the trend step artifact used to keep track the time of the data so we know the expected trend of the input data. For example, on the first data which is trend_step = 1 the trend value is 10, then if the trend_step = 10 (the tenth data) our regressor will predict the trend value of the selected trend_step. this method is still in research to make it more efficient so it doesn't need to upload artifact every request

X is the sequence generated from df. df contains 2 columns (date and value). Size of X for this example is (1,60,1) with type np.array, X is sequence with size 1(number of data), 60(timestep), 1(value from 'value' column of df).