fix col selection bug

app.py

@@ -63,26 +63,35 @@ with gr.Blocks(title="Open Agent Leaderboard", head=head_style) as demo:
                 interactive=True,
             )
 
-            headers = ['Rank'] + check_box['essential'] + checkbox_group.value
+            # 修改这里：确保初始显示的列都存在于表格中
+            initial_headers = ['Rank'] + check_box['essential'] + checkbox_group.value
+            available_headers = [h for h in initial_headers if h in table.columns]
+            
             data_component = gr.components.DataFrame(
-                value=table[headers],
+                value=table[available_headers],  # 只使用可用的列
                 type='pandas',
-                datatype=[type_map[x] for x in headers],
+                datatype=[type_map[x] for x in available_headers],
                 interactive=False,
                 wrap=True,
                 visible=True)
             
             def filter_df(fields, *args):
-                # 获取基础列和选中的列
                 headers = ['Rank'] + check_box['essential'] + fields
                 df = table.copy()
-
+                
+                # 确保所有请求的列都存在
+                available_headers = [h for h in headers if h in df.columns]
+                
+                # 如果没有可用的列，返回一个带有基本列的空DataFrame
+                if not available_headers:
+                    available_headers = ['Rank'] + check_box['essential']
+                
                 comp = gr.components.DataFrame(
-                    value=table[headers],  # 只显示选中的列
+                    value=df[available_headers],
                     type='pandas',
-                    datatype=[type_map[x] for x in headers],
+                    datatype=[type_map[x] for x in available_headers],
                     interactive=False,
-                    wrap=True, 
+                    wrap=True,
                     visible=True)
                 return comp
 

gen_table.py

@@ -33,17 +33,17 @@ def nth_large(val, vals):
 def BUILD_L1_DF(results, fields):
     check_box = {}
     check_box['essential'] = ['Algorithm', 'LLM', 'Eval Date']
-    # revise there to set default dataset
-    check_box['required'] = ['Avg Score'] +  [item for f in fields for item in (f'{f}-Score', f'{f}-Cost($)')]
+    # 修改这里：确保列名与generate_table函数生成的列名一致
+    check_box['required'] = ['Avg Score'] + [f for field in fields for f in [f'{field}-Score', f'{field}-Cost($)']]
     check_box['avg'] = ['Avg Score']
-    check_box['all'] = check_box['avg'] +  [item for f in fields for item in (f'{f}-Score', f'{f}-Cost($)')]
+    check_box['all'] = check_box['avg'] + [f for field in fields for f in [f'{field}-Score', f'{field}-Cost($)']]
+    
     type_map = defaultdict(lambda: 'number')
     type_map['Algorithm'] = 'html'
     type_map['LLM'] = type_map['Vision Model'] = 'html'
     type_map['Eval Date'] = 'str'
     check_box['type_map'] = type_map
 
-    # df = generate_table(results, fields)
     return check_box
 
 
@@ -85,21 +85,20 @@ def BUILD_L2_DF(results, fields):
     df['Rank'] = df.groupby('Dataset').cumcount() + 1
     
     # Rearrange column order
-    columns = ['Rank', 'Algorithm', 'Dataset', 'LLM', 'Eval Date', 'Score', 'Pass rate', 'X-shot', 'Parameters']
+    columns = ['Rank', 'Algorithm', 'Dataset', 'LLM', 'Eval Date', 'Score', 'Pass rate', 'X-shot']
     remaining_columns = [col for col in df.columns if col not in columns]
     df = df[columns + remaining_columns]
 
     # Set checkbox configuration
     check_box = {}
     check_box['essential'] = ['Algorithm', 'Dataset', 'LLM', 'Eval Date']
-    check_box['required'] = check_box['essential'] + ['Score', 'Pass rate', 'X-shot', 'Parameters', 'Samples', 'All tokens', 'Cost($)']
-    check_box['all'] = ['Score', 'Pass rate', 'X-shot', 'Parameters', 'Samples', 'Total input tokens', 'Average input tokens', 'Total output tokens', 'Average output tokens', 'All tokens', 'Cost($)']
+    check_box['required'] = check_box['essential'] + ['Score', 'Pass rate', 'X-shot', 'Samples', 'All tokens', 'Cost($)']
+    check_box['all'] = ['Score', 'Pass rate', 'X-shot', 'Samples', 'Total input tokens', 'Average input tokens', 'Total output tokens', 'Average output tokens', 'All tokens', 'Cost($)']
     type_map = defaultdict(lambda: 'number')
     type_map['Algorithm'] = 'html'
     type_map['LLM'] = type_map['Vision Model'] = 'html'
     type_map['Eval Date'] = 'str'
     type_map['Dataset'] = 'str'
-    type_map['Parameters'] = 'str'
     type_map['All tokens'] = 'number'
     type_map['Cost($)'] = 'number'
     check_box['type_map'] = type_map
@@ -211,7 +210,7 @@ def generate_table_detail(results, fields):
     df['Rank'] = df.groupby('Dataset').cumcount() + 1
     
     # Rearrange column order
-    columns = ['Rank', 'Dataset', 'Algorithm', 'LLM', 'Eval Date', 'Score', 'Pass rate', 'X-shot', 'Parameters']
+    columns = ['Rank', 'Dataset', 'Algorithm', 'LLM', 'Eval Date', 'Score', 'Pass rate', 'X-shot']
     remaining_columns = [col for col in df.columns if col not in columns]
     df = df[columns + remaining_columns]