debug

app.py

@@ -403,17 +403,17 @@ def init_leaderboard_mib_subgraph(dataframe, track):
     renamed_df = dataframe.rename(columns=display_mapping)
 
     # Original code 
-    # return Leaderboard(
-    #     value=renamed_df,  # Use DataFrame with display names
-    #     datatype=[c.type for c in fields(AutoEvalColumn_mib_subgraph)],
-    #     select_columns=SelectColumns(
-    #         default_selection=all_columns,  # Now contains display names
-    #         label="Select Results:"
-    #     ),
-    #     search_columns=["Method"],
-    #     hide_columns=[],
-    #     interactive=False,
-    # )
+    return Leaderboard(
+        value=renamed_df,  # Use DataFrame with display names
+        datatype=[c.type for c in fields(AutoEvalColumn_mib_subgraph)],
+        select_columns=SelectColumns(
+            default_selection=all_columns,  # Now contains display names
+            label="Select Results:"
+        ),
+        search_columns=["Method"],
+        hide_columns=[],
+        interactive=False,
+    )
     
 
 
@@ -465,42 +465,42 @@ def init_leaderboard_mib_subgraph(dataframe, track):
     # print(f"Successfully created leaderboard.")
     # return leaderboard
 
-    print("\nDebugging DataFrame columns:", dataframe.columns.tolist())
+    # print("\nDebugging DataFrame columns:", dataframe.columns.tolist())
 
-    # Define simple keywords for filtering
-    benchmark_keywords = ["ioi", "mcqa", "arithmetic", "arc"]
-    model_keywords = ["qwen2_5", "gpt2", "gemma2", "llama3"]
-
-    # Create SmartSelectColumns instance with exact same parameters as working version
-    smart_columns = SmartSelectColumns(
-        benchmark_keywords=benchmark_keywords,
-        model_keywords=model_keywords,
-        initial_selected=["Method", "Average"],
-        allow=True,
-        label=None,
-        show_label=True,
-        info=None
-    )
+    # # Define simple keywords for filtering
+    # benchmark_keywords = ["ioi", "mcqa", "arithmetic", "arc"]
+    # model_keywords = ["qwen2_5", "gpt2", "gemma2", "llama3"]
 
-    try:
-        print("\nCreating leaderboard...")
-        # Get groups before creating leaderboard
-        smart_columns.get_filtered_groups(dataframe.columns)
+    # # Create SmartSelectColumns instance with exact same parameters as working version
+    # smart_columns = SmartSelectColumns(
+    #     benchmark_keywords=benchmark_keywords,
+    #     model_keywords=model_keywords,
+    #     initial_selected=["Method", "Average"],
+    #     allow=True,
+    #     label=None,
+    #     show_label=True,
+    #     info=None
+    # )
+
+    # try:
+    #     print("\nCreating leaderboard...")
+    #     # Get groups before creating leaderboard
+    #     smart_columns.get_filtered_groups(dataframe.columns)
         
-        leaderboard = Leaderboard(
-            value=dataframe,
-            datatype=[c.type for c in fields(AutoEvalColumn_mib_subgraph)],
-            select_columns=smart_columns,
-            search_columns=["Method"],
-            hide_columns=[],
-            interactive=False
-        )
-        print("Leaderboard created successfully")
-        return leaderboard
+    #     leaderboard = Leaderboard(
+    #         value=dataframe,
+    #         datatype=[c.type for c in fields(AutoEvalColumn_mib_subgraph)],
+    #         select_columns=smart_columns,
+    #         search_columns=["Method"],
+    #         hide_columns=[],
+    #         interactive=False
+    #     )
+    #     print("Leaderboard created successfully")
+    #     return leaderboard
         
-    except Exception as e:
-        print("Error creating leaderboard:", str(e))
-        raise
+    # except Exception as e:
+    #     print("Error creating leaderboard:", str(e))
+    #     raise
 
 
 

custom-select-columns.py

@@ -807,3 +807,4 @@ To create a public link, set `share=True` in `launch()`.
 
 
 
+model_id: llama3, gemma2, gpt2, qwen2.5,