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Merge pull request #30 from JobDri-Developer/feat/#27-job-posting
[Feat] 실제 공고 지원 API (#27)
2 parents 2d0d5b6 + 1582ae5 commit 289d712

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‎build.gradle‎

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@@ -43,6 +43,9 @@ dependencies {
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implementation 'org.springframework.retry:spring-retry'
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implementation 'org.springframework.boot:spring-boot-starter-aop'
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//openai
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implementation 'com.openai:openai-java:4.35.0'
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compileOnly 'org.projectlombok:lombok'
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developmentOnly 'org.springframework.boot:spring-boot-devtools'

‎src/main/java/com/jobdri/jobdri_api/domain/jobposting/controller/JobPostingAiController.java‎

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package com.jobdri.jobdri_api.domain.jobposting.controller;
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import com.jobdri.jobdri_api.domain.jobposting.dto.request.JobPostingExtractRequest;
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import com.jobdri.jobdri_api.domain.jobposting.dto.request.JobPostingExtractMultipartRequest;
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import com.jobdri.jobdri_api.domain.jobposting.dto.response.JobPostingExtractResponse;
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import com.jobdri.jobdri_api.domain.jobposting.service.JobPostingAiService;
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import com.jobdri.jobdri_api.global.apiPayload.ApiResponse;
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import io.swagger.v3.oas.annotations.Operation;
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import io.swagger.v3.oas.annotations.tags.Tag;
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import jakarta.validation.Valid;
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import lombok.RequiredArgsConstructor;
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import org.springframework.http.MediaType;
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import org.springframework.web.bind.annotation.PostMapping;
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import org.springframework.web.bind.annotation.RequestBody;
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import org.springframework.web.bind.annotation.ModelAttribute;
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import org.springframework.web.bind.annotation.RequestMapping;
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import org.springframework.web.bind.annotation.RestController;
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@RestController
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@RequiredArgsConstructor
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@RequestMapping("/api/job-postings")
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@Tag(name = "JobPosting AI", description = "채용 공고 추출 AI API")
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public class JobPostingAiController {
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private final JobPostingAiService jobPostingAiService;
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@Operation(
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summary = "채용 공고 정보 추출",
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description = "채용 공고 원문 텍스트를 기반으로 회사명, 직무명, 주요 업무, 자격 요건, 우대 사항을 AI로 추출합니다."
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)
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@PostMapping(value = "/extract", consumes = MediaType.APPLICATION_JSON_VALUE)
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public ApiResponse<JobPostingExtractResponse> extractJobPostingFromText(
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@Valid @RequestBody JobPostingExtractRequest request
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) {
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return ApiResponse.onSuccess(
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"채용 공고 추출에 성공했습니다.",
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jobPostingAiService.extractJobPosting(request.rawText())
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);
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}
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@Operation(
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summary = "채용 공고 정보 추출(이미지 또는 텍스트)",
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description = "프론트에서 캡처한 채용 공고 이미지 파일과 선택적 텍스트, 원본 URL을 함께 보내면 AI가 구조화된 채용 공고 정보를 추출합니다."
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)
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@PostMapping(value = "/extract", consumes = MediaType.MULTIPART_FORM_DATA_VALUE)
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public ApiResponse<JobPostingExtractResponse> extractJobPostingFromMultipart(
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@ModelAttribute JobPostingExtractMultipartRequest request
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) {
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return ApiResponse.onSuccess(
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"채용 공고 추출에 성공했습니다.",
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jobPostingAiService.extractJobPosting(request)
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);
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}
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}

‎src/main/java/com/jobdri/jobdri_api/domain/jobposting/dto/request/JobPostingExtractMultipartRequest.java‎

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package com.jobdri.jobdri_api.domain.jobposting.dto.request;
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import lombok.Getter;
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import lombok.Setter;
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import org.springframework.web.multipart.MultipartFile;
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@Getter
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@Setter
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public class JobPostingExtractMultipartRequest {
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private String rawText;
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private String sourceUrl;
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private MultipartFile image;
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}

‎src/main/java/com/jobdri/jobdri_api/domain/jobposting/dto/request/JobPostingExtractRequest.java‎

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package com.jobdri.jobdri_api.domain.jobposting.dto.request;
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import jakarta.validation.constraints.NotBlank;
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public record JobPostingExtractRequest(
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@NotBlank(message = "채용 공고 원문은 필수입니다.")
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String rawText
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) {
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}

‎src/main/java/com/jobdri/jobdri_api/domain/jobposting/dto/response/JobPostingExtractResponse.java‎

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package com.jobdri.jobdri_api.domain.jobposting.dto.response;
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import lombok.AllArgsConstructor;
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import lombok.Getter;
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import lombok.NoArgsConstructor;
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import lombok.Setter;
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@Getter
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@Setter
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@NoArgsConstructor
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@AllArgsConstructor
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public class JobPostingExtractResponse {
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private String companyName;
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private String jobTitle;
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private String task;
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private String requirements;
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private String preferredQualifications;
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private String rawText;
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private double confidence;
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}

