Update app.py

app.py

@@ -172,9 +172,11 @@ def predict(u_id, i_id, timestamp, mem):
     top_values = [v.item() for v in topk.values]  # Flatten and convert each tensor to float
     
     # Format the top-k values
-    formatted_result = "\n".join([f"{i+1}. {val:.4f}" for i, val in enumerate(top_values)])
+    #formatted_result = "\n".join([f"{i+1}. {val:.4f}" for i, val in enumerate(top_values)])
+    formatted_result = "\n".join([f"{val:.4f}" for i, val in enumerate(top_values)])
     
-    return f"Top {len(top_values)} predicted interaction probabilities:\n{formatted_result}"
+    #return f"Top {len(top_values)} predicted interaction probabilities:\n{formatted_result}"
+    return f"Predicted interaction probability: {formatted_result}"
 
 
 with gr.Blocks() as demo: