Update app.py

app.py

@@ -99,26 +99,29 @@ def preprocess_data(data):
 
 # Define your prediction function
 def make_prediction(rank,map,agent_picks):
-    data = [rank,map,agent_picks[0],agent_picks[1],agent_picks[2],agent_picks[3],agent_picks[4]] 
+    try:
+        data = [rank,map,agent_picks[0],agent_picks[1],agent_picks[2],agent_picks[3],agent_picks[4]] 
+        
+        # Preprocess the data (replace this with your specific preprocessing steps)
+        processed_data = preprocess_data(data)
     
-    # Preprocess the data (replace this with your specific preprocessing steps)
-    processed_data = preprocess_data(data)
-
-    # Feed the data to the model
-    prediction = model(processed_data)
-
-    # Post-process the output (replace this with your specific post-processing steps)
-    #prediction = model(data)
-    prediction = prediction.item()
-    if prediction > 1:
-        prediction -= (prediction - 1)/2
-    prediction = 0 if prediction < 0 else prediction
-
-    winrate = str(round(prediction * 100)) + '%'
-
-    print(f"Calculated Winrate: {winrate}")
-
-    return winrate
+        # Feed the data to the model
+        prediction = model(processed_data)
+    
+        # Post-process the output (replace this with your specific post-processing steps)
+        #prediction = model(data)
+        prediction = prediction.item()
+        if prediction > 1:
+            prediction -= (prediction - 1)/2
+        prediction = 0 if prediction < 0 else prediction
+    
+        winrate = str(round(prediction * 100)) + '%'
+    
+        print(f"Calculated Winrate: {winrate}")
+    
+        return winrate
+    except:
+        return 'Error, you probably forgot to fill out a component'
 
 # Example usage
 #data = ...  # your input data