app.py

import joblib
import pandas as pd
import streamlit as st

model = joblib.load('model.joblib')
unique_values = joblib.load('unique_values.joblib')
    
unique_topping =  unique_values["topping"]
unique_variant =  unique_values["variant"]
unique_size =  unique_values["size"]
unique_extra_sauce =  unique_values["extra_sauce"]
unique_extra_cheese =  unique_values["extra_cheese"]
unique_extra_mushrooms = unique_values["extra_mushrooms"]

def main():
    st.title("Predict Pizza Prices")

    with st.form("questionaire"):
        diameter = st.slider("diameter", min_value=0, max_value=30)
        topping = st.selectbox("topping", options=unique_topping)
        variant = st.selectbox("variant", options=unique_variant)
        size = st.selectbox("size", options=unique_size)
        extra_sauce = st.selectbox("extra_sauce", options=unique_extra_sauce)
        extra_cheese = st.selectbox("extra_cheese", options=unique_extra_cheese)
        extra_mushrooms = st.selectbox("extra_mushrooms", options=unique_extra_mushrooms)

        # clicked==True only when the button is clicked
        clicked = st.form_submit_button("Predict Price")
        if clicked:
            result=model.predict(pd.DataFrame({"diameter": [diameter],
                                               "topping": [topping],
                                               "variant": [variant],
                                               "size": [size],
                                               "extra_sauce": [extra_sauce],
                                               "extra_cheese": [extra_cheese],
                                               "extra_mushrooms": [extra_mushrooms]}))
                                              
            # Show prediction
            st.success(f"The pizza price is {result * 0.000067}$")

if __name__ == "__main__":
    main()