Agentic Retrieval-Augmented Generation

Agentic RAG explores the evolution of Retrieval-Augmented Generation (RAG) into intelligent AI systems that can reason, plan, retrieve knowledge, use external tools, and continuously improve their responses. The book begins with the fundamentals of traditional RAG, its architecture, and its limitations, before introducing Agentic RAG as a more autonomous and adaptive approach. It explains how AI agents understand user intent, rewrite and decompose complex queries, select appropriate knowled...