Fix filtering issues

app.py

@@ -92,9 +92,10 @@ def update_table(
     columns: list,
     query: str,
 ):
-    columns += "_" # The dataframe does not display the last column - BUG in gradio?
+    columns += " " # The dataframe does not display the last column - BUG in gradio?
     #filtered_df = filter_models(hidden_df, type_query, size_query, precision_query, show_deleted)
     filtered_df = filter_queries(query, hidden_df)
+    filtered_df["Model"] = filtered_df.apply(add_model_hyperlinks, axis=1)
     df = select_columns(filtered_df, columns)
     return df
 
@@ -183,7 +184,7 @@ def validate_captcha(input, text, img):
 
 
 
-demo = gr.Blocks(css=custom_css)
+demo = gr.Blocks(css=custom_css, theme=gr.themes.Default(primary_hue=gr.themes.colors.orange, secondary_hue=gr.themes.colors.orange))
 with demo:
     gr.HTML(TITLE)
     gr.Markdown(INTRODUCTION_TEXT, elem_classes="markdown-text")
@@ -203,7 +204,7 @@ with demo:
                             choices=[
                                 c.name
                                 for c in fields(AutoEvalColumn)
-                                if not c.hidden and not c.never_hidden and not c.dummy
+                                if not c.hidden and not c.never_hidden # and not c.dummy  # Causes errors
                             ],
                             value=[
                                 c.name
@@ -214,31 +215,7 @@ with demo:
                             elem_id="column-select",
                             interactive=True,
                         )
-                """
-                with gr.Column(min_width=320):
-                    # with gr.Box(elem_id="box-filter"):
-                    filter_columns_type = gr.CheckboxGroup(
-                        label="Model types",
-                        choices=[t.to_str() for t in ModelType],
-                        value=[t.to_str() for t in ModelType],
-                        interactive=True,
-                        elem_id="filter-columns-type",
-                    )
-                    filter_columns_precision = gr.CheckboxGroup(
-                        label="Precision",
-                        choices=[i.value.name for i in Precision],
-                        value=[i.value.name for i in Precision],
-                        interactive=True,
-                        elem_id="filter-columns-precision",
-                    )
-                    filter_columns_size = gr.CheckboxGroup(
-                        label="Model sizes (in billions of parameters)",
-                        choices=list(NUMERIC_INTERVALS.keys()),
-                        value=list(NUMERIC_INTERVALS.keys()),
-                        interactive=True,
-                        elem_id="filter-columns-size",
-                    )
-                """
+                
             gr.Markdown(TABLE_DESC, elem_classes="markdown-text")
             leaderboard_table = gr.Dataframe(
                 value=leaderboard_df[
@@ -268,22 +245,19 @@ with demo:
                 ],
                 leaderboard_table,
             )
-            for selector in [
-                shown_columns,
-            ]:
-                selector.change(
-                    update_table,
-                    [
-                        hidden_leaderboard_table_for_search,
-                        shown_columns,
-                        search_bar,
-                    ],
-                    leaderboard_table,
-                    queue=True,
-                )
+            shown_columns.change(
+                update_table,
+                [
+                    hidden_leaderboard_table_for_search,
+                    shown_columns,
+                    search_bar,
+                ],
+                leaderboard_table,
+                queue=True,
+            )
 
             model_num = len(original_df)
-            graph_df = original_df.drop(columns=["_", "Precision", "Model URL"]).set_index("Model").T
+            graph_df = original_df.drop(columns=[" ", "Precision", "Model URL"]).set_index("Model").T
             graph_ax = graph_df.plot(
                 kind="barh", 
                 title="Graphical performance comparison", 

src/display/utils.py

@@ -72,7 +72,7 @@ auto_eval_column_dict.append(["mmlu_cs", ColumnContent, ColumnContent("MMLU", "n
 auto_eval_column_dict.append(["sqad_cs", ColumnContent, ColumnContent("SQAD", "number", True)])
 auto_eval_column_dict.append(["subjectivity_cs", ColumnContent, ColumnContent("Subjectivity", "number", True)])
 auto_eval_column_dict.append(["truthfulqa_cs", ColumnContent, ColumnContent("TruthfulQA", "number", True)])
-auto_eval_column_dict.append(["dummy", ColumnContent, ColumnContent("_", "str", True, dummy=True)])  # The dataframe does not display the last column - BUG in gradio?
+auto_eval_column_dict.append(["dummy", ColumnContent, ColumnContent(" ", "str", True, dummy=True)])  # The dataframe does not display the last column - BUG in gradio?
 
 
 
@@ -100,7 +100,7 @@ HEADER_MAP = {
     "sqad_cs": "SQAD",
     "subjectivity_cs": "Subjectivity",
     "truthfulqa_cs": "TruthfulQA",
-    "dummy": "_",
+    "dummy": " ",
     "aggregate_score": "Aggregate Score",
 }
 

src/populate.py

@@ -22,7 +22,7 @@ def get_leaderboard_df(results_path: str, requests_path: str, cols: list, benchm
     df["Math (Avg.)"] = df[["GSM8K", "Klokanek"]].mean(axis=1)
     df["Classification (Avg.)"] = df[["Czech News", "Facebook Comments", "Mall Reviews", "Subjectivity"]].mean(axis=1)
     df["Aggregate Score"] = df[["Grammar (Avg.)", "Knowledge (Avg.)", "Reasoning (Avg.)", "Math (Avg.)", "Classification (Avg.)"]].mean(axis=1)
-    df["_"] = ""  # The dataframe does not display the last column - BUG in gradio?
+    df[" "] = ""  # The dataframe does not display the last column - BUG in gradio?
     df = df[cols].round(decimals=2)
     df.replace(r'\s+', np.nan, regex=True)
     # filter out if any of the benchmarks have not been produced