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Comments (3)

andrewferlitsch avatar andrewferlitsch commented on May 16, 2024

This does appear to be a limitation the prebuilt components. You could then write your own python component, something like:

@component()
def get_endpoint(resource_name: str,
endpoint: Output[Artifact]
)
endpoint = aiplatform.Endpoint(endpoint_name=resource_name)

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MMichael-S avatar MMichael-S commented on May 16, 2024

@andrewferlitsch
Thank you very much.
We have done in the same way by using customized components to import the existed endpoint.

Code as following, for someone who need the reference:

from google_cloud_pipeline_components.types import artifact_types
from kfp.v2.components import importer_node


endpoint = importer_node.importer(
    artifact_uri="https://us-central1-aiplatform.googleapis.com/v1/projects/xxxxxxxx/locations/us-central1/endpoints/xxxxxx",
    artifact_class=artifact_types.VertexEndpoint,
    metadata={
        "resourceName": "projects/xxxx/locations/us-central1/endpoints/xxxxx"
    }
)
...
ModelDeployOp(
        model=training_run_task.outputs["model"],
        endpoint=endpoint.outputs['artifact'],
        automatic_resources_min_replica_count=1,
        automatic_resources_max_replica_count=1,
    )

from vertex-ai-samples.

andrewferlitsch avatar andrewferlitsch commented on May 16, 2024

Thanks @MMichael-S for posting example using the importer_node method

from vertex-ai-samples.

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