Update app.py

app.py

@@ -8,54 +8,18 @@ import os
 
 print(f"Prediction environment scikit-learn version: {sklearn.__version__}")
 
-def load_model():
-    """Load the model with detailed error checking"""
-    model_path = "model.pkl"
-    
-    try:
-        print(f"Attempting to load model from {os.path.abspath(model_path)}")
-        if not os.path.exists(model_path):
-            print(f"Error: Model file not found at {os.path.abspath(model_path)}")
-            return None
-            
-        with open(model_path, 'rb') as f:
-            try:
-                model = pickle.load(f)
-                print("Model loaded successfully, testing prediction...")
-                
-                # Test if model can make predictions
-                dummy_data = pd.DataFrame({
-                    'num__age': [0],
-                    'num__avg_glucose_level': [0],
-                    'num__bmi': [0],
-                    'cat__gender_Male': [0],
-                    'cat__gender_Other': [0],
-                    'cat__hypertension_1': [0],
-                    'cat__heart_disease_1': [0],
-                    'cat__ever_married_Yes': [0],
-                    'cat__work_type_Never_worked': [0],
-                    'cat__work_type_Private': [0],
-                    'cat__work_type_Self-employed': [0],
-                    'cat__work_type_children': [0],
-                    'cat__Residence_type_Urban': [0],
-                    'cat__smoking_status_formerly smoked': [0],
-                    'cat__smoking_status_never smoked': [0],
-                    'cat__smoking_status_smokes': [0]
-                })
-                model.predict_proba(dummy_data)
-                print("Model testing successful")
-                return model
-            except Exception as e:
-                print(f"Error testing model: {str(e)}")
-                print(f"Model type: {type(model)}")
-                print(f"Model attributes: {dir(model)}")
-                return None
-    except Exception as e:
-        print(f"Error loading model file: {str(e)}")
-        return None
+def decode_file(file_path):
+    with open(file_path, 'rb') as file:
+        obj = pickle.load(file)
+    return obj
 
 # Load the model once when starting the app
-model = load_model()
+try:
+    model = decode_file('model.pkl')
+    print("Model loaded successfully")
+except Exception as e:
+    print(f"Error loading model: {e}")
+    model = None
 
 def preprocess_input(data_dict):
     """Preprocess input data to match the training format"""