[Fix] Few-shot 유사도 임계값과 선택 품질 로그 추가

src/main/java/com/jobdri/jobdri_api/domain/analysis/service/ai/fewshot/DefaultFewShotSearchService.java

@@ -76,7 +76,11 @@ public List<SelectedFewShotCase> searchRelevantFewShots(FewShotSearchQuery query
         FewShotSelectionMode selectionMode = selected.isEmpty()
                 ? FewShotSelectionMode.STATIC_FALLBACK
                 : FewShotSelectionMode.EMBEDDING;
-        if (selected.isEmpty() && properties.isFallbackEnabled()) {
+        int minimumSelectedCount = Math.max(
+                1,
+                Math.min(properties.getSearch().getMinimumSelectedCount(), requestedTopK)
+        );
+        if (selected.size() < minimumSelectedCount && properties.isFallbackEnabled()) {
             selected = selectLocally(query, candidates, requestedTopK, "local-fallback");
             if (!selected.isEmpty()) {
                 selectionMode = FewShotSelectionMode.LOCAL_FALLBACK;
@@ -114,12 +118,15 @@ private List<SelectedFewShotCase> selectWithCohere(
             float[] queryEmbedding = cohereEmbeddingClient.embedQuery(queryText);
             List<float[]> documentEmbeddings = resolveDocumentEmbeddings(candidates, documents);
             List<SelectedFewShotCase> ranked = new ArrayList<>();
+            List<Double> similarityScores = new ArrayList<>();
             for (int i = 0; i < candidates.size(); i++) {
                 double score = cosineSimilarity(queryEmbedding, documentEmbeddings.get(i));
-                if (score >= properties.getSearch().getMinRerankScore()) {
+                similarityScores.add(score);
+                if (score >= properties.getSearch().getMinSimilarity()) {
                     ranked.add(new SelectedFewShotCase(candidates.get(i), score, "cohere-embedding"));
                 }
             }
+            logSimilarityDistribution(similarityScores, ranked.size());
             ranked.sort(Comparator
                     .comparingDouble(SelectedFewShotCase::score).reversed()
                     .thenComparingInt(item -> -item.fewShotCase().priority())
@@ -132,6 +139,28 @@ private List<SelectedFewShotCase> selectWithCohere(
         }
     }
 
+    private void logSimilarityDistribution(List<Double> scores, int passedThresholdCount) {
+        if (scores.isEmpty()) {
+            return;
+        }
+        double topScore = scores.stream().mapToDouble(Double::doubleValue).max().orElse(0.0);
+        double bottomScore = scores.stream().mapToDouble(Double::doubleValue).min().orElse(0.0);
+        double avgScore = scores.stream().mapToDouble(Double::doubleValue).average().orElse(0.0);
+        log.info(
+                "few-shot embedding similarity distribution. candidateCount={}, passedThresholdCount={}, minSimilarity={}, topScore={}, bottomScore={}, avgScore={}",
+                scores.size(),
+                passedThresholdCount,
+                formatScore(properties.getSearch().getMinSimilarity()),
+                formatScore(topScore),
+                formatScore(bottomScore),
+                formatScore(avgScore)
+        );
+    }
+
+    private static String formatScore(double score) {
+        return String.format(Locale.ROOT, "%.4f", score);
+    }
+
     private List<float[]> resolveDocumentEmbeddings(
             List<FewShotCase> candidates,
             List<String> documents
@@ -314,6 +343,10 @@ private String selectionCacheKey(FewShotSearchQuery query, int topK, String data
         return sha256(
                 datasetFingerprint
                         + "\n" + topK
+                        + "\n" + properties.getSearch().getMinSimilarity()
+                        + "\n" + properties.getSearch().getMinimumSelectedCount()
+                        + "\n" + properties.isFallbackEnabled()
+                        + "\n" + properties.getSearch().isDiversityEnabled()
                         + "\n" + defaultString(query.caseId())
                         + "\n" + textBuilder.buildQueryText(query)
         );

src/main/java/com/jobdri/jobdri_api/domain/analysis/service/ai/fewshot/FewShotProperties.java

