RAG Model with Llama and SHAP Interpretability Prerequisites Python 3.8+ pip (Python Package Manager) Virtual Environment (recommended) Setup Guide 1. Clone the Repository git clone https://github.com/gober9/Rag-Creation-Python-Llama.git cd Rag-Creation-Python-Llama 2. Create a Virtual Environment # On Windows python -m venv venv venv\Scripts\activate # On macOS/Linux python3 -m venv venv source venv/bin/activate 3. Install Dependencies pip install -r requirements.txt 4. Download Llama Model Visit Hugging Face: https://huggingface.co/models Search for and download a Llama model Place the model in a models/ directory 5. Run the RAG Model python rag_model.py Troubleshooting Ensure all dependencies are installed Check Python version compatibility Verify model file paths Project Structure rag_model.py: Main RAG model implementation requirements.txt: Project dependencies models/: Directory for storing Llama models data/: Directory for input/output data Contributing Fork the repository Create a feature branch Commit your changes Push to the branch Create a Pull Request