‎src/main/java/com/jobdri/jobdri_api/domain/jobposting/service/JobPostingAiService.java‎

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package com.jobdri.jobdri_api.domain.jobposting.service;
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import com.jobdri.jobdri_api.domain.jobposting.dto.request.JobPostingExtractMultipartRequest;
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import com.jobdri.jobdri_api.domain.jobposting.dto.response.JobPostingExtractResponse;
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import com.jobdri.jobdri_api.global.apiPayload.code.GeneralErrorCode;
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import com.jobdri.jobdri_api.global.apiPayload.exception.GeneralException;
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import com.openai.client.OpenAIClient;
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import com.openai.models.responses.ResponseCreateParams;
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import com.openai.models.responses.ResponseInputContent;
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import com.openai.models.responses.ResponseInputImage;
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import com.openai.models.responses.ResponseInputItem;
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import com.openai.models.responses.StructuredResponse;
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import lombok.RequiredArgsConstructor;
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import lombok.extern.slf4j.Slf4j;
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import org.springframework.beans.factory.annotation.Value;
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import org.springframework.stereotype.Service;
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import org.springframework.web.multipart.MultipartFile;
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import java.io.IOException;
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import java.util.ArrayList;
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import java.util.List;
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import java.util.Set;
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import java.util.Base64;
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@Service
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@Slf4j
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@RequiredArgsConstructor
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public class JobPostingAiService {
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private final OpenAIClient openAIClient;
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@Value("${openai.model.job-posting-extractor:gpt-4o-mini}")
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private String extractionModel;
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private static final Set<String> SUPPORTED_IMAGE_TYPES = Set.of(
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"image/png",
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"image/jpeg",
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"image/jpg",
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"image/webp",
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"image/gif"
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);
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public JobPostingExtractResponse extractJobPosting(String rawText) {
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return extractJobPosting(rawText, null, null);
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}
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public JobPostingExtractResponse extractJobPosting(JobPostingExtractMultipartRequest request) {
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return extractJobPosting(request.getRawText(), request.getImage(), request.getSourceUrl());
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}
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public JobPostingExtractResponse extractJobPosting(String rawText, MultipartFile imageFile, String sourceUrl) {
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validateInput(rawText, imageFile);
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List<ResponseInputContent> contents = new ArrayList<>();
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contents.add(ResponseInputContent.ofInputText(
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com.openai.models.responses.ResponseInputText.builder()
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.text(buildPrompt(rawText, sourceUrl, imageFile != null))
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.build()
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));
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if (imageFile != null && !imageFile.isEmpty()) {
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contents.add(ResponseInputContent.ofInputImage(buildImageContent(imageFile)));
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}
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var params = ResponseCreateParams.builder()
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.model(extractionModel)
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.inputOfResponse(List.of(
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ResponseInputItem.ofMessage(
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ResponseInputItem.Message.builder()
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.role(ResponseInputItem.Message.Role.USER)
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.content(contents)
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.build()
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)
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))
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.temperature(0.1)
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.text(JobPostingExtractResponse.class)
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.build();
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try {
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StructuredResponse<JobPostingExtractResponse> response = openAIClient.responses().create(params);
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JobPostingExtractResponse extracted = extractStructuredContent(response);
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normalizeResponse(extracted, rawText);
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return extracted;
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} catch (Exception e) {
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log.error("채용 공고 추출 OpenAI API 호출 오류: {}", e.getMessage(), e);
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return createFallbackResponse(rawText);
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}
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}
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private String buildPrompt(String rawText, String sourceUrl, boolean hasImage) {
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String normalizedRawText = rawText == null ? "" : rawText;
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String normalizedSourceUrl = sourceUrl == null ? "" : sourceUrl;
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return """
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이 %s는 채용 공고입니다.
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회사명, 직무명, 주요 업무, 자격 요건, 우대 사항을 추출해주세요.
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반드시 아래 JSON 형식으로만 응답해주세요.
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설명 문장, 마크다운, 코드블럭은 포함하지 마세요.
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{
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"companyName": "string",
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"jobTitle": "string",
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"task": "string",
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"requirements": "string",
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"preferredQualifications": "string",
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"rawText": "string",
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"confidence": number
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}
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규칙:
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1. 이미지가 있으면 이미지 안의 채용 공고 문구를 읽어 rawText에 정리해주세요.
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2. 텍스트가 있으면 rawText에는 입력 원문을 최대한 그대로 넣어주세요.
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3. 이미지와 텍스트가 둘 다 있으면 둘을 함께 참고해서 가장 정확한 값으로 채워주세요.
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4. 정보가 없거나 확실하지 않으면 해당 필드는 빈 문자열로 두세요.
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5. confidence는 추출 결과 전체에 대한 신뢰도를 0~1 사이 실수로 반환하세요.
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6. JSON 외의 다른 텍스트는 절대 출력하지 마세요.
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[원본 URL]
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%s
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[채용 공고 텍스트]
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%s
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""".formatted(hasImage ? "이미지 또는 텍스트" : "텍스트", normalizedSourceUrl, normalizedRawText);
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}
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private ResponseInputImage buildImageContent(MultipartFile imageFile) {
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validateImage(imageFile);
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try {
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String contentType = imageFile.getContentType();
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String base64 = Base64.getEncoder().encodeToString(imageFile.getBytes());
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String dataUrl = "data:%s;base64,%s".formatted(contentType, base64);
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return ResponseInputImage.builder()
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.imageUrl(dataUrl)
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.detail(ResponseInputImage.Detail.HIGH)
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.build();
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} catch (IOException e) {
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throw new GeneralException(GeneralErrorCode.INVALID_PARAMETER, "이미지 파일을 읽을 수 없습니다.");
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}
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}
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private JobPostingExtractResponse extractStructuredContent(StructuredResponse<JobPostingExtractResponse> response) {
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return response.output().stream()
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.filter(item -> item.message().isPresent())
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.flatMap(item -> item.asMessage().content().stream())
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.filter(content -> content.outputText().isPresent())
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.map(content -> content.asOutputText())
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.findFirst()
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.orElseThrow(() -> new GeneralException(
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GeneralErrorCode.INTERNAL_SERVER_ERROR,
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"AI 응답에서 채용 공고 추출 결과를 찾을 수 없습니다."
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));
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}
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private void validateInput(String rawText, MultipartFile imageFile) {
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boolean hasRawText = rawText != null && !rawText.isBlank();
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boolean hasImage = imageFile != null && !imageFile.isEmpty();
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if (!hasRawText && !hasImage) {
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throw new GeneralException(
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GeneralErrorCode.INVALID_PARAMETER,
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"rawText 또는 image 중 하나는 반드시 포함되어야 합니다."
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);
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}
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}
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private void validateImage(MultipartFile imageFile) {
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String contentType = imageFile.getContentType();
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if (contentType == null || !SUPPORTED_IMAGE_TYPES.contains(contentType.toLowerCase())) {
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throw new GeneralException(
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GeneralErrorCode.INVALID_PARAMETER,
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"지원하는 이미지 형식은 png, jpg, jpeg, webp, gif 입니다."
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);
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}
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}
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private void normalizeResponse(JobPostingExtractResponse response, String rawText) {
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if (response == null) {
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throw new GeneralException(
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GeneralErrorCode.INTERNAL_SERVER_ERROR,
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"AI 응답이 비어 있습니다."
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);
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}
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if (response.getCompanyName() == null) {
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response.setCompanyName("");
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}
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if (response.getJobTitle() == null) {
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response.setJobTitle("");
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}
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if (response.getTask() == null) {
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response.setTask("");
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}
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if (response.getRequirements() == null) {
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response.setRequirements("");
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}
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if (response.getPreferredQualifications() == null) {
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response.setPreferredQualifications("");
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}
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if (response.getRawText() == null || response.getRawText().isBlank()) {
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response.setRawText(rawText == null ? "" : rawText);
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}
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double confidence = response.getConfidence();
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if (Double.isNaN(confidence) || Double.isInfinite(confidence)) {
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response.setConfidence(0.0);
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} else if (confidence < 0.0) {
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response.setConfidence(0.0);
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} else if (confidence > 1.0) {
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response.setConfidence(1.0);
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}
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}
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private JobPostingExtractResponse createFallbackResponse(String rawText) {
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return new JobPostingExtractResponse(
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"",
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"",
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"",
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"",
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"",
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rawText == null ? "" : rawText,
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0.0
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);
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}
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}

