Preface
Building AI Agents with LLMs, RAG, and Knowledge Graphs introduces you to the evolving landscape of large language models (LLMs) and AI agents, offering both a theoretical foundation and practical guidance. It begins by explaining how text data can be represented and processed using deep learning, then progresses to modern architectures such as the Transformer model. From there, the book explores how LLMs are scaled and fine-tuned, and how their capabilities can be extended with tools, external memory systems, and agent-based frameworks. Technologies such as retrieval-augmented generation (RAG), GraphRAG, and multi-agent systems are explained in detail, with a focus on real-world applications and deployment. By the end of the book, you will have a clear understanding of how to build intelligent, tool-using AI agents and the role these systems play in shaping the future of AI.
