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Merged
yeonjae02 merged 1 commit into from
Oct 27, 2025
Merged

feat: defalut 값 설정 #143

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2 changes: 1 addition & 1 deletion ...main/java/com/howWeather/howWeather_backend/domain/ai_model/schedular/ModelScheduler.java
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Original file line number Diff line number Diff line change
Expand Up @@ -43,7 +43,7 @@ public class ModelScheduler {
* 매일 새벽 5시에 모델 서버로 예측에 필요한 데이터를 암호화된 형태로 전송합니다.
*/
@Transactional
@Scheduled(cron = "0 10 16 * * *")
@Scheduled(cron = "0 0 5 * * *")
public void pushPredictionAESDataToAiServer() {
try {
List<Member> members = memberRepository.findAllByIsDeletedFalse();
Expand Down
173 changes: 128 additions & 45 deletions ...java/com/howWeather/howWeather_backend/domain/ai_model/service/RecommendationService.java
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Expand Up @@ -44,20 +44,110 @@ public List<RecommendPredictDto> getRecommendList(Member member) {
LocalDate targetDate = now.isBefore(LocalTime.of(6, 0)) ? today.minusDays(1) : today;

List<ClothingRecommendation> modelPredictList = getModelPrediction(member.getId(), targetDate);

Closet closet = getClosetWithAll(member);
List<RecommendPredictDto> result = new ArrayList<>();
for (ClothingRecommendation recommendation : modelPredictList) {
RecommendPredictDto dto = makeResultForPredict(closet, recommendation, member);
Closet closet = getClosetWithAll(member);
if (!modelPredictList.isEmpty()) {
log.info("[AI 추천] memberId={} AI 예측 결과 사용 ({}개)", member.getId(), modelPredictList.size());
for (ClothingRecommendation recommendation : modelPredictList) {
RecommendPredictDto dto = makeResultForPredict(closet, recommendation, member);
boolean isUppersExist = dto.getUppersTypeList() != null && !dto.getUppersTypeList().isEmpty();
boolean isFeelingExist = dto.getFeelingList() != null && !dto.getFeelingList().isEmpty();
if (isUppersExist && isFeelingExist) {
result.add(dto);
}
}
} else {
result.addAll(generateFallbackRecommendation(member, targetDate, closet));
}

boolean isUppersExist = dto.getUppersTypeList() != null && !dto.getUppersTypeList().isEmpty();
boolean isFeelingExist = dto.getFeelingList() != null && !dto.getFeelingList().isEmpty();
return result;
}

private List<RecommendPredictDto> generateFallbackRecommendation(Member member, LocalDate targetDate, Closet closet) {
log.warn("[Fallback 추천] memberId={} AI 예측 결과 없음. 대체 추천 로직 시작.", member.getId());
List<RecommendPredictDto> fallbackResult = new ArrayList<>();

if (isUppersExist && isFeelingExist) {
result.add(dto);
try {
final Long MIN_OUTER_TYPE = 10L;
final Long MAX_OUTER_TYPE = 25L;
final Long MIN_UPPER_TYPE = 3L;
final Long MAX_UPPER_TYPE = 9L;

List<Integer> fallbackOuterTypes = closet.getOuterList().stream()
.filter(Outer::isActive)
.filter(outer -> outer.getOuterType() != null &&
outer.getOuterType() >= MIN_OUTER_TYPE &&
outer.getOuterType() <= MAX_OUTER_TYPE)
.map(outer -> outer.getOuterType().intValue())
.distinct()
.collect(Collectors.toList());

List<Integer> fallbackUpperTypes = closet.getUpperList().stream()
.filter(Upper::isActive)
.filter(upper -> upper.getUpperType() != null &&
upper.getUpperType() >= MIN_UPPER_TYPE &&
upper.getUpperType() <= MAX_UPPER_TYPE)
.map(upper -> upper.getUpperType().intValue())
.distinct()
.collect(Collectors.toList());

if (fallbackOuterTypes.isEmpty() && fallbackUpperTypes.isEmpty()) {
log.info("[Fallback 추천] memberId={} 추천할 활성 상의 또는 아우터 없음 (기준: Upper {}-{}, Outer {}-{}). 예외 발생.",
member.getId(), MIN_UPPER_TYPE, MAX_UPPER_TYPE, MIN_OUTER_TYPE, MAX_OUTER_TYPE);
throw new CustomException(ErrorCode.NO_PREDICT_DATA);
}

