import streamlit as st
import pandas as pd


def get_user_input() -> pd.DataFrame:
    """
    Render Streamlit widgets for each predictor and
    return a 1-row DataFrame ready for prediction.
    """
    st.sidebar.header('Patient Information')
    inputs = {
        'GENDER': st.sidebar.selectbox('Gender', ['Male', 'Female']),
        'SMOKING': st.sidebar.selectbox('Smoking', ['YES', 'NO']),
        'YELLOW_FINGERS': st.sidebar.selectbox('Yellow Fingers', ['YES', 'NO']),
        'ANXIETY': st.sidebar.selectbox('Anxiety', ['YES', 'NO']),
        'PEER_PRESSURE': st.sidebar.selectbox('Peer Pressure', ['YES', 'NO']),
        'CHRONIC DISEASE': st.sidebar.selectbox('Chronic Disease', ['YES', 'NO']),
        'FATIGUE ': st.sidebar.selectbox('Fatigue', ['YES', 'NO']),
        'ALLERGY ': st.sidebar.selectbox('Allergy', ['YES', 'NO']),
        'WHEEZING': st.sidebar.selectbox('Wheezing', ['YES', 'NO']),
        'ALCOHOL CONSUMING': st.sidebar.selectbox('Alcohol Consuming', ['YES', 'NO']),
        'COUGHING': st.sidebar.selectbox('Coughing', ['YES', 'NO']),
        'SHORTNESS OF BREATH': st.sidebar.selectbox('Shortness of Breath', ['YES', 'NO']),
        'SWALLOWING DIFFICULTY': st.sidebar.selectbox('Swallowing Difficulty', ['YES', 'NO']),
        'CHEST PAIN': st.sidebar.selectbox('Chest Pain', ['YES', 'NO'])
    }
    # Convert to DataFrame
    df = pd.DataFrame(inputs, index=[0])
    mapping = {'YES': 1, 'NO': 0, 'Male': 0, 'Female': 1}
    for col in df.columns:
        df[col] = df[col].map(mapping)

    return df