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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
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

Building Indexes on top of other Indexes with ComposableGraph

The ComposableGraph in LlamaIndex represents a sophisticated way to structure information by stacking Indexes on top of each other.

Figure 5.12 provides an overview of a ComposableGraph:

Figure 5.12 – The structure of a ComposableGraph

Figure 5.12 – The structure of a ComposableGraph

This approach allows for the construction of Indexes within individual documents – lower-level Indexes – and the aggregation of these Indexes into higher-order ones over a collection of documents. For example, you can build a TreeIndex for the text within each document and a SummaryIndex that encompasses each TreeIndex in a collection.

How to use the ComposableGraph

Here’s a simple code example demonstrating the usage of ComposableGraph:

from llama_index.core import (
    ComposableGraph, SimpleDirectoryReader, 
    TreeIndex, SummaryIndex)
documents = SimpleDirectoryReader("files...
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