@@ -141,7 +141,8 @@ public void setReviewedProductionEnabled(boolean reviewedProductionEnabled) {
     public static class Search {
         private int candidateLimit = 30;
         private int topK = 5;
-        private double minRerankScore = -1.0;
+        private double minSimilarity = -1.0;
+        private int minimumSelectedCount = 1;
         private boolean diversityEnabled = true;
 
         public int getCandidateLimit() {
@@ -161,11 +162,27 @@ public void setTopK(int topK) {
         }
 
         public double getMinRerankScore() {
-            return minRerankScore;
+            return minSimilarity;
         }
 
         public void setMinRerankScore(double minRerankScore) {
-            this.minRerankScore = minRerankScore;
+            this.minSimilarity = minRerankScore;
+        }
+
+        public double getMinSimilarity() {
+            return minSimilarity;
+        }
+
+        public void setMinSimilarity(double minSimilarity) {
+            this.minSimilarity = minSimilarity;
+        }
+
+        public int getMinimumSelectedCount() {
+            return minimumSelectedCount;
+        }
+
+        public void setMinimumSelectedCount(int minimumSelectedCount) {
+            this.minimumSelectedCount = minimumSelectedCount;
         }
 
         public boolean isDiversityEnabled() {

src/main/java/com/jobdri/jobdri_api/domain/analysis/service/core/AnalysisInputFingerprintProvider.java

@@ -114,6 +114,8 @@ private Map<String, Object> fewShotPolicy() {
         fewShotPolicy.put("datasetVersion", fewShotProperties.getDatasetVersion());
         fewShotPolicy.put("topK", fewShotProperties.getSearch().getTopK());
         fewShotPolicy.put("candidateLimit", fewShotProperties.getSearch().getCandidateLimit());
+        fewShotPolicy.put("minSimilarity", fewShotProperties.getSearch().getMinSimilarity());
+        fewShotPolicy.put("minimumSelectedCount", fewShotProperties.getSearch().getMinimumSelectedCount());
         fewShotPolicy.put("reviewedEvaluationEnabled", fewShotProperties.getSource().isReviewedEvaluationEnabled());
         return fewShotPolicy;
     }

src/main/resources/application-analysis-eval.yaml

@@ -103,7 +103,8 @@ analysis:
     search:
       candidate-limit: ${ANALYSIS_FEW_SHOT_CANDIDATE_LIMIT:30}
       top-k: ${ANALYSIS_FEW_SHOT_TOP_K:5}
-      min-rerank-score: ${ANALYSIS_FEW_SHOT_MIN_RERANK_SCORE:-1.0}
+      min-similarity: ${ANALYSIS_FEW_SHOT_MIN_SIMILARITY:${ANALYSIS_FEW_SHOT_MIN_RERANK_SCORE:-1.0}}
+      minimum-selected-count: ${ANALYSIS_FEW_SHOT_MINIMUM_SELECTED_COUNT:1}
       diversity-enabled: ${ANALYSIS_FEW_SHOT_DIVERSITY_ENABLED:true}
 
 cohere:

src/main/resources/application-dev.yaml

@@ -177,7 +177,8 @@ analysis:
     search:
       candidate-limit: ${ANALYSIS_FEW_SHOT_CANDIDATE_LIMIT:30}
       top-k: ${ANALYSIS_FEW_SHOT_TOP_K:5}
-      min-rerank-score: ${ANALYSIS_FEW_SHOT_MIN_RERANK_SCORE:-1.0}
+      min-similarity: ${ANALYSIS_FEW_SHOT_MIN_SIMILARITY:${ANALYSIS_FEW_SHOT_MIN_RERANK_SCORE:-1.0}}
+      minimum-selected-count: ${ANALYSIS_FEW_SHOT_MINIMUM_SELECTED_COUNT:1}
       diversity-enabled: ${ANALYSIS_FEW_SHOT_DIVERSITY_ENABLED:true}
 
 cohere:

src/main/resources/application-prod.yaml

@@ -179,7 +179,8 @@ analysis:
     search:
       candidate-limit: ${ANALYSIS_FEW_SHOT_CANDIDATE_LIMIT:30}
       top-k: ${ANALYSIS_FEW_SHOT_TOP_K:5}
-      min-rerank-score: ${ANALYSIS_FEW_SHOT_MIN_RERANK_SCORE:-1.0}
+      min-similarity: ${ANALYSIS_FEW_SHOT_MIN_SIMILARITY:${ANALYSIS_FEW_SHOT_MIN_RERANK_SCORE:-1.0}}
+      minimum-selected-count: ${ANALYSIS_FEW_SHOT_MINIMUM_SELECTED_COUNT:1}
       diversity-enabled: ${ANALYSIS_FEW_SHOT_DIVERSITY_ENABLED:true}
 
 cohere:

src/test/java/com/jobdri/jobdri_api/domain/analysis/service/ai/fewshot/DefaultFewShotSearchServiceTest.java

