A newer version of the Gradio SDK is available:
5.46.1
metadata
title: RAG MVP - Document Q&A
emoji: 📚
colorFrom: blue
colorTo: purple
sdk: gradio
sdk_version: 5.44.1
app_file: app.py
pinned: false
RAG MVP - Document Q&A System
A simple Retrieval-Augmented Generation (RAG) system that allows you to upload PDF documents and ask questions about their content.
Features
- PDF Upload: Upload any PDF document
- Text Processing: Automatic text extraction and chunking
- Semantic Search: Find relevant information using sentence embeddings
- Q&A Interface: Ask questions and get answers based on document content
How to Use
- Upload a PDF document using the file upload interface
- Click "Process Document" and wait for processing to complete
- Ask questions about the document in the question box
- Get relevant answers based on the document content
Technical Stack
- Gradio: Web interface
- sentence-transformers: Text embeddings (all-MiniLM-L6-v2)
- PyPDF2: PDF text extraction
- scikit-learn: Similarity search
- NumPy: Numerical operations
Example Questions
- What is the main topic of this document?
- Can you summarize the key points?
- What are the important details mentioned?
This is a minimal viable product (MVP) demonstrating core RAG functionality with a simple, user-friendly interface.