Java AI Development
Integrating Google Gemini with Spring AI
A step-by-step guide to building intelligent applications using the familiar Spring Boot ecosystem.
Spring AI provides **Model Abstraction** and **Prompt Templates** to integrate Large Language Models (LLMs) like Google Gemini into Java applications seamlessly, following familiar Spring patterns.
Start a project via `start.spring.io`, adding **Spring Web** and **Spring AI** dependencies. Then, manually include the specific Gemini starter dependency in your `pom.xml`.
Generate your **Google AI Studio API Key** and configure it in `application.yml`, specifying the base URL and the target model, such as `gemini-2.0-flash-exp`.
Implement a `@Service` class that uses the injected `ChatClient`. This abstracts the LLM call using a fluent API: 'chatClient.prompt() .user(prompt).call().content()'.
A simple `@RestController` maps an endpoint (e.g., `/ai/ask`) to the service layer. It handles a request parameter (`?question=...`) and returns the AI-generated response as a string.
Test the running app (e.g., `http://localhost:8080/ai/ask`). Further expansion includes implementing **Prompt Templates** for structured output and enabling **Streaming Responses**.