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Spring / Spring Boot 4 Basics Interview Questions

What is Spring AI and how does it integrate with Spring Boot 4?

Spring AI is a first-class Spring ecosystem project that reached 1.0 GA in May 2025 and is now on a 2.x development track. It provides a model-agnostic abstraction layer for integrating LLMs, vector stores, and AI pipelines into Spring Boot 4 applications.

Spring AI core concepts
ConceptDescription
ChatModelAbstraction over LLM providers (OpenAI, Gemini, Anthropic, Mistral, Ollama, etc.)
EmbeddingModelGenerates vector embeddings from text
VectorStoreAuto-configured integration with 10+ vector databases (pgvector, Pinecone, Chroma, Weaviate, etc.)
ChatClientFluent API for building prompt chains, advisors, and tool calling
Tool callingLLMs can invoke Spring beans as tools (@Tool annotation)
MCP supportModel Context Protocol server integration
RAG pipelinesQuestionAnswerAdvisor for retrieval-augmented generation
// Spring AI: ChatClient in Spring Boot 4
@Service
public class CustomerSupportService {

    private final ChatClient chatClient;

    public CustomerSupportService(ChatClient.Builder builder,
                                  VectorStore vectorStore) {
        this.chatClient = builder
            .defaultSystem("You are a helpful customer support agent.")
            .defaultAdvisors(
                // RAG: retrieve relevant documents before answering
                new QuestionAnswerAdvisor(vectorStore),
                new MessageChatMemoryAdvisor(new InMemoryChatMemory())
            )
            .build();
    }

    public String answer(String question) {
        return chatClient.prompt()
            .user(question)
            .call()
            .content();
    }
}

// Tool calling: LLM can call Spring beans as tools
@Service
public class OrderTools {
    @Tool(description = "Get the current status of an order by its ID")
    public String getOrderStatus(String orderId) {
        return orderService.findById(orderId).status().name();
    }
}

# application.yml: Spring AI OpenAI configuration
spring:
  ai:
    openai:
      api-key: ${OPENAI_API_KEY}
      chat:
        options:
          model: gpt-4o-mini
          temperature: 0.7

What is the primary advantage of Spring AI's ChatModel abstraction over calling LLM APIs directly?
What does the @Tool annotation do in Spring AI when used on a Spring bean method?

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