‎src/main/java/com/jobdri/jobdri_api/global/config/OpenAiConfig.java‎

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package com.jobdri.jobdri_api.global.config;
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import com.openai.client.OpenAIClient;
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import com.openai.client.okhttp.OpenAIOkHttpClient;
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import org.springframework.beans.factory.annotation.Value;
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import org.springframework.context.annotation.Bean;
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import org.springframework.context.annotation.Configuration;
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import java.time.Duration;
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@Configuration
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public class OpenAiConfig {
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@Value("${openai.api.key}")
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private String openAiApiKey;
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@Bean
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public OpenAIClient openAIClient() {
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return OpenAIOkHttpClient.builder()
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.apiKey(openAiApiKey)
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.timeout(Duration.ofSeconds(60))
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.maxRetries(2)
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.build();
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}
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}

‎src/main/resources/application-prod.yaml‎

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expiration:
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access-token: ${JWT_ACCESS_TOKEN_EXPIRATION}
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refresh-token: ${JWT_REFRESH_TOKEN_EXPIRATION}
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openai:
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api:
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key: ${OPENAI_API_KEY}
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model:
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job-posting-extractor: ${OPENAI_JOB_POSTING_MODEL:gpt-4o-mini}

‎src/main/resources/application.yaml‎

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expiration:
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access-token: ${JWT_ACCESS_TOKEN_EXPIRATION:3600000}
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refresh-token: ${JWT_REFRESH_TOKEN_EXPIRATION:1209600000}
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openai:
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api:
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key: ${OPENAI_API_KEY:}
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model:
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job-posting-extractor: ${OPENAI_JOB_POSTING_MODEL:gpt-4o-mini}

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