@@ -97,6 +97,43 @@ void fallsBackToLocalSelectionWhenCohereFails() {
         assertThat(result.getFirst().selectionMethod()).isEqualTo("local-fallback");
     }
 
+    @Test
+    @DisplayName("임계값을 통과한 후보가 최소 개수보다 적으면 로컬 선택으로 fallback한다")
+    void fallsBackToLocalSelectionWhenEmbeddingResultsAreBelowMinimumCount() {
+        properties.setDynamicSelectionEnabled(true);
+        properties.getSearch().setMinSimilarity(0.5);
+        properties.getSearch().setMinimumSelectedCount(2);
+        when(caseStore.loadActiveCases()).thenReturn(List.of(
+                caseItem("FS-1", "Spring Boot API 개발", 0),
+                caseItem("FS-2", "브랜드 운영", 0)
+        ));
+        when(cohereEmbeddingClient.embedQuery(any())).thenReturn(new float[]{1, 0});
+        when(cohereEmbeddingClient.embedDocuments(any())).thenReturn(List.of(
+                new float[]{1, 0},
+                new float[]{0, 1}
+        ));
+
+        List<SelectedFewShotCase> result = service.searchRelevantFewShots(query("EV-99"), 2);
+
+        assertThat(result).hasSize(2);
+        assertThat(result).allMatch(item -> item.selectionMethod().equals("local-fallback"));
+    }
+
+    @Test
+    @DisplayName("fallback이 비활성화되면 최소 유사도 미만 후보를 선택하지 않는다")
+    void excludesCandidatesBelowMinimumSimilarityWhenFallbackDisabled() {
+        properties.setDynamicSelectionEnabled(true);
+        properties.setFallbackEnabled(false);
+        properties.getSearch().setMinSimilarity(0.5);
+        when(caseStore.loadActiveCases()).thenReturn(List.of(caseItem("FS-1", "브랜드 운영", 0)));
+        when(cohereEmbeddingClient.embedQuery(any())).thenReturn(new float[]{1, 0});
+        when(cohereEmbeddingClient.embedDocuments(any())).thenReturn(List.of(new float[]{0, 1}));
+
+        List<SelectedFewShotCase> result = service.searchRelevantFewShots(query("EV-99"), 1);
+
+        assertThat(result).isEmpty();
+    }
+
     @Test
     @DisplayName("서로 다른 검색 요청에서도 동일한 후보의 document embedding을 재사용한다")
     void reusesDocumentEmbeddingAcrossDifferentQueries() {

src/test/java/com/jobdri/jobdri_api/domain/analysis/service/core/AnalysisInputFingerprintProviderTest.java

@@ -100,6 +100,34 @@ void fingerprintIgnoresCorpusQuestionDistance() {
         assertThat(provider.create(first)).isEqualTo(provider.create(changedDistance));
     }
 
+    @Test
+    @DisplayName("Few-shot 유사도 임계값이 달라지면 fingerprint가 달라진다")
+    void fingerprintChangesWhenFewShotSimilarityPolicyChanges() {
+        when(fewShotPromptProvider.getPrompt()).thenReturn("few-shot");
+        FewShotProperties defaultProperties = new FewShotProperties();
+        FewShotProperties changedProperties = new FewShotProperties();
+        changedProperties.getSearch().setMinSimilarity(0.5);
+        changedProperties.getSearch().setMinimumSelectedCount(2);
+        AnalysisExecutionPayload payload = payload(currentJobPosting(), similarContext("Spring Boot API 개발", 0.91));
+
+        assertThat(providerWith(defaultProperties).create(payload))
+                .isNotEqualTo(providerWith(changedProperties).create(payload));
+    }
+
+    private AnalysisInputFingerprintProvider providerWith(FewShotProperties properties) {
+        return new AnalysisInputFingerprintProvider(
+                new ObjectMapper(),
+                fewShotPromptProvider,
+                properties,
+                new CohereProperties(null, null, null),
+                "gpt-4o-mini",
+                false,
+                "",
+                3,
+                5
+        );
+    }
+
     private AnalysisExecutionPayload payload(JobPosting jobPosting, SimilarJobPostingContext context) {
         return new AnalysisExecutionPayload(
                 1L,