return the str label not the array

model.py

@@ -12,6 +12,7 @@ class SmokerModel:
     def __init__(self, model_path, scaler_path):
         self.model = load(model_path)
         self.scaler = load(scaler_path)
+        self.labels = ["non-smoker", "smoker"]
         
     def scale(self, X):
         """
@@ -30,7 +31,7 @@ class SmokerModel:
 
         return new_data_scaled
 
-    def predict(self, X: np.ndarray):
+    def predict(self, X: np.ndarray) -> str:
         """
         Make a prediction on one sample using the loaded model.
 
@@ -55,8 +56,9 @@ class SmokerModel:
         X_scaled = self.scale(X)
 
         # Now, use the scaled data to make predictions using the loaded model
-        predicted_label = self.model.predict(X_scaled)
+        array = self.model.predict(X_scaled)
 
-        print(predicted_label)
-
-        return predicted_label
+        #predict
+        predicted_label = array[0]
+        str_label = self.labels[predicted_label]
+        return str_label