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Spring / Spring AI interview questions

What are the Spring AI Spring Initializr options and how do you bootstrap a project?

The fastest way to start a Spring AI project is through start.spring.io. The Spring Initializr now includes Spring AI dependencies as first-class options in the AI category. You pick the AI starters you need alongside your other Spring Boot starters, and the generator creates a ready-to-run project with correct BOMs, repository declarations, and starter wiring.

Available AI starters in Spring Initializr include: OpenAI, Azure OpenAI, Ollama, Anthropic Claude, Mistral AI, Amazon Bedrock, Google Vertex AI Gemini, as well as vector store starters for PgVector, Redis, Chroma, and others.

If you prefer the Spring CLI:

spring boot new --dependencies spring-ai-openai,web,actuator my-ai-app

If you bootstrap manually (adding dependencies by hand), two things are commonly missed:

  1. Import the spring-ai-bom in dependencyManagement so you do not have to manage individual module versions.
  2. Add the Spring Milestone repository because Spring AI releases are not yet published to Maven Central as GA artifacts for some versions.
<repositories>
    <repository>
        <id>spring-milestones</id>
        <url>https://repo.spring.io/milestone</url>
    </repository>
</repositories>

More Related questions...

What is Spring AI and what problem does it solve? What AI model providers does Spring AI support? What is the difference between ChatModel and ChatClient in Spring AI? How do you create and use a ChatClient in a Spring Boot application? What message types does Spring AI support in a Prompt? What is Retrieval-Augmented Generation (RAG) and how does Spring AI implement it? What is a VectorStore in Spring AI and which implementations are available? What is an EmbeddingModel in Spring AI and why must the same model be used for ingestion and retrieval? How does PromptTemplate work in Spring AI? What is structured output in Spring AI and how does it work internally? What are Advisors in Spring AI and what built-in advisors are available? How does conversation memory work in Spring AI? What is function calling (tool use) in Spring AI and how do you register a function? How do you stream responses from an LLM in Spring AI? What is the Document class in Spring AI and how is it used in RAG? What is TokenTextSplitter and why is document chunking necessary? What DocumentReaders does Spring AI provide for loading content into the RAG pipeline? What is the Spring AI ETL pipeline and how does it work? How does Spring AI integrate with Spring Boot auto-configuration? What are ChatOptions in Spring AI and how do you apply them per-request? What is the SearchRequest API in Spring AI's VectorStore? How does Spring AI support multimodal inputs such as images? What is image generation in Spring AI and how do you use ImageModel? How does Spring AI handle observability and what metrics does it expose? How do you test Spring AI components without calling real AI APIs? What is the Spring AI MCP (Model Context Protocol) integration? What is the role of MetadataEnricher and KeywordMetadataEnricher in Spring AI? What are the Spring AI Chat Model options for controlling response determinism? What is the Spring AI Agentic pattern and how does it differ from a single-turn chat call? What does the spring-ai-bom do and why should you use it? What is PgVector and how do you configure it as a VectorStore in Spring AI? How does Spring AI's retry and resilience mechanism work for LLM API calls? What is the Spring AI Evaluation framework and how do you use it? How do you use Spring AI with Spring WebFlux for a reactive AI endpoint? What are the Spring AI Spring Initializr options and how do you bootstrap a project? What is the Spring AI content moderation strategy and how do you implement it? How does Spring AI support multi-tenancy where different users need different LLM configurations? What is the Spring AI AudioModel and how does it support speech synthesis? How does Spring AI handle prompt injection attacks? What are the performance tuning strategies for a Spring AI RAG application at scale? How does Spring AI support the Ollama provider for local model development? What is semantic caching in Spring AI and how would you implement it? How does Spring AI integrate with Spring Security for securing AI endpoints? How does Spring AI's Document metadata filtering work with PgVector and what filter operators are available?
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