It will always set it's own environment, wither with static analysis or with "pip freeze" / "conda freeze"
It needs to log the exact setup that was actually installed.
When you later launch it on a remote machine, it can either use this to recreate the environment (using pip or conda), or you can clear the entire section, where it will fall back to "requirements.txt"
Any reason for specifically using the "environment.yaml" ?

Thank you, I set it, but clearml still creates its own evironment regardless of my environment.yaml.

So I guess I am referring to the auto package detection. I am running the job though the web ui. My actual problem is that I have a private repo on my requirements.txt (listed with the github url) that is not being installed. Also, my environment.yaml uses python 3.8, while 3.9 is being installed.

The only reason is that I can specify the python version to be used and conda will install it. On requirements.txt, the default python version will be used.

Hi SkinnyPanda43
Do you mean the cleaml-agent or the cleaml python (a.k.a the auto package detection) ?

Try to set this line in your clearml.conf to true:
https://github.com/allegroai/clearml/blob/6e6271fb91f2aeb2aa7a13c6d07d4e635baaa670/docs/clearml.conf#L177

Notice this is only when:
Using Conda as package manager in the agent the requested python version is already installed (multiple python version installation on the same machine/container are supported)

python version to be used and conda will install it

clearml does that automatically (albeit it is not shown in the UI, which should be fixed)