Update app.py

app.py

@@ -41,7 +41,10 @@ X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_
 model = xgb.XGBClassifier()
 model.fit(X_train, y_train)
 
-def predict(input_data):
+def predict(*inputs):
+    # Convert the list of inputs into a dictionary
+    input_data = {col: val for col, val in zip(X.columns, inputs)}
+
     # Handle missing values or intentionally omitted fields
     for col in X.columns:
         if input_data.get(col) is None:
@@ -57,6 +60,7 @@ def predict(input_data):
 
 
 
+
 # Set up Gradio interface for data exploration
 def explore_data(row_number):
     return df.iloc[row_number].to_dict()