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[FIX]: 시나리오 생성 디버깅 #140

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Merged
johnbosco0414 merged 1 commit into from
Oct 14, 2025
Merged

[FIX]: 시나리오 생성 디버깅 #140

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3 changes: 3 additions & 0 deletions back/src/main/java/com/back/domain/node/repository/DecisionLineRepository.java
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Expand Up @@ -20,5 +20,8 @@ public interface DecisionLineRepository extends JpaRepository<DecisionLine, Long
@EntityGraph(attributePaths = {"user"})
Optional<DecisionLine> findWithUserById(Long id);

@EntityGraph(attributePaths = {"user", "baseLine", "baseLine.baseNodes"})
Optional<DecisionLine> findWithUserAndBaseLineById(Long id);

void deleteByBaseLine_Id(Long baseLineId);
}
4 changes: 2 additions & 2 deletions back/src/main/java/com/back/domain/scenario/service/ScenarioService.java
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Expand Up @@ -102,8 +102,8 @@ private ScenarioValidationResult validateScenarioCreation(
ScenarioCreateRequest request,
@Nullable DecisionNodeNextRequest lastDecision) {

// DecisionLine 존재 여부 확인 (User EAGER 로딩)
DecisionLine decisionLine = decisionLineRepository.findWithUserById(request.decisionLineId())
// DecisionLine 존재 여부 확인 (User, BaseLine, BaseLine.baseNodes EAGER 로딩)
DecisionLine decisionLine = decisionLineRepository.findWithUserAndBaseLineById(request.decisionLineId())
.orElseThrow(() -> new ApiException(ErrorCode.DECISION_LINE_NOT_FOUND));

// 권한 검증
Expand Down
1 change: 1 addition & 0 deletions back/src/main/java/com/back/global/ai/client/text/GeminiJsonTextClient.java
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Expand Up @@ -57,6 +57,7 @@ public CompletableFuture<String> generateText(String prompt) {

@Override
public CompletableFuture<String> generateText(AiRequest aiRequest) {
log.info("[CLIENT] GeminiJsonTextClient (2.0) is being used.");
if (aiRequest == null || aiRequest.prompt() == null) {
return CompletableFuture.failedFuture(new AiParsingException("Prompt is null"));
}
Expand Down
19 changes: 10 additions & 9 deletions back/src/main/java/com/back/global/ai/client/text/GeminiTextClient.java
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Expand Up @@ -45,11 +45,12 @@ public CompletableFuture<String> generateText(String prompt) {

@Override
public CompletableFuture<String> generateText(AiRequest aiRequest) {
log.info("[CLIENT] GeminiTextClient (2.5) is being used.");
return webClient
.post()
.uri("/v1beta/models/{model}:generateContent", textAiConfig.getModel())
.contentType(MediaType.APPLICATION_JSON)
.bodyValue(createGeminiRequest(aiRequest.prompt(), aiRequest.maxTokens()))
.bodyValue(createGeminiRequest(aiRequest))
.retrieve()
.onStatus(HttpStatusCode::isError, this::handleErrorResponse)
.bodyToMono(GeminiResponse.class)
Expand All @@ -64,17 +65,17 @@ public CompletableFuture<String> generateText(AiRequest aiRequest) {
.toFuture();
}

private Map<String, Object> createGeminiRequest(String prompt, int maxTokens) {
private Map<String, Object> createGeminiRequest(AiRequest aiRequest) {
// AiRequest로부터 generationConfig를 가져와 사용
java.util.Map<String, Object> generationConfig = new java.util.HashMap<>(aiRequest.parameters());
// maxTokens는 AiRequest의 전용 필드에서 가져와 확실히 설정
generationConfig.put("maxOutputTokens", aiRequest.maxTokens());

return Map.of(
"contents", List.of(
Map.of("parts", List.of(Map.of("text", prompt)))
Map.of("parts", List.of(Map.of("text", aiRequest.prompt())))
),
"generationConfig", Map.of(
"temperature", 0.8, // 시나리오 생성용 창의성 향상 (0.7 → 0.8)
"topK", 3, // 성능 최적화 (40 → 3, 10-15% 속도 향상)
"topP", 0.95,
"maxOutputTokens", maxTokens // AiRequest의 maxTokens 사용
)
"generationConfig", generationConfig
);
}

