example_usage.py

import joblib
import re
import string

# 🧹 Reuse the same clean_text function
def clean_text(text):
    text = text.lower()
    text = re.sub(r'\d+', '', text)  # remove numbers
    text = text.translate(str.maketrans('', '', string.punctuation))  # remove punctuation
    text = text.strip()
    return text

# 💾 Load the saved model and vectorizer
model = joblib.load("spam_detection_model.pkl")
vectorizer = joblib.load("spam_detection_vectorizer.pkl")

# 💬 Function to predict a new message
def predict_message(msg):
    msg_clean = clean_text(msg)
    msg_vec = vectorizer.transform([msg_clean])
    pred = model.predict(msg_vec)[0]
    return "🚨 Spam" if pred == 1 else "✅ Not Spam"

# 🧪 Test with some examples
print(predict_message("Congratulations! You have won a car"))
print(predict_message("Hey, click here to claim your reward"))
print(predict_message("Exclusive offer! Click here to claim your reward now"))