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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Code lab 8.3 – Hybrid search with LangChain’s EnsembleRetriever to replace our custom function

The file you need to access from the GitHub repository is titled CHAPTER8-3_HYBRID-ENSEMBLE.ipynb.

We continue this code from the last lab starting with the CHAPTER8-2_HYBRID-CUSTOM.ipynb file. The complete code for this code lab is CHAPTER8-3_HYBRID-ENSEMBLE.ipynb. First, we need to import the retriever from LangChain; add this to your imports:

from langchain.retrievers import EnsembleRetriever

This adds EnsembleRetriever from LangChain to be used as a third retriever that combines the other two retrievers. Note that previously, in Code lab 8.2, we added k=10 to each of the two retrievers to make sure we got enough responses to be similar to the other response.

In the past, we just had one set of documents that we defined as documents, but here we want to change the name of those documents to dense_documents, and then add a second set of documents called sparse_documents...

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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 8.3 – Hybrid search with LangChain’s EnsembleRetriever to replace our custom function

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Code lab 8.3 – Hybrid search with LangChain’s EnsembleRetriever to replace our custom function

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Table of Contents (20) Chapters