ent.active_user.id,  # ran by you

Resource ModelsThe methods of the ZenML Client all return Response Models, which are Pydantic Models that allow ZenML to validate that the returned data always has the correct attributes and types. E.g., the client.list_pipeline_runs method always returns type Page[PipelineRunResponseModel].

You can think of these models as similar to types in strictly-typed languages, or as the requirements of a single endpoint in an API. In particular, they are not related to machine learning models like decision trees, neural networks, etc.

ZenML also has similar models that define which information is required to create, update, or search resources, named Request Models, Update Models, and Filter Models respectively. However, these models are only used for the server API endpoints, and not for the Client methods.

To find out which fields a specific resource model contains, checkout the ZenML Models SDK Documentation and expand the source code to see a list of all fields of the respective model. Note that all resources have Base Models that define fields that response, request, update, and filter models have in common, so you need to take a look at the base model source code as well.

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Last updated 15 days ago