Update app.py

app.py

@@ -11,41 +11,51 @@ def create_reranking_interface(task_data):
     
     def save_ranking(rankings, sample_id):
         """Save the current set of rankings."""
-        # Check if all documents have rankings
-        all_ranked = all(r is not None and r != "" for r in rankings)
-        if not all_ranked:
-            return "⚠️ Please assign a rank to all documents before submitting", f"Progress: {sum(completed_samples.values())}/{len(samples)}"
-        
-        # Convert rankings to integers
-        processed_rankings = [int(r) for r in rankings]
-        
-        # Check for duplicate rankings
-        if len(set(processed_rankings)) != len(processed_rankings):
-            return "⚠️ Each document must have a unique rank. Please review your rankings.", f"Progress: {sum(completed_samples.values())}/{len(samples)}"
+        try:
+            # Check if all documents have rankings
+            all_ranked = all(r is not None and r != "" for r in rankings)
+            if not all_ranked:
+                return "⚠️ Please assign a rank to all documents before submitting", f"Progress: {sum(completed_samples.values())}/{len(samples)}"
+            
+            # Convert rankings to integers with better error handling
+            try:
+                processed_rankings = [int(r) for r in rankings]
+            except ValueError:
+                return "⚠️ Invalid ranking value. Please use only numbers.", f"Progress: {sum(completed_samples.values())}/{len(samples)}"
+            
+            # Check for duplicate rankings
+            if len(set(processed_rankings)) != len(processed_rankings):
+                return "⚠️ Each document must have a unique rank. Please review your rankings.", f"Progress: {sum(completed_samples.values())}/{len(samples)}"
                 
-        # Store this annotation
-        existing_idx = next((i for i, a in enumerate(results["annotations"]) if a["sample_id"] == sample_id), None)
-        if existing_idx is not None:
-            results["annotations"][existing_idx] = {
-                "sample_id": sample_id,
-                "rankings": processed_rankings
-            }
-        else:
-            results["annotations"].append({
-                "sample_id": sample_id,
-                "rankings": processed_rankings
-            })
-        
-        completed_samples[sample_id] = True
-        success_msg = f"✅ Rankings for query '{sample_id}' successfully saved!"
-        progress = f"Progress: {sum(completed_samples.values())}/{len(samples)}"
-        
-        # Auto-save results after each submission
-        output_path = f"{task_data['task_name']}_human_results.json"
-        with open(output_path, "w") as f:
-            json.dump(results, f, indent=2)
-        
-        return success_msg, progress
+            # Store this annotation
+            existing_idx = next((i for i, a in enumerate(results["annotations"]) if a["sample_id"] == sample_id), None)
+            if existing_idx is not None:
+                results["annotations"][existing_idx] = {
+                    "sample_id": sample_id,
+                    "rankings": processed_rankings
+                }
+            else:
+                results["annotations"].append({
+                    "sample_id": sample_id,
+                    "rankings": processed_rankings
+                })
+            
+            completed_samples[sample_id] = True
+            success_msg = f"✅ Rankings for query '{sample_id}' successfully saved!"
+            progress = f"Progress: {sum(completed_samples.values())}/{len(samples)}"
+            
+            # Auto-save results after each submission with error handling
+            try:
+                output_path = f"{task_data['task_name']}_human_results.json"
+                with open(output_path, "w") as f:
+                    json.dump(results, f, indent=2)
+            except Exception as e:
+                return f"⚠️ Rankings saved in memory but couldn't write to file: {str(e)}", f"Progress: {sum(completed_samples.values())}/{len(samples)}"
+            
+            return success_msg, progress
+        except Exception as e:
+            # Catch-all for any other unexpected errors
+            return f"⚠️ An error occurred: {str(e)}", f"Progress: {sum(completed_samples.values())}/{len(samples)}"
     
     with gr.Blocks(theme=gr.themes.Soft()) as demo:
         gr.Markdown(f"# {task_data['task_name']} - Human Reranking Evaluation")