Expand Down
12 changes: 12 additions & 0 deletions back/src/main/java/com/back/global/ai/config/BaseScenarioAiProperties.java
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Expand Up @@ -11,9 +11,21 @@ public class BaseScenarioAiProperties {
private int maxOutputTokens = 1000;
private int timeoutSeconds = 60;

// Generation Config (AI 응답 품질 제어)
private double temperature = 0.7;
private double topP = 0.9;
private int topK = 40;

// getters/setters
public int getMaxOutputTokens() { return maxOutputTokens; }
public void setMaxOutputTokens(int maxOutputTokens) { this.maxOutputTokens = maxOutputTokens; }
public int getTimeoutSeconds() { return timeoutSeconds; }
public void setTimeoutSeconds(int timeoutSeconds) { this.timeoutSeconds = timeoutSeconds; }

public double getTemperature() { return temperature; }
public void setTemperature(double temperature) { this.temperature = temperature; }
public double getTopP() { return topP; }
public void setTopP(double topP) { this.topP = topP; }
public int getTopK() { return topK; }
public void setTopK(int topK) { this.topK = topK; }
}
12 changes: 12 additions & 0 deletions back/src/main/java/com/back/global/ai/config/DecisionScenarioAiProperties.java
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Expand Up @@ -11,9 +11,21 @@ public class DecisionScenarioAiProperties {
private int maxOutputTokens = 1200;
private int timeoutSeconds = 60;

// Generation Config (AI 응답 품질 제어)
private double temperature = 0.7;
private double topP = 0.9;
private int topK = 40;

// getters/setters
public int getMaxOutputTokens() { return maxOutputTokens; }
public void setMaxOutputTokens(int maxOutputTokens) { this.maxOutputTokens = maxOutputTokens; }
public int getTimeoutSeconds() { return timeoutSeconds; }
public void setTimeoutSeconds(int timeoutSeconds) { this.timeoutSeconds = timeoutSeconds; }

public double getTemperature() { return temperature; }
public void setTemperature(double temperature) { this.temperature = temperature; }
public double getTopP() { return topP; }
public void setTopP(double topP) { this.topP = topP; }
public int getTopK() { return topK; }
public void setTopK(int topK) { this.topK = topK; }
}
6 changes: 6 additions & 0 deletions back/src/main/java/com/back/global/ai/dto/result/BaseScenarioResult.java
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Expand Up @@ -31,6 +31,9 @@ public record Indicator(
* indicators 배열을 Map<Type, Integer>로 변환
*/
public Map<Type, Integer> indicatorScores() {
if (indicators == null) {
return java.util.Collections.emptyMap();
}
return indicators.stream()
.collect(java.util.stream.Collectors.toMap(
ind -> Type.valueOf(ind.type),
Expand All @@ -42,6 +45,9 @@ public Map<Type, Integer> indicatorScores() {
* indicators 배열을 Map<Type, String>로 변환
*/
public Map<Type, String> indicatorAnalysis() {
if (indicators == null) {
return java.util.Collections.emptyMap();
}
return indicators.stream()
.collect(java.util.stream.Collectors.toMap(
ind -> Type.valueOf(ind.type),
Expand Down
9 changes: 9 additions & 0 deletions back/src/main/java/com/back/global/ai/dto/result/DecisionScenarioResult.java
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Expand Up @@ -42,6 +42,9 @@ public record Comparison(
* indicators 배열을 Map<Type, Integer>로 변환
*/
public Map<Type, Integer> indicatorScores() {
if (indicators == null) {
return java.util.Collections.emptyMap();
}
return indicators.stream()
.collect(java.util.stream.Collectors.toMap(
ind -> Type.valueOf(ind.type),
Expand All @@ -53,6 +56,9 @@ public Map<Type, Integer> indicatorScores() {
* indicators 배열을 Map<Type, String>로 변환
*/
public Map<Type, String> indicatorAnalysis() {
if (indicators == null) {
return java.util.Collections.emptyMap();
}
return indicators.stream()
.collect(java.util.stream.Collectors.toMap(
ind -> Type.valueOf(ind.type),
Expand All @@ -64,6 +70,9 @@ public Map<Type, String> indicatorAnalysis() {
* comparisons 배열을 Map<String, String>로 변환
*/
public Map<String, String> comparisonResults() {
if (comparisons == null) {
return java.util.Collections.emptyMap();
}
return comparisons.stream()
.collect(java.util.stream.Collectors.toMap(
Comparison::type,
Expand Down
25 changes: 15 additions & 10 deletions back/src/main/java/com/back/global/ai/prompt/BaseScenarioPrompt.java
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Expand Up @@ -34,7 +34,7 @@ public class BaseScenarioPrompt {
## 현재 삶 정보
베이스라인: {baselineDescription}

