Update app.py

app.py

@@ -4,6 +4,8 @@ import pandas as pd
 import plotly.graph_objects as go
 from datetime import datetime
 import os
+import asyncio
+import aiohttp
 
 HF_TOKEN = os.getenv("HF_TOKEN")
 
@@ -387,10 +389,32 @@ def get_all_models(limit=3000):
             if model.get('id', '') not in existing_ids:
                 all_models.append(model)
                 existing_ids.add(model.get('id', ''))
+    else:
+        print(f"Failed to fetch Korea models: {korea_response.status_code}")
     
     print(f"Total unique models: {len(all_models)}")
     return all_models[:limit]
 
+# 비동기 API 호출을 위한 함수들
+async def fetch_model_data(session, model_id):
+    url = f"https://huggingface.co/api/models/{model_id.strip('/')}"
+    try:
+        async with session.get(url, headers={'Accept': 'application/json'}) as response:
+            if response.status == 200:
+                return await response.json()
+            else:
+                print(f"Failed to fetch {model_id}: {response.status}")
+                return None
+    except Exception as e:
+        print(f"Error fetching {model_id}: {e}")
+        return None
+
+async def fetch_all_target_models(model_ids):
+    async with aiohttp.ClientSession() as session:
+        tasks = [fetch_model_data(session, model_id) for model_id in model_ids]
+        results = await asyncio.gather(*tasks)
+    return results
+
 def get_models_data(progress=gr.Progress()):
     def calculate_rank(model_id, all_global_models, korea_models):
         # 글로벌 순위 확인
@@ -448,43 +472,32 @@ def get_models_data(progress=gr.Progress()):
         # 시각화를 위한 Figure 생성
         fig = go.Figure()
         
-        # 순위 정보 수집
+        # 비동기 API 호출로 target_models 데이터 가져오기
+        target_model_ids = list(target_models.keys())
+        model_results = asyncio.run(fetch_all_target_models(target_model_ids))
+        
         filtered_models = []
-        for model_id in target_models.keys():
-            try:
-                normalized_id = model_id.strip('/')
-                model_url_api = f"https://huggingface.co/api/models/{normalized_id}"
-                response = requests.get(
-                    model_url_api, 
-                    headers={'Accept': 'application/json'}
-                )
-                
-                if response.status_code == 200:
-                    model_data = response.json()
-                    rank, is_korea = calculate_rank(model_id, all_global_models, korea_models)
-                    
-                    filtered_models.append({
-                        'id': model_id,
-                        'global_rank': rank,
-                        'downloads': model_data.get('downloads', 0),
-                        'likes': model_data.get('likes', 0),
-                        'title': model_data.get('title', 'No Title'),
-                        'is_korea': is_korea
-                    })
-                    
-                    print(f"Model {model_id}: Rank={rank}, Is Korea={is_korea}")
-                else:
-                    filtered_models.append({
-                        'id': model_id,
-                        'global_rank': 'Not in top 3000',
-                        'downloads': 0,
-                        'likes': 0,
-                        'title': 'No Title',
-                        'is_korea': False
-                    })
-            except Exception as e:
-                print(f"Error processing {model_id}: {str(e)}")
-                continue
+        for model_id, model_data in zip(target_model_ids, model_results):
+            if model_data is not None:
+                rank, is_korea = calculate_rank(model_id, all_global_models, korea_models)
+                filtered_models.append({
+                    'id': model_id,
+                    'global_rank': rank,
+                    'downloads': model_data.get('downloads', 0),
+                    'likes': model_data.get('likes', 0),
+                    'title': model_data.get('title', 'No Title'),
+                    'is_korea': is_korea
+                })
+                print(f"Model {model_id}: Rank={rank}, Is Korea={is_korea}")
+            else:
+                filtered_models.append({
+                    'id': model_id,
+                    'global_rank': 'Not in top 3000',
+                    'downloads': 0,
+                    'likes': 0,
+                    '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'])
@@ -920,7 +933,7 @@ def get_spaces_data(sort_type="trending", progress=gr.Progress()):
                 tickmode='array',
                 ticktext=[str(i) for i in range(1, 501, 20)],  # 1부터 400까지 20 간격으로 표시
                 tickvals=[i for i in range(1, 501, 20)],
-                range=[1, 500]  # Y축 범위를 1부터 400까지로 설정
+                range=[1, 500]
             ),
             height=800,
             showlegend=False,
@@ -1088,8 +1101,6 @@ def get_trending_spaces_without_token():
 if not HF_TOKEN:
     get_trending_spaces = get_trending_spaces_without_token
 
-
-
 def create_error_plot():
     fig = go.Figure()
     fig.add_annotation(
@@ -1107,7 +1118,6 @@ def create_error_plot():
     )
     return fig
 
-
 def create_space_info_html(spaces_data):
     if not spaces_data:
         return "<div style='padding: 20px;'><h2>데이터를 불러오는데 실패했습니다.</h2></div>"
@@ -1461,4 +1471,4 @@ demo.launch(
     server_port=7860,
     share=False,
     show_error=True
-)
+)