app.py

import joblib
import pandas as pd
import streamlit as st 



model = joblib.load('model.joblib')
unique_values = joblib.load('unique_values.joblib')
    
unique_hypertension =  unique_values["hypertension"]
unique_heart_disease =  unique_values["heart_disease"]
unique_gender =  unique_values["gender"]
unique_smoking_history = unique_values["smoking_history"]

def main():
    st.title("diabetes prediction")

    with st.form("questionaire"):
        age = st.slider("Age", min_value=10, max_value=100)
        hypertension = st.selectbox("Hypertemsion", unique_hypertension)
        heart_disease = st.selectbox("Heart_desease", unique_heart_disease)
        bmi = st.slider("Bmi", min_value=10, max_value=100)
        HbA1c_level =  st.slider("HbA1c_level", min_value=1, max_value=100)
        blood_glucose_level = st.slider("Blood_glucose_level", min_value=1, max_value=100) 
        gender = st.selectbox("Gender", unique_gender)
        smoking_history = st.selectbox("Smoking_history", unique_smoking_history)


        clicked = st.form_submit_button("Predict diabetes")
        if clicked:
            result=model.predict(pd.DataFrame({"age": [age],
                                               "hypertension": [hypertension],
                                               "heart_disease": [heart_disease],
                                               "bmi": [bmi],
                                               "HbA1c_level": [HbA1c_level],
                                               "blood_glucose_level": [blood_glucose_level],
                                               "gender": [gender],
                                               "smoking_history": [smoking_history]}))
            result = 'have diabetes' if result[0] == 1 else 'does not have diabetes'
            st.success('The predicted is {}'.format(result))


if __name__=='__main__':
    main()