Thanks for the background. I now have a big picture of the process ClearML goes through. It was helpful in clarifying some of the questions that I didn't know how to ask properly. So, the idea is that a base task is already stored on the ClearML server for later use in a production environment. This is because such a task will always be created during the model development process.

Going back to my initial question, as far as I understood, if the environment caching option is enabled, the clearml-agent will not only not reinstall all the packages of an environment shared by all the tasks of the same pipeline, but it will also be able to re-use an identical environment that has already been used for other tasks stored on the server.

So, the only remaining part of my question is if there is a way for Task.init to automatically detect the imported packages in a custom module ( helpers.py in this case), which contains functions and classes that I need to use in the script where I put Task.init , and for them to work the agent must install the packages imported in this custom module.