Update app.py

app.py

@@ -58,15 +58,78 @@ def analyze_text_sections(text):
 
 @safe_process
 def calculate_topic_correlations(topics):
-    topic_scores = {}
-    for topic in topics:
-        topic_scores[topic['label']] = topic['score_mean']
-    
-    if len(topic_scores) < 2:
-        return np.array([[1]]), list(topic_scores.keys())
-    
-    correlation_matrix = np.corrcoef(list(topic_scores.values()))
-    return correlation_matrix, list(topic_scores.keys())
+    try:
+        if not topics or len(topics) < 1:
+            return np.array([[1]]), ['No topics']
+            
+        topic_scores = {}
+        for topic in topics:
+            if 'score_mean' in topic:
+                topic_scores[topic['label']] = topic['score_mean']
+            elif 'score' in topic:  # score로도 확인
+                topic_scores[topic['label']] = topic['score'] / 100.0
+        
+        if len(topic_scores) < 1:
+            return np.array([[1]]), ['No valid scores']
+            
+        correlation_matrix = np.corrcoef(list(topic_scores.values()))
+        return correlation_matrix, list(topic_scores.keys())
+    except Exception as e:
+        print(f"Correlation calculation error: {e}")
+        return np.array([[1]]), ['Error']
+
+@spaces.GPU()
+def process_all_analysis(text):
+    try:
+        # 기본 주제 분석
+        raw_results = clf.suggest_topics(text)
+        topics = process_results(raw_results)
+        
+        # 추가 분석
+        section_topics = analyze_text_sections(text)
+        corr_matrix, labels = calculate_topic_correlations(topics)
+        sentiments = perform_sentiment_analysis(text)
+        clusters = create_topic_clusters(topics)
+        
+        # 차트 생성
+        bar_chart, radar_chart = create_main_charts(topics)
+        heatmap = create_correlation_heatmap(corr_matrix, labels)
+        evolution_chart = create_topic_evolution(section_topics)
+        gauge_chart = create_confidence_gauge(topics)
+        
+        results = {
+            'topics': topics,
+            'bar_chart': bar_chart,
+            'radar_chart': radar_chart,
+            'heatmap': heatmap,
+            'evolution': evolution_chart,
+            'gauge': gauge_chart,
+            'sentiments': sentiments.to_dict() if sentiments is not None else {},
+            'clusters': clusters.tolist() if clusters is not None else []
+        }
+        
+        # 개별 결과 반환
+        return (
+            results,  # JSON output
+            bar_chart,  # plot1
+            radar_chart,  # plot2
+            heatmap,  # plot3
+            evolution_chart,  # plot4
+            gauge_chart,  # plot5
+            go.Figure()  # plot6 (빈 감성 분석 차트)
+        )
+    except Exception as e:
+        print(f"Analysis error: {str(e)}")
+        empty_fig = go.Figure()
+        return (
+            {'error': str(e), 'topics': []},
+            empty_fig,
+            empty_fig,
+            empty_fig,
+            empty_fig,
+            empty_fig,
+            empty_fig
+        )
 
 @safe_process
 def perform_sentiment_analysis(text):
@@ -197,50 +260,8 @@ def process_results(results):
     
     return formatted_topics
 
-@spaces.GPU(enable_queue=True, duration=50)
-def process_all_analysis(text):
-    try:
-        # 기본 주제 분석
-        raw_results = clf.suggest_topics(text)
-        topics = process_results(raw_results)
-        
-        # 추가 분석
-        section_topics = analyze_text_sections(text)
-        corr_matrix, labels = calculate_topic_correlations(topics)
-        sentiments = perform_sentiment_analysis(text)
-        clusters = create_topic_clusters(topics)
-        
-        # 차트 생성
-        bar_chart, radar_chart = create_main_charts(topics)
-        heatmap = create_correlation_heatmap(corr_matrix, labels)
-        evolution_chart = create_topic_evolution(section_topics)
-        gauge_chart = create_confidence_gauge(topics)
-        
-        return {
-            'topics': topics,
-            'bar_chart': bar_chart,
-            'radar_chart': radar_chart,
-            'heatmap': heatmap,
-            'evolution': evolution_chart,
-            'gauge': gauge_chart,
-            'sentiments': sentiments.to_dict() if sentiments is not None else {},
-            'clusters': clusters.tolist() if clusters is not None else []
-        }
-    except Exception as e:
-        print(f"Analysis error: {str(e)}")
-        return {
-            'error': str(e),
-            'topics': [],
-            'bar_chart': go.Figure(),
-            'radar_chart': go.Figure(),
-            'heatmap': go.Figure(),
-            'evolution': go.Figure(),
-            'gauge': go.Figure(),
-            'sentiments': {},
-            'clusters': []
-        }
 
-# Gradio 인터페이스
+
 with gr.Blocks(title="고급 문서 주제 분석기") as demo:
     gr.Markdown("## 📊 고급 문서 주제 분석기")
     gr.Markdown("문서를 입력하면 다양한 분석 결과를 시각화하여 보여줍니다.")
@@ -283,10 +304,10 @@ with gr.Blocks(title="고급 문서 주제 분석기") as demo:
     )
 
 if __name__ == "__main__":
-    demo.queue(max_size=1)  # concurrency_count 대신 max_size 사용
+    demo.queue(max_size=1)
     demo.launch(
         server_name="0.0.0.0",
         server_port=7860,
-        share=False,
+        share=True,  # 공개 링크 생성을 위해 True로 설정
         debug=True
     )