Spring AI로 OpenAI 연동하기 : Kotlin + Spring Boot

// build.gradle.kts

extra["springAiVersion"] = "1.0.3"
extra["springCloudVersion"] = "2025.0.0"

repositories {
    mavenCentral()
    maven { url = uri("https://repo.spring.io/milestone") }
    maven { url = uri("https://repo.spring.io/snapshot") }
}

dependencies {
    implementation("org.springframework.boot:spring-boot-starter-web")

    // Spring AI - OpenAI 연동에 필요한 두 가지 의존성
    implementation("org.springframework.ai:spring-ai-openai")
    implementation("org.springframework.ai:spring-ai-starter-model-openai")
}

dependencyManagement {
    imports {
        mavenBom("org.springframework.ai:spring-ai-bom:${property("springAiVersion")}")
        mavenBom("org.springframework.cloud:spring-cloud-dependencies:${property("springCloudVersion")}")
    }
}

spring:
  ai:
    openai:
      api-key: ${OPENAI_API_KEY}   # 환경변수로 주입 권장
      chat:
        options:
          model: gpt-4o            # 사용할 모델 지정
    chat:
      client:
        enabled: true              # ChatClient Auto-configuration 활성화

// config/ChatClientConfig.kt

package com.walter.config

import org.springframework.ai.chat.client.ChatClient
import org.springframework.context.annotation.Bean
import org.springframework.context.annotation.Configuration

@Configuration
class ChatClientConfig {

    @Bean
    fun openAiChatClient(builder: ChatClient.Builder): ChatClient {
        return builder.build()
    }
}

@Bean
fun openAiChatClient(builder: ChatClient.Builder): ChatClient {
    return builder
        .defaultSystem("당신은 친절한 한국어 어시스턴트입니다.")
        .defaultOptions(
            OpenAiChatOptions.builder()
                .model("gpt-4o")
                .temperature(0.7)
                .build()
        )
        .build()
}

// service/OpenAiService.kt

package com.walter.service

import com.walter.controller.dto.request.OpenAiChatResponse
import org.apache.commons.lang3.StringUtils
import org.springframework.ai.chat.client.ChatClient
import org.springframework.ai.chat.messages.UserMessage
import org.springframework.stereotype.Service

@Service
class OpenAiService(
    private val openAiChatClient: ChatClient
) {

    fun getChatCompletion(userComment: String): OpenAiChatResponse {
        val message = UserMessage.builder()
            .text(userComment)
            .build()

        val completion = openAiChatClient.prompt()
            .messages(listOf(message))
            .call()
            .content() ?: StringUtils.EMPTY

        return OpenAiChatResponse(completion)
    }
}

// 시스템 + 유저 메시지를 함께 전달하는 예시
val completion = openAiChatClient.prompt()
    .system("당신은 코드 리뷰 전문가입니다.")
    .user(userComment)
    .call()
    .content()

// controller/dto/request/OpenAiChatRequest.kt
data class OpenAiChatRequest(
    val prompt: String
)

// controller/dto/request/OpenAiChatResponse.kt
data class OpenAiChatResponse(
    val completion: String
)

// controller/dto/Rest.kt
import java.time.LocalDateTime

data class Rest<T>(
    val timeStamp: LocalDateTime,
    val data: T
) {
    companion object {
        fun <T> ok(data: T): Rest<T> = Rest(LocalDateTime.now(), data)
    }
}

// controller/OpenAiController.kt

package com.walter.controller

import com.walter.controller.dto.Rest
import com.walter.controller.dto.request.OpenAiChatRequest
import com.walter.controller.dto.request.OpenAiChatResponse
import com.walter.service.OpenAiService
import org.springframework.web.bind.annotation.PostMapping
import org.springframework.web.bind.annotation.RequestBody
import org.springframework.web.bind.annotation.RestController

@RestController
class OpenAiController(
    private val openAiService: OpenAiService
) {

    @PostMapping("/open-ai/request")
    fun getOpenAiResponse(
        @RequestBody openAiChatRequest: OpenAiChatRequest
    ): Rest<OpenAiChatResponse> {
        val response = openAiService.getChatCompletion(openAiChatRequest.prompt)
        return Rest.ok(response)
    }
}

# 환경변수로 API 키를 주입하면서 실행
OPENAI_API_KEY=sk-... ./gradlew bootRun

curl -X POST http://localhost:8080/open-ai/request \
  -H "Content-Type: application/json" \
  -d '{"prompt": "Spring AI가 무엇인지 한 문장으로 설명해줘"}'

{
  "timeStamp": "2026-03-19T10:30:00",
  "data": {
    "completion": "Spring AI는 Spring 생태계에서 AI 언어 모델과 쉽게 통합할 수 있도록 지원하는 공식 프레임워크입니다."
  }
}

ChatClient (추상화 인터페이스)
    ├── OpenAI ChatClient (spring-ai-openai)
    ├── Anthropic ChatClient (spring-ai-anthropic)
    ├── Ollama ChatClient (spring-ai-ollama)
    └── ...

fun getChatCompletionStream(userComment: String): Flux<String> {
    return openAiChatClient.prompt()
        .user(userComment)
        .stream()
        .content()
}

@GetMapping("/open-ai/stream", produces = [MediaType.TEXT_EVENT_STREAM_VALUE])
fun streamResponse(@RequestParam prompt: String): Flux<String> {
    return openAiService.getChatCompletionStream(prompt)
}