app.py

import joblib import pandas as pd import streamlit as st

model = joblib.load("daimondx.joblib") unique_values = joblib.load("unique_values (1).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],
                                           "size": [size],
                                           "length(mm)":[x],
                                           "width(mm)":[y],
                                           "depth(mm)":[z]}))
        # Show prediction
        st.success("Your predicted income is"+result)
if name == "main": main()