app.py

import gradio as gr
import numpy as np
import joblib

# Load the saved logistic regression model file (place model.pkl in Space repo)
model = joblib.load("heart_disease_model.pkl")

feature_names = [
    "age", "sex", "cp", "trestbps", "chol", "fbs",
    "restecg", "thalach", "exang", "oldpeak", "slope", "ca", "thal"
]

def predict_heart_disease(age, sex, cp, trestbps, chol, fbs, restecg, thalach,
                          exang, oldpeak, slope, ca, thal):
    input_data = np.array([[age, sex, cp, trestbps, chol, fbs, restecg, thalach,
                            exang, oldpeak, slope, ca, thal]])
    prediction = model.predict(input_data)
    if prediction[0] == 0:
        return "The Person does not have a Heart Disease"
    else:
        return "The Person has Heart Disease"

inputs = [gr.Number(label=feature) for feature in feature_names]

demo = gr.Interface(fn=predict_heart_disease, inputs=inputs, outputs="text",
                    title="Heart Disease Prediction")

if __name__ == "__main__":
    demo.launch()