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langchain4j-spring-boot-integration

Configure LangChain4j in Spring Boot with auto-configuration and declarative AI services.

3|Updated Oct 6, 2025
Search Tags:#rag#memory#starter#spring-boot#dependency-injection#langchain4j#ai-service
One-click install
npx skills add https://github.com/lgzarturo/springboot-course --skill langchain4j-spring-boot-integration-lgzarturo
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: langchain4j-spring-boot-integration
Source: https://github.com/lgzarturo/springboot-course/tree/main/.agents/skills/langchain4j-spring-boot-integration
Command: npx skills add https://github.com/lgzarturo/springboot-course --skill langchain4j-spring-boot-integration-lgzarturo

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill helps developers embed LangChain4j into Spring Boot apps by providing auto-configuration, Spring-friendly AI service patterns.

Core Features & Use Cases

  • Auto-configuration and Spring Starter integration for LangChain4j.
  • Declarative AI services with @AiService, chat memory management, and RAG pipelines with Spring Data.
  • Multi-provider support (OpenAI, Azure, Anthropic, Ollama) and bean-based configuration for production-grade apps.
  • Use cases: building AI-powered microservices, chat-assisted workflows, and knowledge-enabled applications within Spring ecosystems.

Quick Start

Create a Spring Boot project, add the LangChain4j Spring Boot starter dependencies, and define an @AiService interface to start building AI-powered features.

Frequently Asked Questions about langchain4j-spring-boot-integration

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I integrate LangChain4j into a Spring Boot application?▼

You can integrate LangChain4j into Spring Boot by adding the Spring Boot starter dependencies and defining an @AiService interface. This provides auto-configuration and Spring-friendly AI service patterns for your application.

Does the LangChain4j Spring Boot starter support chat memory and RAG pipelines?▼

Yes, the LangChain4j Spring Boot starter supports chat memory management within the Spring context and RAG pipelines with Spring Data. It enables declarative AI services and property-based configuration.

Can I configure multiple AI providers like OpenAI and Ollama in Spring Boot?▼

Yes, LangChain4j Spring Boot integration supports multi-provider configurations including OpenAI, Azure, Anthropic, and Ollama. It uses bean-based configuration to manage these providers for production-grade apps.

What is the best way to build AI-powered microservices using Spring Boot?▼

The best way to build AI-powered microservices is using the LangChain4j Spring Boot starter. It offers auto-configuration, declarative @AiService interfaces, and Spring Data integration for knowledge-enabled applications.

Can I use property-based configuration for AI services in Spring Boot?▼

Yes, LangChain4j Spring Boot integration supports property-based configuration. This allows you to define and manage AI services, chat memory, and model beans declaratively within your Spring ecosystem.

Do I need Spring Data to build RAG pipelines with LangChain4j?▼

Spring Data is used for RAG pipeline integration within the LangChain4j Spring Boot starter. It provides the Spring-friendly data access layer needed to build knowledge-enabled applications.

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