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Unlocking Data with Generative AI and RAG

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

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Product type Paperback
Published in Sep 2024
Publisher Packt
ISBN-13 9781835887905
Length 346 pages
Edition 1st Edition
Concepts
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Author (1):
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Keith Bourne Keith Bourne
Author Profile Icon Keith Bourne
Keith Bourne
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Table of Contents (20) Chapters Close

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 19. Other Books You May Enjoy

Code lab – Adding a Gradio interface

This code picks up right where we left off in Chapter 5, except for the last set of lines representing the prompt probe attack. As we have at the beginning of all of our code labs, we are going to start with installing a new package, which is, of course, Gradio! We are also going to uninstall uvloop, because of a conflict with our other packages:

%pip install gradio
%pip uninstall uvloop -y

This installs the gradio package and removes the conflicting uvloop package.

Next, we will add multiple packages to the list of imports:

import asyncio
import nest_asyncio
asyncio.set_event_loop_policy(asyncio.DefaultEventLoopPolicy())
nest_asyncio.apply()
import gradio as gr

These lines import the asyncio and nest_asyncio libraries and set up the event loop policy. asyncio is a library for writing concurrent code using coroutines and event loops. nest_asyncio is a library that allows nested event loops in Jupyter notebook. The asyncio.set_event_loop_policy...

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