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[Refactor] 동기 api 삭제 (#38) #55

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Merged
shinae1023 merged 1 commit into from
May 20, 2026
Merged

[Refactor] 동기 api 삭제 (#38) #55

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133 changes: 8 additions & 125 deletions src/main/java/com/jobdri/jobdri_api/domain/jobposting/controller/JobPostingAiController.java
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Expand Up @@ -6,10 +6,8 @@
import com.jobdri.jobdri_api.domain.jobposting.dto.response.JobPostingAsyncStatusResponse;
import com.jobdri.jobdri_api.domain.jobposting.dto.response.JobPostingAsyncSubmitResponse;
import com.jobdri.jobdri_api.domain.jobposting.dto.response.JobPostingExtractResponse;
import com.jobdri.jobdri_api.domain.jobposting.dto.response.JobPostingIngestResponse;
import com.jobdri.jobdri_api.domain.jobposting.service.JobPostingAiService;
import com.jobdri.jobdri_api.domain.jobposting.service.JobPostingAsyncFacadeService;
import com.jobdri.jobdri_api.domain.jobposting.service.JobPostingIngestService;
import com.jobdri.jobdri_api.domain.user.service.UserService;
import com.jobdri.jobdri_api.global.apiPayload.ApiResponse;
import com.jobdri.jobdri_api.global.security.UserDetailsImpl;
Expand Down Expand Up @@ -38,7 +36,6 @@
public class JobPostingAiController {

private final JobPostingAiService jobPostingAiService;
private final JobPostingIngestService jobPostingIngestService;
private final JobPostingAsyncFacadeService jobPostingAsyncFacadeService;
private final UserService userService;

Expand Down Expand Up @@ -75,123 +72,25 @@ public ApiResponse<JobPostingExtractResponse> extractJobPostingFromMultipart(
}

@Operation(
summary = "채용 공고 추출부터 분류, 생성, 저장까지 일괄 처리",
description = "이미지 또는 텍스트 공고를 추출하고, trigram 후보 검색과 AI 재분류를 거쳐 최종 소분류를 선택한 뒤 공고를 생성하고 저장합니다."
summary = "채용 공고 비동기 일괄 처리 접수",
description = "이미지 또는 텍스트 공고를 비동기로 추출, 분류, 생성, 저장합니다. 응답으로 받은 taskId로 상태를 조회할 수 있습니다."
)
@ApiResponses(value = {
@io.swagger.v3.oas.annotations.responses.ApiResponse(
responseCode = "200",
description = "분류 confidence가 충분하여 저장까지 완료된 경우",
description = "비동기 작업이 정상 접수된 경우",
content = @Content(
mediaType = "application/json",
schema = @Schema(implementation = ApiResponse.class),
examples = @ExampleObject(value = """
{
"isSuccess": true,
"code": "COMMON2000",
"message": "채용 공고 추출 및 저장에 성공했습니다.",
"message": "채용 공고 비동기 작업 접수에 성공했습니다.",
"result": {
"savedToDatabase": true,
"message": "채용 공고 추출 및 저장에 성공했습니다.",
"extracted": {
"companyName": "삼성전자",
"jobTitle": "백엔드 개발자",
"task": "백엔드 서비스 개발 및 운영",
"requirements": "Java/Spring 기반 개발 경험",
"preferredQualifications": "대용량 트래픽 처리 경험",
"rawText": "채용 공고 원문 내용",
"confidence": 0.92
},
"candidates": [
{
"detailClassificationId": 101,
"detailClassificationName": "Java/Spring",
"middleClassificationName": "백엔드",
"bigClassificationName": "개발",
"score": 0.91
}
],
"classification": {
"detailClassificationId": 101,
"detailClassificationName": "Java/Spring",
"middleClassificationName": "백엔드",
"bigClassificationName": "개발",
"reason": "Spring Boot, JPA, API 개발 맥락이 가장 강합니다.",
"confidence": 0.87
},
"generated": {
"companyName": "삼성전자",
"jobTitle": "Java/Spring 백엔드 개발자",
"task": "백엔드 서비스 개발 및 운영\\nAPI 설계 및 성능 개선",
"requirements": "Java/Spring 기반 개발 경험\\nRDB 사용 경험",
"preferredQualifications": "대용량 트래픽 처리 경험\\nRedis 사용 경험",
"summary": "서비스 백엔드 개발과 운영을 담당할 인재를 찾습니다."
},
"saved": {
"jobPostingId": 10,
"companyId": 3,
"companyName": "삼성전자",
"detailClassificationId": 101,
"detailClassificationName": "Java/Spring",
"task": "백엔드 서비스 개발 및 운영\\nAPI 설계 및 성능 개선",
"requirement": "Java/Spring 기반 개발 경험\\nRDB 사용 경험",
"preferred": "대용량 트래픽 처리 경험\\nRedis 사용 경험"
}
},
"error": null
}
""")
)
),
@io.swagger.v3.oas.annotations.responses.ApiResponse(
responseCode = "200",
description = "분류 confidence가 낮아 저장을 보류한 경우",
content = @Content(
mediaType = "application/json",
schema = @Schema(implementation = ApiResponse.class),
examples = @ExampleObject(value = """
{
"isSuccess": true,
"code": "COMMON2000",
"message": "채용 공고 추출 및 저장에 성공했습니다.",
"result": {
"savedToDatabase": false,
"message": "소분류 분류 confidence가 낮아 저장을 보류했습니다.",
"extracted": {
"companyName": "어떤회사",
"jobTitle": "개발자",
"task": "서비스 개발",
"requirements": "개발 경험",
"preferredQualifications": "우대 사항",
"rawText": "채용 공고 원문 내용",
"confidence": 0.79
},
"candidates": [
{
"detailClassificationId": 101,
"detailClassificationName": "Java/Spring",
"middleClassificationName": "백엔드",
"bigClassificationName": "개발",
"score": 0.62
},
{
"detailClassificationId": 102,
"detailClassificationName": "Node.js",
"middleClassificationName": "백엔드",
"bigClassificationName": "개발",
"score": 0.58
}
],
"classification": {
"detailClassificationId": 101,
"detailClassificationName": "Java/Spring",
"middleClassificationName": "백엔드",
"bigClassificationName": "개발",
"reason": "후보 간 차이가 크지 않습니다.",
"confidence": 0.49
},
"generated": null,
"saved": null
"taskId": "f7f4eac0-b241-4d40-bf39-5b10c8a53943",
"status": "PENDING",
"message": "채용 공고 비동기 작업이 접수되었습니다."
},
"error": null
}
Expand All @@ -200,23 +99,7 @@ public ApiResponse<JobPostingExtractResponse> extractJobPostingFromMultipart(
)
})
@PostMapping(value = "/ingest", consumes = MediaType.MULTIPART_FORM_DATA_VALUE)
public ApiResponse<JobPostingIngestResponse> ingestJobPosting(
@AuthenticationPrincipal UserDetailsImpl userDetails,
@ModelAttribute JobPostingIngestMultipartRequest request
) {
var user = validateAuthenticatedUser(userDetails);
return ApiResponse.onSuccess(
"채용 공고 추출 및 저장에 성공했습니다.",
jobPostingIngestService.ingestAndCreate(user, request)
);
}

