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Generative AI Application Integration Patterns

Generative AI Application Integration Patterns

By : Juan Pablo Bustos, Luis Lopez Soria
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Generative AI Application Integration Patterns

Generative AI Application Integration Patterns

By: Juan Pablo Bustos, Luis Lopez Soria

Overview of this book

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.
Table of Contents (13 chapters)
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7
Integration Pattern: Real-Time Intent Classification
11
Other Books You May Enjoy
12
Index

Entry point

The entry point is where an application accepts a user’s input that will be processed by GenAI models. This might be:

  • A text box where a user enters a prompt: Interactive
  • An uploaded image that will be processed: Interactive or batch
  • A voice recording that will be transcribed and analyzed: Batch

The entry point acts as the front door for users to access the power of GenAI within an application. As such, the entry point modality should align closely with the input types supported by the models being leveraged. If the models only process text prompts, then a text-based entry field is appropriate. For image generation models, the entry could be an interface supporting image uploads. Multi-modal models may warrant options for both text and images.

Beyond matching supported input types, the entry point UX should aim to make providing prompts fast, intuitive, and even delightful for users. Well-designed interfaces guide users naturally...

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