Update app.py

app.py

@@ -191,7 +191,12 @@ def train_model(_):
 
 def prepare_data():
     """Prepares the dataset by splitting into X and y, and returns training and test sets."""
-    global X_train, X_test, y_train, y_test
+    global df_global, X_train, X_test, y_train, y_test
+    
+    # Check if df_global is None, which means no file has been uploaded yet
+    if df_global is None:
+        raise ValueError("DataFrame is None. Please upload a dataset first.")
+    
     target = df_global.columns[-1]
     X = df_global.drop(target, axis=1)
     y = df_global[target]
@@ -202,8 +207,13 @@ def prepare_data():
     X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2)
     return X_train, X_test, y_train, y_test
 
-# Prepare the data before the optimization process
-X_train, X_test, y_train, y_test = prepare_data()
+# Prepare the data before the optimization process, with a check for df_global
+try:
+    X_train, X_test, y_train, y_test = prepare_data()
+except ValueError as e:
+    print(e)  # You can log this or return it as a message in the UI
+    # Handle the error by returning or setting defaults as needed.
+
 
 def objective(trial):
     params = {