Update app.py

app.py

@@ -393,31 +393,40 @@ def get_all_models(limit=1000):
     return all_models[:limit]
 
 def get_models_data(progress=gr.Progress()):
-    """모델 데이터 가져오기"""
     try:
         progress(0, desc="Fetching models...")
         
-        # 모델 가져오기
+        # 일반 모델과 Korea 관련 모델 모두 가져오기
         all_global_models = get_all_models(limit=1000)
-        print(f"Actually fetched models count: {len(all_global_models)}")
+        korea_models = get_korea_models()  # Korea 검색 결과 추가
+        
+        # 모든 모델 통합 (중복 제거)
+        all_models = all_global_models.copy()
+        existing_ids = {model.get('id', '') for model in all_global_models}
+        
+        for korea_model in korea_models:
+            if korea_model.get('id', '') not in existing_ids:
+                all_models.append(korea_model)
+                existing_ids.add(korea_model.get('id', ''))
+        
+        print(f"Total models (including Korea search): {len(all_models)}")
         
         # API 응답 순서를 순위로 사용하여 순위 맵 생성
         rank_map = {}
-        for rank, model in enumerate(all_global_models, 1):
+        for rank, model in enumerate(all_models, 1):
             model_id = model.get('id', '').strip()
             rank_map[model_id] = {
                 'rank': rank,
                 'likes': model.get('likes', 0),
                 'downloads': model.get('downloads', 0),
-                'title': model.get('title', 'No Title')
+                'title': model.get('title', 'No Title'),
+                'is_korea': model in korea_models  # Korea 검색 결과 여부 표시
             }
-            print(f"Rank {rank}: {model_id}")
 
         # target_models의 순위 확인 및 정보 수집
         filtered_models = []
         for model_id in target_models.keys():
             try:
-                # 개별 모델 API 호출
                 normalized_id = model_id.strip('/')
                 model_url_api = f"https://huggingface.co/api/models/{normalized_id}"
                 response = requests.get(
@@ -428,8 +437,6 @@ def get_models_data(progress=gr.Progress()):
                 if response.status_code == 200:
                     model_data = response.json()
                     api_id = model_data.get('id', '').strip()
-                    
-                    # API 응답 순서에서 순위 찾기
                     rank_info = rank_map.get(api_id)
                     
