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:

interface Assistant {
    String chat(String userMessage);
}

2. Add Annotations for System and User Messages

Use @SystemMessage and @UserMessage annotations to define prompts:

interface CustomerSupportBot {
    @SystemMessage("You are a helpful customer support agent for TechCorp")
    String handleInquiry(String customerMessage);

    @UserMessage("Analyze sentiment: {{it}}")
    Sentiment analyzeSentiment(String feedback);
}

3. Create AI Service Instance

Use AiServices builder or create to instantiate the service:

// Simple creation
Assistant assistant = AiServices.create(Assistant.class, chatModel);

// Or with builder for advanced configuration
Assistant assistant = AiServices.builder(Assistant.class)
    .chatModel(chatModel)
    .build();

4. Configure Memory for Multi-turn Conversations

Add memory management using @MemoryId for multi-user scenarios:

interface MultiUserAssistant {
    String chat(@MemoryId String userId, String userMessage);
}

Assistant assistant = AiServices.builder(MultiUserAssistant.class)
    .chatModel(model)
    .chatMemoryProvider(userId -> MessageWindowChatMemory.withMaxMessages(10))
    .build();