app.py

import streamlit as st
import joblib
import numpy as np

model = joblib.load("hdfc_life_final_model.joblib")
poly_obj = joblib.load("polynomial_object.joblib")


col1, col2 = st.columns([0.2,0.8])

with col1:
    st.image("HDFC-Life-Logo.png")

with col2:
    st.header("Premium Prediction App")

st.image("banner.jpg")

age = st.number_input("Enter your Age", min_value=0,
                      max_value= 100,step = 1,
                      value= 30)

label, ft_col, in_col = st.columns([0.4,0.3,0.3])
with label:
    st.write("Enter your height in Feet and inches")
with ft_col:
    feet = st.number_input("Feet",min_value=0, max_value=11,
                    value = 5,step = 1)

with in_col:
    inches = st.number_input("Inches",min_value=0, max_value=11,
                    value = 8,step = 1)
    
weight = st.number_input("Enter your Weight in KG", min_value=0, max_value=150,
                         value = 80, step=1)

height_meter = feet*0.3048 + inches*0.0254
bmi = weight/(height_meter)**2

# Determine BMI category
if bmi < 18.5:
    category = "Underweight"
elif 18.5 <= bmi < 25:
    category = "Normal weight"
elif 25 <= bmi < 30:
    category = "Overweight"
elif 30 <= bmi < 35:
    category = "Obesity Class I (Moderate)"
elif 35 <= bmi < 40:
    category = "Obesity Class II (Severe)"
else:
    category = "Obesity Class III (Very severe)"

# Display result in Streamlit
st.write(f"Your BMI is: {round(bmi, 2)}, Category: **{category}**")


children = st.slider("Enter Number of Children", min_value=0, max_value=5,
                     value = 0, step = 1)

smoker = st.selectbox("Enter Smoking status",["Yes", "No"])

smoker_num = 1 if smoker == "Yes" else 0

test_data = [[age, bmi, children, smoker_num]]

if st.button("Get Premium"):
    poly_data = poly_obj.transform(test_data)
    y_pred_log = model.predict(poly_data)
    y_pred = np.exp(y_pred_log)
    st.write(f"**Your Premium Amount is: ${round(y_pred[0],2)}**")