You're reading from Unlocking Data with Generative AI and RAG Enhance generative AI systems by integrating internal data with large language models using RAG

Product type Paperback

Published in Sep 2024

Publisher Packt

ISBN-13 9781835887905

Length 346 pages

Edition 1st Edition

Concepts

GPT/LLMs

Author (1):

Keith Bourne

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Table of Contents (20) Chapters

Preface

1. Part 1 – Introduction to Retrieval-Augmented Generation (RAG) FREE CHAPTER

2. Chapter 1: What Is Retrieval-Augmented Generation (RAG)

3. Chapter 2: Code Lab – An Entire RAG Pipeline

4. Chapter 3: Practical Applications of RAG

5. Chapter 4: Components of a RAG System

6. Chapter 5: Managing Security in RAG Applications

7. Part 2 – Components of RAG

8. Chapter 6: Interfacing with RAG and Gradio

9. Chapter 7: The Key Role Vectors and Vector Stores Play in RAG

10. Chapter 8: Similarity Searching with Vectors

11. Chapter 9: Evaluating RAG Quantitatively and with Visualizations

12. Chapter 10: Key RAG Components in LangChain

13. Chapter 11: Using LangChain to Get More from RAG

14. Part 3 – Implementing Advanced RAG

15. Chapter 12: Combining RAG with the Power of AI Agents and LangGraph

16. Chapter 13: Using Prompt Engineering to Improve RAG Efforts

17. Chapter 14: Advanced RAG-Related Techniques for Improving Results

18. Index

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19. Other Books You May Enjoy

Part 1 – Introduction to Retrieval-Augmented Generation (RAG)

In this part, you will be introduced to retrieval-augmented generation (RAG), covering its basics, advantages, challenges, and practical applications across various industries. You will learn how to implement a complete RAG pipeline using Python, manage security risks, and build interactive applications with Gradio. We will also explore the key components of RAG systems, including indexing, retrieval, generation, and evaluation, and demonstrate how to optimize each stage for enhanced performance and user experience.

This part contains the following chapters:

Chapter 1, What Is Retrieval-Augmented Generation (RAG)
Chapter 2, Code Lab – An Entire RAG Pipeline
Chapter 3, Practical Applications of RAG
Chapter 4, Components of a RAG System
Chapter 5, Managing Security in RAG Applications

You're reading from Unlocking Data with Generative AI and RAG Enhance generative AI systems by integrating internal data with large language models using RAG

Table of Contents (20) Chapters

Part 1 – Introduction to Retrieval-Augmented Generation (RAG)

Authors (1)

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