Spring AI

Pattern: Process

Framework for integrating AI models into Spring Boot applications. Targets Spring AI 1.0+ on Boot 3.4+, Java 17+.

Mental model: Spring AI mirrors Spring's HTTP client layering. ChatModel is the low-level provider wrapper (like RestTemplate). ChatClient is the fluent high-level API (like RestClient) — it adds advisors, tools, memory, and structured output. Always use ChatClient unless you need raw provider access.

Do NOT Load for general machine learning, data science, or non-LLM AI. For event-driven patterns use spring-events. For web endpoints exposing AI features use spring-web.

When to Use

• Calling LLM providers (OpenAI, Anthropic, Ollama, Bedrock, etc.) from Spring Boot
• Converting LLM responses to typed Java objects (structured output)
• Registering tools/functions that LLMs can invoke
• Building RAG pipelines with vector stores and document ingestion
• Managing conversation history with chat memory
• Creating or consuming MCP servers
• Adding observability to AI calls