mirror of
https://github.com/langbot-app/LangBot.git
synced 2026-06-02 12:05:54 +00:00
Compare commits
94 Commits
copilot/fi
...
v4.8.7
| Author | SHA1 | Date | |
|---|---|---|---|
|
b34ebf85a6 | ||
|
|
06d3298cde | ||
|
|
614621ab7b | ||
|
|
8600d0a8e7 | ||
|
|
b83e6a53be | ||
|
|
88132dff8a | ||
|
|
2dc5999583 | ||
|
|
73461814c9 | ||
|
|
210e5e50d3 | ||
|
|
4fd488b97a | ||
|
|
422a34ead4 | ||
|
|
02a1036d63 | ||
|
|
2d837c9cb4 | ||
|
|
2ded774747 | ||
|
|
d9a630b8c1 | ||
|
|
b8df0dbd7f | ||
|
|
298437f352 | ||
|
|
94d72c378c | ||
|
|
f09ba6a0e3 | ||
|
|
1eda076b93 | ||
|
|
d6c10763a8 | ||
|
|
9df50d2cab | ||
|
|
6c6b510a0a | ||
|
|
063dc6fe97 | ||
|
|
42caae1bcf | ||
|
|
aa09a27a63 | ||
|
|
96e32a10e2 | ||
|
|
9a9f0eaa7d | ||
|
|
f5dea3c64c | ||
|
|
e213046302 | ||
|
|
41d31d77d8 | ||
|
|
6fb7fc80cc | ||
|
|
7bee5ff2f8 | ||
|
|
afe82ebdfd | ||
|
|
65c10ea54b | ||
|
|
ff0023c6c2 | ||
|
|
0e17d869ab | ||
|
|
7ec41bb91a | ||
|
|
da164c214e | ||
|
|
32a5de9bbb | ||
|
|
1b12b1fc35 | ||
|
|
caa1ed9d6a | ||
|
|
05f40e72ff | ||
|
|
27fb22d7be | ||
|
|
ca504384d2 | ||
|
|
b7e1e43fbd | ||
|
|
deabb19389 | ||
|
|
809035daac | ||
|
|
1eac87b89f | ||
|
|
70a2d137f0 | ||
|
|
c72b785c1f | ||
|
|
8588199640 | ||
|
|
2e42cd2faf | ||
|
|
7b3555af45 | ||
|
|
e12a77ca05 | ||
|
|
9ce3ad8300 | ||
|
|
1f60d9c3d6 | ||
|
|
d855d29c15 | ||
|
|
18083e9160 | ||
|
|
7f9e8ecac1 | ||
|
|
995c852f0a | ||
|
|
682962cc47 | ||
|
|
24e90a7f9b | ||
|
|
6a5a7182db | ||
|
|
c581c8e809 | ||
|
|
ffd2423920 | ||
|
|
c388339bd5 | ||
|
|
28492a62bb | ||
|
|
6a687ebeeb | ||
|
|
29dfae1518 | ||
|
|
791877d391 | ||
|
|
8fd0c3cc18 | ||
|
|
10dd8c86d0 | ||
|
|
c2574bdd3a | ||
|
|
d2d7892325 | ||
|
|
6d858475d7 | ||
|
|
59d55b382d | ||
|
|
8c17e55913 | ||
|
|
af509fe61f | ||
|
|
87e2a2099a | ||
|
|
3f22f62332 | ||
|
|
d1ee5f931a | ||
|
|
35506dd2bb | ||
|
|
2f06321ebf | ||
|
|
023281ae56 | ||
|
|
50dff55217 | ||
|
|
3204292360 | ||
|
|
f4ae829f59 | ||
|
|
3af8c13fab | ||
|
|
a8f7924867 | ||
|
|
77047e87d6 | ||
|
|
24d865bcd3 | ||
|
|
81ec7c201c | ||
|
|
ee2d4e3ab9 |
2
.github/ISSUE_TEMPLATE/bug-report.yml
vendored
2
.github/ISSUE_TEMPLATE/bug-report.yml
vendored
@@ -19,7 +19,7 @@ body:
|
||||
- type: textarea
|
||||
attributes:
|
||||
label: 复现步骤
|
||||
description: 提供越多信息，我们会越快解决问题，建议多提供配置截图；**如果你不认真填写（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
|
||||
|
||||
2
.github/ISSUE_TEMPLATE/bug-report_en.yml
vendored
2
.github/ISSUE_TEMPLATE/bug-report_en.yml
vendored
@@ -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
|
||||
|
||||
235
README.md
235
README.md
@@ -1,49 +1,69 @@
|
||||
|
||||
<p align="center">
|
||||
<a href="https://langbot.app">
|
||||
<img width="130" src="https://docs.langbot.app/langbot-logo.png" alt="LangBot"/>
|
||||
<img width="130" src="res/logo-blue.png" alt="LangBot"/>
|
||||
</a>
|
||||
|
||||
<div align="center">
|
||||
|
||||
<a href="https://hellogithub.com/repository/langbot-app/LangBot" target="_blank"><img src="https://abroad.hellogithub.com/v1/widgets/recommend.svg?rid=5ce8ae2aa4f74316bf393b57b952433c&claim_uid=gtmc6YWjMZkT21R" alt="Featured｜HelloGitHub" style="width: 250px; height: 54px;" width="250" height="54" /></a>
|
||||
<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>使用 LangBot 快速构建、调试、部署即时通信机器人。</h3>
|
||||
<h3>Production-grade platform for building agentic IM bots.</h3>
|
||||
<h4>Quickly build, debug, and ship AI bots to Slack, Discord, Telegram, WeChat, and more.</h4>
|
||||
|
||||
[English](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)
|
||||
English / [简体中文](README_CN.md) / [繁體中文](README_TW.md) / [日本語](README_JP.md) / [Español](README_ES.md) / [Français](README_FR.md) / [한국어](README_KO.md) / [Русский](README_RU.md) / [Tiếng Việt](README_VI.md)
|
||||
|
||||
[](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://gitcode.com/RockChinQ/LangBot)
|
||||
[](https://github.com/langbot-app/LangBot/stargazers)
|
||||
|
||||
<a href="https://langbot.app">项目主页</a> ｜
|
||||
<a href="https://docs.langbot.app/zh/insight/features.html">规格特性</a> ｜
|
||||
<a href="https://docs.langbot.app/zh/insight/guide.html">部署文档</a> ｜
|
||||
<a href="https://docs.langbot.app/zh/tags/readme.html">API 集成</a> ｜
|
||||
<a href="https://space.langbot.app">插件市场</a> ｜
|
||||
<a href="https://langbot.featurebase.app/roadmap">路线图</a>
|
||||
<a href="https://langbot.app">Website</a> ｜
|
||||
<a href="https://docs.langbot.app/en/insight/features">Features</a> ｜
|
||||
<a href="https://docs.langbot.app/en/insight/guide">Docs</a> ｜
|
||||
<a href="https://docs.langbot.app/en/tags/readme">API</a> ｜
|
||||
<a href="https://space.langbot.app/cloud">Cloud</a> ｜
|
||||
<a href="https://space.langbot.app">Plugin Market</a> ｜
|
||||
<a href="https://langbot.featurebase.app/roadmap">Roadmap</a>
|
||||
|
||||
</div>
|
||||
|
||||
</p>
|
||||
|
||||
---
|
||||
|
||||
## 📦 开始使用
|
||||
## What is LangBot?
|
||||
|
||||
#### 快速部署
|
||||
LangBot is an **open-source, production-grade platform** for building AI-powered instant messaging bots. It connects Large Language Models (LLMs) to any chat platform, enabling you to create intelligent agents that can converse, execute tasks, and integrate with your existing workflows.
|
||||
|
||||
使用 `uvx` 一键启动（需要先安装 [uv](https://docs.astral.sh/uv/getting-started/installation/)）：
|
||||
### Key Capabilities
|
||||
|
||||
- **AI Conversations & Agents** — Multi-turn dialogues, tool calling, multi-modal support, streaming output. Built-in RAG (knowledge base) with deep integration to [Dify](https://dify.ai), [Coze](https://coze.com), [n8n](https://n8n.io), [Langflow](https://langflow.org).
|
||||
- **Universal IM Platform Support** — One codebase for Discord, Telegram, Slack, LINE, QQ, WeChat, WeCom, Lark, DingTalk, KOOK.
|
||||
- **Production-Ready** — Access control, rate limiting, sensitive word filtering, comprehensive monitoring, and exception handling. Trusted by enterprises.
|
||||
- **Plugin Ecosystem** — Hundreds of plugins, event-driven architecture, component extensions, and [MCP protocol](https://modelcontextprotocol.io/) support.
|
||||
- **Web Management Panel** — Configure, manage, and monitor your bots through an intuitive browser interface. No YAML editing required.
|
||||
- **Multi-Pipeline Architecture** — Different bots for different scenarios, with comprehensive monitoring and exception handling.
|
||||
|
||||
[→ Learn more about all features](https://docs.langbot.app/en/insight/features)
|
||||
|
||||
---
|
||||
|
||||
## Quick Start
|
||||
|
||||
### ☁️ LangBot Cloud (Recommended)
|
||||
|
||||
**[LangBot Cloud](https://space.langbot.app/cloud)** — Zero deployment, ready to use.
|
||||
|
||||
### One-Line Launch
|
||||
|
||||
```bash
|
||||
uvx langbot
|
||||
```
|
||||
|
||||
访问 http://localhost:5300 即可开始使用。
|
||||
> Requires [uv](https://docs.astral.sh/uv/getting-started/installation/). Visit http://localhost:5300 — done.
|
||||
|
||||
#### Docker Compose 部署
|
||||
### Docker Compose
|
||||
|
||||
```bash
|
||||
git clone https://github.com/langbot-app/LangBot
|
||||
@@ -51,127 +71,102 @@ cd LangBot/docker
|
||||
docker compose up -d
|
||||
```
|
||||
|
||||
访问 http://localhost:5300 即可开始使用。
|
||||
|
||||
详细文档[Docker 部署](https://docs.langbot.app/zh/deploy/langbot/docker.html)。
|
||||
|
||||
#### 宝塔面板部署
|
||||
|
||||
已上架宝塔面板，若您已安装宝塔面板，可以根据[文档](https://docs.langbot.app/zh/deploy/langbot/one-click/bt.html)使用。
|
||||
|
||||
#### Zeabur 云部署
|
||||
|
||||
社区贡献的 Zeabur 模板。
|
||||
|
||||
[](https://zeabur.com/zh-CN/templates/ZKTBDH)
|
||||
|
||||
#### Railway 云部署
|
||||
### One-Click Cloud Deploy
|
||||
|
||||
[](https://zeabur.com/en-US/templates/ZKTBDH)
|
||||
[](https://railway.app/template/yRrAyL?referralCode=vogKPF)
|
||||
|
||||
#### 手动部署
|
||||
**More options:** [Docker](https://docs.langbot.app/en/deploy/langbot/docker) · [Manual](https://docs.langbot.app/en/deploy/langbot/manual) · [BTPanel](https://docs.langbot.app/en/deploy/langbot/one-click/bt) · [Kubernetes](./docker/README_K8S.md)
|
||||
|
||||
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
|
||||
## Supported Platforms
|
||||
|
||||
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。
|
||||
|
||||
|
||||
|
||||
## ✨ 特性
|
||||
|
||||
<img width="500" src="https://docs.langbot.app/ui/bot-page-zh-rounded.png" />
|
||||
|
||||
|
||||
- 💬 大模型对话、Agent：支持多种大模型，适配群聊和私聊；具有多轮对话、工具调用、多模态、流式输出能力，自带 RAG（知识库）实现，并深度适配 [Dify](https://dify.ai)、[Coze](https://coze.com)、[n8n](https://n8n.io)、[Langflow](https://langflow.org)等 LLMOps 平台。
|
||||
- 🤖 多平台支持：目前支持 QQ、QQ频道、企业微信、个人微信、飞书、Discord、Telegram、KOOK、Slack、LINE 等平台。
|
||||
- 🛠️ 高稳定性、功能完备：原生支持访问控制、限速、敏感词过滤等机制；配置简单，支持多种部署方式。
|
||||
- 🧩 插件扩展、活跃社区：高稳定性、高安全性的生产级插件系统，支持事件驱动、组件扩展等插件机制；适配 Anthropic [MCP 协议](https://modelcontextprotocol.io/)；目前已有数百个插件。
|
||||
- 😻 Web 管理面板：提供先进的 WebUI 管理面板，用最直观的方式配置、管理、监控机器人。
|
||||
- 📊 生产级特性：支持多流水线配置，不同机器人用于不同应用场景。具有全面的监控和异常处理能力。已被多家企业采用。
|
||||
|
||||
详细规格特性请访问[文档](https://docs.langbot.app/zh/insight/features.html)。
|
||||
|
||||
或访问 demo 环境：https://demo.langbot.dev/
|
||||
- 登录信息：邮箱：`demo@langbot.app` 密码：`langbot123456`
|
||||
- 注意：仅展示 WebUI 效果，公开环境，请不要在其中填入您的任何敏感信息。
|
||||
|
||||
### 消息平台
|
||||
|
||||
| 平台 | 状态 | 备注 |
|
||||
| --- | --- | --- |
|
||||
| QQ 个人号 | ✅ | QQ 个人号私聊、群聊 |
|
||||
| QQ 官方机器人 | ✅ | QQ 官方机器人，支持频道、私聊、群聊 |
|
||||
| 企业微信 | ✅ | |
|
||||
| 企微对外客服 | ✅ | |
|
||||
| 企微智能机器人 | ✅ | |
|
||||
| 个人微信 | ✅ | |
|
||||
| 微信公众号 | ✅ | |
|
||||
| 飞书 | ✅ | |
|
||||
| 钉钉 | ✅ | |
|
||||
| KOOK | ✅ | |
|
||||
| Platform | Status | Notes |
|
||||
|----------|--------|-------|
|
||||
| Discord | ✅ | |
|
||||
| Telegram | ✅ | |
|
||||
| Slack | ✅ | |
|
||||
| LINE | ✅ | |
|
||||
| QQ | ✅ | Personal & Official API |
|
||||
| WeCom | ✅ | Enterprise WeChat, External CS, AI Bot |
|
||||
| WeChat | ✅ | Personal & Official Account |
|
||||
| Lark | ✅ | |
|
||||
| DingTalk | ✅ | |
|
||||
| KOOK | ✅ | |
|
||||
| Satori | ✅ | |
|
||||
|
||||
### 大模型能力
|
||||
---
|
||||
|
||||
| 模型 | 状态 | 备注 |
|
||||
| --- | --- | --- |
|
||||
| [OpenAI](https://platform.openai.com/) | ✅ | 可接入任何 OpenAI 接口格式模型 |
|
||||
| [DeepSeek](https://www.deepseek.com/) | ✅ | |
|
||||
| [Moonshot](https://www.moonshot.cn/) | ✅ | |
|
||||
| [Anthropic](https://www.anthropic.com/) | ✅ | |
|
||||
| [xAI](https://x.ai/) | ✅ | |
|
||||
| [智谱AI](https://open.bigmodel.cn/) | ✅ | |
|
||||
| [胜算云](https://www.shengsuanyun.com/?from=CH_KYIPP758) | ✅ | 全球大模型都可调用（友情推荐） |
|
||||
| [优云智算](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | ✅ | 大模型和 GPU 资源平台 |
|
||||
| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | ✅ | 大模型和 GPU 资源平台 |
|
||||
| [接口 AI](https://jiekou.ai/) | ✅ | 大模型聚合平台，专注全球大模型接入 |
|
||||
| [302.AI](https://share.302.ai/SuTG99) | ✅ | 大模型聚合平台 |
|
||||
| [Google Gemini](https://aistudio.google.com/prompts/new_chat) | ✅ | |
|
||||
| [Dify](https://dify.ai) | ✅ | LLMOps 平台 |
|
||||
| [Ollama](https://ollama.com/) | ✅ | 本地大模型运行平台 |
|
||||
| [LMStudio](https://lmstudio.ai/) | ✅ | 本地大模型运行平台 |
|
||||
| [GiteeAI](https://ai.gitee.com/) | ✅ | 大模型接口聚合平台 |
|
||||
| [SiliconFlow](https://siliconflow.cn/) | ✅ | 大模型聚合平台 |
|
||||
| [小马算力](https://www.tokenpony.cn/453z1) | ✅ | 大模型聚合平台 |
|
||||
| [阿里云百炼](https://bailian.console.aliyun.com/) | ✅ | 大模型聚合平台, LLMOps 平台 |
|
||||
| [火山方舟](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | ✅ | 大模型聚合平台, LLMOps 平台 |
|
||||
| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | ✅ | 大模型聚合平台 |
|
||||
| [MCP](https://modelcontextprotocol.io/) | ✅ | 支持通过 MCP 协议获取工具 |
|
||||
| [百宝箱Tbox](https://www.tbox.cn/open) | ✅ | 蚂蚁百宝箱智能体平台，每月免费10亿大模型Token |
|
||||
## Supported LLMs & Integrations
|
||||
|
||||
### TTS
|
||||
| Provider | Type | Status |
|
||||
|----------|------|--------|
|
||||
| [OpenAI](https://platform.openai.com/) | LLM | ✅ |
|
||||
| [Anthropic](https://www.anthropic.com/) | LLM | ✅ |
|
||||
| [DeepSeek](https://www.deepseek.com/) | LLM | ✅ |
|
||||
| [Google Gemini](https://aistudio.google.com/prompts/new_chat) | LLM | ✅ |
|
||||
| [xAI](https://x.ai/) | LLM | ✅ |
|
||||
| [Moonshot](https://www.moonshot.cn/) | LLM | ✅ |
|
||||
| [Zhipu AI](https://open.bigmodel.cn/) | LLM | ✅ |
|
||||
| [Ollama](https://ollama.com/) | Local LLM | ✅ |
|
||||
| [LM Studio](https://lmstudio.ai/) | Local LLM | ✅ |
|
||||
| [Dify](https://dify.ai) | LLMOps | ✅ |
|
||||
| [MCP](https://modelcontextprotocol.io/) | Protocol | ✅ |
|
||||
| [SiliconFlow](https://siliconflow.cn/) | Gateway | ✅ |
|
||||
| [Aliyun Bailian](https://bailian.console.aliyun.com/) | Gateway | ✅ |
|
||||
| [Volc Engine Ark](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | Gateway | ✅ |
|
||||
| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | Gateway | ✅ |
|
||||
| [GiteeAI](https://ai.gitee.com/) | Gateway | ✅ |
|
||||
| [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | GPU Platform | ✅ |
|
||||
| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | GPU Platform | ✅ |
|
||||
| [ShengSuanYun](https://www.shengsuanyun.com/?from=CH_KYIPP758) | GPU Platform | ✅ |
|
||||
| [接口 AI](https://jiekou.ai/) | Gateway | ✅ |
|
||||
| [302.AI](https://share.302.ai/SuTG99) | Gateway | ✅ |
|
||||
|
||||
| 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) |
|
||||
[→ View all integrations](https://docs.langbot.app/en/insight/features)
|
||||
|
||||
### 文生图
|
||||
---
|
||||
|
||||
| 平台/模型 | 备注 |
|
||||
| --- | --- |
|
||||
| 阿里云百炼 | [插件](https://github.com/Thetail001/LangBot_BailianTextToImagePlugin)
|
||||
## Why LangBot?
|
||||
|
||||
## 😘 社区贡献
|
||||
| Use Case | How LangBot Helps |
|
||||
|----------|-------------------|
|
||||
| **Customer Support** | Deploy AI agents to Slack/Discord/Telegram that answer questions using your knowledge base |
|
||||
| **Internal Tools** | Connect n8n/Dify workflows to WeCom/DingTalk for automated business processes |
|
||||
| **Community Management** | Moderate QQ/Discord groups with AI-powered content filtering and interaction |
|
||||
| **Multi-Platform Presence** | One bot, all platforms. Manage from a single dashboard |
|
||||
|
||||
感谢以下[代码贡献者](https://github.com/langbot-app/LangBot/graphs/contributors)和社区里其他成员对 LangBot 的贡献：
|
||||
---
|
||||
|
||||
## Live Demo
|
||||
|
||||
**Try it now:** https://demo.langbot.dev/
|
||||
- Email: `demo@langbot.app`
|
||||
- Password: `langbot123456`
|
||||
|
||||
*Note: Public demo environment. Do not enter sensitive information.*
|
||||
|
||||
---
|
||||
|
||||
## Community
|
||||
|
||||
[](https://discord.gg/wdNEHETs87)
|
||||
|
||||
- [Discord Community](https://discord.gg/wdNEHETs87)
|
||||
|
||||
---
|
||||
|
||||
## Star History
|
||||
|
||||
[](https://star-history.com/#langbot-app/LangBot&Date)
|
||||
|
||||
---
|
||||
|
||||
## Contributors
|
||||
|
||||
Thanks to all [contributors](https://github.com/langbot-app/LangBot/graphs/contributors) who have helped make LangBot better:
|
||||
|
||||
<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.
|
||||
-->
|
||||
|
||||
197
README_CN.md
Normal file
197
README_CN.md
Normal file
@@ -0,0 +1,197 @@
|
||||
<p align="center">
|
||||
<a href="https://langbot.app">
|
||||
<img width="130" src="res/logo-blue.png" alt="LangBot"/>
|
||||
</a>
|
||||
|
||||
<div align="center">
|
||||
|
||||
<a href="https://hellogithub.com/repository/langbot-app/LangBot" target="_blank"><img src="https://abroad.hellogithub.com/v1/widgets/recommend.svg?rid=5ce8ae2aa4f74316bf393b57b952433c&claim_uid=gtmc6YWjMZkT21R" alt="Featured｜HelloGitHub" style="width: 250px; height: 54px;" width="250" height="54" /></a>
|
||||
|
||||
<h3>生产级 AI 即时通信机器人开发平台。</h3>
|
||||
<h4>快速构建、调试和部署 AI 机器人到微信、QQ、飞书、Slack、Discord、Telegram 等平台。</h4>
|
||||
|
||||
[English](README.md) / 简体中文 / [繁體中文](README_TW.md) / [日本語](README_JP.md) / [Español](README_ES.md) / [Français](README_FR.md) / [한국어](README_KO.md) / [Русский](README_RU.md) / [Tiếng Việt](README_VI.md)
|
||||
|
||||
[](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/cloud">Cloud</a> ｜
|
||||
<a href="https://space.langbot.app">插件市场</a> ｜
|
||||
<a href="https://langbot.featurebase.app/roadmap">路线图</a>
|
||||
|
||||
</div>
|
||||
|
||||
</p>
|
||||
|
||||
---
|
||||
|
||||
## 什么是 LangBot？
|
||||
|
||||
LangBot 是一个**开源的生产级平台**，用于构建 AI 驱动的即时通信机器人。它将大语言模型（LLM）连接到各种聊天平台，帮助你创建能够对话、执行任务、并集成到现有工作流程中的智能 Agent。
|
||||
|
||||
### 核心能力
|
||||
|
||||
- **AI 对话与 Agent** — 多轮对话、工具调用、多模态、流式输出。自带 RAG（知识库），深度集成 [Dify](https://dify.ai)、[Coze](https://coze.com)、[n8n](https://n8n.io)、[Langflow](https://langflow.org) 等 LLMOps 平台。
|
||||
- **全平台支持** — 一套代码，覆盖 QQ、微信、企业微信、飞书、钉钉、Discord、Telegram、Slack、LINE、KOOK 等平台。
|
||||
- **生产就绪** — 访问控制、限速、敏感词过滤、全面监控与异常处理，已被多家企业采用。
|
||||
- **插件生态** — 数百个插件，事件驱动架构，组件扩展，适配 [MCP 协议](https://modelcontextprotocol.io/)。
|
||||
- **Web 管理面板** — 通过浏览器直观地配置、管理和监控机器人，无需手动编辑配置文件。
|
||||
- **多流水线架构** — 不同机器人用于不同场景，具备全面的监控和异常处理能力。
|
||||
|
||||
[→ 了解更多功能特性](https://docs.langbot.app/zh/insight/features.html)
|
||||
|
||||
---
|
||||
|
||||
## 快速开始
|
||||
|
||||
### ☁️ LangBot Cloud（推荐）
|
||||
|
||||
**[LangBot Cloud](https://space.langbot.app/cloud)** — 免部署，开箱即用。
|
||||
|
||||
### 一键启动
|
||||
|
||||
```bash
|
||||
uvx langbot
|
||||
```
|
||||
|
||||
> 需要安装 [uv](https://docs.astral.sh/uv/getting-started/installation/)。访问 http://localhost:5300 即可使用。
|
||||
|
||||
### Docker Compose
|
||||
|
||||
```bash
|
||||
git clone https://github.com/langbot-app/LangBot
|
||||
cd LangBot/docker
|
||||
docker compose up -d
|
||||
```
|
||||
|
||||
### 一键云部署
|
||||
|
||||
[](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.
|
||||
-->
|
||||
151
README_EN.md
151
README_EN.md
@@ -1,151 +0,0 @@
|
||||
<p align="center">
|
||||
<a href="https://langbot.app">
|
||||
<img width="130" src="https://docs.langbot.app/langbot-logo.png" alt="LangBot"/>
|
||||
</a>
|
||||
|
||||
<div align="center">
|
||||
|
||||
<a href="https://www.producthunt.com/products/langbot?utm_source=badge-follow&utm_medium=badge&utm_source=badge-langbot" target="_blank"><img src="https://api.producthunt.com/widgets/embed-image/v1/follow.svg?product_id=1077185&theme=light" alt="LangBot - Production-grade IM bot made easy. | Product Hunt" style="width: 250px; height: 54px;" width="250" height="54" /></a>
|
||||
|
||||
<h3>Quickly build, debug, and ship IM bots with LangBot.</h3>
|
||||
|
||||
English / [简体中文](README.md) / [繁體中文](README_TW.md) / [日本語](README_JP.md) / [Español](README_ES.md) / [Français](README_FR.md) / [한국어](README_KO.md) / [Русский](README_RU.md) / [Tiếng Việt](README_VI.md)
|
||||
|
||||
[](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">
|
||||
|
||||
<a href="https://langbot.app">Home</a> ｜
|
||||
<a href="https://docs.langbot.app/en/insight/features.html">Features</a> ｜
|
||||
<a href="https://docs.langbot.app/en/insight/guide.html">Deployment</a> ｜
|
||||
<a href="https://docs.langbot.app/en/tags/readme.html">API Integration</a> ｜
|
||||
<a href="https://space.langbot.app">Plugin Market</a> ｜
|
||||
<a href="https://langbot.featurebase.app/roadmap">Roadmap</a>
|
||||
|
||||
</div>
|
||||
|
||||
</p>
|
||||
|
||||
|
||||
## 📦 Getting Started
|
||||
|
||||
#### Quick Start
|
||||
|
||||
Use `uvx` to start with one command (need to install [uv](https://docs.astral.sh/uv/getting-started/installation/)):
|
||||
|
||||
```bash
|
||||
uvx langbot
|
||||
```
|
||||
|
||||
Visit http://localhost:5300 to start using it.
|
||||
|
||||
#### Docker Compose Deployment
|
||||
|
||||
```bash
|
||||
git clone https://github.com/langbot-app/LangBot
|
||||
cd LangBot/docker
|
||||
docker compose up -d
|
||||
```
|
||||
|
||||
Visit http://localhost:5300 to start using it.
|
||||
|
||||
Detailed documentation [Docker Deployment](https://docs.langbot.app/en/deploy/langbot/docker.html).
|
||||
|
||||
#### One-click Deployment on BTPanel
|
||||
|
||||
LangBot has been listed on the BTPanel, if you have installed the BTPanel, you can use the [document](https://docs.langbot.app/en/deploy/langbot/one-click/bt.html) to use it.
|
||||
|
||||
#### Zeabur Cloud Deployment
|
||||
|
||||
Community contributed Zeabur template.
|
||||
|
||||
[](https://zeabur.com/en-US/templates/ZKTBDH)
|
||||
|
||||
#### Railway Cloud Deployment
|
||||
|
||||
[](https://railway.app/template/yRrAyL?referralCode=vogKPF)
|
||||
|
||||
#### Other Deployment Methods
|
||||
|
||||
Directly use the released version to run, see the [Manual Deployment](https://docs.langbot.app/en/deploy/langbot/manual.html) documentation.
|
||||
|
||||
#### Kubernetes Deployment
|
||||
|
||||
Refer to the [Kubernetes Deployment](./docker/README_K8S.md) documentation.
|
||||
|
||||
## 😎 Stay Ahead
|
||||
|
||||
Click the Star and Watch button in the upper right corner of the repository to get the latest updates.
|
||||
|
||||
|
||||
|
||||
## ✨ Features
|
||||
|
||||
<img width="500" src="https://docs.langbot.app/ui/bot-page-en-rounded.png" />
|
||||
|
||||
|
||||
- 💬 Chat with LLM / Agent: Supports multiple LLMs, adapt to group chats and private chats; Supports multi-round conversations, tool calls, multi-modal, and streaming output capabilities. Built-in RAG (knowledge base) implementation, and deeply integrates with [Dify](https://dify.ai), [Coze](https://coze.com), [n8n](https://n8n.io), [Langflow](https://langflow.org) etc. LLMOps platforms.
|
||||
- 🤖 Multi-platform Support: Currently supports QQ, QQ Channel, WeCom, personal WeChat, Lark, DingTalk, Discord, Telegram, KOOK, Slack, LINE, etc.
|
||||
- 🛠️ High Stability, Feature-rich: Native access control, rate limiting, sensitive word filtering, etc. mechanisms; Easy to use, supports multiple deployment methods.
|
||||
- 🧩 Plugin Extension, Active Community: High stability, high security production-level plugin system; Support event-driven, component extension, etc. plugin mechanisms; Integrate Anthropic [MCP protocol](https://modelcontextprotocol.io/); Currently has hundreds of plugins.
|
||||
- 😻 Web UI: Support management LangBot instance through the browser. No need to manually write configuration files.
|
||||
- 📊 Production-grade Features: Supports multiple pipeline configurations, different bots can be used for different scenarios. Has comprehensive monitoring and exception handling capabilities.
|
||||
|
||||
For more detailed specifications, please refer to the [documentation](https://docs.langbot.app/en/insight/features.html).
|
||||
|
||||
Or visit the demo environment: https://demo.langbot.dev/
|
||||
- Login information: Email: `demo@langbot.app` Password: `langbot123456`
|
||||
- Note: For WebUI demo only, please do not fill in any sensitive information in the public environment.
|
||||
|
||||
### Message Platform
|
||||
|
||||
| Platform | Status | Remarks |
|
||||
| --- | --- | --- |
|
||||
| Discord | ✅ | |
|
||||
| Telegram | ✅ | |
|
||||
| Slack | ✅ | |
|
||||
| LINE | ✅ | |
|
||||
| Personal QQ | ✅ | |
|
||||
| QQ Official API | ✅ | |
|
||||
| WeCom | ✅ | |
|
||||
| WeComCS | ✅ | |
|
||||
| WeCom AI Bot | ✅ | |
|
||||
| Personal WeChat | ✅ | |
|
||||
| Lark | ✅ | |
|
||||
| DingTalk | ✅ | |
|
||||
| KOOK | ✅ | |
|
||||
|
||||
### LLMs
|
||||
|
||||
| LLM | Status | Remarks |
|
||||
| --- | --- | --- |
|
||||
| [OpenAI](https://platform.openai.com/) | ✅ | Available for any OpenAI interface format model |
|
||||
| [DeepSeek](https://www.deepseek.com/) | ✅ | |
|
||||
| [Moonshot](https://www.moonshot.cn/) | ✅ | |
|
||||
| [Anthropic](https://www.anthropic.com/) | ✅ | |
|
||||
| [xAI](https://x.ai/) | ✅ | |
|
||||
| [Zhipu AI](https://open.bigmodel.cn/) | ✅ | |
|
||||
| [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | ✅ | LLM and GPU resource platform |
|
||||
| [Dify](https://dify.ai) | ✅ | LLMOps platform |
|
||||
| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | ✅ | LLM and GPU resource platform |
|
||||
| [接口 AI](https://jiekou.ai/) | ✅ | LLM aggregation platform, dedicated to global LLMs |
|
||||
| [ShengSuanYun](https://www.shengsuanyun.com/?from=CH_KYIPP758) | ✅ | LLM and GPU resource platform |
|
||||
| [302.AI](https://share.302.ai/SuTG99) | ✅ | LLM gateway(MaaS) |
|
||||
| [Google Gemini](https://aistudio.google.com/prompts/new_chat) | ✅ | |
|
||||
| [Ollama](https://ollama.com/) | ✅ | Local LLM running platform |
|
||||
| [LMStudio](https://lmstudio.ai/) | ✅ | Local LLM running platform |
|
||||
| [GiteeAI](https://ai.gitee.com/) | ✅ | LLM interface gateway(MaaS) |
|
||||
| [SiliconFlow](https://siliconflow.cn/) | ✅ | LLM gateway(MaaS) |
|
||||
| [Aliyun Bailian](https://bailian.console.aliyun.com/) | ✅ | LLM gateway(MaaS), LLMOps platform |
|
||||
| [Volc Engine Ark](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | ✅ | LLM gateway(MaaS), LLMOps platform |
|
||||
| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | ✅ | LLM gateway(MaaS) |
|
||||
| [MCP](https://modelcontextprotocol.io/) | ✅ | Support tool access through MCP protocol |
|
||||
|
||||
## 🤝 Community Contribution
|
||||
|
||||
Thank you for the following [code contributors](https://github.com/langbot-app/LangBot/graphs/contributors) and other members in the community for their contributions to LangBot:
|
||||
|
||||
<a href="https://github.com/langbot-app/LangBot/graphs/contributors">
|
||||
<img src="https://contrib.rocks/image?repo=langbot-app/LangBot" />
|
||||
</a>
|
||||
198
README_ES.md
198
README_ES.md
@@ -1,25 +1,27 @@
|
||||
<p align="center">
|
||||
<a href="https://langbot.app">
|
||||
<img width="130" src="https://docs.langbot.app/langbot-logo.png" alt="LangBot"/>
|
||||
<img width="130" src="res/logo-blue.png" alt="LangBot"/>
|
||||
</a>
|
||||
|
||||
<div align="center">
|
||||
|
||||
<a href="https://www.producthunt.com/products/langbot?utm_source=badge-follow&utm_medium=badge&utm_source=badge-langbot" target="_blank"><img src="https://api.producthunt.com/widgets/embed-image/v1/follow.svg?product_id=1077185&theme=light" alt="LangBot - Production-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 +29,40 @@
|
||||
|
||||
</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
|
||||
|
||||
### ☁️ LangBot Cloud (Recomendado)
|
||||
|
||||
**[LangBot Cloud](https://space.langbot.app/cloud)** — Sin despliegue, listo para usar.
|
||||
|
||||
### 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
|
||||
@@ -48,103 +70,101 @@ 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" />
|
||||
|
||||
199
README_FR.md
199
README_FR.md
@@ -1,25 +1,27 @@
|
||||
<p align="center">
|
||||
<a href="https://langbot.app">
|
||||
<img width="130" src="https://docs.langbot.app/langbot-logo.png" alt="LangBot"/>
|
||||
<img width="130" src="res/logo-blue.png" alt="LangBot"/>
|
||||
</a>
|
||||
|
||||
<div align="center">
|
||||
|
||||
<a href="https://www.producthunt.com/products/langbot?utm_source=badge-follow&utm_medium=badge&utm_source=badge-langbot" target="_blank"><img src="https://api.producthunt.com/widgets/embed-image/v1/follow.svg?product_id=1077185&theme=light" alt="LangBot - Production-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 +29,40 @@
|
||||
|
||||
</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
|
||||
|
||||
### ☁️ LangBot Cloud (Recommandé)
|
||||
|
||||
**[LangBot Cloud](https://space.langbot.app/cloud)** — Sans déploiement, prêt à utiliser.
|
||||
|
||||
### 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
|
||||
@@ -47,103 +70,101 @@ 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" />
|
||||
|
||||
199
README_JP.md
199
README_JP.md
@@ -1,25 +1,27 @@
|
||||
<p align="center">
|
||||
<a href="https://langbot.app">
|
||||
<img width="130" src="https://docs.langbot.app/langbot-logo.png" alt="LangBot"/>
|
||||
<img width="130" src="res/logo-blue.png" alt="LangBot"/>
|
||||
</a>
|
||||
|
||||
<div align="center">
|
||||
|
||||
<a href="https://www.producthunt.com/products/langbot?utm_source=badge-follow&utm_medium=badge&utm_source=badge-langbot" target="_blank"><img src="https://api.producthunt.com/widgets/embed-image/v1/follow.svg?product_id=1077185&theme=light" alt="LangBot - Production-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 +29,40 @@
|
||||
|
||||
</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
|
||||
|
||||
### ☁️ LangBot Cloud（推奨）
|
||||
|
||||
**[LangBot Cloud](https://space.langbot.app/cloud)** — デプロイ不要、すぐに使えます。
|
||||
|
||||
### ワンライン起動
|
||||
|
||||
```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
|
||||
@@ -47,103 +70,101 @@ 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" />
|
||||
|
||||
201
README_KO.md
201
README_KO.md
@@ -1,25 +1,27 @@
|
||||
<p align="center">
|
||||
<a href="https://langbot.app">
|
||||
<img width="130" src="https://docs.langbot.app/langbot-logo.png" alt="LangBot"/>
|
||||
<img width="130" src="res/logo-blue.png" alt="LangBot"/>
|
||||
</a>
|
||||
|
||||
<div align="center">
|
||||
|
||||
<a href="https://www.producthunt.com/products/langbot?utm_source=badge-follow&utm_medium=badge&utm_source=badge-langbot" target="_blank"><img src="https://api.producthunt.com/widgets/embed-image/v1/follow.svg?product_id=1077185&theme=light" alt="LangBot - Production-grade IM bot made easy. | Product Hunt" style="width: 250px; height: 54px;" width="250" height="54" /></a>
|
||||
|
||||
<h3>LangBot으로 IM 봇을 빠르게 구축, 디버그 및 배포하세요.</h3>
|
||||
<h3>AI 에이전트 IM 봇 구축을 위한 프로덕션 등급 플랫폼.</h3>
|
||||
<h4>Slack, Discord, Telegram, WeChat 등에 AI 봇을 빠르게 구축, 디버그 및 배포.</h4>
|
||||
|
||||
[English](README_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)
|
||||
[English](README.md) / [简体中文](README_CN.md) / [繁體中文](README_TW.md) / [日本語](README_JP.md) / [Español](README_ES.md) / [Français](README_FR.md) / 한국어 / [Русский](README_RU.md) / [Tiếng Việt](README_VI.md)
|
||||
|
||||
[](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">홈</a> ｜
|
||||
<a href="https://docs.langbot.app/en/insight/features.html">기능 사양</a> ｜
|
||||
<a href="https://docs.langbot.app/en/insight/guide.html">배포</a> ｜
|
||||
<a href="https://docs.langbot.app/en/tags/readme.html">API 통합</a> ｜
|
||||
<a href="https://docs.langbot.app/en/insight/features.html">기능</a> ｜
|
||||
<a href="https://docs.langbot.app/en/insight/guide.html">문서</a> ｜
|
||||
<a href="https://docs.langbot.app/en/tags/readme.html">API</a> ｜
|
||||
<a href="https://space.langbot.app">플러그인 마켓</a> ｜
|
||||
<a href="https://langbot.featurebase.app/roadmap">로드맵</a>
|
||||
|
||||
@@ -27,19 +29,40 @@
|
||||
|
||||
</p>
|
||||
|
||||
## 📦 시작하기
|
||||
---
|
||||
|
||||
#### 빠른 시작
|
||||
## LangBot이란?
|
||||
|
||||
`uvx`를 사용하여 한 명령으로 시작하세요 ([uv](https://docs.astral.sh/uv/getting-started/installation/) 설치 필요):
|
||||
LangBot은 AI 기반 인스턴트 메시징 봇을 구축하기 위한 **오픈소스 프로덕션 등급 플랫폼**입니다. 대규모 언어 모델(LLM)을 모든 채팅 플랫폼에 연결하여 대화, 작업 실행, 기존 워크플로우와의 통합이 가능한 지능형 에이전트를 만들 수 있습니다.
|
||||
|
||||
### 핵심 기능
|
||||
|
||||
- **AI 대화 및 에이전트** — 멀티턴 대화, 도구 호출, 멀티모달 지원, 스트리밍 출력. 내장 RAG(지식 베이스)와 [Dify](https://dify.ai), [Coze](https://coze.com), [n8n](https://n8n.io), [Langflow](https://langflow.org) 심층 통합.
|
||||
- **유니버설 IM 플랫폼 지원** — 단일 코드베이스로 Discord, Telegram, Slack, LINE, QQ, WeChat, WeCom, Lark, DingTalk, KOOK 지원.
|
||||
- **프로덕션 레디** — 접근 제어, 속도 제한, 민감어 필터링, 종합 모니터링 및 예외 처리. 기업 환경에서 검증됨.
|
||||
- **플러그인 생태계** — 수백 개의 플러그인, 이벤트 기반 아키텍처, 컴포넌트 확장, [MCP 프로토콜](https://modelcontextprotocol.io/) 지원.
|
||||
- **웹 관리 패널** — 직관적인 브라우저 인터페이스로 봇을 구성, 관리 및 모니터링. YAML 편집 불필요.
|
||||
- **멀티 파이프라인 아키텍처** — 다양한 시나리오에 맞는 다양한 봇 구성, 종합 모니터링 및 예외 처리.