List<WeatherFeelingDto> fallbackFeelingList = createFallbackFeelingList(member, targetDate);

RecommendPredictDto fallbackDto = RecommendPredictDto.builder()
.feelingList(fallbackFeelingList)
.uppersTypeList(fallbackUpperTypes)
.outersTypeList(fallbackOuterTypes)
.build();
fallbackResult.add(fallbackDto);
log.info("[Fallback 추천] memberId={} 최종 추천 결과: Uppers={}, Outers={}, FeelingsGenerated={}",
member.getId(), fallbackUpperTypes, fallbackOuterTypes, !fallbackFeelingList.isEmpty());

} catch (CustomException e) {
log.error("[Fallback 추천 실패] memberId={} 처리 중 Custom 오류: {}", member.getId(), e.getMessage());
throw new CustomException(ErrorCode.NO_PREDICT_DATA);
} catch (Exception e) {
log.error("[Fallback 추천 실패] memberId={} 알 수 없는 오류 발생: {}", member.getId(), e.getMessage(), e);
throw new CustomException(ErrorCode.NO_PREDICT_DATA);
}
return result;

return fallbackResult;
}

private List<WeatherFeelingDto> createFallbackFeelingList(Member member, LocalDate targetDate) {
List<WeatherFeelingDto> fallbackFeelingList = new ArrayList<>();
String regionName = member.getRegionName() != null ? member.getRegionName() : "서울특별시 용산구";
List<Integer> targetHours = List.of(9, 12, 15, 18, 21);
final int DEFAULT_FEELING = 2;

try {
List<WeatherForecast> forecasts = weatherForecastRepository
.findByRegionNameAndForecastDateAndHourInOrderByHourAsc(regionName, targetDate, targetHours);

if (!forecasts.isEmpty()) {
for (WeatherForecast forecast : forecasts) {
WeatherFeelingDto dto = WeatherFeelingDto.builder()
.date(forecast.getForecastDate())
.time(forecast.getHour())
.feeling(DEFAULT_FEELING)
.temperature(forecast.getTemperature())
.build();
fallbackFeelingList.add(dto);
}
log.info("[Fallback 추천] memberId={} 기본 체감온도(2)로 그래프 생성 완료 ({}개 시간대)", member.getId(), fallbackFeelingList.size());
} else {
log.warn("[Fallback 추천] memberId={} 날씨 예보 데이터가 없어 체감온도 그래프를 생성할 수 없습니다. region={}, date={}, hours={}",
member.getId(), regionName, targetDate, targetHours);
}
} catch (Exception e) {
log.error("[Fallback 추천] memberId={} 날씨 예보 조회 중 오류 발생: {}", member.getId(), e.getMessage(), e);
}
return fallbackFeelingList;
}

private RecommendPredictDto makeResultForPredict(Closet closet, ClothingRecommendation recommendation, Member member) {
Expand All @@ -83,7 +173,9 @@ private List<Integer> makeOuterList(Closet closet, List<Integer> outers) {
if (outers.isEmpty()) return new ArrayList<>();

Set<Long> ownedClothTypes = closet.getOuterList().stream()
.filter(Outer::isActive)
.map(Outer::getOuterType)
.filter(Objects::nonNull)
.collect(Collectors.toSet());

Set<Integer> resultSet = new HashSet<>();
Expand All @@ -101,7 +193,9 @@ private List<Integer> makeOuterList(Closet closet, List<Integer> outers) {

private List<Integer> makeUpperList(Closet closet, List<Integer> tops) {
Set<Long> ownedClothTypes = closet.getUpperList().stream()
.filter(Upper::isActive)
.map(Upper::getUpperType)
.filter(Objects::nonNull)
.collect(Collectors.toSet());

