import mlflow
import numpy as np
import json

artifact_path = 'mlruns_s444417/1/169f2bf3d53f4de088c494e889c6e65a/artifacts/model'
model = mlflow.pyfunc.load_model(artifact_path)

with open(f'input_example.json') as f:
    input_example_data = json.load(f)

input_example = np.array(input_example_data['inputs']).reshape(-1, 8)

print(f'Input example: {input_example}')
print(f'Model prediction: {model.predict(input_example)}')