Update app.py

app.py

@@ -39,11 +39,26 @@ feature_options = {
 
 def predict_mushroom(*features):
     # Convert the feature names to a dictionary based on the order
-    feature_names = list(feature_options.keys())
-    numerical_features = {feature_names[i]: feature_options[feature_names[i]][value] for i, value in enumerate(features)}
-    
+    feature_names = list(mappings.keys())
+    numerical_features = {}
+
+    # Convert the string values to numerical values using the mappings
+    for i, feature in enumerate(features):
+        if feature in mappings[feature_names[i]]:
+            numerical_features[feature_names[i]] = mappings[feature_names[i]][feature]
+        else:
+            raise ValueError(f"Invalid value for feature '{feature_names[i]}': {feature}")
+
+    # Convert the numerical features into a DataFrame for the model
     input_df = pd.DataFrame([numerical_features])
-    prediction = model.predict(input_df)
+    
+    # Ensure the data is in the right format
+    try:
+        prediction = model.predict(input_df)
+    except Exception as e:
+        raise ValueError(f"Error during prediction: {e}")
+    
+    # Return the classification result based on the model output
     return 'Poisonous' if prediction[0] == 1 else 'Edible'
 
 demo = gr.Interface(