From Sticky Notes to Smart Answers: RAG Implementation with Spring Boot 4.1 & Spring AI 2.0
In previous articles, we integrated local LLMs for test generation and set up semantic search with Qdrant. Now it’s time to tie these ideas together and build a proper RAG application. We’ll create a service that can retrieve relevant notes, pass them into an LLM context, and — crucially — use Tool Calling to perform exact calculations. Using monthly expense tracking as our example, we’ll see how Spring AI 2.0 and Spring Boot 4.1 help unify search, generation, and external tools into a cohesive, reliable solution. ...