Update app.py

app.py

@@ -393,32 +393,64 @@ with gr.Blocks(css=css_tech_theme) as demo:
             """)    
 
 
+        # with gr.TabItem("📤 Submission"):
+        #     gr.Markdown("<div class='tabs'><h2>Submit Your Predictions</h2></div>")
+        #     with gr.Row():
+        #         file_input = gr.File(label="Upload Prediction CSV", file_types=[".csv"], interactive=True)
+        #         model_name_input = gr.Textbox(label="Model Name", placeholder="Enter your model name")
+
+        #     with gr.Row():
+        #         overall_accuracy_display = gr.Number(label="Overall Accuracy", interactive=False)
+        #         add_to_leaderboard_checkbox = gr.Checkbox(label="Add to Leaderboard?", value=True)
+
+        #     eval_button = gr.Button("Evaluate")
+        #     eval_status = gr.Textbox(label="Evaluation Status", interactive=False)
+
+        #     def handle_evaluation(file, model_name, add_to_leaderboard):
+        #         status, leaderboard = evaluate_predictions(file, model_name, add_to_leaderboard)
+        #         if leaderboard.empty:
+        #             overall_accuracy = 0
+        #         else:
+        #             overall_accuracy = leaderboard.iloc[-1]["Overall Accuracy"]
+        #         return status, overall_accuracy
+
+        #     eval_button.click(
+        #         handle_evaluation,
+        #         inputs=[file_input, model_name_input, add_to_leaderboard_checkbox],
+        #         outputs=[eval_status, overall_accuracy_display],
+        #     )
+
         with gr.TabItem("📤 Submission"):
-            gr.Markdown("<div class='tabs'><h2>Submit Your Predictions</h2></div>")
             with gr.Row():
                 file_input = gr.File(label="Upload Prediction CSV", file_types=[".csv"], interactive=True)
                 model_name_input = gr.Textbox(label="Model Name", placeholder="Enter your model name")
-
             with gr.Row():
                 overall_accuracy_display = gr.Number(label="Overall Accuracy", interactive=False)
-                add_to_leaderboard_checkbox = gr.Checkbox(label="Add to Leaderboard?", value=True)
-
-            eval_button = gr.Button("Evaluate")
-            eval_status = gr.Textbox(label="Evaluation Status", interactive=False)
-
-            def handle_evaluation(file, model_name, add_to_leaderboard):
-                status, leaderboard = evaluate_predictions(file, model_name, add_to_leaderboard)
+                eval_button = gr.Button("Evaluate")
+                eval_status = gr.Textbox(label="Evaluation Status", interactive=False)
+                submit_button = gr.Button("Prove and Submit to Leaderboard", visible=False)  # Initially hidden
+            def handle_evaluation(file, model_name):
+                # Perform evaluation
+                status, leaderboard = evaluate_predictions(file, model_name, add_to_leaderboard=False)
                 if leaderboard.empty:
                     overall_accuracy = 0
                 else:
                     overall_accuracy = leaderboard.iloc[-1]["Overall Accuracy"]
-                return status, overall_accuracy
-
+                    # Show the submit button after evaluation
+                    return status, overall_accuracy, gr.update(visible=True)
+            def handle_submission(file, model_name):
+                # Handle leaderboard submission
+                status, _ = evaluate_predictions(file, model_name, add_to_leaderboard=True)
+                return f"Submission to leaderboard completed: {status}"
             eval_button.click(
                 handle_evaluation,
-                inputs=[file_input, model_name_input, add_to_leaderboard_checkbox],
-                outputs=[eval_status, overall_accuracy_display],
-            )
+                inputs=[file_input, model_name_input],
+                outputs=[eval_status, overall_accuracy_display, submit_button],)
+            submit_button.click(
+                handle_submission,
+                inputs=[file_input, model_name_input],
+                outputs=[eval_status],)
+
 
         with gr.TabItem("🏅 Leaderboard"):
             leaderboard_table = gr.Dataframe(
@@ -454,7 +486,7 @@ with gr.Blocks(css=css_tech_theme) as demo:
         </p>
         <div class="social-links">
         <a href="https://website.com" target="_blank" class="social-link">🌐 Website</a>
-        <a href="https://github.com" target="_blank" class="social-link">🐙 GitHub</a>
+        <a href="https://github.com/VILA-Lab/Mobile-MMLU" target="_blank" class="social-link">🐙 GitHub</a>
     </div>
     </footer>
     """)