|
||||
|
||||
[→ 모든 기능 자세히 보기](https://docs.langbot.app/en/insight/features.html)
|
||||
|
||||
---
|
||||
|
||||
## 빠른 시작
|
||||
|
||||
### ☁️ LangBot Cloud (추천)
|
||||
|
||||
**[LangBot Cloud](https://space.langbot.app/cloud)** — 배포 없이 바로 사용.
|
||||
|
||||
### 원라인 실행
|
||||
|
||||
```bash
|
||||
uvx langbot
|
||||
```
|
||||
|
||||
http://localhost:5300을 방문하여 사용을 시작하세요.
|
||||
> [uv](https://docs.astral.sh/uv/getting-started/installation/) 설치 필요. http://localhost:5300 방문 — 완료.
|
||||
|
||||
#### Docker Compose 배포
|
||||
### Docker Compose
|
||||
|
||||
```bash
|
||||
git clone https://github.com/langbot-app/LangBot
|
||||
@@ -47,103 +70,101 @@ 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.
|
||||
### 원클릭 클라우드 배포
|
||||
|
||||
[](https://zeabur.com/en-US/templates/ZKTBDH)
|
||||
|
||||
#### Railway 클라우드 배포
|
||||
|
||||
[](https://railway.app/template/yRrAyL?referralCode=vogKPF)
|
||||
|
||||
#### 기타 배포 방법
|
||||
**더 많은 옵션:** [Docker](https://docs.langbot.app/en/deploy/langbot/docker.html) · [수동 배포](https://docs.langbot.app/en/deploy/langbot/manual.html) · [BTPanel](https://docs.langbot.app/en/deploy/langbot/one-click/bt.html) · [Kubernetes](./docker/README_K8S.md)
|
||||
|
||||
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.
|
||||
|
||||
|
||||
|
||||
## ✨ 기능
|
||||
|
||||
<img width="500" src="https://docs.langbot.app/ui/bot-page-en-rounded.png" />
|
||||
|
||||
|
||||
- 💬 LLM / Agent와 채팅: 여러 LLM을 지원하며 그룹 채팅 및 개인 채팅에 적응; 멀티 라운드 대화, 도구 호출, 멀티모달, 스트리밍 출력 기능을 지원합니다. 내장된 RAG(지식 베이스) 구현 및 [Dify](https://dify.ai)、[Coze](https://coze.com)、[n8n](https://n8n.io)、[Langflow](https://langflow.org)등의 LLMOps 플랫폼과 깊이 통합됩니다.
|
||||
- 🤖 다중 플랫폼 지원: 현재 QQ, QQ Channel, WeCom, 개인 WeChat, Lark, DingTalk, Discord, Telegram, KOOK, Slack, LINE 등을 지원합니다.
|
||||
- 🛠️ 높은 안정성, 풍부한 기능: 네이티브 액세스 제어, 속도 제한, 민감한 단어 필터링 등의 메커니즘; 사용하기 쉽고 여러 배포 방법을 지원합니다.
|
||||
- 🧩 플러그인 확장, 활발한 커뮤니티: 고안정성, 고보안 생산 수준의 플러그인 시스템; 이벤트 기반, 컴포넌트 확장 등의 플러그인 메커니즘을 지원; Anthropic [MCP 프로토콜](https://modelcontextprotocol.io/) 통합; 현재 수백 개의 플러그인이 있습니다.
|
||||
- 😻 웹 UI: 브라우저를 통해 LangBot 인스턴스 관리를 지원합니다. 구성 파일을 수동으로 작성할 필요가 없습니다.
|
||||
- 📊 생산 수준의 기능: 여러 파이프라인 구성을 지원하며 다양한 시나리오에 대해 다른 봇을 사용할 수 있습니다. 포괄적인 모니터링 및 예외 처리 기능을 갖추고 있습니다.
|
||||
|
||||
더 자세한 사양은 [문서](https://docs.langbot.app/en/insight/features.html)를 참조하세요.
|
||||
|
||||
또는 데모 환경을 방문하세요: https://demo.langbot.dev/
|
||||
- 로그인 정보: 이메일: `demo@langbot.app` 비밀번호: `langbot123456`
|
||||
- 참고: WebUI 데모 전용이므로 공개 환경에서는 민감한 정보를 입력하지 마세요.
|
||||
|
||||
### 메시징 플랫폼
|
||||
## 지원 플랫폼
|
||||
|
||||
| 플랫폼 | 상태 | 비고 |
|
||||
| --- | --- | --- |
|
||||
|--------|------|------|
|
||||
| Discord | ✅ | |
|
||||
| Telegram | ✅ | |
|
||||
| Slack | ✅ | |
|
||||
| LINE | ✅ | |
|
||||
| 개인 QQ | ✅ | |
|
||||
| QQ 공식 API | ✅ | |
|
||||
| WeCom | ✅ | |
|
||||
| WeComCS | ✅ | |
|
||||
| WeCom AI Bot | ✅ | |
|
||||
| 개인 WeChat | ✅ | |
|
||||
| KOOK | ✅ | |
|
||||
| QQ | ✅ | 개인 및 공식 API |
|
||||
| WeCom | ✅ | 기업 WeChat, 외부 CS, AI Bot |
|
||||
| WeChat | ✅ | 개인 및 공식 계정 |
|
||||
| Lark | ✅ | |
|
||||
| DingTalk | ✅ | |
|
||||
| KOOK | ✅ | |
|
||||
| Satori | ✅ | |
|
||||
|
||||
### 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 |
|
||||
## 지원 LLM 및 통합
|
||||
|
||||
## 🤝 커뮤니티 기여
|
||||
| 제공자 | 유형 | 상태 |
|
||||
|--------|------|------|
|
||||
| [OpenAI](https://platform.openai.com/) | LLM | ✅ |
|
||||
| [Anthropic](https://www.anthropic.com/) | LLM | ✅ |
|
||||
| [DeepSeek](https://www.deepseek.com/) | LLM | ✅ |
|
||||
| [Google Gemini](https://aistudio.google.com/prompts/new_chat) | LLM | ✅ |
|
||||
| [xAI](https://x.ai/) | LLM | ✅ |
|
||||
| [Moonshot](https://www.moonshot.cn/) | LLM | ✅ |
|
||||
| [Zhipu AI](https://open.bigmodel.cn/) | LLM | ✅ |
|
||||
| [Ollama](https://ollama.com/) | 로컬 LLM | ✅ |
|
||||
| [LM Studio](https://lmstudio.ai/) | 로컬 LLM | ✅ |
|
||||
| [Dify](https://dify.ai) | LLMOps | ✅ |
|
||||
| [MCP](https://modelcontextprotocol.io/) | 프로토콜 | ✅ |
|
||||
| [SiliconFlow](https://siliconflow.cn/) | 게이트웨이 | ✅ |
|
||||
| [Aliyun Bailian](https://bailian.console.aliyun.com/) | 게이트웨이 | ✅ |
|
||||
| [Volc Engine Ark](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | 게이트웨이 | ✅ |
|
||||
| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | 게이트웨이 | ✅ |
|
||||
| [GiteeAI](https://ai.gitee.com/) | 게이트웨이 | ✅ |
|
||||
| [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | GPU 플랫폼 | ✅ |
|
||||
| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | GPU 플랫폼 | ✅ |
|
||||
| [ShengSuanYun](https://www.shengsuanyun.com/?from=CH_KYIPP758) | GPU 플랫폼 | ✅ |
|
||||
| [接口 AI](https://jiekou.ai/) | 게이트웨이 | ✅ |
|
||||
| [302.AI](https://share.302.ai/SuTG99) | 게이트웨이 | ✅ |
|
||||
|
||||
다음 [코드 기여자](https://github.com/langbot-app/LangBot/graphs/contributors) 및 커뮤니티의 다른 구성원들의 LangBot 기여에 감사드립니다:
|
||||
[→ 모든 통합 보기](https://docs.langbot.app/en/insight/features.html)
|
||||
|
||||
---
|
||||
|
||||
## 왜 LangBot인가?
|
||||
|
||||
| 사용 사례 | LangBot 활용 방법 |
|
||||
|-----------|-------------------|
|
||||
| **고객 지원** | 지식 베이스를 활용하여 질문에 답변하는 AI 에이전트를 Slack/Discord/Telegram에 배포 |
|
||||
| **내부 도구** | n8n/Dify 워크플로우를 WeCom/DingTalk에 연결하여 비즈니스 프로세스 자동화 |
|
||||
| **커뮤니티 관리** | AI 기반 콘텐츠 필터링 및 상호작용으로 QQ/Discord 그룹 관리 |
|
||||
| **멀티 플랫폼** | 하나의 봇으로 모든 플랫폼 지원. 단일 대시보드에서 관리 |
|
||||
|
||||
---
|
||||
|
||||
## 라이브 데모
|
||||
|
||||
**지금 체험:** https://demo.langbot.dev/
|
||||
- 이메일: `demo@langbot.app`
|
||||
- 비밀번호: `langbot123456`
|
||||
|
||||
*참고: 공개 데모 환경입니다. 민감한 정보를 입력하지 마세요.*
|
||||
|
||||
---
|
||||
|
||||
## 커뮤니티
|
||||
|
||||
[](https://discord.gg/wdNEHETs87)
|
||||
|
||||
- [Discord 커뮤니티](https://discord.gg/wdNEHETs87)
|
||||
|
||||
---
|
||||
|
||||
## Star 추이
|
||||
|
||||
[](https://star-history.com/#langbot-app/LangBot&Date)
|
||||
|
||||
---
|
||||
|
||||
## 기여자
|
||||
|
||||
LangBot을 더 나은 프로젝트로 만들어 주신 모든 [기여자](https://github.com/langbot-app/LangBot/graphs/contributors)분들께 감사드립니다:
|
||||
|
||||
<a href="https://github.com/langbot-app/LangBot/graphs/contributors">
|
||||
<img src="https://contrib.rocks/image?repo=langbot-app/LangBot" />
|
||||
|
||||
201
README_RU.md
201
README_RU.md
@@ -1,25 +1,27 @@
|
||||
<p align="center">
|
||||
<a href="https://langbot.app">
|
||||
<img width="130" src="https://docs.langbot.app/langbot-logo.png" alt="LangBot"/>
|
||||
<img width="130" src="res/logo-blue.png" alt="LangBot"/>
|
||||
</a>
|
||||
|
||||
<div align="center">
|
||||
|
||||
<a href="https://www.producthunt.com/products/langbot?utm_source=badge-follow&utm_medium=badge&utm_source=badge-langbot" target="_blank"><img src="https://api.producthunt.com/widgets/embed-image/v1/follow.svg?product_id=1077185&theme=light" alt="LangBot - Production-grade IM bot made easy. | Product Hunt" style="width: 250px; height: 54px;" width="250" height="54" /></a>
|
||||
|
||||
<h3>Быстро создавайте, отлаживайте и развертывайте IM-ботов с LangBot.</h3>
|
||||
<h3>Платформа производственного уровня для создания агентных IM-ботов.</h3>
|
||||
<h4>Быстро создавайте, отлаживайте и развертывайте ИИ-ботов в Slack, Discord, Telegram, WeChat и других платформах.</h4>
|
||||
|
||||
[English](README_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)
|
||||
[English](README.md) / [简体中文](README_CN.md) / [繁體中文](README_TW.md) / [日本語](README_JP.md) / [Español](README_ES.md) / [Français](README_FR.md) / [한국어](README_KO.md) / Русский / [Tiếng Việt](README_VI.md)
|
||||
|
||||
[](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">Главная</a> ｜
|
||||
<a href="https://docs.langbot.app/en/insight/features.html">Характеристики</a> ｜
|
||||
<a href="https://docs.langbot.app/en/insight/guide.html">Развертывание</a> ｜
|
||||
<a href="https://docs.langbot.app/en/tags/readme.html">Интеграция API</a> ｜
|
||||
<a href="https://docs.langbot.app/en/insight/features.html">Возможности</a> ｜
|
||||
<a href="https://docs.langbot.app/en/insight/guide.html">Документация</a> ｜
|
||||
<a href="https://docs.langbot.app/en/tags/readme.html">API</a> ｜
|
||||
<a href="https://space.langbot.app">Магазин плагинов</a> ｜
|
||||
<a href="https://langbot.featurebase.app/roadmap">Дорожная карта</a>
|
||||
|
||||
@@ -27,19 +29,40 @@
|
||||
|
||||
</p>
|
||||
|
||||
## 📦 Начало работы
|
||||
---
|
||||
|
||||
#### Быстрый старт
|
||||
## Что такое LangBot?
|
||||
|
||||
Используйте `uvx` для запуска одной командой (требуется установка [uv](https://docs.astral.sh/uv/getting-started/installation/)):
|
||||
LangBot — это **платформа с открытым исходным кодом производственного уровня** для создания ИИ-ботов в мессенджерах. Она связывает большие языковые модели (LLM) с любой чат-платформой, позволяя создавать интеллектуальных агентов, которые могут вести диалоги, выполнять задачи и интегрироваться с вашими существующими рабочими процессами.
|
||||
|
||||
### Ключевые возможности
|
||||
|
||||
- **ИИ-диалоги и агенты** — Многораундовые диалоги, вызов инструментов, мультимодальная поддержка, потоковый вывод. Встроенная реализация RAG (база знаний) с глубокой интеграцией в [Dify](https://dify.ai), [Coze](https://coze.com), [n8n](https://n8n.io), [Langflow](https://langflow.org).
|
||||
- **Универсальная поддержка IM-платформ** — Единая кодовая база для Discord, Telegram, Slack, LINE, QQ, WeChat, WeCom, Lark, DingTalk, KOOK.
|
||||
- **Готовность к продакшену** — Контроль доступа, ограничение скорости, фильтрация чувствительных слов, комплексный мониторинг и обработка исключений. Проверено в корпоративной среде.
|
||||
- **Экосистема плагинов** — Сотни плагинов, событийно-ориентированная архитектура, расширения компонентов и поддержка [протокола MCP](https://modelcontextprotocol.io/).
|
||||
- **Веб-панель управления** — Настраивайте, управляйте и мониторьте ваших ботов через интуитивный браузерный интерфейс. Ручное редактирование YAML не требуется.
|
||||
- **Мультиконвейерная архитектура** — Разные боты для разных сценариев с комплексным мониторингом и обработкой исключений.
|
||||
|
||||
[→ Подробнее обо всех возможностях](https://docs.langbot.app/en/insight/features.html)
|
||||
|
||||
---
|
||||
|
||||
## Быстрый старт
|
||||
|
||||
### ☁️ LangBot Cloud (Рекомендуется)
|
||||
|
||||
**[LangBot Cloud](https://space.langbot.app/cloud)** — Без развёртывания, готово к использованию.
|
||||
|
||||
### Запуск одной командой
|
||||
|
||||
```bash
|
||||
uvx langbot
|
||||
```
|
||||
|
||||
Посетите http://localhost:5300, чтобы начать использование.
|
||||
> Требуется [uv](https://docs.astral.sh/uv/getting-started/installation/). Откройте http://localhost:5300 — готово.
|
||||
|
||||
#### Развертывание с Docker Compose
|
||||
### Docker Compose
|
||||
|
||||
```bash
|
||||
git clone https://github.com/langbot-app/LangBot
|
||||
@@ -47,103 +70,101 @@ 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.
|
||||
### Облачное развертывание одним кликом
|
||||
|
||||
[](https://zeabur.com/en-US/templates/ZKTBDH)
|
||||
|
||||
#### Облачное развертывание Railway
|
||||
|
||||
[](https://railway.app/template/yRrAyL?referralCode=vogKPF)
|
||||
|
||||
#### Другие методы развертывания
|
||||
**Другие варианты:** [Docker](https://docs.langbot.app/en/deploy/langbot/docker.html) · [Ручная установка](https://docs.langbot.app/en/deploy/langbot/manual.html) · [BTPanel](https://docs.langbot.app/en/deploy/langbot/one-click/bt.html) · [Kubernetes](./docker/README_K8S.md)
|
||||
|
||||
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.
|
||||
|
||||
|
||||
|
||||
## ✨ Функции
|
||||
|
||||
<img width="500" src="https://docs.langbot.app/ui/bot-page-en-rounded.png" />
|
||||
|
||||
|
||||
- 💬 Чат с LLM / Agent: Поддержка нескольких LLM, адаптация к групповым и личным чатам; Поддержка многораундовых разговоров, вызовов инструментов, мультимодальных возможностей и потоковой передачи. Встроенная реализация RAG (база знаний) и глубокая интеграция с [Dify](https://dify.ai), [Coze](https://coze.com), [n8n](https://n8n.io), [Langflow](https://langflow.org) и др. LLMOps платформами.
|
||||
- 🤖 Многоплатформенная поддержка: В настоящее время поддерживает QQ, QQ Channel, WeCom, личный WeChat, Lark, DingTalk, Discord, Telegram, KOOK, Slack, LINE и т.д.
|
||||
- 🛠️ Высокая стабильность, богатство функций: Нативный контроль доступа, ограничение скорости, фильтрация чувствительных слов и т.д.; Простота в использовании, поддержка нескольких методов развертывания.
|
||||
- 🧩 Расширение плагинов, активное сообщество: Высокая стабильность, высокая безопасность уровня производства; Поддержка механизмов плагинов, управляемых событиями, расширения компонентов и т.д.; Интеграция протокола [MCP](https://modelcontextprotocol.io/) от Anthropic; В настоящее время сотни плагинов.
|
||||
- 😻 Веб-интерфейс: Поддержка управления экземплярами LangBot через браузер. Нет необходимости вручную писать конфигурационные файлы.
|
||||
- 📊 Функции уровня производства: Поддержка нескольких конфигураций конвейера, разные боты для разных сценариев. Имеет комплексные возможности мониторинга и обработки исключений.
|
||||
|
||||
Для более подробных спецификаций обратитесь к [документации](https://docs.langbot.app/en/insight/features.html).
|
||||
|
||||
Или посетите демонстрационную среду: https://demo.langbot.dev/
|
||||
- Информация для входа: Email: `demo@langbot.app` Пароль: `langbot123456`
|
||||
- Примечание: Только для демонстрации WebUI, пожалуйста, не вводите конфиденциальную информацию в общедоступной среде.
|
||||
|
||||
### Платформы обмена сообщениями
|
||||
## Поддерживаемые платформы
|
||||
|
||||
| Платформа | Статус | Примечания |
|
||||
| --- | --- | --- |
|
||||
|-----------|--------|------------|
|
||||
| Discord | ✅ | |
|
||||
| Telegram | ✅ | |
|
||||
| Slack | ✅ | |
|
||||
| LINE | ✅ | |
|
||||
| Личный QQ | ✅ | |
|
||||
| Официальный API QQ | ✅ | |
|
||||
| WeCom | ✅ | |
|
||||
| WeComCS | ✅ | |
|
||||
| WeCom AI Bot | ✅ | |
|
||||
| Личный WeChat | ✅ | |
|
||||
| KOOK | ✅ | |
|
||||
| QQ | ✅ | Личный и официальный API |
|
||||
| WeCom | ✅ | Корпоративный WeChat, внешний CS, AI-бот |
|
||||
| WeChat | ✅ | Личный и официальный аккаунт |
|
||||
| Lark | ✅ | |
|
||||
| DingTalk | ✅ | |
|
||||
| KOOK | ✅ | |
|
||||
| Satori | ✅ | |
|
||||
|
||||
### 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 |
|
||||
## Поддерживаемые LLM и интеграции
|
||||
|
||||
## 🤝 Вклад сообщества
|
||||
| Провайдер | Тип | Статус |
|
||||
|-----------|-----|--------|
|
||||
| [OpenAI](https://platform.openai.com/) | LLM | ✅ |
|
||||
| [Anthropic](https://www.anthropic.com/) | LLM | ✅ |
|
||||
| [DeepSeek](https://www.deepseek.com/) | LLM | ✅ |
|
||||
| [Google Gemini](https://aistudio.google.com/prompts/new_chat) | LLM | ✅ |
|
||||
| [xAI](https://x.ai/) | LLM | ✅ |
|
||||
| [Moonshot](https://www.moonshot.cn/) | LLM | ✅ |
|
||||
| [Zhipu AI](https://open.bigmodel.cn/) | LLM | ✅ |
|
||||
| [Ollama](https://ollama.com/) | Локальный LLM | ✅ |
|
||||
| [LM Studio](https://lmstudio.ai/) | Локальный LLM | ✅ |
|
||||
| [Dify](https://dify.ai) | LLMOps | ✅ |
|
||||
| [MCP](https://modelcontextprotocol.io/) | Протокол | ✅ |
|
||||
| [SiliconFlow](https://siliconflow.cn/) | Шлюз | ✅ |
|
||||
| [Aliyun Bailian](https://bailian.console.aliyun.com/) | Шлюз | ✅ |
|
||||
| [Volc Engine Ark](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | Шлюз | ✅ |
|
||||
| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | Шлюз | ✅ |
|
||||
| [GiteeAI](https://ai.gitee.com/) | Шлюз | ✅ |
|
||||
| [302.AI](https://share.302.ai/SuTG99) | Шлюз | ✅ |
|
||||
| [接口 AI](https://jiekou.ai/) | Шлюз | ✅ |
|
||||
| [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | Платформа GPU | ✅ |
|
||||
| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | Платформа GPU | ✅ |
|
||||
| [ShengSuanYun](https://www.shengsuanyun.com/?from=CH_KYIPP758) | Платформа GPU | ✅ |
|
||||
|
||||
Спасибо следующим [контрибьюторам кода](https://github.com/langbot-app/LangBot/graphs/contributors) и другим членам сообщества за их вклад в LangBot:
|
||||
[→ Смотреть все интеграции](https://docs.langbot.app/en/insight/features.html)
|
||||
|
||||
---
|
||||
|
||||
## Почему LangBot?
|
||||
|
||||
| Сценарий использования | Как помогает LangBot |
|
||||
|------------------------|----------------------|
|
||||
| **Поддержка клиентов** | Разверните ИИ-агентов в Slack/Discord/Telegram, которые отвечают на вопросы, используя вашу базу знаний |
|
||||
| **Внутренние инструменты** | Подключите рабочие процессы n8n/Dify к WeCom/DingTalk для автоматизации бизнес-процессов |
|
||||
| **Управление сообществом** | Модерируйте группы QQ/Discord с помощью ИИ-фильтрации контента и взаимодействия |
|
||||
| **Мультиплатформенное присутствие** | Один бот — все платформы. Управляйте из единой панели |
|
||||
|
||||
---
|
||||
|
||||
## Демо
|
||||
|
||||
**Попробуйте прямо сейчас:** https://demo.langbot.dev/
|
||||
- Email: `demo@langbot.app`
|
||||
- Пароль: `langbot123456`
|
||||
|
||||
*Примечание: Публичная демо-среда. Не вводите конфиденциальную информацию.*
|
||||
|
||||
---
|
||||
|
||||
## Сообщество
|
||||
|
||||
[](https://discord.gg/wdNEHETs87)
|
||||
|
||||
- [Сообщество Discord](https://discord.gg/wdNEHETs87)
|
||||
|
||||
---
|
||||
|
||||
## История Stars
|
||||
|
||||
[](https://star-history.com/#langbot-app/LangBot&Date)
|
||||
|
||||
---
|
||||
|
||||
## Участники
|
||||
|
||||
Спасибо всем [участникам](https://github.com/langbot-app/LangBot/graphs/contributors), которые помогли сделать LangBot лучше:
|
||||
|
||||
<a href="https://github.com/langbot-app/LangBot/graphs/contributors">
|
||||
<img src="https://contrib.rocks/image?repo=langbot-app/LangBot" />
|
||||
|
||||
221
README_TW.md
221
README_TW.md
@@ -1,25 +1,29 @@
|
||||
<p align="center">
|
||||
<a href="https://langbot.app">
|
||||
<img width="130" src="https://docs.langbot.app/langbot-logo.png" alt="LangBot"/>
|
||||
<img width="130" src="res/logo-blue.png" alt="LangBot"/>
|
||||
</a>
|
||||
|
||||
<div align="center"><a href="https://hellogithub.com/repository/langbot-app/LangBot" target="_blank"><img src="https://abroad.hellogithub.com/v1/widgets/recommend.svg?rid=5ce8ae2aa4f74316bf393b57b952433c&claim_uid=gtmc6YWjMZkT21R" alt="Featured｜HelloGitHub" style="width: 250px; height: 54px;" width="250" height="54" /></a>
|
||||
<div align="center">
|
||||
|
||||
<h3>使用 LangBot 快速建構、除錯和部署 IM 機器人。</h3>
|
||||
<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) / [Español](README_ES.md) / [Français](README_FR.md) / [한국어](README_KO.md) / [Русский](README_RU.md) / [Tiếng Việt](README_VI.md)
|
||||
<h3>生產級 AI 即時通訊機器人開發平台。</h3>
|
||||
<h4>快速建構、除錯和部署 AI 機器人到微信、QQ、飛書、Slack、Discord、Telegram 等平台。</h4>
|
||||
|
||||
[English](README.md) / [简体中文](README_CN.md) / 繁體中文 / [日本語](README_JP.md) / [Español](README_ES.md) / [Français](README_FR.md) / [한국어](README_KO.md) / [Русский](README_RU.md) / [Tiếng Việt](README_VI.md)
|
||||
|
||||
[](https://discord.gg/wdNEHETs87)
|
||||
[](https://qm.qq.com/q/JLi38whHum)
|
||||
[](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">主頁</a> ｜
|
||||
<a href="https://docs.langbot.app/zh/insight/features.html">規格特性</a> ｜
|
||||
<a href="https://docs.langbot.app/zh/insight/guide.html">部署文件</a> ｜
|
||||
<a href="https://docs.langbot.app/zh/tags/readme.html">API 整合</a> ｜
|
||||
<a href="https://langbot.app">官網</a> ｜
|
||||
<a href="https://docs.langbot.app/zh/insight/features.html">特性</a> ｜
|
||||
<a href="https://docs.langbot.app/zh/insight/guide.html">文件</a> ｜
|
||||
<a href="https://docs.langbot.app/zh/tags/readme.html">API</a> ｜
|
||||
<a href="https://space.langbot.app">外掛市場</a> ｜
|
||||
<a href="https://langbot.featurebase.app/roadmap">路線圖</a>
|
||||
|
||||
@@ -27,19 +31,40 @@
|
||||
|
||||
</p>
|
||||
|
||||
## 📦 開始使用
|
||||
---
|
||||
|
||||
#### 快速部署
|
||||
## 什麼是 LangBot？
|
||||
|
||||
使用 `uvx` 一鍵啟動（需要先安裝 [uv](https://docs.astral.sh/uv/getting-started/installation/) ）：
|
||||
LangBot 是一個**開源的生產級平台**，用於建構 AI 驅動的即時通訊機器人。它將大語言模型（LLM）連接到各種聊天平台，幫助你創建能夠對話、執行任務、並整合到現有工作流程中的智能 Agent。
|
||||
|
||||
### 核心能力
|
||||
|
||||
- **AI 對話與 Agent** — 多輪對話、工具調用、多模態、流式輸出。自帶 RAG（知識庫），深度整合 [Dify](https://dify.ai)、[Coze](https://coze.com)、[n8n](https://n8n.io)、[Langflow](https://langflow.org) 等 LLMOps 平台。
|
||||
- **全平台支援** — 一套程式碼，覆蓋 QQ、微信、企業微信、飛書、釘釘、Discord、Telegram、Slack、LINE、KOOK 等平台。
|
||||
- **生產就緒** — 存取控制、限速、敏感詞過濾、全面監控與異常處理，已被多家企業採用。
|
||||
- **外掛生態** — 數百個外掛，事件驅動架構，組件擴展，適配 [MCP 協議](https://modelcontextprotocol.io/)。
|
||||
- **Web 管理面板** — 透過瀏覽器直觀地配置、管理和監控機器人，無需手動編輯設定檔。
|
||||
- **多流水線架構** — 不同機器人用於不同場景，具備全面的監控和異常處理能力。
|
||||
|
||||
[→ 了解更多功能特性](https://docs.langbot.app/zh/insight/features.html)
|
||||
|
||||
---
|
||||
|
||||
## 快速開始
|
||||
|
||||
### ☁️ LangBot Cloud（推薦）
|
||||
|
||||
**[LangBot Cloud](https://space.langbot.app/cloud)** — 免部署，開箱即用。
|
||||
|
||||
### 一鍵啟動
|
||||
|
||||
```bash
|
||||
uvx langbot
|
||||
```
|
||||
|
||||
訪問 http://localhost:5300 即可開始使用。
|
||||
> 需要安裝 [uv](https://docs.astral.sh/uv/getting-started/installation/)。訪問 http://localhost:5300 即可使用。
|
||||
|
||||
#### Docker Compose 部署
|
||||
### Docker Compose
|
||||
|
||||
```bash
|
||||
git clone https://github.com/langbot-app/LangBot
|
||||
@@ -47,104 +72,63 @@ cd LangBot/docker
|
||||
docker compose up -d
|
||||
```
|
||||
|
||||
訪問 http://localhost:5300 即可開始使用。
|
||||
|
||||
詳細文件[Docker 部署](https://docs.langbot.app/zh/deploy/langbot/docker.html)。
|
||||
|
||||
#### 寶塔面板部署
|
||||
|
||||
已上架寶塔面板，若您已安裝寶塔面板，可以根據[文件](https://docs.langbot.app/zh/deploy/langbot/one-click/bt.html)使用。
|
||||
|
||||
#### Zeabur 雲端部署
|
||||
|
||||
社群貢獻的 Zeabur 模板。
|
||||
### 一鍵雲端部署
|
||||
|
||||
[](https://zeabur.com/zh-CN/templates/ZKTBDH)
|
||||
|
||||
#### Railway 雲端部署
|
||||
|
||||
[](https://railway.app/template/yRrAyL?referralCode=vogKPF)
|
||||
|
||||
#### 手動部署
|
||||
**更多方式：** [Docker](https://docs.langbot.app/zh/deploy/langbot/docker.html) · [手動部署](https://docs.langbot.app/zh/deploy/langbot/manual.html) · [寶塔面板](https://docs.langbot.app/zh/deploy/langbot/one-click/bt.html) · [Kubernetes](./docker/README_K8S.md)
|
||||
|
||||
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。
|
||||
|
||||
|
||||
|
||||
## ✨ 特性
|
||||
|
||||
<img width="500" src="https://docs.langbot.app/ui/bot-page-en-rounded.png" />
|
||||
|
||||
|
||||
- 💬 大模型對話、Agent：支援多種大模型，適配群聊和私聊；具有多輪對話、工具調用、多模態、流式輸出能力，自帶 RAG（知識庫）實現，並深度適配 [Dify](https://dify.ai)、[Coze](https://coze.com)、[n8n](https://n8n.io)、[Langflow](https://langflow.org)等 LLMOps 平台。
|
||||
- 🤖 多平台支援：目前支援 QQ、QQ頻道、企業微信、個人微信、飛書、Discord、Telegram、KOOK、Slack、LINE 等平台。
|
||||
- 🛠️ 高穩定性、功能完備：原生支援訪問控制、限速、敏感詞過濾等機制；配置簡單，支援多種部署方式。
|
||||
- 🧩 外掛擴展、活躍社群：高穩定性、高安全性的生產級外掛系統；支援事件驅動、組件擴展等外掛機制；適配 Anthropic [MCP 協議](https://modelcontextprotocol.io/)；目前已有數百個外掛。
|
||||
- 😻 Web 管理面板：提供先進的 WebUI 管理面板，用最直觀的方式配置、管理、監控機器人。
|
||||
- 📊 生產級特性：支援多流水線配置，不同機器人用於不同應用場景。具有全面的監控和異常處理能力。
|
||||
|
||||
詳細規格特性請訪問[文件](https://docs.langbot.app/zh/insight/features.html)。
|
||||
|
||||
或訪問 demo 環境：https://demo.langbot.dev/
|
||||
- 登入資訊：郵箱：`demo@langbot.app` 密碼：`langbot123456`
|
||||
- 注意：僅展示 WebUI 效果，公開環境，請不要在其中填入您的任何敏感資訊。
|
||||
|
||||
### 訊息平台
|
||||
## 支援的平台
|
||||
|
||||
| 平台 | 狀態 | 備註 |
|
||||
| --- | --- | --- |
|
||||
|------|------|------|
|
||||
| QQ | ✅ | 個人號、官方機器人（頻道、私聊、群聊） |
|
||||
| 微信 | ✅ | 個人微信、微信公眾號 |
|
||||
| 企業微信 | ✅ | 應用訊息、對外客服、智能機器人 |
|
||||
| 飛書 | ✅ | |
|
||||
| 釘釘 | ✅ | |
|
||||
| Discord | ✅ | |
|
||||
| Telegram | ✅ | |
|
||||
| Slack | ✅ | |
|
||||
| LINE | ✅ | |
|
||||
| QQ 個人號 | ✅ | QQ 個人號私聊、群聊 |
|
||||
| QQ 官方機器人 | ✅ | QQ 官方機器人，支援頻道、私聊、群聊 |
|
||||
| 微信 | ✅ | |
|
||||
| 企微對外客服 | ✅ | |
|
||||
| 企微智能機器人 | ✅ | |
|
||||
| 微信公眾號 | ✅ | |
|
||||
| KOOK | ✅ | |
|
||||
| Lark | ✅ | |
|
||||
| DingTalk | ✅ | |
|
||||
| Satori | ✅ | |
|
||||
|
||||
### 大模型能力
|
||||
---
|
||||
|
||||
| 模型 | 狀態 | 備註 |
|
||||
| --- | --- | --- |
|
||||
| [OpenAI](https://platform.openai.com/) | ✅ | 可接入任何 OpenAI 介面格式模型 |
|
||||
| [DeepSeek](https://www.deepseek.com/) | ✅ | |
|
||||
| [Moonshot](https://www.moonshot.cn/) | ✅ | |
|
||||
| [Anthropic](https://www.anthropic.com/) | ✅ | |
|
||||
| [xAI](https://x.ai/) | ✅ | |
|
||||
| [智譜AI](https://open.bigmodel.cn/) | ✅ | |
|
||||
| [勝算雲](https://www.shengsuanyun.com/?from=CH_KYIPP758) | ✅ | 大模型和 GPU 資源平台 |
|
||||
| [優雲智算](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | ✅ | 大模型和 GPU 資源平台 |
|
||||
| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | ✅ | 大模型和 GPU 資源平台 |
|
||||
| [接口 AI](https://jiekou.ai/) | ✅ | 大模型聚合平台，專注全球大模型接入 |
|
||||
| [302.AI](https://share.302.ai/SuTG99) | ✅ | 大模型聚合平台 |
|
||||
| [Google Gemini](https://aistudio.google.com/prompts/new_chat) | ✅ | |
|
||||
| [Dify](https://dify.ai) | ✅ | LLMOps 平台 |
|
||||
| [Ollama](https://ollama.com/) | ✅ | 本地大模型運行平台 |
|
||||
| [LMStudio](https://lmstudio.ai/) | ✅ | 本地大模型運行平台 |
|
||||
| [GiteeAI](https://ai.gitee.com/) | ✅ | 大模型介面聚合平台 |
|
||||
| [SiliconFlow](https://siliconflow.cn/) | ✅ | 大模型聚合平台 |
|
||||
| [阿里雲百煉](https://bailian.console.aliyun.com/) | ✅ | 大模型聚合平台, LLMOps 平台 |
|
||||
| [火山方舟](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | ✅ | 大模型聚合平台, LLMOps 平台 |
|
||||
| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | ✅ | 大模型聚合平台 |
|
||||
| [MCP](https://modelcontextprotocol.io/) | ✅ | 支援通過 MCP 協議獲取工具 |
|
||||
## 支援的大模型與整合
|
||||
|
||||
### TTS
|
||||
| 提供商 | 類型 | 狀態 |
|
||||
|--------|------|------|
|
||||
| [OpenAI](https://platform.openai.com/) | LLM | ✅ |
|
||||
| [Anthropic](https://www.anthropic.com/) | LLM | ✅ |
|
||||
| [DeepSeek](https://www.deepseek.com/) | LLM | ✅ |
|
||||
| [Google Gemini](https://aistudio.google.com/prompts/new_chat) | LLM | ✅ |
|
||||
| [xAI](https://x.ai/) | LLM | ✅ |
|
||||
| [Moonshot](https://www.moonshot.cn/) | LLM | ✅ |
|
||||
| [智譜AI](https://open.bigmodel.cn/) | LLM | ✅ |
|
||||
| [Ollama](https://ollama.com/) | 本地 LLM | ✅ |
|
||||
| [LM Studio](https://lmstudio.ai/) | 本地 LLM | ✅ |
|
||||
| [Dify](https://dify.ai) | LLMOps | ✅ |
|
||||
| [MCP](https://modelcontextprotocol.io/) | 協議 | ✅ |
|
||||
| [SiliconFlow](https://siliconflow.cn/) | 聚合平台 | ✅ |
|
||||
| [阿里雲百煉](https://bailian.console.aliyun.com/) | 聚合平台 | ✅ |
|
||||
| [火山方舟](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | 聚合平台 | ✅ |
|
||||
| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | 聚合平台 | ✅ |
|
||||
| [GiteeAI](https://ai.gitee.com/) | 聚合平台 | ✅ |
|
||||
| [勝算雲](https://www.shengsuanyun.com/?from=CH_KYIPP758) | GPU 平台 | ✅ |
|
||||
| [優雲智算](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | GPU 平台 | ✅ |
|
||||
| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | GPU 平台 | ✅ |
|
||||
| [接口 AI](https://jiekou.ai/) | 聚合平台 | ✅ |
|
||||
| [302.AI](https://share.302.ai/SuTG99) | 聚合平台 | ✅ |
|
||||
|
||||
### TTS（語音合成）
|
||||
|
||||
| 平台/模型 | 備註 |
|
||||
| --- | --- |
|
||||
|-----------|------|
|
||||
| [FishAudio](https://fish.audio/zh-CN/discovery/) | [外掛](https://github.com/the-lazy-me/NewChatVoice) |
|
||||
| [海豚 AI](https://www.ttson.cn/?source=thelazy) | [外掛](https://github.com/the-lazy-me/NewChatVoice) |
|
||||
| [AzureTTS](https://portal.azure.com/) | [外掛](https://github.com/Ingnaryk/LangBot_AzureTTS) |
|
||||
@@ -152,13 +136,54 @@ docker compose up -d
|
||||
### 文生圖
|
||||
|
||||
| 平台/模型 | 備註 |
|
||||
| --- | --- |
|
||||
| 阿里雲百煉 | [外掛](https://github.com/Thetail001/LangBot_BailianTextToImagePlugin)
|
||||
|-----------|------|
|
||||
| 阿里雲百煉 | [外掛](https://github.com/Thetail001/LangBot_BailianTextToImagePlugin) |
|
||||
|
||||
## 😘 社群貢獻
|
||||
[→ 查看完整整合列表](https://docs.langbot.app/zh/insight/features.html)
|
||||
|
||||
感謝以下[程式碼貢獻者](https://github.com/langbot-app/LangBot/graphs/contributors)和社群裡其他成員對 LangBot 的貢獻：
|
||||
---
|
||||
|
||||
## 為什麼選擇 LangBot？
|
||||
|
||||
| 使用場景 | LangBot 如何幫助 |
|
||||
|----------|------------------|
|
||||
| **客戶服務** | 將 AI Agent 部署到微信/企微/釘釘/飛書，基於知識庫自動回答使用者問題 |
|
||||
| **內部工具** | 將 n8n/Dify 工作流接入企微/釘釘，實現業務流程自動化 |
|
||||
| **社群運營** | 在 QQ/Discord 群中使用 AI 驅動的內容審核與智能互動 |
|
||||
| **多平台觸達** | 一個機器人，覆蓋所有平台。透過統一面板集中管理 |
|
||||
|
||||
---
|
||||
|
||||
## 線上演示
|
||||
|
||||
**立即體驗：** https://demo.langbot.dev/
|
||||
- 信箱：`demo@langbot.app`
|
||||
- 密碼：`langbot123456`
|
||||
|
||||
*注意：公開演示環境，請不要在其中填入任何敏感資訊。*
|
||||
|
||||
---
|
||||
|
||||
## 社群
|
||||
|
||||
[](https://discord.gg/wdNEHETs87)
|
||||
[](https://qm.qq.com/q/JLi38whHum)
|
||||
|
||||
- [Discord 社群](https://discord.gg/wdNEHETs87)
|
||||
- [QQ 社群群](https://qm.qq.com/q/JLi38whHum)
|
||||
|
||||
---
|
||||
|
||||
## Star 趨勢
|
||||
|
||||
[](https://star-history.com/#langbot-app/LangBot&Date)
|
||||
|
||||
---
|
||||
|
||||
## 貢獻者
|
||||
|
||||
感謝所有[貢獻者](https://github.com/langbot-app/LangBot/graphs/contributors)對 LangBot 的幫助：
|
||||
|
||||
<a href="https://github.com/langbot-app/LangBot/graphs/contributors">
|
||||
<img src="https://contrib.rocks/image?repo=langbot-app/LangBot" />
|
||||
</a>
|
||||
</a>
|
||||
|
||||
199
README_VI.md
199
README_VI.md
@@ -1,25 +1,27 @@
|
||||
<p align="center">
|
||||
<a href="https://langbot.app">
|
||||
<img width="130" src="https://docs.langbot.app/langbot-logo.png" alt="LangBot"/>
|
||||
<img width="130" src="res/logo-blue.png" alt="LangBot"/>
|
||||
</a>
|
||||
|
||||
<div align="center">
|
||||
|
||||
<a href="https://www.producthunt.com/products/langbot?utm_source=badge-follow&utm_medium=badge&utm_source=badge-langbot" target="_blank"><img src="https://api.producthunt.com/widgets/embed-image/v1/follow.svg?product_id=1077185&theme=light" alt="LangBot - Production-grade IM bot made easy. | Product Hunt" style="width: 250px; height: 54px;" width="250" height="54" /></a>
|
||||
|
||||
<h3>Xây dựng, gỡ lỗi và triển khai bot IM nhanh chóng với LangBot.</h3>
|
||||
<h3>Nền tảng cấp sản xuất để xây dựng bot IM với AI agent.</h3>
|
||||
<h4>Xây dựng, gỡ lỗi và triển khai bot AI nhanh chóng trên Slack, Discord, Telegram, WeChat và nhiều nền tảng khác.</h4>
|
||||
|
||||
[English](README_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
|
||||
[English](README.md) / [简体中文](README_CN.md) / [繁體中文](README_TW.md) / [日本語](README_JP.md) / [Español](README_ES.md) / [Français](README_FR.md) / [한국어](README_KO.md) / [Русский](README_RU.md) / Tiếng Việt
|
||||
|
||||
[](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">Trang chủ</a> ｜
|
||||
<a href="https://docs.langbot.app/en/insight/features.html">Tính năng</a> ｜
|
||||
<a href="https://docs.langbot.app/en/insight/guide.html">Triển khai</a> ｜
|
||||
<a href="https://docs.langbot.app/en/tags/readme.html">Tích hợp API</a> ｜
|
||||
<a href="https://docs.langbot.app/en/insight/guide.html">Tài liệu</a> ｜
|
||||
<a href="https://docs.langbot.app/en/tags/readme.html">API</a> ｜
|
||||
<a href="https://space.langbot.app">Chợ Plugin</a> ｜
|
||||
<a href="https://langbot.featurebase.app/roadmap">Lộ trình</a>
|
||||
|
||||
@@ -27,19 +29,40 @@
|
||||
|
||||
</p>
|
||||
|
||||
## 📦 Bắt đầu
|
||||
---
|
||||
|
||||
#### Khởi động Nhanh
|
||||
## LangBot là gì?
|
||||
|
||||
Sử dụng `uvx` để khởi động bằng một lệnh (cần cài đặt [uv](https://docs.astral.sh/uv/getting-started/installation/)):
|
||||
LangBot là một **nền tảng mã nguồn mở, cấp sản xuất** để xây dựng bot nhắn tin tức thời được hỗ trợ bởi AI. Nó kết nối các Mô hình Ngôn ngữ Lớn (LLM) với bất kỳ nền tảng chat nào, cho phép bạn tạo các agent thông minh có thể trò chuyện, thực hiện tác vụ và tích hợp với quy trình làm việc hiện có của bạn.
