A hands-on tutorial covering LangChain4j's AiServices abstraction for interacting with LLMs in Java. Shows how to define typed Java interfaces that map inputs and outputs to specific formats using annotations like @UserMessage, @SystemMessage, and @StructuredPrompt. Covers practical use cases including text summarization in plain text, structured text, JSON, and Java record objects, as well as sentiment analysis using enums. Also introduces @StructuredPrompt for mapping Java objects to prompts.
Table of contents
Using AiServices to interact with LLMsSummarizing the given textMapping Java object to UserMessage using StructuredPromptSentiment AnalysisConclusionSort: