MuseBot

This repository provides a Chat bot (Telegram, Discord, Slack, Lark（飞书），钉钉, 企业微信, QQ, 微信) that integrates with LLM API to provide AI-powered responses. The bot supports openai deepseek gemini openrouter orcarouter LLMs, making interactions feel more natural and dynamic.
中文文档
Китайская документация

Thanks

感谢阮一峰老师的weekly，很荣幸能登榜：https://github.com/ruanyf/weekly
感谢linux.do 社区，佬友们很给力，给一个我的介绍贴链接：https://linux.do/t/topic/1128110
Thanks to the Reddit community as well, even though a few of my subreddits got banned 😅: https://www.reddit.com/

🚀 Features

• 🤖 AI Responses: Uses LLM API for chatbot replies.
• ⏳ Streaming Output: Sends responses in real-time to improve user experience.
• 🏗 Easy Deployment: Run locally or deploy to a cloud server.
• 👀 Identify Image: use image to communicate with LLM, see doc.
• 🎺 Support Voice: use voice to communicate with LLM, see doc.
• 🐂 Function Call: transform mcp protocol to function call, see doc.
• 🌊 RAG: Support Rag to fill context, see doc.
• 🌞 AdminPlatform: Use platform to manage MuseBot, see doc.
• 🌛 Register: With the service registration module, robot instances can be automatically registered to the registration center doc
• 🌈 Metrics: Support Metrics for monitoring, see doc.
• 🐶 Cron: Support Cron to trigger LLM, see doc.

Usage Video

easiest way to use: https://www.youtube.com/watch?v=4UHoKRMfNZg
deepseek: https://www.youtube.com/watch?v=kPtNdLjKVn0
gemini: https://www.youtube.com/watch?v=7mV9RYvdE6I
chatgpt: https://www.youtube.com/watch?v=G_DZYMvd5Ug

📸 Support Platform

Platform	Supported	Description	Docs / Links
🟦 Telegram	✅	Supports Telegram bot (go-telegram-bot-api based, handles commands, inline buttons, ForceReply, etc.)	Docs
🌈 Discord	✅	Supports Discord bot	Docs
🌛 Web API	✅	Provides HTTP/Web API for interacting with LLM (great for custom frontends/backends)	Docs
🔷 Slack	✅	Supports Slack (Socket Mode / Events API / Block Kit interactions)	Docs
🟣 Lark (Feishu)	✅	Supports Lark long connection & message handling (based on larksuite SDK, with image/audio download & message update)	Docs
🆙 DingDing	✅	Supports Dingding long connection	Docs
⚡️ Work WeChat	✅	Support Work WeChat http callback to trigger LLM	Docs
🌞 QQ	✅	Support QQ http callback to trigger LLM	Docs
🚇 Wechat	✅	Support Wechat http callback to trigger LLM	Docs

Supported Large Language Models

Model	Provider	Text Generation	Image Generation	Video Generation	Recognize Photo	TTS	Link
🌟 Gemini	Google	✅	✅	✅	✅	✅	doc
💬 ChatGPT	OpenAI	✅	✅	❌	✅	✅	doc
🐦 Doubao	ByteDance	✅	✅	✅	✅	✅	doc
🐦 Qwen	Aliyun	✅	✅	✅	✅	✅	doc
🧠 DeepSeek	DeepSeek	✅	❌	❌	❌	❌	doc
⚙️ 302.AI	302.AI	✅	✅	✅	✅	❌	doc
🌐 OpenRouter	OpenRouter	✅	✅	❌	✅	❌	doc
🛡️ OrcaRouter	OrcaRouter	✅	✅	❌	✅	❌	doc
🌐 ChatAnywhere	ChatAnywhere	✅	✅	❌	✅	❌	doc

🤖 Text Example

🎺 Multimodal Example

📥 Installation

1. Clone the repository

   git clone https://github.com/yincongcyincong/MuseBot.git
   cd MuseBot
   

2. Install dependencies

    go mod tidy
   

3. Set up environment variables

    export TELEGRAM_BOT_TOKEN="your_telegram_bot_token"
    export DEEPSEEK_TOKEN="your_deepseek_api_key"
   

