Introducing Spring AI

Abstract

By now, you've no doubt noticed that Generative AI is making waves across many industries. In between all of the hype and doubt, there are several use cases for Generative AI in many software projects. Whether it be as simple as building a live chat to help your users or using AI to analyze data and provide recommendations, Generative AI is becoming a key piece of software architecture.

So how can you implement Generative AI in your projects? Let me introduce you to Spring AI.

For over two decades, the Spring Framework and its immense portfolio of projects has been making complex problems easy for Java developers. And now with the new Spring AI project, adding Generative AI to your Spring Boot projects couldn't be easier! Spring AI brings an AI client and templated prompting that handles all of the ceremony necessary to communicate with common AI APIs (such as OpenAI and Azure OpenAI). And with Spring Boot auto-configuration, you'll be able to get straight to the point of asking questions and getting answers your application needs.

In this session, we'll consider a handful of use cases for Generative AI and see how to implement them with Spring AI. We'll start simple, then build up to some more advanced uses of Spring AI that employ your application's own data when generating answers.

Craig Walls

Craig Walls is an engineer with VMware, Java Champion, Alexa Champion, and the author of Spring in Action, Spring Boot in Action, and Build Talking Apps. He's a zealous promoter of the Spring Framework, speaking frequently at local user groups and conferences and writing about Spring. When he's not slinging code, Craig is planning his next trip to Disney World or Disneyland and spending as much time as he can with his wife, two daughters, 1 bird and 3 dogs.