anky3733/RAG-Nomad

RAG Nomad: Q&A Journey with LLAMA Index

This repository contains code for a question-answering assistant, developed for the NOMAD LLM hackathon. The assistant utilizes the Retrieval-Augmented Generation (RAG) approach along with LLAMA Index to provide accurate responses to user queries within the NOMAD toolkit domain.

Setup Instructions

1. Clone the repository: git clone <repository_url> cd <repository_name>

2. Install the required dependencies: pip install -r requirements.txt

3. Ensure you have the necessary documents in the data folder for optimizing RAG. If not, please provide the required documents in the data folder.

4. Run the Streamlit app: streamlit run my_app.py

5. Access the app in your web browser at http://localhost:8501.

File Descriptions

• rag.ipynb: Jupyter Notebook containing code for building the LLAMA Index model and performing question-answering tasks.
• my_app.py: Python script for the Streamlit web application, providing a user interface for querying the LLAMA Index model.
• requirements.txt: List of Python dependencies required to run the code.
• readme.md: This file, providing an overview of the project and setup instructions.
• data/: Folder containing documents required for optimizing RAG.