Update app.py

app.py

@@ -212,31 +212,60 @@ with gr.Blocks(title="Bambara ASR Leaderboard") as demo:
     gr.Markdown(
         """
         # Bambara ASR Leaderboard
-        Upload a CSV file with 'id' and 'text' columns to evaluate your ASR predictions.
-        The 'id's must match those in the dataset.
         
-        - **WER**: Word Error Rate (lower is better).
-        - **CER**: Character Error Rate (lower is better).
+        This leaderboard ranks and evaluates speech recognition models for the Bambara language.
+        Models are ranked based on their Word Error Rate (WER), from lowest to highest.
         """
     )
     
-    with gr.Row():
-        submitter = gr.Textbox(label="Submitter Name or Model Name", placeholder="e.g., MALIBA-AI/asr")
-        csv_upload = gr.File(label="Upload CSV File", file_types=[".csv"])
+    # Load and display current leaderboard immediately
+    with gr.Tabs() as tabs:
+        with gr.TabItem("🏅 Current Rankings"):
+            # Show current leaderboard rankings
+            current_leaderboard = pd.read_csv(leaderboard_file).sort_values("WER")
+            
+            gr.Markdown("### Current ASR Model Rankings")
+            leaderboard_view = gr.DataFrame(
+                value=current_leaderboard,
+                interactive=False,
+                label="Models are ranked by Word Error Rate (WER) - lower is better"
+            )
+            
+            gr.Markdown(
+                """
+                ## Metrics Explanation
+                - **WER**: Word Error Rate (lower is better) - measures word-level accuracy
+                - **CER**: Character Error Rate (lower is better) - measures character-level accuracy
+                """
+            )
         
-    submit_btn = gr.Button("Submit")
-    output_msg = gr.Textbox(label="Status", interactive=False)
-    leaderboard_display = gr.DataFrame(
-        label="Leaderboard",
-        value=pd.read_csv(leaderboard_file),
-        interactive=False
-    )
-    
-    submit_btn.click(
-        fn=process_submission,
-        inputs=[submitter, csv_upload],
-        outputs=[output_msg, leaderboard_display]
-    )
+        with gr.TabItem("📊 Submit New Results"):
+            gr.Markdown(
+                """
+                ### Submit a new model for evaluation
+                
+                Upload a CSV file with 'id' and 'text' columns to evaluate your ASR predictions.
+                The 'id's must match those in the reference dataset.
+                """
+            )
+            
+            with gr.Row():
+                submitter = gr.Textbox(label="Submitter Name or Model Name", placeholder="e.g., MALIBA-AI/asr")
+                csv_upload = gr.File(label="Upload CSV File", file_types=[".csv"])
+                
+            submit_btn = gr.Button("Submit")
+            output_msg = gr.Textbox(label="Status", interactive=False)
+            leaderboard_display = gr.DataFrame(
+                label="Updated Leaderboard",
+                value=current_leaderboard,
+                interactive=False
+            )
+            
+            submit_btn.click(
+                fn=process_submission,
+                inputs=[submitter, csv_upload],
+                outputs=[output_msg, leaderboard_display]
+            )
 
 # Print startup message
 print("Starting Bambara ASR Leaderboard app...")