Generative AI Application Integration Patterns

eBook Details:

• Paperback: 218 pages
• Publisher: WOW! eBook (September 5, 2024)
• Language: English
• ISBN-10: 1835887600
• ISBN-13: 978-1835887615

eBook Description:

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

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 Generative AI Application Integration Patterns 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.

• 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

Additionally in this Generative AI Application Integration Patterns book, 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.

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