Retrieval-Augmented Generation (RAG) is how artificial intelligence prioritizes facts in a given domain over and above all the information the basic, foundational model offers. It allows businesses, scientists, and others to prioritize their custom knowledge instead of making up answers. It’s an extremely powerful tool that most AI users don’t understand. This book tries to explain the basics of a RAG system in Python code.
Unfortunately, despite a grasp on the basics of RAG, it has a few disappointing flaws. First, the code blocks are printed in extremely light font so that they’re almost unreadable. Second, it seems heavy on technologies and code but relatively light on deep conceptual teaching. It’s as if someone researched the depths of a coding project without understanding the theoretical nuances first. In this book’s case, the word “practical” in the subtitle means devoid of profound ideas, not necessarily quick to launch. I recommend trying another book that explains RAG, not just implements it.
Retrieval-Augmented Generation (RAG) and Vector Databases: A Practical Guide for AI Developers
By Gus G. Newton
Copyright (c) 2025
Independently Published
ISBN13 9798314910122
Page Count: 129
Genre: Artificial Intelligence
www.amazon.com