A collection of Jupyter notebooks demonstrating various Large Language Model (LLM) applications and features.
This project showcases implementations of RAG (Retrieval-Augmented Generation), agent orchestration, and other LLM-powered applications. Each notebook provides hands-on examples and tutorials for working with modern AI models.
Navigate to the source/ directory and open any .ipynb file in Jupyter. Run the cells in order to execute the demonstrations.
- Python 3.8+
- Jupyter Notebook
- API keys for respective services
Create a .env file in the root directory:
OPENAI_API_KEY=sk-proj-your-api-key-here # Connect to OpenAI models for LLM operations
MIT License
Contributions are welcome! Please feel free to submit issues, feature requests, or pull requests.