import streamlit as st
import pandas as pd
import joblib

# Load the model
model = joblib.load('xgb_model_pipeline.pkl')

st.title("ExtraaLearn Lead Conversion Predictor")

# Input form
with st.form("lead_form"):
    age = st.number_input("Age", min_value=18, max_value=70, step=1)
    current_occupation = st.selectbox("Current Occupation", ['Professional', 'Unemployed', 'Student'])
    first_interaction = st.selectbox("First Interaction", ['Website', 'Mobile App'])
    profile_completed = st.selectbox("Profile Completed", ['Low', 'Medium', 'High'])
    website_visits = st.number_input("Website Visits", min_value=0)
    time_spent_on_website = st.number_input("Time Spent on Website (seconds)", min_value=0)
    page_views_per_visit = st.number_input("Page Views Per Visit", min_value=0.0)
    last_activity = st.selectbox("Last Activity", ['Email Activity', 'Phone Activity', 'Website Activity'])
    print_media_type1 = st.selectbox("Saw Newspaper Ad?", ['Yes', 'No'])
    print_media_type2 = st.selectbox("Saw Magazine Ad?", ['Yes', 'No'])
    digital_media = st.selectbox("Saw Digital Ad?", ['Yes', 'No'])
    educational_channels = st.selectbox("Heard on Educational Channels?", ['Yes', 'No'])
    referral = st.selectbox("Heard via Referral?", ['Yes', 'No'])

    submit = st.form_submit_button("Predict")

    if submit:
        input_df = pd.DataFrame([{
            'age': age,
            'current_occupation': current_occupation,
            'first_interaction': first_interaction,
            'profile_completed': profile_completed,
            'website_visits': website_visits,
            'time_spent_on_website': time_spent_on_website,
            'page_views_per_visit': page_views_per_visit,
            'last_activity': last_activity,
            'print_media_type1': print_media_type1,
            'print_media_type2': print_media_type2,
            'digital_media': digital_media,
            'educational_channels': educational_channels,
            'referral': referral
        }])

        prediction = model.predict(input_df)[0]
        result = "Likely to Convert" if prediction == 1 else "Not Likely to Convert"
        st.success(f"Prediction: {result}")