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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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Toc

Table of Contents (13) Chapters Close

Preface 1. Introduction to Generative AI Patterns 2. Identifying Generative AI Use Cases FREE CHAPTER 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

Operationalizing Generative AI Integration Patterns

In previous chapters, we explored various integration patterns that leverage the power of Generative AI (GenAI) models like Google Gemini on Vertex AI. We discussed developing production-grade enterprise architectures according to targeted business use cases. In this chapter, we will discuss in depth best practices to be considered while operationalizing your GenAI integrations as production-grade applications. As we transition from conceptual design to real-world application, operational challenges such as scalability, reliability, and maintainability come to the forefront. In a nutshell, we are going to cover the following topics in this chapter:

  • Introduction to operationalizing GenAI integration patterns
  • A four-layer framework for GenAI operationalization
  • Data layer:
    • Data quality and pre-processing
    • Data security and encryption
    • Data governance and versioning
    • Regulatory...
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