Larkagentx

🚀 LarkAgentX Project Documentation

LarkAgentX is a powerful robotic agent system built on the Feishu platform. It leverages large language models (LLMs) for function calls and persists messages in a database. Designed to enhance internal corporate communication efficiency, this system supports command execution in both group and private chat environments.

🚀 Quick Start

After the system starts:

1. Initialize the MCP server.
2. Connect to the Feishu API and use your Feishu account as an AI assistant.
3. Monitor incoming messages.
4. Process and execute function calls initiated by the large model via Feishu.
5. Store messages in the MySQL database.

✨ Features

• Intelligent Function Call: Trigger preset function operations by parsing natural language or commands input by users.
• Message Persistence: All conversation records are stored in a MySQL database for easy future reference and analysis.
• Multi - Environment Support: Provide Docker image building and running methods to simplify the deployment process.
• Feishu Robot Integration: Use Feishu accounts directly as agents without additional robot identity configuration.

📦 Installation

Direct Run Method

python main.py

Docker Method (Recommended)

Method 1: Build the Image Individually

# Build the image 
docker build -t feishuapp .

# Run the container. It needs an external MySQL and connects to the host MySQL through the Docker gateway. It is recommended to use --env - file
docker run -it feishuapp bash

Method 2: Start the Service Using Docker Compose

# Start all services (application and database)
docker-compose up -d

# View logs
docker-compose logs -f

# Stop all services
docker-compose down

📚 Documentation

Configuration Instructions

Copy the .env.example file and name it .env. Modify the following configurations:

# Database settings
DB_HOST=localhost
DB_PORT=3306
DB_USER=root
DB_PASSWORD=123456
DB_NAME=lark_messages

# Feishu's Cookie settings - Only need to configure LARK_COOKIE, no need for Feishu robots
LARK_COOKIE=""

# Trigger prefix for function calls (Messages starting with FUNCTION_TRIGGER_FLAG will be parsed by the large model. All messages will be recorded in the database, regardless of whether they start with this prefix)
FUNCTION_TRIGGER_FLAG="/run"

# Prefix for robot messages (Not currently in use)
AI_BOT_PREFIX="Lark AI Bot:"

# OpenAI API configuration. By default, it uses Tongyi Qianwen. Any large - model provider compatible with OpenAI can be used.
OPENAI_API_KEY=""
OPENAI_API_BASE_URL="https://dashscope.aliyuncs.com/compatible - mode/v1"
OPENAI_API_MODEL="qwen - plus"

Usage Guide

Starting the Application

• Direct Run

  python main.py
  

• Using Docker Compose

  docker-compose up -d
  

🔧 Technical Details

Database Structure

All conversation records will be stored in the MySQL database. The specific table structure is as follows:

🤝 Project Contribution

We welcome community developers to contribute to the project!

• Submit an Issue to report problems.
• Fork the code repository.
• Open a Pull Request to fix bugs or add new features.

📄 License

This project adheres to the MIT open - source license. For specific terms, please refer to the LICENSE file.

📞 Contact

If you need to contact the development team, please send an email to: contact@larkagentx.com