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feat(evaluation): 1차 수정본(최소 기능 부착 완료)
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‎backend/src/main/java/com/backend/domain/analysis/service/AnalysisService.java‎

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package com.backend.domain.analysis.service;
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import com.backend.domain.evaluation.service.EvaluationService;
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import com.backend.domain.repository.dto.response.RepositoryData;
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import com.backend.domain.analysis.entity.AnalysisResult;
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import com.backend.domain.analysis.repository.AnalysisResultRepository;
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public class AnalysisService {
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private final RepositoryService repositoryService;
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private final AnalysisResultRepository analysisResultRepository;
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private final EvaluationService evaluationService; // ★ 추가
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@Transactional
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public void analyze(String githubUrl) {
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log.info("🫠 ResponseData: {}", repositoryData);
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// TODO: AI 평가
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// EvaluationResult evaluation = evaluationService.evaluate(repositoryData);
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evaluationService.evaluateAndSave(repositoryData); // ★ 이 한 줄로 끝!
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// TODO: AI 평가 저장
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}

‎backend/src/main/java/com/backend/domain/evaluation/dto/EvaluationDto.java‎

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package com.backend.domain.evaluation.dto;
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import java.util.List;
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public class EvaluationDto {
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/** AI가 반환해야 할 점수 묶음 */
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public record Scores(
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int readme, // 0~25
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int test, // 0~25
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int commit, // 0~25
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int cicd // 0~25
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) {}
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/** AI가 반환해야 할 전체 결과 */
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public record AiResult(
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String summary,
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List<String> strengths,
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List<String> improvements,
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Scores scores
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) {}
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}

‎backend/src/main/java/com/backend/domain/evaluation/service/EvaluationService.java‎

