the output above is what the agent has as it seems... obviously on my machine I have it installed

I never installed trains on this environment

I don't even know where trains is coming from... While using the same environment I can't even import trains, see

no this is from the task execution that failed

Nope, quite some time has passed since 🙂 I might be able to replicate it later... still battling with the pipeline to make it work

That is not very informative

Why is that an issue?

AgitatedDove14
So I couldn't kill the service agent myself (permission denied, I'm not sudo). What I did is I docker-compose down ed, commented out only the environment variable of GOOGLE_APPLICATION_CREDENTIALS from the clearml services agent service and upped the docker-compose again. I enqueued the Cleanup Service and now it works. Really weird, looks like the setting of GOOGLE_APPLICATION_CREDENTIALS causes an error when set even though I'm 100% is it not used for storag...

and I run these command manually

Let's take a step back. Let's remove the clearml-services from the docker compose for a second, and run it manually (then you can control everything). Once you have it running manually, let's try to replicate the setup back to the docker compose, make sense ?

I'd prefer not to docker-compose down as researchers are actively working on it, what do you say that I will manually kill the services agent and launch one myself?

the path to the JSON file

to fix it, I excluded this var entirely from the docker-compose

Very nice thanks, I'm going to try the SA server + agents setup this week, let's see how it goes ✌

I can try do an ls to see what it will print out

but I don't really know

why not use my user and group?

what if i want it to use ssh creds?

Please update me 🙂

see gif:

I mean the code in whatever form it is - I'm working with git specifically, but if i have diffs I'd like to see the code with the diffs applied

eventually i think it should display the contents of the script executed in the most straightforward manner regardless of version control

Done

As a part of a repo

So the scale will also appear?

That's a fix, but I think it is a basic feature and very usefull to see the actual code in the UI

👍

Especially coming from the standpoint of a team leader or other kind of supervision (or anyone who wants to view the experiment which is not the code author), when looking at an experiment you want to see the actual code

I assume it has nothing to do with my client version

🤔 is the "installed packages" part editable? good to know

Isn't it a bit risky manually changing a package version? what if it won't be compatible with the rest?

I'm saying that because in the task under "INSTALLED PACKAGES" this is what appears

We try to break up every thing into independent tasks and group them using a pipeline. The dependency on an agnet caused an unnecessary overhead since we just want to execute locally. It became a burden once new data scientists join the project and instead of just telling them "yeah, just execute this script" you have to now teach them about clearml, the role of agents, how to launch them, how they behave, how to remove them and stuff like that... things you want to avoid with data scientists