I have a pyfunc model that I can use to get predictions. It takes time series data with context information at each date, and produces a string of predictions. For example:

The data is set up like below (temp/pressure/output are different than my input data columns)

date,sales,temperature,pressure,output
01-09-2020,100,101,5000,10
01-10-2020,120,91,4000,24
01-11-2020,50,110,6000,30

let's say the model is trained using a window size of 60 and prediction inverval of 14. then in the model, you provide provide 60 records, and the prediction will get 14 predictions starting the last date+1 in your prediction dataset.

the return is just of the form

date,prediction
01-12-2022,81
01-13-2022,60
01-14-2022,111
...

with N records (in our example 14). it works brilliantly if I augment the data myself and work with the predict function.

Does working with the feature store support this? score batch doesn't seem to be able to return arbitrary/different shaped data. I could try making the data wide, but then that would defeat the purpose of trying to use the feature store.

don't know if I'm making sense.