Generative AI Application Integration Patterns (Paperback)

Luis Lopez Soria

ISBN 10: 1835887600 / ISBN 13: 9781835887608

Edité par Packt Publishing Limited, Birmingham, 2024

A propos de cet article

Paperback. Unleash the transformative potential of GenAI with this comprehensive guide that serves as an indispensable roadmap for integrating large language models into real-world applications. Gain invaluable insights into identifying compelling use cases, leveraging state-of-the-art models effectively, deploying these models into your applications at scale, and navigating ethical considerations.Key FeaturesGet familiar with the most important tools and concepts used in real scenarios to design GenAI appsInteract with GenAI models to tailor model behavior to minimize hallucinationsGet acquainted with a variety of strategies and an easy to follow 4 step frameworks for integrating GenAI into applicationsBook DescriptionExplore the transformative potential of GenAI in the application development lifecycle. Through concrete examples, you will go through the process of ideation and integration, understanding the tradeoffs and the decision points when integrating GenAI.With recent advances in models like Google Gemini, Anthropic Claude, DALL-E and GPT-4o, this timely resource will help you harness these technologies through proven design patterns.We then delve into the practical applications of GenAI, identifying common use cases and applying design patterns to address real-world challenges. From summarization and metadata extraction to intent classification and question answering, each chapter offers practical examples and blueprints for leveraging GenAI across diverse domains and tasks. You will learn how to fine-tune models for specific applications, progressing from basic prompting to sophisticated strategies such as retrieval augmented generation (RAG) and chain of thought.Additionally, we provide end-to-end guidance on operationalizing models, including data prep, training, deployment, and monitoring. We also focus on responsible and ethical development techniques for transparency, auditing, and governance as crucial design patterns.What you will learnConcepts of GenAI: pre-training, fine-tuning, prompt engineering, and RAGFramework for integrating AI: entry points, prompt pre-processing, inference, post-processing, and presentationPatterns for batch and real-time integrationCode samples for metadata extraction, summarization, intent classification, question-answering with RAG, and moreEthical use: bias mitigation, data privacy, and monitoringDeployment and hosting options for GenAI modelsWho this book is forThis book is not an introduction to AI/ML or Python. It offers practical guides for designing, building, and deploying GenAI applications in production. While all readers are welcome, those who benefit most include:Developer engineers with foundational tech knowledgeSoftware architects seeking best practices and design patternsProfessionals using ML for data science, research, etc., who want a deeper understanding of Generative AITechnical product managers with a software development backgroundThis concise focus ensures practical, actionable insights for experienced professionals Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

N° de réf. du vendeur 9781835887608

Détails bibliographiques

• Titre: Generative AI Application Integration Patterns (Paperback)
• Éditeur: Packt Publishing Limited, Birmingham
• Date de parution: 2024
• Langue: anglais
• ISBN à 10 chiffres: 1835887600
• ISBN à 13 chiffres: 9781835887608
• Reliure: Paperback
• État de l'article: new

A propos de ce titre

Synopsis

Unleash the transformative potential of GenAI with this comprehensive guide that serves as an indispensable roadmap for integrating large language models into real-world applications. Gain invaluable insights into identifying compelling use cases, leveraging state-of-the-art models effectively, deploying these models into your applications at scale, and navigating ethical considerations.

Key Features

• Get familiar with the most important tools and concepts used in real scenarios to design GenAI apps
• Interact with GenAI models to tailor model behavior to minimize hallucinations
• Get acquainted with a variety of strategies and an easy to follow 4 step frameworks for integrating GenAI into applications

Book Description

Explore the transformative potential of GenAI in the application development lifecycle. Through concrete examples, you will go through the process of ideation and integration, understanding the tradeoffs and the decision points when integrating GenAI.

With recent advances in models like Google Gemini, Anthropic Claude, DALL-E and GPT-4o, this timely resource will help you harness these technologies through proven design patterns.

We then delve into the practical applications of GenAI, identifying common use cases and applying design patterns to address real-world challenges. From summarization and metadata extraction to intent classification and question answering, each chapter offers practical examples and blueprints for leveraging GenAI across diverse domains and tasks. You will learn how to fine-tune models for specific applications, progressing from basic prompting to sophisticated strategies such as retrieval augmented generation (RAG) and chain of thought.

Additionally, we provide end-to-end guidance on operationalizing models, including data prep, training, deployment, and monitoring. We also focus on responsible and ethical development techniques for transparency, auditing, and governance as crucial design patterns.

What you will learn

• Concepts of GenAI: pre-training, fine-tuning, prompt engineering, and RAG
• Framework for integrating AI: entry points, prompt pre-processing, inference, post-processing, and presentation
• Patterns for batch and real-time integration
• Code samples for metadata extraction, summarization, intent classification, question-answering with RAG, and more
• Ethical use: bias mitigation, data privacy, and monitoring
• Deployment and hosting options for GenAI models

Who this book is for

This book is not an introduction to AI/ML or Python. It offers practical guides for designing, building, and deploying GenAI applications in production. While all readers are welcome, those who benefit most include:

Developer engineers with foundational tech knowledge

Software architects seeking best practices and design patterns

Professionals using ML for data science, research, etc., who want a deeper understanding of Generative AI

Technical product managers with a software development background

This concise focus ensures practical, actionable insights for experienced professionals

Table of Contents

1. Introduction to Generative AI Design Patterns
2. Identifying Generative AI Use Cases
3. Designing Patterns for Interacting with Generative AI
4. Generative AI Batch & Real-time Integration Patterns
5. Integration Pattern: Batch Metadata Extraction
6. Integration Pattern: Batch Summarization
7. Integration Pattern: Real-Time Intent Classification
8. Integration Pattern: Real-Time Retrieval Augmented Generation
9. Operationalizing Generative AI Integration Patterns
10. Embedding Responsible AI into your GenAI Applications

À propos de l?auteur

Juan Pablo Bustos is a seasoned technologist with over 20 years of experience in driving innovation and delivering impactful solutions across diverse industries. Juan brings expertise in solution architecture, product incubation, and integration, coupled with expertise in cloud computing, AI, and machine learning.

Luis Lopez Soria is an experienced software architect specialized in AI/ML. He has gained practical experience from top firms across heavily regulated industries (healthcare, and finance) as well as big tech. He brings a blended lens from his experience managing global partnerships, AI product development, and customer facing roles.