I found this issue but not sure if it's the same thing as it's from awhile back: None and also not sure what the final solution here was.

I've figured out that this is because I have a config.yaml file with secrets in it in the repository. This is not committed to git. So, when running remotely, the file is no present. Is the recommendation to put this in the docker image and then I have to specify an entry point in the dockerfile? Previously, I was hoping to just get away with creating a docker image with the installed packages for the agent, not with the repository code as well. Is this not the recommended approach?

I'm just installing the required packages (one of which is an internal package on CodeArtifact).

Also, we use Dagster for orchestration.

Run is still marked as "Completed"

It says N/A for Status?

@<1523701070390366208:profile|CostlyOstrich36> here is the INFO section:

I found this issue but not sure if it's the same thing as it's from awhile back: None And the link I'm trying to clone doesn't start with https but with git@bitbucket

I just cleared the cache, but still getting the error:

Python executable with version '3.10' requested by the Task, not found in path, using '/usr/local/bin/python3' (v3.9.9) instead
created virtual environment CPython3.9.9.final.0-64 in 661ms
  creator CPython3Posix(dest=/root/.clearml/venvs-builds/3.9, clear=False, no_vcs_ignore=False, global=True)
  seeder FromAppData(download=False, pip=bundle, setuptools=bundle, wheel=bundle, via=copy, app_data_dir=/root/.local/share/virtualenv)
 ...

Yes, it does. And I can clone this repo and branch to the server outside of clearml just using git clone .... as I've added ssh keys and authenticated.

Ah, ok thanks so much, I'll work on this now.

@<1523701070390366208:profile|CostlyOstrich36> , a quick follow up, I've been looking at the ClearML API documentation to see how to trigger a pipeline via the API. Do you use queues and add_task , as specified here: None ?

Here is an example of the pipeline code, simplified:

"""Forecasting Pipeline"""

from clearml.automation.controller import PipelineDecorator
from clearml import TaskTypes

@Pipe...

Sorry, was trying to figure out how to do this. So, looks like I can't as get an error NameError: name 'ssh' is not defined

Hi @<1523701070390366208:profile|CostlyOstrich36> , another quick question, can you run a pipeline on a schedule or are schedules only for Tasks? We are battling to figure out how to automate the pipelines.

@<1523701205467926528:profile|AgitatedDove14> Hi! Could you give any feedback on the above? We are trying to figure out if/how we can run pipelines on a schedule and also trigger them with an external event.

Hi @<1523701070390366208:profile|CostlyOstrich36> , I've gotten past the environment set up phase - I have the agent running in --services-mode for the pipeline, but the pipeline step is failing and I can't see why from the error message. When I run this locally it works (ie. if I add PipelineDecorator.run_locally() ).

Environment setup completed successfully

Starting Task Execution:


1710160150496 direct-relief:cpu:0:service:5062dce7ff1d49cfbaf36c96abe3282c DEBUG ClearML res...

Hi there, I am getting this exact same error. I have set force_git_ssh_protocol: true and have commented out the git_user and git_pass , but still getting the error. Is the only way to fix this to clear the cache? Do you have to do this every time then?

Here is a sample from the end of the logs where it failed:

/home/megan/code/direct-relief-forecasting/forecast.py:277: FutureWarning:
The behavior of DatetimeProperties.to_pydatetime is deprecated, in a future version this will return a Series containing python datetime objects instead of an ndarray. To retain the old behavior, call `np.array` on the result
2024-07-04 12:14:04.589 | INFO     | forecast:infer:281 - Inferring for dates: ['2024-06-13']
2024-07-04 12:14:04.734 | INFO     |...

Ok, thanks! Going to try this now. I included an entry point from reading some other messages on Slack here when trying to figure out how to use Docker for running remotely.

Yes, I have a log in for the clearml server and I've set up an agent using a docker image. And I've added the ssh keys here. I then start the agent with clearml-agent daemon --queue direct-relief-forecasting --cpu-only -d But, then when I try run the pipeline remotely, I'm getting the error above.

Ah ok, so if I have two steps, this means 3 queues with 3 agents, one for the controller and one each dedicated to the steps, just to confirm?

I have an agent running and assigned to the queue megan-testing :

Thanks, I'll have a look at the youtube videos. I've been going over the documentation a lot and haven't found much about actually running and deploying pipelines, and a lot of details seem to be missing.

This is schedule.py where the schedule_task_id is the id for a pipeline that has previously been run and now we want to schedule it:

from clearml import Task
from clearml.automation import TaskScheduler

if __name__ == "__main__":

    scheduler = TaskScheduler(force_create_task_name='megan-test-remote-pipeline')

    scheduler.add_task(
        name='Simple Pipeline Schedule Run Test',
        schedule_task_id='94a7e898bb3f4494a31828187710f5bd',
        queue='megan_testing',
...

/usr/lib/python3/dist-packages/requests/__init__.py:89: RequestsDependencyWarning: urllib3 (1.25.8) or chardet (5.1.0) doesn't match a supported version!
  warnings.warn("urllib3 ({}) or chardet ({}) doesn't match a supported "
Current configuration (clearml_agent v1.7.0, location: /tmp/.clearml_agent.r_86l8jq.cfg):
----------------------
agent.worker_id = megan-vm
agent.worker_name = vm
agent.force_git_ssh_protocol = true
agent.python_binary = 
agent.package_manager.type = poetry
agent...

Error when executing schedule with a pipeline task ID defined:

Launching job: ScheduleJob(name='Simple Pipeline Schedule Run Test', base_task_id='4cf5b603e3ae4593a8c2dd6c34190c6d', base_function=None, queue='megan_testing', target_project=None, single_instance=False, task_parameters={}, task_overrides={}, clone_task=True, _executed_instances=None, execution_limit_hours=None, recurring=True, starting_time=datetime.datetime(1970, 1, 1, 0, 0), minute=2, hour=None, day=None, weekdays=['mon...

Schedule testing code:

# Schedule for running the pipeline daily

from clearml import Task
from clearml.automation import TaskScheduler


def simple_function():
    print('This code is executed in a background thread, '
          'on the same machine as the TaskScheduler process')
    # add some logic here
    print('done')

if __name__ == "__main__":

    scheduler = TaskScheduler(force_create_task_name='megan-test-remote-pipeline')

    scheduler.add_task(
        name='Simple Pipeli...

I am using the pipeline id of when I last ran the pipeline and got this through the UI in ClearML.

Thanks @<1523701070390366208:profile|CostlyOstrich36> , I've figured this out and specified how to build the ClearML agent now with the correct python version.

Hi @<1523701205467926528:profile|AgitatedDove14> , I'm still having issues with this set up. See my latest comment here: None

I created a new queue megan-testing and have an agent running on my machine that I assigned to it. It works when I just use a simple task and schedule it, but when I try run the pipeline, it says it can't find the queue.