Beginner8 min read
Introduction to the Spring AI Framework
What Spring AI is, how its abstractions map onto Spring concepts you already know, when to choose it over LangChain4j, and a working ChatClient example in under five minutes.
Read tutorialAI Engineering · Phase 1
Spring Boot AI Integration
Wire large language models into Spring Boot with Spring AI — chat clients, embeddings, RAG, tool calling, structured output, and production observability.
Beginner6 min read
Setting Up Spring AI with OpenAI
A complete Spring Boot + OpenAI setup: dependencies, API key management, model options, timeouts, retries and the five errors every developer hits on the first run.
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The Spring AI ChatClient API
Master the Spring AI ChatClient: system messages, prompt templates, streaming with SSE, chat memory, advisors and per-call options — with complete Spring Boot code.
Read tutorialBeginner5 min read
Prompt Engineering for Java Developers
Prompt engineering explained for engineers, not marketers: system prompts, few-shot, delimiters, output contracts and grounding — each as testable Spring AI code, not vibes.
Read tutorialIntermediate6 min read
Spring AI Embeddings & Vector Stores
How embeddings and vector stores work in Spring AI, with a complete pgvector Spring Boot setup — schema, indexes, metadata filtering, dimensions and the mistakes that force a re-ingest.
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Building a RAG Pipeline with Spring Boot
Build a production RAG pipeline in Spring Boot: document ingestion, chunking, pgvector retrieval, the QuestionAnswerAdvisor, citations, evaluation and the failure modes nobody warns you about.
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Spring AI Function Calling & @Tool
How Spring AI function calling works, with complete @Tool examples: registering tools, typed parameters, error handling, the agent loop, and how to stop a tool-using model doing damage.
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Structured Output with Spring AI
Turn LLM responses into typed Java objects with Spring AI: BeanOutputConverter, .entity(), generic lists, enums and validation — the reliable alternative to parsing text by hand.
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Multimodal AI with Spring Boot
Send images and audio to vision models from Spring Boot with Spring AI: the Media API, image analysis, document extraction from scans, and handling multimodal input safely.
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Spring AI with Ollama (Local LLMs)
Run local LLMs in Spring Boot with Spring AI and Ollama: setup, model selection, offline development, cost and privacy trade-offs, and when a local model is the right call.
Read tutorialAdvanced4 min read
Spring AI Observability & Monitoring
Instrument Spring AI with Micrometer and OpenTelemetry: token and cost metrics per feature, latency tracking, tracing model calls, and dashboards that catch a cost problem before the invoice does.
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Security in AI-Powered Spring Applications
Secure a Spring Boot AI application against the OWASP LLM Top 10: prompt injection defenses, output validation, rate limiting, PII handling and safe tool authorization — with code.
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Testing AI Applications
How to test non-deterministic AI code in Spring Boot: mocking the ChatModel for unit tests, golden datasets for retrieval, property-based assertions, and LLM-as-judge for quality.
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