## 현재 분기점들
## 과거 주요 인생 기록
{baseNodes}

## 요구사항 (JSON 형식)
Expand Down Expand Up @@ -99,13 +99,13 @@ public static String generatePrompt(BaseLine baseLine) {
BaseNode node = baseNodes.get(i);
int actualYear = birthYear + node.getAgeYear() - 1; // 실제 연도 계산

baseNodesInfo.append(String.format("%d. 카테고리: %s | 나이: %d세 (%d년) | 상황: %s | 결정: %s\n",
baseNodesInfo.append(String.format("%d. 카테고리: %s | 나이: %d세 (%d년) | 사건: %s | 결과: %s\n",
i + 1,
node.getCategory() != null ? node.getCategory().name() : "없음",
node.getAgeYear(),
actualYear,
node.getSituation() != null ? node.getSituation() : "상황 없음",
node.getDecision() != null ? node.getDecision() : "결정 없음"));
node.getSituation() != null ? node.getSituation() : "사건 없음",
node.getDecision() != null ? node.getDecision() : "결과 없음"));

// 가장 최근 노드의 연도를 시나리오 기준 연도로 사용
if (i == baseNodes.size() - 1) {
Expand All @@ -117,13 +117,18 @@ public static String generatePrompt(BaseLine baseLine) {
int currentYear = java.time.LocalDate.now().getYear();
int userCurrentAge = currentYear - birthYear + 1;

// BaseNode들의 실제 연도들을 타임라인 연도로 사용
// 맨 처음과 맨 끝 노드를 제외한 중간 노드들의 연도만 타임라인에 사용
StringBuilder timelineYears = new StringBuilder();
for (int i = 0; i < baseNodes.size(); i++) {
BaseNode node = baseNodes.get(i);
int actualYear = birthYear + node.getAgeYear() - 1;
if (i > 0) timelineYears.append(", ");
timelineYears.append('"').append(actualYear).append('"').append(": \"제목 (5단어 이내)\"");
if (baseNodes.size() > 2) {
java.util.List<BaseNode> intermediateNodes = baseNodes.subList(1, baseNodes.size() - 1);
for (int i = 0; i < intermediateNodes.size(); i++) {
BaseNode node = intermediateNodes.get(i);
int actualYear = birthYear + node.getAgeYear() - 1;
if (i > 0) {
timelineYears.append(", ");
}
timelineYears.append('"').append(actualYear).append('"').append(": \"해당 연도 요약 (5단어 이내)\"");
}
}

