Generative AI Application Integration Patterns: Integrate large language models into your applications

Juan Pablo Bustos

Luis Lopez Soria

$34.98 ~~$49.99~~

Paperback Sep 2024 218 pages 1st Edition

Juan Pablo Bustos

Luis Lopez Soria

$34.98 ~~$49.99~~

Paperback Sep 2024 218 pages 1st Edition

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Key benefits

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

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.

Who is this book 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

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

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Generative AI Application Integration Patterns: Integrate large language models into your applications

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