utils.py

# utils.py (Helper Functions)
import pickle
import numpy as np

def load_model():
    """

    Loads the trained model from file.

    """
    with open("models/model.pkl", "rb") as file:  
        model = pickle.load(file)  # Use pickle to load the model
    return model

def model_predict(email):
    """

    Predicts using the loaded model.

    """
    model = load_model()  # Load the model before predicting
    prediction = model.predict([email])  # Use the predict method to make predictions
    
    # If the email is spam, prediction should be 1, otherwise 0
    # Convert the prediction to 1 or -1 as specified
    prediction = 1 if prediction[0] == 1 else -1
    
    return prediction

with open("models/model.pkl", "rb") as file:
    model = pickle.load(file)

print("Model loaded successfully!")