This project presents Shiksha Setu, an intelligent multi-source educational chatbot built using Retrieval-Augmented Generation (RAG). It allows users to upload documents or provide website URLs, which are processed, embedded, and stored using ChromaDB for semantic search. User queries are handled using a sentence transformer model, and relevant context is passed to the Llama-3.2 language model to generate accurate responses. Built with ReactJS, Tailwind CSS, and FastAPI, the system transforms static learning materials into interactive, queryable knowledge sources, enhancing personalized learning and academic support.