refactor: chat controller에 DTO 적용

Author: ChoHadam

src/main/kotlin/com/example/spring_ai_tutorial/controller/ChatController.kt

@@ -1,5 +1,7 @@
 package com.example.spring_ai_tutorial.controller
 
+import com.example.spring_ai_tutorial.domain.dto.ApiResponseDto
+import com.example.spring_ai_tutorial.domain.dto.ChatRequestDto
 import com.example.spring_ai_tutorial.service.ChatService
 import io.github.oshai.kotlinlogging.KotlinLogging
 import io.swagger.v3.oas.annotations.Operation
@@ -35,22 +37,22 @@ class ChatController(
     @SwaggerResponse(
         responseCode = "200",
         description = "LLM 응답 성공",
-        content = [Content(schema = Schema(implementation = ApiResponse::class))]
+        content = [Content(schema = Schema(implementation = ApiResponseDto::class))]
     )
     @SwaggerResponse(responseCode = "400", description = "잘못된 요청")
     @SwaggerResponse(responseCode = "500", description = "서버 오류")
     @PostMapping("/query")
     suspend fun sendMessage(
         @Parameter(description = "채팅 요청 객체", required = true)
-        @RequestBody request: ChatRequest
-    ): ResponseEntity<ApiResponse<Map<String, Any>>> {
+        @RequestBody request: ChatRequestDto
+    ): ResponseEntity<ApiResponseDto<Map<String, Any>>> {
         logger.info { "Chat API 요청 받음: model=${request.model}" }
 
         // 유효성 검사
         if (request.query.isBlank()) {
             logger.warn { "빈 질의가 요청됨" }
             return ResponseEntity.badRequest().body(
-                ApiResponse(success = false, error = "질의가 비어있습니다.")
+                ApiResponseDto(success = false, error = "질의가 비어있습니다.")
             )
         }
 
@@ -68,15 +70,15 @@ class ChatController(
 
             response?.let { chatResponse ->
                 ResponseEntity.ok(
-                    ApiResponse(
+                    ApiResponseDto(
                         success = true,
                         data = mapOf("answer" to chatResponse.result.output.text)
                     )
                 )
             } ?: run {
                 logger.error { "LLM 응답 생성 실패" }
                 ResponseEntity.status(HttpStatus.INTERNAL_SERVER_ERROR).body(
-                    ApiResponse(
+                    ApiResponseDto(
                         success = false,
                         error = "LLM 응답 생성 중 오류 발생"
                     )
@@ -85,32 +87,11 @@ class ChatController(
         } catch (e: Exception) {
             logger.error(e) { "Chat API 처리 중 오류 발생" }
             ResponseEntity.status(HttpStatus.INTERNAL_SERVER_ERROR).body(
-                ApiResponse(
+                ApiResponseDto(
                     success = false,
                     error = e.message ?: "알 수 없는 오류 발생"
                 )
             )
         }
     }
 }
-
-@Schema(description = "채팅 요청 데이터 모델")
-data class ChatRequest(
-    @Schema(description = "사용자 질문", example = "안녕하세요")
-    val query: String,
-
-    @Schema(description = "사용할 LLM 모델", example = "gpt-3.5-turbo", defaultValue = "gpt-3.5-turbo")
-    val model: String = "gpt-3.5-turbo"
-)
-
-@Schema(description = "API 응답 포맷")
-data class ApiResponse<T>(
-    @Schema(description = "요청 처리 성공 여부")
-    val success: Boolean,
-
-    @Schema(description = "성공 응답 데이터")
-    val data: T? = null,
-
-    @Schema(description = "실패 오류 메시지")
-    val error: String? = null
-)