|
||||
|
||||
### Khả năng chính
|
||||
|
||||
- **Hội thoại AI & Agent** — Đối thoại nhiều lượt, gọi công cụ, hỗ trợ đa phương thức, đầu ra streaming. RAG (cơ sở kiến thức) tích hợp sẵn với tích hợp sâu vào [Dify](https://dify.ai), [Coze](https://coze.com), [n8n](https://n8n.io), [Langflow](https://langflow.org).
|
||||
- **Hỗ trợ đa nền tảng IM** — Một mã nguồn cho Discord, Telegram, Slack, LINE, QQ, WeChat, WeCom, Lark, DingTalk, KOOK.
|
||||
- **Sẵn sàng cho sản xuất** — Kiểm soát truy cập, giới hạn tốc độ, lọc từ nhạy cảm, giám sát toàn diện và xử lý ngoại lệ. Được doanh nghiệp tin dùng.
|
||||
- **Hệ sinh thái Plugin** — Hàng trăm plugin, kiến trúc hướng sự kiện, mở rộng thành phần, và hỗ trợ [giao thức MCP](https://modelcontextprotocol.io/).
|
||||
- **Bảng quản lý Web** — Cấu hình, quản lý và giám sát bot thông qua giao diện trình duyệt trực quan. Không cần chỉnh sửa YAML.
|
||||
- **Kiến trúc đa Pipeline** — Các bot khác nhau cho các kịch bản khác nhau, với giám sát toàn diện và xử lý ngoại lệ.
|
||||
|
||||
[→ Tìm hiểu thêm về tất cả tính năng](https://docs.langbot.app/en/insight/features.html)
|
||||
|
||||
---
|
||||
|
||||
## Bắt đầu nhanh
|
||||
|
||||
### ☁️ LangBot Cloud (Khuyên dùng)
|
||||
|
||||
**[LangBot Cloud](https://space.langbot.app/cloud)** — Không cần triển khai, sẵn sàng sử dụng.
|
||||
|
||||
### Khởi chạy một dòng
|
||||
|
||||
```bash
|
||||
uvx langbot
|
||||
```
|
||||
|
||||
Truy cập http://localhost:5300 để bắt đầu sử dụng.
|
||||
> Yêu cầu [uv](https://docs.astral.sh/uv/getting-started/installation/). Truy cập http://localhost:5300 — xong.
|
||||
|
||||
#### Triển khai Docker Compose
|
||||
### Docker Compose
|
||||
|
||||
```bash
|
||||
git clone https://github.com/langbot-app/LangBot
|
||||
@@ -47,103 +70,101 @@ 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.
|
||||
### Triển khai đám mây một cú nhấp
|
||||
|
||||
[](https://zeabur.com/en-US/templates/ZKTBDH)
|
||||
|
||||
#### Triển khai Cloud Railway
|
||||
|
||||
[](https://railway.app/template/yRrAyL?referralCode=vogKPF)
|
||||
|
||||
#### Các Phương pháp Triển khai Khác
|
||||
**Thêm tùy chọn:** [Docker](https://docs.langbot.app/en/deploy/langbot/docker.html) · [Thủ công](https://docs.langbot.app/en/deploy/langbot/manual.html) · [BTPanel](https://docs.langbot.app/en/deploy/langbot/one-click/bt.html) · [Kubernetes](./docker/README_K8S.md)
|
||||
|
||||
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.
|
||||
|
||||
|
||||
|
||||
## ✨ Tính năng
|
||||
|
||||
<img width="500" src="https://docs.langbot.app/ui/bot-page-en-rounded.png" />
|
||||
|
||||
|
||||
- 💬 Chat với LLM / Agent: Hỗ trợ nhiều LLM, thích ứng với chat nhóm và chat riêng tư; Hỗ trợ các cuộc trò chuyện nhiều vòng, gọi công cụ, khả năng đa phương thức và đầu ra streaming. Triển khai RAG (cơ sở kiến thức) tích hợp sẵn và tích hợp sâu với [Dify](https://dify.ai), [Coze](https://coze.com), [n8n](https://n8n.io), [Langflow](https://langflow.org) v.v. LLMOps platforms.
|
||||
- 🤖 Hỗ trợ Đa nền tảng: Hiện hỗ trợ QQ, QQ Channel, WeCom, WeChat cá nhân, Lark, DingTalk, Discord, Telegram, KOOK, Slack, LINE, v.v.
|
||||
- 🛠️ Độ ổn định Cao, Tính năng Phong phú: Kiểm soát truy cập gốc, giới hạn tốc độ, lọc từ nhạy cảm, v.v.; Dễ sử dụng, hỗ trợ nhiều phương pháp triển khai.
|
||||
- 🧩 Mở rộng Plugin, Cộng đồng Hoạt động: Hỗ trợ các cơ chế plugin hướng sự kiện, mở rộng thành phần, v.v.; Tích hợp giao thức [MCP](https://modelcontextprotocol.io/) của Anthropic; Hiện có hàng trăng plugin.
|
||||
- 😻 Giao diện Web: Hỗ trợ quản lý các phiên bản LangBot thông qua trình duyệt. Không cần viết tệp cấu hình thủ công.
|
||||
- 📊 Tính năng Cấp sản xuất: Hỗ trợ nhiều cấu hình pipeline, các bot khác nhau cho các kịch bản khác nhau. Có khả năng giám sát toàn diện và xử lý ngoại lệ.
|
||||
|
||||
Để biết thêm thông số kỹ thuật chi tiết, vui lòng tham khảo [tài liệu](https://docs.langbot.app/en/insight/features.html).
|
||||
|
||||
Hoặc truy cập môi trường demo: https://demo.langbot.dev/
|
||||
- Thông tin đăng nhập: Email: `demo@langbot.app` Mật khẩu: `langbot123456`
|
||||
- Lưu ý: Chỉ dành cho demo WebUI, vui lòng không nhập bất kỳ thông tin nhạy cảm nào trong môi trường công cộng.
|
||||
|
||||
### Nền tảng Nhắn tin
|
||||
## Nền tảng được hỗ trợ
|
||||
|
||||
| Nền tảng | Trạng thái | Ghi chú |
|
||||
| --- | --- | --- |
|
||||
|----------|--------|-------|
|
||||
| Discord | ✅ | |
|
||||
| Telegram | ✅ | |
|
||||
| Slack | ✅ | |
|
||||
| LINE | ✅ | |
|
||||
| QQ Cá nhân | ✅ | |
|
||||
| QQ API Chính thức | ✅ | |
|
||||
| WeCom | ✅ | |
|
||||
| WeComCS | ✅ | |
|
||||
| WeCom AI Bot | ✅ | |
|
||||
| WeChat Cá nhân | ✅ | |
|
||||
| KOOK | ✅ | |
|
||||
| QQ | ✅ | Cá nhân & API chính thức |
|
||||
| WeCom | ✅ | WeChat doanh nghiệp, CS bên ngoài, AI Bot |
|
||||
| WeChat | ✅ | Cá nhân & Tài khoản công khai |
|
||||
| Lark | ✅ | |
|
||||
| DingTalk | ✅ | |
|
||||
| KOOK | ✅ | |
|
||||
| Satori | ✅ | |
|
||||
|
||||
### 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 |
|
||||
## LLM và tích hợp được hỗ trợ
|
||||
|
||||
## 🤝 Đóng góp Cộng đồng
|
||||
| Nhà cung cấp | Loại | Trạng thái |
|
||||
|----------|------|--------|
|
||||
| [OpenAI](https://platform.openai.com/) | LLM | ✅ |
|
||||
| [Anthropic](https://www.anthropic.com/) | LLM | ✅ |
|
||||
| [DeepSeek](https://www.deepseek.com/) | LLM | ✅ |
|
||||
| [Google Gemini](https://aistudio.google.com/prompts/new_chat) | LLM | ✅ |
|
||||
| [xAI](https://x.ai/) | LLM | ✅ |
|
||||
| [Moonshot](https://www.moonshot.cn/) | LLM | ✅ |
|
||||
| [Zhipu AI](https://open.bigmodel.cn/) | LLM | ✅ |
|
||||
| [Ollama](https://ollama.com/) | LLM cục bộ | ✅ |
|
||||
| [LM Studio](https://lmstudio.ai/) | LLM cục bộ | ✅ |
|
||||
| [Dify](https://dify.ai) | LLMOps | ✅ |
|
||||
| [MCP](https://modelcontextprotocol.io/) | Giao thức | ✅ |
|
||||
| [SiliconFlow](https://siliconflow.cn/) | Cổng | ✅ |
|
||||
| [Aliyun Bailian](https://bailian.console.aliyun.com/) | Cổng | ✅ |
|
||||
| [Volc Engine Ark](https://console.volcengine.com/ark/region:ark+cn-beijing/model?vendor=Bytedance&view=LIST_VIEW) | Cổng | ✅ |
|
||||
| [ModelScope](https://modelscope.cn/docs/model-service/API-Inference/intro) | Cổng | ✅ |
|
||||
| [GiteeAI](https://ai.gitee.com/) | Cổng | ✅ |
|
||||
| [CompShare](https://www.compshare.cn/?ytag=GPU_YY-gh_langbot) | Nền tảng GPU | ✅ |
|
||||
| [PPIO](https://ppinfra.com/user/register?invited_by=QJKFYD&utm_source=github_langbot) | Nền tảng GPU | ✅ |
|
||||
| [ShengSuanYun](https://www.shengsuanyun.com/?from=CH_KYIPP758) | Nền tảng GPU | ✅ |
|
||||
| [接口 AI](https://jiekou.ai/) | Cổng | ✅ |
|
||||
| [302.AI](https://share.302.ai/SuTG99) | Cổng | ✅ |
|
||||
|
||||
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:
|
||||
[→ Xem tất cả tích hợp](https://docs.langbot.app/en/insight/features.html)
|
||||
|
||||
---
|
||||
|
||||
## Tại sao chọn LangBot?
|
||||
|
||||
| Trường hợp sử dụng | LangBot giúp như thế nào |
|
||||
|----------|-------------------|
|
||||
| **Hỗ trợ khách hàng** | Triển khai agent AI trên Slack/Discord/Telegram để trả lời câu hỏi bằng cơ sở kiến thức của bạn |
|
||||
| **Công cụ nội bộ** | Kết nối quy trình n8n/Dify với WeCom/DingTalk để tự động hóa quy trình kinh doanh |
|
||||
| **Quản lý cộng đồng** | Quản lý nhóm QQ/Discord với tính năng lọc nội dung và tương tác được hỗ trợ bởi AI |
|
||||
| **Đa nền tảng** | Một bot, tất cả nền tảng. Quản lý từ một bảng điều khiển duy nhất |
|
||||
|
||||
---
|
||||
|
||||
## Demo trực tuyến
|
||||
|
||||
**Thử ngay:** https://demo.langbot.dev/
|
||||
- Email: `demo@langbot.app`
|
||||
- Mật khẩu: `langbot123456`
|
||||
|
||||
*Lưu ý: Môi trường demo công khai. Không nhập thông tin nhạy cảm.*
|
||||
|
||||
---
|
||||
|
||||
## Cộng đồng
|
||||
|
||||
[](https://discord.gg/wdNEHETs87)
|
||||
|
||||
- [Cộng đồng Discord](https://discord.gg/wdNEHETs87)
|
||||
|
||||
---
|
||||
|
||||
## Lịch sử Star
|
||||
|
||||
[](https://star-history.com/#langbot-app/LangBot&Date)
|
||||
|
||||
---
|
||||
|
||||
## Người đóng góp
|
||||
|
||||
Cảm ơn tất cả [người đóng góp](https://github.com/langbot-app/LangBot/graphs/contributors) đã giúp LangBot trở nên tốt hơn:
|
||||
|
||||
<a href="https://github.com/langbot-app/LangBot/graphs/contributors">
|
||||
<img src="https://contrib.rocks/image?repo=langbot-app/LangBot" />
|
||||
|
||||
@@ -9,7 +9,7 @@
|
||||
"url": "https://langbot.app"
|
||||
},
|
||||
"license": {
|
||||
"name": "AGPL-3.0",
|
||||
"name": "Apache-2.0",
|
||||
"url": "https://github.com/langbot-app/LangBot/blob/master/LICENSE"
|
||||
}
|
||||
},
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
[project]
|
||||
name = "langbot"
|
||||
version = "4.8.1"
|
||||
version = "4.8.7"
|
||||
description = "Production-grade platform for building agentic IM bots"
|
||||
readme = "README.md"
|
||||
license-files = ["LICENSE"]
|
||||
@@ -17,7 +17,7 @@ dependencies = [
|
||||
"certifi>=2025.4.26",
|
||||
"colorlog~=6.6.0",
|
||||
"cryptography>=44.0.3",
|
||||
"dashscope>=1.23.2",
|
||||
"dashscope>=1.25.10",
|
||||
"dingtalk-stream>=0.24.0",
|
||||
"discord-py>=2.5.2",
|
||||
"pynacl>=1.5.0", # Required for Discord voice support
|
||||
@@ -64,13 +64,14 @@ dependencies = [
|
||||
"chromadb>=0.4.24",
|
||||
"qdrant-client (>=1.15.1,<2.0.0)",
|
||||
"pyseekdb==1.0.0b7",
|
||||
"langbot-plugin==0.2.5",
|
||||
"langbot-plugin==0.2.7",
|
||||
"asyncpg>=0.30.0",
|
||||
"line-bot-sdk>=3.19.0",
|
||||
"tboxsdk>=0.0.10",
|
||||
"boto3>=1.35.0",
|
||||
"pymilvus>=2.6.4",
|
||||
"pgvector>=0.4.1",
|
||||
"botocore>=1.42.39",
|
||||
]
|
||||
keywords = [
|
||||
"bot",
|
||||
|
||||
BIN
res/logo-blue.png
Normal file
BIN
res/logo-blue.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 24 KiB |
@@ -1,3 +1,3 @@
|
||||
"""LangBot - Production-grade platform for building agentic IM bots"""
|
||||
|
||||
__version__ = '4.8.1'
|
||||
__version__ = '4.8.7'
|
||||
|
||||
@@ -347,10 +347,15 @@ class DingTalkClient:
|
||||
raise Exception(f'failed to send proactive massage to group: {traceback.format_exc()}')
|
||||
|
||||
async def create_and_card(
|
||||
self, temp_card_id: str, incoming_message: dingtalk_stream.ChatbotMessage, quote_origin: bool = False
|
||||
self,
|
||||
temp_card_id: str,
|
||||
incoming_message: dingtalk_stream.ChatbotMessage,
|
||||
quote_origin: bool = False,
|
||||
card_auto_layout: bool = False,
|
||||
):
|
||||
content_key = 'content'
|
||||
card_data = {content_key: ''}
|
||||
card_data = {}
|
||||
card_data['config'] = json.dumps({'autoLayout': card_auto_layout})
|
||||
card_data['content'] = ''
|
||||
|
||||
card_instance = dingtalk_stream.AICardReplier(self.client, incoming_message)
|
||||
# print(card_instance)
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
import requests
|
||||
import aiohttp
|
||||
from langbot.pkg.utils import httpclient
|
||||
|
||||
|
||||
def post_json(base_url, token, data=None):
|
||||
@@ -63,16 +63,16 @@ async def async_request(
|
||||
"""
|
||||
headers = {'Content-Type': 'application/json'}
|
||||
url = f'{base_url}?key={token_key}'
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.request(
|
||||
method=method, url=url, params=params, headers=headers, data=data, json=json
|
||||
) as response:
|
||||
response.raise_for_status() # 如果状态码不是200，抛出异常
|
||||
result = await response.json()
|
||||
# print(result)
|
||||
return result
|
||||
# if result.get('Code') == 200:
|
||||
#
|
||||
# return await result
|
||||
# else:
|
||||
# raise RuntimeError("请求失败",response.text)
|
||||
session = httpclient.get_session()
|
||||
async with session.request(
|
||||
method=method, url=url, params=params, headers=headers, data=data, json=json
|
||||
) as response:
|
||||
response.raise_for_status() # 如果状态码不是200，抛出异常
|
||||
result = await response.json()
|
||||
# print(result)
|
||||
return result
|
||||
# if result.get('Code') == 200:
|
||||
#
|
||||
# return await result
|
||||
# else:
|
||||
# raise RuntimeError("请求失败",response.text)
|
||||
|
||||
@@ -52,6 +52,7 @@ class MonitoringRouterGroup(group.RouterGroup):
|
||||
# Parse query parameters
|
||||
bot_ids = quart.request.args.getlist('botId')
|
||||
pipeline_ids = quart.request.args.getlist('pipelineId')
|
||||
session_ids = quart.request.args.getlist('sessionId')
|
||||
start_time_str = quart.request.args.get('startTime')
|
||||
end_time_str = quart.request.args.get('endTime')
|
||||
limit = int(quart.request.args.get('limit', 100))
|
||||
@@ -64,6 +65,7 @@ class MonitoringRouterGroup(group.RouterGroup):
|
||||
messages, total = await self.ap.monitoring_service.get_messages(
|
||||
bot_ids=bot_ids if bot_ids else None,
|
||||
pipeline_ids=pipeline_ids if pipeline_ids else None,
|
||||
session_ids=session_ids if session_ids else None,
|
||||
start_time=start_time,
|
||||
end_time=end_time,
|
||||
limit=limit,
|
||||
@@ -323,3 +325,164 @@ 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
|
||||
|
||||
@@ -14,6 +14,18 @@ from langbot_plugin.runtime.plugin.mgr import PluginInstallSource
|
||||
|
||||
@group.group_class('plugins', '/api/v1/plugins')
|
||||
class PluginsRouterGroup(group.RouterGroup):
|
||||
async def _check_extensions_limit(self) -> str | None:
|
||||
"""Check if extensions limit is reached. Returns error response if limit exceeded, None otherwise."""
|
||||
limitation = self.ap.instance_config.data.get('system', {}).get('limitation', {})
|
||||
max_extensions = limitation.get('max_extensions', -1)
|
||||
if max_extensions >= 0:
|
||||
plugins = await self.ap.plugin_connector.list_plugins()
|
||||
mcp_servers = await self.ap.mcp_service.get_mcp_servers()
|
||||
total_extensions = len(plugins) + len(mcp_servers)
|
||||
if total_extensions >= max_extensions:
|
||||
return self.http_status(400, -1, f'Maximum number of extensions ({max_extensions}) reached')
|
||||
return None
|
||||
|
||||
async def initialize(self) -> None:
|
||||
@self.route('', methods=['GET'], auth_type=group.AuthType.USER_TOKEN_OR_API_KEY)
|
||||
async def _() -> str:
|
||||
@@ -239,6 +251,10 @@ class PluginsRouterGroup(group.RouterGroup):
|
||||
@self.route('/install/github', methods=['POST'], auth_type=group.AuthType.USER_TOKEN_OR_API_KEY)
|
||||
async def _() -> str:
|
||||
"""Install plugin from GitHub release asset"""
|
||||
limit_error = await self._check_extensions_limit()
|
||||
if limit_error is not None:
|
||||
return limit_error
|
||||
|
||||
data = await quart.request.json
|
||||
asset_url = data.get('asset_url', '')
|
||||
owner = data.get('owner', '')
|
||||
@@ -273,6 +289,10 @@ class PluginsRouterGroup(group.RouterGroup):
|
||||
auth_type=group.AuthType.USER_TOKEN_OR_API_KEY,
|
||||
)
|
||||
async def _() -> str:
|
||||
limit_error = await self._check_extensions_limit()
|
||||
if limit_error is not None:
|
||||
return limit_error
|
||||
|
||||
data = await quart.request.json
|
||||
|
||||
ctx = taskmgr.TaskContext.new()
|
||||
@@ -288,6 +308,10 @@ class PluginsRouterGroup(group.RouterGroup):
|
||||
|
||||
@self.route('/install/local', methods=['POST'], auth_type=group.AuthType.USER_TOKEN_OR_API_KEY)
|
||||
async def _() -> str:
|
||||
limit_error = await self._check_extensions_limit()
|
||||
if limit_error is not None:
|
||||
return limit_error
|
||||
|
||||
file = (await quart.request.files).get('file')
|
||||
if file is None:
|
||||
return self.http_status(400, -1, 'file is required')
|
||||
|
||||
47
src/langbot/pkg/api/http/controller/groups/survey.py
Normal file
47
src/langbot/pkg/api/http/controller/groups/survey.py
Normal file
@@ -0,0 +1,47 @@
|
||||
import quart
|
||||
|
||||
from .. import group
|
||||
|
||||
|
||||
@group.group_class('survey', '/api/v1/survey')
|
||||
class SurveyRouterGroup(group.RouterGroup):
|
||||
async def initialize(self) -> None:
|
||||
@self.route('/pending', methods=['GET'], auth_type=group.AuthType.USER_TOKEN)
|
||||
async def _get_pending() -> str:
|
||||
"""Get pending survey for the frontend to display."""
|
||||
survey = self.ap.survey.get_pending_survey() if self.ap.survey else None
|
||||
return self.success(data={'survey': survey})
|
||||
|
||||
@self.route('/respond', methods=['POST'], auth_type=group.AuthType.USER_TOKEN)
|
||||
async def _respond() -> str:
|
||||
"""Submit survey response."""
|
||||
json_data = await quart.request.json
|
||||
survey_id = json_data.get('survey_id')
|
||||
answers = json_data.get('answers', {})
|
||||
completed = json_data.get('completed', True)
|
||||
|
||||
if not survey_id:
|
||||
return self.fail(1, 'survey_id required')
|
||||
|
||||
if self.ap.survey:
|
||||
ok = await self.ap.survey.submit_response(survey_id, answers, completed)
|
||||
if ok:
|
||||
return self.success()
|
||||
return self.fail(2, 'Failed to submit response')
|
||||
return self.fail(3, 'Survey not available')
|
||||
|
||||
@self.route('/dismiss', methods=['POST'], auth_type=group.AuthType.USER_TOKEN)
|
||||
async def _dismiss() -> str:
|
||||
"""Dismiss survey."""
|
||||
json_data = await quart.request.json
|
||||
survey_id = json_data.get('survey_id')
|
||||
|
||||
if not survey_id:
|
||||
return self.fail(1, 'survey_id required')
|
||||
|
||||
if self.ap.survey:
|
||||
ok = await self.ap.survey.dismiss_survey(survey_id)
|
||||
if ok:
|
||||
return self.success()
|
||||
return self.fail(2, 'Failed to dismiss')
|
||||
return self.fail(3, 'Survey not available')
|
||||
@@ -13,6 +13,7 @@ class SystemRouterGroup(group.RouterGroup):
|
||||
data={
|
||||
'version': constants.semantic_version,
|
||||
'debug': constants.debug_mode,
|
||||
'edition': constants.edition,
|
||||
'enable_marketplace': self.ap.instance_config.data.get('plugin', {}).get(
|
||||
'enable_marketplace', True
|
||||
),
|
||||
@@ -25,6 +26,7 @@ class SystemRouterGroup(group.RouterGroup):
|
||||
'disable_models_service': self.ap.instance_config.data.get('space', {}).get(
|
||||
'disable_models_service', False
|
||||
),
|
||||
'limitation': self.ap.instance_config.data.get('system', {}).get('limitation', {}),
|
||||
}
|
||||
)
|
||||
|
||||
|
||||
@@ -83,6 +83,14 @@ class BotService:
|
||||
|
||||
async def create_bot(self, bot_data: dict) -> str:
|
||||
"""Create bot"""
|
||||
# Check limitation
|
||||
limitation = self.ap.instance_config.data.get('system', {}).get('limitation', {})
|
||||
max_bots = limitation.get('max_bots', -1)
|
||||
if max_bots >= 0:
|
||||
existing_bots = await self.get_bots()
|
||||
if len(existing_bots) >= max_bots:
|
||||
raise ValueError(f'Maximum number of bots ({max_bots}) reached')
|
||||
|
||||
# TODO: 检查配置信息格式
|
||||
bot_data['uuid'] = str(uuid.uuid4())
|
||||
|
||||
|
||||
@@ -38,6 +38,16 @@ class MCPService:
|
||||
return serialized_servers
|
||||
|
||||
async def create_mcp_server(self, server_data: dict) -> str:
|
||||
# Check limitation (extensions = MCP servers + plugins)
|
||||
limitation = self.ap.instance_config.data.get('system', {}).get('limitation', {})
|
||||
max_extensions = limitation.get('max_extensions', -1)
|
||||
if max_extensions >= 0:
|
||||
existing_mcp_servers = await self.get_mcp_servers()
|
||||
plugins = await self.ap.plugin_connector.list_plugins()
|
||||
total_extensions = len(existing_mcp_servers) + len(plugins)
|
||||
if total_extensions >= max_extensions:
|
||||
raise ValueError(f'Maximum number of extensions ({max_extensions}) reached')
|
||||
|
||||
server_data['uuid'] = str(uuid.uuid4())
|
||||
await self.ap.persistence_mgr.execute_async(sqlalchemy.insert(persistence_mcp.MCPServer).values(server_data))
|
||||
|
||||
|
||||
@@ -64,7 +64,9 @@ class LLMModelsService:
|
||||
models = result.all()
|
||||
return [self.ap.persistence_mgr.serialize_model(persistence_model.LLMModel, m) for m in models]
|
||||
|
||||
async def create_llm_model(self, model_data: dict, preserve_uuid: bool = False) -> str:
|
||||
async def create_llm_model(
|
||||
self, model_data: dict, preserve_uuid: bool = False, auto_set_to_default_pipeline: bool = True
|
||||
) -> str:
|
||||
"""Create a new LLM model"""
|
||||
if not preserve_uuid:
|
||||
model_data['uuid'] = str(uuid.uuid4())
|
||||
@@ -95,18 +97,19 @@ class LLMModelsService:
|
||||
)
|
||||
self.ap.model_mgr.llm_models.append(runtime_llm_model)
|
||||
|
||||
# set the default pipeline model to this model
|
||||
result = await self.ap.persistence_mgr.execute_async(
|
||||
sqlalchemy.select(persistence_pipeline.LegacyPipeline).where(
|
||||
persistence_pipeline.LegacyPipeline.is_default == True
|
||||
if auto_set_to_default_pipeline:
|
||||
# set the default pipeline model to this model
|
||||
result = await self.ap.persistence_mgr.execute_async(
|
||||
sqlalchemy.select(persistence_pipeline.LegacyPipeline).where(
|
||||
persistence_pipeline.LegacyPipeline.is_default == True
|
||||
)
|
||||
)
|
||||
)
|
||||
pipeline = result.first()
|
||||
if pipeline is not None and pipeline.config['ai']['local-agent']['model'] == '':
|
||||
pipeline_config = pipeline.config
|
||||
pipeline_config['ai']['local-agent']['model'] = model_data['uuid']
|
||||
pipeline_data = {'config': pipeline_config}
|
||||
await self.ap.pipeline_service.update_pipeline(pipeline.uuid, pipeline_data)
|
||||
pipeline = result.first()
|
||||
if pipeline is not None and pipeline.config['ai']['local-agent']['model'] == '':
|
||||
pipeline_config = pipeline.config
|
||||
pipeline_config['ai']['local-agent']['model'] = model_data['uuid']
|
||||
pipeline_data = {'config': pipeline_config}
|
||||
await self.ap.pipeline_service.update_pipeline(pipeline.uuid, pipeline_data)
|
||||
|
||||
return model_data['uuid']
|
||||
|
||||
|
||||
@@ -32,6 +32,7 @@ class MonitoringService:
|
||||
user_id: str | None = None,
|
||||
runner_name: str | None = None,
|
||||
variables: str | None = None,
|
||||
role: str = 'user',
|
||||
) -> str:
|
||||
"""Record a message"""
|
||||
message_id = str(uuid.uuid4())
|
||||
@@ -50,6 +51,7 @@ class MonitoringService:
|
||||
'user_id': user_id,
|
||||
'runner_name': runner_name,
|
||||
'variables': variables,
|
||||
'role': role,
|
||||
}
|
||||
|
||||
await self.ap.persistence_mgr.execute_async(
|
||||
@@ -355,6 +357,7 @@ class MonitoringService:
|
||||
self,
|
||||
bot_ids: list[str] | None = None,
|
||||
pipeline_ids: list[str] | None = None,
|
||||
session_ids: list[str] | None = None,
|
||||
start_time: datetime.datetime | None = None,
|
||||
end_time: datetime.datetime | None = None,
|
||||
limit: int = 100,
|
||||
@@ -367,6 +370,8 @@ class MonitoringService:
|
||||
conditions.append(persistence_monitoring.MonitoringMessage.bot_id.in_(bot_ids))
|
||||
if pipeline_ids:
|
||||
conditions.append(persistence_monitoring.MonitoringMessage.pipeline_id.in_(pipeline_ids))
|
||||
if session_ids:
|
||||
conditions.append(persistence_monitoring.MonitoringMessage.session_id.in_(session_ids))
|
||||
if start_time:
|
||||
conditions.append(persistence_monitoring.MonitoringMessage.timestamp >= start_time)
|
||||
if end_time:
|
||||
@@ -794,3 +799,332 @@ 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
|
||||
]
|
||||
|
||||
@@ -76,6 +76,14 @@ class PipelineService:
|
||||
async def create_pipeline(self, pipeline_data: dict, default: bool = False) -> str:
|
||||
from ....utils import paths as path_utils
|
||||
|
||||
# Check limitation
|
||||
limitation = self.ap.instance_config.data.get('system', {}).get('limitation', {})
|
||||
max_pipelines = limitation.get('max_pipelines', -1)
|
||||
if max_pipelines >= 0:
|
||||
existing_pipelines = await self.get_pipelines()
|
||||
if len(existing_pipelines) >= max_pipelines:
|
||||
raise ValueError(f'Maximum number of pipelines ({max_pipelines}) reached')
|
||||
|
||||
pipeline_data['uuid'] = str(uuid.uuid4())
|
||||
pipeline_data['for_version'] = self.ap.ver_mgr.get_current_version()
|
||||
pipeline_data['stages'] = default_stage_order.copy()
|
||||
@@ -153,6 +161,14 @@ class PipelineService:
|
||||
|
||||
async def copy_pipeline(self, pipeline_uuid: str) -> str:
|
||||
"""Copy a pipeline with all its configurations"""
|
||||
# Check limitation
|
||||
limitation = self.ap.instance_config.data.get('system', {}).get('limitation', {})
|
||||
max_pipelines = limitation.get('max_pipelines', -1)
|
||||
if max_pipelines >= 0:
|
||||
existing_pipelines = await self.get_pipelines()
|
||||
if len(existing_pipelines) >= max_pipelines:
|
||||
raise ValueError(f'Maximum number of pipelines ({max_pipelines}) reached')
|
||||
|
||||
# Get the original pipeline
|
||||
result = await self.ap.persistence_mgr.execute_async(
|
||||
sqlalchemy.select(persistence_pipeline.LegacyPipeline).where(
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import aiohttp
|
||||
from langbot.pkg.utils import httpclient
|
||||
import typing
|
||||
import datetime
|
||||
import time
|
||||
@@ -99,49 +99,49 @@ class SpaceService:
|
||||
space_config = self._get_space_config()
|
||||
space_url = space_config['url']
|
||||
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.post(
|
||||
f'{space_url}/api/v1/accounts/oauth/token',
|
||||
json={'code': code, 'instance_id': constants.instance_id},
|
||||
) as response:
|
||||
if response.status != 200:
|
||||
raise ValueError(f'Failed to exchange OAuth code: {await response.text()}')
|
||||
data = await response.json()
|
||||
if data.get('code') != 0:
|
||||
raise ValueError(f'Failed to exchange OAuth code: {data.get("msg")}')
|
||||
return data.get('data', {})
|
||||
session = httpclient.get_session()
|
||||
async with session.post(
|
||||
f'{space_url}/api/v1/accounts/oauth/token',
|
||||
json={'code': code, 'instance_id': constants.instance_id},
|
||||
) as response:
|
||||
if response.status != 200:
|
||||
raise ValueError(f'Failed to exchange OAuth code: {await response.text()}')
|
||||
data = await response.json()
|
||||
if data.get('code') != 0:
|
||||
raise ValueError(f'Failed to exchange OAuth code: {data.get("msg")}')
|
||||
return data.get('data', {})
|
||||
|
||||
async def refresh_token(self, refresh_token: str) -> typing.Dict:
|
||||
"""Refresh Space access token"""
|
||||
space_config = self._get_space_config()
|
||||
space_url = space_config['url']
|
||||
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.post(
|
||||
f'{space_url}/api/v1/accounts/token/refresh', json={'refresh_token': refresh_token}
|
||||
) as response:
|
||||
if response.status != 200:
|
||||
raise ValueError(f'Failed to refresh token: {await response.text()}')
|
||||
data = await response.json()
|
||||
if data.get('code') != 0:
|
||||
raise ValueError(f'Failed to refresh token: {data.get("msg")}')
|
||||
return data.get('data', {})
|
||||
session = httpclient.get_session()
|
||||
async with session.post(
|
||||
f'{space_url}/api/v1/accounts/token/refresh', json={'refresh_token': refresh_token}
|
||||
) as response:
|
||||
if response.status != 200:
|
||||
raise ValueError(f'Failed to refresh token: {await response.text()}')
|
||||
data = await response.json()
|
||||
if data.get('code') != 0:
|
||||
raise ValueError(f'Failed to refresh token: {data.get("msg")}')
|
||||
return data.get('data', {})
|
||||
|
||||
async def get_user_info_raw(self, access_token: str) -> typing.Dict:
|
||||
"""Get user info from Space using access token (no validation)"""
|
||||
space_config = self._get_space_config()
|
||||
space_url = space_config['url']
|
||||
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.get(
|
||||
f'{space_url}/api/v1/accounts/me', headers={'Authorization': f'Bearer {access_token}'}
|
||||
) as response:
|
||||
if response.status != 200:
|
||||
raise ValueError(f'Failed to get user info: {await response.text()}')
|
||||
data = await response.json()
|
||||
if data.get('code') != 0:
|
||||
raise ValueError(f'Failed to get user info: {data.get("msg")}')
|
||||
return data.get('data', {})
|
||||
session = httpclient.get_session()
|
||||
async with session.get(
|
||||
f'{space_url}/api/v1/accounts/me', headers={'Authorization': f'Bearer {access_token}'}
|
||||
) as response:
|
||||
if response.status != 200:
|
||||
raise ValueError(f'Failed to get user info: {await response.text()}')
|
||||
data = await response.json()
|
||||
if data.get('code') != 0:
|
||||
raise ValueError(f'Failed to get user info: {data.get("msg")}')
|
||||
return data.get('data', {})
|
||||
|
||||
# === API calls with token validation ===
|
||||
|
||||
@@ -178,12 +178,12 @@ class SpaceService:
|
||||
space_config = self._get_space_config()
|
||||
space_url = space_config['url']
|
||||
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.get(f'{space_url}/api/v1/models') as response:
|
||||
if response.status != 200:
|
||||
raise ValueError(f'Failed to get models: {await response.text()}')
|
||||
data = await response.json()
|
||||
if data.get('code') != 0:
|
||||
raise ValueError(f'Failed to get models: {data.get("msg")}')
|
||||
models_data = data.get('data', {}).get('models', [])
|
||||
return [SpaceModel.model_validate(model_dict) for model_dict in models_data]
|
||||
session = httpclient.get_session()
|
||||
async with session.get(f'{space_url}/api/v1/models') as response:
|
||||
if response.status != 200:
|
||||
raise ValueError(f'Failed to get models: {await response.text()}')
|
||||
data = await response.json()
|
||||
if data.get('code') != 0:
|
||||
raise ValueError(f'Failed to get models: {data.get("msg")}')
|
||||
models_data = data.get('data', {}).get('models', [])
|
||||
return [SpaceModel.model_validate(model_dict) for model_dict in models_data]
|
||||
|
||||
@@ -15,6 +15,7 @@ from ..command import cmdmgr
|
||||
from ..plugin import connector as plugin_connector
|
||||
from ..pipeline import pool
|
||||
from ..pipeline import controller, pipelinemgr
|
||||
from ..pipeline import aggregator as message_aggregator
|
||||
from ..utils import version as version_mgr, proxy as proxy_mgr
|
||||
from ..persistence import mgr as persistencemgr
|
||||
from ..api.http.controller import main as http_controller
|
||||
@@ -38,6 +39,7 @@ from . import entities as core_entities
|
||||
from ..rag.knowledge import kbmgr as rag_mgr
|
||||
from ..vector import mgr as vectordb_mgr
|
||||
from ..telemetry import telemetry as telemetry_module
|
||||
from ..survey import manager as survey_module
|
||||
|
||||
|
||||
class Application:
|
||||
@@ -96,6 +98,8 @@ class Application:
|
||||
|
||||
query_pool: pool.QueryPool = None
|
||||
|
||||
msg_aggregator: message_aggregator.MessageAggregator = None
|
||||
|
||||
ctrl: controller.Controller = None
|
||||
|
||||
pipeline_mgr: pipelinemgr.PipelineManager = None
|
||||
@@ -144,6 +148,8 @@ class Application:
|
||||
|
||||
telemetry: telemetry_module.TelemetryManager = None
|
||||
|
||||
survey: survey_module.SurveyManager = None
|
||||
|
||||
monitoring_service: monitoring_service.MonitoringService = None
|
||||
|
||||
def __init__(self):
|
||||
|
||||
@@ -1,3 +1,4 @@
|
||||
import importlib.util
|
||||
import pip
|
||||
import os
|
||||
from ...utils import pkgmgr
|
||||
@@ -49,9 +50,10 @@ async def check_deps() -> list[str]:
|
||||
|
||||
missing_deps = []
|
||||
for dep in required_deps:
|
||||
try:
|
||||
__import__(dep)
|
||||
except ImportError:
|
||||
# Use find_spec instead of __import__ to avoid actually loading
|
||||
# all modules into memory. find_spec only checks if the module
|
||||
# can be found, without executing module-level code.
|
||||
if importlib.util.find_spec(dep) is None:
|
||||
missing_deps.append(dep)
|
||||
return missing_deps
|
||||
|
||||
|
||||
@@ -0,0 +1,17 @@
|
||||
from __future__ import annotations
|
||||
|
||||
from .. import migration
|
||||
|
||||
|
||||
@migration.migration_class('dingtalk_card_auto_layout', 41)
|
||||
class DingTalkCardAutoLayoutMigration(migration.Migration):
|
||||
"""迁移"""
|
||||
|
||||
async def need_migrate(self) -> bool:
|
||||
"""判断当前环境是否需要运行此迁移"""
|
||||
return True
|
||||
|
||||
async def run(self):
|
||||
"""执行迁移"""
|
||||
self.ap.platform_cfg.data['platform-adapters']['app']['dingtalk']['card_auto_layout'] = False
|
||||
await self.ap.platform_cfg.dump_config()
|
||||
@@ -5,6 +5,7 @@ import asyncio
|
||||
from .. import stage, app
|
||||
from ...utils import version, proxy
|
||||
from ...pipeline import pool, controller, pipelinemgr
|
||||
from ...pipeline import aggregator as message_aggregator
|
||||
from ...plugin import connector as plugin_connector
|
||||
from ...command import cmdmgr
|
||||
from ...provider.session import sessionmgr as llm_session_mgr
|
||||
@@ -33,6 +34,7 @@ from ...utils import logcache
|
||||
from ...vector import mgr as vectordb_mgr
|
||||
from .. import taskmgr
|
||||
from ...telemetry import telemetry as telemetry_module
|
||||
from ...survey import manager as survey_module
|
||||
|
||||
|
||||
@stage.stage_class('BuildAppStage')
|
||||
@@ -109,6 +111,11 @@ class BuildAppStage(stage.BootingStage):
|
||||
await telemetry_inst.initialize()
|
||||
ap.telemetry = telemetry_inst
|
||||
|
||||
# Survey manager
|
||||
survey_inst = survey_module.SurveyManager(ap)
|
||||
await survey_inst.initialize()
|
||||
ap.survey = survey_inst
|
||||
|
||||
cmd_mgr_inst = cmdmgr.CommandManager(ap)
|
||||
await cmd_mgr_inst.initialize()
|
||||
ap.cmd_mgr = cmd_mgr_inst
|
||||
@@ -137,6 +144,10 @@ class BuildAppStage(stage.BootingStage):
|
||||
await pipeline_mgr.initialize()
|
||||
ap.pipeline_mgr = pipeline_mgr
|
||||
|
||||
# Initialize message aggregator (after pipeline_mgr, as it needs pipeline config)
|
||||
msg_aggregator_inst = message_aggregator.MessageAggregator(ap)
|
||||
ap.msg_aggregator = msg_aggregator_inst
|
||||
|
||||
rag_mgr_inst = rag_mgr.RAGManager(ap)
|
||||
await rag_mgr_inst.initialize()
|
||||
ap.rag_mgr = rag_mgr_inst
|
||||
|
||||
@@ -156,8 +156,10 @@ class LoadConfigStage(stage.BootingStage):
|
||||
)
|
||||
|
||||
constants.instance_id = ap.instance_id.data['instance_id']
|
||||
constants.edition = ap.instance_config.data.get('system', {}).get('edition', 'community')
|
||||
|
||||
print(f'LangBot instance id: {constants.instance_id}')
|
||||
print(f'LangBot edition: {constants.edition}')
|
||||
|
||||
await ap.instance_id.dump_config()
|
||||
|
||||
|
||||
@@ -22,6 +22,7 @@ class MonitoringMessage(Base):
|
||||
user_id = sqlalchemy.Column(sqlalchemy.String(255), nullable=True)
|
||||
runner_name = sqlalchemy.Column(sqlalchemy.String(255), nullable=True) # Runner name for this query
|
||||
variables = sqlalchemy.Column(sqlalchemy.Text, nullable=True) # Query variables as JSON string
|
||||
role = sqlalchemy.Column(sqlalchemy.String(50), nullable=True, default='user') # user, assistant
|
||||
|
||||
|
||||
class MonitoringLLMCall(Base):
|
||||
|
||||
@@ -0,0 +1,24 @@
|
||||
import sqlalchemy
|
||||
from .. import migration
|
||||
|
||||
|
||||
@migration.migration_class(19)
|
||||
class DBMigrateMonitoringMessageRole(migration.DBMigration):
|
||||
"""Add role column to monitoring_messages table"""
|
||||
|
||||
async def upgrade(self):
|
||||
"""Upgrade"""
|
||||
try:
|
||||
sql_text = sqlalchemy.text("ALTER TABLE monitoring_messages ADD COLUMN role VARCHAR(50) DEFAULT 'user'")
|
||||
await self.ap.persistence_mgr.execute_async(sql_text)
|
||||
except Exception:
|
||||
# Column may already exist
|
||||
pass
|
||||
|
||||
async def downgrade(self):
|
||||
"""Downgrade"""
|
||||
try:
|
||||
sql_text = sqlalchemy.text('ALTER TABLE monitoring_messages DROP COLUMN role')
|
||||
await self.ap.persistence_mgr.execute_async(sql_text)
|
||||
except Exception:
|
||||
pass
|
||||
289
src/langbot/pkg/pipeline/aggregator.py
Normal file
289
src/langbot/pkg/pipeline/aggregator.py
Normal file
@@ -0,0 +1,289 @@
|
||||
"""Message Aggregator Module
|
||||
|
||||
This module provides message aggregation/debounce functionality.
|
||||
When users send multiple messages consecutively, the aggregator will wait
|
||||
for a configurable delay period and merge them into a single message
|
||||
before processing.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import asyncio
|
||||
import time
|
||||
import typing
|
||||
from dataclasses import dataclass, field
|
||||
|
||||
import langbot_plugin.api.entities.builtin.platform.message as platform_message
|
||||
import langbot_plugin.api.entities.builtin.platform.events as platform_events
|
||||
import langbot_plugin.api.entities.builtin.provider.session as provider_session
|
||||
import langbot_plugin.api.definition.abstract.platform.adapter as abstract_platform_adapter
|
||||
|
||||
if typing.TYPE_CHECKING:
|
||||
from ..core import app
|
||||
|
||||
# Maximum number of messages to buffer before forcing a flush
|
||||
MAX_BUFFER_MESSAGES = 10
|
||||
|
||||
|
||||
@dataclass
|
||||
class PendingMessage:
|
||||
"""A pending message waiting to be aggregated"""
|
||||
|
||||
bot_uuid: str
|
||||
launcher_type: provider_session.LauncherTypes
|
||||
launcher_id: typing.Union[int, str]
|
||||
sender_id: typing.Union[int, str]
|
||||
message_event: platform_events.MessageEvent
|
||||
message_chain: platform_message.MessageChain
|
||||
adapter: abstract_platform_adapter.AbstractMessagePlatformAdapter
|
||||
pipeline_uuid: typing.Optional[str]
|
||||
timestamp: float = field(default_factory=time.time)
|
||||
|
||||
|
||||
@dataclass
|
||||
class SessionBuffer:
|
||||
"""Buffer for a single session's pending messages"""
|
||||
|
||||
session_id: str
|
||||
messages: list[PendingMessage] = field(default_factory=list)
|
||||
timer_task: typing.Optional[asyncio.Task] = None
|
||||
last_message_time: float = field(default_factory=time.time)
|
||||
|
||||
|
||||
class MessageAggregator:
|
||||
"""Message aggregator that buffers and merges consecutive messages
|
||||
|
||||
This class implements a debounce mechanism for incoming messages.
|
||||
When a message arrives, it starts a timer. If more messages arrive
|
||||
before the timer expires, they are buffered. When the timer expires,
|
||||
all buffered messages are merged and sent to the query pool.
|
||||
"""
|
||||
|
||||
ap: app.Application
|
||||
|
||||
buffers: dict[str, SessionBuffer]
|
||||
"""Session ID -> SessionBuffer mapping"""
|
||||
|
||||
lock: asyncio.Lock
|
||||
"""Lock for thread-safe buffer operations"""
|
||||
|
||||
def __init__(self, ap: app.Application):
|
||||
self.ap = ap
|
||||
self.buffers = {}
|
||||
self.lock = asyncio.Lock()
|
||||
|
||||
def _get_session_id(
|
||||
self,
|
||||
bot_uuid: str,
|
||||
launcher_type: provider_session.LauncherTypes,
|
||||
launcher_id: typing.Union[int, str],
|
||||
) -> str:
|
||||
"""Generate a unique session ID"""
|
||||
return f'{bot_uuid}:{launcher_type.value}:{launcher_id}'
|
||||
|
||||
async def _get_aggregation_config(self, pipeline_uuid: typing.Optional[str]) -> tuple[bool, float]:
|
||||
"""Get aggregation configuration for a pipeline
|
||||
|
||||
Returns:
|
||||
tuple: (enabled, delay_seconds)
|
||||
"""
|
||||
default_enabled = False
|
||||
default_delay = 1.5
|
||||
|
||||
if pipeline_uuid is None:
|
||||
return default_enabled, default_delay
|
||||
|
||||
# Get pipeline from pipeline manager
|
||||
pipeline = await self.ap.pipeline_mgr.get_pipeline_by_uuid(pipeline_uuid)
|
||||
if pipeline is None:
|
||||
return default_enabled, default_delay
|
||||
|
||||
config = pipeline.pipeline_entity.config or {}
|
||||
trigger_config = config.get('trigger', {})
|
||||
aggregation_config = trigger_config.get('message-aggregation', {})
|
||||
|
||||
enabled = aggregation_config.get('enabled', default_enabled)
|
||||
|
||||
delay_raw = aggregation_config.get('delay', default_delay)
|
||||
try:
|
||||
delay = float(delay_raw)
|
||||
except (TypeError, ValueError):
|
||||
delay = default_delay
|
||||
|
||||
# Clamp delay to valid range
|
||||
delay = max(1.0, min(10.0, delay))
|
||||
|
||||
return enabled, delay
|
||||
|
||||
async def add_message(
|
||||
self,
|
||||
bot_uuid: str,
|
||||
launcher_type: provider_session.LauncherTypes,
|
||||
launcher_id: typing.Union[int, str],
|
||||
sender_id: typing.Union[int, str],
|
||||
message_event: platform_events.MessageEvent,
|
||||
message_chain: platform_message.MessageChain,
|
||||
adapter: abstract_platform_adapter.AbstractMessagePlatformAdapter,
|
||||
pipeline_uuid: typing.Optional[str] = None,
|
||||
) -> None:
|
||||
"""Add a message to the aggregation buffer
|
||||
|
||||
If aggregation is disabled for the pipeline, the message is sent
|
||||
directly to the query pool. Otherwise, it's buffered and will be
|
||||
merged with other messages from the same session.
|
||||
"""
|
||||
enabled, delay = await self._get_aggregation_config(pipeline_uuid)
|
||||
|
||||
if not enabled:
|
||||
# Aggregation disabled, send directly to query pool
|
||||
await self.ap.query_pool.add_query(
|
||||
bot_uuid=bot_uuid,
|
||||
launcher_type=launcher_type,
|
||||
launcher_id=launcher_id,
|
||||
sender_id=sender_id,
|
||||
message_event=message_event,
|
||||
message_chain=message_chain,
|
||||
adapter=adapter,
|
||||
pipeline_uuid=pipeline_uuid,
|
||||
)
|
||||
return
|
||||
|
||||
session_id = self._get_session_id(bot_uuid, launcher_type, launcher_id)
|
||||
|
||||
pending_msg = PendingMessage(
|
||||
bot_uuid=bot_uuid,
|
||||
launcher_type=launcher_type,
|
||||
launcher_id=launcher_id,
|
||||
sender_id=sender_id,
|
||||
message_event=message_event,
|
||||
message_chain=message_chain,
|
||||
adapter=adapter,
|
||||
pipeline_uuid=pipeline_uuid,
|
||||
)
|
||||
|
||||
force_flush = False
|
||||
async with self.lock:
|
||||
if session_id in self.buffers:
|
||||
buffer = self.buffers[session_id]
|
||||
# Cancel existing timer (just cancel, don't await inside lock)
|
||||
if buffer.timer_task and not buffer.timer_task.done():
|
||||
buffer.timer_task.cancel()
|
||||
buffer.messages.append(pending_msg)
|
||||
else:
|
||||
buffer = SessionBuffer(
|
||||
session_id=session_id,
|
||||
messages=[pending_msg],
|
||||
)
|
||||
self.buffers[session_id] = buffer
|
||||
|
||||
buffer.last_message_time = time.time()
|
||||
|
||||
# Check if buffer reached max capacity
|
||||
if len(buffer.messages) >= MAX_BUFFER_MESSAGES:
|
||||
force_flush = True
|
||||
else:
|
||||
# Start new timer
|
||||
buffer.timer_task = asyncio.create_task(self._delayed_flush(session_id, delay))
|
||||
|
||||
if force_flush:
|
||||
await self._flush_buffer(session_id)
|
||||
|
||||
async def _delayed_flush(self, session_id: str, delay: float) -> None:
|
||||
"""Wait for delay then flush the buffer"""
|
||||
try:
|
||||
await asyncio.sleep(delay)
|
||||
await self._flush_buffer(session_id)
|
||||
except asyncio.CancelledError:
|
||||
# Timer was cancelled, new message arrived
|
||||
pass
|
||||
|
||||
async def _flush_buffer(self, session_id: str) -> None:
|
||||
"""Flush the buffer for a session, merging all messages"""
|
||||
async with self.lock:
|
||||
buffer = self.buffers.pop(session_id, None)
|
||||
|
||||
if buffer is None or not buffer.messages:
|
||||
return
|
||||
|
||||
if len(buffer.messages) == 1:
|
||||
# Only one message, no need to merge
|
||||
msg = buffer.messages[0]
|
||||
await self.ap.query_pool.add_query(
|
||||
bot_uuid=msg.bot_uuid,
|
||||
launcher_type=msg.launcher_type,
|
||||
launcher_id=msg.launcher_id,
|
||||
sender_id=msg.sender_id,
|
||||
message_event=msg.message_event,
|
||||
message_chain=msg.message_chain,
|
||||
adapter=msg.adapter,
|
||||
pipeline_uuid=msg.pipeline_uuid,
|
||||
)
|
||||
return
|
||||
|
||||
# Merge multiple messages
|
||||
merged_msg = self._merge_messages(buffer.messages)
|
||||
await self.ap.query_pool.add_query(
|
||||
bot_uuid=merged_msg.bot_uuid,
|
||||
launcher_type=merged_msg.launcher_type,
|
||||
launcher_id=merged_msg.launcher_id,
|
||||
sender_id=merged_msg.sender_id,
|
||||
message_event=merged_msg.message_event,
|
||||
message_chain=merged_msg.message_chain,
|
||||
adapter=merged_msg.adapter,
|
||||
pipeline_uuid=merged_msg.pipeline_uuid,
|
||||
)
|
||||
|
||||
def _merge_messages(self, messages: list[PendingMessage]) -> PendingMessage:
|
||||
"""Merge multiple messages into one
|
||||
|
||||
The merged message uses the first message as base and combines
|
||||
all message chains with newline separators.
|
||||
The original message_event is kept unmodified to preserve
|
||||
message metadata (message_id, etc.) for reply/quote.
|
||||
"""
|
||||
if len(messages) == 1:
|
||||
return messages[0]
|
||||
|
||||
base_msg = messages[0]
|
||||
|
||||
# Build merged message chain
|
||||
merged_chain = platform_message.MessageChain([])
|
||||
|
||||
for i, msg in enumerate(messages):
|
||||
if i > 0:
|
||||
# Add newline separator between messages
|
||||
merged_chain.append(platform_message.Plain(text='\n'))
|
||||
|
||||
# Copy all components from this message
|
||||
for component in msg.message_chain:
|
||||
merged_chain.append(component)
|
||||
|
||||
# Keep message_event unmodified (preserves original message_id and
|
||||
# metadata for reply/quote), only pass merged chain separately
|
||||
return PendingMessage(
|
||||
bot_uuid=base_msg.bot_uuid,
|
||||
launcher_type=base_msg.launcher_type,
|
||||
launcher_id=base_msg.launcher_id,
|
||||
sender_id=base_msg.sender_id,
|
||||
message_event=base_msg.message_event,
|
||||
message_chain=merged_chain,
|
||||
adapter=base_msg.adapter,
|
||||
pipeline_uuid=base_msg.pipeline_uuid,
|
||||
)
|
||||
|
||||
async def flush_all(self) -> None:
|
||||
"""Flush all pending buffers immediately
|
||||
|
||||
This is useful during shutdown to ensure no messages are lost.
|
||||
"""
|
||||
# Snapshot session IDs and cancel all timers under lock
|
||||
async with self.lock:
|
||||
session_ids = list(self.buffers.keys())
|
||||
for sid in session_ids:
|
||||
buffer = self.buffers.get(sid)
|
||||
if buffer and buffer.timer_task and not buffer.timer_task.done():
|
||||
buffer.timer_task.cancel()
|
||||
|
||||
# Flush each buffer outside the lock
|
||||
for session_id in session_ids:
|
||||
await self._flush_buffer(session_id)
|
||||
@@ -1,10 +1,9 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import aiohttp
|
||||
|
||||
from .. import entities
|
||||
from .. import filter as filter_model
|
||||
import langbot_plugin.api.entities.builtin.pipeline.query as pipeline_query
|
||||
from langbot.pkg.utils import httpclient
|
||||
|
||||
BAIDU_EXAMINE_URL = 'https://aip.baidubce.com/rest/2.0/solution/v1/text_censor/v2/user_defined?access_token={}'
|
||||
BAIDU_EXAMINE_TOKEN_URL = 'https://aip.baidubce.com/oauth/2.0/token'
|
||||
@@ -15,50 +14,50 @@ class BaiduCloudExamine(filter_model.ContentFilter):
|
||||
"""百度云内容审核"""
|
||||
|
||||
async def _get_token(self) -> str:
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.post(
|
||||
BAIDU_EXAMINE_TOKEN_URL,
|
||||
params={
|
||||
'grant_type': 'client_credentials',
|
||||
'client_id': self.ap.pipeline_cfg.data['baidu-cloud-examine']['api-key'],
|
||||
'client_secret': self.ap.pipeline_cfg.data['baidu-cloud-examine']['api-secret'],
|
||||
},
|
||||
) as resp:
|
||||
return (await resp.json())['access_token']
|
||||
session = httpclient.get_session()
|
||||
async with session.post(
|
||||
BAIDU_EXAMINE_TOKEN_URL,
|
||||
params={
|
||||
'grant_type': 'client_credentials',
|
||||
'client_id': self.ap.pipeline_cfg.data['baidu-cloud-examine']['api-key'],
|
||||
'client_secret': self.ap.pipeline_cfg.data['baidu-cloud-examine']['api-secret'],
|
||||
},
|
||||
) as resp:
|
||||
return (await resp.json())['access_token']
|
||||
|
||||
async def process(self, query: pipeline_query.Query, message: str) -> entities.FilterResult:
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.post(
|
||||
BAIDU_EXAMINE_URL.format(await self._get_token()),
|
||||
headers={
|
||||
'Content-Type': 'application/x-www-form-urlencoded',
|
||||
'Accept': 'application/json',
|
||||
},
|
||||
data=f'text={message}'.encode('utf-8'),
|
||||
) as resp:
|
||||
result = await resp.json()
|
||||
session = httpclient.get_session()
|
||||
async with session.post(
|
||||
BAIDU_EXAMINE_URL.format(await self._get_token()),
|
||||
headers={
|
||||
'Content-Type': 'application/x-www-form-urlencoded',
|
||||
'Accept': 'application/json',
|
||||
},
|
||||
data=f'text={message}'.encode('utf-8'),
|
||||
) as resp:
|
||||
result = await resp.json()
|
||||
|
||||
if 'error_code' in result:
|
||||
if 'error_code' in result:
|
||||
return entities.FilterResult(
|
||||
level=entities.ResultLevel.BLOCK,
|
||||
replacement=message,
|
||||
user_notice='',
|
||||
console_notice=f'百度云判定出错，错误信息：{result["error_msg"]}',
|
||||
)
|
||||
else:
|
||||
conclusion = result['conclusion']
|
||||
|
||||
if conclusion in ('合规'):
|
||||
return entities.FilterResult(
|
||||
level=entities.ResultLevel.PASS,
|
||||
replacement=message,
|
||||
user_notice='',
|
||||
console_notice=f'百度云判定结果：{conclusion}',
|
||||
)
|
||||
else:
|
||||
return entities.FilterResult(
|
||||
level=entities.ResultLevel.BLOCK,
|
||||
replacement=message,
|
||||
user_notice='',
|
||||
console_notice=f'百度云判定出错，错误信息：{result["error_msg"]}',
|
||||
user_notice='消息中存在不合适的内容, 请修改',
|
||||
console_notice=f'百度云判定结果：{conclusion}',
|
||||
)
|
||||
else:
|
||||
conclusion = result['conclusion']
|
||||
|
||||
if conclusion in ('合规'):
|
||||
return entities.FilterResult(
|
||||
level=entities.ResultLevel.PASS,
|
||||
replacement=message,
|
||||
user_notice='',
|
||||
console_notice=f'百度云判定结果：{conclusion}',
|
||||
)
|
||||
else:
|
||||
return entities.FilterResult(
|
||||
level=entities.ResultLevel.BLOCK,
|
||||
replacement=message,
|
||||
user_notice='消息中存在不合适的内容, 请修改',
|
||||
console_notice=f'百度云判定结果：{conclusion}',
|
||||
)
|
||||
|
||||
@@ -114,6 +114,60 @@ class MonitoringHelper:
|
||||
except Exception as e:
|
||||
ap.logger.error(f'Failed to record query success: {e}')
|
||||
|
||||
@staticmethod
|
||||
async def record_query_response(
|
||||
ap: app.Application,
|
||||
query: pipeline_query.Query,
|
||||
bot_id: str,
|
||||
bot_name: str,
|
||||
pipeline_id: str,
|
||||
pipeline_name: str,
|
||||
runner_name: str | None = None,
|
||||
):
|
||||
"""Record bot response message to monitoring"""
|
||||
try:
|
||||
session_id = f'{query.launcher_type}_{query.launcher_id}'
|
||||
|
||||
# Extract response content from resp_message_chain
|
||||
if hasattr(query, 'resp_message_chain') and query.resp_message_chain:
|
||||
# Serialize the last response message chain
|
||||
last_resp = query.resp_message_chain[-1]
|
||||
if hasattr(last_resp, 'model_dump'):
|
||||
message_content = json.dumps(last_resp.model_dump(), ensure_ascii=False)
|
||||
else:
|
||||
message_content = str(last_resp)
|
||||
elif hasattr(query, 'resp_messages') and query.resp_messages:
|
||||
last_resp = query.resp_messages[-1]
|
||||
if hasattr(last_resp, 'get_content_platform_message_chain'):
|
||||
chain = last_resp.get_content_platform_message_chain()
|
||||
if hasattr(chain, 'model_dump'):
|
||||
message_content = json.dumps(chain.model_dump(), ensure_ascii=False)
|
||||
else:
|
||||
message_content = str(chain)
|
||||
else:
|
||||
message_content = str(last_resp)
|
||||
else:
|
||||
return # No response to record
|
||||
|
||||
await ap.monitoring_service.record_message(
|
||||
bot_id=bot_id,
|
||||
bot_name=bot_name,
|
||||
pipeline_id=pipeline_id,
|
||||
pipeline_name=pipeline_name,
|
||||
message_content=message_content,
|
||||
session_id=session_id,
|
||||
status='success',
|
||||
level='info',
|
||||
platform=query.launcher_type.value
|
||||
if hasattr(query.launcher_type, 'value')
|
||||
else str(query.launcher_type),
|
||||
user_id=query.sender_id,
|
||||
runner_name=runner_name,
|
||||
role='assistant',
|
||||
)
|
||||
except Exception as e:
|
||||
ap.logger.error(f'Failed to record query response: {e}')
|
||||
|
||||
@staticmethod
|
||||
async def record_query_error(
|
||||
ap: app.Application,
|
||||
|
||||
@@ -339,6 +339,20 @@ class RuntimePipeline:
|
||||
except Exception as e:
|
||||
self.ap.logger.error(f'Failed to record query success: {e}')
|
||||
|
||||
# Record bot response message
|
||||
try:
|
||||
await monitoring_helper.MonitoringHelper.record_query_response(
|
||||
ap=self.ap,
|
||||
query=query,
|
||||
bot_id=query.bot_uuid or 'unknown',
|
||||
bot_name=bot_name,
|
||||
pipeline_id=self.pipeline_entity.uuid,
|
||||
pipeline_name=pipeline_name,
|
||||
runner_name=runner_name,
|
||||
)
|
||||
except Exception as e:
|
||||
self.ap.logger.error(f'Failed to record query response: {e}')
|
||||
|
||||
except Exception as e:
|
||||
inst_name = query.current_stage_name if query.current_stage_name else 'unknown'
|
||||
self.ap.logger.error(f'Error processing query {query.query_id} stage={inst_name} : {e}')
|
||||
@@ -369,8 +383,6 @@ class RuntimePipeline:
|
||||
class PipelineManager:
|
||||
"""流水线管理器"""
|
||||
|
||||
# ====== 4.0 ======
|
||||
|
||||
ap: app.Application
|
||||
|
||||
pipelines: list[RuntimePipeline]
|
||||
|
||||
@@ -200,6 +200,11 @@ class ChatMessageHandler(handler.MessageHandler):
|
||||
|
||||
# Send telemetry asynchronously and do not block pipeline via app's telemetry manager
|
||||
await self.ap.telemetry.start_send_task(payload)
|
||||
|
||||
# Trigger survey event on first successful non-WebSocket response
|
||||
if not locals().get('error_info') and adapter_name and 'WebSocket' not in adapter_name:
|
||||
if self.ap.survey:
|
||||
await self.ap.survey.trigger_event('first_bot_response_success')
|
||||
except Exception as ex:
|
||||
# Ensure telemetry issues do not affect normal flow
|
||||
self.ap.logger.warning(f'Failed to send telemetry: {ex}')
|
||||
|
||||
@@ -82,7 +82,7 @@ class RuntimeBot:
|
||||
if custom_launcher_id:
|
||||
launcher_id = custom_launcher_id
|
||||
|
||||
await self.ap.query_pool.add_query(
|
||||
await self.ap.msg_aggregator.add_message(
|
||||
bot_uuid=self.bot_entity.uuid,
|
||||
launcher_type=provider_session.LauncherTypes.PERSON,
|
||||
launcher_id=launcher_id,
|
||||
@@ -125,7 +125,7 @@ class RuntimeBot:
|
||||
if custom_launcher_id:
|
||||
launcher_id = custom_launcher_id
|
||||
|
||||
await self.ap.query_pool.add_query(
|
||||
await self.ap.msg_aggregator.add_message(
|
||||
bot_uuid=self.bot_entity.uuid,
|
||||
launcher_type=provider_session.LauncherTypes.GROUP,
|
||||
launcher_id=launcher_id,
|
||||
|
||||
@@ -375,6 +375,18 @@ class AiocqhttpAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter)
|
||||
self.bot = aiocqhttp.CQHttp()
|
||||
|
||||
async def send_message(self, target_type: str, target_id: str, message: platform_message.MessageChain):
|
||||
# Check if message contains a Forward component
|
||||
forward_msg = message.get_first(platform_message.Forward)
|
||||
if forward_msg:
|
||||
if target_type == 'group':
|
||||
# Send as merged forward message via OneBot API
|
||||
await self._send_forward_message(int(target_id), forward_msg)
|
||||
return
|
||||
else:
|
||||
await self.logger.warning(
|
||||
f'Forward message is only supported for group targets, got target_type={target_type}. Falling through to normal send.'
|
||||
)
|
||||
|
||||
aiocq_msg = (await AiocqhttpMessageConverter.yiri2target(message))[0]
|
||||
|
||||
if target_type == 'group':
|
||||
@@ -382,6 +394,90 @@ class AiocqhttpAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter)
|
||||
elif target_type == 'person':
|
||||
await self.bot.send_private_msg(user_id=int(target_id), message=aiocq_msg)
|
||||
|
||||
async def _send_forward_message(self, group_id: int, forward: platform_message.Forward):
|
||||
"""Send a merged forward message to a group using NapCat extended API."""
|
||||
messages = []
|
||||
|
||||
for node in forward.node_list:
|
||||
# Build content for each node
|
||||
content = []
|
||||
if node.message_chain:
|
||||
for component in node.message_chain:
|
||||
if isinstance(component, platform_message.Plain):
|
||||
if component.text:
|
||||
content.append({'type': 'text', 'data': {'text': component.text}})
|
||||
elif isinstance(component, platform_message.Image):
|
||||
img_data = {}
|
||||
if component.base64:
|
||||
b64 = component.base64
|
||||
if b64.startswith('data:'):
|
||||
b64 = b64.split(',', 1)[-1] if ',' in b64 else b64
|
||||
img_data['file'] = f'base64://{b64}'
|
||||
elif component.url:
|
||||
img_data['file'] = component.url
|
||||
elif component.path:
|
||||
img_data['file'] = str(component.path)
|
||||
|
||||
if img_data:
|
||||
content.append({'type': 'image', 'data': img_data})
|
||||
|
||||
if not content:
|
||||
continue
|
||||
|
||||
# Build node data - use user_id and nickname format for NapCat
|
||||
user_id = str(node.sender_id) if node.sender_id else str(self.bot_account_id or '10000')
|
||||
node_data = {
|
||||
'type': 'node',
|
||||
'data': {
|
||||
'user_id': user_id,
|
||||
'nickname': node.sender_name or '未知',
|
||||
'content': content,
|
||||
},
|
||||
}
|
||||
|
||||
messages.append(node_data)
|
||||
|
||||
if not messages:
|
||||
return
|
||||
|
||||
# Build the full message payload for NapCat's send_forward_msg API
|
||||
# This matches the format used by GiveMeSetuPlugin
|
||||
bot_id = str(self.bot_account_id) if self.bot_account_id else '10000'
|
||||
payload = {
|
||||
'group_id': group_id,
|
||||
'user_id': bot_id, # Required by NapCat for display
|
||||
'messages': messages,
|
||||
}
|
||||
|
||||
# Add display settings if available
|
||||
if forward.display:
|
||||
if forward.display.title:
|
||||
payload['news'] = [{'text': forward.display.title}]
|
||||
if forward.display.brief:
|
||||
payload['prompt'] = forward.display.brief
|
||||
if forward.display.summary:
|
||||
payload['summary'] = forward.display.summary
|
||||
if forward.display.source:
|
||||
payload['source'] = forward.display.source
|
||||
|
||||
try:
|
||||
# Use send_forward_msg (NapCat extended API) instead of send_group_forward_msg
|
||||
await self.logger.info(
|
||||
f'Sending forward message to group {group_id} with {len(messages)} nodes, payload keys: {list(payload.keys())}'
|
||||
)
|
||||
result = await self.bot.call_action('send_forward_msg', **payload)
|
||||
await self.logger.info(f'Forward message sent to group {group_id}, result: {result}')
|
||||
except Exception as e:
|
||||
await self.logger.error(f'Failed to send forward message to group {group_id}: {e}')
|
||||
# Fallback: try standard OneBot API with integer group_id
|
||||
try:
|
||||
await self.logger.info('Trying fallback API send_group_forward_msg')
|
||||
await self.bot.call_action('send_group_forward_msg', group_id=group_id, messages=messages)
|
||||
await self.logger.info(f'Forward message sent via fallback API to group {group_id}')
|
||||
except Exception as e2:
|
||||
await self.logger.error(f'Fallback also failed: {e2}')
|
||||
raise
|
||||
|
||||
async def reply_message(
|
||||
self,
|
||||
message_source: platform_events.MessageEvent,
|
||||
|
||||
@@ -231,7 +231,10 @@ class DingTalkAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
|
||||
card_template_id = self.config['card_template_id']
|
||||
incoming_message = event.source_platform_object.incoming_message
|
||||
# message_id = incoming_message.message_id
|
||||
card_instance, card_instance_id = await self.bot.create_and_card(card_template_id, incoming_message)
|
||||
card_auto_layout = self.config.get('card_ auto_layout', False)
|
||||
card_instance, card_instance_id = await self.bot.create_and_card(
|
||||
card_template_id, incoming_message, card_auto_layout=card_auto_layout
|
||||
)
|
||||
self.card_instance_id_dict[message_id] = (card_instance, card_instance_id)
|
||||
return True
|
||||
|
||||
|
||||
@@ -56,6 +56,13 @@ spec:
|
||||
type: boolean
|
||||
required: true
|
||||
default: false
|
||||
- name: card_auto_layout
|
||||
label:
|
||||
en_US: Card Auto Layout
|
||||
zh_Hans: 卡片宽屏自动布局
|
||||
type: boolean
|
||||
required: false
|
||||
default: false
|
||||
- name: card_template_id
|
||||
label:
|
||||
en_US: card template id
|
||||
|
||||
@@ -14,7 +14,7 @@ import io
|
||||
import asyncio
|
||||
from enum import Enum
|
||||
|
||||
import aiohttp
|
||||
from langbot.pkg.utils import httpclient
|
||||
import pydantic
|
||||
|
||||
import langbot_plugin.api.definition.abstract.platform.adapter as abstract_platform_adapter
|
||||
@@ -622,23 +622,23 @@ class DiscordMessageConverter(abstract_platform_adapter.AbstractMessageConverter
|
||||
image_bytes = base64.b64decode(base64_data)
|
||||
elif ele.url:
|
||||
# 从URL下载图片
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.get(ele.url) as response:
|
||||
image_bytes = await response.read()
|
||||
# 从URL或Content-Type推断文件类型
|
||||
content_type = response.headers.get('Content-Type', '')
|
||||
if 'jpeg' in content_type or 'jpg' in content_type:
|
||||
filename = f'{uuid.uuid4()}.jpg'
|
||||
elif 'gif' in content_type:
|
||||
filename = f'{uuid.uuid4()}.gif'
|
||||
elif 'webp' in content_type:
|
||||
filename = f'{uuid.uuid4()}.webp'
|
||||
elif ele.url.lower().endswith(('.jpg', '.jpeg')):
|
||||
filename = f'{uuid.uuid4()}.jpg'
|
||||
elif ele.url.lower().endswith('.gif'):
|
||||
filename = f'{uuid.uuid4()}.gif'
|
||||
elif ele.url.lower().endswith('.webp'):
|
||||
filename = f'{uuid.uuid4()}.webp'
|
||||
session = httpclient.get_session()
|
||||
async with session.get(ele.url) as response:
|
||||
image_bytes = await response.read()
|
||||
# 从URL或Content-Type推断文件类型
|
||||
content_type = response.headers.get('Content-Type', '')
|
||||
if 'jpeg' in content_type or 'jpg' in content_type:
|
||||
filename = f'{uuid.uuid4()}.jpg'
|
||||
elif 'gif' in content_type:
|
||||
filename = f'{uuid.uuid4()}.gif'
|
||||
elif 'webp' in content_type:
|
||||
filename = f'{uuid.uuid4()}.webp'
|
||||
elif ele.url.lower().endswith(('.jpg', '.jpeg')):
|
||||
filename = f'{uuid.uuid4()}.jpg'
|
||||
elif ele.url.lower().endswith('.gif'):
|
||||
filename = f'{uuid.uuid4()}.gif'
|
||||
elif ele.url.lower().endswith('.webp'):
|
||||
filename = f'{uuid.uuid4()}.webp'
|
||||
elif ele.path:
|
||||
# 从文件路径读取图片
|
||||
# 确保路径没有空字节
|
||||
@@ -702,9 +702,9 @@ class DiscordMessageConverter(abstract_platform_adapter.AbstractMessageConverter
|
||||
file_base64 = ele.base64.split(',')[-1]
|
||||
file_bytes = base64.b64decode(file_base64)
|
||||
elif ele.url:
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.get(ele.url) as response:
|
||||
file_bytes = await response.read()
|
||||
session = httpclient.get_session()
|
||||
async with session.get(ele.url) as response:
|
||||
file_bytes = await response.read()
|
||||
if file_bytes:
|
||||
files.append(discord.File(fp=io.BytesIO(file_bytes), filename=filename))
|
||||
elif isinstance(ele, platform_message.File):
|
||||
@@ -717,9 +717,9 @@ class DiscordMessageConverter(abstract_platform_adapter.AbstractMessageConverter
|
||||
else:
|
||||
file_bytes = base64.b64decode(ele.base64)
|
||||
elif ele.url:
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.get(ele.url) as response:
|
||||
file_bytes = await response.read()
|
||||
session = httpclient.get_session()
|
||||
async with session.get(ele.url) as response:
|
||||
file_bytes = await response.read()
|
||||
if file_bytes:
|
||||
files.append(discord.File(fp=io.BytesIO(file_bytes), filename=filename))
|
||||
elif isinstance(ele, platform_message.Forward):
|
||||
@@ -775,12 +775,12 @@ class DiscordMessageConverter(abstract_platform_adapter.AbstractMessageConverter
|
||||
|
||||
# attachments
|
||||
for attachment in message.attachments:
|
||||
async with aiohttp.ClientSession(trust_env=True) as session:
|
||||
async with session.get(attachment.url) as response:
|
||||
image_data = await response.read()
|
||||
image_base64 = base64.b64encode(image_data).decode('utf-8')
|
||||
image_format = response.headers['Content-Type']
|
||||
element_list.append(platform_message.Image(base64=f'data:{image_format};base64,{image_base64}'))
|
||||
session = httpclient.get_session(trust_env=True)
|
||||
async with session.get(attachment.url) as response:
|
||||
image_data = await response.read()
|
||||
image_base64 = base64.b64encode(image_data).decode('utf-8')
|
||||
image_format = response.headers['Content-Type']
|
||||
element_list.append(platform_message.Image(base64=f'data:{image_format};base64,{image_base64}'))
|
||||
|
||||
return platform_message.MessageChain(element_list)
|
||||
|
||||
|
||||
@@ -9,6 +9,8 @@ import traceback
|
||||
import time
|
||||
|
||||
import aiohttp
|
||||
|
||||
from langbot.pkg.utils import httpclient
|
||||
import websockets
|
||||
import pydantic
|
||||
|
||||
@@ -120,16 +122,16 @@ class KookMessageConverter(abstract_platform_adapter.AbstractMessageConverter):
|
||||
if content:
|
||||
# Download image and convert to base64
|
||||
try:
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.get(content) as response:
|
||||
if response.status == 200:
|
||||
image_bytes = await response.read()
|
||||
image_base64 = base64.b64encode(image_bytes).decode('utf-8')
|
||||
# Detect image format
|
||||
content_type = response.headers.get('Content-Type', 'image/png')
|
||||
components.append(
|
||||
platform_message.Image(base64=f'data:{content_type};base64,{image_base64}')
|
||||
)
|
||||
session = httpclient.get_session()
|
||||
async with session.get(content) as response:
|
||||
if response.status == 200:
|
||||
image_bytes = await response.read()
|
||||
image_base64 = base64.b64encode(image_bytes).decode('utf-8')
|
||||
# Detect image format
|
||||
content_type = response.headers.get('Content-Type', 'image/png')
|
||||
components.append(
|
||||
platform_message.Image(base64=f'data:{content_type};base64,{image_base64}')
|
||||
)
|
||||
except Exception:
|
||||
# If download fails, just add as plain text
|
||||
components.append(platform_message.Plain(text=f'[Image: {content}]'))
|
||||
@@ -295,17 +297,17 @@ class KookAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
|
||||
'Authorization': f'Bot {self.config["token"]}',
|
||||
}
|
||||
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.get(base_url, params=params, headers=headers) as response:
|
||||
if response.status == 200:
|
||||
data = await response.json()
|
||||
if data.get('code') == 0:
|
||||
gateway_url = data['data']['url']
|
||||
return gateway_url
|
||||
else:
|
||||
raise Exception(f'Failed to get gateway URL: {data.get("message")}')
|
||||
session = httpclient.get_session()
|
||||
async with session.get(base_url, params=params, headers=headers) as response:
|
||||
if response.status == 200:
|
||||
data = await response.json()
|
||||
if data.get('code') == 0:
|
||||
gateway_url = data['data']['url']
|
||||
return gateway_url
|
||||
else:
|
||||
raise Exception(f'Failed to get gateway URL: HTTP {response.status}')
|
||||
raise Exception(f'Failed to get gateway URL: {data.get("message")}')
|
||||
else:
|
||||
raise Exception(f'Failed to get gateway URL: HTTP {response.status}')
|
||||
|
||||
async def _get_bot_user_info(self) -> dict:
|
||||
"""Get bot's own user information from KOOK API"""
|
||||
@@ -315,17 +317,17 @@ class KookAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
|
||||
'Authorization': f'Bot {self.config["token"]}',
|
||||
}
|
||||
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.get(base_url, headers=headers) as response:
|
||||
if response.status == 200:
|
||||
data = await response.json()
|
||||
if data.get('code') == 0:
|
||||
user_info = data['data']
|
||||
return user_info
|
||||
else:
|
||||
raise Exception(f'Failed to get bot user info: {data.get("message")}')
|
||||
session = httpclient.get_session()
|
||||
async with session.get(base_url, headers=headers) as response:
|
||||
if response.status == 200:
|
||||
data = await response.json()
|
||||
if data.get('code') == 0:
|
||||
user_info = data['data']
|
||||
return user_info
|
||||
else:
|
||||
raise Exception(f'Failed to get bot user info: HTTP {response.status}')
|
||||
raise Exception(f'Failed to get bot user info: {data.get("message")}')
|
||||
else:
|
||||
raise Exception(f'Failed to get bot user info: HTTP {response.status}')
|
||||
|
||||
async def _handle_hello(self, data: dict):
|
||||
"""Handle HELLO signal (signal 1)"""
|
||||
@@ -510,7 +512,7 @@ class KookAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
|
||||
|
||||
try:
|
||||
if not self.http_session:
|
||||
self.http_session = aiohttp.ClientSession()
|
||||
self.http_session = httpclient.get_session()
|
||||
|
||||
async with self.http_session.post(url, json=payload, headers=headers) as response:
|
||||
if response.status == 200:
|
||||
@@ -576,7 +578,7 @@ class KookAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
|
||||
|
||||
try:
|
||||
if not self.http_session:
|
||||
self.http_session = aiohttp.ClientSession()
|
||||
self.http_session = httpclient.get_session()
|
||||
|
||||
async with self.http_session.post(url, json=payload, headers=headers) as response:
|
||||
if response.status == 200:
|
||||
@@ -624,7 +626,7 @@ class KookAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
|
||||
|
||||
try:
|
||||
# Create HTTP session
|
||||
self.http_session = aiohttp.ClientSession()
|
||||
self.http_session = httpclient.get_session()
|
||||
|
||||
await self.logger.info('Starting KOOK adapter')
|
||||
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import lark_oapi
|
||||
from lark_oapi.api.im.v1 import CreateImageRequest, CreateImageRequestBody
|
||||
from lark_oapi.api.im.v1 import CreateImageRequest, CreateImageRequestBody, CreateFileRequest, CreateFileRequestBody
|
||||
import traceback
|
||||
import typing
|
||||
import asyncio
|
||||
@@ -17,7 +17,7 @@ import tempfile
|
||||
import os
|
||||
import mimetypes
|
||||
|
||||
import aiohttp
|
||||
from langbot.pkg.utils import httpclient
|
||||
import lark_oapi.ws.exception
|
||||
import quart
|
||||
from lark_oapi.api.im.v1 import *
|
||||
@@ -78,13 +78,13 @@ class LarkMessageConverter(abstract_platform_adapter.AbstractMessageConverter):
|
||||
return None
|
||||
elif msg.url:
|
||||
try:
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.get(msg.url) as response:
|
||||
if response.status == 200:
|
||||
image_bytes = await response.read()
|
||||
else:
|
||||
print(f'Failed to download image from {msg.url}: HTTP {response.status}')
|
||||
return None
|
||||
session = httpclient.get_session()
|
||||
async with session.get(msg.url) as response:
|
||||
if response.status == 200:
|
||||
image_bytes = await response.read()
|
||||
else:
|
||||
print(f'Failed to download image from {msg.url}: HTTP {response.status}')
|
||||
return None
|
||||
except Exception as e:
|
||||
print(f'Failed to download image from {msg.url}: {e}')
|
||||
traceback.print_exc()
|
||||
@@ -141,6 +141,88 @@ class LarkMessageConverter(abstract_platform_adapter.AbstractMessageConverter):
|
||||
traceback.print_exc()
|
||||
return None
|
||||
|
||||
@staticmethod
|
||||
async def upload_file_to_lark(
|
||||
file_bytes: bytes,
|
||||
api_client: lark_oapi.Client,
|
||||
file_type: str,
|
||||
file_name: str = 'file',
|
||||
duration: typing.Optional[int] = None,
|
||||
) -> typing.Optional[str]:
|
||||
"""Upload a file to Lark and return the file_key, or None if upload fails.
