Update app.py

app.py

@@ -90,16 +90,25 @@ def update_table(
     
     print(f"Filter applied: query={query}, columns={columns}, type_query={type_query}, precision_query={precision_query}")
     print(f"Filtered DataFrame shape: {filtered_df.shape}")
-    print(filtered_df.head())  # フィルタ後のデータを確認
+    
+    if not filtered_df.empty:
+        print(filtered_df.head())  # フィルタ後のデータを確認
+    else:
+        print("Filtered DataFrame is empty.")
     
     df = select_columns(filtered_df, columns)
     print(f"DataFrame after selecting columns: {df.shape}")
-    print(df.head())  # 選択後のデータを確認
+    
+    if not df.empty:
+        print(df.head())  # 選択後のデータを確認
+    else:
+        print("DataFrame after selecting columns is empty.")
     
     return df
 
 
 
+
 def load_query(request: gr.Request):  # triggered only once at startup => read query parameter if it exists
     query = request.query_params.get("query") or ""
     return query, query # return one for the "search_bar", one for a hidden component that triggers a reload only if value has changed
@@ -163,24 +172,14 @@ def filter_models(
         filtered_df = df[df[AutoEvalColumn.still_on_hub.name] == True]
         print(f"After filtering deleted models: {filtered_df.shape}")
     
-    # Show merges フィルタ（コメントアウトされている場合はスキップ）
-    # if not show_merges:
-    #     filtered_df = filtered_df[filtered_df[AutoEvalColumn.merged.name] == False]
-    #     print(f"After filtering merged models: {filtered_df.shape}")
-    
-    # Show flagged フィルタ（コメントアウトされている場合はスキップ）
-    # if not show_flagged:
-    #     filtered_df = filtered_df[filtered_df[AutoEvalColumn.flagged.name] == False]
-    #     print(f"After filtering flagged models: {filtered_df.shape}")
-    
     # Model type フィルタ
     type_emoji = [t[0] for t in type_query]
     filtered_df = filtered_df[filtered_df[AutoEvalColumn.model_type_symbol.name].isin(type_emoji)]
     print(f"After filtering by model type: {filtered_df.shape}")
     
-    # Precision フィルタ
-    filtered_df = filtered_df[filtered_df[AutoEvalColumn.precision.name].isin(precision_query + ["None"])]
-    print(f"After filtering by precision: {filtered_df.shape}")
+    # Precision フィルタ（"Unknown" を含める）
+    filtered_df = filtered_df[filtered_df[AutoEvalColumn.precision.name].isin(precision_query + ["None", "Unknown"])]
+    print(f"After filtering by precision (including 'Unknown'): {filtered_df.shape}")
     
     # Add Special Tokens フィルタ
     filtered_df = filtered_df[filtered_df[AutoEvalColumn.add_special_tokens.name].isin(add_special_tokens_query)]