RAGBOT

What it does

This project provides a real-time chat interface with a custom RAG pipeline, featuring a React frontend and FastAPI backend. It supports file uploads, document chunking, and semantic search, while storing data in an SQLite database.

RAGBot is a full-stack application that combines a React frontend with a FastAPI backend to create a powerful real-time chat interface. The system leverages a custom-built Retrieval-Augmented Generation (RAG) developed from scratch pipeline for efficient document retrieval and query answering - amajji/chat-interface-with-react-and-rag-from-scratch

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. The Users can interact with the LLM by typing queries. The backend uses the RAG pipeline to retrieve relevant document chunks…from github.com

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