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import streamlit as st
import pandas as pd
import joblib
import re
import string
# Page configuration
st.set_page_config(page_title="SMS Spam Detector", layout="centered")
st.title("📩 SMS Spam Detection App")
st.markdown("🔍 Enter a message below to check if it's **Spam** or **Not Spam (Ham)**")
# --- Load Model and Vectorizer ---
model = joblib.load("model/spam_model.pkl") # Make sure path is correct
vectorizer = joblib.load("model/tfidf_vectorizer.pkl") # Adjust as per your folder
# --- Text Cleaning Function ---
def clean_text(text):
text = text.lower()
text = re.sub(r"http\S+|www\S+|https\S+", '', text, flags=re.MULTILINE)
text = re.sub(r'\@w+|\#','', text)
text = re.sub(r'[^\w\s]', '', text)
text = re.sub(r'\d+', '', text)
text = text.translate(str.maketrans('', '', string.punctuation))
return text.strip()
# --- Prediction Function ---
def predict_spam(message):
cleaned = clean_text(message)
vector = vectorizer.transform([cleaned])
prediction = model.predict(vector)
return "Spam" if prediction[0] == 1 else "Not Spam"
# --- Input Section ---
user_input = st.text_area("✉️ Enter your SMS message here:")
if st.button("Check Message"):
if user_input.strip() == "":
st.warning("⚠️ Please enter a valid message.")
else:
result = predict_spam(user_input)
if result == "Spam":
st.error("🚫 This message is classified as **SPAM**.")
else:
st.success("✅ This message is classified as **NOT SPAM (HAM)**.")
# Footer
st.markdown("---")
st.markdown("🔒 **Note**: This is a demo model and not intended for production use without proper testing.")