import json
import mlflow
import numpy as np

logged_model = 'mlruns/1/4b83e774512444188fb587288818c298/artifacts/model'
loaded_model = mlflow.pyfunc.load_model(logged_model)


with open('input_example.json') as f:
    data = json.load(f)
    input_example = np.array([data['inputs'][0]], dtype=np.float64).reshape(-1, 2)


print(f'Prediction: {loaded_model.predict(input_example)}')