eBook - ePub

Building Data-Driven Applications with LlamaIndex

Name: Building Data-Driven Applications with LlamaIndex
Author: Andrei Gheorghiu

A practical guide to retrieval-augmented generation (RAG) to enhance LLM applications

Andrei Gheorghiu,

368 pages
English
ePUB (mobile friendly)
Available on iOS & Android

eBook - ePub

Building Data-Driven Applications with LlamaIndex

A practical guide to retrieval-augmented generation (RAG) to enhance LLM applications

Andrei Gheorghiu,

About this book

Solve real-world problems easily with artificial intelligence (AI) using the LlamaIndex data framework to enhance your LLM-based Python applications

Key Features

Examine text chunking effects on RAG workflows and understand security in RAG app development
Discover chatbots and agents and learn how to build complex conversation engines
Build as you learn by applying the knowledge you gain to a hands-on project

Book Description

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.

What you will learn

Understand the LlamaIndex ecosystem and common use cases
Master techniques to ingest and parse data from various sources into LlamaIndex
Discover how to create optimized indexes tailored to your use cases
Understand how to query LlamaIndex effectively and interpret responses
Build an end-to-end interactive web application with LlamaIndex, Python, and Streamlit
Customize a LlamaIndex configuration based on your project needs
Predict costs and deal with potential privacy issues
Deploy LlamaIndex applications that others can use

Who this book is for

This book is for Python developers with basic knowledge of natural language processing (NLP) and LLMs looking to build interactive LLM applications. Experienced developers and conversational AI developers will also benefit from the advanced techniques covered in the book to fully unleash the capabilities of the framework.

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Yes, you can access Building Data-Driven Applications with LlamaIndex by Andrei Gheorghiu in PDF and/or ePUB format, as well as other popular books in Computer Science & Programming Algorithms. We have over one million books available in our catalogue for you to explore.