import streamlit as st
import numpy as np
import joblib

col1, col2 = st.columns([0.25,0.75], vertical_alignment  = "center")

with col1:
    st.image("./src/lic logo.png")
with col2:
    st.title("Lic Insurance App")


age = st.number_input(label = "Enter your Age",
                      value = 30, min_value = 5, max_value = 70,
                      step = 1)

col3, col4 = st.columns([0.5,0.5], vertical_alignment  = "center")
with col3:
    feet = st.number_input(label = "Height in feet",
                      value = 5, min_value = 0, max_value = 10,
                      step = 1)
    
with col4:
    inches = st.number_input(label = "Height in inches",
                      value = 0, min_value = 0, max_value = 11,
                      step = 1)

weight = st.number_input(label = "Weight in kg",
                      value = 50.0, min_value = 5.0, max_value = 200.0,
                      step = 0.5)
height_m = feet*0.3048 + inches*0.0254
bmi = weight / (height_m)**2
st.write(f"Your BMI is -: {round(bmi,2)}")

children = st.slider(label = "Select number of Children",
                      min_value=0, max_value=5, value=0, step=1)
smoker = st.selectbox(label = "Enter Smoking Status",
                      options = ("Yes", "No"))

smoker_num = 1 if smoker == "Yes" else 0
test_data = [[age, bmi, children, smoker_num]]

model = joblib.load("./src/model.joblib") 
std_scaler = joblib.load("./src/scaler.joblib")
poly = joblib.load("./src/poly.joblib")

if st.button("Get Premium") == True:
    test_scale = std_scaler.transform(test_data)
    test_poly = poly.transform(test_scale)
    y_pred_sqrt = model.predict(test_poly)[0]
    y_pred = round(y_pred_sqrt**2,2)
    st.header(f"Your Premium amount is ${y_pred}")