app.py

import streamlit as st
import pandas as pd
import numpy as np
import pickle

# Set page configuration
st.set_page_config(page_title="🎯 Direct Message Influence Predictor", layout="wide")

# Custom background and styling
st.markdown("""
    <style>
        body {
            background-color: #080808;
        }
        .stApp {
            background-color: #080808;
        }
        .title-text {
            color: #00FFFF;
            font-size: 32px;
            font-weight: bold;
        }
        .sidebar-title {
            font-size: 18px;
            font-weight: bold;
        }
        .feature-box {
            background-color: #080808 ;
            padding: 15px;
            border-radius: 10px;
            box-shadow: 0px 2px 6px rgba(0,0,0,0.1);
        }
    </style>
""", unsafe_allow_html=True)

# Load the model
try:
    with open("best_random_forest_model (1).pkl", "rb") as file:
        model = pickle.load(file)
except FileNotFoundError:
    st.error("❌ Model file 'best_random_forest_model (1).pkl' not found. Please make sure it is in the same directory as this app.")
    st.stop()

# Title
st.markdown('<div class="title-text">🎯 Coupon Influence Prediction</div>', unsafe_allow_html=True)
st.write("Fill in the customer data below to predict if the direct mail coupon was effective.")

# Two-column layout
col1, col2 = st.columns([1, 1])

with col1:
    st.markdown("### 🧾 Customer Input")
    with st.form(key="predict_form"):
        used_coupon = st.selectbox("Used Coupon After DM?", [0, 1])
        after_spend = st.number_input("Spend After DM ($)", min_value=0.0, format="%.2f")
        after_units = st.number_input("Units After DM", min_value=0)
        before_spend = st.number_input("Spend Before DM ($)", min_value=0.0, format="%.2f")
        submit_button = st.form_submit_button("🔍 Predict")

    if submit_button:
        input_data = pd.DataFrame([[used_coupon, after_spend, after_units, before_spend]],
                                  columns=["used_coupon_after_dm", "after_spend", "after_units", "before_spend"])
        prediction = model.predict(input_data)[0]
        proba = model.predict_proba(input_data)[0][prediction]

        label = "✅ Influenced by DM" if prediction == 1 else "❌ Not Influenced"
        st.success(f"**Prediction:** {label}")
        st.info(f"**Confidence:** {proba * 100:.2f}%")

with col2:
    st.markdown("### 📘 Feature Descriptions")
    st.markdown("""
    <div class='feature-box'>
    <ul>
    <li><b>Used Coupon After DM?</b><br>Whether the customer used the direct mail (DM) coupon. <br><code>1 = Yes</code>, <code>0 = No</code></li><br>
    <li><b>Spend After DM ($)</b><br>Total money the customer spent <b>after</b> receiving the direct mail coupon.</li><br>
    <li><b>Units After DM</b><br>Number of items purchased <b>after</b> receiving the coupon.</li><br>
    <li><b>Spend Before DM ($)</b><br>Total money spent <b>before</b> receiving the direct mail coupon.</li>
    </ul>
    </div>
    """, unsafe_allow_html=True)