Julep AI w/ Llama

A Python application that integrates Julep AI with a custom Llama model endpoint, providing a flexible and powerful AI agent system with persistent memory and efficient caching.

Features

• 🤖 Custom Llama model integration via OpenAI-compatible API
• 💾 Persistent storage with SQLite
• 🧠 Vector embeddings with ChromaDB
• ⚡ Fast caching with Redis
• 🔒 Secure environment configuration
• 📝 Comprehensive logging system

Prerequisites

• Python 3.12+
• Redis server
• Git
• A Julep API key from dev.julep.ai

Installation & Setup

Please refer to setup.md for detailed installation and configuration instructions.

Project Structure

Julep-AI-Llama/
├── config/
│   ├── agent_config.example.yaml  # Template for agent configuration
│   ├── agent_config.yaml         # Your custom agent config (git-ignored)
│   └── memory_config.yaml       # Memory settings
├── storage/
│   ├── chromadb/           # Vector embeddings storage
│   ├── logs/               # Application logs
│   └── julep.db            # SQLite database
├── .env                    # Environment variables
├── .env.example           # Environment template
├── main.py               # Main application
├── requirements.txt      # Python dependencies
└── README.md            # This file

Development

Code Style

This project follows:

• PEP 8 style guide
• Type hints throughout
• Google-style docstrings
• Black code formatting

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.

Acknowledgments

• Julep AI for the agent framework
• The Llama model community
• All contributors to this project