title: RAG MVP - Document Q&A | |
emoji: π | |
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 | |
1. Upload a PDF document using the file upload interface | |
2. Click "Process Document" and wait for processing to complete | |
3. Ask questions about the document in the question box | |
4. 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. | |