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

Benefits of using Gradio

Besides being just really easy to use for non-web developers, Gradio has many advantages. Gradio’s core library is open source, which means developers can freely use, modify, and contribute to the project. Gradio integrates well with widely used machine learning frameworks, such as TensorFlow, PyTorch, and Keras. In addition to the open source library, Gradio offers a hosted platform where developers can deploy their model interfaces and manage access. Gradio includes features that facilitate collaboration among teams working on machine learning projects, such as sharing interfaces and collecting feedback.

Another exciting feature of Gradio is that it integrates well with Hugging Face. Founded by former employees of OpenAI, Hugging Face has a lot of resources meant to support the generative AI community, such as model sharing and dataset hosting. One of the resources is the ability to set up a permanent link to your Gradio demo on the internet, using...

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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

Benefits of using Gradio

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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

Benefits of using Gradio

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