This repository provides a comprehensive tutorial for developing RAG-based LLM applications from scratch. It covers key stages including document loading, chunking, embedding, indexing, serving, and evaluation. The guide also addresses scaling these components using Ray, implementing hybrid routing between open-source and closed LLMs, and optimizing both retrieval and quality scores through systematic evaluation.