the current my solution is upload my config to s3, and the pipeline will download it and read it when execute. but its decrase flexiblity.

Thanks! i just prove it can run in next day, but not for the same day. i hope can run in same day too.

Syncing scheduler
Waiting for next run, sleeping for 5.13 minutes, until next sync.
Launching job: ScheduleJob(name='fetch feedback', base_task_id='', base_function=<function test_make at 0x7f91fd123d90>, queue=None, target_project='Automation/testing', single_instance=False, task_parameters={}, task_overrides={}, clone_task=True, _executed_instances=None, execution_limit_hours=None, r...

hi @<1523701070390366208:profile|CostlyOstrich36> , i mean uv this None

Hi @<1523701070390366208:profile|CostlyOstrich36>
i mean we can do a form dropdown for others configuration like hyperparameters (task.connect)

i see, it solved right now using default_output_uri, Thanks!
i need custom output_uri for some function because split dataset and model artifacs.

Hi @<1523701070390366208:profile|CostlyOstrich36> , i think can try this to run it as standalone:

wow, okay, i think will move all logs/plot/artifacs to my storage s3. Thanks! really helpful!

Hi @<1523701994743664640:profile|AppetizingMouse58> , i have update on #228. Thanks!

remove this params will solve use_current_task=True,

Hi @<1523701205467926528:profile|AgitatedDove14> , Thanks for rresponse!
this my simple code to test scheduler

import datetime
from clearml.automation import TaskScheduler
  
def test_make():
    print('test running', datetime.datetime.now())

if __name__ == '__main__':
    task_scheduler = TaskScheduler(
        sync_frequency_minutes=30,
        force_create_task_name='controller_feedback',
        force_create_task_project='Automation/Controller',
    )

    print('\n[utc_timestamp]...

maybe accidently install my custom solution on this https://github.com/muhammadAgfian96/clearml/commit/01db9aa40537a6c2f83977220423556a48614c3a at that time. so i said the test is passed.

it seems your clearml-agent didn't setup the right git account. are you sure setup on your agent conf?

wow, so cool!
Thanks, really great tools!

my case more like there is a task/process that running but somehow its takes too long to completed. it can be because connection issue forgot to put connection timeout, a problem connection database, etc that makes status still running, but its traped in a situation like that.

so i want to force shutdown a task to failed if that happen

Hi @<1523701087100473344:profile|SuccessfulKoala55> , Thanks for your response.

I'm not entirely sure about the use of CLEARML_ENV since I haven't interacted with it before. Could you guide me on what I should set as its value?

Previously, the system was running smoothly. However, I've run into some issues after making certain configuration changes to modify the server permissions. Specifically, I'm curious if these changes might have influenced the agent's permission to access certain...

Hi SmugDolphin23 , i have try 1.8.4rc1, and yeah its working! Thanks!

i want to download model before i run the my inference code. i can actually make simple script using cleaml-sdk before that, but i just look for CLI based solution.

oh okay, so i need to set that to path ssd, yeah?
is it this one? or there is

    docker_internal_mounts {
        sdk_cache: "/clearml_agent_cache"
        apt_cache: "path/to/ssd/apt-cache"
        ssh_folder: "/root/.ssh"
        pip_cache: "path/to/ssd/clearml-cache/pip"
        poetry_cache: "/mnt/hdd_2/clearml-cache/pypoetry"
        vcs_cache: "path/to/ssd/clearml-cache/vcs-cache"
        venv_build: "path/to/ssd/clearml-cache/venvs-builds"
        pip_download: "path/to/ssd/cle...

alright, will try thanks!

Hi @<1523701070390366208:profile|CostlyOstrich36>
i attach for complete log

here my structure:

.
├── app
│   ├── backend
│   └── frontend
├── assets
│   ├── demo-app-sample.png
│   └── workflow.png
├── config
│   ├── clearml.conf
│   ├── list_models.py
│   ├── list_optimizer.py
│   ├── __pycache__
│   └── train_config.py
├── docker
│   ├── Dockerfile
│   ├── Dockerfile.app
│   ├── requirements.prod.txt
│   ├── requirements.train.txt
│   └── requirements.txt
├── lightning_logs
├── Mak...

its auto to fileserver instance

do you mean i can change?

files_server: 

 -> 

i set like this: for init Task Scheduler

    task_scheduler = TaskScheduler(
        sync_frequency_minutes=5,
        force_create_task_name='controller_feedback',
        force_create_task_project='Automation/Controller',

    )

Hi, CostlyOstrich36 , Sure!