app.py

import streamlit as st
import pandas as pd
from utils import load_model, predict
from ui import get_user_input


def local_css(file_name):
    with open(file_name) as f:
        st.markdown(f"<style>{f.read()}</style>", unsafe_allow_html=True)

local_css("styles.css")

st.title("Lung Cancer Risk Predictor")

# 1. Load trained model
model = load_model('./models/model.pkl')

# 2. Collect user input as dataframe
input_df = get_user_input()
st.subheader("Patient Data")
st.write(input_df)

# 3. Make prediction
prediction, proba = predict(model, input_df)

# 4. Display results
st.subheader("Prediction")
print(prediction[0])
label = 'Cancer' if prediction[0] == 1 else 'No Cancer'
st.write(f"**{label}**")

st.subheader("Prediction Probability")
st.write(f"Probability of Cancer: {proba[0][1]:.2f}")