langchain4j-ai-services-patterns

# LangChain4j AI Services Patterns This skill provides guidance for building declarative AI Services with LangChain4j using interface-based patterns, annotations for system and user messages, memory management, tools integration, and advanced AI application patterns that abstract away low-level LLM interactions. ## Overview LangChain4j AI Services define AI functionality using Java interfaces with annotations, providing type-safe, declarative AI with minimal boilerplate. ## When to Use Use this skill when: - Building declarative AI services with minimal boilerplate using Java interfaces - Creating type-safe conversational AI with memory management - Implementing AI agents with function/tool calling capabilities - Designing AI services returning structured data (enums, POJOs, lists) - Integrating RAG patterns declaratively ## Instructions Follow these steps to create declarative AI Services with LangChain4j: ### 1. Define AI Service Interface Create a Java interface with method signatures for AI interactions: ```java interface Assistant { String chat(String userMessage); } ``` ### 2. Add Annotations for System and User Messages Use `@SystemMessage` and `@UserMessage` annotations to define prompts: ```java interface CustomerSupportBot { @SystemMessage("You are a helpful customer support agent for TechCorp") String handleInquiry(String customerMessage); @UserMessage("Analyze sentiment: {{it}}") Sentiment analyzeSentiment(String feedback); } ``` ...