|
||||
|
||||
Args:
|
||||
file_bytes: Raw file bytes.
|
||||
api_client: Lark API client.
|
||||
file_type: Lark file type, e.g. 'opus', 'mp4', 'pdf', 'doc', etc.
|
||||
file_name: Display name for the file.
|
||||
duration: Duration in milliseconds (for audio files).
|
||||
"""
|
||||
try:
|
||||
with tempfile.NamedTemporaryFile(delete=False) as temp_file:
|
||||
temp_file.write(file_bytes)
|
||||
temp_file_path = temp_file.name
|
||||
|
||||
try:
|
||||
body_builder = (
|
||||
CreateFileRequestBody.builder()
|
||||
.file_type(file_type)
|
||||
.file_name(file_name)
|
||||
.file(open(temp_file_path, 'rb'))
|
||||
)
|
||||
if duration is not None:
|
||||
body_builder = body_builder.duration(duration)
|
||||
|
||||
request = CreateFileRequest.builder().request_body(body_builder.build()).build()
|
||||
|
||||
response = await api_client.im.v1.file.acreate(request)
|
||||
|
||||
if not response.success():
|
||||
print(
|
||||
f'client.im.v1.file.create failed, code: {response.code}, msg: {response.msg}, log_id: {response.get_log_id()}'
|
||||
)
|
||||
return None
|
||||
|
||||
return response.data.file_key
|
||||
finally:
|
||||
os.unlink(temp_file_path)
|
||||
except Exception as e:
|
||||
print(f'Failed to upload file to Lark: {e}')
|
||||
traceback.print_exc()
|
||||
return None
|
||||
|
||||
@staticmethod
|
||||
async def _get_media_bytes(
|
||||
msg: typing.Union[platform_message.Voice, platform_message.File],
|
||||
) -> typing.Optional[bytes]:
|
||||
"""Get bytes from a Voice or File message (base64, url, or path)."""
|
||||
data = None
|
||||
|
||||
if msg.base64:
|
||||
try:
|
||||
base64_str = msg.base64
|
||||
if ',' in base64_str:
|
||||
base64_str = base64_str.split(',', 1)[1]
|
||||
data = base64.b64decode(base64_str)
|
||||
except Exception:
|
||||
pass
|
||||
elif msg.url:
|
||||
try:
|
||||
session = httpclient.get_session()
|
||||
async with session.get(msg.url) as resp:
|
||||
if resp.status == 200:
|
||||
data = await resp.read()
|
||||
except Exception:
|
||||
pass
|
||||
elif msg.path:
|
||||
try:
|
||||
with open(msg.path, 'rb') as f:
|
||||
data = f.read()
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
return data
|
||||
|
||||
@staticmethod
|
||||
async def yiri2target(
|
||||
message_chain: platform_message.MessageChain, api_client: lark_oapi.Client
|
||||
@@ -150,10 +232,10 @@ class LarkMessageConverter(abstract_platform_adapter.AbstractMessageConverter):
|
||||
Returns:
|
||||
Tuple of (text_elements, image_keys):
|
||||
- text_elements: List of paragraphs for post message format
|
||||
- image_keys: List of image_key strings for separate image messages
|
||||
- media_items: List of dicts with 'msg_type' and 'content' for separate media messages
|
||||
"""
|
||||
message_elements = []
|
||||
image_keys = []
|
||||
media_items = []
|
||||
pending_paragraph = []
|
||||
|
||||
# Regex pattern to match Markdown image syntax: 
|
||||
@@ -196,40 +278,77 @@ class LarkMessageConverter(abstract_platform_adapter.AbstractMessageConverter):
|
||||
# Check for and extract Markdown images from text
|
||||
cleaned_text, extracted_urls = await process_text_with_images(text)
|
||||
|
||||
# Add cleaned text if not empty
|
||||
# Split by blank lines to create separate paragraphs for Lark post format.
|
||||
# Lark truncates md elements at the first \n\n, so we must use the
|
||||
# post format's native paragraph structure instead.
|
||||
if cleaned_text:
|
||||
pending_paragraph.append({'tag': 'md', 'text': cleaned_text})
|
||||
segments = re.split(r'\n\s*\n', cleaned_text)
|
||||
for i, segment in enumerate(segments):
|
||||
segment = segment.strip()
|
||||
if not segment:
|
||||
continue
|
||||
if i > 0 and pending_paragraph:
|
||||
message_elements.append(pending_paragraph)
|
||||
pending_paragraph = []
|
||||
pending_paragraph.append({'tag': 'md', 'text': segment})
|
||||
|
||||
# Process extracted image URLs
|
||||
for url in extracted_urls:
|
||||
# Create a temporary Image message to upload
|
||||
temp_image = platform_message.Image(url=url)
|
||||
image_key = await LarkMessageConverter.upload_image_to_lark(temp_image, api_client)
|
||||
if image_key:
|
||||
image_keys.append(image_key)
|
||||
media_items.append({'msg_type': 'image', 'content': {'image_key': image_key}})
|
||||
|
||||
elif isinstance(msg, platform_message.At):
|
||||
pending_paragraph.append({'tag': 'at', 'user_id': msg.target, 'style': []})
|
||||
elif isinstance(msg, platform_message.AtAll):
|
||||
pending_paragraph.append({'tag': 'at', 'user_id': 'all', 'style': []})
|
||||
elif isinstance(msg, platform_message.Image):
|
||||
# Upload image and get image_key
|
||||
image_key = await LarkMessageConverter.upload_image_to_lark(msg, api_client)
|
||||
if image_key:
|
||||
# Store image_key for separate image message
|
||||
image_keys.append(image_key)
|
||||
media_items.append({'msg_type': 'image', 'content': {'image_key': image_key}})
|
||||
elif isinstance(msg, platform_message.Voice):
|
||||
data = await LarkMessageConverter._get_media_bytes(msg)
|
||||
if data:
|
||||
duration = int(msg.length * 1000) if msg.length else None
|
||||
file_key = await LarkMessageConverter.upload_file_to_lark(
|
||||
data, api_client, file_type='opus', file_name='voice.opus', duration=duration
|
||||
)
|
||||
if file_key:
|
||||
media_items.append({'msg_type': 'audio', 'content': {'file_key': file_key}})
|
||||
elif isinstance(msg, platform_message.File):
|
||||
data = await LarkMessageConverter._get_media_bytes(msg)
|
||||
if data:
|
||||
file_name = msg.name or 'file'
|
||||
# Guess file_type from extension
|
||||
ext = os.path.splitext(file_name)[1].lstrip('.').lower() if file_name else ''
|
||||
file_type_map = {
|
||||
'opus': 'opus',
|
||||
'mp4': 'mp4',
|
||||
'pdf': 'pdf',
|
||||
'doc': 'doc',
|
||||
'docx': 'doc',
|
||||
'xls': 'xls',
|
||||
'xlsx': 'xls',
|
||||
'ppt': 'ppt',
|
||||
'pptx': 'ppt',
|
||||
}
|
||||
file_type = file_type_map.get(ext, 'stream')
|
||||
file_key = await LarkMessageConverter.upload_file_to_lark(
|
||||
data, api_client, file_type=file_type, file_name=file_name
|
||||
)
|
||||
if file_key:
|
||||
media_items.append({'msg_type': 'file', 'content': {'file_key': file_key}})
|
||||
elif isinstance(msg, platform_message.Forward):
|
||||
for node in msg.node_list:
|
||||
sub_elements, sub_image_keys = await LarkMessageConverter.yiri2target(
|
||||
node.message_chain, api_client
|
||||
)
|
||||
sub_elements, sub_media = await LarkMessageConverter.yiri2target(node.message_chain, api_client)
|
||||
message_elements.extend(sub_elements)
|
||||
image_keys.extend(sub_image_keys)
|
||||
media_items.extend(sub_media)
|
||||
|
||||
if pending_paragraph:
|
||||
message_elements.append(pending_paragraph)
|
||||
|
||||
return message_elements, image_keys
|
||||
return message_elements, media_items
|
||||
|
||||
@staticmethod
|
||||
async def target2yiri(
|
||||
@@ -917,23 +1036,40 @@ class LarkAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
|
||||
):
|
||||
# 不再需要了，因为message_id已经被包含到message_chain中
|
||||
# lark_event = await self.event_converter.yiri2target(message_source)
|
||||
text_elements, image_keys = await self.message_converter.yiri2target(message, self.api_client)
|
||||
text_elements, media_items = await self.message_converter.yiri2target(message, self.api_client)
|
||||
|
||||
# Send text message if there are text elements
|
||||
if text_elements:
|
||||
final_content = {
|
||||
'zh_Hans': {
|
||||
'title': '',
|
||||
'content': text_elements,
|
||||
},
|
||||
}
|
||||
# Determine msg_type based on content: use 'post' if at mentions
|
||||
# are present (requires post paragraph structure), otherwise 'text'
|
||||
needs_post = any(ele['tag'] == 'at' for paragraph in text_elements for ele in paragraph)
|
||||
|
||||
if needs_post:
|
||||
msg_type = 'post'
|
||||
final_content = json.dumps(
|
||||
{
|
||||
'zh_Hans': {
|
||||
'title': '',
|
||||
'content': text_elements,
|
||||
},
|
||||
}
|
||||
)
|
||||
else:
|
||||
msg_type = 'text'
|
||||
parts = []
|
||||
for paragraph in text_elements:
|
||||
para_text = ''.join(ele.get('text', '') for ele in paragraph)
|
||||
if para_text:
|
||||
parts.append(para_text)
|
||||
final_content = json.dumps({'text': '\n\n'.join(parts)})
|
||||
|
||||
request: ReplyMessageRequest = (
|
||||
ReplyMessageRequest.builder()
|
||||
.message_id(message_source.message_chain.message_id)
|
||||
.request_body(
|
||||
ReplyMessageRequestBody.builder()
|
||||
.content(json.dumps(final_content))
|
||||
.msg_type('post')
|
||||
.content(final_content)
|
||||
.msg_type(msg_type)
|
||||
.reply_in_thread(False)
|
||||
.uuid(str(uuid.uuid4()))
|
||||
.build()
|
||||
@@ -963,17 +1099,15 @@ class LarkAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
|
||||
f'client.im.v1.message.reply failed, code: {response.code}, msg: {response.msg}, log_id: {response.get_log_id()}, resp: \n{json.dumps(json.loads(response.raw.content), indent=4, ensure_ascii=False)}'
|
||||
)
|
||||
|
||||
# Send image messages separately using msg_type='image'
|
||||
for image_key in image_keys:
|
||||
image_content = json.dumps({'image_key': image_key})
|
||||
|
||||
# Send media messages separately (image, audio, file, etc.)
|
||||
for media in media_items:
|
||||
request: ReplyMessageRequest = (
|
||||
ReplyMessageRequest.builder()
|
||||
.message_id(message_source.message_chain.message_id)
|
||||
.request_body(
|
||||
ReplyMessageRequestBody.builder()
|
||||
.content(image_content)
|
||||
.msg_type('image')
|
||||
.content(json.dumps(media['content']))
|
||||
.msg_type(media['msg_type'])
|
||||
.reply_in_thread(False)
|
||||
.uuid(str(uuid.uuid4()))
|
||||
.build()
|
||||
@@ -1000,7 +1134,7 @@ class LarkAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
|
||||
|
||||
if not response.success():
|
||||
raise Exception(
|
||||
f'client.im.v1.message.reply (image) failed, code: {response.code}, msg: {response.msg}, log_id: {response.get_log_id()}, resp: \n{json.dumps(json.loads(response.raw.content), indent=4, ensure_ascii=False)}'
|
||||
f'client.im.v1.message.reply ({media["msg_type"]}) failed, code: {response.code}, msg: {response.msg}, log_id: {response.get_log_id()}, resp: \n{json.dumps(json.loads(response.raw.content), indent=4, ensure_ascii=False)}'
|
||||
)
|
||||
|
||||
async def reply_message_chunk(
|
||||
@@ -1018,15 +1152,16 @@ class LarkAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
|
||||
message_id = bot_message.resp_message_id
|
||||
msg_seq = bot_message.msg_sequence
|
||||
if msg_seq % 8 == 0 or is_final:
|
||||
text_elements, image_keys = await self.message_converter.yiri2target(message, self.api_client)
|
||||
text_elements, media_items = await self.message_converter.yiri2target(message, self.api_client)
|
||||
|
||||
text_message = ''
|
||||
if text_elements:
|
||||
for ele in text_elements[0]:
|
||||
if ele['tag'] == 'text':
|
||||
text_message += ele['text']
|
||||
elif ele['tag'] == 'md':
|
||||
text_message += ele['text']
|
||||
parts = []
|
||||
for paragraph in text_elements:
|
||||
para_text = ''.join(ele['text'] for ele in paragraph if ele['tag'] in ('text', 'md'))
|
||||
if para_text:
|
||||
parts.append(para_text)
|
||||
text_message = '\n\n'.join(parts)
|
||||
|
||||
# content = {
|
||||
# 'type': 'card_json',
|
||||
@@ -1076,6 +1211,30 @@ class LarkAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
|
||||
)
|
||||
return
|
||||
|
||||
# Send media messages when streaming is done
|
||||
if is_final and media_items:
|
||||
for media in media_items:
|
||||
media_request: ReplyMessageRequest = (
|
||||
ReplyMessageRequest.builder()
|
||||
.message_id(message_source.message_chain.message_id)
|
||||
.request_body(
|
||||
ReplyMessageRequestBody.builder()
|
||||
.content(json.dumps(media['content']))
|
||||
.msg_type(media['msg_type'])
|
||||
.reply_in_thread(False)
|
||||
.uuid(str(uuid.uuid4()))
|
||||
.build()
|
||||
)
|
||||
.build()
|
||||
)
|
||||
media_response: ReplyMessageResponse = await self.api_client.im.v1.message.areply(
|
||||
media_request, req_opt
|
||||
)
|
||||
if not media_response.success():
|
||||
raise Exception(
|
||||
f'client.im.v1.message.reply ({media["msg_type"]}) failed, code: {media_response.code}, msg: {media_response.msg}, log_id: {media_response.get_log_id()}'
|
||||
)
|
||||
|
||||
async def is_muted(self, group_id: int) -> bool:
|
||||
return False
|
||||
|
||||
|
||||
@@ -9,7 +9,7 @@ import copy
|
||||
import threading
|
||||
|
||||
import quart
|
||||
import aiohttp
|
||||
from langbot.pkg.utils import httpclient
|
||||
|
||||
import langbot_plugin.api.definition.abstract.platform.adapter as abstract_platform_adapter
|
||||
from ....core import app
|
||||
@@ -639,14 +639,14 @@ class GeWeChatAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
|
||||
|
||||
async def run_async(self):
|
||||
if not self.config['token']:
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.post(
|
||||
f'{self.config["gewechat_url"]}/v2/api/tools/getTokenId',
|
||||
json={'app_id': self.config['app_id']},
|
||||
) as response:
|
||||
if response.status != 200:
|
||||
raise Exception(f'获取gewechat token失败: {await response.text()}')
|
||||
self.config['token'] = (await response.json())['data']
|
||||
session = httpclient.get_session()
|
||||
async with session.post(
|
||||
f'{self.config["gewechat_url"]}/v2/api/tools/getTokenId',
|
||||
json={'app_id': self.config['app_id']},
|
||||
) as response:
|
||||
if response.status != 200:
|
||||
raise Exception(f'获取gewechat token失败: {await response.text()}')
|
||||
self.config['token'] = (await response.json())['data']
|
||||
|
||||
self.bot = gewechat_client.GewechatClient(f'{self.config["gewechat_url"]}/v2/api', self.config['token'])
|
||||
|
||||
|
||||
BIN
src/langbot/pkg/platform/sources/satori.png
Normal file
BIN
src/langbot/pkg/platform/sources/satori.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 10 KiB |
1090
src/langbot/pkg/platform/sources/satori.py
Normal file
1090
src/langbot/pkg/platform/sources/satori.py
Normal file
File diff suppressed because it is too large
Load Diff
65
src/langbot/pkg/platform/sources/satori.yaml
Normal file
65
src/langbot/pkg/platform/sources/satori.yaml
Normal file
@@ -0,0 +1,65 @@
|
||||
apiVersion: v1
|
||||
kind: MessagePlatformAdapter
|
||||
metadata:
|
||||
name: satori
|
||||
label:
|
||||
en_US: Satori
|
||||
zh_Hans: Satori
|
||||
description:
|
||||
en_US: SatoriAdapter
|
||||
zh_Hans: 古明地觉协议适配器
|
||||
icon: satori.png
|
||||
spec:
|
||||
config:
|
||||
- name: platform
|
||||
label:
|
||||
en_US: Platform
|
||||
zh_Hans: 平台名称
|
||||
type: string
|
||||
required: true
|
||||
default: "llonebot"
|
||||
description:
|
||||
en_US: The platform name (e.g., llonebot, discord, telegram)
|
||||
zh_Hans: 平台名称（如 llonebot, discord, telegram）
|
||||
- name: host
|
||||
label:
|
||||
en_US: Host
|
||||
zh_Hans: 主机地址
|
||||
type: string
|
||||
required: true
|
||||
default: "127.0.0.1"
|
||||
description:
|
||||
en_US: The host address of LLOneBot Satori server (e.g., 127.0.0.1, localhost, 192.168.1.100)
|
||||
zh_Hans: LLOneBot Satori服务器的主机地址（如 127.0.0.1, localhost, 192.168.1.100）
|
||||
- name: port
|
||||
label:
|
||||
en_US: Port
|
||||
zh_Hans: 监听端口
|
||||
type: integer
|
||||
required: true
|
||||
default: 5600
|
||||
- name: satori_api_base_url
|
||||
label:
|
||||
en_US: Satori API Endpoint
|
||||
zh_Hans: Satori API 终结点
|
||||
type: string
|
||||
required: true
|
||||
default: "http://localhost:5600/v1"
|
||||
- name: satori_endpoint
|
||||
label:
|
||||
en_US: Satori WebSocket Endpoint
|
||||
zh_Hans: Satori WebSocket 终结点
|
||||
type: string
|
||||
required: true
|
||||
default: "ws://localhost:5600/v1/events"
|
||||
- name: token
|
||||
label:
|
||||
en_US: Token
|
||||
zh_Hans: 令牌
|
||||
type: string
|
||||
required: true
|
||||
default: ""
|
||||
execution:
|
||||
python:
|
||||
path: ./satori.py
|
||||
attr: SatoriAdapter
|
||||
@@ -9,9 +9,9 @@ import telegramify_markdown
|
||||
import typing
|
||||
import traceback
|
||||
import base64
|
||||
import aiohttp
|
||||
import pydantic
|
||||
|
||||
from langbot.pkg.utils import httpclient
|
||||
import langbot_plugin.api.definition.abstract.platform.adapter as abstract_platform_adapter
|
||||
import langbot_plugin.api.entities.builtin.platform.message as platform_message
|
||||
import langbot_plugin.api.entities.builtin.platform.events as platform_events
|
||||
@@ -33,9 +33,9 @@ class TelegramMessageConverter(abstract_platform_adapter.AbstractMessageConverte
|
||||
if component.base64:
|
||||
photo_bytes = base64.b64decode(component.base64)
|
||||
elif component.url:
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.get(component.url) as response:
|
||||
photo_bytes = await response.read()
|
||||
session = httpclient.get_session()
|
||||
async with session.get(component.url) as response:
|
||||
photo_bytes = await response.read()
|
||||
elif component.path:
|
||||
with open(component.path, 'rb') as f:
|
||||
photo_bytes = f.read()
|
||||
@@ -74,10 +74,9 @@ class TelegramMessageConverter(abstract_platform_adapter.AbstractMessageConverte
|
||||
file_bytes = None
|
||||
file_format = ''
|
||||
|
||||
async with aiohttp.ClientSession(trust_env=True) as session:
|
||||
async with session.get(file.file_path) as response:
|
||||
file_bytes = await response.read()
|
||||
file_format = 'image/jpeg'
|
||||
async with httpclient.get_session(trust_env=True).get(file.file_path) as response:
|
||||
file_bytes = await response.read()
|
||||
file_format = 'image/jpeg'
|
||||
|
||||
message_components.append(
|
||||
platform_message.Image(
|
||||
@@ -85,6 +84,25 @@ class TelegramMessageConverter(abstract_platform_adapter.AbstractMessageConverte
|
||||
)
|
||||
)
|
||||
|
||||
if message.voice:
|
||||
if message.caption:
|
||||
message_components.extend(parse_message_text(message.caption))
|
||||
|
||||
file = await message.voice.get_file()
|
||||
|
||||
file_bytes = None
|
||||
file_format = message.voice.mime_type or 'audio/ogg'
|
||||
|
||||
async with httpclient.get_session(trust_env=True).get(file.file_path) as response:
|
||||
file_bytes = await response.read()
|
||||
|
||||
message_components.append(
|
||||
platform_message.Voice(
|
||||
base64=f'data:{file_format};base64,{base64.b64encode(file_bytes).decode("utf-8")}',
|
||||
length=message.voice.duration,
|
||||
)
|
||||
)
|
||||
|
||||
return platform_message.MessageChain(message_components)
|
||||
|
||||
|
||||
@@ -159,7 +177,9 @@ class TelegramAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
|
||||
|
||||
application = ApplicationBuilder().token(config['token']).build()
|
||||
bot = application.bot
|
||||
application.add_handler(MessageHandler(filters.TEXT | (filters.COMMAND) | filters.PHOTO, telegram_callback))
|
||||
application.add_handler(
|
||||
MessageHandler(filters.TEXT | (filters.COMMAND) | filters.PHOTO | filters.VOICE, telegram_callback)
|
||||
)
|
||||
super().__init__(
|
||||
config=config,
|
||||
logger=logger,
|
||||
@@ -172,7 +192,31 @@ class TelegramAdapter(abstract_platform_adapter.AbstractMessagePlatformAdapter):
|
||||
)
|
||||
|
||||
async def send_message(self, target_type: str, target_id: str, message: platform_message.MessageChain):
|
||||
pass
|
||||
components = await TelegramMessageConverter.yiri2target(message, self.bot)
|
||||
|
||||
chat_id_str, _, thread_id_str = str(target_id).partition('#')
|
||||
chat_id: int | str = int(chat_id_str) if chat_id_str.lstrip('-').isdigit() else chat_id_str
|
||||
message_thread_id = int(thread_id_str) if thread_id_str and thread_id_str.isdigit() else None
|
||||
|
||||
for component in components:
|
||||
component_type = component.get('type')
|
||||
args = {'chat_id': chat_id}
|
||||
if message_thread_id is not None:
|
||||
args['message_thread_id'] = message_thread_id
|
||||
|
||||
if component_type == 'text':
|
||||
text = component.get('text', '')
|
||||
if self.config['markdown_card'] is True:
|
||||
text = telegramify_markdown.markdownify(content=text)
|
||||
args['parse_mode'] = 'MarkdownV2'
|
||||
args['text'] = text
|
||||
await self.bot.send_message(**args)
|
||||
elif component_type == 'photo':
|
||||
photo = component.get('photo')
|
||||
if photo is None:
|
||||
continue
|
||||
args['photo'] = telegram.InputFile(photo)
|
||||
await self.bot.send_photo(**args)
|
||||
|
||||
async def reply_message(
|
||||
self,
|
||||
|
||||
@@ -3,6 +3,8 @@ from __future__ import annotations
|
||||
import asyncio
|
||||
import logging
|
||||
import aiohttp
|
||||
|
||||
from langbot.pkg.utils import httpclient
|
||||
import uuid
|
||||
from typing import TYPE_CHECKING
|
||||
|
||||
@@ -119,23 +121,23 @@ class WebhookPusher:
|
||||
dict | None: The response JSON if successful, None otherwise
|
||||
"""
|
||||
try:
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.post(
|
||||
url,
|
||||
json=payload,
|
||||
headers={'Content-Type': 'application/json'},
|
||||
timeout=aiohttp.ClientTimeout(total=15),
|
||||
) as response:
|
||||
if response.status >= 400:
|
||||
self.logger.warning(f'Webhook {url} returned status {response.status}')
|
||||
session = httpclient.get_session()
|
||||
async with session.post(
|
||||
url,
|
||||
json=payload,
|
||||
headers={'Content-Type': 'application/json'},
|
||||
timeout=aiohttp.ClientTimeout(total=15),
|
||||
) as response:
|
||||
if response.status >= 400:
|
||||
self.logger.warning(f'Webhook {url} returned status {response.status}')
|
||||
return None
|
||||
else:
|
||||
self.logger.debug(f'Successfully pushed to webhook {url}')
|
||||
try:
|
||||
return await response.json()
|
||||
except Exception as json_error:
|
||||
self.logger.debug(f'Failed to parse JSON response from webhook {url}: {json_error}')
|
||||
return None
|
||||
else:
|
||||
self.logger.debug(f'Successfully pushed to webhook {url}')
|
||||
try:
|
||||
return await response.json()
|
||||
except Exception as json_error:
|
||||
self.logger.debug(f'Failed to parse JSON response from webhook {url}: {json_error}')
|
||||
return None
|
||||
except asyncio.TimeoutError:
|
||||
self.logger.warning(f'Timeout pushing to webhook {url}')
|
||||
return None
|
||||
|
||||
@@ -279,6 +279,7 @@ class RuntimeConnectionHandler(handler.Handler):
|
||||
target_id = data['target_id']
|
||||
message_chain = data['message_chain']
|
||||
|
||||
# Use custom deserializer that properly handles Forward messages
|
||||
message_chain_obj = platform_message.MessageChain.model_validate(message_chain)
|
||||
|
||||
bot = await self.ap.platform_mgr.get_bot_by_uuid(bot_uuid)
|
||||
|
||||
@@ -149,6 +149,7 @@ class ModelManager:
|
||||
'prefered_ranking': space_model.featured_order,
|
||||
},
|
||||
preserve_uuid=True,
|
||||
auto_set_to_default_pipeline=False,
|
||||
)
|
||||
|
||||
elif space_model.category == 'embedding':
|
||||
|
||||
@@ -43,7 +43,7 @@ class DeepseekChatCompletions(chatcmpl.OpenAIChatCompletions):
|
||||
# deepseek 不支持多模态，把content都转换成纯文字
|
||||
for m in messages:
|
||||
if 'content' in m and isinstance(m['content'], list):
|
||||
m['content'] = ' '.join([c['text'] for c in m['content']])
|
||||
m['content'] = ' '.join([c['text'] for c in m['content'] if 'text' in c])
|
||||
|
||||
args['messages'] = messages
|
||||
|
||||
|
||||
@@ -20,24 +20,6 @@ class GeminiChatCompletions(chatcmpl.OpenAIChatCompletions):
|
||||
'timeout': 120,
|
||||
}
|
||||
|
||||
def _add_thought_signature_to_messages(self, messages: list[dict]) -> list[dict]:
|
||||
"""Add thought_signature to tool_calls in messages for Gemini API compatibility
|
||||
|
||||
Gemini API requires a thought_signature field in function call parts.
|
||||
See: https://ai.google.dev/gemini-api/docs/thought-signatures
|
||||
|
||||
Note: This function modifies the dictionaries in the messages list in place.
|
||||
"""
|
||||
for msg in messages:
|
||||
if 'tool_calls' in msg and msg['tool_calls']:
|
||||
# Ensure we're working with a mutable copy of tool_calls
|
||||
if not isinstance(msg['tool_calls'], list):
|
||||
continue
|
||||
for tool_call in msg['tool_calls']:
|
||||
if isinstance(tool_call, dict) and 'thought_signature' not in tool_call:
|
||||
tool_call['thought_signature'] = ''
|
||||
return messages
|
||||
|
||||
async def _closure_stream(
|
||||
self,
|
||||
query: pipeline_query.Query,
|
||||
@@ -60,9 +42,6 @@ class GeminiChatCompletions(chatcmpl.OpenAIChatCompletions):
|
||||
# 设置此次请求中的messages
|
||||
messages = req_messages.copy()
|
||||
|
||||
# Add thought_signature to tool_calls for Gemini compatibility
|
||||
messages = self._add_thought_signature_to_messages(messages)
|
||||
|
||||
# 检查vision
|
||||
for msg in messages:
|
||||
if 'content' in msg and isinstance(msg['content'], list):
|
||||
@@ -161,29 +140,3 @@ class GeminiChatCompletions(chatcmpl.OpenAIChatCompletions):
|
||||
|
||||
yield provider_message.MessageChunk(**chunk_data)
|
||||
chunk_idx += 1
|
||||
|
||||
async def _closure(
|
||||
self,
|
||||
query: pipeline_query.Query,
|
||||
req_messages: list[dict],
|
||||
use_model: requester.RuntimeLLMModel,
|
||||
use_funcs: list[resource_tool.LLMTool] = None,
|
||||
extra_args: dict[str, typing.Any] = {},
|
||||
remove_think: bool = False,
|
||||
) -> tuple[provider_message.Message, dict]:
|
||||
"""Override _closure to add thought_signature to messages"""
|
||||
# Make a shallow copy to avoid mutating the caller's list
|
||||
messages = req_messages.copy()
|
||||
|
||||
# Add thought_signature to tool_calls for Gemini compatibility
|
||||
messages = self._add_thought_signature_to_messages(messages)
|
||||
|
||||
# Call parent implementation
|
||||
return await super()._closure(
|
||||
query=query,
|
||||
req_messages=messages,
|
||||
use_model=use_model,
|
||||
use_funcs=use_funcs,
|
||||
extra_args=extra_args,
|
||||
remove_think=remove_think,
|
||||
)
|
||||
|
||||
@@ -118,6 +118,7 @@ class DashScopeAPIRunner(runner.RequestRunner):
|
||||
stream=True, # 流式输出
|
||||
incremental_output=True, # 增量输出，使用流式输出需要开启增量输出
|
||||
session_id=query.session.using_conversation.uuid, # 会话ID用于，多轮对话
|
||||
enable_thinking=has_thoughts,
|
||||
has_thoughts=has_thoughts,
|
||||
# rag_options={ # 主要用于文件交互，暂不支持
|
||||
# "session_file_ids": ["FILE_ID1"], # FILE_ID1 替换为实际的临时文件ID,逗号隔开多个
|
||||
@@ -141,14 +142,14 @@ class DashScopeAPIRunner(runner.RequestRunner):
|
||||
# 获取流式传输的output
|
||||
stream_output = chunk.get('output', {})
|
||||
stream_think = stream_output.get('thoughts', [])
|
||||
if stream_think[0].get('thought'):
|
||||
if stream_think and stream_think[0].get('thought'):
|
||||
if not think_start:
|
||||
think_start = True
|
||||
pending_content += f'<think>\n{stream_think[0].get("thought")}'
|
||||
else:
|
||||
# 继续输出 reasoning_content
|
||||
pending_content += stream_think[0].get('thought')
|
||||
elif stream_think[0].get('thought') == '' and not think_end:
|
||||
elif (not stream_think or stream_think[0].get('thought') == '') and not think_end:
|
||||
think_end = True
|
||||
pending_content += '\n</think>\n'
|
||||
if stream_output.get('text') is not None:
|
||||
|
||||
@@ -289,12 +289,16 @@ class DifyServiceAPIRunner(runner.RequestRunner):
|
||||
yield msg
|
||||
if chunk['event'] == 'message_file':
|
||||
if chunk['type'] == 'image' and chunk['belongs_to'] == 'assistant':
|
||||
base_url = self.dify_client.base_url
|
||||
# 检查URL是否已经是完整的连接
|
||||
if chunk['url'].startswith('http://') or chunk['url'].startswith('https://'):
|
||||
image_url = chunk['url']
|
||||
else:
|
||||
base_url = self.dify_client.base_url
|
||||
|
||||
if base_url.endswith('/v1'):
|
||||
base_url = base_url[:-3]
|
||||
if base_url.endswith('/v1'):
|
||||
base_url = base_url[:-3]
|
||||
|
||||
image_url = base_url + chunk['url']
|
||||
image_url = base_url + chunk['url']
|
||||
|
||||
yield provider_message.Message(
|
||||
role='assistant',
|
||||
@@ -559,12 +563,16 @@ class DifyServiceAPIRunner(runner.RequestRunner):
|
||||
if chunk['event'] == 'message_file':
|
||||
message_idx += 1
|
||||
if chunk['type'] == 'image' and chunk['belongs_to'] == 'assistant':
|
||||
base_url = self.dify_client.base_url
|
||||
# 检查URL是否已经是完整的连接
|
||||
if chunk['url'].startswith('http://') or chunk['url'].startswith('https://'):
|
||||
image_url = chunk['url']
|
||||
else:
|
||||
base_url = self.dify_client.base_url
|
||||
|
||||
if base_url.endswith('/v1'):
|
||||
base_url = base_url[:-3]
|
||||
if base_url.endswith('/v1'):
|
||||
base_url = base_url[:-3]
|
||||
|
||||
image_url = base_url + chunk['url']
|
||||
image_url = base_url + chunk['url']
|
||||
|
||||
yield provider_message.MessageChunk(
|
||||
role='assistant',
|
||||
|
||||
@@ -5,6 +5,8 @@ import json
|
||||
import uuid
|
||||
import aiohttp
|
||||
|
||||
from langbot.pkg.utils import httpclient
|
||||
|
||||
from .. import runner
|
||||
from ...core import app
|
||||
import langbot_plugin.api.entities.builtin.pipeline.query as pipeline_query
|
||||
@@ -217,50 +219,50 @@ class N8nServiceAPIRunner(runner.RequestRunner):
|
||||
self.ap.logger.debug('no auth')
|
||||
|
||||
# 调用webhook
|
||||
async with aiohttp.ClientSession() as session:
|
||||
if is_stream:
|
||||
# 流式请求
|
||||
async with session.post(
|
||||
self.webhook_url, json=payload, headers=headers, auth=auth, timeout=self.timeout
|
||||
) as response:
|
||||
session = httpclient.get_session()
|
||||
if is_stream:
|
||||
# 流式请求
|
||||
async with session.post(
|
||||
self.webhook_url, json=payload, headers=headers, auth=auth, timeout=self.timeout
|
||||
) as response:
|
||||
if response.status != 200:
|
||||
error_text = await response.text()
|
||||
self.ap.logger.error(f'n8n webhook call failed: {response.status}, {error_text}')
|
||||
raise Exception(f'n8n webhook call failed: {response.status}, {error_text}')
|
||||
|
||||
# 处理流式响应
|
||||
async for chunk in self._process_stream_response(response):
|
||||
yield chunk
|
||||
else:
|
||||
async with session.post(
|
||||
self.webhook_url, json=payload, headers=headers, auth=auth, timeout=self.timeout
|
||||
) as response:
|
||||
try:
|
||||
async for chunk in self._process_stream_response(response):
|
||||
output_content = chunk.content if chunk.is_final else ''
|
||||
except:
|
||||
# 非流式请求（保持原有逻辑）
|
||||
if response.status != 200:
|
||||
error_text = await response.text()
|
||||
self.ap.logger.error(f'n8n webhook call failed: {response.status}, {error_text}')
|
||||
raise Exception(f'n8n webhook call failed: {response.status}, {error_text}')
|
||||
|
||||
# 处理流式响应
|
||||
async for chunk in self._process_stream_response(response):
|
||||
yield chunk
|
||||
else:
|
||||
async with session.post(
|
||||
self.webhook_url, json=payload, headers=headers, auth=auth, timeout=self.timeout
|
||||
) as response:
|
||||
try:
|
||||
async for chunk in self._process_stream_response(response):
|
||||
output_content = chunk.content if chunk.is_final else ''
|
||||
except:
|
||||
# 非流式请求（保持原有逻辑）
|
||||
if response.status != 200:
|
||||
error_text = await response.text()
|
||||
self.ap.logger.error(f'n8n webhook call failed: {response.status}, {error_text}')
|
||||
raise Exception(f'n8n webhook call failed: {response.status}, {error_text}')
|
||||
# 解析响应
|
||||
response_data = await response.json()
|
||||
self.ap.logger.debug(f'n8n webhook response: {response_data}')
|
||||
|
||||
# 解析响应
|
||||
response_data = await response.json()
|
||||
self.ap.logger.debug(f'n8n webhook response: {response_data}')
|
||||
# 从响应中提取输出
|
||||
if self.output_key in response_data:
|
||||
output_content = response_data[self.output_key]
|
||||
else:
|
||||
# 如果没有指定的输出键，则使用整个响应
|
||||
output_content = json.dumps(response_data, ensure_ascii=False)
|
||||
|
||||
# 从响应中提取输出
|
||||
if self.output_key in response_data:
|
||||
output_content = response_data[self.output_key]
|
||||
else:
|
||||
# 如果没有指定的输出键，则使用整个响应
|
||||
output_content = json.dumps(response_data, ensure_ascii=False)
|
||||
|
||||
# 返回消息
|
||||
yield provider_message.Message(
|
||||
role='assistant',
|
||||
content=output_content,
|
||||
)
|
||||
# 返回消息
|
||||
yield provider_message.Message(
|
||||
role='assistant',
|
||||
content=output_content,
|
||||
)
|
||||
except Exception as e:
|
||||
self.ap.logger.error(f'n8n webhook call exception: {str(e)}')
|
||||
raise N8nAPIError(f'n8n webhook call exception: {str(e)}')
|
||||
|
||||
@@ -3,7 +3,7 @@ from __future__ import annotations
|
||||
|
||||
from ..core import app
|
||||
from . import provider
|
||||
from .providers import localstorage, s3storage
|
||||
from .providers import localstorage
|
||||
|
||||
|
||||
class StorageMgr:
|
||||
@@ -21,6 +21,8 @@ class StorageMgr:
|
||||
storage_type = storage_config.get('use', 'local')
|
||||
|
||||
if storage_type == 's3':
|
||||
from .providers import s3storage
|
||||
|
||||
self.storage_provider = s3storage.S3StorageProvider(self.ap)
|
||||
self.ap.logger.info('Initialized S3 storage backend.')
|
||||
else:
|
||||
|
||||
1
src/langbot/pkg/survey/__init__.py
Normal file
1
src/langbot/pkg/survey/__init__.py
Normal file
@@ -0,0 +1 @@
|
||||
"""Survey module for in-product surveys triggered by events."""
|
||||
148
src/langbot/pkg/survey/manager.py
Normal file
148
src/langbot/pkg/survey/manager.py
Normal file
@@ -0,0 +1,148 @@
|
||||
"""Survey manager: tracks events, communicates with Space to fetch/submit surveys."""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import asyncio
|
||||
import json
|
||||
import typing
|
||||
import httpx
|
||||
import sqlalchemy
|
||||
|
||||
from ..core import app as core_app
|
||||
from ..entity.persistence.metadata import Metadata
|
||||
from ..utils import constants
|
||||
|
||||
SURVEY_TRIGGERED_KEY = 'survey_triggered_events'
|
||||
|
||||
|
||||
class SurveyManager:
|
||||
"""Manages survey lifecycle: event tracking, pending survey fetch, submission."""
|
||||
|
||||
def __init__(self, ap: core_app.Application):
|
||||
self.ap = ap
|
||||
self._triggered_events: set[str] = set()
|
||||
self._pending_survey: typing.Optional[dict] = None
|
||||
self._space_url: str = ''
|
||||
|
||||
async def initialize(self):
|
||||
space_config = self.ap.instance_config.data.get('space', {})
|
||||
self._space_url = space_config.get('url', '').rstrip('/')
|
||||
await self._load_triggered_events()
|
||||
|
||||
async def _load_triggered_events(self):
|
||||
"""Load previously triggered events from metadata table."""
|
||||
try:
|
||||
result = await self.ap.persistence_mgr.execute_async(
|
||||
sqlalchemy.select(Metadata).where(Metadata.key == SURVEY_TRIGGERED_KEY)
|
||||
)
|
||||
row = result.first()
|
||||
if row:
|
||||
self._triggered_events = set(json.loads(row[0].value))
|
||||
except Exception:
|
||||
self._triggered_events = set()
|
||||
|
||||
async def _save_triggered_events(self):
|
||||
"""Persist triggered events to metadata table."""
