import os

import joblib
from keras.models import load_model


class Model:
    def __init__(self) -> None:
        # Time-Series
        self.__model_lstm = os.path.join("model", "model_health_best.keras")
        
        # Anomaly Detection
        self.__model_binary = os.path.join("model", "model_binary_smote.pkl")
        self.__model_multiclass = os.path.join("model", "model_multi.pkl")
        
        # Scaler Time-Series
        self.__scaler_lstm = os.path.join("model", "scaler_lstm.pkl")
        
        # Scaler Anomaly
        self.__preprocessor_anomaly = os.path.join("model", "scaler_anomaly.pkl")

        self._load_model_and_scalers()

    def _load_model_and_scalers(self):
        try:
            if os.path.exists(self.__model_lstm):
                self.model_lstm = load_model(self.__model_lstm)
                print("LSTM model loaded successfully")
            else:
                print(f"⚠ Model not found at {self.__model_lstm}")
            
            if os.path.exists(self.__model_binary):
                self.model_binary = joblib.load(self.__model_binary)
                print("Binary model loaded successfully")
            else:
                print(f"⚠ Model not found at {self.__model_binary}")
                
            if os.path.exists(self.__model_multiclass):
                self.model_multiclass = joblib.load(self.__model_multiclass)
                print("Multiclass model loaded successfully")
            else:
                print(f"⚠ Model not found at {self.__model_multiclass}")
                
            if os.path.exists(self.__preprocessor_anomaly):
                self.preprocessor_anomaly = joblib.load(self.__preprocessor_anomaly)
                print("Scaler anomaly model loaded successfully")
            else:
                print(f"⚠ preprocessor_anomaly not found at {self.__preprocessor_anomaly}")


            if os.path.exists(self.__scaler_lstm):
                self.scaler_lstm = joblib.load(self.__scaler_lstm)
                print("scaler_y loaded successfully")
            else:
                print(f"⚠ scaler_y not found at {self.__scaler_lstm}")

        except Exception as e:
            print(f"✗ Error loading model/scalers: {str(e)}")