import gradio as gr import pickle import numpy as np # Load your model (make sure to upload model.pkl to your Space root directory) try: with open("model.pkl", "rb") as f: model = pickle.load(f) except Exception as e: model = None print(f"Error loading model: {e}") def predict(*args): if model is None: return "Model file 'model.pkl' not found. Please upload your .pkl file." # Example prediction logic — adjust feature array according to your model features = np.array([args]) prediction = model.predict(features) return f"Prediction: {prediction[0]}" # Customize your Gradio inputs according to your model's required inputs demo = gr.Interface( fn=predict, inputs=[ gr.Number(label="Age"), gr.Radio([0, 1], label="Sex (0 = Female, 1 = Male)"), gr.Number(label="Resting Blood Pressure"), gr.Number(label="Cholesterol") ], outputs="text", title="Heart Disease Predictor" ) demo.launch()