oh, I found it 🙂
cd /opt/clearml sudo docker-compose restart apiserver

CostlyOstrich36 thank you 🙂 I suppose the issues isn’t necessary if someone is already working on a fix?

thank you so much SweetBadger76

is https://clear.ml/docs/latest/docs/faq/#clearml-api the only place to see how to use the backend_api?

so, yes each user has its own credentials

Here it is https://github.com/allegroai/clearml/issues/671 🙂

yes

just to clarify, you mean clearml api credentials (not the aws ones)?

SuccessfulKoala55 this is what I see on the Profile page:
WebApp: 1.3.1-169 • Server: 1.3.1-169 • API: 2.17

I’d like to programmatically (e.g. jupyter notebook) retrieve files/info related to a task from the server

some actions can be done using clearml.Task , for instance get a local copy of a model, pull down the scalars etc.

give it few seconds an should work. That’s what I’ve experienced 🙂

storage { cache { # Defaults to system temp folder / cache default_base_dir: "/scratch/clearml-cache" }this is it. I’ve only changed this bit

CostlyOstrich36 any updates on this?

how do I restart just the apiserver? If I’m not wrong this command
sudo docker-compose -f /opt/clearml/docker-compose.yml downwill stop all the services

thanks CostlyOstrich36

cc. SuccessfulKoala55

Is there a vital reason why you want to keep the two accounts separate when they run on the same machine?

I’ve already implicitly answered this, but to be more precise, having multiple users allows to know who ran the experiment 🙂

FYI: I’ve added a possible fix to the issue https://github.com/allegroai/clearml/issues/671#issuecomment-1146640498

upgraded to 1.3.2

Hey UnevenDolphin73 I'm also interested in this feature. Currently trying it out

ops. 1.1.6

yes, I’m following these instructions https://clear.ml/docs/latest/docs/deploying_clearml/clearml_server_config#web-login-authentication

I was on 1.2.0
Upgrading to 1.3.0 resolved the issue with S3 credentials request 🙂
thank you

Hey CostlyOstrich36 thank you 🙂 I haven’t yet started using the agent to run a task. I’m in the phase of tracking the experiments. The setup that I have is that there’s an yml conda env file (generated via conda env export ) that includes conda and pip packages. I’d like to log the content of that file in ClearML. I’ve tried to use force_requirements_env_freeze but it doesn’t do what I’d hope for. Any suggestion?

maybe I need to call this: https://clear.ml/docs/latest/docs/references/sdk/logger#set_default_upload_destination

Your suggestion CostlyOstrich36 works: I’ve added the line in the clearml.conf file.

However, now when I go in the Results -> Debug Samples tab, the s3 credential window pops up. Every time that I refresh the page 😞

that works 🙂

getting the same behaviour

I’ll put together some more info and raise an issue