Enhance your machine learning workflows by integrating Argilla, an open-source data curation platform, with ZenML. This integration enables efficient data annotation within ZenML pipelines, leveraging Argilla's human-in-the-loop approach for improved data quality and model performance.
# register an annotator authentication secret first
# zenml secret create argilla_secrets --api_key="<your_argilla_api_key>"
# then register the annotator itself
# zenml annotator register argilla --flavor argilla --authentication_secret=argilla_secrets
from zenml.client import Client
client = Client()
annotator = client.active_stack.annotator
# list dataset names
dataset_names = annotator.get_dataset_names()
# get a specific dataset
dataset = annotator.get_dataset("dataset_name")
# get the annotations for a dataset
annotations = annotator.get_labeled_data(dataset_name="dataset_name")
# launch the annotation interface via the CLI
# zenml annotator dataset annotate <dataset_name>
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