`stream` functionality

I have read that the stream function should be able to update (at least?) the model parameters. However, I'm not able to find models that has this method implemented. Am I wrong, or hasn't this been implemented yet? I can see that there is a stream.ARIMA, but that it is only a comment in the current devel version?

What is the anticipated behaviour of this compared to refit? I imagine that I would have an use-case where the data is streamed over time, and that updating a model with new arriving data should be easy. Say, that I have data from 2025 and fit a model to these data, e.g., ETS. Then, later I get data from 2026. Would stream(model_2025, newdata = df_2026) and refit(model_2025, newdata = df_2026) be different in compute time and/or outcome? And what would be the main difference to model(MODEL, .data = bind_rows(df_2025, df_2026))?

Thanks for a very impressive ecosystem of packages!

Start by examining the referenced stream.ARIMA comment and the existing refit and model entry points. The issue does not identify implementation files or tests; first establish the intended streaming behavior and its differences in computation and outcome from refitting or combining the data, then define tests for the agreed behavior.