app.py

import joblib
import pandas as pd
import streamlit as st 

model_tp = joblib.load('model_tp_xg.joblib')
model_acc = joblib.load('model_acc_xg.joblib')
unique_values = joblib.load('unique_values.joblib')
    
unique_acc =  unique_values["accommodation_type"]
unique_trans =  unique_values["transportation_type"]
unique_city = unique_values["city"]
unique_country =  unique_values["country"]

def main():
    st.title("Angie Assistance")

    with st.form("questionaire"):
        day = st.number_input("Stay Duration")
        trans = st.selectbox("Preferred Transportation", unique_trans)
        acc = st.selectbox("Preferred Accommodation",unique_acc)
        city = st.selectbox("City",unique_city)
        country = st.selectbox("Country", unique_country)

        clicked = st.form_submit_button("Predict expense of transportaion and accommodation")
        if clicked:
            result1 = model_tp.predict(pd.DataFrame({"duration_(days)": [day],
                                               "accommodation_type": [acc],
                                               "transportation_type": [trans],
                                               "city": [city],
                                               "country": [country]}))
            result2 = model_acc.predict(pd.DataFrame({"duration_(days)": [day],
                                               "accommodation_type": [acc],
                                               "transportation_type": [trans],
                                               "city": [city],
                                               "country": [country]}))
            result = result1[0] + result2[0]
            st.success('The predicted expense is {:.2f}'.format(result))

if __name__=='__main__':
    main()