https://github.com/viraj-gavade/rag-document-q-a

A Streamlit-based application for Question & Answering over research papers using Retrieval-Augmented Generation (RAG) and LLMs.
https://github.com/viraj-gavade/rag-document-q-a

langchain python rag streamlit

Last synced: 2 months ago
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A Streamlit-based application for Question & Answering over research papers using Retrieval-Augmented Generation (RAG) and LLMs.

• Host: GitHub
• URL: https://github.com/viraj-gavade/rag-document-q-a
• Owner: viraj-gavade
• Created: 2025-08-14T12:07:24.000Z (11 months ago)
• Default Branch: master
• Last Pushed: 2025-08-16T04:21:14.000Z (10 months ago)
• Last Synced: 2025-09-02T02:24:08.723Z (10 months ago)
• Topics: langchain, python, rag, streamlit
• Language: Python
• Homepage:
• Size: 2.19 MB
• Stars: 0
• Watchers: 0
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# RAG Document Q&A

A Streamlit-based application for Question & Answering over research papers using Retrieval-Augmented Generation (RAG) and LLMs.

## Features

- Upload multiple PDF research papers.

- Vector embedding creation using HuggingFace models.

- Semantic search and retrieval using FAISS.

- LLM-powered Q&A (Groq's Gemma2-9b-it).

- Document similarity search for context.

## How It Works

1. **Upload PDFs**: Add your research papers via the UI.

2. **Vectorization**: PDFs are split, embedded, and stored in a FAISS vector database.

3. **Ask Questions**: Enter queries to get answers based on the uploaded documents.

4. **Contextual Results**: View document snippets most relevant to your query.

## Setup

1. Clone this repo.

2. Install dependencies:

   ```powershell

   pip install -r requirements.txt

   ```

3. Add a `.env` file with your Groq API key:

   ```env

   GROQ_API_KEY=your_groq_api_key_here

   ```

4. Run the app:

   ```powershell

   streamlit run app.py

   ```

## Folder Structure

- `app.py` : Main Streamlit app.

- `requirements.txt` : Python dependencies.

- `research_papers/` : Example PDFs for testing.

## Requirements

See `requirements.txt` for all Python packages.

## Example PDFs

- `Attention.pdf`

- `LLM.pdf`

## License

MIT