RAGBOT

This project provides a real-time Chat Interface powered by a custom-built Retrieval Augmented Generation (RAG) pipeline, developed from scratch. It incorporates both frontend (React) and backend (FastAPI) components, supporting file uploads, document chunking, embedding generation, and semantic search for efficient document retrieval. The system enables plugging any LLM for document retrieval and allows efficient search through a collection of documents. The project includes functionality for document processing and chunk management, stored in an SQLite database.