langbot-app/LangBot

⭐ 15,998  ·  Python  ·  GitHub Repo

LangBot solves the problem of building and deploying AI-powered instant messaging bots across multiple platforms from a single codebase. It stands out by offering a production-grade, open-source platform with a plugin ecosystem, web management panel, and deep integrations with major LLMs and LLMOps tools like Dify, Coze, and n8n, making it easy to create intelligent, multi-platform agents without YAML editing.

agent coze deepseek dify dingtalk discord feishu kook

1-Sentence Summary

One codebase, every major chat platform, production-grade AI agents with plugins and a web panel.

🔥 Key Capabilities & USP

• Universal Platform Support: LangBot solves the fragmentation nightmare of maintaining separate bots for Discord, Telegram, Slack, LINE, WeChat, DingTalk, Feishu, QQ, and more. One codebase deploys to all.
• Deep LLM & Tool Orchestration: Integrates natively with ChatGPT, DeepSeek, Dify, Coze, n8n, Langflow, Ollama, and dozens more. This eliminates the vendor lock-in and integration hell of wiring AI backends to chat platforms.
• Plugin Ecosystem & MCP Protocol: Hundreds of plugins and an event-driven architecture allow for unlimited extensibility without forking the core. The MCP protocol support future-proofs the bot against new tool standards.
• Web Management Panel: A browser-based UI for configuration, monitoring, and management eliminates the need for YAML editing, dramatically lowering the operational overhead for teams.
• Production-Grade Guardrails: Built-in access control, rate limiting, sensitive word filtering, and comprehensive monitoring mean you can trust this bot in customer-facing or enterprise environments without building safety rails from scratch.

Technical Architecture

Component	Detail
Core Language	Python 3.10 - 3.13
Architecture Pattern	Multi-pipeline, event-driven
Deployment	Docker Compose (primary), manual deploy
Extensibility	Plugin system, component extensions, MCP protocol
AI Integration	Native connectors to OpenAI, DeepSeek, Dify, Coze, n8n, Langflow, Ollama, SiliconFlow, and more
Management	Web-based admin panel (no YAML editing)
Monitoring	Built-in exception handling, rate limiting, access control

The multi-pipeline architecture is the standout feature here: it allows different bots for different scenarios (e.g., a customer support agent on Telegram, a community manager on Discord) to run from the same codebase with independent configurations.

Quick Start Guide

The fastest way to get started is via uvx (requires Python and uv):

uvx langbot

For a full production deployment with Docker:

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

After startup, access the web management panel at http://localhost:8024 to configure your bot instances, connect LLM providers, and enable chat platforms.

Pros, Cons & Use Cases

Pros

• Truly multi-platform – one bot, all major chat apps
• Massive ecosystem – integrates with every major LLM and LLMOps tool
• Production-ready – access control, rate limiting, monitoring out of the box
• Extensible – plugin system and MCP protocol for custom functionality
• Web UI – no YAML editing required for configuration

Cons

• Self-hosting required – requires Docker or manual deployment knowledge
• Cloud version limitations – free tier may have usage caps
• Demo environment – public demo is not suitable for sensitive data
• Python dependency – non-Python teams may find customization challenging

Who should NOT use this?

• Non-technical users who cannot self-host or manage a Docker-based deployment
• Teams needing a single-platform bot (e.g., only Discord) – simpler tools exist
• Projects requiring real-time, low-latency responses – the multi-pipeline architecture adds overhead
• Organizations with strict data sovereignty – cloud version may not meet compliance requirements

Ideal Use Cases

• Enterprise customer support agents deployed across WeChat, Telegram, and Slack
• Community management bots for Discord, QQ, and KOOK with AI moderation
• Internal tooling for teams using DingTalk, Feishu, or Lark
• Multi-platform AI assistants integrated with Dify, Coze, or n8n workflows
• Developer sandbox for prototyping agentic bots before production deployment

Community & Activity

LangBot is on a strong growth trajectory with 15,998 stars and active development as of May 2026. The project has a vibrant ecosystem with hundreds of plugins and deep integrations across the AI tooling landscape. The last update is recent (May 2026), indicating an actively maintained codebase. The combination of production-grade features, massive platform support, and a growing plugin ecosystem makes this one of the most compelling open-source bot platforms available today. If you're building multi-platform AI agents, this is the project to watch.