Update app.py

app.py

@@ -396,9 +396,20 @@ def get_models_data(progress=gr.Progress()):
     try:
         progress(0, desc="Fetching models...")
         
+        if not HF_TOKEN:
+            fig = create_error_plot()
+            error_html = """
+            <div style='padding: 20px; background: #fee; border-radius: 10px; margin: 10px 0;'>
+                <h3 style='color: #c00;'>⚠️ API 인증이 필요합니다</h3>
+                <p>HuggingFace API 토큰이 설정되지 않았습니다. 완전한 기능을 사용하기 위해서는 API 토큰이 필요합니다.</p>
+            </div>
+            """
+            empty_df = pd.DataFrame(columns=['Global Rank', 'Model ID', 'Title', 'Downloads', 'Likes', 'Korea Search', 'URL'])
+            return fig, error_html, empty_df
+
         # 일반 모델과 Korea 관련 모델 모두 가져오기
         all_global_models = get_all_models(limit=1000)
-        korea_models = get_korea_models()  # Korea 검색 결과 추가
+        korea_models = get_korea_models()
         
         # 모든 모델 통합 (중복 제거)
         all_models = all_global_models.copy()
@@ -409,21 +420,10 @@ def get_models_data(progress=gr.Progress()):
                 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_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'),
-                'is_korea': model in korea_models  # Korea 검색 결과 여부 표시
-            }
-
-        # target_models의 순위 확인 및 정보 수집
+        # 시각화를 위한 Figure 생성
+        fig = go.Figure()
+        
+        # 순위 정보 수집
         filtered_models = []
         for model_id in target_models.keys():
             try:
@@ -436,23 +436,15 @@ def get_models_data(progress=gr.Progress()):
                 
                 if response.status_code == 200:
                     model_data = response.json()
-                    api_id = model_data.get('id', '').strip()
-                    rank_info = rank_map.get(api_id)
-                    
-                    model_info = {
+                    filtered_models.append({
                         'id': model_id,
-                        'global_rank': rank_info['rank'] if rank_info else 'Not in top 1000',
+                        'global_rank': next((idx for idx, m in enumerate(all_models, 1) 
+                                          if m.get('id', '').strip() == model_id.strip()), 'Not in top 1000'),
                         'downloads': model_data.get('downloads', 0),
                         'likes': model_data.get('likes', 0),
                         '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)
-                    
-                    # 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}")
-                    
+                        'is_korea': any(m.get('id', '').strip() == model_id.strip() for m in korea_models)
+                    })
                 else:
                     filtered_models.append({
                         'id': model_id,
@@ -464,19 +456,46 @@ def get_models_data(progress=gr.Progress()):
                     })
             except Exception as e:
                 print(f"Error processing {model_id}: {str(e)}")
-                filtered_models.append({
-                    'id': model_id,
-                    'global_rank': 'Not in top 1000',
-                    'downloads': 0,
-                    'likes': 0,
-                    'title': 'No Title',
-                    'is_korea': False
-                })
+                continue
 
-        # HTML 카드에 Korea 검색 결과 표시 추가
+        # 순위로 정렬
+        filtered_models.sort(key=lambda x: float('inf') if isinstance(x['global_rank'], str) else x['global_rank'])
+        
+        # 시각화 데이터 준비
+        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]
+            
+            fig.add_trace(go.Bar(
+                x=ids,
+                y=[1001 - r for r in ranks],  # Y축 반전
+                text=[f"Rank: #{r}<br>Downloads: {format(m['downloads'], ',')}<br>Likes: {format(m['likes'], ',')}"
+                      for r, m in zip(ranks, valid_models)],
+                textposition='auto',
+                marker_color=['rgba(255,0,0,0.6)' if m['is_korea'] else 'rgba(0,0,255,0.6)' 
+                            for m in valid_models],
+                opacity=0.8
+            ))
+
+            fig.update_layout(
+                title="HuggingFace Models Global Rankings",
+                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
+            )
+
+        # HTML 카드 생성
         html_content = """
         <div style='padding: 20px; background: #f5f5f5;'>
-            <h2 style='color: #2c3e50;'>Models Global Rankings</h2>
+            <h2 style='color: #2c3e50;'>Models Rankings</h2>
             <div style='display: grid; grid-template-columns: repeat(auto-fill, minmax(300px, 1fr)); gap: 20px;'>
         """
         
@@ -491,10 +510,11 @@ def get_models_data(progress=gr.Progress()):
                 border-radius: 10px;
                 box-shadow: 0 2px 4px rgba(0,0,0,0.1);
                 transition: transform 0.2s;
+                {f"border: 2px solid #e74c3c;" if model['is_korea'] else ""}
             '>
                 <h3 style='color: #34495e;'>{rank_display}</h3>
                 <h4 style='color: #2c3e50;'>{model['id']}</h4>
-                <p style='color: #e74c3c;'>{korea_badge}</p>
+                <p style='color: #e74c3c; font-weight: bold;'>{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']]}' 
@@ -515,7 +535,7 @@ def get_models_data(progress=gr.Progress()):
         
         html_content += "</div></div>"
         
-        # 데이터프레임에 Korea 검색 결과 컬럼 추가
+        # 데이터프레임 생성
         df = pd.DataFrame([{
             'Global Rank': f"#{m['global_rank']}" if isinstance(m['global_rank'], (int, float)) else m['global_rank'],
             'Model ID': m['id'],
@@ -531,7 +551,15 @@ def get_models_data(progress=gr.Progress()):
         
     except Exception as e:
         print(f"Error in get_models_data: {str(e)}")
-        return create_error_plot(), f"<div>에러 발생: {str(e)}</div>", pd.DataFrame()
+        error_fig = create_error_plot()
+        error_html = f"""
+        <div style='padding: 20px; background: #fee; border-radius: 10px; margin: 10px 0;'>
+            <h3 style='color: #c00;'>⚠️ 오류가 발생했습니다</h3>
+            <p>{str(e)}</p>
+        </div>
+        """
+        empty_df = pd.DataFrame(columns=['Global Rank', 'Model ID', 'Title', 'Downloads', 'Likes', 'Korea Search', 'URL'])
+        return error_fig, error_html, empty_df
 
         
 # 관심 스페이스 URL 리스트와 정보