import json
import mlflow
import numpy as np
import sys

mlflow.set_tracking_uri("http://172.17.0.1:5000")
client =mlflow.tracking .MlflowClient()
model_version = 14
model_name = "s449288"

experiment = client.get_latest_versions(model_name, stages=None)
print(experiment)
print(experiment[0].source)
model = mlflow.pyfunc.load_model(
    model_uri=f"models:/{model_name}/{model_version}"
)

with open(f'{experiment[0].source}/{(sys.argv[1:])[0]}', 'r') as file:
    json_data = json.load(file)
    print(f"Prediction: {model.predict(np.array([json_data['inputs']]))}")


'''
PATH = "mlruns/14/80fe21a0804844088147d15a3cebb3e5/artifacts/lego-model"

model = mlflow.pyfunc.load_model(PATH)

with open(f'{PATH}/{(sys.argv[1:])[0]}', 'r') as file:
    json_data = json.load(file)
    print(f"Prediction: {model.predict(np.array([json_data['inputs']]))}")
'''