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

Code lab 13.2 – Prompting options

This code can be found in the CHAPTER13-2_PROMPT_OPTIONS.ipynb file in the CHAPTER13 directory of the GitHub repository.

Generally, when you approach the design of your prompt, there are a variety of general concepts that you will want to keep in mind. These include iterating, summarizing, transforming, and expanding. Each of these concepts has different use cases and they can all often be combined in various ways. You will find it useful, when improving your RAG applications, to have this foundational knowledge of how to design your prompts. We will walk through different prompt approaches using a real-world scenario wherein you are helping to write prompts for the marketing department at your company. We will start with iterating.

Iterating

This concept is simply focused on iterating your prompt to get better results. It is rare that your first prompt will be the best and final prompt you could use. This section focuses on some basic...

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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

Code lab 13.2 – Prompting options

Iterating

Authors (1)

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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

Code lab 13.2 – Prompting options

Iterating

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Authors (1)

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