| 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 | |
| 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. | |