Update app.py

app.py

@@ -92,35 +92,27 @@ def calculate_metrics(predictions_df):
     
     return avg_wer, avg_cer, weighted_wer, weighted_cer, results
 
-def format_as_percentage(value):
-    """Convert decimal to percentage with 2 decimal places"""
-    return f"{value * 100:.2f}%"
-
-def make_clickable_model(model_name):
-    """Format model name as clickable link to Hugging Face hub"""
-    link = f"https://huggingface.co/{model_name}"
-    return f'<a href="{link}" target="_blank" style="text-decoration: underline;">{model_name}</a>'
-
 def prepare_leaderboard_for_display(df, sort_by="Combined_Score"):
     """Format leaderboard for display with ranking and percentages"""
     if len(df) == 0:
         return pd.DataFrame(columns=["Rank", "Model_Name", "WER (%)", "CER (%)", "Combined_Score (%)", "timestamp"])
     
-
+    # Make a copy to avoid modifying the original
     display_df = df.copy()
     
+    # Sort by specified column
     display_df = display_df.sort_values(sort_by)
     
+    # Add ranking column
     display_df.insert(0, "Rank", range(1, len(display_df) + 1))
     
+    # Convert metrics to percentages for display
     for col in ["WER", "CER", "Combined_Score"]:
         if col in display_df.columns:
+            # Format to 2 decimal places but keep as numeric for sorting
             display_df[f"{col} (%)"] = display_df[col].apply(lambda x: f"{x * 100:.2f}")
             display_df = display_df.drop(col, axis=1)
     
-    if "Model_Name" in display_df.columns:
-        display_df["Model_Name"] = display_df["Model_Name"].apply(make_clickable_model)
-    
     return display_df
 
 def update_ranking(method):
@@ -137,9 +129,11 @@ def update_ranking(method):
         elif method == "CER Only":
             sort_column = "CER"
         
+        # Format for display with ranking and percentages
         return prepare_leaderboard_for_display(current_lb, sort_column)
         
     except Exception:
+        # Return empty dataframe with formatted columns
         return pd.DataFrame(columns=["Rank", "Model_Name", "WER (%)", "CER (%)", "Combined_Score (%)", "timestamp"])
 
 def process_submission(model_name, csv_file):
@@ -186,17 +180,33 @@ def process_submission(model_name, csv_file):
             columns=["Model_Name", "WER", "CER", "Combined_Score", "timestamp"]
         )
         
-
+        # Update leaderboard without formatting for CSV storage
         updated_leaderboard = pd.concat([leaderboard, new_entry]).sort_values("Combined_Score")
         updated_leaderboard.to_csv(leaderboard_file, index=False)
         
+        # Format for display with ranking and percentages
         display_leaderboard = prepare_leaderboard_for_display(updated_leaderboard)
         
-        return f"Submission processed successfully! WER: {format_as_percentage(avg_wer)}, CER: {format_as_percentage(avg_cer)}, Combined Score: {format_as_percentage(combined_score)}", display_leaderboard
+        # Format percentages for the result message
+        wer_pct = f"{avg_wer * 100:.2f}%"
+        cer_pct = f"{avg_cer * 100:.2f}%"
+        combined_pct = f"{combined_score * 100:.2f}%"
+        
+        return f"Submission processed successfully! WER: {wer_pct}, CER: {cer_pct}, Combined Score: {combined_pct}", display_leaderboard
         
     except Exception as e:
         return f"Error processing submission: {str(e)}", None
 
+def add_model_info_section():
+    """Return HTML with information about viewing model details"""
+    return """
+    <div style="margin-top: 20px; padding: 10px; background-color: #f8f9fa; border-radius: 5px;">
+        <p><strong>📌 Note:</strong> To view details about a specific model, visit its page on the Hugging Face Hub:</p>
+        <p>https://huggingface.co/MODEL_NAME</p>
+        <p>For example: <a href="https://huggingface.co/MALIBA-AI/bambara-asr" target="_blank">https://huggingface.co/MALIBA-AI/bambara-asr</a></p>
+    </div>
+    """
+
 with gr.Blocks(title="Bambara ASR Leaderboard") as demo:
     gr.Markdown(
         """
@@ -215,6 +225,7 @@ with gr.Blocks(title="Bambara ASR Leaderboard") as demo:
                 if "Combined_Score" not in current_leaderboard.columns:
                     current_leaderboard["Combined_Score"] = current_leaderboard["WER"] * 0.7 + current_leaderboard["CER"] * 0.3
                 
+                # Format for display with ranking and percentages
                 display_leaderboard = prepare_leaderboard_for_display(current_leaderboard)
             except Exception:
                 display_leaderboard = pd.DataFrame(columns=["Rank", "Model_Name", "WER (%)", "CER (%)", "Combined_Score (%)", "timestamp"])
@@ -239,6 +250,9 @@ with gr.Blocks(title="Bambara ASR Leaderboard") as demo:
                 outputs=[leaderboard_view]
             )
             
+            # Add info about viewing model details
+            gr.HTML(add_model_info_section())
+            
             gr.Markdown(
                 """
                 ## Metrics Explanation