app.py

import joblib
import pandas as pd
import streamlit as st


model = joblib.load("daimondjubjub.joblib")
unique_values = joblib.load("unique_values.joblib")
    
unique_cut =  unique_values["cut"]
unique_color =  unique_values["color"]
unique_clarity =  unique_values["clarity"]


def main():
    st.title("Diamond Prices")

    with st.form("questionaire"):
        carat = st.slider("Carat",min_value=0.00,max_value=5.00) 
        cut = st.selectbox("Cut", options=unique_cut)
        color = st.selectbox("Color", options=unique_color)
        clarity = st.selectbox("Clarity", options=unique_clarity) 
        depth = st.slider("Depth",min_value=0.00,max_value=100.00)
        table = st.slider("table",min_value=0.00,max_value=100.00)
        x = st.slider("length(mm)",min_value=0.01,max_value=10.00) 
        y = st.slider("width(mm)",min_value=0.01,max_value=10.00)
        z = st.slider("depth(mm)",min_value=0.01,max_value=10.00)
 

        # clicked==True only when the button is clicked
        clicked = st.form_submit_button("Predict Price")
        if clicked:
            result=model.predict(pd.DataFrame({"carat":[carat],
                                               "cut":[cut],
                                               "color":[color],
                                               "clarity":[clarity],
                                               "depth":[depth],
                                               "table":[table],
                                               "x":[x],
                                               "y":[y],
                                               "z":[z]}))
            # Show prediction
            st.success(f"Your predicted price is{result}")
if __name__ == "__main__":
    main()