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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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Toc

Table of Contents (18) Chapters Close

Preface 1. Part 1:Introduction to Generative AI and LlamaIndex
2. Chapter 1: Understanding Large Language Models FREE CHAPTER 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

Index

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.

Symbols

8-bit integers (INT8) 269

16-bit floating-point (FP16) 269

A

abstract syntax tree (AST) 72

advanced node parsers

HTMLNodeParser 75

JSONNodeParser 75

LangchainNodeParser 74

MarkdownNodeParser 75

SentenceWindowNodeParser 73

SimpleFileNodeParser 74

using 73

advanced prompting techniques

using, in LlamaIndex 309

advanced retrieval mechanisms

building, with naive retrieval method 164

metadata filters, implementing 165-167

queries, transforming 171-173

queries, rewriting 171-173

selectors, using for advanced decision logic 167, 168

specific sub-queries, creating 173, 174

tools 169-171

advanced routing

implementing , with RouterQueryEngine 214-216

advanced tracing

using 280, 281

agentic functionality 169

agentic strategies...

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