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Building Data-Driven Applications with LlamaIndex

Building Data-Driven Applications with LlamaIndex

By : Andrei Gheorghiu
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Building Data-Driven Applications with LlamaIndex

Building Data-Driven Applications with LlamaIndex

5 (10)
By: Andrei Gheorghiu

Overview of this book

Discover the immense potential of Generative AI and Large Language Models (LLMs) with this comprehensive guide. Learn to overcome LLM limitations, such as contextual memory constraints, prompt size issues, real-time data gaps, and occasional ‘hallucinations’. Follow practical examples to personalize and launch your LlamaIndex projects, mastering skills in ingesting, indexing, querying, and connecting dynamic knowledge bases. From fundamental LLM concepts to LlamaIndex deployment and customization, this book provides a holistic grasp of LlamaIndex's capabilities and applications. By the end, you'll be able to resolve LLM challenges and build interactive AI-driven applications using best practices in prompt engineering and troubleshooting Generative AI projects.
Table of Contents (18 chapters)
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1
Part 1:Introduction to Generative AI and LlamaIndex
4
Part 2: Starting Your First LlamaIndex Project
8
Part 3: Retrieving and Working with Indexed Data
12
Part 4: Customization, Prompt Engineering, and Final Words

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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