If you train LSTM model to predict future values one step ahead, you can use a deque object to obtain a forecast for several steps ahead. At first you put your latest available data to the deque and pass this same data to the model to get a predicted value for the next time step. Then you use popleft() to remove the earliest value from the deque and append the predicted next value to the right. Repeat this procedure as many times as necessary.
Other option is to create LSTM model which will output predicted values for several steps ahead. If your model contains one or several LSTM layers put a dense layer with several units at the end and train this model with targets representing equal number of future data points.