About This Project
A document question-answering system that leverages Retrieval-Augmented Generation (RAG) via LangFlow for processing PDF documents. Users can upload documents or paste text and ask natural language questions, receiving context-aware responses extracted from the document content. Note: This project is not hosted publicly as it uses an official API key. Hosting it could lead to unauthorized usage and API quota exhaustion.
Key Features
- PDF document upload and text extraction
- Direct text input support
- Natural language question answering with RAG
- Context-aware response generation
- Session-based conversation memory
- Modern, responsive chat interface
Technology Stack
- FastAPI for REST API backend
- LangFlow for RAG pipeline orchestration
- Google Gemini for LLM capabilities (via LangFlow)
- PyMuPDF for PDF parsing
- HTML/CSS/JavaScript for frontend UI