@<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

@PipelineDecorator.component(cache=True, task_type=TaskTypes.data_processing)
def project_pipeline(config_path: str):
    """
    Pipeline steps

    Args:
        config_path (str): Path to config file
    """

    from clearml_pipeline.modeling_utils import generate_predictions
    from loguru import logger

    try:
        results = generate_predictions(config_path)

    except Exception as e:
        logger.error(f"{e}")


@PipelineDecorator.pipeline(
    name="pipeline", project="project_name", version="0.0.1"
)
def executing_pipeline(config_path: str):
    """Decorator for executing the pipeline"""

    project_pipeline(config_path)


if __name__ == "__main__":

    PipelineDecorator.run_locally()

    executing_pipeline("clearml_pipeline/config/ml_config.yaml")