RAG Systems from Scratch

RAG Systems from Scratch is a practical, 15-chapter guide to building Retrieval-Augmented Generation applications that are actually ready for production — not just a demo. Written for AI engineers, GenAI/LLM engineers, software developers, and CS students, it covers the full pipeline: embeddings, chunking, vector databases (FAISS, Chroma, pgvector), semantic and hybrid search, reranking, prompt engineering for grounding, LangChain and LangGraph orchestration, FastAPI serving, evaluation and hallucination reduction, security and access control, and deployment and monitoring. Each chapter pairs working Python code with the engineering judgment that separates a working prototype from a system you can trust with real users — common mistakes, production tips, and what to measure. Includes companion source code, architecture diagrams, and a production readiness checklist. If you can write Python, this book gets you from first principles to a system you'd defend in a design review.

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