langchain4j-spring-boot-integration

SKILL.md

Spring Boot auto-configuration and declarative AI services for LangChain4j integration.

Provides property-based configuration for multiple AI providers (OpenAI, Azure, Ollama) with Spring Boot starters and automatic bean wiring

Enables interface-based AI service definitions using @AiService annotations combined with message templates and Spring dependency injection

Supports RAG systems through configurable embedding stores (pgvector, Neo4j, Pinecone) and document ingestion pipelines

Includes tool registration via Spring components, conversation memory management, and streaming response handling with Reactor

LangChain4j Spring Boot Integration

Integrate LangChain4j with Spring Boot using declarative AI Services, auto-configuration, and Spring Boot starters. Configure AI model beans, set up chat memory, implement RAG pipelines with Spring Data, and build production-ready AI applications.

When to Use

Use this skill when:

Integrating LangChain4j into existing Spring Boot applications

Building AI-powered microservices with Spring Boot

Configuring AI model beans with @Bean annotations

Setting up auto-configuration for AI models and services

Creating declarative AI Services with Spring dependency injection

Implementing RAG systems with Spring Data integrations

Setting up chat memory with Spring context management

Configuring multiple AI providers (OpenAI, Azure, Ollama, Anthropic)

Building production-ready AI applications with Spring Boot

Overview