app.py

import joblib
from huggingface_hub import hf_hub_download
import streamlit as st
import pandas as pd

# Download model from Hugging Face Hub
model_path = hf_hub_download(
    repo_id="Satyanjay/Tourism_Model",
    filename="best_model.pkl"
)

# Load the model
model = joblib.load(model_path)

st.title("Tourism Package Purchase Prediction")

# Collect inputs
Age = st.number_input("Age", 18, 100, 30)
CityTier = st.selectbox("City Tier", [1, 2, 3])
DurationOfPitch = st.number_input("Duration of Pitch (minutes)", 1, 60, 10)
NumberOfPersonVisiting = st.number_input("Number of Persons Visiting", 1, 10, 1)
NumberOfFollowups = st.number_input("Number of Followups", 0, 20, 1)
PreferredPropertyStar = st.number_input("Preferred Property Star", 1, 5, 3)
NumberOfTrips = st.number_input("Number of Trips per Year", 0, 50, 1)
Passport = st.selectbox("Passport (0=No, 1=Yes)", [0,1])
PitchSatisfactionScore = st.number_input("Pitch Satisfaction Score", 0, 10, 5)
OwnCar = st.selectbox("Own Car (0=No, 1=Yes)", [0,1])
MonthlyIncome = st.number_input("Monthly Income", 1000, 1000000, 30000)

# Convert inputs to dataframe for model
input_df = pd.DataFrame([{
    "Age": Age,
    "CityTier": CityTier,
    "DurationOfPitch": DurationOfPitch,
    "NumberOfPersonVisiting": NumberOfPersonVisiting,
    "NumberOfFollowups": NumberOfFollowups,
    "PreferredPropertyStar": PreferredPropertyStar,
    "NumberOfTrips": NumberOfTrips,
    "Passport": Passport,
    "PitchSatisfactionScore": PitchSatisfactionScore,
    "OwnCar": OwnCar,
    "MonthlyIncome": MonthlyIncome
}])