Hi JitteryCoyote63 ,
The easiest would probably be to list the experiment folder, and delete its content.
I might be missing a few things but the general gist should be:
from trains.storage import StorageHelper h = StorageHelper('s3://my_bucket') files = h.list(prefix='s3://my_bucket/task_project/task_name.task_id') for f in files: h.delete(f)Obviously you should have the right credentials 🙂

Hi JitteryCoyote63

You don’t need to run in from the Trains Server machine, you just need ~/trains.conf file with configuration to your Trains Server

Thanks TimelyPenguin76 and AgitatedDove14 ! I would like to delete artifacts/models related to the old archived experiments, but they are stored on s3. Would that be possible?

Hi JitteryCoyote63

cleanup_service task in the DevOps project: Does it assume that the agent in services mode is in the trains-server machine?

It assumes you have an agent connected to the "services" queue 🙂
That said, it also tries to delete the tasks artifacts/models etc, you can see it here:
https://github.com/allegroai/trains/blob/c234837ce2f0f815d3251cde7917ab733b79d223/examples/services/cleanup/cleanup_service.py#L89
The default configuration will assume you are running it on the trains-server, since by default this is where you have your files-server