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package com.backend.domain.evaluation.service;
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import com.backend.domain.analysis.entity.AnalysisResult;
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import com.backend.domain.analysis.entity.Score;
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import com.backend.domain.analysis.repository.AnalysisResultRepository;
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import com.backend.domain.evaluation.dto.EvaluationDto;
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import com.backend.domain.evaluation.dto.EvaluationDto.AiResult;
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import com.backend.domain.evaluation.dto.EvaluationDto.Scores;
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import com.backend.domain.evaluation.service.AiService;
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import com.backend.domain.evaluation.dto.AiDto; // 이미 존재하는 DTO(complete 요청용)
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import com.backend.domain.repository.dto.response.RepositoryData;
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import com.backend.domain.repository.entity.Repositories;
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import com.backend.domain.repository.repository.RepositoryJpaRepository;
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import com.backend.global.exception.BusinessException;
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import com.backend.global.exception.ErrorCode;
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import com.fasterxml.jackson.core.type.TypeReference;
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import com.fasterxml.jackson.databind.ObjectMapper;
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import lombok.RequiredArgsConstructor;
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import lombok.extern.slf4j.Slf4j;
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import org.springframework.stereotype.Service;
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import org.springframework.transaction.annotation.Transactional;
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import java.time.LocalDateTime;
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import java.util.List;
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import java.util.Objects;
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import java.util.regex.Matcher;
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import java.util.regex.Pattern;
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@Slf4j
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@Service
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@RequiredArgsConstructor
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public class EvaluationService {
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private final AiService aiService; // OpenAI 호출 래퍼(이미 프로젝트에 있음)
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private final ObjectMapper objectMapper = new ObjectMapper(); // JSON 파싱용
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private final RepositoryJpaRepository repositoryJpaRepository; // Repo 엔티티 조회
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private final AnalysisResultRepository analysisResultRepository; // 결과 저장
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/**
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* 평가 + 저장까지 한 번에 처리합니다.
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* @param data (RepositoryData) 수집된 깃허브 종합 데이터
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* @return 저장된 분석결과 ID(Long)
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*/
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@Transactional
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public Long evaluateAndSave(RepositoryData data) {
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// 1) AI 호출
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AiResult ai = callAiAndParse(data);
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// 2) Repositories 엔티티 찾기 (URL로 조회)
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String url = data.getRepositoryUrl();
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Repositories repo = repositoryJpaRepository.findByHtmlUrl(url)
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.orElseThrow(() -> new BusinessException(ErrorCode.GITHUB_REPO_NOT_FOUND));
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// 3) 엔티티 생성 (AnalysisResult + Score)
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AnalysisResult analysis = AnalysisResult.builder()
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.repositories(repo)
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.summary(safe(ai.summary()))
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.strengths(joinBullets(ai.strengths()))
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.improvements(joinBullets(ai.improvements()))
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.createDate(LocalDateTime.now())
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.build();
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Score score = Score.builder()
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.analysisResult(analysis) // ★ Score가 연관관계의 주인일 가능성이 높음
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.readmeScore(ai.scores().readme())
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.testScore(ai.scores().test())
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.commitScore(ai.scores().commit())
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.cicdScore(ai.scores().cicd())
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.build();
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// AnalysisResult ←→ Score 양쪽 세팅이 필요하다면,
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// AnalysisResult에 세터가 없을 수 있어도 JPA가 연관 찾아옵니다(지연 로딩).
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// 만약 세터가 있다면 아래 한 줄도 함께 두세요.
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// analysis.setScore(score);
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// 4) 저장 (cascade = ALL 이라면 Score도 함께 저장됩니다)
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AnalysisResult saved = analysisResultRepository.save(analysis);
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log.info("✅ Evaluation saved. analysisResultId={}", saved.getId());
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return saved.getId();
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}
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/**
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* 실제 AI 호출부
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* @param data (RepositoryData)
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* @return (EvaluationDto.AiResult) AI 결과
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*/
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public AiResult callAiAndParse(RepositoryData data) {
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try {
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// content: 원본 데이터(JSON으로 넘기면 모델이 읽기 쉽습니다)
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String content = objectMapper.writeValueAsString(data);
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// prompt: 모델에게 "이 스키마로만 JSON"을 만들라고 강하게 지시
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String prompt = """
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You are a senior software engineering reviewer.
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Analyze the given GitHub repository data and return ONLY a valid JSON. No commentary.
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Scoring: total 100 (README 0~25, TEST 0~25, COMMIT 0~25, CICD 0~25).
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Consider test folders, CI configs(e.g., .github/workflows), commit frequency/messages, README depth, etc.
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JSON schema:
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{
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"summary": "one-paragraph summary in Korean",
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"strengths": ["...","..."],
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"improvements": ["...","..."],
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"scores": { "readme": 0, "test": 0, "commit": 0, "cicd": 0 }
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}
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""";
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AiDto.CompleteResponse res =
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aiService.complete(new AiDto.CompleteRequest(content, prompt));
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String raw = res.result();
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String json = extractJson(raw);
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// {"summary":...,"strengths":[...],...} → AiResult로 역직렬화
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return objectMapper.readValue(json, new TypeReference<AiResult>() {});
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} catch (Exception e) {
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log.error("AI evaluation failed", e);
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throw new BusinessException(ErrorCode.INTERNAL_ERROR);
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}
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}
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/** 모델이 앞/뒤에 텍스트를 붙여도 JSON 본문만 뽑아냅니다. */
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private String extractJson(String text) {
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if (text == null) throw new IllegalArgumentException("AI result is null");
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// ```json ... ``` 같은 포맷도 대비
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String cleaned = text.replaceAll("```json", "```").trim();
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// 가장 바깥 { ... } 블록을 정규식으로 추출
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Pattern p = Pattern.compile("\\{.*}", Pattern.DOTALL);
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Matcher m = p.matcher(cleaned);
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if (m.find()) return m.group();
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// 못 찾으면 그대로 시도(모델이 운좋게 순수 JSON만 준 경우)
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return cleaned;
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}
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private String joinBullets(List<String> list) {
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if (list == null || list.isEmpty()) return "";
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return list.stream()
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.filter(Objects::nonNull)
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.map(String::trim)
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.filter(s -> !s.isEmpty())
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.map(s -> "- " + s)
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.reduce((a, b) -> a + "\n" + b)
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.orElse("");
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}
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private String safe(String s) { return s == null ? "" : s.trim(); }
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}

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