Update space

app.py

@@ -114,7 +114,11 @@ def process_submission(
     code_repo, csv_file, model_description, hardware, paper_link
 ):
     """Process and validate submission"""
-    # Validation checks
+    # Input validation
+    if not method_name or not team_name or not dataset or not split or not contact_email or not code_repo or not csv_file:
+        return "Error: Please fill in all required fields"
+    
+    # Length validation
     if len(method_name) > 25:
         return "Error: Method name must be 25 characters or less"
     if len(team_name) > 25:
@@ -175,70 +179,74 @@ def process_submission(
     except Exception as e:
         return f"Error processing submission: {str(e)}"
 
-# Add this to your existing Gradio interface
 def add_submission_form(demo):
     with demo:
+        gr.Markdown("---")
         gr.Markdown("## Submit Your Results")
         gr.Markdown("""
         Submit your results to be included in the leaderboard. Please ensure your submission meets all requirements.
         For questions, contact stark-qa@cs.stanford.edu
         """)
         
-        with gr.Form(elem_id="submission_form"):
-            method_name = gr.Textbox(
-                label="Method Name (max 25 chars)",
-                placeholder="e.g., MyRetrievalModel-v1"
-            )
-            team_name = gr.Textbox(
-                label="Team Name (max 25 chars)",
-                placeholder="e.g., Stanford NLP"
-            )
-            dataset = gr.Dropdown(
-                choices=["amazon", "mag", "prime"],
-                label="Dataset"
-            )
-            split = gr.Dropdown(
-                choices=["test", "test-0.1", "human_generated_eval"],
-                label="Split",
-                value="test"
-            )
-            contact_email = gr.Textbox(
-                label="Contact Email(s)",
-                placeholder="email@example.com; another@example.com"
-            )
-            code_repo = gr.Textbox(
-                label="Code Repository",
-                placeholder="https://github.com/username/repository"
-            )
-            csv_file = gr.File(
-                label="Prediction CSV",
-                file_types=[".csv"]
-            )
-            model_description = gr.Textbox(
-                label="Model Description",
-                lines=3,
-                placeholder="Briefly describe how your retriever model works..."
-            )
-            hardware = gr.Textbox(
-                label="Hardware Specifications",
-                placeholder="e.g., 4x NVIDIA A100 80GB"
-            )
-            paper_link = gr.Textbox(
-                label="Paper Link (Optional)",
-                placeholder="https://arxiv.org/abs/..."
-            )
-            
-            submit_btn = gr.Button("Submit", variant="primary")
-            result = gr.Textbox(label="Submission Status", interactive=False)
+        with gr.Row():
+            with gr.Column():
+                method_name = gr.Textbox(
+                    label="Method Name (max 25 chars)*",
+                    placeholder="e.g., MyRetrievalModel-v1"
+                )
+                team_name = gr.Textbox(
+                    label="Team Name (max 25 chars)*",
+                    placeholder="e.g., Stanford NLP"
+                )
+                dataset = gr.Dropdown(
+                    choices=["amazon", "mag", "prime"],
+                    label="Dataset*",
+                    value="amazon"
+                )
+                split = gr.Dropdown(
+                    choices=["test", "test-0.1", "human_generated_eval"],
+                    label="Split*",
+                    value="test"
+                )
+                contact_email = gr.Textbox(
+                    label="Contact Email(s)*",
+                    placeholder="email@example.com; another@example.com"
+                )
             
-            submit_btn.click(
-                process_submission,
-                inputs=[
-                    method_name, team_name, dataset, split, contact_email,
-                    code_repo, csv_file, model_description, hardware, paper_link
-                ],
-                outputs=result
-            )
+            with gr.Column():
+                code_repo = gr.Textbox(
+                    label="Code Repository*",
+                    placeholder="https://github.com/username/repository"
+                )
+                csv_file = gr.File(
+                    label="Prediction CSV*",
+                    file_types=[".csv"]
+                )
+                model_description = gr.Textbox(
+                    label="Model Description*",
+                    lines=3,
+                    placeholder="Briefly describe how your retriever model works..."
+                )
+                hardware = gr.Textbox(
+                    label="Hardware Specifications*",
+                    placeholder="e.g., 4x NVIDIA A100 80GB"
+                )
+                paper_link = gr.Textbox(
+                    label="Paper Link (Optional)",
+                    placeholder="https://arxiv.org/abs/..."
+                )
+        
+        submit_btn = gr.Button("Submit", variant="primary")
+        result = gr.Textbox(label="Submission Status", interactive=False)
+        
+        submit_btn.click(
+            process_submission,
+            inputs=[
+                method_name, team_name, dataset, split, contact_email,
+                code_repo, csv_file, model_description, hardware, paper_link
+            ],
+            outputs=result
+        )
 
 def format_dataframe(df, dataset):
     # Filter the dataframe for the selected dataset