Applied RAG - Practical Retrieval-Augmented Generation with Python: A Comprehensive Guide to Building Knowledge-Grounded AI Applications

Applied RAG: Practical Retrieval-Augmented Generation with Python, authored by Dr. Balaji Venkateswaran, provides a hands-on blueprint for building reliable, knowledge-grounded AI systems. The book addresses LLM limitations like hallucination and static knowledge, guiding readers through RAG theory, architecture, and practical Python workflows. It covers building blocks such as retrievers and embeddings, advanced retrieval techniques, and integration with frameworks like LangChain. Real-world applications, operational challenges, evaluation, security, and ethical AI are emphasized. This book empowers engineers, scientists, and leaders to master RAG and innovate in creating robust, up-to-date AI solutions for tasks such as QA, summarization, and agents for enterprises.