Yes! I was looking at it wrong. The task execution details are only there for logging previous execution.
To modify the execution of the next run I had to modify the clearml agent. In this case I added this to the clearml.conf of my agent (I only have one worker right now):
python_binary: "/usr/local/bin/python3.10"
ignore_requested_python_version: true

That's exactly what I was looking for! Thanks a lot.
Just two followup questions

1. if I connect a dict with task.connect and I edit it in the UI, will the new values be passed to the next run?
   2)with connect_configuration, can I pass a python file containing the configuration (like, a configuration-as-code file, instead of a yml or a json)? Could I modify it from UI?

I had no idea you could do this, that's amazing thanks a lot!
Although after reviewing the options, probably managing everything with Hydra is the better way :D

Yeah that sounds great, look forward to try it! Thanks a lot :)

I can imagine :D I'll look into it, thanks!

Cool thanks! So for online Feature transformation I would set up a feast server, and the tasks would use feast to create and retrieve features, right?

I know it's a huge project, but it would be great to have a feature store as part of ClearML, do you have any plans to do that?

@<1694157594333024256:profile|DisturbedParrot38> thanks a lot! I didn't know it. On my project, clearml can't recognize the requirements from the code, I have to pass them explicitly, either with poetry or with a requirements.txt. Does that work for you?

@<1523701070390366208:profile|CostlyOstrich36> It's 1.8.0