You're reading from Building Data-Driven Applications with LlamaIndex A practical guide to retrieval-augmented generation (RAG) to enhance LLM applications

Product type Paperback

Published in May 2024

Publisher Packt

ISBN-13 9781835089507

Length 368 pages

Edition 1st Edition

Languages

Python

Tools

LlamaIndex

Concepts

GPT/LLMs

Author (1):

Andrei Gheorghiu

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Table of Contents (18) Chapters

Preface

1. Part 1:Introduction to Generative AI and LlamaIndex FREE CHAPTER

2. Chapter 1: Understanding Large Language Models

3. Chapter 2: LlamaIndex: The Hidden Jewel - An Introduction to the LlamaIndex Ecosystem

4. Part 2: Starting Your First LlamaIndex Project

5. Chapter 3: Kickstarting Your Journey with LlamaIndex

6. Chapter 4: Ingesting Data into Our RAG Workflow

7. Chapter 5: Indexing with LlamaIndex

8. Part 3: Retrieving and Working with Indexed Data

9. Chapter 6: Querying Our Data, Part 1 – Context Retrieval

10. Chapter 7: Querying Our Data, Part 2 – Postprocessing and Response Synthesis

11. Chapter 8: Building Chatbots and Agents with LlamaIndex

12. Part 4: Customization, Prompt Engineering, and Final Words

13. Chapter 9: Customizing and Deploying Our LlamaIndex Project

14. Chapter 10: Prompt Engineering Guidelines and Best Practices

15. Chapter 11: Conclusion and Additional Resources

16. Index

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17. Other Books You May Enjoy

Part 3: Retrieving and Working with Indexed Data

This part progresses from exploring LlamaIndex’s querying capabilities within a RAG workflow, focusing on retrieval mechanisms, query mechanics, and advanced retrieval strategies, to refining these queries through post-processing techniques and integrating them into comprehensive query engines. It culminates in a practical examination of building chatbots and intelligent agents, covering various engine modes, agent architectures, and the implementation of conversational features, thereby equipping you with the knowledge to create dynamic, conversational RAG interfaces.

This part has the following chapters:

Chapter 6, Querying Our Data, Part 1 – Context Retrieval
Chapter 7, Querying Our Data, Part 2 – Postprocessing and Response Synthesis
Chapter 8, Building Chatbots and Agents with LlamaIndex

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You're reading from Building Data-Driven Applications with LlamaIndex A practical guide to retrieval-augmented generation (RAG) to enhance LLM applications

Table of Contents (18) Chapters

Part 3: Retrieving and Working with Indexed Data

Authors (1)

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You're reading from Building Data-Driven Applications with LlamaIndex A practical guide to retrieval-augmented generation (RAG) to enhance LLM applications

Table of Contents (18) Chapters

Part 3: Retrieving and Working with Indexed Data

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Authors (1)

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