app.py

import streamlit as st
import pickle
import numpy as np

loaded_model = None  # Define the variable outside the try block

try:
    with open('heart_disease_model.pkl', 'rb') as file:
        loaded_model = pickle.load(file)
    print("Model loaded successfully!")
except FileNotFoundError:
    print("Error: The file 'heart_disease_model.pkl' was not found.")
except Exception as e:
    print("An error occurred while loading the model:", e)

def predict_heart_disease(input_data):
    if loaded_model is None:
        return None  # Handle case where the model wasn't loaded successfully
    input_data_reshaped = np.asarray(input_data).reshape(1, -1)
    prediction = loaded_model.predict(input_data_reshaped)
    return prediction[0]

def main():
    st.set_page_config(layout="centered")
    st.title('Heart Disease Prediction')
    st.markdown('Enter the values for the input features:')
    feature_names = [
        'age',
        'sex',
        'cp',
        'trestbps',
        'chol',
        'fbs',
        'restecg',
        'thalach',
        'exang',
        'oldpeak',
        'ca',
        'thal',
		'target',
    ]
    
    col1, col2 = st.columns([2, 1])
    
    with col1:
        input_data = []
        for feature_name in feature_names:
            input_value = st.number_input(feature_name, step=0.01)
            input_data.append(float(input_value))
        
        if st.button('Predict'):
            prediction = predict_heart_disease(input_data)
            if prediction is None:st.warning('The Person has Heart Disease')
        elif prediction == 0:
                st.error('The Person has Heart Disease')
        else:
                st.success('The Person does not have Heart Disease')
    
    with col2:
        st.markdown('**IF YES**')
        st.write('The person has heart disease, and they should seek medical care immediately. '
                 'It requires prompt medical attention and treatment.')
        
        st.markdown('**NO**')
        st.write('The person does not have any heart-related issues. '
                 'There is no need to worry.')
        
        st.markdown('**NOTE:** The prediction provided by this app is for informational purposes only. '
                    'It is not a substitute for professional medical advice or diagnosis.')

    st.markdown('<br>', unsafe_allow_html=True)

if __name__ == '__main__':
    main()