🚀 Usage

Run the bot locally:

 go run main.go -telegram_bot_token=telegram-bot-token -deepseek_token=deepseek-auth-token

Use docker

  docker pull jackyin0822/musebot:latest
  chmod 777 /home/user/data
  docker run -d -v /home/user/data:/app/data -e TELEGRAM_BOT_TOKEN="telegram-bot-token" -e DEEPSEEK_TOKEN="deepseek-auth-token" -p 36060:36060 --name my-bot  jackyin0822/MuseBot:latest

 ALIYUN:
 docker pull crpi-i1dsvpjijxpgjgbv.cn-hangzhou.personal.cr.aliyuncs.com/jackyin0822/musebot:latest
 chmod 777 /home/user/data
  docker run -d -v /home/user/data:/app/data -e TELEGRAM_BOT_TOKEN="telegram-bot-token" -e DEEPSEEK_TOKEN="deepseek-auth-token" -p 36060:36060 --name my-bot  crpi-i1dsvpjijxpgjgbv.cn-hangzhou.personal.cr.aliyuncs.com/jackyin0822/musebot:latest

command: (doc)[https://github.com/yincongcyincong/MuseBot/blob/main/static/doc/param_conf.md]

⚙️ Configuration

You can configure the bot via environment variables:

Here’s the English version of your environment variable table: If you use parameter. Please use lower letter and underscore. for example: ./MuseBot -telegram_bot_token=xxx

Variable Name	Description	Default Value
TELEGRAM_BOT_TOKEN	Telegram bot token	-
DISCORD_BOT_TOKEN	Discord bot token	-
SLACK_BOT_TOKEN	Slack bot token	-
SLACK_APP_TOKEN	Slack app-level token	-
LARK_APP_ID	Lark (Feishu) App ID	-
LARK_APP_SECRET	Lark (Feishu) App Secret	-
DING_CLIENT_ID	DingTalk App Key / Client ID	-
DING_CLIENT_SECRET	DingTalk App Secret	-
DING_TEMPLATE_ID	DingTalk template message ID	-
COM_WECHAT_TOKEN	WeCom (Enterprise WeChat) token	-
COM_WECHAT_ENCODING_AES_KEY	WeCom EncodingAESKey	-
COM_WECHAT_CORP_ID	WeCom CorpID	-
COM_WECHAT_SECRET	WeCom App Secret	-
COM_WECHAT_AGENT_ID	WeCom Agent ID	-
WECHAT_APP_ID	WeChat Official Account AppID	-
WECHAT_APP_SECRET	WeChat Official Account AppSecret	-
WECHAT_ENCODING_AES_KEY	WeChat Official Account EncodingAESKey	-
WECHAT_TOKEN	WeChat Official Account Token	-
WECHAT_ACTIVE	Whether to enable WeChat message listening (true/false)	false
QQ_APP_ID	QQ Open Platform AppID	-
QQ_APP_SECRET	QQ Open Platform AppSecret	-
QQ_ONEBOT_RECEIVE_TOKEN	Token for ONEBOT → MuseBot event messages	MuseBot
QQ_ONEBOT_SEND_TOKEN	Token for MuseBot → ONEBOT message sending	MuseBot
QQ_ONEBOT_HTTP_SERVER	ONEBOT HTTP server address	http://127.0.0.1:3000
DEEPSEEK_TOKEN	DeepSeek API key	-
OPENAI_TOKEN	OpenAI API key	-
GEMINI_TOKEN	Google Gemini API token	-
OPEN_ROUTER_TOKEN	OpenRouter token doc	-
ORCAROUTER_TOKEN	OrcaRouter API key doc	-
ALIYUN_TOKEN	Aliyun Bailian token doc	-
AI_302_TOKEN	302.AI token doc	-
VOL_TOKEN	Volcano Engine general token doc	-
VOLC_AK	Volcano Engine multimedia access key doc	-
VOLC_SK	Volcano Engine multimedia secret key doc	-
ERNIE_AK	Baidu ERNIE large model AK doc	-
ERNIE_SK	Baidu ERNIE large model SK doc	-
CUSTOM_URL	Custom LLM API endpoint	https://api.deepseek.com/
TYPE	LLM type (deepseek/openai/gemini/openrouter/vol/302-ai/chatanywhere/orcarouter)	deepseek
MEDIA_TYPE	Media generation source (openai/gemini/vol/openrouter/aliyun/302-ai/orcarouter)	vol
DB_TYPE	Database type (sqlite3/mysql)	sqlite3
DB_CONF	Database config path or connection string	./data/muse_bot.db
LLM_PROXY	LLM network proxy (e.g. http://127.0.0.1:7890)	-
ROBOT_PROXY	Bot network proxy (e.g. http://127.0.0.1:7890)	-
LANG	Language (en/zh)	en
TOKEN_PER_USER	Max tokens allowed per user, 0 means no limit	10000
MAX_USER_CHAT	Maximum concurrent chats per user	2
HTTP_HOST	MuseBot HTTP server port	:36060
USE_TOOLS	Enable function-calling tools (true/false)	false
MAX_QA_PAIR	Max number of question-answer pairs to keep as context	100
CHARACTER	AI personality description	-
CRT_FILE	HTTPS certificate file path	-
KEY_FILE	HTTPS private key file path	-
CA_FILE	HTTPS CA certificate file path	-
ADMIN_USER_IDS	Comma-separated list of admin user IDs	-
ALLOWED_USER_IDS	Comma-separated user IDs allowed to use the bot; empty = all allowed; 0 = all banned	-
ALLOWED_GROUP_IDS	Comma-separated group IDs allowed to use the bot; empty = all allowed; 0 = all banned	-
BOT_NAME	Bot name	MuseBot
CHAT_ANY_WHERE_TOKEN	ChatAnyWhere platform token	-
SMART_MODE	Automatically check what you want to generate (txt/photo/video)	true
SEND_MCP_RES	send mcp result to user	false
DEFAULT_MODEL	default txt model	-

