Why Spring AI: The Seamless Path for Spring Developers to the World of Generative AI

Intro

As a Java developer exploring the world of generative AI, you’re probably aware of several frameworks that promise to make AI integration easy. I believe Spring AI stands out as the natural choice, especially for developers already working within the Spring ecosystem. Built on the same foundation as Spring Boot and Spring Data, Spring AI makes adding AI capabilities to your applications seamless and intuitive, without requiring you to learn an entirely new set of paradigms.

Seamless Integration with the…

Recap of Part I

In the first part of this blog series, we explored the basics of integrating Spring AI with large language models. We walked through building a custom ChatClient, leveraging Function Calling for dynamic interactions, and refining our prompts to suit the Spring Petclinic use case. By the end, we had a functional AI assistant capable of understanding and processing requests related to our veterinary clinic domain.

Now, in Part II, we’ll go a step further by exploring Retrieval-Augmented Generation (RAG), a technique that enables us to handle large datasets that wouldn’t fit…

Introduction

In this two-parts blog post, I will discuss the modifications I made to Spring Petclinic to incorporate an AI assistant that allows users to interact with the application using natural language.

Introduction to Spring Petclinic

Spring Petclinic serves as the primary reference application within the Spring ecosystem. According to GitHub, the repository was created on January 9, 2013. Since then, it has become the model application for writing simple, developer-friendly code using Spring Boot. As of this writing, it has garnered over 7,600 stars and 23,000 forks.

The application…