// 사용자 정보 추출 (null-safe)
Expand Down
25 changes: 15 additions & 10 deletions back/src/main/java/com/back/global/ai/prompt/DecisionScenarioPrompt.java
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Expand Up @@ -39,7 +39,7 @@ public class DecisionScenarioPrompt {
설명: {baseDescription}
지표: {baseIndicators}

## 대안 선택 경로
## 새로운 선택 기록
{decisionNodes}

## 요구사항 (JSON 형식)
Expand Down Expand Up @@ -116,12 +116,12 @@ public static String generatePrompt(DecisionLine decisionLine, Scenario baseScen
int actualYear = birthYear + node.getAgeYear() - 1; // 실제 연도 계산

decisionNodesInfo.append(String.format(
"%d단계 선택 (%d세, %d년):\n상황: %s\n결정: %s\n\n",
"%d단계 선택 (%d세, %d년):\n사건: %s\n선택: %s\n\n",
i + 1,
node.getAgeYear(),
actualYear,
node.getSituation() != null ? node.getSituation() : "상황 정보 없음",
node.getDecision() != null ? node.getDecision() : "결정 정보 없음"
node.getSituation() != null ? node.getSituation() : "사건 정보 없음",
node.getDecision() != null ? node.getDecision() : "선택 정보 없음"
));
}

Expand All @@ -146,13 +146,18 @@ public static String generatePrompt(DecisionLine decisionLine, Scenario baseScen
int careerScore = getScoreByType(baseSceneTypes, "직업");
int healthScore = getScoreByType(baseSceneTypes, "건강");

// DecisionNode들의 실제 연도들을 타임라인 연도로 사용
// 맨 처음과 맨 끝 노드를 제외한 중간 노드들의 연도만 타임라인에 사용
StringBuilder timelineYears = new StringBuilder();
for (int i = 0; i < decisionNodes.size(); i++) {
DecisionNode node = decisionNodes.get(i);
int actualYear = birthYear + node.getAgeYear() - 1;
if (i > 0) timelineYears.append(", ");
timelineYears.append('"').append(actualYear).append('"').append(": \"제목 (5단어 이내)\"");
if (decisionNodes.size() > 2) {
java.util.List<DecisionNode> intermediateNodes = decisionNodes.subList(1, decisionNodes.size() - 1);
for (int i = 0; i < intermediateNodes.size(); i++) {
DecisionNode node = intermediateNodes.get(i);
int actualYear = birthYear + node.getAgeYear() - 1;
if (i > 0) {
timelineYears.append(", ");
}
timelineYears.append('"').append(actualYear).append('"').append(": \"해당 연도 요약 (5단어 이내)\"");
}
}

// 사용자 정보 추출 (null-safe)
Expand Down
55 changes: 48 additions & 7 deletions back/src/main/java/com/back/global/ai/service/AiServiceImpl.java
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Expand Up @@ -35,11 +35,11 @@
*/

@Service
@RequiredArgsConstructor
@Slf4j
public class AiServiceImpl implements AiService {

private final @Qualifier("gemini25TextClient") TextAiClient textAiClient;
private final TextAiClient scenarioClient;
private final TextAiClient situationClient;
private final ObjectMapper objectMapper;
private final SceneTypeRepository sceneTypeRepository;
private final SituationAiProperties situationAiProperties;
Expand All @@ -48,6 +48,26 @@ public class AiServiceImpl implements AiService {
private final ImageAiClient imageAiClient;
private final com.back.global.storage.StorageService storageService;

public AiServiceImpl(@Qualifier("gemini25TextClient") TextAiClient scenarioClient,
@Qualifier("gemini20JsonClient") TextAiClient situationClient,
ObjectMapper objectMapper,
SceneTypeRepository sceneTypeRepository,
SituationAiProperties situationAiProperties,
BaseScenarioAiProperties baseScenarioAiProperties,
DecisionScenarioAiProperties decisionScenarioAiProperties,
ImageAiClient imageAiClient,
com.back.global.storage.StorageService storageService) {
this.scenarioClient = scenarioClient;
this.situationClient = situationClient;
this.objectMapper = objectMapper;
this.sceneTypeRepository = sceneTypeRepository;
this.situationAiProperties = situationAiProperties;
this.baseScenarioAiProperties = baseScenarioAiProperties;
this.decisionScenarioAiProperties = decisionScenarioAiProperties;
this.imageAiClient = imageAiClient;
this.storageService = storageService;
}

