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

Technical requirements

The code for this chapter is available here: https://github.com/PacktPublishing/Unlocking-Data-with-Generative-AI-and-RAG/tree/main/Chapter_02

You will need to run this chapter’s code in an environment that’s been set up to run Jupyter notebooks. Experience with Jupyter notebooks is a prerequisite for using this book, and it is too difficult to cover it in a short amount of text. There are numerous ways to set up a notebook environment. There are online versions, versions you can download, notebook environments that universities provide students, and different interfaces you can use. If you are doing this at a company, they will likely have an environment you will want to get familiar with. Each of these options takes very different instructions to set up, and those instructions change often. If you need to brush up on your knowledge about this type of environment, you can start on the Jupyter website: https://docs.jupyter.org/en/latest/. Start...

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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

Technical requirements

Authors (1)

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Table of Contents (20) Chapters

Technical requirements

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