Update app.py

app.py

@@ -30,7 +30,7 @@ def format_stars(score):
     Convert the energy_score (assumed to be an integer from 1 to 5)
     into that many star characters wrapped in a span styled with color #3fa45bff
     and with a font size increased to 2em.
-    The use of '!important' forces the styling immediately.
+    The '!important' rules force the styling immediately.
     """
     try:
         score_int = int(score)
@@ -50,12 +50,15 @@ def make_link(mname):
 def get_plots(task):
     """
     Read the energy CSV for a given task and return a Plotly scatter plot.
-    X-axis: Numeric GPU Energy (Wh) (rounded to 4 decimals)
-    Y-axis: Display only the model name (extracted from the model field)
+    The x-axis uses the 'total_gpu_energy' column (rounded to 4 decimals) and 
+    the y-axis displays only the model name (extracted from the 'model' column).
     """
     df = pd.read_csv('data/energy/' + task)
+    # If an extra unnamed index column exists, drop it.
+    if df.columns[0].startswith("Unnamed:"):
+        df = df.iloc[:, 1:]
     df['energy_score'] = df['energy_score'].astype(int)
-    # Use the raw energy (no multiplication) rounded to 4 decimals for plotting
+    # Use the correct column: "total_gpu_energy"
     df['GPU Energy (Wh)'] = df['total_gpu_energy'].round(4)
     # Create a column that displays only the model name (the part after '/')
     df['Display Model'] = df['model'].apply(lambda m: m.split('/')[-1])
@@ -97,6 +100,8 @@ def get_all_plots():
     all_df = pd.DataFrame()
     for task in tasks:
         df = pd.read_csv('data/energy/' + task)
+        if df.columns[0].startswith("Unnamed:"):
+            df = df.iloc[:, 1:]
         df['energy_score'] = df['energy_score'].astype(int)
         df['GPU Energy (Wh)'] = df['total_gpu_energy'].round(4)
         df['Display Model'] = df['model'].apply(lambda m: m.split('/')[-1])
@@ -140,8 +145,10 @@ def get_model_names(task):
     The final column order is: Model, GPU Energy (Wh), Score, [Class].
     """
     df = pd.read_csv('data/energy/' + task)
+    if df.columns[0].startswith("Unnamed:"):
+        df = df.iloc[:, 1:]
     df['energy_score'] = df['energy_score'].astype(int)
-    # Format the energy as a string with 4 decimals so that very small values display correctly
+    # Format the energy as a string with 4 decimals
     df['GPU Energy (Wh)'] = df['total_gpu_energy'].apply(lambda x: f"{x:.4f}")
     df['Model'] = df['model'].apply(make_link)
     df['Score'] = df['energy_score'].apply(format_stars)
@@ -164,6 +171,8 @@ def get_all_model_names():
     all_df = pd.DataFrame()
     for task in tasks:
         df = pd.read_csv('data/energy/' + task)
+        if df.columns[0].startswith("Unnamed:"):
+            df = df.iloc[:, 1:]
         df['energy_score'] = df['energy_score'].astype(int)
         df['GPU Energy (Wh)'] = df['total_gpu_energy'].apply(lambda x: f"{x:.4f}")
         df['Model'] = df['model'].apply(make_link)
@@ -174,7 +183,19 @@ def get_all_model_names():
     return all_df[['Model', 'GPU Energy (Wh)', 'Score']]
 
 # Build the Gradio interface.
-demo = gr.Blocks()
+# The css argument below makes all tables (e.g. leaderboard) use a fixed layout with narrower columns.
+demo = gr.Blocks(css="""
+.gr-dataframe table {
+    table-layout: fixed;
+    width: 100%;
+}
+.gr-dataframe th, .gr-dataframe td {
+    max-width: 150px;
+    white-space: nowrap;
+    overflow: hidden;
+    text-overflow: ellipsis;
+}
+""")
 
 with demo:
     gr.Markdown(