app.py

import streamlit as st
import pandas as pd
import joblib

# Load model
model = joblib.load("model.pkl")

st.title("Tourism Prediction App")

# -------------------------
# INPUT FIELDS (YOUR UI)
# -------------------------

Age = st.slider("Age", 18, 70, 30)
TypeofContact = st.selectbox("Type of Contact", ["Self Enquiry", "Company Invited"])
CityTier = st.selectbox("City Tier", [1, 2, 3])
DurationOfPitch = st.slider("Duration of Pitch (mins)", 0, 100, 15)
Occupation = st.selectbox("Occupation", ["Salaried", "Small Business", "Large Business", "Free Lancer"])
Gender = st.selectbox("Gender", ["Male", "Female", "Others"])
NumberOfPersonVisiting = st.slider("Number of Persons Visiting", 1, 5, 2)
NumberOfFollowups = st.slider("Number of Follow-ups", 1, 10, 3)
ProductPitched = st.selectbox("Product Pitched", ["Basic", "Standard", "Deluxe", "Super Deluxe", "King"])
PreferredPropertyStar = st.selectbox("Preferred Property Star", [1, 2, 3, 4, 5])
MaritalStatus = st.selectbox("Marital Status", ["Married", "Single", "Divorced", "Unmarried"])
NumberOfTrips = st.slider("Number of Trips", 1, 20, 3)
Passport = st.selectbox("Has Passport?", ["Yes", "No"])
PitchSatisfactionScore = st.slider("Pitch Satisfaction Score", 1, 5, 3)
OwnCar = st.selectbox("Owns a Car?", ["Yes", "No"])
NumberOfChildrenVisiting = st.slider("Number of Children Visited", 0, 5, 1)
Designation = st.selectbox("Designation", ["Executive", "Manager", "AVP", "VP", "Sr. Manager"])
MonthlyIncome = st.number_input("Monthly Income", min_value=1000.0, value=30000.0)

# -------------------------
# VALUE FIXING
# -------------------------

# Convert Yes/No → 1/0
Passport = 1 if Passport == "Yes" else 0
OwnCar = 1 if OwnCar == "Yes" else 0

# Fix category mismatches (VERY IMPORTANT)
if Designation == "Sr. Manager":
    Designation = "Senior Manager"

if MaritalStatus == "Unmarried":
    MaritalStatus = "Single"

# -------------------------
# PREDICTION
# -------------------------

if st.button("Predict"):
    try:
        input_data = pd.DataFrame([[
            Age, TypeofContact, CityTier, DurationOfPitch, Occupation, Gender,
            NumberOfPersonVisiting, NumberOfFollowups, ProductPitched,
            PreferredPropertyStar, MaritalStatus, NumberOfTrips, Passport,
            PitchSatisfactionScore, OwnCar, NumberOfChildrenVisiting,
            Designation, MonthlyIncome
        ]], columns=[
            'Age', 'TypeofContact', 'CityTier', 'DurationOfPitch', 'Occupation', 'Gender',
            'NumberOfPersonVisiting', 'NumberOfFollowups', 'ProductPitched',
            'PreferredPropertyStar', 'MaritalStatus', 'NumberOfTrips', 'Passport',
            'PitchSatisfactionScore', 'OwnCar', 'NumberOfChildrenVisiting',
            'Designation', 'MonthlyIncome'
        ])

        st.write("Input Data:", input_data)

        prediction = model.predict(input_data)

        st.success(f"Prediction: {prediction[0]}")

    except Exception as e:
        st.error(f"Error: {e}")