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Building Data-Driven Applications with LlamaIndex

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

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Product type Paperback
Published in May 2024
Publisher Packt
ISBN-13 9781835089507
Length 368 pages
Edition 1st Edition
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Author (1):
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Andrei Gheorghiu Andrei Gheorghiu
Author Profile Icon Andrei Gheorghiu
Andrei Gheorghiu
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Table of Contents (18) Chapters Close

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 17. Other Books You May Enjoy

Kickstarting Your Journey with LlamaIndex

As this ebook edition doesn't have fixed pagination, the page numbers below are hyperlinked for reference only, based on the printed edition of this book.

It’s time to dive deeper and gain a more technical understanding of how LlamaIndex works its magic under the hood. In this chapter, we’ll explore some of the key concepts and components that make up LlamaIndex’s architecture. We’ll learn about the core building blocks used by the framework to ingest, structure, and query our data. Understanding these fundamentals will provide a solid foundation before we start applying them hands-on. We’ll go through the theoretical aspects of each concept and then connect the dots between the theory and practical application.

Here are the main topics covered in this chapter:

  • Uncovering the essential building blocks of LlamaIndex – Documents, Nodes, and indexes
  • Building our first interactive, augmented...
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