Update app.py

app.py

@@ -15,7 +15,10 @@ target_models = {
     "LGAI-EXAONE/EXAONE-3.5-7.8B-Instruct": "https://huggingface.co/LGAI-EXAONE/EXAONE-3.5-7.8B-Instruct",
     "ginipick/flux-lora-eric-cat": "https://huggingface.co/ginipick/flux-lora-eric-cat",
     "seawolf2357/flux-lora-car-rolls-royce": "https://huggingface.co/seawolf2357/flux-lora-car-rolls-royce",
-
+    
+    "moreh/Llama-3-Motif-102B-Instruct": "https://huggingface.co/moreh/Llama-3-Motif-102B-Instruct",
+    "moreh/Llama-3-Motif-102B": "https://huggingface.co/moreh/Llama-3-Motif-102B",
+    
     "Saxo/Linkbricks-Horizon-AI-Korean-Gemma-2-sft-dpo-27B": "https://huggingface.co/Saxo/Linkbricks-Horizon-AI-Korean-Gemma-2-sft-dpo-27B",
     "AALF/gemma-2-27b-it-SimPO-37K": "https://huggingface.co/AALF/gemma-2-27b-it-SimPO-37K",
     "nbeerbower/mistral-nemo-wissenschaft-12B": "https://huggingface.co/nbeerbower/mistral-nemo-wissenschaft-12B",
@@ -288,14 +291,20 @@ target_models = {
     "sel303/llama3-diverce-ver1.6": "https://huggingface.co/sel303/llama3-diverce-ver1.6"    
 }
 
+# all_models 관련 코드 제거하고 get_models_data 함수 내부에서 처리하도록 수정
+
 def get_models_data(progress=gr.Progress()):
     """모델 데이터 가져오기"""
+    def normalize_model_id(model_id):
+        """모델 ID를 정규화"""
+        return model_id.strip().lower()
+        
     url = "https://huggingface.co/api/models"
     
     try:
         progress(0, desc="Fetching models data...")
         
-        # 여러 정렬 방식으로 모델 검색
+        # 여러 정렬 방식으로 시도
         all_found_models = []
         sort_options = [
             {'sort': 'downloads', 'direction': -1},
@@ -303,11 +312,6 @@ def get_models_data(progress=gr.Progress()):
             {'sort': 'likes', 'direction': -1}
         ]
         
-        headers = {
-            'Accept': 'application/json',
-            'User-Agent': 'Mozilla/5.0'
-        }
-        
         for sort_params in sort_options:
             params = {
                 'full': 'true',
@@ -315,29 +319,28 @@ def get_models_data(progress=gr.Progress()):
                 **sort_params
             }
             
+            headers = {'Accept': 'application/json'}
+            
             response = requests.get(url, params=params, headers=headers)
             if response.status_code == 200:
                 models = response.json()
                 all_found_models.extend(models)
-                print(f"Found {len(models)} models with {sort_params['sort']} sort")
-        
-        if not all_found_models:
-            print("No models found from API")
-            return create_error_plot(), "<div>모델 데이터를 가져오는데 실패했습니다.</div>", pd.DataFrame()
         
         # 중복 제거
-        unique_models = {model['id']: model for model in all_found_models}.values()
-        print(f"Total unique models: {len(unique_models)}")
-        
-        # target_models와 매칭
+        seen_ids = set()
         filtered_models = []
-        for model in unique_models:
-            if model['id'] in target_models:
-                model['rank'] = len(filtered_models) + 1
+        for model in all_found_models:
+            model_id = normalize_model_id(model.get('id', ''))
+            if model_id not in seen_ids and model_id in [normalize_model_id(tid) for tid in target_models.keys()]:
+                seen_ids.add(model_id)
                 filtered_models.append(model)
-                print(f"Matched model: {model['id']}")
         
