app.py

# week_3_mls/deployment/app.py
import streamlit as st
import pandas as pd
import joblib
from huggingface_hub import hf_hub_download

# Load model from HF Hub
MODEL_REPO = "roshra/machine-failure-prediction"
MODEL_FILE = "tourism_clean_model.joblib"

model_path = hf_hub_download(repo_id=MODEL_REPO, filename=MODEL_FILE, repo_type="space")
model = joblib.load(model_path)

st.title("🧳 Tourism Package Purchase Prediction App")
st.write("Fill in details to predict if the customer will purchase the package.")

# UI inputs
age = st.number_input("Age", 18, 100, 30)
duration = st.number_input("Trip Duration (days)", 1, 30, 5)
adults = st.number_input("Number of Adults", 1, 10, 2)
children = st.number_input("Number of Children", 0, 10, 0)
income = st.number_input("Monthly Income", 1000, 200000, 30000)

prop = st.selectbox("Preferred Property", ["Hotel", "Resort", "Guest House", "Other"])
travel = st.selectbox("Mode of Travel", ["Air", "Train", "Car", "Bus"])
gender = st.selectbox("Gender", ["Male", "Female", "Other"])
occupation = st.selectbox("Occupation", ["Salaried", "Self-Employed", "Business", "Other"])
marital = st.selectbox("Marital Status", ["Single", "Married", "Divorced", "Other"])

if st.button("Predict Purchase"):
    input_df = pd.DataFrame([{
        "Age": age,
        "Duration": duration,
        "NumberOfAdults": adults,
        "NumberOfChildren": children,
        "MonthlyIncome": income,
        "PreferredProperty": prop,
        "ModeOfTravel": travel,
        "Gender": gender,
        "Occupation": occupation,
        "MaritalStatus": marital
    }])

    prediction = model.predict(input_df)[0]
    if prediction == 1:
        st.success("✅ Customer is likely to purchase the package!")
    else:
        st.error("❌ Customer is unlikely to purchase the package.")