: <Users className="w-4 h-4 mr-2" />,
|
||||
},
|
||||
];
|
||||
|
||||
return (
|
||||
<DropdownMenu>
|
||||
<DropdownMenuTrigger asChild>
|
||||
<Button
|
||||
variant="outline"
|
||||
size="sm"
|
||||
className="bg-white dark:bg-[#2a2a2e] hover:bg-gray-50 dark:hover:bg-gray-800 border-gray-300 dark:border-gray-600 shadow-sm flex-shrink-0"
|
||||
disabled={exporting !== null}
|
||||
>
|
||||
{exporting ? (
|
||||
<>
|
||||
<svg
|
||||
className="w-4 h-4 mr-2 animate-spin"
|
||||
xmlns="http://www.w3.org/2000/svg"
|
||||
fill="none"
|
||||
viewBox="0 0 24 24"
|
||||
>
|
||||
<circle
|
||||
className="opacity-25"
|
||||
cx="12"
|
||||
cy="12"
|
||||
r="10"
|
||||
stroke="currentColor"
|
||||
strokeWidth="4"
|
||||
/>
|
||||
<path
|
||||
className="opacity-75"
|
||||
fill="currentColor"
|
||||
d="M4 12a8 8 0 018-8V0C5.373 0 0 5.373 0 12h4zm2 5.291A7.962 7.962 0 014 12H0c0 3.042 1.135 5.824 3 7.938l3-2.647z"
|
||||
/>
|
||||
</svg>
|
||||
{t('monitoring.export.exporting')}
|
||||
</>
|
||||
) : (
|
||||
<>
|
||||
<Download className="w-4 h-4 mr-2" />
|
||||
{t('monitoring.exportData')}
|
||||
</>
|
||||
)}
|
||||
</Button>
|
||||
</DropdownMenuTrigger>
|
||||
<DropdownMenuContent align="end" className="w-48">
|
||||
<DropdownMenuLabel>{t('monitoring.export.title')}</DropdownMenuLabel>
|
||||
<DropdownMenuSeparator />
|
||||
{exportOptions.map((option) => (
|
||||
<DropdownMenuItem
|
||||
key={option.type}
|
||||
onClick={() => handleExport(option.type)}
|
||||
disabled={exporting !== null}
|
||||
className="cursor-pointer"
|
||||
>
|
||||
{option.icon}
|
||||
{option.label}
|
||||
</DropdownMenuItem>
|
||||
))}
|
||||
</DropdownMenuContent>
|
||||
</DropdownMenu>
|
||||
);
|
||||
}
|
||||
@@ -74,7 +74,10 @@ export default function TrafficChart({
|
||||
// <= 7 days: 4-hour buckets
|
||||
bucketSize = 4 * 60 * 60 * 1000;
|
||||
formatTime = (date) =>
|
||||
`${date.toLocaleDateString([], { month: 'short', day: 'numeric' })} ${date.toLocaleTimeString([], { hour: '2-digit' })}`;
|
||||
`${date.toLocaleDateString([], {
|
||||
month: 'short',
|
||||
day: 'numeric',
|
||||
})} ${date.toLocaleTimeString([], { hour: '2-digit' })}`;
|
||||
} else {
|
||||
// > 7 days: 1-day buckets
|
||||
bucketSize = 24 * 60 * 60 * 1000;
|
||||
|
||||
@@ -7,6 +7,7 @@ import { Button } from '@/components/ui/button';
|
||||
import { ChevronRight, ChevronDown, ExternalLink } from 'lucide-react';
|
||||
import OverviewCards from './components/overview-cards/OverviewCards';
|
||||
import MonitoringFilters from './components/filters/MonitoringFilters';
|
||||
import { ExportDropdown } from './components/ExportDropdown';
|
||||
import { useMonitoringFilters } from './hooks/useMonitoringFilters';
|
||||
import { useMonitoringData } from './hooks/useMonitoringData';
|
||||
import { MessageDetailsCard } from './components/MessageDetailsCard';
|
||||
@@ -200,22 +201,25 @@ function MonitoringPageContent() {
|
||||
onPipelinesChange={setSelectedPipelines}
|
||||
onTimeRangeChange={setTimeRange}
|
||||
/>
|
||||
<Button
|
||||
variant="outline"
|
||||
size="sm"
|
||||
onClick={refetch}
|
||||
className="bg-white dark:bg-[#2a2a2e] hover:bg-gray-50 dark:hover:bg-gray-800 border-gray-300 dark:border-gray-600 shadow-sm flex-shrink-0"
|
||||
>
|
||||
<svg
|
||||
className="w-4 h-4 mr-2"
|
||||
xmlns="http://www.w3.org/2000/svg"
|
||||
viewBox="0 0 24 24"
|
||||
fill="currentColor"
|
||||
<div className="flex items-center gap-2">
|
||||
<ExportDropdown filterState={filterState} />
|
||||
<Button
|
||||
variant="outline"
|
||||
size="sm"
|
||||
onClick={refetch}
|
||||
className="bg-white dark:bg-[#2a2a2e] hover:bg-gray-50 dark:hover:bg-gray-800 border-gray-300 dark:border-gray-600 shadow-sm flex-shrink-0"
|
||||
>
|
||||