-        print(f"Matched {len(filtered_models)} models out of {len(target_models)} targets")
+        # 다운로드 수로 정렬
+        filtered_models.sort(key=lambda x: x.get('downloads', 0), reverse=True)
+        
+        # 순위 할당
+        for idx, model in enumerate(filtered_models, 1):
+            model['rank'] = idx
         
         if not filtered_models:
             return create_error_plot(), "<div>선택된 모델의 데이터를 찾을 수 없습니다.</div>", pd.DataFrame()
@@ -349,15 +352,9 @@ def get_models_data(progress=gr.Progress()):
         
         # 데이터 준비
         ids = [model['id'] for model in filtered_models]
-        downloads = [model.get('downloads', 0) for model in filtered_models]
+        ranks = [model['rank'] for model in filtered_models]
         likes = [model.get('likes', 0) for model in filtered_models]
-        
-        # 다운로드 수를 기준으로 순위 재계산
-        sorted_models = sorted(filtered_models, key=lambda x: x.get('downloads', 0), reverse=True)
-        for idx, model in enumerate(sorted_models):
-            model['rank'] = idx + 1
-        
-        ranks = [model['rank'] for model in sorted_models]
+        downloads = [model.get('downloads', 0) for model in filtered_models]
         
         # Y축 값을 반전
         y_values = [1001 - r for r in ranks]
@@ -366,8 +363,8 @@ def get_models_data(progress=gr.Progress()):
         fig.add_trace(go.Bar(
             x=ids,
             y=y_values,
-            text=[f"Rank: {r}<br>Downloads: {d}<br>Likes: {l}" 
-                  for r, d, l in zip(ranks, downloads, likes)],
+            text=[f"Rank: {r}<br>Likes: {l}<br>Downloads: {d}" 
+                  for r, l, d in zip(ranks, likes, downloads)],
             textposition='auto',
             marker_color='rgb(158,202,225)',
             opacity=0.8
@@ -375,7 +372,7 @@ def get_models_data(progress=gr.Progress()):
         
         fig.update_layout(
             title={
-                'text': 'Hugging Face Models Rankings (Top 1000)',
+                'text': 'Hugging Face Models Trending Rankings (Top 1000)',
                 'y':0.95,
                 'x':0.5,
                 'xanchor': 'center',
@@ -399,15 +396,16 @@ def get_models_data(progress=gr.Progress()):
         # HTML 카드 생성
         html_content = """
         <div style='padding: 20px; background: #f5f5f5;'>
-            <h2 style='color: #2c3e50;'>Models Rankings</h2>
+            <h2 style='color: #2c3e50;'>Models Trending Rankings</h2>
             <div style='display: grid; grid-template-columns: repeat(auto-fill, minmax(300px, 1fr)); gap: 20px;'>
         """
         
-        for model in sorted_models:
+        # 순위권 내 모델 카드 생성
+        for model in filtered_models:
             model_id = model['id']
             rank = model['rank']
-            downloads = model.get('downloads', 0)
             likes = model.get('likes', 0)
+            downloads = model.get('downloads', 0)
             
             html_content += f"""
             <div style='
@@ -418,8 +416,8 @@ def get_models_data(progress=gr.Progress()):
                 transition: transform 0.2s;
             '>
                 <h3 style='color: #34495e;'>Rank #{rank} - {model_id}</h3>
-                <p style='color: #7f8c8d;'>⬇️ Downloads: {downloads}</p>
                 <p style='color: #7f8c8d;'>👍 Likes: {likes}</p>
+                <p style='color: #7f8c8d;'>⬇️ Downloads: {downloads}</p>
                 <a href='{target_models[model_id]}' 
                    target='_blank' 
                    style='
@@ -436,16 +434,58 @@ def get_models_data(progress=gr.Progress()):
             </div>
             """
         
+        # 순위권 밖 모델 카드 생성
+        for model_id in target_models:
+            if model_id not in [m['id'] for m in filtered_models]:
+                html_content += f"""
+                <div style='
+                    background: #f8f9fa;
+                    padding: 20px;
+                    border-radius: 10px;
+                    box-shadow: 0 2px 4px rgba(0,0,0,0.1);
+                '>
+                    <h3 style='color: #34495e;'>{model_id}</h3>
+                    <p style='color: #7f8c8d;'>Not in top 1000</p>
+                    <a href='{target_models[model_id]}' 
+                       target='_blank' 
+                       style='
+                        display: inline-block;
+                        padding: 8px 16px;
+                        background: #95a5a6;
+                        color: white;
+                        text-decoration: none;
+                        border-radius: 5px;
+                       '>
+                       Visit Model 🔗
+                    </a>
+                </div>
+                """
+        
         html_content += "</div></div>"
         
