Awesome. If I end up convincing the team to use ClearML, Ill probably have a ton of small requests to streamline the automation side of orchestration, is the team open to PRs from external people?

Fantastic. Essentially the example provide just prints out ids to the log file, and Im trying to play around with better things to do so that the top models and similar are saved out in some way I can access without manually reading a log file. Maybe reporting a scalar thats a string which has the task id for the top model? Unsure the best way, hence why I was trying to access the optimiser itself which would naturally contain that info

How so? The view can be used to just initialise the plot above like I had done all the steps by hand, but any flexibility (add in other scalars/parameters) Id expect would still be viable options in the UI

Heres the landing page, now with no option for settings or sidebar navigation:

Yes, this is expected, because you are trying to log a matplotlib figure as if it was a plotly figure. Try using report_matplotlib_figure

And heres the profile page if I access it via the URL. No option to add credentials

Yeah its trying to plan down the line into model deployment. Whilst its easy to save out a keras SavedModel or similar and have that artifact uploaded into the store, just wanted to check if there was a more generic solution. I could just create a Python class and serialise that out such that it has a standard interface, but good to check. So for example, some artifact representing an arbitrary math function. For better context, the idea is to make deploying any artifact we upload using clear...