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.

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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
What is this?An open-source, production-grade platform for building AI-powered instant messaging bots: it connects LLMs to chat platforms so you can ship agents that converse, execute tasks, and plug into your workflows.
Is it a hosted service I sign up for, or something I self-host?Both: there is a zero-deployment LangBot Cloud, but the main path is self-hosting — you deploy the platform and manage, configure, and monitor your bots from a browser-based web panel, no YAML editing required.
How do I get a bot running?Try the public live demo first (sign in with [email protected] / langbot123456 — keep sensitive data out of it). To self-host: a one-line launch that requires uv, Docker Compose, or one-click cloud deploy; Docker, Manual, BTPanel, and Kubernetes are listed as further options.
Am I locked into one AI provider?No — OpenAI, Anthropic, DeepSeek, Gemini, xAI, Moonshot, and Zhipu AI are built in, local models run through Ollama and LM Studio, and there are gateways like SiliconFlow and 302.AI.
Is it really ready for production, or more of a toy?Production is the design goal: access control, rate limiting, sensitive word filtering, comprehensive monitoring, and exception handling are built in, and the project is described as trusted by enterprises.
What do people actually build with it?The README calls out customer-support agents answering from a knowledge base on Slack/Discord/Telegram, internal n8n/Dify workflows wired into WeCom/DingTalk, AI moderation for QQ/Discord communities, and one bot present across all platforms.
Which chat platforms can a bot live on?Discord, Telegram, Slack, LINE, QQ, WeChat, WeCom, Lark, DingTalk, KOOK, Matrix, Satori, and Email — and Matrix bridges to Signal, WhatsApp, Messenger, iMessage, Google Chat, IRC, XMPP, and more.
Can I run several different bots for different scenarios?Yes — the multi-pipeline architecture lets different bots serve different scenarios, each with its own monitoring and exception handling.
Can I extend it with plugins?There is a plugin ecosystem with hundreds of plugins, an event-driven architecture, and component extensions, plus MCP protocol support. Plugins, MCP servers, and skills are distributed through the LangBot Space marketplace.
Can coding agents like Claude Code operate LangBot for me?Yes, it is agent-friendly by design: a built-in MCP server at /mcp mirrors the HTTP API so an agent can manage bots, pipelines, plugins, and models with your API key, and the repo ships a skills/ directory plus AGENTS.md describing architecture and conventions.
How does the knowledge base (RAG) side work?RAG is built in, with deep integration to Dify, Coze, n8n, Langflow, Deerflow, and Weknora, so bots can answer questions from your own documents.
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