ParsaLLM Chatbot

A powerful LangChain-powered chatbot built with Python, featuring real-time communication through MCP (Multi-Channel Platform) integration.

Features

• 🤖 Intelligent responses using LangChain and LLMs
• 🔄 Real-time communication via MCP
• 🎯 Modular and extensible architecture
• 📝 Message analysis and processing
• 🔧 Easy configuration and deployment

Project Structure

parsallm/
├── src/
│   ├── __init__.py
│   ├── bot.py
│   ├── config.py
│   └── utils.py
├── .env.example
├── main.py
├── requirements.txt
└── README.md

Prerequisites

• Python 3.8 or higher
• pip (Python package manager)

Installation

1. Clone the repository:

   git clone https://github.com/parsahpmx/parsallm.git
   cd parsallm
   

2. Create a virtual environment:

   python -m venv venv
   source venv/bin/activate  # On Windows: .\venv\Scripts\activate
   

3. Install dependencies:

   pip install -r requirements.txt
   

4. Configure environment variables:

   cp .env.example .env
   # Edit .env with your configuration
   

Configuration

Configure the following environment variables in your .env file:

OPENAI_API_KEY=your_openai_api_key
MCP_API_KEY=your_mcp_api_key
MODEL_NAME=gpt-3.5-turbo
DEBUG=False

Usage

Run the chatbot:

python main.py

Development

Adding New Features

1. Create new modules in the src directory
2. Update the configuration in config.py
3. Implement new functionality in modular components
4. Update main.py to integrate new features

Testing

The project includes a basic test suite. Run tests with:

python -m pytest tests/

Contributing

1. Fork the repository
2. Create a feature branch
3. Commit your changes
4. Push to the branch
5. Create a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Support

For support, please open an issue in the GitHub repository.