         # 데이터프레임 생성
-        df = pd.DataFrame([{
-            'Rank': model['rank'],
-            'Model ID': model['id'],
-            'Downloads': model.get('downloads', 'N/A'),
-            'Likes': model.get('likes', 'N/A'),
-            'URL': target_models[model['id']]
-        } for model in sorted_models])
+        df_data = []
+        # 순위권 내 모델
+        for model in filtered_models:
+            df_data.append({
+                'Rank': model['rank'],
+                'Model ID': model['id'],
+                'Likes': model.get('likes', 'N/A'),
+                'Downloads': model.get('downloads', 'N/A'),
+                'URL': target_models[model['id']]
+            })
+        # 순위권 밖 모델
+        for model_id in target_models:
+            if model_id not in [m['id'] for m in filtered_models]:
+                df_data.append({
+                    'Rank': 'Not in top 1000',
+                    'Model ID': model_id,
+                    'Likes': 'N/A',
+                    'Downloads': 'N/A',
+                    'URL': target_models[model_id]
+                })
+        
+        df = pd.DataFrame(df_data)
         
         progress(1.0, desc="Complete!")
         return fig, html_content, df
@@ -454,60 +494,10 @@ def get_models_data(progress=gr.Progress()):
         print(f"Error in get_models_data: {str(e)}")
         return create_error_plot(), f"<div>에러 발생: {str(e)}</div>", pd.DataFrame()
         
-# API 응답 형식에 맞게 모델 ID 수정
-def normalize_model_id(model_id):
-    """모델 ID를 정규화"""
-    return model_id.strip().lower()
-
-# 매칭 로직 수정
-filtered_models = []
-for model in all_models:
-    model_id = normalize_model_id(model.get('id', ''))
-    target_id = next(
-        (tid for tid in target_models.keys() 
-         if normalize_model_id(tid) == model_id),
-        None
-    )
-    
-    if target_id:
-        model['rank'] = len(filtered_models) + 1
-        filtered_models.append(model)
-        print(f"Matched model: {model_id} with target: {target_id}")
-
-print(f"\nMatched {len(filtered_models)} models out of {len(target_models)} targets")
-
-def try_different_sorts():
-    """다양한 정렬 방식으로 모델 검색"""
-    sort_options = [
-        {'sort': 'downloads', 'direction': -1},
-        {'sort': 'lastModified', 'direction': -1},
-        {'sort': 'likes', 'direction': -1}
-    ]
-    
-    all_found_models = set()
-    for sort_params in sort_options:
-        params = {
-            'full': 'true',
-            'limit': 1000,
-            **sort_params
-        }
-        
-        response = requests.get(url, params=params, headers=headers)
-        if response.status_code == 200:
-            models = response.json()
-            for model in models:
-                model_id = normalize_model_id(model.get('id', ''))
-                if model_id in [normalize_model_id(tid) for tid in target_models.keys()]:
-                    all_found_models.add(model_id)
-    
-    return all_found_models
-
-# 메인 함수에서 사용
-all_found_models = try_different_sorts()
-print(f"\nTotal unique models found across all sorts: {len(all_found_models)}")        
-        
 # 관심 스페이스 URL 리스트와 정보
 target_spaces = {
+
+    "openfree/Korean-Leaderboard": "https://huggingface.co/spaces/openfree/Korean-Leaderboard",
     "ginipick/FLUXllama": "https://huggingface.co/spaces/ginipick/FLUXllama",
     "ginipick/SORA-3D": "https://huggingface.co/spaces/ginipick/SORA-3D",
     "fantaxy/Sound-AI-SFX": "https://huggingface.co/spaces/fantaxy/Sound-AI-SFX",