Add functions to update displayed columns and their widths in retrieval and reranking leaderboards

app.py

@@ -105,6 +105,17 @@ def retrieval_search_leaderboard(model_name, columns_to_show):
 def reranking_search_leaderboard(model_name, columns_to_show):
     return search_leaderboard(reranking_df, model_name, columns_to_show)
 
+def update_retrieval_columns_to_show(columns_to_show):
+    global retrieval_df
+    dummy_df = retrieval_df.loc[:, columns_to_show]
+    columns_widths = [400] + [150] * (len(columns_to_show) - 1)
+    return gr.update(value=dummy_df, column_widths=columns_widths)
+
+def update_reranker_columns_to_show(columns_to_show):
+    global reranking_df
+    dummy_df = reranking_df.loc[:, columns_to_show]
+    columns_widths = [400] + [150] * (len(columns_to_show) - 1)
+    return gr.update(value=dummy_df, column_widths=columns_widths)
 
 def main():
     global retrieval_df, reranking_df
@@ -112,11 +123,13 @@ def main():
     # Prepare retrieval dataframe
     retrieval_df = load_retrieval_results(True, "Web Search Dataset (Overall Score)", ["Revision", "Precision", "Task"])
     retrieval_columns_to_show = ["Model", "Web Search Dataset (Overall Score)", "Model Size (MB)", "Embedding Dimension", "Max Tokens", "Num Likes"]
+    
     retrieval_cols = retrieval_df.columns.tolist()  # cache columns
 
     # Prepare reranking dataframe
     reranking_df = load_reranking_results(True, sort_col="Overall Score", drop_cols=["Revision", "Precision", "Task"])
     reranking_columns_to_show = ["Model", "Overall Score", "Model Parameters (in Millions)", "Embedding Dimensions", "Downloads Last Month", "MRR", "nDCG", "MAP"]
+    reranking_columns_widths = [400, 150, 150, 150, 150, 150, 150]
     reranking_cols = reranking_df.columns.tolist()  # cache columns
 
     with gr.Blocks() as demo:
@@ -142,9 +155,10 @@ def main():
                         retrieval_leaderboard = gr.Dataframe(
                             value=retrieval_df[retrieval_columns_to_show],
                             datatype="markdown",
-                            wrap=True,
+                            wrap=False,
                             show_fullscreen_button=True,
-                            interactive=False
+                            interactive=False,
+                            column_widths=reranking_columns_widths
                         )
                         
                         # Submit the search box and the leaderboard
@@ -154,7 +168,7 @@ def main():
                             outputs=retrieval_leaderboard
                         )
                         retrieval_columns_to_show_input.select(
-                            lambda columns: retrieval_df.loc[:, columns],
+                            update_retrieval_columns_to_show,
                             inputs=retrieval_columns_to_show_input,
                             outputs=retrieval_leaderboard
                         )
@@ -184,9 +198,10 @@ def main():
                         reranker_leaderboard = gr.Dataframe(
                             value=reranking_df[reranking_columns_to_show],
                             datatype="markdown",
-                            wrap=True,
+                            wrap=False,
                             show_fullscreen_button=True,
                             interactive=False,
+                            column_widths=reranking_columns_widths
                         )
 
                         # Submit the search box and the leaderboard
@@ -196,7 +211,7 @@ def main():
                             outputs=reranker_leaderboard
                         )
                         reranking_columns_to_show_input.select(
-                            lambda columns: reranking_df.loc[:, columns],
+                            update_reranker_columns_to_show,
                             inputs=reranking_columns_to_show_input,
                             outputs=reranker_leaderboard
                         )