August 2025

Spring AI Spring AI is an advanced framework in the Spring ecosystem designed to seamlessly integrate artificial intelligence into Java applications. It abstracts the complexity of AI model integration, making it easier for developers to interact with popular AI providers such as OpenAI, Hugging Face, and Local Large Language Models (LLMs). With Spring AI, developers can focus on building intelligent features without worrying about the intricate details of model APIs or deployment pipelines. How Spring AI Works- Spring AI works by providing a standard programming model that integrates AI model calls into Spring Boot applications. Here’s the process:Input – The application sends prompts, queries, or structured data to the AI client.Processing – The AI client interacts with the chosen AI model using provider-specific APIs.Output – The model returns results, which are transformed into usable Java objects via mappers. Setup Procedure for Spring AI Step 1: Create a Spring Boot ProjectUse Spring Initializr (https://start.spring.io/) to generate a new project. Step 2: Add Spring AI Dependency For Maven:<dependency><groupId>org.springframework.ai</groupId><artifactId>spring-ai-openai-spring-boot-starter</artifactId><version>0.8.0</version></dependency> For Gradle:implementation ‘org.springframework.ai:spring-ai-openai-spring-boot-starter:0.8.0’ Step 3: Configure Application Properties In application.yml or application.properties, set your OpenAI API key:spring:ai:openai: api-key: YOUR_OPENAI_API_KEY Step 4: Create a Service to Use AI import org.springframework.ai.openai.OpenAiChatModel; importorg.springframework.beans.factory.annotation.Autowired; importorg.springframework.stereotype.Service;@Service public classAiService { @Autowired privateOpenAiChatModel chatModel; public String getResponse(String prompt) {return chatModel.call(prompt);}} Step 5: Create a REST Controller  import org.springframework.web.bind.annotation.*;  @RestController @RequestMapping(“/ai”) public class AiController {      private final AiService aiService;      public AiController(AiService aiService) {        this.aiService = aiService;     }  @GetMapping(“/chat”)      public String chat(@RequestParam String message) {          return aiService.getResponse(message);      }  }  Step 6: Run and Test  Run your Spring Boot application.  Send a GET request:  http://localhost:8080/ai/chat?message=Hello  You’ll receive an AI-generated response from the configured model.   Use Cases of Spring AI  Advantages of Spring AI  Limitations of Spring AI  –External Dependencies – Relies on third-party AI providers unless self-hosted.  –Latency – Large models or remote calls can introduce delays.  –Cost – Paid AI APIs may result in higher operational expenses.  Conclusion  Spring AI enables developers to bring the power of AI into Java applications quickly and efficiently. By providing an easy-to-use, production-ready integration layer, it empowers teams to build smarter, more interactive, and more capable applications without the overhead of managing complex AI pipelines.  At LogicalWings, we bring this spirit of innovation to everything we do. We specialize in software development, mobile app creation, and cloud consulting, serving various sectors, including healthcare, retail, travel, and enterprise. Our expert team delivers secure, scalable, and industry-focused solutions that drive measurable results for clients across the UK, the Netherlands, and Australia. Empowering your business with next-gen technology—get started now. Contact us on: +91 9665797912 Please email us: contact@logicalwings.com