                     model_info = {
@@ -437,17 +444,23 @@ def get_models_data(progress=gr.Progress()):
                         'global_rank': rank_info['rank'] if rank_info else 'Not in top 1000',
                         'downloads': model_data.get('downloads', 0),
                         'likes': model_data.get('likes', 0),
-                        'title': model_data.get('title', 'No Title')
+                        'title': model_data.get('title', 'No Title'),
+                        'is_korea': rank_info.get('is_korea', False) if rank_info else False
                     }
                     filtered_models.append(model_info)
-                    print(f"Model {model_id}: Rank={model_info['global_rank']}, Downloads={model_info['downloads']}, Likes={model_info['likes']}")
+                    
+                    # Korea 검색 결과인 경우 표시
+                    korea_status = "🇰🇷" if model_info['is_korea'] else ""
+                    print(f"Model {model_id}: Rank={model_info['global_rank']}, Downloads={model_info['downloads']}, Likes={model_info['likes']} {korea_status}")
+                    
                 else:
                     filtered_models.append({
                         'id': model_id,
                         'global_rank': 'Not in top 1000',
                         'downloads': 0,
                         'likes': 0,
-                        'title': 'No Title'
+                        'title': 'No Title',
+                        'is_korea': False
                     })
             except Exception as e:
                 print(f"Error processing {model_id}: {str(e)}")
@@ -456,63 +469,11 @@ def get_models_data(progress=gr.Progress()):
                     'global_rank': 'Not in top 1000',
                     'downloads': 0,
                     'likes': 0,
-                    'title': 'No Title'
+                    'title': 'No Title',
+                    'is_korea': False
                 })
-        
-        # 순위로 정렬
-        filtered_models.sort(key=lambda x: float('inf') if isinstance(x['global_rank'], str) else x['global_rank'])
-        
-        progress(0.3, desc="Creating visualization...")
-        
-        # 시각화 생성
-        fig = go.Figure()
-        
-        # 순위권 내 모델만 필터링하여 시각화
-        valid_models = [m for m in filtered_models if isinstance(m['global_rank'], (int, float))]
-        
-        if valid_models:
-            ids = [m['id'] for m in valid_models]
-            ranks = [m['global_rank'] for m in valid_models]
-            likes = [m['likes'] for m in valid_models]
-            downloads = [m['downloads'] for m in valid_models]
-            
-            # Y축 값을 반전 (높은 순위가 위로 가도록)
-            y_values = [1001 - r for r in ranks]
-            
-            fig.add_trace(go.Bar(
-                x=ids,
-                y=y_values,
-                text=[f"Global Rank: #{r}<br>Downloads: {format(d, ',')}<br>Likes: {format(l, ',')}" 
-                      for r, d, l in zip(ranks, downloads, likes)],
-                textposition='auto',
-                marker_color='rgb(158,202,225)',
-                opacity=0.8
-            ))
-            
-            fig.update_layout(
-                title={
-                    'text': 'Hugging Face Models Global Rankings',
-                    'y':0.95,
-                    'x':0.5,
-                    'xanchor': 'center',
-                    'yanchor': 'top'
-                },
-                xaxis_title='Model ID',
-                yaxis_title='Global Rank',
-                yaxis=dict(
-                    ticktext=[f"#{i}" for i in range(1, 1001, 50)],
-                    tickvals=[1001 - i for i in range(1, 1001, 50)],
-                    range=[0, 1000]
-                ),
-                height=800,
-                showlegend=False,
-                template='plotly_white',
-                xaxis_tickangle=-45
-            )
-        
-        progress(0.6, desc="Creating model cards...")
-        
-        # HTML 카드 생성
+
+        # HTML 카드에 Korea 검색 결과 표시 추가
         html_content = """
         <div style='padding: 20px; background: #f5f5f5;'>
             <h2 style='color: #2c3e50;'>Models Global Rankings</h2>
@@ -521,6 +482,7 @@ def get_models_data(progress=gr.Progress()):
         
         for model in filtered_models:
             rank_display = f"Global Rank #{model['global_rank']}" if isinstance(model['global_rank'], (int, float)) else "Not in top 1000"
+            korea_badge = "🇰🇷 Korea Search Result" if model['is_korea'] else ""
             
             html_content += f"""
             <div style='
@@ -532,6 +494,7 @@ def get_models_data(progress=gr.Progress()):
             '>
                 <h3 style='color: #34495e;'>{rank_display}</h3>
                 <h4 style='color: #2c3e50;'>{model['id']}</h4>
+                <p style='color: #e74c3c;'>{korea_badge}</p>
                 <p style='color: #7f8c8d;'>⬇️ Downloads: {format(model['downloads'], ',')}</p>
                 <p style='color: #7f8c8d;'>👍 Likes: {format(model['likes'], ',')}</p>
                 <a href='{target_models[model['id']]}' 
@@ -552,13 +515,14 @@ def get_models_data(progress=gr.Progress()):
         
         html_content += "</div></div>"
         
-        # 데이터프레임 생성
+        # 데이터프레임에 Korea 검색 결과 컬럼 추가
         df = pd.DataFrame([{
             'Global Rank': f"#{m['global_rank']}" if isinstance(m['global_rank'], (int, float)) else m['global_rank'],
             'Model ID': m['id'],
             'Title': m['title'],
             'Downloads': format(m['downloads'], ','),
             'Likes': format(m['likes'], ','),
+            'Korea Search': '🇰🇷' if m['is_korea'] else '',
             'URL': target_models[m['id']]
         } for m in filtered_models])