LangBot README

The project's README from github.com/langbot-app/LangBot. As one markdown file: README.md.

LangBot

LangBot - Easy-to-use global IM bot platform designed for the LLM era | Product Hunt

Production-grade platform for building agentic IM bots.

Quickly build, debug, and ship AI bots to Slack, Discord, Telegram, WeChat, and more.

English / 简体中文 / 繁體中文 / 日本語 / Español / Français / 한국어 / Русский / Tiếng Việt

Discord Ask DeepWiki GitHub release (latest by date) python GitHub stars

Website | Features | Docs | API | Cloud | Plugin Market | Roadmap


What is LangBot?

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.

LangBot web management dashboard — real-time monitoring of message volume, model calls, success rate and active sessions

Key Capabilities

→ Learn more about all features

📍 Practical guides: deploy a multi-platform AI bot in 5 minutes, connect DeepSeek to WeChat, Discord, and Telegram, run a Dify Agent in Discord, Telegram, and Slack, and build an n8n-powered chatbot.


😎 Stay Updated

Click the Star and Watch buttons in the top-right corner of the repository to get the latest updates.

star gif

Quick Start

LangBot Cloud — Zero deployment, ready to use.

One-Line Launch

uvx langbot

Requires uv. Visit http://localhost:5300 — done.

Docker Compose

git clone https://github.com/langbot-app/LangBot
cd LangBot/docker
docker compose --profile all up -d

One-Click Cloud Deploy

Deploy on Zeabur Deploy on Railway

More options: Docker · Manual · BTPanel · Kubernetes


Live Demo

Try it now: https://demo.langbot.dev/

Note: Public demo environment. Do not enter sensitive information.


Supported Platforms

Platform Status Notes
Discord ✅ Official
Telegram ✅ Official
Slack ✅ Official
LINE ✅ Official
QQ ✅ Personal & Official API (Channel, DM, Group)
WeCom ✅ Enterprise WeChat, External CS, AI Bot
WeChat ✅ Personal & Official Account
Lark ✅ Official
DingTalk ✅ Official
KOOK ✅ Official
Satori ✅
Email ✅ Matrix, Satori
Matrix ✅ Supports multiple bridged platforms such as Signal, WhatsApp, Messenger, iMessage, Mattermost, Google Chat, IRC, XMPP, Zulip, and more

Supported LLMs & Integrations

Provider Type Status
OpenAI LLM ✅
Anthropic LLM ✅
DeepSeek LLM ✅
Google Gemini LLM ✅
xAI LLM ✅
Moonshot LLM ✅
Zhipu AI LLM ✅
Ollama Local LLM ✅
LM Studio Local LLM ✅
Dify LLMOps ✅
MCP Protocol ✅
SiliconFlow Gateway ✅
Aliyun Bailian Gateway ✅
Volc Engine Ark Gateway ✅
ModelScope Gateway ✅
GiteeAI Gateway ✅
CompShare GPU Platform ✅
PPIO GPU Platform ✅
ShengSuanYun GPU Platform ✅
接口 AI Gateway ✅
302.AI Gateway ✅
Qiniu Gateway ✅

→ View all integrations


Why LangBot?

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

Built for AI Agents 🤖

LangBot is agent-friendly by design — your coding agents (Claude Code, Codex, Copilot, Cursor, …) can operate, extend, and deploy LangBot with first-class support:

Cloud / Marketplace: LangBot Space also exposes an MCP server so agents can search and inspect the plugin / MCP / skill marketplace, authenticated with a Personal Access Token.


Community

Discord


Contributors

Thanks to all contributors who have helped make LangBot better:

LangBot (langbot-app/LangBot)

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18.2K ·GitHub
这是什么?一个开源、生产级的 AI 即时通讯机器人搭建平台:它把大语言模型接入各类聊天平台,让你可以发布能对话、能执行任务、能接入你工作流程的智能体。
它是注册就能用的托管服务,还是要自己部署的?两者都有:有一个零部署的 LangBot 云端版,但主要方式是自己部署——你把平台部署起来后,通过网页面板在浏览器里管理、配置和监控你的机器人,不需要编辑 YAML。
我怎么让一个机器人跑起来?可以先试试公开的在线演示(用 [email protected] / langbot123456 登录——不要在里面放敏感数据)。自己部署的话:有需要 uv 的一行启动命令、Docker Compose,或一键云端部署;此外还列有 Docker、手动安装、宝塔面板和 Kubernetes 等方式。
我是不是只能用一家 AI 服务商?不是——内置了 OpenAI、Anthropic、DeepSeek、Gemini、xAI、Moonshot 和智谱 AI,本地模型可以通过 Ollama 和 LM Studio 运行,还有 SiliconFlow、302.AI 这类网关。
它真的能用于生产环境,还是个玩具?生产环境就是它的设计目标:内置了访问控制、限流、敏感词过滤、完善的监控和异常处理,项目介绍中称其受到企业信赖。
大家实际用它做什么?README 里提到的例子有:在 Slack/Discord/Telegram 上基于知识库回答的客服机器人、接入企业微信/钉钉的 n8n/Dify 内部工作流、面向 QQ/Discord 社区的 AI 审核机器人,以及一个机器人同时覆盖所有平台。
机器人可以跑在哪些聊天平台上?Discord、Telegram、Slack、LINE、QQ、微信、企业微信、飞书、钉钉、KOOK、Matrix、Satori 和电子邮件——Matrix 还能桥接到 Signal、WhatsApp、Messenger、iMessage、Google Chat、IRC、XMPP 等更多平台。
我可以针对不同场景运行多个不同的机器人吗?可以——多流水线架构让不同的机器人服务不同的场景,每个都有各自的监控和异常处理。
我可以用插件扩展它吗?它有包含数百个插件的插件生态、事件驱动架构和组件扩展机制,还支持 MCP 协议。插件、MCP 服务器和技能都通过 LangBot Space 市场分发。
像 Claude Code 这样的编程智能体能帮我操作 LangBot 吗?可以,它天生对智能体友好:内置了一个 /mcp 的 MCP 服务器,镜像了 HTTP API,智能体可以用你的 API 密钥来管理机器人、流水线、插件和模型;仓库里还带有 skills/ 目录和介绍架构与约定的 AGENTS.md。
知识库(RAG)这块是怎么运作的?RAG 是内置功能,并与 Dify、Coze、n8n、Langflow、Deerflow 和 Weknora 深度集成,让机器人能根据你自己的文档回答问题。
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