Document Q&A System 📄

A powerful document question-answering system that uses Claude AI to answer questions about uploaded PDF documents with vector similarity search for accurate context retrieval.

View Live App View on GitHub

Features

• PDF document upload and processing
• Intelligent text chunking with overlap for context preservation
• Question answering powered by Claude AI (Anthropic)
• Clean and intuitive Streamlit interface
• Hosted on Google Cloud Platform (Cloud Run)
• Modular architecture for easy maintenance and scaling

Technology Stack

• Backend: Python with modular architecture
• AI: Claude API (Anthropic)
• Vector Search: FAISS for efficient similarity search
• Frontend: Streamlit for interactive web interface
• Document Processing: PyPDF2 for PDF text extraction
• Cloud: Google Cloud Platform (Cloud Run)

Architecture

The system follows a clean, modular design:

1. Document Processing: Extract and chunk text from PDFs
2. Vector Storage: Create embeddings and store in FAISS index
3. Query Processing: Find relevant passages using similarity search
4. Answer Generation: Use Claude AI to generate contextual answers

Document Q&A System Interface and Functionality