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Spring Boot Integration

LangChain4j provides Spring Boot starters for popular integrations.

To use one of the Spring Boot starters, first import the corresponding dependency:

<dependency>
    <groupId>dev.langchain4j</groupId>
    <artifactId>langchain4j-open-ai-spring-boot-starter</artifactId>
    <version>0.30.0</version>
</dependency>

Then, you can configure model parameters in the application.properties file as follows:

langchain4j.open-ai.chat-model.api-key=${OPENAI_API_KEY}
...

The complete list of supported properties can be found here.

In this case, an instance of OpenAiChatModel (an implementation of a ChatLanguageModel) will be automatically created, and you can autowire it where needed.

If you need an instance of a StreamingChatLanguageModel, use the streaming-chat-model instead of the chat-model properties:

langchain4j.open-ai.streaming-chat-model.api-key=${OPENAI_API_KEY}
...

LangChain4j Spring Boot Starter​

LangChain4j provides a Spring Boot starter for auto-configuring AI Services, RAG, Tools etc.

Assuming you have already imported one of the integrations starters (see above), import langchain4j-spring-boot-starter:

<dependency>
    <groupId>dev.langchain4j</groupId>
    <artifactId>langchain4j-spring-boot-starter</artifactId>
    <version>0.30.0</version>
</dependency>

You can now define AI Service interface and annotate it with @AiService:

@AiService
interface Assistant {

    @SystemMessage("You are a polite assistant")
    String chat(String userMessage);
}

Think of it as a standard Spring Boot @Service, but with AI capabilities.

When the application starts, LangChain4j starter will scan the classpath and find all interfaces annotated with @AiService. For each AI Service found, it will create an implementation of this interface using all LangChain4j components available in the application context and will register it as a bean, so you can auto-wire it where needed:

@RestController
class AssistantController {

    @Autowired
    Assistant assistant;

    @GetMapping("/chat")
    public String chat(String message) {
        return assistant.chat(message);
    }
}

More details here.

Supported Spring Boot Versions​

Spring Boot 2 and 3 are supported.

Examples​