src/streamlit_app.py

import streamlit as st
import joblib
import numpy as np

# Load the model
model = joblib.load("src/insurance_analysis_model")

st.title(":orange[Insurance Premium Predictor 💰]")

# Input fields
age = st.slider("Age", 18, 100, step=1)
bmi = st.number_input("BMI", min_value=10.0, max_value=50.0, step=0.1)
children = st.number_input("Number of Children", min_value=0, max_value=10, step=1)
sex = st.selectbox("Sex", ["male", "female"])
smoker = st.selectbox("Smoker", ["yes", "no"])
region = st.selectbox("Region", ["northeast", "southeast", "southwest", "northwest"])

# Convert to numeric or one-hot
sex_val = 1 if sex == "male" else 0
smoker_val = 1 if smoker == "yes" else 0
region_val = {"northeast": 0, "southeast": 1, "southwest": 2, "northwest": 3}[region]

# Predict
if st.button("Predict"):
    st.snow()
    input_data = np.array([[age, bmi, children, sex_val, smoker_val, region_val]])
    prediction = model.predict(input_data)[0]
    prediction = float(prediction)  # Convert to float
    st.success(f"Predicted Insurance Premium: 💲{round(prediction, 2)}")