Building Data-Driven Applications with LlamaIndexEbook A practical guide to retrieval-augmented generation (RAG) to enhance LLM applications

Le prix initial était : 25.99 €.Le prix actuel est : 7.80 €.

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…

Passer à la caisse
SKU: WRRYWJB4066825014382
Category:

Description

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 DescriptionDiscover 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.

LangueenVersionlivre numériqueDate de sortie initiale10 mai 2024Format ebookEPUB3

Personnes impliquées

Auteur principal

Andrei Gheorghiu

Editeur principal

Packt Publishing

Options de lecture

Lisez cet ebook suriOS (smartphone et tablette)Windows (smartphone et tablette)Lecteur électronique KoboOrdinateur de bureau (Mac et Windows)Android (smartphone et tablette)

Informations sur le fabricant

Informations sur le fabricantLes informations du fabricant ne sont actuellement pas disponibles

Autres spécifications

Livre d‘étudeNon

EAN

EAN9781805124405

Sécurité des produits

Opérateur économique responsable dans l’UE

Afficher les données

Vous trouverez cet article :

CatégoriesDisponibilitéDisponible à l’adresse suivanteAuteurAndrei Gheorghiu

Avis

Il n’y a pas encore d’avis.

Soyez le premier à laisser votre avis sur “Building Data-Driven Applications with LlamaIndexEbook A practical guide to retrieval-augmented generation (RAG) to enhance LLM applications”

Votre adresse e-mail ne sera pas publiée. Les champs obligatoires sont indiqués avec *