No sorry maybe I wasn't clear, let me clarify
Suppose I have setup a Tranis server and a Trains agent (which uses docker to enforce reproducibility)

Consider I have a script script.py
` from trains import Task
import numpy as np

task = Task.init(project_name="my project", task_name="my task")
task.execute_remotely()

print(np.any_fuction(...)) UserA has a python environment with numpy==1.16 and launches script through python script.py UserB has a python environment with numpy==1.19 and launches script through python script.py `

If I understood correctly the script.py will be run on the remote train agent (in a docker container)
after having installed numpy==1.16 in the first case or numpy==1.19 in the second case. Is it correct?

What I think is worth is to have the chance to fix the requirements of a project (for example through a requirements.txt )
and then ensure that when python script.py is executed in that Trains agent, only requirements.txt will be used
(the reason is simply that I'd like to setup an MLOps system where the ouput of the experiments does not depend upon the local environment used to run the experiments, as is the case for script.py )