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)

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

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

Why Gradio?

Up until this point, we have focused on topics that are typically relegated to the world of data science. Machine learning, natural language processing (NLP), generative artificial intelligence (generative AI), large language models (LLMs), and RAG are technologies that require significant expertise and often take up enough time that we are not able to build expertise in other technical areas, such as working with web technologies and building web frontends. Web development is a highly technical field in its own right, and requires significant experience and expertise to implement successfully.

However, with RAG, it can be very helpful to have a UI, especially if you want to test it or demonstrate it to potential users. How can we provide that if we do not have the time to learn web development?

That is the primary reason why many data scientists, including myself, use Gradio. It allows you to get a UI up and running very quickly (relative to building a web frontend...

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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

Why Gradio?

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Table of Contents (20) Chapters

Why Gradio?

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