[Add] average to df

app.py

@@ -1,5 +1,5 @@
 import gradio as gr
-from gradio_leaderboard import Leaderboard
+from gradio_leaderboard import Leaderboard, SelectColumns, ColumnFilter
 from pathlib import Path
 import pandas as pd
 
@@ -10,7 +10,7 @@ import json
 import requests
 
 from envs import API, EVAL_REQUESTS_PATH, TOKEN, QUEUE_REPO
-from utils import LLM_BENCHMARKS_ABOUT_TEXT, LLM_BENCHMARKS_SUBMIT_TEXT, custom_css, jsonl_to_dataframe
+from utils import LLM_BENCHMARKS_ABOUT_TEXT, LLM_BENCHMARKS_SUBMIT_TEXT, custom_css, jsonl_to_dataframe, add_average_column_to_df
 
 
 
@@ -108,8 +108,10 @@ base_df = jsonl_to_dataframe(str(abs_path / "leaderboard_base.jsonl"))
 all_columns = ["Average ⬆️", "Precision", "#Params (B)", "Part Multiple Choice", "ARC Easy", "ARC Challenging", "MMLU Pro", "GSM8k Persian", "Multiple Choice Persian"]
 columns_to_average = ["Part Multiple Choice", "ARC Easy", "ARC Challenging", "MMLU Pro", "GSM8k Persian", "Multiple Choice Persian"]
 
-persian_df["Average ⬆️"] = persian_df[columns_to_average].mean(axis=1)
-base_df["Average ⬆️"] = base_df[columns_to_average].mean(axis=1)
+
+base_df = add_average_column_to_df(base_df, columns_to_average, index=3)
+persian_df = add_average_column_to_df(persian_df, columns_to_average, index=3)
+
 
 
 with gr.Blocks(css=custom_css) as demo:
@@ -134,7 +136,12 @@ with gr.Blocks(css=custom_css) as demo:
                 """)
         Leaderboard(
         value=base_df,
-        select_columns=all_columns,
+        # select_columns=all_columns,
+        select_columns=SelectColumns(
+            default_selection=all_columns,
+            cant_deselect=["Model"],
+            label="Select Columns to Show",
+        ),
         search_columns=["model_name_for_query"],
         hide_columns=["model_name_for_query",],
         filter_columns=["Precision", "#Params (B)"],

utils.py

@@ -149,3 +149,9 @@ def load_jsonl(input_file):
 def jsonl_to_dataframe(input_file):
     data = load_jsonl(input_file)
     return pd.DataFrame(data)
+
+
+def add_average_column_to_df(df,columns_to_average, index=3):
+    average_column = df[columns_to_average].mean(axis=1)
+    df.insert(index, "Average ⬆️", average_column)
+    return df