app.py

import gradio as gr
import pickle

# Load trained model and vectorizer
model = pickle.load(open("spam_mail_model.pkl", "rb"))
vectorizer = pickle.load(open("vectorizer.pkl", "rb"))

# Prediction function
def predict_mail(text):
    input_data = vectorizer.transform([text])
    prediction = model.predict(input_data)[0]
    return "✅ Ham Mail" if prediction == 1 else "🚫 Spam Mail"

# Gradio interface
demo = gr.Interface(
    fn=predict_mail,
    inputs=gr.Textbox(lines=3, placeholder="Enter your email text here..."),
    outputs="text",
    title="📧 Spam Mail Classifier",
    description="Detect if an email is Spam 🚫 or Ham ✅ using Logistic Regression."
)

demo.launch()