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Generative AI Application Integration Patterns

You're reading from   Generative AI Application Integration Patterns Integrate large language models into your applications

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Product type Paperback
Published in Sep 2024
Publisher Packt
ISBN-13 9781835887608
Length 218 pages
Edition 1st Edition
Languages
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Authors (2):
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Luis Lopez Soria Luis Lopez Soria
Author Profile Icon Luis Lopez Soria
Luis Lopez Soria
Juan Pablo Bustos Juan Pablo Bustos
Author Profile Icon Juan Pablo Bustos
Juan Pablo Bustos
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Table of Contents (13) Chapters Close

Preface 1. Introduction to Generative AI Patterns FREE CHAPTER 2. Identifying Generative AI Use Cases 3. Designing Patterns for Interacting with Generative AI 4. Generative AI Batch and 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 11. Other Books You May Enjoy
12. Index

Designing Patterns for Interacting with Generative AI

In the previous chapters, we explored the world of generative AI (GenAI), including the types of use cases and applications that can be developed using this exciting new technology. We also discussed evaluating the business value that GenAI can potentially bring to the table for different organizations and industries.

In this chapter, we will dive deeper into the practical considerations around integrating GenAI capabilities into real-world applications. A key question that arises is, where and how should we incorporate GenAI models within an application’s architecture and workflow? There are a few different approaches we can take, depending on factors like the application type, existing infrastructure, team skills, and more.

Figure 3.1: Image generated by AI to depict AI integration

We will start by examining how user requests or inputs can serve as entry points for generating content or predictions using...

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