Set<Integer> resultSet = new HashSet<>();
Expand All @@ -119,52 +213,42 @@ private List<Integer> makeUpperList(Closet closet, List<Integer> tops) {
private List<WeatherFeelingDto> makeWeatherFeeling(Map<String, Integer> predictionMap,
ClothingRecommendation recommendation) {
List<WeatherFeelingDto> feelingList = new ArrayList<>();

LocalDate forecastDate = recommendation.getDate();

String regionName = recommendation.getRegionName();

List<Integer> hours = predictionMap.keySet().stream()
.map(Integer::parseInt)
.collect(Collectors.toList());
List<Integer> targetHours = List.of(9, 12, 15, 18, 21);

List<WeatherForecast> forecasts = weatherForecastRepository
.findByRegionNameAndForecastDateAndHourInOrderByCreatedAtDesc(regionName, forecastDate, hours);

Map<Integer, WeatherForecast> hourToForecastMap = forecasts.stream()
.collect(Collectors.toMap(
WeatherForecast::getHour,
forecast -> forecast,
(oldVal, newVal) -> oldVal
));

for (Map.Entry<String, Integer> entry : predictionMap.entrySet()) {
int hour = Integer.parseInt(entry.getKey());
int feeling = entry.getValue();
WeatherForecast forecast = hourToForecastMap.get(hour);

if (forecast != null) {
WeatherFeelingDto dto = WeatherFeelingDto.builder()
.date(forecast.getForecastDate())
.time(hour)
.feeling(feeling)
.temperature(forecast.getTemperature())
.build();
feelingList.add(dto);
} else {
log.warn("날씨 데이터 없음: region={}, date={}, hour={}", regionName, forecastDate, hour);
.findByRegionNameAndForecastDateAndHourInOrderByHourAsc(regionName, forecastDate, targetHours);

Map<String, Integer> safePredictionMap = Optional.ofNullable(predictionMap).orElseGet(Collections::emptyMap);
final int DEFAULT_FEELING = 2;

for (WeatherForecast forecast : forecasts) {
int hour = forecast.getHour();
int feeling = safePredictionMap.getOrDefault(String.valueOf(hour), DEFAULT_FEELING);

WeatherFeelingDto dto = WeatherFeelingDto.builder()
.date(forecast.getForecastDate())
.time(hour)
.feeling(feeling)
.temperature(forecast.getTemperature())
.build();
feelingList.add(dto);

if (feeling == DEFAULT_FEELING && !safePredictionMap.containsKey(String.valueOf(hour))) {
log.debug("AI 체감온도 예측값 없음. 기본값(2) 사용: region={}, date={}, hour={}", regionName, forecastDate, hour);
}
}

if (forecasts.isEmpty()) {
log.warn("날씨 예보 데이터 없음: region={}, date={}, hours={}", regionName, forecastDate, targetHours);
}
return feelingList;
}


private List<ClothingRecommendation> getModelPrediction(Long id, LocalDate now) {
List<ClothingRecommendation> list = clothingRecommendationRepository.findByMemberIdAndDate(id, now);
if (list.isEmpty()) {
throw new CustomException(ErrorCode.NO_PREDICT_DATA);
}
return list;
return clothingRecommendationRepository.findByMemberIdAndDate(id, now);
}

@Transactional
Expand Down Expand Up @@ -196,7 +280,6 @@ public void save(ModelClothingRecommendationDto dto, Member member) {
}
}


private Closet getClosetWithAll(Member member) {
Closet closetWithUppers = closetRepository.findClosetWithUppers(member.getId())
.orElseThrow(() -> new CustomException(ErrorCode.CLOSET_NOT_FOUND));
Expand Down
2 changes: 2 additions & 0 deletions ...om/howWeather/howWeather_backend/domain/weather/repository/WeatherForecastRepository.java
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Expand Up @@ -22,4 +22,6 @@ List<WeatherForecast> findByRegionNameAndForecastDateAndHourInOrderByCreatedAtDe
void deleteByForecastDateGreaterThanEqual(LocalDate baseDate);

List<WeatherForecast> findByRegionNameAndForecastDateAndHourIn(String regionName, LocalDate now, List<Integer> targetHours);

List<WeatherForecast> findByRegionNameAndForecastDateAndHourInOrderByHourAsc(String regionName, LocalDate forecastDate, List<Integer> targetHours);
}
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