Great! setting the default_output_uri worked!
Thank you.

Thanks for the reply CostlyOstrich36
The local machine & agent machine has the same clearml.conf . As I sad, storing something via StorageManager has no problem on both side.
But PipelineDecorator.upload_model(model_name, model_path) doesn't work on both side.

Self-answering after digging into it.
from os import environ environ['CLEARML_WEB_HOST'] = ' ' environ['CLEARML_API_HOST'] = ' ' environ['CLEARML_FILES_HOST'] = ' ` '
environ['CLEARML_API_ACCESS_KEY'] = 'access_key'
environ['CLEARML_API_SECRET_KEY'] = 'secret_key'

from clearml import Task `

Thanks for the reply. Yes, I got the point.
Still, My problem is calling pipe.start() crashes.
I want to run an API server that starts the pipeline on request, and I don't want it kills the API server.

Ah! sorry I just found the doc 😉
https://clear.ml/docs/latest/docs/pipelines/pipelines_sdk_function_decorators#running-the-pipeline

Good day AgitatedDove14

just one more question AgitatedDove14 .
How can I do the same thing to pipe.start_locally(run_pipeline_steps_locally=False) with decorators?

Thank you. AgitatedDove14 auto_connect_frameworks worked nicely.

Oh. If the behavior is intentional, I think I must call it via subprocess.
Thanks for the answers. AgitatedDove14