@Operation(
summary = "채용 공고 비동기 일괄 처리 접수",
description = "이미지 또는 텍스트 공고를 비동기로 추출, 분류, 생성, 저장합니다. 응답으로 받은 taskId로 상태를 조회할 수 있습니다."
)
@PostMapping(value = "/ingest/async", consumes = MediaType.MULTIPART_FORM_DATA_VALUE)
public ApiResponse<JobPostingAsyncSubmitResponse> submitIngestJobPostingAsync(
public ApiResponse<JobPostingAsyncSubmitResponse> ingestJobPosting(
@AuthenticationPrincipal UserDetailsImpl userDetails,
@ModelAttribute JobPostingIngestMultipartRequest request
) {
Expand Down
23 changes: 23 additions & 0 deletions src/main/java/com/jobdri/jobdri_api/domain/jobposting/service/JobPostingIngestService.java
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Expand Up @@ -17,7 +17,9 @@
import lombok.RequiredArgsConstructor;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.stereotype.Service;
import org.springframework.web.multipart.MultipartFile;

import java.io.IOException;
import java.util.List;

@Service
Expand All @@ -39,6 +41,8 @@ public JobPostingIngestResponse ingestAndCreate(User user, JobPostingIngestMulti
.userId(user.getId())
.rawText(request.rawText())
.sourceUrl(request.sourceUrl())
.imageBytes(readBytes(request.image()))
.imageContentType(readContentType(request.image()))
.build();
return ingestAndCreate(command);
}
Expand Down Expand Up @@ -128,4 +132,23 @@ private User resolveUser(JobPostingIngestCommand command) {
}
return userService.getUser(command.getUserId());
}

private byte[] readBytes(MultipartFile image) {
if (image == null || image.isEmpty()) {
return null;
}

try {
return image.getBytes();
} catch (IOException e) {
throw new GeneralException(GeneralErrorCode.INVALID_PARAMETER, "이미지 파일을 읽을 수 없습니다.");
}
}

private String readContentType(MultipartFile image) {
if (image == null || image.isEmpty()) {
return null;
}
return image.getContentType();
}
}
145 changes: 145 additions & 0 deletions ...est/java/com/jobdri/jobdri_api/domain/jobposting/service/JobPostingIngestServiceTest.java
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@@ -0,0 +1,145 @@
package com.jobdri.jobdri_api.domain.jobposting.service;

