"spring ai" stars:>50 language:java path:src/main/resources prompts You don’t need to wait for the PDF. Let’s build a microservice that uses the core concept from Spring AI in Action : portable LLM access . Step 1: Dependencies ( pom.xml ) <dependency> <groupId>org.springframework.ai</groupId> <artifactId>spring-ai-openai-spring-boot-starter</artifactId> <version>1.0.0-M2</version> </dependency> <dependency> <groupId>org.springframework.boot</groupId> <artifactId>spring-boot-starter-web</artifactId> </dependency> Step 2: Configuration ( application.yml ) spring: ai: openai: api-key: $OPENAI_API_KEY chat: options: model: gpt-4o-mini temperature: 0.7 Step 3: The AI Service (Inspired by Chapter 2) @Service public class LegalAssistant private final ChatClient chatClient; public LegalAssistant(ChatClient.Builder builder) this.chatClient = builder.build();
The intersection of enterprise Java (Spring Boot) and Generative AI is no longer a futuristic concept—it’s a present-day necessity. As developers scramble to integrate Large Language Models (LLMs) like OpenAI’s GPT-4, Google’s Gemini, or local Ollama models into production systems, a new beacon has emerged: Spring AI . spring ai in action pdf github
@Bean public VectorStore vectorStore(EmbeddingModel embeddingModel) return new SimpleVectorStore(embeddingModel); // or Redis, Chroma As developers scramble to integrate Large Language Models