Visualizing RAGs
An educational tool for understanding Retrieval-Augmented Generation systems
A small interactive application designed to demystify the inner workings of RAG systems through visual representation. Built as a teaching tool to help users understand how RAGs process documents, create embeddings, and generate contextual responses.
Project Overview
Visualizing RAGs is an educational tool that makes the inner workings of Retrieval-Augmented Generation systems visible and understandable. By processing PDF documents and creating visual representations of embeddings and retrieval processes, this application helps users grasp how RAG systems chunk text, create semantic embeddings, and retrieve relevant context for question answering.
Technical Implementation
The tool supports multiple AI providers including OpenAI (for embeddings), Mistral, Gemini, and Anthropic for text generation. Gradio is used to make the interface and llama index for the chunking and retrieval