import com.jobdri.jobdri_api.domain.jobposting.dto.request.JobPostingCreateRequest;
import com.jobdri.jobdri_api.domain.jobposting.dto.request.JobPostingIngestMultipartRequest;
import com.jobdri.jobdri_api.domain.jobposting.dto.response.JobPostingClassificationCandidateResponse;
import com.jobdri.jobdri_api.domain.jobposting.dto.response.JobPostingClassificationResultResponse;
import com.jobdri.jobdri_api.domain.jobposting.dto.response.JobPostingExtractResponse;
import com.jobdri.jobdri_api.domain.jobposting.dto.response.JobPostingGenerateResponse;
import com.jobdri.jobdri_api.domain.jobposting.dto.response.JobPostingIngestResponse;
import com.jobdri.jobdri_api.domain.jobposting.dto.response.JobPostingResponse;
import com.jobdri.jobdri_api.domain.user.entity.User;
import com.jobdri.jobdri_api.domain.user.service.UserService;
import org.junit.jupiter.api.BeforeEach;
import org.junit.jupiter.api.DisplayName;
import org.junit.jupiter.api.Test;
import org.junit.jupiter.api.extension.ExtendWith;
import org.mockito.ArgumentCaptor;
import org.mockito.InjectMocks;
import org.mockito.Mock;
import org.mockito.junit.jupiter.MockitoExtension;
import org.springframework.mock.web.MockMultipartFile;
import org.springframework.test.util.ReflectionTestUtils;

import java.util.List;

import static org.assertj.core.api.Assertions.assertThat;
import static org.mockito.ArgumentMatchers.any;
import static org.mockito.ArgumentMatchers.eq;
import static org.mockito.Mockito.verify;
import static org.mockito.Mockito.when;

@ExtendWith(MockitoExtension.class)
class JobPostingIngestServiceTest {

@Mock
private JobPostingAiService jobPostingAiService;

@Mock
private JobPostingClassificationService jobPostingClassificationService;

@Mock
private JobPostingService jobPostingService;

@Mock
private UserService userService;

@InjectMocks
private JobPostingIngestService jobPostingIngestService;

private User user;

@BeforeEach
void setUp() {
user = User.signup("테스트 사용자", "ingest@example.com", "encoded-password");
ReflectionTestUtils.setField(user, "id", 1L);
ReflectionTestUtils.setField(jobPostingIngestService, "classificationConfidenceThreshold", 0.65);
}

@Test
@DisplayName("동기 ingest는 multipart 이미지와 content type을 추출 단계로 전달한다")
void ingestAndCreatePassesMultipartImageToExtract() {
MockMultipartFile image = new MockMultipartFile(
"image",
"posting.png",
"image/png",
new byte[]{1, 2, 3}
);
JobPostingIngestMultipartRequest request = new JobPostingIngestMultipartRequest(
"채용 공고 원문",
"https://example.com/job-posting",
image
);

JobPostingExtractResponse extracted = new JobPostingExtractResponse(
"해커스 교육그룹",
"클라우드 엔지니어",
"클라우드 운영",
"경력",
"",
"채용 공고 원문",
0.9
);
JobPostingClassificationCandidateResponse candidate = new JobPostingClassificationCandidateResponse(
1L,
"백엔드 개발",
"AI·개발·데이터",
"개발·데이터",
0.8
);
JobPostingClassificationResultResponse classification = new JobPostingClassificationResultResponse(
1L,
"백엔드 개발",
"AI·개발·데이터",
"개발·데이터",
"가장 적합한 소분류입니다.",
0.9
);
JobPostingGenerateResponse generated = new JobPostingGenerateResponse(
"해커스 교육그룹",
"클라우드 엔지니어",
"정제된 주요 업무",
"정제된 자격 요건",
"정제된 우대 사항",
"요약"
);
JobPostingResponse saved = JobPostingResponse.builder()
.jobPostingId(10L)
.userId(1L)
.companyId(2L)
.companyName("해커스 교육그룹")
.detailClassificationId(1L)
.detailClassificationName("백엔드 개발")
.task("정제된 주요 업무")
.requirement("정제된 자격 요건")
.preferred("정제된 우대 사항")
.build();

when(jobPostingAiService.extractJobPosting(any(), any(byte[].class), any(), any()))
.thenReturn(extracted);
when(jobPostingClassificationService.findCandidates(extracted, 5))
.thenReturn(List.of(candidate));
when(jobPostingAiService.classifyDetailClassification(extracted, List.of(candidate)))
.thenReturn(classification);
when(jobPostingAiService.generateJobPosting(any()))
.thenReturn(generated);
when(userService.getUser(1L)).thenReturn(user);
when(jobPostingService.createJobPosting(eq(user), any(JobPostingCreateRequest.class)))
.thenReturn(saved);

JobPostingIngestResponse response = jobPostingIngestService.ingestAndCreate(user, request);

ArgumentCaptor<byte[]> imageBytesCaptor = ArgumentCaptor.forClass(byte[].class);
ArgumentCaptor<String> contentTypeCaptor = ArgumentCaptor.forClass(String.class);
verify(jobPostingAiService).extractJobPosting(
eq("채용 공고 원문"),
imageBytesCaptor.capture(),
contentTypeCaptor.capture(),
eq("https://example.com/job-posting")
);

assertThat(imageBytesCaptor.getValue()).containsExactly(1, 2, 3);
assertThat(contentTypeCaptor.getValue()).isEqualTo("image/png");
assertThat(response.isSavedToDatabase()).isTrue();
}
}
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