<path d="M5.46257 4.43262C7.21556 2.91688 9.5007 2 12 2C17.5228 2 22 6.47715 22 12C22 14.1361 21.3302 16.1158 20.1892 17.7406L17 12H20C20 7.58172 16.4183 4 12 4C9.84982 4 7.89777 4.84827 6.46023 6.22842L5.46257 4.43262ZM18.5374 19.5674C16.7844 21.0831 14.4993 22 12 22C6.47715 22 2 17.5228 2 12C2 9.86386 2.66979 7.88416 3.8108 6.25944L7 12H4C4 16.4183 7.58172 20 12 20C14.1502 20 16.1022 19.1517 17.5398 17.7716L18.5374 19.5674Z"></path>
|
||||
</svg>
|
||||
{t('monitoring.refreshData')}
|
||||
</Button>
|
||||
<svg
|
||||
className="w-4 h-4 mr-2"
|
||||
xmlns="http://www.w3.org/2000/svg"
|
||||
viewBox="0 0 24 24"
|
||||
fill="currentColor"
|
||||
>
|
||||
<path d="M5.46257 4.43262C7.21556 2.91688 9.5007 2 12 2C17.5228 2 22 6.47715 22 12C22 14.1361 21.3302 16.1158 20.1892 17.7406L17 12H20C20 7.58172 16.4183 4 12 4C9.84982 4 7.89777 4.84827 6.46023 6.22842L5.46257 4.43262ZM18.5374 19.5674C16.7844 21.0831 14.4993 22 12 22C6.47715 22 2 17.5228 2 12C2 9.86386 2.66979 7.88416 3.8108 6.25944L7 12H4C4 16.4183 7.58172 20 12 20C14.1502 20 16.1022 19.1517 17.5398 17.7716L18.5374 19.5674Z"></path>
|
||||
</svg>
|
||||
{t('monitoring.refreshData')}
|
||||
</Button>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
@@ -389,7 +389,9 @@ const PluginInstalledComponent = forwardRef<PluginInstalledComponentRef>(
|
||||
<DialogHeader className="px-6 pt-6 pb-2 border-b">
|
||||
<DialogTitle>
|
||||
{readmePlugin &&
|
||||
`${readmePlugin.author}/${readmePlugin.name} - ${t('plugins.readme')}`}
|
||||
`${readmePlugin.author}/${readmePlugin.name} - ${t(
|
||||
'plugins.readme',
|
||||
)}`}
|
||||
</DialogTitle>
|
||||
</DialogHeader>
|
||||
<div className="flex-1 overflow-y-auto">
|
||||
|
||||
@@ -206,4 +206,19 @@ export abstract class BaseHttpClient {
|
||||
...config,
|
||||
});
|
||||
}
|
||||
|
||||
public async downloadFile(
|
||||
url: string,
|
||||
config?: RequestConfig,
|
||||
): Promise<AxiosResponse<Blob>> {
|
||||
try {
|
||||
const response = await this.instance.get<Blob>(url, {
|
||||
responseType: 'blob',
|
||||
...config,
|
||||
});
|
||||
return response;
|
||||
} catch (error) {
|
||||
return this.handleError(error as object);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
@@ -952,6 +952,15 @@ const enUS = {
|
||||
viewMonitoring: 'View Monitoring',
|
||||
refreshData: 'Refresh Data',
|
||||
exportData: 'Export Data',
|
||||
export: {
|
||||
title: 'Export Data',
|
||||
exporting: 'Exporting...',
|
||||
messages: 'Messages',
|
||||
llmCalls: 'LLM Calls',
|
||||
embeddingCalls: 'Embedding Calls',
|
||||
errors: 'Error Logs',
|
||||
sessions: 'Sessions',
|
||||
},
|
||||
},
|
||||
};
|
||||
|
||||
|
||||
@@ -939,6 +939,15 @@ const jaJP = {
|
||||
viewMonitoring: 'モニタリングを表示',
|
||||
refreshData: 'データを更新',
|
||||
exportData: 'データをエクスポート',
|
||||
export: {
|
||||
title: 'データをエクスポート',
|
||||
exporting: 'エクスポート中...',
|
||||
messages: 'メッセージ',
|
||||
llmCalls: 'LLM コール',
|
||||
embeddingCalls: 'Embedding コール',
|
||||
errors: 'エラーログ',
|
||||
sessions: 'セッション',
|
||||
},
|
||||
},
|
||||
};
|
||||
|
||||
|
||||
@@ -912,6 +912,15 @@ const zhHans = {
|
||||
viewMonitoring: '查看日志监控',
|
||||
refreshData: '刷新数据',
|
||||
exportData: '导出数据',
|
||||
export: {
|
||||
title: '导出数据',
|
||||
exporting: '导出中...',
|
||||
messages: '消息记录',
|
||||
llmCalls: 'LLM 调用',
|
||||
embeddingCalls: 'Embedding 调用',
|
||||
errors: '错误日志',
|
||||
sessions: '会话记录',
|
||||
},
|
||||
},
|
||||
};
|
||||
|
||||
|
||||
@@ -887,6 +887,15 @@ const zhHant = {
|
||||
viewMonitoring: '查看日誌監控',
|
||||
refreshData: '重新整理資料',
|
||||
exportData: '匯出資料',
|
||||
export: {
|
||||
title: '匯出資料',
|
||||
exporting: '匯出中...',
|
||||
messages: '訊息記錄',
|
||||
llmCalls: 'LLM 呼叫',
|
||||
embeddingCalls: 'Embedding 呼叫',
|
||||
errors: '錯誤日誌',
|
||||
sessions: '會話記錄',
|
||||
},
|
||||
},
|
||||
};
|
||||
|
||||
|
||||
Reference in New Issue
Block a user