@Override
public CompletableFuture<BaseScenarioResult> generateBaseScenario(BaseLine baseLine) {
if (baseLine == null) {
Expand All @@ -65,10 +85,21 @@ public CompletableFuture<BaseScenarioResult> generateBaseScenario(BaseLine baseL
// Step 2: AI 호출 및 파싱
int maxTokens = baseScenarioAiProperties.getMaxOutputTokens();
log.info("Using maxOutputTokens: {} for base scenario generation", maxTokens);
AiRequest request = new AiRequest(baseScenarioPrompt, Map.of(), maxTokens);
return textAiClient.generateText(request)

// JSON 모드 강제 + 구조화된 응답 유도 (application.yml에서 관리)
Map<String, Object> generationConfig = Map.of(
"temperature", baseScenarioAiProperties.getTemperature(),
"topP", baseScenarioAiProperties.getTopP(),
"topK", baseScenarioAiProperties.getTopK(),
"candidateCount", 1,
"response_mime_type", "application/json" // JSON 모드 강제
);

AiRequest request = new AiRequest(baseScenarioPrompt, generationConfig, maxTokens);
return scenarioClient.generateText(request)
.thenApply(aiResponse -> {
try {
log.info("Raw AI response for BaseLine ID: {}: {}", baseLine.getId(), aiResponse);
log.debug("Received AI response for BaseLine ID: {}, length: {}",
baseLine.getId(), aiResponse.length());
// Remove markdown code block wrappers (```json ... ```)
Expand Down Expand Up @@ -131,10 +162,20 @@ public CompletableFuture<DecisionScenarioResult> generateDecisionScenario(Decisi
log.debug("Generated decision scenario prompt for DecisionLine ID: {}", decisionLine.getId());

// Step 2: AI 호출 및 파싱
AiRequest request = new AiRequest(newScenarioPrompt, Map.of(), decisionScenarioAiProperties.getMaxOutputTokens());
return textAiClient.generateText(request)
// JSON 모드 강제 + 구조화된 응답 유도 (application.yml에서 관리)
Map<String, Object> generationConfig = Map.of(
"temperature", decisionScenarioAiProperties.getTemperature(),
"topP", decisionScenarioAiProperties.getTopP(),
"topK", decisionScenarioAiProperties.getTopK(),
"candidateCount", 1,
"response_mime_type", "application/json" // JSON 모드 강제
);

AiRequest request = new AiRequest(newScenarioPrompt, generationConfig, decisionScenarioAiProperties.getMaxOutputTokens());
return scenarioClient.generateText(request)
.thenApply(aiResponse -> {
try {
log.info("Raw AI response for DecisionLine ID: {}: {}", decisionLine.getId(), aiResponse);
log.debug("Received AI response for DecisionLine ID: {}, length: {}",
decisionLine.getId(), aiResponse.length());
// Remove markdown code block wrappers (```json ... ```)
Expand Down Expand Up @@ -215,7 +256,7 @@ public CompletableFuture<String> generateSituation(List<DecisionNode> previousNo

// Step 2: AI 호출 및 상황 텍스트 추출
AiRequest request = new AiRequest(situationPrompt, Map.of(), situationAiProperties.getMaxOutputTokens());
return textAiClient.generateText(request)
return situationClient.generateText(request)
.thenApply(aiResponse -> {
try {
log.debug("Received AI response for situation generation, length: {}",
Expand Down
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