Update app.py

app.py

@@ -53,9 +53,7 @@ except Exception:
     restart_space()
 
 LEADERBOARD_DF = get_leaderboard_df(EVAL_RESULTS_PATH, EVAL_REQUESTS_PATH, COLS, BENCHMARK_COLS)
-print("Initial LEADERBOARD_DF:")
 print(LEADERBOARD_DF.head())
-print(f"LEADERBOARD_DF shape: {LEADERBOARD_DF.shape}")
 original_df = LEADERBOARD_DF
 leaderboard_df = original_df.copy()
 (
@@ -79,23 +77,12 @@ def update_table(
     show_flagged: bool,
     query: str,
 ):
-    print(f"Update table called with: type_query={type_query}, precision_query={precision_query}, size_query={size_query}")
-    print(f"hidden_df shape before filtering: {hidden_df.shape}")
     
     filtered_df = filter_models(hidden_df, type_query, size_query, precision_query, add_special_tokens_query, num_few_shots_query, show_deleted, show_merges, show_flagged)
-    print(f"filtered_df shape after filter_models: {filtered_df.shape}")
     
     filtered_df = filter_queries(query, filtered_df)
-    print(f"filtered_df shape after filter_queries: {filtered_df.shape}")
-    
-    print(f"Filter applied: query={query}, columns={columns}, type_query={type_query}, precision_query={precision_query}")
-    print("Filtered dataframe head:")
-    print(filtered_df.head())
 
     df = select_columns(filtered_df, columns)
-    print(f"Final df shape: {df.shape}")
-    print("Final dataframe head:")
-    print(df.head())
     return df
 
 
@@ -162,8 +149,8 @@ def filter_models(
 
     type_emoji = [t[0] for t in type_query]
     filtered_df = filtered_df.loc[df[AutoEvalColumn.model_type_symbol.name].isin(type_emoji)]
-    print(f"After type filter: {filtered_df.shape}")
-    filtered_df = filtered_df.loc[df[AutoEvalColumn.precision.name].isin(precision_query + ["None"])]
+    print(f"Unique values in precision column: {filtered_df[AutoEvalColumn.precision.name].unique()}")
+    filtered_df = filtered_df.loc[filtered_df[AutoEvalColumn.precision.name].isin(precision_query + ["None"])]
     print(f"After precision filter: {filtered_df.shape}")
     filtered_df = filtered_df.loc[df[AutoEvalColumn.add_special_tokens.name].isin(add_special_tokens_query)]
     print(f"After add_special_tokens filter: {filtered_df.shape}")
@@ -261,22 +248,37 @@ with demo:
                         elem_id="filter-columns-num-few-shots",
                     )
 
+            # leaderboard_table = gr.components.Dataframe(
+            #     value=leaderboard_df[
+            #         [c.name for c in fields(AutoEvalColumn) if c.never_hidden]
+            #         + shown_columns.value
+            #         # + [AutoEvalColumn.dummy.name]
+            #     ],
+            #     headers=[c.name for c in fields(AutoEvalColumn) if c.never_hidden] + shown_columns.value,
+            #     datatype=TYPES,
+            #     elem_id="leaderboard-table",
+            #     interactive=False,
+            #     visible=True,
+            #     #column_widths=["2%", "33%"] 
+            # )
+            initial_data = leaderboard_df[
+                [c.name for c in fields(AutoEvalColumn) if c.never_hidden]
+                + shown_columns.value
+            ].to_dict('records')
+            
             leaderboard_table = gr.components.Dataframe(
-                value=leaderboard_df[
-                    [c.name for c in fields(AutoEvalColumn) if c.never_hidden]
-                    + shown_columns.value
-                    # + [AutoEvalColumn.dummy.name]
-                ],
+                value=initial_data,
                 headers=[c.name for c in fields(AutoEvalColumn) if c.never_hidden] + shown_columns.value,
                 datatype=TYPES,
                 elem_id="leaderboard-table",
                 interactive=False,
                 visible=True,
-                #column_widths=["2%", "33%"] 
             )
+            # print("Leaderboard table initial value:")
+            # print(leaderboard_table.value.head())
+            # print(f"Leaderboard table shape: {leaderboard_table.value.shape}")
             print("Leaderboard table initial value:")
-            print(leaderboard_table.value.head())
-            print(f"Leaderboard table shape: {leaderboard_table.value.shape}")
+            print(initial_data[:5] if initial_data else "Empty")
 
             # Dummy leaderboard for handling the case when the user uses backspace key
             hidden_leaderboard_table_for_search = gr.components.Dataframe(