|
||||
try:
|
||||
value = json.dumps(list(self._triggered_events))
|
||||
result = await self.ap.persistence_mgr.execute_async(
|
||||
sqlalchemy.select(Metadata).where(Metadata.key == SURVEY_TRIGGERED_KEY)
|
||||
)
|
||||
if result.first():
|
||||
await self.ap.persistence_mgr.execute_async(
|
||||
sqlalchemy.update(Metadata).where(Metadata.key == SURVEY_TRIGGERED_KEY).values(value=value)
|
||||
)
|
||||
else:
|
||||
await self.ap.persistence_mgr.execute_async(
|
||||
sqlalchemy.insert(Metadata).values(key=SURVEY_TRIGGERED_KEY, value=value)
|
||||
)
|
||||
except Exception as e:
|
||||
self.ap.logger.debug(f'Failed to save survey triggered events: {e}')
|
||||
|
||||
def _is_space_configured(self) -> bool:
|
||||
space_config = self.ap.instance_config.data.get('space', {})
|
||||
if space_config.get('disable_telemetry', False):
|
||||
return False
|
||||
return bool(self._space_url)
|
||||
|
||||
async def trigger_event(self, event: str):
|
||||
"""Called when an event occurs. Checks Space for a pending survey."""
|
||||
if event in self._triggered_events:
|
||||
return
|
||||
if not self._is_space_configured():
|
||||
return
|
||||
|
||||
self._triggered_events.add(event)
|
||||
await self._save_triggered_events()
|
||||
|
||||
# Check for pending survey asynchronously
|
||||
asyncio.create_task(self._fetch_pending_survey(event))
|
||||
|
||||
async def _fetch_pending_survey(self, event: str):
|
||||
"""Fetch pending survey from Space for this event."""
|
||||
try:
|
||||
url = f'{self._space_url}/api/v1/survey/pending'
|
||||
payload = {
|
||||
'instance_id': constants.instance_id,
|
||||
'event': event,
|
||||
}
|
||||
async with httpx.AsyncClient(timeout=httpx.Timeout(10)) as client:
|
||||
resp = await client.post(url, json=payload)
|
||||
if resp.status_code == 200:
|
||||
data = resp.json()
|
||||
if data.get('code') == 0 and data.get('data', {}).get('survey'):
|
||||
self._pending_survey = data['data']['survey']
|
||||
self.ap.logger.info(f'Survey pending: {self._pending_survey.get("survey_id")}')
|
||||
except Exception as e:
|
||||
self.ap.logger.debug(f'Failed to fetch pending survey: {e}')
|
||||
|
||||
def get_pending_survey(self) -> typing.Optional[dict]:
|
||||
"""Return the current pending survey (if any) for the frontend to display."""
|
||||
return self._pending_survey
|
||||
|
||||
def clear_pending_survey(self):
|
||||
"""Clear the pending survey (after user responds or dismisses)."""
|
||||
self._pending_survey = None
|
||||
|
||||
async def submit_response(self, survey_id: str, answers: dict, completed: bool = True) -> bool:
|
||||
"""Submit a survey response to Space."""
|
||||
if not self._is_space_configured():
|
||||
return False
|
||||
try:
|
||||
url = f'{self._space_url}/api/v1/survey/respond'
|
||||
payload = {
|
||||
'survey_id': survey_id,
|
||||
'instance_id': constants.instance_id,
|
||||
'answers': answers,
|
||||
'metadata': {
|
||||
'version': constants.semantic_version,
|
||||
},
|
||||
'completed': completed,
|
||||
}
|
||||
async with httpx.AsyncClient(timeout=httpx.Timeout(10)) as client:
|
||||
resp = await client.post(url, json=payload)
|
||||
if resp.status_code == 200:
|
||||
self.clear_pending_survey()
|
||||
return True
|
||||
except Exception as e:
|
||||
self.ap.logger.warning(f'Failed to submit survey response: {e}')
|
||||
return False
|
||||
|
||||
async def dismiss_survey(self, survey_id: str) -> bool:
|
||||
"""Dismiss a survey."""
|
||||
if not self._is_space_configured():
|
||||
return False
|
||||
try:
|
||||
url = f'{self._space_url}/api/v1/survey/dismiss'
|
||||
payload = {
|
||||
'survey_id': survey_id,
|
||||
'instance_id': constants.instance_id,
|
||||
}
|
||||
async with httpx.AsyncClient(timeout=httpx.Timeout(10)) as client:
|
||||
resp = await client.post(url, json=payload)
|
||||
if resp.status_code == 200:
|
||||
self.clear_pending_survey()
|
||||
return True
|
||||
except Exception as e:
|
||||
self.ap.logger.warning(f'Failed to dismiss survey: {e}')
|
||||
return False
|
||||
@@ -2,7 +2,7 @@ import langbot
|
||||
|
||||
semantic_version = f'v{langbot.__version__}'
|
||||
|
||||
required_database_version = 18
|
||||
required_database_version = 19
|
||||
"""Tag the version of the database schema, used to check if the database needs to be migrated"""
|
||||
|
||||
debug_mode = False
|
||||
|
||||
43
src/langbot/pkg/utils/httpclient.py
Normal file
43
src/langbot/pkg/utils/httpclient.py
Normal file
@@ -0,0 +1,43 @@
|
||||
"""Shared aiohttp.ClientSession to avoid repeated SSL context creation.
|
||||
|
||||
Each call to `aiohttp.ClientSession()` creates a new `TCPConnector` which in turn
|
||||
creates a new `ssl.SSLContext` and loads all system root certificates. This is
|
||||
extremely expensive in both CPU and memory (~270MB total allocations observed via
|
||||
memray profiling).
|
||||
|
||||
This module provides a shared session pool so that all HTTP client code in LangBot
|
||||
reuses the same underlying SSL context and connection pool.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import aiohttp
|
||||
|
||||
_sessions: dict[str, aiohttp.ClientSession] = {}
|
||||
|
||||
|
||||
def get_session(*, trust_env: bool = False) -> aiohttp.ClientSession:
|
||||
"""Get or create a shared aiohttp.ClientSession.
|
||||
|
||||
Args:
|
||||
trust_env: Whether to trust environment variables for proxy settings.
|
||||
|
||||
Returns:
|
||||
A shared aiohttp.ClientSession instance.
|
||||
"""
|
||||
key = f'trust_env={trust_env}'
|
||||
|
||||
session = _sessions.get(key)
|
||||
if session is None or session.closed:
|
||||
session = aiohttp.ClientSession(trust_env=trust_env)
|
||||
_sessions[key] = session
|
||||
|
||||
return session
|
||||
|
||||
|
||||
async def close_all():
|
||||
"""Close all shared sessions. Call on application shutdown."""
|
||||
for session in _sessions.values():
|
||||
if not session.closed:
|
||||
await session.close()
|
||||
_sessions.clear()
|
||||
@@ -5,6 +5,8 @@ from urllib.parse import urlparse, parse_qs
|
||||
import ssl
|
||||
|
||||
import aiohttp
|
||||
|
||||
from langbot.pkg.utils import httpclient
|
||||
import PIL.Image
|
||||
import httpx
|
||||
|
||||
@@ -47,53 +49,54 @@ async def get_gewechat_image_base64(
|
||||
)
|
||||
|
||||
try:
|
||||
async with aiohttp.ClientSession(timeout=timeout) as session:
|
||||
# 获取图片下载链接
|
||||
try:
|
||||
async with session.post(
|
||||
f'{gewechat_url}/v2/api/message/downloadImage',
|
||||
headers=headers,
|
||||
json={'appId': app_id, 'type': image_type, 'xml': xml_content},
|
||||
) as response:
|
||||
if response.status != 200:
|
||||
# print(response)
|
||||
raise Exception(f'获取gewechat图片下载失败: {await response.text()}')
|
||||
session = httpclient.get_session()
|
||||
# 获取图片下载链接
|
||||
try:
|
||||
async with session.post(
|
||||
f'{gewechat_url}/v2/api/message/downloadImage',
|
||||
headers=headers,
|
||||
json={'appId': app_id, 'type': image_type, 'xml': xml_content},
|
||||
timeout=timeout,
|
||||
) as response:
|
||||
if response.status != 200:
|
||||
# print(response)
|
||||
raise Exception(f'获取gewechat图片下载失败: {await response.text()}')
|
||||
|
||||
resp_data = await response.json()
|
||||
if resp_data.get('ret') != 200:
|
||||
raise Exception(f'获取gewechat图片下载链接失败: {resp_data}')
|
||||
resp_data = await response.json()
|
||||
if resp_data.get('ret') != 200:
|
||||
raise Exception(f'获取gewechat图片下载链接失败: {resp_data}')
|
||||
|
||||
file_url = resp_data['data']['fileUrl']
|
||||
except asyncio.TimeoutError:
|
||||
raise Exception('获取图片下载链接超时')
|
||||
except aiohttp.ClientError as e:
|
||||
raise Exception(f'获取图片下载链接网络错误: {str(e)}')
|
||||
file_url = resp_data['data']['fileUrl']
|
||||
except asyncio.TimeoutError:
|
||||
raise Exception('获取图片下载链接超时')
|
||||
except aiohttp.ClientError as e:
|
||||
raise Exception(f'获取图片下载链接网络错误: {str(e)}')
|
||||
|
||||
# 解析原始URL并替换端口
|
||||
base_url = gewechat_file_url
|
||||
download_url = f'{base_url}/download/{file_url}'
|
||||
# 解析原始URL并替换端口
|
||||
base_url = gewechat_file_url
|
||||
download_url = f'{base_url}/download/{file_url}'
|
||||
|
||||
# 下载图片
|
||||
try:
|
||||
async with session.get(download_url) as img_response:
|
||||
if img_response.status != 200:
|
||||
raise Exception(f'下载图片失败: {await img_response.text()}, URL: {download_url}')
|
||||
# 下载图片
|
||||
try:
|
||||
async with session.get(download_url) as img_response:
|
||||
if img_response.status != 200:
|
||||
raise Exception(f'下载图片失败: {await img_response.text()}, URL: {download_url}')
|
||||
|
||||
image_data = await img_response.read()
|
||||
image_data = await img_response.read()
|
||||
|
||||
content_type = img_response.headers.get('Content-Type', '')
|
||||
if content_type:
|
||||
image_format = content_type.split('/')[-1]
|
||||
else:
|
||||
image_format = file_url.split('.')[-1]
|
||||
content_type = img_response.headers.get('Content-Type', '')
|
||||
if content_type:
|
||||
image_format = content_type.split('/')[-1]
|
||||
else:
|
||||
image_format = file_url.split('.')[-1]
|
||||
|
||||
base64_str = base64.b64encode(image_data).decode('utf-8')
|
||||
base64_str = base64.b64encode(image_data).decode('utf-8')
|
||||
|
||||
return base64_str, image_format
|
||||
except asyncio.TimeoutError:
|
||||
raise Exception(f'下载图片超时, URL: {download_url}')
|
||||
except aiohttp.ClientError as e:
|
||||
raise Exception(f'下载图片网络错误: {str(e)}, URL: {download_url}')
|
||||
return base64_str, image_format
|
||||
except asyncio.TimeoutError:
|
||||
raise Exception(f'下载图片超时, URL: {download_url}')
|
||||
except aiohttp.ClientError as e:
|
||||
raise Exception(f'下载图片网络错误: {str(e)}, URL: {download_url}')
|
||||
except Exception as e:
|
||||
raise Exception(f'获取图片失败: {str(e)}') from e
|
||||
|
||||
@@ -104,24 +107,24 @@ async def get_wecom_image_base64(pic_url: str) -> tuple[str, str]:
|
||||
:param pic_url: 企业微信图片URL
|
||||
:return: (base64_str, image_format)
|
||||
"""
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.get(pic_url) as response:
|
||||
if response.status != 200:
|
||||
raise Exception(f'Failed to download image: {response.status}')
|
||||
session = httpclient.get_session()
|
||||
async with session.get(pic_url) as response:
|
||||
if response.status != 200:
|
||||
raise Exception(f'Failed to download image: {response.status}')
|
||||
|
||||
# 读取图片数据
|
||||
image_data = await response.read()
|
||||
# 读取图片数据
|
||||
image_data = await response.read()
|
||||
|
||||
# 获取图片格式
|
||||
content_type = response.headers.get('Content-Type', '')
|
||||
image_format = content_type.split('/')[-1] # 例如 'image/jpeg' -> 'jpeg'
|
||||
# 获取图片格式
|
||||
content_type = response.headers.get('Content-Type', '')
|
||||
image_format = content_type.split('/')[-1] # 例如 'image/jpeg' -> 'jpeg'
|
||||
|
||||
# 转换为 base64
|
||||
import base64
|
||||
# 转换为 base64
|
||||
import base64
|
||||
|
||||
image_base64 = base64.b64encode(image_data).decode('utf-8')
|
||||
image_base64 = base64.b64encode(image_data).decode('utf-8')
|
||||
|
||||
return image_base64, image_format
|
||||
return image_base64, image_format
|
||||
|
||||
|
||||
async def get_qq_official_image_base64(pic_url: str, content_type: str) -> tuple[str, str]:
|
||||
@@ -152,21 +155,19 @@ async def get_qq_image_bytes(image_url: str, query: dict = {}) -> tuple[bytes, s
|
||||
ssl_context = ssl.create_default_context()
|
||||
ssl_context.check_hostname = False
|
||||
ssl_context.verify_mode = ssl.CERT_NONE
|
||||
async with aiohttp.ClientSession(trust_env=False) as session:
|
||||
async with session.get(
|
||||
image_url, params=query, ssl=ssl_context, timeout=aiohttp.ClientTimeout(total=30.0)
|
||||
) as resp:
|
||||
resp.raise_for_status()
|
||||
file_bytes = await resp.read()
|
||||
content_type = resp.headers.get('Content-Type')
|
||||
if not content_type:
|
||||
image_format = 'jpeg'
|
||||
elif not content_type.startswith('image/'):
|
||||
pil_img = PIL.Image.open(io.BytesIO(file_bytes))
|
||||
image_format = pil_img.format.lower()
|
||||
else:
|
||||
image_format = content_type.split('/')[-1]
|
||||
return file_bytes, image_format
|
||||
session = httpclient.get_session()
|
||||
async with session.get(image_url, params=query, ssl=ssl_context, timeout=aiohttp.ClientTimeout(total=30.0)) as resp:
|
||||
resp.raise_for_status()
|
||||
file_bytes = await resp.read()
|
||||
content_type = resp.headers.get('Content-Type')
|
||||
if not content_type:
|
||||
image_format = 'jpeg'
|
||||
elif not content_type.startswith('image/'):
|
||||
pil_img = PIL.Image.open(io.BytesIO(file_bytes))
|
||||
image_format = pil_img.format.lower()
|
||||
else:
|
||||
image_format = content_type.split('/')[-1]
|
||||
return file_bytes, image_format
|
||||
|
||||
|
||||
async def qq_image_url_to_base64(image_url: str) -> typing.Tuple[str, str]:
|
||||
@@ -204,11 +205,11 @@ async def extract_b64_and_format(image_base64_data: str) -> typing.Tuple[str, st
|
||||
async def get_slack_image_to_base64(pic_url: str, bot_token: str):
|
||||
headers = {'Authorization': f'Bearer {bot_token}'}
|
||||
try:
|
||||
async with aiohttp.ClientSession() as session:
|
||||
async with session.get(pic_url, headers=headers) as resp:
|
||||
mime_type = resp.headers.get('Content-Type', 'application/octet-stream')
|
||||
file_bytes = await resp.read()
|
||||
base64_str = base64.b64encode(file_bytes).decode('utf-8')
|
||||
return f'data:{mime_type};base64,{base64_str}'
|
||||
session = httpclient.get_session()
|
||||
async with session.get(pic_url, headers=headers) as resp:
|
||||
mime_type = resp.headers.get('Content-Type', 'application/octet-stream')
|
||||
file_bytes = await resp.read()
|
||||
base64_str = base64.b64encode(file_bytes).decode('utf-8')
|
||||
return f'data:{mime_type};base64,{base64_str}'
|
||||
except Exception as e:
|
||||
raise (e)
|
||||
|
||||
@@ -15,8 +15,13 @@ proxy:
|
||||
http: ''
|
||||
https: ''
|
||||
system:
|
||||
edition: community
|
||||
recovery_key: ''
|
||||
allow_modify_login_info: true
|
||||
limitation:
|
||||
max_bots: -1
|
||||
max_pipelines: -1
|
||||
max_extensions: -1
|
||||
jwt:
|
||||
expire: 604800
|
||||
secret: ''
|
||||
|
||||
@@ -17,6 +17,10 @@
|
||||
"prefix": [],
|
||||
"regexp": []
|
||||
},
|
||||
"message-aggregation": {
|
||||
"enabled": false,
|
||||
"delay": 1.5
|
||||
},
|
||||
"misc": {
|
||||
"combine-quote-message": true
|
||||
}
|
||||
|
||||
@@ -123,6 +123,34 @@ stages:
|
||||
type: array[string]
|
||||
required: true
|
||||
default: []
|
||||
- name: message-aggregation
|
||||
label:
|
||||
en_US: Message Aggregation
|
||||
zh_Hans: 消息聚合
|
||||
description:
|
||||
en_US: When a user sends multiple messages consecutively, wait for a period and merge them into one before processing
|
||||
zh_Hans: 当用户连续发送多条消息时，等待一段时间后合并为一条消息再处理（防抖）
|
||||
config:
|
||||
- name: enabled
|
||||
label:
|
||||
en_US: Enable Message Aggregation
|
||||
zh_Hans: 启用消息聚合
|
||||
description:
|
||||
en_US: If enabled, consecutive messages from the same user will be merged after a delay
|
||||
zh_Hans: 如果启用，同一用户连续发送的消息将在延迟后合并处理
|
||||
type: boolean
|
||||
required: true
|
||||
default: false
|
||||
- name: delay
|
||||
label:
|
||||
en_US: Aggregation Delay (seconds)
|
||||
zh_Hans: 聚合延迟（秒）
|
||||
description:
|
||||
en_US: 'Wait time before merging messages. Range: 1.0-10.0 seconds.'
|
||||
zh_Hans: '合并消息前的等待时间。范围：1.0-10.0 秒。'
|
||||
type: float
|
||||
required: true
|
||||
default: 1.5
|
||||
- name: misc
|
||||
label:
|
||||
en_US: Misc
|
||||
|
||||
@@ -15,7 +15,6 @@ const config = {
|
||||
singleQuote: true,
|
||||
// 大括号前后空格
|
||||
bracketSpacing: true,
|
||||
attributeVerticalAlignment: 'auto',
|
||||
trailingComma: 'all',
|
||||
};
|
||||
|
||||
|
||||
11240
web/package-lock.json
generated
Normal file
11240
web/package-lock.json
generated
Normal file
File diff suppressed because it is too large
Load Diff
@@ -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",
|
||||
@@ -68,6 +68,7 @@
|
||||
"rehype-autolink-headings": "^7.1.0",
|
||||
"rehype-highlight": "^7.0.2",
|
||||
"rehype-raw": "^7.0.0",
|
||||
"rehype-sanitize": "^6.0.0",
|
||||
"rehype-slug": "^6.0.0",
|
||||
"remark-gfm": "^4.0.1",
|
||||
"sonner": "^2.0.3",
|
||||
|
||||
1339
web/pnpm-lock.yaml
generated
1339
web/pnpm-lock.yaml
generated
File diff suppressed because it is too large
Load Diff
@@ -5,6 +5,7 @@ import {
|
||||
Dialog,
|
||||
DialogContent,
|
||||
DialogHeader,
|
||||
DialogDescription,
|
||||
DialogTitle,
|
||||
DialogFooter,
|
||||
} from '@/components/ui/dialog';
|
||||
@@ -21,6 +22,7 @@ import {
|
||||
import { Button } from '@/components/ui/button';
|
||||
import BotForm from '@/app/home/bots/components/bot-form/BotForm';
|
||||
import { BotLogListComponent } from '@/app/home/bots/components/bot-log/view/BotLogListComponent';
|
||||
import BotSessionMonitor from '@/app/home/bots/components/bot-session/BotSessionMonitor';
|
||||
import { useTranslation } from 'react-i18next';
|
||||
import { z } from 'zod';
|
||||
import { httpClient } from '@/app/infra/http/HttpClient';
|
||||
@@ -82,6 +84,19 @@ export default function BotDetailDialog({
|
||||
</svg>
|
||||
),
|
||||
},
|
||||
{
|
||||
key: 'sessions',
|
||||
label: t('bots.sessionMonitor.title'),
|
||||
icon: (
|
||||
<svg
|
||||
xmlns="http://www.w3.org/2000/svg"
|
||||
viewBox="0 0 24 24"
|
||||
fill="currentColor"
|
||||
>
|
||||
<path d="M2 22C2 17.5817 5.58172 14 10 14C14.4183 14 18 17.5817 18 22H16C16 18.6863 13.3137 16 10 16C6.68629 16 4 18.6863 4 22H2ZM10 13C6.685 13 4 10.315 4 7C4 3.685 6.685 1 10 1C13.315 1 16 3.685 16 7C16 10.315 13.315 13 10 13ZM10 11C12.21 11 14 9.21 14 7C14 4.79 12.21 3 10 3C7.79 3 6 4.79 6 7C6 9.21 7.79 11 10 11ZM18.2837 14.7028C21.0644 15.9561 23 18.752 23 22H21C21 19.564 19.5483 17.4671 17.4628 16.5271L18.2837 14.7028ZM17.5962 3.41321C19.5944 4.23703 21 6.20361 21 8.5C21 11.3702 18.8042 13.7252 16 13.9776V11.9646C17.6967 11.7222 19 10.264 19 8.5C19 7.11935 18.2016 5.92603 17.041 5.35635L17.5962 3.41321Z"></path>
|
||||
</svg>
|
||||
),
|
||||
},
|
||||
];
|
||||
|
||||
// eslint-disable-next-line @typescript-eslint/no-explicit-any
|
||||
@@ -122,6 +137,9 @@ export default function BotDetailDialog({
|
||||
<main className="flex flex-1 flex-col h-[70vh]">
|
||||
<DialogHeader className="px-6 pt-6 pb-4 shrink-0">
|
||||
<DialogTitle>{t('bots.createBot')}</DialogTitle>
|
||||
<DialogDescription className="sr-only">
|
||||
{t('bots.createBot')}
|
||||
</DialogDescription>
|
||||
</DialogHeader>
|
||||
<div className="flex-1 overflow-y-auto px-6 pb-6">
|
||||
<BotForm
|
||||
@@ -155,7 +173,7 @@ export default function BotDetailDialog({
|
||||
return (
|
||||
<>
|
||||
<Dialog open={open} onOpenChange={onOpenChange}>
|
||||
<DialogContent className="overflow-hidden p-0 !max-w-[50rem] max-h-[75vh] flex">
|
||||
<DialogContent className="overflow-hidden p-0 !max-w-[70rem] max-h-[75vh] flex">
|
||||
<SidebarProvider className="items-start w-full flex">
|
||||
<Sidebar
|
||||
collapsible="none"
|
||||
@@ -189,10 +207,25 @@ export default function BotDetailDialog({
|
||||
<DialogTitle>
|
||||
{activeMenu === 'config'
|
||||
? t('bots.editBot')
|
||||
: t('bots.botLogTitle')}
|
||||
: activeMenu === 'logs'
|
||||
? t('bots.botLogTitle')
|
||||
: t('bots.sessionMonitor.title')}
|
||||
</DialogTitle>
|
||||
<DialogDescription className="sr-only">
|
||||
{activeMenu === 'config'
|
||||
? t('bots.editBot')
|
||||
: activeMenu === 'logs'
|
||||
? t('bots.botLogTitle')
|
||||
: t('bots.sessionMonitor.title')}
|
||||
</DialogDescription>
|
||||
</DialogHeader>
|
||||
<div className="flex-1 overflow-y-auto px-6 pb-6">
|
||||
<div
|
||||
className={
|
||||
activeMenu === 'sessions'
|
||||
? 'flex-1 min-h-0'
|
||||
: 'flex-1 overflow-y-auto px-6 pb-6'
|
||||
}
|
||||
>
|
||||
{activeMenu === 'config' && (
|
||||
<BotForm
|
||||
initBotId={botId}
|
||||
@@ -204,6 +237,9 @@ export default function BotDetailDialog({
|
||||
{activeMenu === 'logs' && botId && (
|
||||
<BotLogListComponent botId={botId} />
|
||||
)}
|
||||
{activeMenu === 'sessions' && botId && (
|
||||
<BotSessionMonitor botId={botId} />
|
||||
)}
|
||||
</div>
|
||||
{activeMenu === 'config' && (
|
||||
<DialogFooter className="px-6 py-4 border-t shrink-0">
|
||||
@@ -238,6 +274,9 @@ export default function BotDetailDialog({
|
||||
<DialogContent>
|
||||
<DialogHeader>
|
||||
<DialogTitle>{t('common.confirmDelete')}</DialogTitle>
|
||||
<DialogDescription className="sr-only">
|
||||
{t('bots.deleteConfirmation')}
|
||||
</DialogDescription>
|
||||
</DialogHeader>
|
||||
<div className="py-4">{t('bots.deleteConfirmation')}</div>
|
||||
<DialogFooter>
|
||||
|
||||
@@ -124,6 +124,12 @@ export default function BotForm({
|
||||
const currentAdapter = form.watch('adapter');
|
||||
const currentAdapterConfig = form.watch('adapter_config');
|
||||
|
||||
// Serialize adapter_config to a stable string so it can be used as a
|
||||
// useEffect dependency without triggering on every render. form.watch()
|
||||
// returns a new object reference each time, which would otherwise cause
|
||||
// the filtering effect below to loop indefinitely.
|
||||
const adapterConfigJson = JSON.stringify(currentAdapterConfig);
|
||||
|
||||
useEffect(() => {
|
||||
setBotFormValues();
|
||||
}, []);
|
||||
@@ -147,7 +153,7 @@ export default function BotForm({
|
||||
// For non-Lark adapters, show all fields
|
||||
setFilteredDynamicFormConfigList(dynamicFormConfigList);
|
||||
}
|
||||
}, [currentAdapter, currentAdapterConfig, dynamicFormConfigList]);
|
||||
}, [currentAdapter, adapterConfigJson, dynamicFormConfigList]);
|
||||
|
||||
// 复制到剪贴板的辅助函数 - 使用页面上的真实input元素
|
||||
const copyToClipboard = () => {
|
||||
|
||||
@@ -0,0 +1,502 @@
|
||||
'use client';
|
||||
|
||||
import React, { useState, useEffect, useRef, useCallback } from 'react';
|
||||
import { useTranslation } from 'react-i18next';
|
||||
import { httpClient } from '@/app/infra/http/HttpClient';
|
||||
import { ScrollArea } from '@/components/ui/scroll-area';
|
||||
import { Button } from '@/components/ui/button';
|
||||
import { cn } from '@/lib/utils';
|
||||
import {
|
||||
MessageChainComponent,
|
||||
Plain,
|
||||
At,
|
||||
Image,
|
||||
Quote,
|
||||
Voice,
|
||||
} from '@/app/infra/entities/message';
|
||||
|
||||
interface SessionInfo {
|
||||
session_id: string;
|
||||
bot_id: string;
|
||||
bot_name: string;
|
||||
pipeline_id: string;
|
||||
pipeline_name: string;
|
||||
message_count: number;
|
||||
start_time: string;
|
||||
last_activity: string;
|
||||
is_active: boolean;
|
||||
platform?: string | null;
|
||||
user_id?: string | null;
|
||||
}
|
||||
|
||||
interface SessionMessage {
|
||||
id: string;
|
||||
timestamp: string;
|
||||
bot_id: string;
|
||||
bot_name: string;
|
||||
pipeline_id: string;
|
||||
pipeline_name: string;
|
||||
message_content: string;
|
||||
session_id: string;
|
||||
status: string;
|
||||
level: string;
|
||||
platform?: string | null;
|
||||
user_id?: string | null;
|
||||
runner_name?: string | null;
|
||||
variables?: string | null;
|
||||
role?: string | null;
|
||||
}
|
||||
|
||||
interface BotSessionMonitorProps {
|
||||
botId: string;
|
||||
}
|
||||
|
||||
export default function BotSessionMonitor({ botId }: BotSessionMonitorProps) {
|
||||
const { t } = useTranslation();
|
||||
const [sessions, setSessions] = useState<SessionInfo[]>([]);
|
||||
const [selectedSessionId, setSelectedSessionId] = useState<string | null>(
|
||||
null,
|
||||
);
|
||||
const [messages, setMessages] = useState<SessionMessage[]>([]);
|
||||
const [loadingSessions, setLoadingSessions] = useState(false);
|
||||
const [loadingMessages, setLoadingMessages] = useState(false);
|
||||
const messagesContainerRef = useRef<HTMLDivElement>(null);
|
||||
|
||||
const loadSessions = useCallback(async () => {
|
||||
setLoadingSessions(true);
|
||||
try {
|
||||
const response = await httpClient.getBotSessions(botId);
|
||||
setSessions(response.sessions ?? []);
|
||||
} catch (error) {
|
||||
console.error('Failed to load sessions:', error);
|
||||
} finally {
|
||||
setLoadingSessions(false);
|
||||
}
|
||||
}, [botId]);
|
||||
|
||||
const loadMessages = useCallback(async (sessionId: string) => {
|
||||
setLoadingMessages(true);
|
||||
try {
|
||||
const response = await httpClient.getSessionMessages(sessionId);
|
||||
const sorted = (response.messages ?? []).sort(
|
||||
(a, b) =>
|
||||
new Date(a.timestamp).getTime() - new Date(b.timestamp).getTime(),
|
||||
);
|
||||
setMessages(sorted);
|
||||
} catch (error) {
|
||||
console.error('Failed to load session messages:', error);
|
||||
} finally {
|
||||
setLoadingMessages(false);
|
||||
}
|
||||
}, []);
|
||||
|
||||
useEffect(() => {
|
||||
loadSessions();
|
||||
}, [loadSessions]);
|
||||
|
||||
useEffect(() => {
|
||||
if (selectedSessionId) {
|
||||
loadMessages(selectedSessionId);
|
||||
} else {
|
||||
setMessages([]);
|
||||
}
|
||||
}, [selectedSessionId, loadMessages]);
|
||||
|
||||
useEffect(() => {
|
||||
const container = messagesContainerRef.current;
|
||||
if (container) {
|
||||
const viewport = container.querySelector(
|
||||
'[data-radix-scroll-area-viewport]',
|
||||
);
|
||||
const scrollTarget = viewport || container;
|
||||
scrollTarget.scrollTop = scrollTarget.scrollHeight;
|
||||
}
|
||||
}, [messages]);
|
||||
|
||||
const parseMessageChain = (content: string): MessageChainComponent[] => {
|
||||
try {
|
||||
const parsed = JSON.parse(content);
|
||||
if (Array.isArray(parsed)) {
|
||||
return parsed as MessageChainComponent[];
|
||||
}
|
||||
} catch {
|
||||
// Not JSON, return as plain text
|
||||
}
|
||||
return [{ type: 'Plain', text: content } as Plain];
|
||||
};
|
||||
|
||||
const isUserMessage = (msg: SessionMessage): boolean => {
|
||||
if (msg.role === 'assistant') return false;
|
||||
if (msg.role === 'user') return true;
|
||||
return !msg.runner_name;
|
||||
};
|
||||
|
||||
const renderMessageComponent = (
|
||||
component: MessageChainComponent,
|
||||
index: number,
|
||||
) => {
|
||||
switch (component.type) {
|
||||
case 'Plain':
|
||||
return <span key={index}>{(component as Plain).text}</span>;
|
||||
|
||||
case 'At': {
|
||||
const atComponent = component as At;
|
||||
const displayName =
|
||||
atComponent.display || atComponent.target?.toString() || '';
|
||||
return (
|
||||
<span
|
||||
key={index}
|
||||
className="inline-flex align-middle mx-0.5 px-1.5 py-0.5 bg-blue-200/60 dark:bg-blue-800/60 text-blue-700 dark:text-blue-300 rounded-md text-xs font-medium"
|
||||
>
|
||||
@{displayName}
|
||||
</span>
|
||||
);
|
||||
}
|
||||
|
||||
case 'AtAll':
|
||||
return (
|
||||
<span
|
||||
key={index}
|
||||
className="inline-flex align-middle mx-0.5 px-1.5 py-0.5 bg-blue-200/60 dark:bg-blue-800/60 text-blue-700 dark:text-blue-300 rounded-md text-xs font-medium"
|
||||
>
|
||||
@All
|
||||
</span>
|
||||
);
|
||||
|
||||
case 'Image': {
|
||||
const img = component as Image;
|
||||
const imageUrl = img.url || (img.base64 ? img.base64 : '');
|
||||
if (!imageUrl) {
|
||||
return (
|
||||
<span
|
||||
key={index}
|
||||
className="inline-flex items-center gap-1 text-muted-foreground text-xs"
|
||||
>
|
||||
[Image]
|
||||
</span>
|
||||
);
|
||||
}
|
||||
return (
|
||||
<div key={index} className="my-1.5">
|
||||
<img
|
||||
src={imageUrl}
|
||||
alt="Image"
|
||||
className="max-w-full max-h-52 rounded-lg"
|
||||
/>
|
||||
</div>
|
||||
);
|
||||
}
|
||||
|
||||
case 'Voice': {
|
||||
const voice = component as Voice;
|
||||
const voiceUrl = voice.url || (voice.base64 ? voice.base64 : '');
|
||||
if (!voiceUrl) {
|
||||
return (
|
||||
<span
|
||||
key={index}
|
||||
className="inline-flex items-center gap-1 text-muted-foreground text-xs"
|
||||
>
|
||||
🎙 [Voice]
|
||||
</span>
|
||||
);
|
||||
}
|
||||
return (
|
||||
<div key={index} className="my-1">
|
||||
<audio controls src={voiceUrl} className="h-8 max-w-[220px]" />
|
||||
</div>
|
||||
);
|
||||
}
|
||||
|
||||
case 'Quote': {
|
||||
const quote = component as Quote;
|
||||
return (
|
||||
<div
|
||||
key={index}
|
||||
className="mb-2 pl-2.5 border-l-2 border-gray-300 dark:border-gray-600 opacity-80"
|
||||
>
|
||||
<div className="text-sm">
|
||||
{quote.origin?.map((comp, idx) =>
|
||||
renderMessageComponent(comp as MessageChainComponent, idx),
|
||||
)}
|
||||
</div>
|
||||
</div>
|
||||
);
|
||||
}
|
||||
|
||||
case 'Source':
|
||||
return null;
|
||||
|
||||
case 'File': {
|
||||
const file = component as MessageChainComponent & { name?: string };
|
||||
return (
|
||||
<span key={index} className="text-muted-foreground text-xs">
|
||||
📎 {file.name || 'File'}
|
||||
</span>
|
||||
);
|
||||
}
|
||||
|
||||
default:
|
||||
return (
|
||||
<span key={index} className="text-muted-foreground text-xs">
|
||||
[{component.type}]
|
||||
</span>
|
||||
);
|
||||
}
|
||||
};
|
||||
|
||||
const renderMessageContent = (msg: SessionMessage) => {
|
||||
const chain = parseMessageChain(msg.message_content);
|
||||
return (
|
||||
<div className="whitespace-pre-wrap break-words">
|
||||
{chain.map((component, index) =>
|
||||
renderMessageComponent(component, index),
|
||||
)}
|
||||
</div>
|
||||
);
|
||||
};
|
||||
|
||||
const formatTime = (timestamp: string): string => {
|
||||
if (!timestamp) return '';
|
||||
const date = new Date(timestamp);
|
||||
const hours = date.getHours().toString().padStart(2, '0');
|
||||
const minutes = date.getMinutes().toString().padStart(2, '0');
|
||||
return `${hours}:${minutes}`;
|
||||
};
|
||||
|
||||
const formatRelativeTime = (timestamp: string): string => {
|
||||
if (!timestamp) return '';
|
||||
const date = new Date(timestamp);
|
||||
const now = new Date();
|
||||
const diffMs = now.getTime() - date.getTime();
|
||||
const diffMins = Math.floor(diffMs / 60000);
|
||||
const diffHours = Math.floor(diffMs / 3600000);
|
||||
const diffDays = Math.floor(diffMs / 86400000);
|
||||
|
||||
if (diffMins < 1) return '<1m';
|
||||
if (diffMins < 60) return `${diffMins}m`;
|
||||
if (diffHours < 24) return `${diffHours}h`;
|
||||
return `${diffDays}d`;
|
||||
};
|
||||
|
||||
const selectedSession = sessions.find(
|
||||
(s) => s.session_id === selectedSessionId,
|
||||
);
|
||||
|
||||
return (
|
||||
<div className="flex h-full min-h-0">
|
||||
{/* Left Panel: Session List */}
|
||||
<div className="w-64 flex-shrink-0 border-r flex flex-col min-h-0">
|
||||
{/* Refresh Button */}
|
||||
<div className="px-2 py-2 border-b shrink-0">
|
||||
<Button
|
||||
variant="ghost"
|
||||
className="w-full h-9 text-sm text-muted-foreground"
|
||||
onClick={loadSessions}
|
||||
disabled={loadingSessions}
|
||||
>
|
||||
<svg
|
||||
xmlns="http://www.w3.org/2000/svg"
|
||||
viewBox="0 0 24 24"
|
||||
fill="none"
|
||||
stroke="currentColor"
|
||||
strokeWidth={2}
|
||||
strokeLinecap="round"
|
||||
strokeLinejoin="round"
|
||||
className={cn(
|
||||
'w-3.5 h-3.5 mr-1.5',
|
||||
loadingSessions && 'animate-spin',
|
||||
)}
|
||||
>
|
||||
<path d="M21.5 2v6h-6M2.5 22v-6h6M2 11.5a10 10 0 0 1 18.8-4.3M22 12.5a10 10 0 0 1-18.8 4.2" />
|
||||
</svg>
|
||||
{t('bots.sessionMonitor.refresh')}
|
||||
</Button>
|
||||
</div>
|
||||
|
||||
{/* Session List */}
|
||||
<ScrollArea className="flex-1 min-h-0">
|
||||
{loadingSessions && sessions.length === 0 ? (
|
||||
<div className="flex items-center justify-center py-12 text-sm text-muted-foreground">
|
||||
{t('bots.sessionMonitor.loading')}
|
||||
</div>
|
||||
) : sessions.length === 0 ? (
|
||||
<div className="text-center text-muted-foreground py-12 text-sm">
|
||||
{t('bots.sessionMonitor.noSessions')}
|
||||
</div>
|
||||
) : (
|
||||
<div className="p-1">
|
||||
{sessions.map((session) => {
|
||||
const isSelected = selectedSessionId === session.session_id;
|
||||
return (
|
||||
<button
|
||||
key={session.session_id}
|
||||
className={cn(
|
||||
'w-full text-left px-3 py-2.5 rounded-md transition-colors',
|
||||
isSelected ? 'bg-accent' : 'hover:bg-accent/50',
|
||||
)}
|
||||
onClick={() => setSelectedSessionId(session.session_id)}
|
||||
>
|
||||
<div className="flex items-center justify-between mb-0.5">
|
||||
<span className="text-sm font-medium truncate mr-2">
|
||||
{session.user_id || session.session_id.slice(0, 12)}
|
||||
</span>
|
||||
<span className="text-[11px] text-muted-foreground tabular-nums flex-shrink-0">
|
||||
{formatRelativeTime(session.last_activity)}
|
||||
</span>
|
||||
</div>
|
||||
<div className="flex items-center gap-1.5 text-xs text-muted-foreground">
|
||||
{session.platform && (
|
||||
<span className="px-1 py-0.5 rounded bg-muted text-[10px]">
|
||||
{session.platform}
|
||||
</span>
|
||||
)}
|
||||
{session.is_active && (
|
||||
<span className="flex items-center gap-0.5 text-green-600 dark:text-green-400">
|
||||
<span className="w-1.5 h-1.5 rounded-full bg-green-500 inline-block" />
|
||||
</span>
|
||||
)}
|
||||
<span>{session.pipeline_name}</span>
|
||||
</div>
|
||||
</button>
|
||||
);
|
||||
})}
|
||||
</div>
|
||||
)}
|
||||
</ScrollArea>
|
||||
</div>
|
||||
|
||||
{/* Right Panel: Messages */}
|
||||
<div className="flex-1 flex flex-col min-h-0 min-w-0">
|
||||
{!selectedSessionId ? (
|
||||
<div className="text-center text-muted-foreground py-12 text-lg flex-1 flex items-center justify-center">
|
||||
{t('bots.sessionMonitor.selectSession')}
|
||||
</div>
|
||||
) : (
|
||||
<>
|
||||
{/* Chat Header */}
|
||||
<div className="px-6 py-3 border-b shrink-0 flex items-center justify-between">
|
||||
<div className="min-w-0">
|
||||
<div className="text-sm font-medium truncate">
|
||||
{selectedSession?.user_id || selectedSessionId.slice(0, 20)}
|
||||
</div>
|
||||
<div className="flex items-center gap-2 text-xs text-muted-foreground">
|
||||
{selectedSession?.platform && (
|
||||
<span>{selectedSession.platform}</span>
|
||||
)}
|
||||
{selectedSession?.pipeline_name && (
|
||||
<>
|
||||
{selectedSession?.platform && <span>·</span>}
|
||||
<span>{selectedSession.pipeline_name}</span>
|
||||
</>
|
||||
)}
|
||||
{selectedSession?.is_active && (
|
||||
<>
|
||||
<span>·</span>
|
||||
<span className="flex items-center gap-1 text-green-600 dark:text-green-400">
|
||||
<span className="w-1.5 h-1.5 rounded-full bg-green-500 inline-block" />
|
||||
Active
|
||||
</span>
|
||||
</>
|
||||
)}
|
||||
</div>
|
||||
</div>
|
||||
<Button
|
||||
variant="ghost"
|
||||
size="icon"
|
||||
className="w-8 h-8"
|
||||
onClick={() => loadMessages(selectedSessionId)}
|
||||
disabled={loadingMessages}
|
||||
>
|
||||
<svg
|
||||
xmlns="http://www.w3.org/2000/svg"
|
||||
viewBox="0 0 24 24"
|
||||
fill="none"
|
||||
stroke="currentColor"
|
||||
strokeWidth={2}
|
||||
strokeLinecap="round"
|
||||
strokeLinejoin="round"
|
||||
className={cn('w-4 h-4', loadingMessages && 'animate-spin')}
|
||||
>
|
||||
<path d="M21.5 2v6h-6M2.5 22v-6h6M2 11.5a10 10 0 0 1 18.8-4.3M22 12.5a10 10 0 0 1-18.8 4.2" />
|
||||
</svg>
|
||||
</Button>
|
||||
</div>
|
||||
|
||||
{/* Messages Area — matches DebugDialog style */}
|
||||
<ScrollArea
|
||||
ref={messagesContainerRef}
|
||||
className="flex-1 p-6 overflow-y-auto min-h-0 bg-white dark:bg-black"
|
||||
>
|
||||
<div className="space-y-6">
|
||||
{loadingMessages ? (
|
||||
<div className="text-center text-muted-foreground py-12 text-lg">
|
||||
{t('bots.sessionMonitor.loading')}
|
||||
</div>
|
||||
) : messages.length === 0 ? (
|
||||
<div className="text-center text-muted-foreground py-12 text-lg">
|
||||
{t('bots.sessionMonitor.noMessages')}
|
||||
</div>
|
||||
) : (
|
||||
messages.map((msg) => {
|
||||
const isUser = isUserMessage(msg);
|
||||
return (
|
||||
<div
|
||||
key={msg.id}
|
||||
className={cn(
|
||||
'flex',
|
||||
isUser ? 'justify-end' : 'justify-start',
|
||||
)}
|
||||
>
|
||||
<div
|
||||
className={cn(
|
||||
'max-w-3xl px-5 py-3 rounded-2xl',
|
||||
isUser
|
||||
? 'bg-blue-100 dark:bg-blue-900 text-gray-900 dark:text-gray-100 rounded-br-none'
|
||||
: 'bg-gray-100 dark:bg-gray-800 text-gray-900 dark:text-gray-100 rounded-bl-none',
|
||||
msg.status === 'error' && 'ring-1 ring-red-400/50',
|
||||
)}
|
||||
>
|
||||
{renderMessageContent(msg)}
|
||||
{/* Role label + timestamp inside bubble, matching DebugDialog */}
|
||||
<div
|
||||
className={cn(
|
||||
'text-xs mt-2 flex items-center gap-2',
|
||||
isUser
|
||||
? 'text-gray-600 dark:text-gray-300'
|
||||
: 'text-gray-500 dark:text-gray-400',
|
||||
)}
|
||||
>
|
||||
<span>
|
||||
{isUser
|
||||
? t('bots.sessionMonitor.userMessage', {
|
||||
defaultValue: 'User',
|
||||
})
|
||||
: t('bots.sessionMonitor.botMessage', {
|
||||
defaultValue: 'Assistant',
|
||||
})}
|
||||
</span>
|
||||
<span className="tabular-nums">
|
||||
{formatTime(msg.timestamp)}
|
||||
</span>
|
||||
{msg.status === 'error' && (
|
||||
<span className="text-red-500">error</span>
|
||||
)}
|
||||
{msg.runner_name && (
|
||||
<span className="opacity-70">
|
||||
{msg.runner_name}
|
||||
</span>
|
||||
)}
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
);
|
||||
})
|
||||
)}
|
||||
</div>
|
||||
</ScrollArea>
|
||||
</>
|
||||
)}
|
||||
</div>
|
||||
</div>
|
||||
);
|
||||
}
|
||||
@@ -12,6 +12,7 @@ import { useTranslation } from 'react-i18next';
|
||||
import { extractI18nObject } from '@/i18n/I18nProvider';
|
||||
import BotDetailDialog from '@/app/home/bots/BotDetailDialog';
|
||||
import { CustomApiError } from '@/app/infra/entities/common';
|
||||
import { systemInfo } from '@/app/infra/http';
|
||||
|
||||
export default function BotConfigPage() {
|
||||
const { t } = useTranslation();
|
||||
@@ -60,6 +61,11 @@ export default function BotConfigPage() {
|
||||
}
|
||||
|
||||
function handleCreateBotClick() {
|
||||
const maxBots = systemInfo.limitation?.max_bots ?? -1;
|
||||
if (maxBots >= 0 && botList.length >= maxBots) {
|
||||
toast.error(t('limitation.maxBotsReached', { max: maxBots }));
|
||||
return;
|
||||
}
|
||||
setSelectedBotId('');
|
||||
setDetailDialogOpen(true);
|
||||
}
|
||||
|
||||
@@ -11,7 +11,7 @@ import {
|
||||
FormMessage,
|
||||
} from '@/components/ui/form';
|
||||
import DynamicFormItemComponent from '@/app/home/components/dynamic-form/DynamicFormItemComponent';
|
||||
import { useEffect, useRef } from 'react';
|
||||
import { useCallback, useEffect, useRef } from 'react';
|
||||
import { extractI18nObject } from '@/i18n/I18nProvider';
|
||||
|
||||
export default function DynamicFormComponent({
|
||||
@@ -141,22 +141,44 @@ export default function DynamicFormComponent({
|
||||
}
|
||||
}, [initialValues, form, itemConfigList]);
|
||||
|
||||
// Stable ref for onSubmit to avoid re-triggering the effect when the
|
||||
// parent passes a new closure on every render.
