langchain4j-spring-boot-integration

Spring Boot integration with LangChain4j uses auto-configuration and starters to wire AI services via dependency injection. Include LangChain4j Spring Boot starters in your pom.xml or build.gradle, then declare @AiService beans to automatically configure chat models, embeddings, and RAG components with property-based configuration.

Yes. LangChain4j Spring Boot integration provides declarative AI services wired through Spring DI. Define @AiService interfaces and let Spring auto-wire them as beans, eliminating manual instantiation and allowing configuration through Spring properties and profiles.

Production patterns include embedding store auto-configuration, multi-provider model support for portability, property-driven configuration for environment-specific profiles, REST and streaming endpoints for client access, observability hooks for monitoring, and security configurations for sensitive data handling.

The integration supports multi-provider model configuration through Spring properties. Define provider credentials and model settings in application.yml or environment variables, then use Spring profiles to activate provider-specific beans for different deployment environments.

Yes. The integration provides patterns for building REST and streaming endpoints that expose AI services as HTTP APIs. Spring Boot controllers can inject @AiService beans and handle request/response mapping, with built-in support for streaming chat and event-driven architectures.

The integration covers observability through metrics and tracing hooks compatible with Spring Actuator, and security via Spring Security integration for authentication and authorization. Environment-specific profiles enable secure credential management across development, staging, and production contexts.