Personal Telegram Bot

A simple Telegram Bot powered by LLM that generates playful, flirtatious responses using the Groq API.

Overview

This project uses a modular design with the following components:

• config: Configuration files and environment variable management
• core: Core integration logic for database and LLM (Groq API)
• handlers: Message and notification processing
• utils: Utility modules for rate limiting and conversation summarization

Key Features

• State Management: Uses conversation summarization instead of full history storage
• Rate Limiting: In-memory rate limiting for message processing
• Notification System: Email alerts for media requests and errors
• Logging: Comprehensive logging system for debugging and operations

Setup and Installation

1. Clone the repository:

git clone https://github.com/yourusername/personal-telegram-bot.git
cd personal-telegram-bot

2. Create and activate a virtual environment:

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

3. Install dependencies:

pip install -r requirements.txt

4. Create a .env file with the following variables:

TELEGRAM_BOT_TOKEN=your_telegram_bot_token
GROQ_API_KEY=your_groq_api_key
MONGODB_URI=your_mongodb_uri
EMAIL_SENDER=your_email
EMAIL_PASSWORD=your_email_password
DEFAULT_RATE_LIMIT_PER_HOUR=30  # Optional, defaults to 30

Running the Bot

Start the bot with:

python main.py

Project Structure

personal-telegram-bot/
├── README.md
├── LICENSE
├── main.py
├── requirements.txt
├── config/
│   └── settings.py
├── core/
│   ├── database.py
│   └── llm.py
├── handlers/
│   ├── message.py
│   └── notification.py
└── utils/
    ├── rate_limiter.py
    └── summarizer.py

Architecture Notes

• Conversation Management: Uses summarization instead of full conversation storage for efficient memory usage
• Rate Limiting: Implements in-memory rate limiting, sufficient for current usage
• Removed Components:
  • Personality module (settings were not actively used)
  • Full conversation memory module (replaced with summarization)

License

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

Contributing

1. Fork the repository
2. Create your feature branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add some AmazingFeature')
4. Push to the branch (git push origin feature/AmazingFeature)
5. Open a Pull Request