|
||||
const onSubmitRef = useRef(onSubmit);
|
||||
onSubmitRef.current = onSubmit;
|
||||
|
||||
// Track the last emitted values to avoid emitting identical snapshots,
|
||||
// which would cause the parent to call setValue with an equivalent object,
|
||||
// triggering a re-render loop.
|
||||
const lastEmittedRef = useRef<string>('');
|
||||
|
||||
const emitValues = useCallback(() => {
|
||||
const formValues = form.getValues();
|
||||
const finalValues = itemConfigList.reduce(
|
||||
(acc, item) => {
|
||||
acc[item.name] = formValues[item.name] ?? item.default;
|
||||
return acc;
|
||||
},
|
||||
{} as Record<string, object>,
|
||||
);
|
||||
const serialized = JSON.stringify(finalValues);
|
||||
if (serialized !== lastEmittedRef.current) {
|
||||
lastEmittedRef.current = serialized;
|
||||
onSubmitRef.current?.(finalValues);
|
||||
}
|
||||
}, [form, itemConfigList]);
|
||||
|
||||
// 监听表单值变化
|
||||
useEffect(() => {
|
||||
// Emit initial form values immediately so the parent always has a valid snapshot,
|
||||
// even if the user saves without modifying any field.
|
||||
// form.watch(callback) only fires on subsequent changes, not on mount.
|
||||
emitValues();
|
||||
|
||||
const subscription = form.watch(() => {
|
||||
// 获取完整的表单值，确保包含所有默认值
|
||||
const formValues = form.getValues();
|
||||
const finalValues = itemConfigList.reduce(
|
||||
(acc, item) => {
|
||||
acc[item.name] = formValues[item.name] ?? item.default;
|
||||
return acc;
|
||||
},
|
||||
{} as Record<string, object>,
|
||||
);
|
||||
onSubmit?.(finalValues);
|
||||
emitValues();
|
||||
});
|
||||
return () => subscription.unsubscribe();
|
||||
}, [form, onSubmit, itemConfigList]);
|
||||
}, [form, itemConfigList, emitValues]);
|
||||
|
||||
return (
|
||||
<Form {...form}>
|
||||
|
||||
@@ -191,7 +191,12 @@ export default function DynamicFormItemComponent({
|
||||
return <Textarea {...field} className="min-h-[120px]" />;
|
||||
|
||||
case DynamicFormItemType.BOOLEAN:
|
||||
return <Switch checked={field.value} onCheckedChange={field.onChange} />;
|
||||
return (
|
||||
<Switch
|
||||
checked={field.value ?? false}
|
||||
onCheckedChange={field.onChange}
|
||||
/>
|
||||
);
|
||||
|
||||
case DynamicFormItemType.STRING_ARRAY:
|
||||
return (
|
||||
@@ -242,7 +247,7 @@ export default function DynamicFormItemComponent({
|
||||
|
||||
case DynamicFormItemType.SELECT:
|
||||
return (
|
||||
<Select value={field.value} onValueChange={field.onChange}>
|
||||
<Select value={field.value ?? ''} onValueChange={field.onChange}>
|
||||
<SelectTrigger className="bg-[#ffffff] dark:bg-[#2a2a2e]">
|
||||
<SelectValue placeholder={t('common.select')} />
|
||||
</SelectTrigger>
|
||||
|
||||
@@ -4,6 +4,7 @@ import { useTranslation } from 'react-i18next';
|
||||
import ReactMarkdown from 'react-markdown';
|
||||
import remarkGfm from 'remark-gfm';
|
||||
import rehypeRaw from 'rehype-raw';
|
||||
import rehypeSanitize from 'rehype-sanitize';
|
||||
import rehypeHighlight from 'rehype-highlight';
|
||||
import i18n from 'i18next';
|
||||
import { ExternalLink } from 'lucide-react';
|
||||
@@ -62,7 +63,7 @@ export default function NewVersionDialog({
|
||||
<div className="markdown-body max-w-none text-sm">
|
||||
<ReactMarkdown
|
||||
remarkPlugins={[remarkGfm]}
|
||||
rehypePlugins={[rehypeRaw, rehypeHighlight]}
|
||||
rehypePlugins={[rehypeRaw, rehypeSanitize, rehypeHighlight]}
|
||||
components={{
|
||||
ul: ({ children }) => <ul className="list-disc">{children}</ul>,
|
||||
ol: ({ children }) => (
|
||||
|
||||
391
web/src/app/home/components/survey/SurveyWidget.tsx
Normal file
391
web/src/app/home/components/survey/SurveyWidget.tsx
Normal file
@@ -0,0 +1,391 @@
|
||||
'use client';
|
||||
|
||||
import React, { useState, useEffect, useCallback } from 'react';
|
||||
import { httpClient } from '@/app/infra/http/HttpClient';
|
||||
import type {
|
||||
SurveyQuestion,
|
||||
SurveyOption,
|
||||
} from '@/app/infra/http/BackendClient';
|
||||
import { X, ChevronRight, ChevronLeft, MessageSquare } from 'lucide-react';
|
||||
import { Button } from '@/components/ui/button';
|
||||
import { Checkbox } from '@/components/ui/checkbox';
|
||||
|
||||
/**
|
||||
* Get i18n text from a Record<string, string> based on browser locale.
|
||||
*/
|
||||
function getI18nText(obj?: Record<string, string> | null): string {
|
||||
if (!obj) return '';
|
||||
const lang = typeof navigator !== 'undefined' ? navigator.language : 'en';
|
||||
if (lang.startsWith('zh'))
|
||||
return obj['zh_Hans'] || obj['en_US'] || Object.values(obj)[0] || '';
|
||||
if (lang.startsWith('ja'))
|
||||
return obj['ja_JP'] || obj['en_US'] || Object.values(obj)[0] || '';
|
||||
return obj['en_US'] || Object.values(obj)[0] || '';
|
||||
}
|
||||
|
||||
interface SurveyData {
|
||||
survey_id: string;
|
||||
version: number;
|
||||
title: Record<string, string>;
|
||||
description: Record<string, string>;
|
||||
questions: SurveyQuestion[];
|
||||
}
|
||||
|
||||
export default function SurveyWidget() {
|
||||
const [survey, setSurvey] = useState<SurveyData | null>(null);
|
||||
const [visible, setVisible] = useState(false);
|
||||
const [currentStep, setCurrentStep] = useState(0);
|
||||
const [answers, setAnswers] = useState<Record<string, unknown>>({});
|
||||
const [otherInputs, setOtherInputs] = useState<Record<string, string>>({});
|
||||
const [submitted, setSubmitted] = useState(false);
|
||||
const [collapsed, setCollapsed] = useState(false);
|
||||
|
||||
// Poll for pending survey
|
||||
useEffect(() => {
|
||||
let timer: NodeJS.Timeout;
|
||||
let cancelled = false;
|
||||
|
||||
const checkSurvey = async () => {
|
||||
try {
|
||||
const resp = await httpClient.getSurveyPending();
|
||||
if (!cancelled && resp?.survey) {
|
||||
setSurvey(resp.survey);
|
||||
setVisible(true);
|
||||
}
|
||||
} catch {
|
||||
// Silently ignore
|
||||
}
|
||||
};
|
||||
|
||||
// Check after 5 seconds, then every 60 seconds
|
||||
timer = setTimeout(() => {
|
||||
checkSurvey();
|
||||
timer = setInterval(checkSurvey, 60000) as unknown as NodeJS.Timeout;
|
||||
}, 5000);
|
||||
|
||||
return () => {
|
||||
cancelled = true;
|
||||
clearTimeout(timer);
|
||||
clearInterval(timer);
|
||||
};
|
||||
}, []);
|
||||
|
||||
const handleDismiss = useCallback(async () => {
|
||||
if (survey) {
|
||||
try {
|
||||
await httpClient.dismissSurvey(survey.survey_id);
|
||||
} catch {
|
||||
/* ignore */
|
||||
}
|
||||
}
|
||||
setVisible(false);
|
||||
}, [survey]);
|
||||
|
||||
const handleSubmit = useCallback(async () => {
|
||||
if (!survey) return;
|
||||
|
||||
// Merge "other" text inputs into answers
|
||||
const finalAnswers = { ...answers };
|
||||
for (const [qId, text] of Object.entries(otherInputs)) {
|
||||
if (text.trim()) {
|
||||
const current = finalAnswers[qId];
|
||||
if (Array.isArray(current)) {
|
||||
// Replace 'other' with the text
|
||||
finalAnswers[qId] = (current as string[]).map((v) =>
|
||||
v === 'other' ? `other:${text}` : v,
|
||||
);
|
||||
} else if (current === 'other') {
|
||||
finalAnswers[qId] = `other:${text}`;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
try {
|
||||
await httpClient.submitSurveyResponse(
|
||||
survey.survey_id,
|
||||
finalAnswers,
|
||||
true,
|
||||
);
|
||||
setSubmitted(true);
|
||||
setTimeout(() => setVisible(false), 2000);
|
||||
} catch {
|
||||
/* ignore */
|
||||
}
|
||||
}, [survey, answers, otherInputs]);
|
||||
|
||||
const setAnswer = useCallback((qId: string, value: unknown) => {
|
||||
setAnswers((prev) => ({ ...prev, [qId]: value }));
|
||||
}, []);
|
||||
|
||||
if (!visible || !survey) return null;
|
||||
|
||||
const questions = survey.questions || [];
|
||||
const totalSteps = questions.length;
|
||||
const currentQuestion = questions[currentStep];
|
||||
|
||||
if (submitted) {
|
||||
return (
|
||||
<div className="fixed bottom-6 right-6 z-50 w-80 bg-card border rounded-xl shadow-lg p-6 animate-in slide-in-from-bottom-4">
|
||||
<div className="text-center">
|
||||
<div className="text-3xl mb-2">🎉</div>
|
||||
<p className="text-sm font-medium">
|
||||
{getI18nText({
|
||||
zh_Hans: '感谢你的反馈！',
|
||||
en_US: 'Thanks for your feedback!',
|
||||
})}
|
||||
</p>
|
||||
</div>
|
||||
</div>
|
||||
);
|
||||
}
|
||||
|
||||
if (collapsed) {
|
||||
return (
|
||||
<button
|
||||
onClick={() => setCollapsed(false)}
|
||||
className="fixed bottom-6 right-6 z-50 w-12 h-12 bg-primary text-primary-foreground rounded-full shadow-lg flex items-center justify-center hover:scale-105 transition-transform"
|
||||
>
|
||||
<MessageSquare className="w-5 h-5" />
|
||||
</button>
|
||||
);
|
||||
}
|
||||
|
||||
return (
|
||||
<div className="fixed bottom-6 right-6 z-50 w-[340px] bg-card border rounded-xl shadow-lg animate-in slide-in-from-bottom-4">
|
||||
{/* Header */}
|
||||
<div className="flex items-center justify-between px-4 py-3 border-b">
|
||||
<div className="flex items-center gap-2">
|
||||
<MessageSquare className="w-4 h-4 text-primary" />
|
||||
<span className="text-sm font-medium">
|
||||
{getI18nText(survey.title)}
|
||||
</span>
|
||||
</div>
|
||||
<div className="flex items-center gap-1">
|
||||
<button
|
||||
onClick={() => setCollapsed(true)}
|
||||
className="p-1 hover:bg-accent rounded"
|
||||
>
|
||||
<ChevronRight className="w-4 h-4 text-muted-foreground" />
|
||||
</button>
|
||||
<button
|
||||
onClick={handleDismiss}
|
||||
className="p-1 hover:bg-accent rounded"
|
||||
>
|
||||
<X className="w-4 h-4 text-muted-foreground" />
|
||||
</button>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
{/* Progress */}
|
||||
<div className="px-4 pt-3">
|
||||
<div className="flex gap-1">
|
||||
{questions.map((_, i) => (
|
||||
<div
|
||||
key={i}
|
||||
className={`h-1 flex-1 rounded-full transition-colors ${
|
||||
i <= currentStep ? 'bg-primary' : 'bg-secondary'
|
||||
}`}
|
||||
/>
|
||||
))}
|
||||
</div>
|
||||
<span className="text-xs text-muted-foreground mt-1 block">
|
||||
{currentStep + 1} / {totalSteps}
|
||||
</span>
|
||||
</div>
|
||||
|
||||
{/* Question */}
|
||||
<div className="px-4 py-3">
|
||||
<p className="text-sm font-medium mb-1">
|
||||
{getI18nText(currentQuestion?.title)}
|
||||
</p>
|
||||
{currentQuestion?.subtitle && (
|
||||
<p className="text-xs text-muted-foreground mb-3">
|
||||
{getI18nText(currentQuestion.subtitle)}
|
||||
</p>
|
||||
)}
|
||||
|
||||
<div className="space-y-2 max-h-[260px] overflow-y-auto">
|
||||
{currentQuestion?.type === 'single_select' &&
|
||||
currentQuestion.options && (
|
||||
<SingleSelectField
|
||||
options={currentQuestion.options}
|
||||
value={answers[currentQuestion.id] as string}
|
||||
onChange={(v) => setAnswer(currentQuestion.id, v)}
|
||||
otherText={otherInputs[currentQuestion.id] || ''}
|
||||
onOtherChange={(t) =>
|
||||
setOtherInputs((prev) => ({
|
||||
...prev,
|
||||
[currentQuestion.id]: t,
|
||||
}))
|
||||
}
|
||||
/>
|
||||
)}
|
||||
|
||||
{currentQuestion?.type === 'multi_select' &&
|
||||
currentQuestion.options && (
|
||||
<MultiSelectField
|
||||
options={currentQuestion.options}
|
||||
value={(answers[currentQuestion.id] as string[]) || []}
|
||||
onChange={(v) => setAnswer(currentQuestion.id, v)}
|
||||
otherText={otherInputs[currentQuestion.id] || ''}
|
||||
onOtherChange={(t) =>
|
||||
setOtherInputs((prev) => ({
|
||||
...prev,
|
||||
[currentQuestion.id]: t,
|
||||
}))
|
||||
}
|
||||
/>
|
||||
)}
|
||||
|
||||
{currentQuestion?.type === 'text' && (
|
||||
<textarea
|
||||
className="w-full h-20 text-sm border rounded-lg p-2 bg-background resize-none focus:outline-none focus:ring-1 focus:ring-primary"
|
||||
placeholder={getI18nText(currentQuestion.placeholder)}
|
||||
maxLength={currentQuestion.max_length || 500}
|
||||
value={(answers[currentQuestion.id] as string) || ''}
|
||||
onChange={(e) => setAnswer(currentQuestion.id, e.target.value)}
|
||||
/>
|
||||
)}
|
||||
</div>
|
||||
</div>
|
||||
|
||||
{/* Footer */}
|
||||
<div className="flex items-center justify-between px-4 py-3 border-t">
|
||||
<Button
|
||||
variant="ghost"
|
||||
size="sm"
|
||||
onClick={() => setCurrentStep(Math.max(0, currentStep - 1))}
|
||||
disabled={currentStep === 0}
|
||||
>
|
||||
<ChevronLeft className="w-4 h-4" />
|
||||
</Button>
|
||||
|
||||
<div className="flex gap-2">
|
||||
{!currentQuestion?.required && currentStep < totalSteps - 1 && (
|
||||
<Button
|
||||
variant="ghost"
|
||||
size="sm"
|
||||
onClick={() => setCurrentStep(currentStep + 1)}
|
||||
>
|
||||
{getI18nText({ zh_Hans: '跳过', en_US: 'Skip' })}
|
||||
</Button>
|
||||
)}
|
||||
|
||||
{currentStep < totalSteps - 1 ? (
|
||||
<Button
|
||||
size="sm"
|
||||
onClick={() => setCurrentStep(currentStep + 1)}
|
||||
disabled={
|
||||
currentQuestion?.required && !answers[currentQuestion?.id]
|
||||
}
|
||||
>
|
||||
{getI18nText({ zh_Hans: '下一题', en_US: 'Next' })}
|
||||
</Button>
|
||||
) : (
|
||||
<Button size="sm" onClick={handleSubmit}>
|
||||
{getI18nText({ zh_Hans: '提交', en_US: 'Submit' })}
|
||||
</Button>
|
||||
)}
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
);
|
||||
}
|
||||
|
||||
// ---- Sub-components for flat radio/checkbox style ----
|
||||
|
||||
function SingleSelectField({
|
||||
options,
|
||||
value,
|
||||
onChange,
|
||||
otherText,
|
||||
onOtherChange,
|
||||
}: {
|
||||
options: SurveyOption[];
|
||||
value?: string;
|
||||
onChange: (v: string) => void;
|
||||
otherText: string;
|
||||
onOtherChange: (t: string) => void;
|
||||
}) {
|
||||
return (
|
||||
<div className="space-y-1.5">
|
||||
{options.map((opt) => (
|
||||
<div key={opt.id}>
|
||||
<button
|
||||
onClick={() => onChange(opt.id)}
|
||||
className={`w-full text-left text-sm px-3 py-2 rounded-lg border transition-colors ${
|
||||
value === opt.id
|
||||
? 'border-primary bg-primary/5 text-primary'
|
||||
: 'border-border hover:bg-accent'
|
||||
}`}
|
||||
>
|
||||
{getI18nText(opt.label)}
|
||||
</button>
|
||||
{opt.has_input && value === opt.id && (
|
||||
<input
|
||||
type="text"
|
||||
className="mt-1 w-full text-sm border rounded-lg px-3 py-1.5 bg-background focus:outline-none focus:ring-1 focus:ring-primary"
|
||||
placeholder="..."
|
||||
value={otherText}
|
||||
onChange={(e) => onOtherChange(e.target.value)}
|
||||
/>
|
||||
)}
|
||||
</div>
|
||||
))}
|
||||
</div>
|
||||
);
|
||||
}
|
||||
|
||||
function MultiSelectField({
|
||||
options,
|
||||
value,
|
||||
onChange,
|
||||
otherText,
|
||||
onOtherChange,
|
||||
}: {
|
||||
options: SurveyOption[];
|
||||
value: string[];
|
||||
onChange: (v: string[]) => void;
|
||||
otherText: string;
|
||||
onOtherChange: (t: string) => void;
|
||||
}) {
|
||||
const toggle = (id: string) => {
|
||||
if (value.includes(id)) {
|
||||
onChange(value.filter((v) => v !== id));
|
||||
} else {
|
||||
onChange([...value, id]);
|
||||
}
|
||||
};
|
||||
|
||||
return (
|
||||
<div className="space-y-1.5">
|
||||
{options.map((opt) => {
|
||||
const selected = value.includes(opt.id);
|
||||
return (
|
||||
<div key={opt.id}>
|
||||
<button
|
||||
onClick={() => toggle(opt.id)}
|
||||
className={`w-full text-left text-sm px-3 py-2 rounded-lg border transition-colors flex items-center gap-2 ${
|
||||
selected
|
||||
? 'border-primary bg-primary/5 text-primary'
|
||||
: 'border-border hover:bg-accent'
|
||||
}`}
|
||||
>
|
||||
<Checkbox checked={selected} className="pointer-events-none" />
|
||||
{getI18nText(opt.label)}
|
||||
</button>
|
||||
{opt.has_input && selected && (
|
||||
<input
|
||||
type="text"
|
||||
className="mt-1 w-full text-sm border rounded-lg px-3 py-1.5 bg-background focus:outline-none focus:ring-1 focus:ring-primary"
|
||||
placeholder="..."
|
||||
value={otherText}
|
||||
onChange={(e) => onOtherChange(e.target.value)}
|
||||
/>
|
||||
)}
|
||||
</div>
|
||||
);
|
||||
})}
|
||||
</div>
|
||||
);
|
||||
}
|
||||
@@ -3,6 +3,7 @@
|
||||
import styles from './layout.module.css';
|
||||
import HomeSidebar from '@/app/home/components/home-sidebar/HomeSidebar';
|
||||
import HomeTitleBar from '@/app/home/components/home-titlebar/HomeTitleBar';
|
||||
import SurveyWidget from '@/app/home/components/survey/SurveyWidget';
|
||||
import React, {
|
||||
useState,
|
||||
useCallback,
|
||||
@@ -54,6 +55,8 @@ export default function HomeLayout({
|
||||
<HomeTitleBar title={title} subtitle={subtitle} helpLink={helpLink} />
|
||||
|
||||
<main className={styles.mainContent}>{mainContent}</main>
|
||||
|
||||
<SurveyWidget />
|
||||
</div>
|
||||
</div>
|
||||
);
|
||||
|
||||
@@ -1,5 +1,9 @@
|
||||
import { LoadingPage } from '@/components/ui/loading-spinner';
|
||||
import { LoadingSpinner } from '@/components/ui/loading-spinner';
|
||||
|
||||
export default function Loading() {
|
||||
return <LoadingPage />;
|
||||
return (
|
||||
<div className="flex h-full items-center justify-center">
|
||||
<LoadingSpinner size="lg" />
|
||||
</div>
|
||||
);
|
||||
}
|
||||
|
||||
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>
|
||||
|
||||
@@ -7,7 +7,6 @@ import {
|
||||
DialogHeader,
|
||||
DialogTitle,
|
||||
} from '@/components/ui/dialog';
|
||||
import { Button } from '@/components/ui/button';
|
||||
import {
|
||||
Sidebar,
|
||||
SidebarContent,
|
||||
@@ -21,6 +20,7 @@ import {
|
||||
import PipelineFormComponent from './components/pipeline-form/PipelineFormComponent';
|
||||
import DebugDialog from './components/debug-dialog/DebugDialog';
|
||||
import PipelineExtension from './components/pipeline-extensions/PipelineExtension';
|
||||
import PipelineMonitoringTab from './components/monitoring-tab/PipelineMonitoringTab';
|
||||
|
||||
interface PipelineDialogProps {
|
||||
open: boolean;
|
||||
@@ -34,7 +34,7 @@ interface PipelineDialogProps {
|
||||
onCancel: () => void;
|
||||
}
|
||||
|
||||
type DialogMode = 'config' | 'debug' | 'extensions';
|
||||
type DialogMode = 'config' | 'debug' | 'extensions' | 'monitoring';
|
||||
|
||||
export default function PipelineDialog({
|
||||
open,
|
||||
@@ -111,6 +111,19 @@ export default function PipelineDialog({
|
||||
</svg>
|
||||
),
|
||||
},
|
||||
{
|
||||
key: 'monitoring',
|
||||
label: t('pipelines.monitoring.title'),
|
||||
icon: (
|
||||
<svg
|
||||
xmlns="http://www.w3.org/2000/svg"
|
||||
viewBox="0 0 24 24"
|
||||
fill="currentColor"
|
||||
>
|
||||
<path d="M2 3.9934C2 3.44476 2.45531 3 2.9918 3H21.0082C21.556 3 22 3.44495 22 3.9934V20.0066C22 20.5552 21.5447 21 21.0082 21H2.9918C2.44405 21 2 20.5551 2 20.0066V3.9934ZM4 5V19H20V5H4ZM6 7H18V9H6V7ZM6 11H18V13H6V11ZM6 15H12V17H6V15Z"></path>
|
||||
</svg>
|
||||
),
|
||||
},
|
||||
];
|
||||
|
||||
const getDialogTitle = () => {
|
||||
@@ -122,6 +135,9 @@ export default function PipelineDialog({
|
||||
if (currentMode === 'extensions') {
|
||||
return t('pipelines.extensions.title');
|
||||
}
|
||||
if (currentMode === 'monitoring') {
|
||||
return t('pipelines.monitoring.title');
|
||||
}
|
||||
return t('pipelines.debugDialog.title');
|
||||
};
|
||||
|
||||
@@ -193,48 +209,23 @@ export default function PipelineDialog({
|
||||
>
|
||||
<DialogTitle>{getDialogTitle()}</DialogTitle>
|
||||
{currentMode === 'debug' && (
|
||||
<>
|
||||
<div className="flex items-center gap-2 ml-2">
|
||||
<div
|
||||
className={`w-2.5 h-2.5 rounded-full ${
|
||||
isWebSocketConnected ? 'bg-green-500' : 'bg-red-500'
|
||||
}`}
|
||||
title={
|
||||
isWebSocketConnected
|
||||
? t('pipelines.debugDialog.connected')
|
||||
: t('pipelines.debugDialog.disconnected')
|
||||
}
|
||||
/>
|
||||
<span className="text-sm text-gray-600 dark:text-gray-400">
|
||||
{isWebSocketConnected
|
||||
<div className="flex items-center gap-2 ml-2">
|
||||
<div
|
||||
className={`w-2.5 h-2.5 rounded-full ${
|
||||
isWebSocketConnected ? 'bg-green-500' : 'bg-red-500'
|
||||
}`}
|
||||
title={
|
||||
isWebSocketConnected
|
||||
? t('pipelines.debugDialog.connected')
|
||||
: t('pipelines.debugDialog.disconnected')}
|
||||
</span>
|
||||
</div>
|
||||
<div className="ml-auto mr-4">
|
||||
<Button
|
||||
variant="outline"
|
||||
size="sm"
|
||||
onClick={() => {
|
||||
router.push(
|
||||
`/home/monitoring?pipelineId=${pipelineId}`,
|
||||
);
|
||||
onOpenChange(false);
|
||||
}}
|
||||
className="bg-white dark:bg-[#2a2a2e]"
|
||||
>
|
||||
<svg
|
||||
className="w-4 h-4 mr-2"
|
||||
xmlns="http://www.w3.org/2000/svg"
|
||||
viewBox="0 0 24 24"
|
||||
fill="currentColor"
|
||||
>
|
||||
<path d="M2 3.9934C2 3.44476 2.45531 3 2.9918 3H21.0082C21.556 3 22 3.44495 22 3.9934V20.0066C22 20.5552 21.5447 21 21.0082 21H2.9918C2.44405 21 2 20.5551 2 20.0066V3.9934ZM4 5V19H20V5H4ZM6 7H18V9H6V7ZM6 11H18V13H6V11ZM6 15H12V17H6V15Z"></path>
|
||||
</svg>
|
||||
{t('monitoring.viewMonitoring')}
|
||||
</Button>
|
||||
</div>
|
||||
</>
|
||||
: t('pipelines.debugDialog.disconnected')
|
||||
}
|
||||
/>
|
||||
<span className="text-sm text-gray-600 dark:text-gray-400">
|
||||
{isWebSocketConnected
|
||||
? t('pipelines.debugDialog.connected')
|
||||
: t('pipelines.debugDialog.disconnected')}
|
||||
</span>
|
||||
</div>
|
||||
)}
|
||||
</DialogHeader>
|
||||
<div
|
||||
@@ -268,6 +259,16 @@ export default function PipelineDialog({
|
||||
onConnectionStatusChange={setIsWebSocketConnected}
|
||||
/>
|
||||
)}
|
||||
|
||||
{currentMode === 'monitoring' && pipelineId && (
|
||||
<PipelineMonitoringTab
|
||||
pipelineId={pipelineId}
|
||||
onNavigateToMonitoring={() => {
|
||||
router.push(`/home/monitoring?pipelineId=${pipelineId}`);
|
||||
onOpenChange(false);
|
||||
}}
|
||||
/>
|
||||
)}
|
||||
</div>
|
||||
</main>
|
||||
</SidebarProvider>
|
||||
|
||||
@@ -25,6 +25,7 @@ import ReactMarkdown from 'react-markdown';
|
||||
import remarkGfm from 'remark-gfm';
|
||||
import rehypeHighlight from 'rehype-highlight';
|
||||
import rehypeRaw from 'rehype-raw';
|
||||
import rehypeSanitize from 'rehype-sanitize';
|
||||
import rehypeSlug from 'rehype-slug';
|
||||
import rehypeAutolinkHeadings from 'rehype-autolink-headings';
|
||||
import '@/styles/github-markdown.css';
|
||||
@@ -622,6 +623,7 @@ export default function DebugDialog({
|
||||
remarkPlugins={[remarkGfm]}
|
||||
rehypePlugins={[
|
||||
rehypeRaw,
|
||||
rehypeSanitize,
|
||||
rehypeHighlight,
|
||||
rehypeSlug,
|
||||
[
|
||||
|
||||
@@ -0,0 +1,665 @@
|
||||
'use client';
|
||||
|
||||
import React, { useState, useMemo } from 'react';
|
||||
import { useTranslation } from 'react-i18next';
|
||||
import { Tabs, TabsContent, TabsList, TabsTrigger } from '@/components/ui/tabs';
|
||||
import { Button } from '@/components/ui/button';
|
||||
import { ChevronRight, ChevronDown, ExternalLink } from 'lucide-react';
|
||||
import { useMonitoringData } from '@/app/home/monitoring/hooks/useMonitoringData';
|
||||
import { MessageContentRenderer } from '@/app/home/monitoring/components/MessageContentRenderer';
|
||||
import { LoadingSpinner } from '@/components/ui/loading-spinner';
|
||||
import { httpClient } from '@/app/infra/http/HttpClient';
|
||||
import { MessageDetails } from '@/app/home/monitoring/types/monitoring';
|
||||
|
||||
interface PipelineMonitoringTabProps {
|
||||
pipelineId: string;
|
||||
onNavigateToMonitoring?: () => void;
|
||||
}
|
||||
|
||||
interface RawMessageData {
|
||||
id: string;
|
||||
timestamp: string;
|
||||
bot_id: string;
|
||||
bot_name: string;
|
||||
pipeline_id: string;
|
||||
pipeline_name: string;
|
||||
message_content: string;
|
||||
session_id: string;
|
||||
status: string;
|
||||
level: string;
|
||||
platform: string;
|
||||
user_id: string;
|
||||
runner_name: string;
|
||||
variables: Record<string, unknown>;
|
||||
}
|
||||
|
||||
interface RawLLMCallData {
|
||||
id: string;
|
||||
timestamp: string;
|
||||
model_name: string;
|
||||
status: string;
|
||||
duration: number;
|
||||
error_message: string | null;
|
||||
input_tokens: number;
|
||||
output_tokens: number;
|
||||
total_tokens: number;
|
||||
}
|
||||
|
||||
interface RawLLMStatsData {
|
||||
total_calls: number;
|
||||
total_input_tokens: number;
|
||||
total_output_tokens: number;
|
||||
total_tokens: number;
|
||||
total_duration_ms: number;
|
||||
average_duration_ms: number;
|
||||
}
|
||||
|
||||
interface RawErrorData {
|
||||
id: string;
|
||||
timestamp: string;
|
||||
error_type: string;
|
||||
error_message: string;
|
||||
stack_trace: string | null;
|
||||
}
|
||||
|
||||
export default function PipelineMonitoringTab({
|
||||
pipelineId,
|
||||
onNavigateToMonitoring,
|
||||
}: PipelineMonitoringTabProps) {
|
||||
const { t } = useTranslation();
|
||||
|
||||
// Filter state - only show data for this pipeline, last 24 hours
|
||||
const filterState = useMemo(
|
||||
() => ({
|
||||
selectedBots: [],
|
||||
selectedPipelines: [pipelineId],
|
||||
timeRange: 'last24Hours' as const,
|
||||
customDateRange: null,
|
||||
}),
|
||||
[pipelineId],
|
||||
);
|
||||
|
||||
const { data, loading, refetch } = useMonitoringData(filterState);
|
||||
|
||||
const [expandedMessageId, setExpandedMessageId] = useState<string | null>(
|
||||
null,
|
||||
);
|
||||
const [messageDetails, setMessageDetails] = useState<
|
||||
Record<string, MessageDetails>
|
||||
>({});
|
||||
const [loadingDetails, setLoadingDetails] = useState<Record<string, boolean>>(
|
||||
{},
|
||||
);
|
||||
const [expandedErrorId, setExpandedErrorId] = useState<string | null>(null);
|
||||
const [activeTab, setActiveTab] = useState<string>('messages');
|
||||
|
||||
const toggleMessageExpand = async (messageId: string) => {
|
||||
if (expandedMessageId === messageId) {
|
||||
setExpandedMessageId(null);
|
||||
} else {
|
||||
setExpandedMessageId(messageId);
|
||||
|
||||
if (!messageDetails[messageId]) {
|
||||
setLoadingDetails((prev) => ({ ...prev, [messageId]: true }));
|
||||
try {
|
||||
const result = await httpClient.get<{
|
||||
message_id: string;
|
||||
found: boolean;
|
||||
message: RawMessageData | null;
|
||||
llm_calls: RawLLMCallData[];
|
||||
llm_stats: RawLLMStatsData;
|
||||
errors: RawErrorData[];
|
||||
}>(`/api/v1/monitoring/messages/${messageId}/details`);
|
||||
|
||||
if (result) {
|
||||
setMessageDetails((prev) => ({
|
||||
...prev,
|
||||
[messageId]: {
|
||||
messageId: result.message_id,
|
||||
found: result.found,
|
||||
message: result.message
|
||||
? {
|
||||
id: result.message.id,
|
||||
timestamp: new Date(result.message.timestamp),
|
||||
botId: result.message.bot_id,
|
||||
botName: result.message.bot_name,
|
||||
pipelineId: result.message.pipeline_id,
|
||||
pipelineName: result.message.pipeline_name,
|
||||
messageContent: result.message.message_content,
|
||||
sessionId: result.message.session_id,
|
||||
status: result.message.status,
|
||||
level: result.message.level,
|
||||
platform: result.message.platform,
|
||||
userId: result.message.user_id,
|
||||
runnerName: result.message.runner_name,
|
||||
variables: result.message.variables,
|
||||
}
|
||||
: undefined,
|
||||
llmCalls: result.llm_calls.map((call: RawLLMCallData) => ({
|
||||
id: call.id,
|
||||
timestamp: new Date(call.timestamp),
|
||||
modelName: call.model_name,
|
||||
status: call.status,
|
||||
duration: call.duration,
|
||||
errorMessage: call.error_message,
|
||||
tokens: {
|
||||
input: call.input_tokens || 0,
|
||||
output: call.output_tokens || 0,
|
||||
total: call.total_tokens || 0,
|
||||
},
|
||||
})),
|
||||
errors: result.errors.map((error: RawErrorData) => ({
|
||||
id: error.id,
|
||||
timestamp: new Date(error.timestamp),
|
||||
errorType: error.error_type,
|
||||
errorMessage: error.error_message,
|
||||
stackTrace: error.stack_trace,
|
||||
})),
|
||||
llmStats: {
|
||||
totalCalls: result.llm_stats.total_calls,
|
||||
totalInputTokens: result.llm_stats.total_input_tokens,
|
||||
totalOutputTokens: result.llm_stats.total_output_tokens,
|
||||
totalTokens: result.llm_stats.total_tokens,
|
||||
totalDurationMs: result.llm_stats.total_duration_ms,
|
||||
averageDurationMs: result.llm_stats.average_duration_ms,
|
||||
},
|
||||
} as MessageDetails,
|
||||
}));
|
||||
}
|
||||
} catch (error) {
|
||||
console.error('Failed to fetch message details:', error);
|
||||
} finally {
|
||||
setLoadingDetails((prev) => ({ ...prev, [messageId]: false }));
|
||||
}
|
||||
}
|
||||
}
|
||||
};
|
||||
|
||||
const toggleErrorExpand = (errorId: string) => {
|
||||
if (expandedErrorId === errorId) {
|
||||
setExpandedErrorId(null);
|
||||
} else {
|
||||
setExpandedErrorId(errorId);
|
||||
}
|
||||
};
|
||||
|
||||
const jumpToMessage = async (messageId: string) => {
|
||||
setActiveTab('messages');
|
||||
// Small delay to ensure tab transition completes before expanding
|
||||
setTimeout(() => {
|
||||
toggleMessageExpand(messageId);
|
||||
}, 100);
|
||||
};
|
||||
|
||||
return (
|
||||
<div className="w-full h-full flex flex-col">
|
||||
{/* Header with refresh button */}
|
||||
<div className="flex items-center justify-between mb-4 pb-4 border-b border-gray-200 dark:border-gray-700">
|
||||
<p className="text-sm text-gray-500 dark:text-gray-400">
|
||||
{t('pipelines.monitoring.description')}
|
||||
</p>
|
||||
<div className="flex items-center gap-2">
|
||||
{onNavigateToMonitoring && (
|
||||
<Button
|
||||
variant="outline"
|
||||
size="sm"
|
||||
onClick={onNavigateToMonitoring}
|
||||
className="bg-white dark:bg-[#2a2a2e] hover:bg-gray-50 dark:hover:bg-gray-800 border-gray-300 dark:border-gray-600"
|
||||
>
|
||||
<svg
|
||||
className="w-4 h-4 mr-2"
|
||||
xmlns="http://www.w3.org/2000/svg"
|
||||
viewBox="0 0 24 24"
|
||||
fill="currentColor"
|
||||
>
|
||||
<path d="M10 6V8H5V19H16V14H18V20C18 20.5523 17.5523 21 17 21H4C3.44772 21 3 20.5523 3 20V7C3 6.44772 3.44772 6 4 6H10ZM21 3V11H19V6.413L11.2071 14.2071L9.79289 12.7929L17.585 5H13V3H21Z"></path>
|
||||
</svg>
|
||||
{t('pipelines.monitoring.detailedLogs')}
|
||||
</Button>
|
||||
)}
|
||||
<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"
|
||||
>
|
||||
<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>
|
||||
|
||||
{/* Overview Stats */}
|
||||
{data && (
|
||||
<div className="grid grid-cols-3 gap-4 mb-6">
|
||||
<div className="bg-white dark:bg-[#2a2a2e] rounded-lg border border-gray-200 dark:border-gray-700 p-4">
|
||||
<div className="text-sm text-gray-500 dark:text-gray-400">
|
||||
{t('monitoring.totalMessages')}
|
||||
</div>
|
||||
<div className="text-2xl font-bold text-gray-900 dark:text-gray-100 mt-1">
|
||||
{data.overview.totalMessages}
|
||||
</div>
|
||||
</div>
|
||||
<div className="bg-white dark:bg-[#2a2a2e] rounded-lg border border-gray-200 dark:border-gray-700 p-4">
|
||||
<div className="text-sm text-gray-500 dark:text-gray-400">
|
||||
{t('monitoring.successRate')}
|
||||
</div>
|
||||
<div className="text-2xl font-bold text-gray-900 dark:text-gray-100 mt-1">
|
||||
{data.overview.successRate.toFixed(1)}%
|
||||
</div>
|
||||
</div>
|
||||
<div className="bg-white dark:bg-[#2a2a2e] rounded-lg border border-gray-200 dark:border-gray-700 p-4">
|
||||
<div className="text-sm text-gray-500 dark:text-gray-400">
|
||||
{t('monitoring.tabs.errors')}
|
||||
</div>
|
||||
<div className="text-2xl font-bold text-red-600 dark:text-red-400 mt-1">
