📄 RAG Document Q&A

Ask questions about any PDF or document - powered by RAG (Retrieval-Augmented Generation)

Status: 🚧 In active development

What This Does

Upload any document (PDF, TXT) → Ask natural language questions → Get accurate, source-grounded answers powered by an LLM.

This is not a generic chatbot. It only answers based on what's in your documents — no hallucination.

Architecture

User Query → Embedding → FAISS Vector Search → Retrieved Chunks → LLM (GPT/Claude) → Answer

Tech Stack

• LangChain — orchestration layer
• FAISS — vector similarity search
• FastAPI — REST API backend
• OpenAI / Anthropic — LLM for answer generation
• Python 3.11+

Progress

• Project architecture planned
• PDF ingestion & chunking
• Embedding pipeline
• FAISS vector store
• FastAPI endpoints
• Frontend (Streamlit)
• Deployment (Hugging Face Spaces / Railway)