CUSTOM_URL

If you are using a self-deployed llm, you can set CUSTOM_URL to route requests to your self-deployed llm.

DB_TYPE

support sqlite3 or mysql

DB_CONF

if DB_TYPE is sqlite3, give a file path, such as ./data/telegram_bot.db if DB_TYPE is mysql, give a mysql link, such as root:admin@tcp(127.0.0.1:3306)/dbname?charset=utf8mb4&parseTime=True&loc=Local, database must be created.

LANG

choose a language for bot, English (en), Chinese (zh), Russian (ru).

other config

deepseek_conf
photo_conf
video_conf
audio_conf

Command

/clear $clear

clear all of your communication record with deepseek. this record use for helping deepseek to understand the context.

/retry $retry

retry last question.

/txt_type /photo_type /video_type /rec_type $txt_type$photo_type $video_type$rec_type

choose txt/photo/video/recognize model type.

/txt_model /img_model /video_model /rec_model $txt_model$img_model $video_model$rec_model

choose txt/photo/video/recognize model.

/mode $mode

show current model type and model.

/state $state

calculate one user token usage.

/photo /edit_photo $photo$edit_photo

/edit_photo will update you photo base on your description.

/video $video

/chat $chat

allows the bot to chat through /chat command in groups, without the bot being set as admin of the group.

/help $help

/task $task

multi agent communicate with each other!

Deployment

Deploy with Docker

1. Build the Docker image

    docker build -t MuseBot .
   

2. Run the container

     docker run -d -v /home/user/xxx/data:/app/data -e TELEGRAM_BOT_TOKEN="telegram-bot-token" -e DEEPSEEK_TOKEN="deepseek-auth-token" --name my-bot MuseBot
   

Contributing

Feel free to submit issues and pull requests to improve this bot. 🚀

group

telegram-group: https://t.me/+WtaMcDpaMOlhZTE1 , or you can have a try robot Guanwushan_bot. every body have 10000 token to try this bot, please give me a star!

QQ群：1031411708

License

MIT License © 2025 jack yin