|
||||
{data.errors.length}
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
)}
|
||||
|
||||
{/* Tabs */}
|
||||
<Tabs
|
||||
value={activeTab}
|
||||
onValueChange={setActiveTab}
|
||||
className="flex-1 flex flex-col min-h-0"
|
||||
>
|
||||
<TabsList className="bg-gray-100 dark:bg-[#1a1a1e] h-10 p-1 mb-4">
|
||||
<TabsTrigger
|
||||
value="messages"
|
||||
className="px-4 py-1.5 text-sm font-medium cursor-pointer data-[state=active]:bg-white dark:data-[state=active]:bg-[#2a2a2e] data-[state=active]:shadow-sm"
|
||||
>
|
||||
{t('monitoring.tabs.messages')}
|
||||
</TabsTrigger>
|
||||
<TabsTrigger
|
||||
value="errors"
|
||||
className="px-4 py-1.5 text-sm font-medium cursor-pointer data-[state=active]:bg-white dark:data-[state=active]:bg-[#2a2a2e] data-[state=active]:shadow-sm"
|
||||
>
|
||||
{t('monitoring.tabs.errors')}
|
||||
</TabsTrigger>
|
||||
<TabsTrigger
|
||||
value="llmCalls"
|
||||
className="px-4 py-1.5 text-sm font-medium cursor-pointer data-[state=active]:bg-white dark:data-[state=active]:bg-[#2a2a2e] data-[state=active]:shadow-sm"
|
||||
>
|
||||
{t('monitoring.tabs.modelCalls')}
|
||||
</TabsTrigger>
|
||||
</TabsList>
|
||||
|
||||
<div className="flex-1 overflow-y-auto min-h-0">
|
||||
{/* Messages Tab */}
|
||||
<TabsContent value="messages" className="m-0 h-full">
|
||||
{loading && (
|
||||
<div className="py-12 flex justify-center">
|
||||
<LoadingSpinner text={t('monitoring.messageList.loading')} />
|
||||
</div>
|
||||
)}
|
||||
|
||||
{!loading && data && data.messages && data.messages.length > 0 && (
|
||||
<div className="space-y-3">
|
||||
{data.messages
|
||||
.filter((msg) => {
|
||||
const content = msg.messageContent?.trim();
|
||||
return content && content !== '[]' && content !== '""';
|
||||
})
|
||||
.map((msg) => (
|
||||
<div
|
||||
key={msg.id}
|
||||
className="border border-gray-200 dark:border-gray-700 rounded-lg overflow-hidden hover:shadow-md transition-all duration-200"
|
||||
>
|
||||
<div
|
||||
className="p-4 cursor-pointer hover:bg-gray-50 dark:hover:bg-gray-800/50 transition-colors"
|
||||
onClick={() => toggleMessageExpand(msg.id)}
|
||||
>
|
||||
<div className="flex items-start justify-between">
|
||||
<div className="flex items-start flex-1">
|
||||
<div className="mr-2 mt-0.5">
|
||||
{expandedMessageId === msg.id ? (
|
||||
<ChevronDown className="w-4 h-4 text-gray-500" />
|
||||
) : (
|
||||
<ChevronRight className="w-4 h-4 text-gray-500" />
|
||||
)}
|
||||
</div>
|
||||
<div className="flex-1">
|
||||
<div className="flex items-center gap-2 mb-1">
|
||||
<span
|
||||
className={`text-xs px-2 py-0.5 rounded ${
|
||||
msg.status === 'success'
|
||||
? 'bg-green-100 text-green-800 dark:bg-green-900 dark:text-green-200'
|
||||
: msg.status === 'error'
|
||||
? 'bg-red-100 text-red-800 dark:bg-red-900 dark:text-red-200'
|
||||
: 'bg-yellow-100 text-yellow-800 dark:bg-yellow-900 dark:text-yellow-200'
|
||||
}`}
|
||||
>
|
||||
{msg.status}
|
||||
</span>
|
||||
<span className="text-xs text-gray-500 dark:text-gray-400">
|
||||
{msg.botName}
|
||||
</span>
|
||||
</div>
|
||||
<div className="text-sm text-gray-700 dark:text-gray-300 line-clamp-2">
|
||||
<MessageContentRenderer
|
||||
content={msg.messageContent}
|
||||
/>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
<span className="text-xs text-gray-500 dark:text-gray-400 whitespace-nowrap ml-4">
|
||||
{msg.timestamp.toLocaleString()}
|
||||
</span>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
{expandedMessageId === msg.id && (
|
||||
<div className="border-t border-gray-200 dark:border-gray-700 p-4 bg-gray-50 dark:bg-gray-900">
|
||||
{loadingDetails[msg.id] && (
|
||||
<div className="flex justify-center py-8">
|
||||
<LoadingSpinner
|
||||
text={t('monitoring.messageList.loading')}
|
||||
/>
|
||||
</div>
|
||||
)}
|
||||
|
||||
{!loadingDetails[msg.id] &&
|
||||
messageDetails[msg.id] && (
|
||||
<div className="space-y-4">
|
||||
{messageDetails[msg.id].errors.length > 0 && (
|
||||
<div className="bg-red-50 dark:bg-red-900/20 rounded-lg p-3">
|
||||
<h4 className="text-sm font-semibold text-red-700 dark:text-red-400 mb-2">
|
||||
{t('monitoring.errors.errorMessage')}
|
||||
</h4>
|
||||
{messageDetails[msg.id].errors.map(
|
||||
(error) => (
|
||||
<div
|
||||
key={error.id}
|
||||
className="text-sm space-y-2"
|
||||
>
|
||||
<div className="text-red-600 dark:text-red-400">
|
||||
{error.errorType}:{' '}
|
||||
{error.errorMessage}
|
||||
</div>
|
||||
{error.stackTrace && (
|
||||
<pre className="text-xs text-gray-600 dark:text-gray-400 overflow-auto max-h-40 bg-white dark:bg-gray-900 p-2 rounded whitespace-pre-wrap break-words">
|
||||
{error.stackTrace}
|
||||
</pre>
|
||||
)}
|
||||
</div>
|
||||
),
|
||||
)}
|
||||
</div>
|
||||
)}
|
||||
|
||||
{messageDetails[msg.id].llmCalls.length > 0 && (
|
||||
<div className="bg-blue-50 dark:bg-blue-900/20 rounded-lg p-3">
|
||||
<h4 className="text-sm font-semibold text-blue-700 dark:text-blue-400 mb-2">
|
||||
{t('monitoring.tabs.modelCalls')} (
|
||||
{messageDetails[msg.id].llmCalls.length})
|
||||
</h4>
|
||||
<div className="text-xs text-gray-600 dark:text-gray-400 space-y-1">
|
||||
<div>
|
||||
{t('monitoring.llmCalls.totalTokens')}:{' '}
|
||||
{
|
||||
messageDetails[msg.id].llmStats
|
||||
.totalTokens
|
||||
}
|
||||
</div>
|
||||
<div>
|
||||
{t('monitoring.llmCalls.duration')}:{' '}
|
||||
{messageDetails[
|
||||
msg.id
|
||||
].llmStats.totalDurationMs.toFixed(0)}
|
||||
ms
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
)}
|
||||
</div>
|
||||
)}
|
||||
</div>
|
||||
)}
|
||||
</div>
|
||||
))}
|
||||
</div>
|
||||
)}
|
||||
|
||||
{!loading &&
|
||||
(!data || !data.messages || data.messages.length === 0) && (
|
||||
<div className="text-center text-gray-500 dark:text-gray-400 py-16">
|
||||
<svg
|
||||
className="w-16 h-16 mx-auto mb-4 text-gray-300 dark:text-gray-600"
|
||||
fill="none"
|
||||
viewBox="0 0 24 24"
|
||||
stroke="currentColor"
|
||||
>
|
||||
<path
|
||||
strokeLinecap="round"
|
||||
strokeLinejoin="round"
|
||||
strokeWidth={1.5}
|
||||
d="M8 12h.01M12 12h.01M16 12h.01M21 12c0 4.418-4.03 8-9 8a9.863 9.863 0 01-4.255-.949L3 20l1.395-3.72C3.512 15.042 3 13.574 3 12c0-4.418 4.03-8 9-8s9 3.582 9 8z"
|
||||
/>
|
||||
</svg>
|
||||
<p className="text-base font-medium">
|
||||
{t('monitoring.messageList.noMessages')}
|
||||
</p>
|
||||
</div>
|
||||
)}
|
||||
</TabsContent>
|
||||
|
||||
{/* Errors Tab */}
|
||||
<TabsContent value="errors" className="m-0 h-full">
|
||||
{loading && (
|
||||
<div className="py-12 flex justify-center">
|
||||
<LoadingSpinner text={t('common.loading')} />
|
||||
</div>
|
||||
)}
|
||||
|
||||
{!loading && data && data.errors && data.errors.length > 0 && (
|
||||
<div className="space-y-3">
|
||||
{data.errors.map((error) => (
|
||||
<div
|
||||
key={error.id}
|
||||
className="border border-red-200 dark:border-red-900 rounded-lg overflow-hidden hover:shadow-md transition-all duration-200"
|
||||
>
|
||||
<div
|
||||
className="p-4 cursor-pointer hover:bg-red-50 dark:hover:bg-red-950/50 transition-colors bg-red-50/50 dark:bg-red-950/30"
|
||||
onClick={() => toggleErrorExpand(error.id)}
|
||||
>
|
||||
<div className="flex items-start justify-between">
|
||||
<div className="flex items-start flex-1">
|
||||
<div className="mr-2 mt-0.5">
|
||||
{expandedErrorId === error.id ? (
|
||||
<ChevronDown className="w-4 h-4 text-red-500" />
|
||||
) : (
|
||||
<ChevronRight className="w-4 h-4 text-red-500" />
|
||||
)}
|
||||
</div>
|
||||
<div className="flex-1">
|
||||
<div className="flex items-center gap-2 mb-1">
|
||||
{error.messageId && (
|
||||
<Button
|
||||
variant="ghost"
|
||||
size="sm"
|
||||
className="h-5 px-1.5 text-xs"
|
||||
onClick={(e) => {
|
||||
e.stopPropagation();
|
||||
jumpToMessage(error.messageId!);
|
||||
}}
|
||||
>
|
||||
<ExternalLink className="w-3 h-3 mr-1" />
|
||||
{t('monitoring.messageList.viewConversation')}
|
||||
</Button>
|
||||
)}
|
||||
</div>
|
||||
<div className="font-medium text-sm text-red-700 dark:text-red-300 mb-1">
|
||||
{error.errorType}
|
||||
</div>
|
||||
<p className="text-sm text-red-600 dark:text-red-400 line-clamp-2">
|
||||
{error.errorMessage}
|
||||
</p>
|
||||
</div>
|
||||
</div>
|
||||
<span className="text-xs text-gray-500 dark:text-gray-400 whitespace-nowrap ml-4">
|
||||
{error.timestamp.toLocaleString()}
|
||||
</span>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
{expandedErrorId === error.id && (
|
||||
<div className="border-t border-red-200 dark:border-red-900 p-4 bg-white dark:bg-gray-900">
|
||||
<div className="space-y-3">
|
||||
<div className="bg-red-50 dark:bg-red-900/20 rounded-lg p-3">
|
||||
<h4 className="text-sm font-semibold text-red-700 dark:text-red-400 mb-2">
|
||||
{t('monitoring.errors.errorMessage')}
|
||||
</h4>
|
||||
<div className="text-sm text-red-600 dark:text-red-400 whitespace-pre-wrap break-words">
|
||||
{error.errorMessage}
|
||||
</div>
|
||||
</div>
|
||||
|
||||
{error.stackTrace && (
|
||||
<div className="bg-gray-50 dark:bg-gray-800 rounded-lg p-3">
|
||||
<h4 className="text-sm font-semibold text-gray-700 dark:text-gray-300 mb-2">
|
||||
{t('monitoring.errors.stackTrace')}
|
||||
</h4>
|
||||
<pre className="text-xs text-gray-600 dark:text-gray-400 overflow-auto max-h-60 bg-white dark:bg-gray-900 p-2 rounded whitespace-pre-wrap break-words">
|
||||
{error.stackTrace}
|
||||
</pre>
|
||||
</div>
|
||||
)}
|
||||
</div>
|
||||
</div>
|
||||
)}
|
||||
</div>
|
||||
))}
|
||||
</div>
|
||||
)}
|
||||
|
||||
{!loading &&
|
||||
(!data || !data.errors || data.errors.length === 0) && (
|
||||
<div className="text-center text-gray-500 dark:text-gray-400 py-16">
|
||||
<svg
|
||||
className="w-16 h-16 mx-auto mb-4 text-green-300 dark:text-green-600"
|
||||
fill="none"
|
||||
viewBox="0 0 24 24"
|
||||
stroke="currentColor"
|
||||
>
|
||||
<path
|
||||
strokeLinecap="round"
|
||||
strokeLinejoin="round"
|
||||
strokeWidth={1.5}
|
||||
d="M9 12l2 2 4-4m6 2a9 9 0 11-18 0 9 9 0 0118 0z"
|
||||
/>
|
||||
</svg>
|
||||
<p className="text-base font-medium text-green-600 dark:text-green-400">
|
||||
{t('monitoring.errors.noErrors')}
|
||||
</p>
|
||||
</div>
|
||||
)}
|
||||
</TabsContent>
|
||||
|
||||
{/* LLM Calls Tab */}
|
||||
<TabsContent value="llmCalls" className="m-0 h-full">
|
||||
{loading && (
|
||||
<div className="py-12 flex justify-center">
|
||||
<LoadingSpinner text={t('common.loading')} />
|
||||
</div>
|
||||
)}
|
||||
|
||||
{!loading && data && data.llmCalls && data.llmCalls.length > 0 && (
|
||||
<div className="space-y-3">
|
||||
{data.llmCalls.map((call) => (
|
||||
<div
|
||||
key={call.id}
|
||||
className="border border-gray-200 dark:border-gray-700 rounded-lg p-4 hover:shadow-md transition-all duration-200"
|
||||
>
|
||||
<div className="flex items-start justify-between">
|
||||
<div className="flex-1">
|
||||
<div className="flex items-center gap-2 mb-2">
|
||||
<span
|
||||
className={`text-xs px-2 py-0.5 rounded ${
|
||||
call.status === 'success'
|
||||
? 'bg-green-100 text-green-800 dark:bg-green-900 dark:text-green-200'
|
||||
: 'bg-red-100 text-red-800 dark:bg-red-900 dark:text-red-200'
|
||||
}`}
|
||||
>
|
||||
{call.status}
|
||||
</span>
|
||||
</div>
|
||||
<div className="font-medium text-sm text-gray-700 dark:text-gray-300 mb-2">
|
||||
{call.modelName}
|
||||
</div>
|
||||
<div className="text-xs text-gray-600 dark:text-gray-400 space-y-1">
|
||||
<div className="flex flex-wrap gap-4">
|
||||
<span>
|
||||
{t('monitoring.llmCalls.inputTokens')}:{' '}
|
||||
{call.tokens.input}
|
||||
</span>
|
||||
<span>
|
||||
{t('monitoring.llmCalls.outputTokens')}:{' '}
|
||||
{call.tokens.output}
|
||||
</span>
|
||||
<span>
|
||||
{t('monitoring.llmCalls.totalTokens')}:{' '}
|
||||
{call.tokens.total}
|
||||
</span>
|
||||
<span>
|
||||
{t('monitoring.llmCalls.duration')}:{' '}
|
||||
{call.duration}ms
|
||||
</span>
|
||||
{call.cost && (
|
||||
<span>
|
||||
{t('monitoring.llmCalls.cost')}: $
|
||||
{call.cost.toFixed(4)}
|
||||
</span>
|
||||
)}
|
||||
</div>
|
||||
</div>
|
||||
{call.errorMessage && (
|
||||
<div className="mt-2 text-xs text-red-600 dark:text-red-400">
|
||||
Error: {call.errorMessage}
|
||||
</div>
|
||||
)}
|
||||
</div>
|
||||
<span className="text-xs text-gray-500 dark:text-gray-400 whitespace-nowrap ml-4">
|
||||
{call.timestamp.toLocaleString()}
|
||||
</span>
|
||||
</div>
|
||||
</div>
|
||||
))}
|
||||
</div>
|
||||
)}
|
||||
|
||||
{!loading &&
|
||||
(!data || !data.llmCalls || data.llmCalls.length === 0) && (
|
||||
<div className="text-center text-gray-500 dark:text-gray-400 py-16">
|
||||
<svg
|
||||
className="w-16 h-16 mx-auto mb-4 text-gray-300 dark:text-gray-600"
|
||||
fill="none"
|
||||
viewBox="0 0 24 24"
|
||||
stroke="currentColor"
|
||||
>
|
||||
<path
|
||||
strokeLinecap="round"
|
||||
strokeLinejoin="round"
|
||||
strokeWidth={1.5}
|
||||
d="M9.75 17L9 20l-1 1h8l-1-1-.75-3M3 13h18M5 17h14a2 2 0 002-2V5a2 2 0 00-2-2H5a2 2 0 00-2 2v10a2 2 0 002 2z"
|
||||
/>
|
||||
</svg>
|
||||
<p className="text-base font-medium">
|
||||
{t('monitoring.llmCalls.noData')}
|
||||
</p>
|
||||
</div>
|
||||
)}
|
||||
</TabsContent>
|
||||
</div>
|
||||
</Tabs>
|
||||
</div>
|
||||
);
|
||||
}
|
||||
@@ -1,4 +1,4 @@
|
||||
import { useEffect, useState } from 'react';
|
||||
import { useEffect, useRef, useState, useMemo } from 'react';
|
||||
import { httpClient } from '@/app/infra/http/HttpClient';
|
||||
import { GetPipelineResponseData, Pipeline } from '@/app/infra/entities/api';
|
||||
import {
|
||||
@@ -118,6 +118,14 @@ export default function PipelineFormComponent({
|
||||
},
|
||||
});
|
||||
|
||||
// Track unsaved changes by comparing current form values against a saved snapshot
|
||||
const savedSnapshotRef = useRef<string>('');
|
||||
const watchedValues = form.watch();
|
||||
const hasUnsavedChanges = useMemo(() => {
|
||||
if (!isEditMode || !savedSnapshotRef.current) return false;
|
||||
return JSON.stringify(watchedValues) !== savedSnapshotRef.current;
|
||||
}, [isEditMode, watchedValues]);
|
||||
|
||||
useEffect(() => {
|
||||
// get config schema from metadata
|
||||
httpClient.getGeneralPipelineMetadata().then((resp) => {
|
||||
@@ -139,7 +147,7 @@ export default function PipelineFormComponent({
|
||||
.getPipeline(pipelineId || '')
|
||||
.then((resp: GetPipelineResponseData) => {
|
||||
setIsDefaultPipeline(resp.pipeline.is_default ?? false);
|
||||
form.reset({
|
||||
const loadedValues = {
|
||||
basic: {
|
||||
name: resp.pipeline.name,
|
||||
description: resp.pipeline.description,
|
||||
@@ -149,7 +157,9 @@ export default function PipelineFormComponent({
|
||||
trigger: resp.pipeline.config.trigger,
|
||||
safety: resp.pipeline.config.safety,
|
||||
output: resp.pipeline.config.output,
|
||||
});
|
||||
};
|
||||
form.reset(loadedValues);
|
||||
savedSnapshotRef.current = JSON.stringify(loadedValues);
|
||||
});
|
||||
}
|
||||
}, []);
|
||||
@@ -216,6 +226,7 @@ export default function PipelineFormComponent({
|
||||
httpClient
|
||||
.updatePipeline(pipelineId || '', pipeline)
|
||||
.then(() => {
|
||||
savedSnapshotRef.current = JSON.stringify(form.getValues());
|
||||
onFinish();
|
||||
toast.success(t('pipelines.saveSuccess'));
|
||||
})
|
||||
@@ -509,7 +520,14 @@ export default function PipelineFormComponent({
|
||||
</form>
|
||||
{/* 按钮栏移到 Tabs 外部，始终固定底部 */}
|
||||
{showButtons && (
|
||||
<div className="flex justify-end gap-2 pt-4 border-t mb-0 bg-white dark:bg-black sticky bottom-0 z-10">
|
||||
<div className="flex justify-end items-center gap-2 pt-4 border-t mb-0 bg-white dark:bg-black sticky bottom-0 z-10">
|
||||
{isEditMode && hasUnsavedChanges && (
|
||||
<div className="text-amber-600 dark:text-amber-400 text-sm flex items-center gap-1.5 mr-auto">
|
||||
<span className="inline-block w-1.5 h-1.5 rounded-full bg-amber-500" />
|
||||
{t('pipelines.unsavedChanges')}
|
||||
</div>
|
||||
)}
|
||||
|
||||
{isEditMode && !isDefaultPipeline && (
|
||||
<Button
|
||||
type="button"
|
||||
|
||||
@@ -15,6 +15,7 @@ import {
|
||||
SelectTrigger,
|
||||
SelectValue,
|
||||
} from '@/components/ui/select';
|
||||
import { systemInfo } from '@/app/infra/http';
|
||||
|
||||
export default function PluginConfigPage() {
|
||||
const { t } = useTranslation();
|
||||
@@ -87,6 +88,11 @@ export default function PluginConfigPage() {
|
||||
};
|
||||
|
||||
const handleCreateNew = () => {
|
||||
const maxPipelines = systemInfo.limitation?.max_pipelines ?? -1;
|
||||
if (maxPipelines >= 0 && pipelineList.length >= maxPipelines) {
|
||||
toast.error(t('limitation.maxPipelinesReached', { max: maxPipelines }));
|
||||
return;
|
||||
}
|
||||
setIsEditForm(false);
|
||||
setSelectedPipelineId('');
|
||||
setDialogOpen(true);
|
||||
|
||||
@@ -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">
|
||||
|
||||
@@ -4,6 +4,7 @@ import { useTranslation } from 'react-i18next';
|
||||
import ReactMarkdown from 'react-markdown';
|
||||
import remarkGfm from 'remark-gfm';
|
||||
import rehypeRaw from 'rehype-raw';
|
||||
import rehypeSanitize from 'rehype-sanitize';
|
||||
import rehypeHighlight from 'rehype-highlight';
|
||||
import rehypeSlug from 'rehype-slug';
|
||||
import rehypeAutolinkHeadings from 'rehype-autolink-headings';
|
||||
@@ -51,6 +52,7 @@ export default function PluginReadme({
|
||||
remarkPlugins={[remarkGfm]}
|
||||
rehypePlugins={[
|
||||
rehypeRaw,
|
||||
rehypeSanitize,
|
||||
rehypeHighlight,
|
||||
rehypeSlug,
|
||||
[
|
||||
|
||||
@@ -1,6 +1,13 @@
|
||||
'use client';
|
||||
|
||||
import { useState, useEffect, useCallback, useRef, Suspense } from 'react';
|
||||
import {
|
||||
useState,
|
||||
useEffect,
|
||||
useCallback,
|
||||
useRef,
|
||||
Suspense,
|
||||
useMemo,
|
||||
} from 'react';
|
||||
import { Input } from '@/components/ui/input';
|
||||
import {
|
||||
Select,
|
||||
@@ -23,6 +30,8 @@ import { LoadingSpinner } from '@/components/ui/loading-spinner';
|
||||
import { TagsFilter } from './TagsFilter';
|
||||
import { PluginTag } from '@/app/infra/http/CloudServiceClient';
|
||||
|
||||
import { RecommendationLists, RecommendationList } from './RecommendationLists';
|
||||
|
||||
interface SortOption {
|
||||
value: string;
|
||||
label: string;
|
||||
@@ -50,6 +59,9 @@ function MarketPageContent({
|
||||
const [currentPage, setCurrentPage] = useState(1);
|
||||
const [total, setTotal] = useState(0);
|
||||
const [sortOption, setSortOption] = useState('install_count_desc');
|
||||
const [recommendationLists, setRecommendationLists] = useState<
|
||||
RecommendationList[]
|
||||
>([]);
|
||||
|
||||
const pageSize = 16; // 每页16个，4行x4列
|
||||
const searchTimeoutRef = useRef<NodeJS.Timeout | null>(null);
|
||||
@@ -203,6 +215,20 @@ function MarketPageContent({
|
||||
}
|
||||
};
|
||||
|
||||
// Fetch recommendation lists
|
||||
useEffect(() => {
|
||||
async function fetchRecommendationLists() {
|
||||
try {
|
||||
const response =
|
||||
await getCloudServiceClientSync().getRecommendationLists();
|
||||
setRecommendationLists(response.lists || []);
|
||||
} catch (error) {
|
||||
console.error('Failed to fetch recommendation lists:', error);
|
||||
}
|
||||
}
|
||||
fetchRecommendationLists();
|
||||
}, []);
|
||||
|
||||
// 搜索功能
|
||||
const handleSearch = useCallback(
|
||||
(query: string) => {
|
||||
@@ -271,15 +297,6 @@ function MarketPageContent({
|
||||
const handleInstallPlugin = useCallback(
|
||||
async (author: string, pluginName: string) => {
|
||||
try {
|
||||
// Find the full plugin object from the list
|
||||
const pluginVO = plugins.find(
|
||||
(p) => p.author === author && p.pluginName === pluginName,
|
||||
);
|
||||
if (!pluginVO) {
|
||||
console.error('Plugin not found:', author, pluginName);
|
||||
return;
|
||||
}
|
||||
|
||||
// Fetch full plugin details to get PluginV4 object
|
||||
const response = await getCloudServiceClientSync().getPluginDetail(
|
||||
author,
|
||||
@@ -306,6 +323,39 @@ function MarketPageContent({
|
||||
};
|
||||
}, []);
|
||||
|
||||
// 计算所有推荐插件的 ID 集合
|
||||
const recommendedPluginIds = useMemo(() => {
|
||||
const ids = new Set<string>();
|
||||
recommendationLists.forEach((list) => {
|
||||
list.plugins.forEach((plugin) => {
|
||||
ids.add(`${plugin.author} / ${plugin.name}`);
|
||||
});
|
||||
});
|
||||
return ids;
|
||||
}, [recommendationLists]);
|
||||
|
||||
// 过滤掉已在推荐列表中展示的插件
|
||||
// 仅在显示推荐列表的条件下（无搜索、无筛选、第一页或后续页的累积数据中）进行过滤
|
||||
// 注意：如果用户翻页，我们希望一直保持去重，否则推荐过的插件会在第二页出现
|
||||
// 但是推荐列表只在第一页且无筛选时显示。
|
||||
// 如果用户进行了筛选/搜索，推荐列表不显示，此时不需要去重。
|
||||
const visiblePlugins = useMemo(() => {
|
||||
const showRecommendations =
|
||||
!searchQuery && componentFilter === 'all' && selectedTags.length === 0;
|
||||
|
||||
if (!showRecommendations) {
|
||||
return plugins;
|
||||
}
|
||||
|
||||
return plugins.filter((p) => !recommendedPluginIds.has(p.pluginId));
|
||||
}, [
|
||||
plugins,
|
||||
recommendedPluginIds,
|
||||
searchQuery,
|
||||
componentFilter,
|
||||
selectedTags,
|
||||
]);
|
||||
|
||||
// 加载更多
|
||||
const loadMore = useCallback(() => {
|
||||
if (!isLoadingMore && hasMore) {
|
||||
@@ -494,6 +544,20 @@ function MarketPageContent({
|
||||
ref={scrollContainerRef}
|
||||
className="flex-1 overflow-y-auto px-3 sm:px-4"
|
||||
>
|
||||
{/* Recommendation Lists */}
|
||||
{!searchQuery &&
|
||||
componentFilter === 'all' &&
|
||||
selectedTags.length === 0 &&
|
||||
currentPage === 1 && (
|
||||
<div className="pt-4">
|
||||
<RecommendationLists
|
||||
lists={recommendationLists}
|
||||
tagNames={tagNames}
|
||||
onInstall={handleInstallPlugin}
|
||||
/>
|
||||
</div>
|
||||
)}
|
||||
|
||||
{isLoading ? (
|
||||
<div className="flex items-center justify-center py-12">
|
||||
<LoadingSpinner text={t('market.loading')} />
|
||||
@@ -507,7 +571,7 @@ function MarketPageContent({
|
||||
) : (
|
||||
<>
|
||||
<div className="grid grid-cols-1 sm:grid-cols-2 lg:grid-cols-3 2xl:grid-cols-4 gap-6 pb-6 pt-4">
|
||||
{plugins.map((plugin) => (
|
||||
{visiblePlugins.map((plugin) => (
|
||||
<PluginMarketCardComponent
|
||||
key={plugin.pluginId}
|
||||
cardVO={plugin}
|
||||
|
||||
@@ -0,0 +1,139 @@
|
||||
'use client';
|
||||
|
||||
import { useState } from 'react';
|
||||
import { ChevronLeft, ChevronRight, Star } from 'lucide-react';
|
||||
import { Button } from '@/components/ui/button';
|
||||
import PluginMarketCardComponent from './plugin-market-card/PluginMarketCardComponent';
|
||||
import { PluginMarketCardVO } from './plugin-market-card/PluginMarketCardVO';
|
||||
import { PluginV4 } from '@/app/infra/entities/plugin';
|
||||
import { I18nObject } from '@/app/infra/entities/common';
|
||||
import { extractI18nObject } from '@/i18n/I18nProvider';
|
||||
import { getCloudServiceClientSync } from '@/app/infra/http';
|
||||
import { useTranslation } from 'react-i18next';
|
||||
|
||||
export interface RecommendationList {
|
||||
uuid: string;
|
||||
label: I18nObject;
|
||||
sort_order: number;
|
||||
plugins: PluginV4[];
|
||||
}
|
||||
|
||||
const PAGE_SIZE = 4; // plugins per page in a recommendation row
|
||||
|
||||
function pluginToVO(
|
||||
plugin: PluginV4,
|
||||
t: (key: string) => string,
|
||||
): PluginMarketCardVO {
|
||||
return new PluginMarketCardVO({
|
||||
pluginId: plugin.author + ' / ' + plugin.name,
|
||||
author: plugin.author,
|
||||
pluginName: plugin.name,
|
||||
label: extractI18nObject(plugin.label),
|
||||
description:
|
||||
extractI18nObject(plugin.description) || t('market.noDescription'),
|
||||
installCount: plugin.install_count,
|
||||
iconURL: getCloudServiceClientSync().getPluginIconURL(
|
||||
plugin.author,
|
||||
plugin.name,
|
||||
),
|
||||
githubURL: plugin.repository,
|
||||
version: plugin.latest_version,
|
||||
components: plugin.components,
|
||||
tags: plugin.tags || [],
|
||||
});
|
||||
}
|
||||
|
||||
function RecommendationListRow({
|
||||
list,
|
||||
tagNames,
|
||||
onInstall,
|
||||
}: {
|
||||
list: RecommendationList;
|
||||
tagNames: Record<string, string>;
|
||||
onInstall: (author: string, pluginName: string) => void;
|
||||
}) {
|
||||
const { t } = useTranslation();
|
||||
const [page, setPage] = useState(0);
|
||||
|
||||
const plugins = list.plugins || [];
|
||||
const totalPages = Math.ceil(plugins.length / PAGE_SIZE);
|
||||
const start = page * PAGE_SIZE;
|
||||
const visiblePlugins = plugins.slice(start, start + PAGE_SIZE);
|
||||
|
||||
if (plugins.length === 0) return null;
|
||||
|
||||
return (
|
||||
<div className="mb-6">
|
||||
<div className="flex items-center justify-between mb-3">
|
||||
<div className="flex items-center gap-2">
|
||||
<Star className="w-4 h-4 text-yellow-500" />
|
||||
<h3 className="font-semibold text-base">
|
||||
{extractI18nObject(list.label)}
|
||||
</h3>
|
||||
</div>
|
||||
{totalPages > 1 && (
|
||||
<div className="flex items-center gap-1">
|
||||
<Button
|
||||
variant="ghost"
|
||||
size="sm"
|
||||
onClick={() => setPage((p) => Math.max(0, p - 1))}
|
||||
disabled={page === 0}
|
||||
className="h-7 w-7 p-0"
|
||||
>
|
||||
<ChevronLeft className="w-4 h-4" />
|
||||
</Button>
|
||||
<span className="text-xs text-muted-foreground px-1">
|
||||
{page + 1} / {totalPages}
|
||||
</span>
|
||||
<Button
|
||||
variant="ghost"
|
||||
size="sm"
|
||||
onClick={() => setPage((p) => Math.min(totalPages - 1, p + 1))}
|
||||
disabled={page >= totalPages - 1}
|
||||
className="h-7 w-7 p-0"
|
||||
>
|
||||
<ChevronRight className="w-4 h-4" />
|
||||
</Button>
|
||||
</div>
|
||||
)}
|
||||
</div>
|
||||
<div className="grid grid-cols-1 sm:grid-cols-2 lg:grid-cols-3 2xl:grid-cols-4 gap-6">
|
||||
{visiblePlugins.map((plugin) => (
|
||||
<PluginMarketCardComponent
|
||||
key={plugin.author + ' / ' + plugin.name}
|
||||
cardVO={pluginToVO(plugin, t)}
|
||||
tagNames={tagNames}
|
||||
onInstall={onInstall}
|
||||
/>
|
||||
))}
|
||||
</div>
|
||||
{totalPages > 1 && <div className="border-b border-border mt-6" />}
|
||||
</div>
|
||||
);
|
||||
}
|
||||
|
||||
export function RecommendationLists({
|
||||
lists,
|
||||
tagNames,
|
||||
onInstall,
|
||||
}: {
|
||||
lists: RecommendationList[];
|
||||
tagNames: Record<string, string>;
|
||||
onInstall: (author: string, pluginName: string) => void;
|
||||
}) {
|
||||
if (!lists || lists.length === 0) return null;
|
||||
|
||||
return (
|
||||
<div className="mt-6">
|
||||
{lists.map((list) => (
|
||||
<RecommendationListRow
|
||||
key={list.uuid}
|
||||
list={list}
|
||||
tagNames={tagNames}
|
||||
onInstall={onInstall}
|
||||
/>
|
||||
))}
|
||||
<div className="border-b border-border mb-6" />
|
||||
</div>
|
||||
);
|
||||
}
|
||||
@@ -110,7 +110,7 @@ export default function PluginMarketCardComponent({
|
||||
<line x1="12" y1="15" x2="12" y2="3" />
|
||||
</svg>
|
||||
<div className="text-xs sm:text-sm text-[#2563eb] dark:text-[#5b8def] font-medium whitespace-nowrap">
|
||||
{cardVO.installCount.toLocaleString()}
|
||||
{cardVO.installCount?.toLocaleString() ?? '0'}
|
||||
</div>
|
||||
</div>
|
||||
|
||||
|
||||
@@ -453,7 +453,10 @@ export default function MCPFormDialog({
|
||||
onSuccess?.();
|
||||
} catch (error) {
|
||||
console.error('Failed to save MCP server:', error);
|
||||
toast.error(isEditMode ? t('mcp.updateFailed') : t('mcp.createFailed'));
|
||||
const errMsg = (error as CustomApiError).msg || '';
|
||||
toast.error(
|
||||
(isEditMode ? t('mcp.updateFailed') : t('mcp.createFailed')) + errMsg,
|
||||
);
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
@@ -186,6 +186,28 @@ export default function PluginConfigPage() {
|
||||
setFetchingAssets(false);
|
||||
}
|
||||
|
||||
async function checkExtensionsLimit(): Promise<boolean> {
|
||||
const maxExtensions = systemInfo.limitation?.max_extensions ?? -1;
|
||||
if (maxExtensions < 0) return true;
|
||||
try {
|
||||
const [pluginsResp, mcpResp] = await Promise.all([
|
||||
httpClient.getPlugins(),
|
||||
httpClient.getMCPServers(),
|
||||
]);
|
||||
const total =
|
||||
(pluginsResp.plugins?.length ?? 0) + (mcpResp.servers?.length ?? 0);
|
||||
if (total >= maxExtensions) {
|
||||
toast.error(
|
||||
t('limitation.maxExtensionsReached', { max: maxExtensions }),
|
||||
);
|
||||
return false;
|
||||
}
|
||||
} catch {
|
||||
// If we can't check, let backend handle it
|
||||
}
|
||||
return true;
|
||||
}
|
||||
|
||||
async function fetchGithubReleases() {
|
||||
if (!githubURL.trim()) {
|
||||
toast.error(t('plugins.enterRepoUrl'));
|
||||
@@ -328,6 +350,8 @@ export default function PluginConfigPage() {
|
||||
return;
|
||||
}
|
||||
|
||||
if (!(await checkExtensionsLimit())) return;
|
||||
|
||||
setModalOpen(true);
|
||||
setPluginInstallStatus(PluginInstallStatus.INSTALLING);
|
||||
setInstallError(null);
|
||||
@@ -336,7 +360,8 @@ export default function PluginConfigPage() {
|
||||
[t, pluginSystemStatus, installPlugin],
|
||||
);
|
||||
|
||||
const handleFileSelect = useCallback(() => {
|
||||
const handleFileSelect = useCallback(async () => {
|
||||
if (!(await checkExtensionsLimit())) return;
|
||||
if (fileInputRef.current) {
|
||||
fileInputRef.current.click();
|
||||
}
|
||||
@@ -633,7 +658,8 @@ export default function PluginConfigPage() {
|
||||
{activeTab === 'mcp-servers' ? (
|
||||
<>
|
||||
<DropdownMenuItem
|
||||
onClick={() => {
|
||||
onClick={async () => {
|
||||
if (!(await checkExtensionsLimit())) return;
|
||||
setActiveTab('mcp-servers');
|
||||
setIsEditMode(false);
|
||||
setEditingServerName(null);
|
||||
@@ -661,7 +687,8 @@ export default function PluginConfigPage() {
|
||||
{t('plugins.uploadLocal')}
|
||||
</DropdownMenuItem>
|
||||
<DropdownMenuItem
|
||||
onClick={() => {
|
||||
onClick={async () => {
|
||||
if (!(await checkExtensionsLimit())) return;
|
||||
setInstallSource('github');
|
||||
setPluginInstallStatus(PluginInstallStatus.WAIT_INPUT);
|
||||
setInstallError(null);
|
||||
@@ -683,7 +710,8 @@ export default function PluginConfigPage() {
|
||||
</TabsContent>
|
||||
<TabsContent value="market" className="flex-1 overflow-y-auto mt-0">
|
||||
<MarketPage
|
||||
installPlugin={(plugin: PluginV4) => {
|
||||
installPlugin={async (plugin: PluginV4) => {
|
||||
if (!(await checkExtensionsLimit())) return;
|
||||
setInstallSource('marketplace');
|
||||
setInstallInfo({
|
||||
plugin_author: plugin.author,
|
||||
|
||||
@@ -240,13 +240,21 @@ export interface PluginReorderElement {
|
||||
}
|
||||
|
||||
// system
|
||||
export interface SystemLimitation {
|
||||
max_bots: number;
|
||||
max_pipelines: number;
|
||||
max_extensions: number;
|
||||
}
|
||||
|
||||
export interface ApiRespSystemInfo {
|
||||
debug: boolean;
|
||||
version: string;
|
||||
edition: string;
|
||||
cloud_service_url: string;
|
||||
enable_marketplace: boolean;
|
||||
allow_modify_login_info: boolean;
|
||||
disable_models_service: boolean;
|
||||
limitation: SystemLimitation;
|
||||
}
|
||||
|
||||
export interface ApiRespPluginSystemStatus {
|
||||
|
||||
Some files were not shown because too many files have changed in this diff Show More
Reference in New Issue
Block a user