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.