API Reference

ModelRegistryClient

class kubeflow.hub.ModelRegistryClient(base_url: str, port: int | None = None, *, author: str | None = None, is_secure: bool | None = None, user_token: str | None = None, custom_ca: str | None = None)

Bases: object

Client for Kubeflow Model Registry operations.

Requires the model-registry package to be installed. Install it with:

pip install ‘kubeflow[hub]’

__init__(base_url: str, port: int | None = None, *, author: str | None = None, is_secure: bool | None = None, user_token: str | None = None, custom_ca: str | None = None)

Initialize the ModelRegistryClient.

Parameters:

base_url (str) – Base URL of the model registry server including scheme. Examples: “https://registry.example.com”, “http://localhost” The scheme is used to infer is_secure and port if not explicitly provided.

Keyword Arguments:

• port – Server port. If not provided, inferred from base_url scheme: - https:// defaults to 443 - http:// defaults to 8080 - no scheme defaults to 443

• author – Name of the author.

• is_secure – Whether to use a secure connection. If not provided, inferred from base_url: - https:// sets is_secure=True - http:// sets is_secure=False - no scheme defaults to True

• user_token – The PEM-encoded user token as a string.

• custom_ca – Path to the PEM-encoded root certificates as a string.

Raises:

ImportError – If model-registry is not installed.

Examples

ModelRegistryClient(”https://example.org”, port=456) # port kwarg ModelRegistryClient(”https://example.org:456”) # base_url (including port) ModelRegistryClient(”https://example.org”) # default port (443 for https, 8080 for http)

register_model(name: str, uri: str, *, version: str, model_format_name: str | None = None, model_format_version: str | None = None, author: str | None = None, owner: str | None = None, version_description: str | None = None, metadata: Mapping[str, bool | int | float | str] | None = None, storage_config: StorageConfig | None = None) → RegisteredModel

Register a model.

This registers a model in the model registry. The model is not downloaded, and has to be stored prior to registration.

Most models can be registered using their URI, along with an optional storage_config describing how KServe should fetch the model at inference time. URI builder utilities are recommended when referring to specialized storage; for example utils.s3_uri_from when using S3 object storage data connections.

Parameters:

• name (str) – Name of the model.

• uri (str) – URI of the model.

Keyword Arguments:

• version – Version of the model. Has to be unique.

• model_format_name – Name of the model format (e.g., “pytorch”, “tensorflow”, “onnx”). Used by KServe to select the appropriate serving runtime.

• model_format_version – Version of the model format (e.g., “2.0”, “1.15”).

• author – Author of the model. Defaults to the client author.

• owner – Owner of the model. Defaults to the client author.

• version_description – Description of the model version.

• metadata – Additional version metadata.

• storage_config – Storage credentials for the model artifact. Groups storage_key, storage_path, and service_account_name used by KServe’s StorageInitializer. See StorageConfig for details.

Returns:

Registered model.

update_model(model: RegisteredModel) → RegisteredModel

Update a registered model.

Parameters:

model (RegisteredModel) – The registered model to update. Must have an ID.

Returns:

Updated registered model.

Raises:

• TypeError – If model is not a RegisteredModel instance.

• model_registry.exceptions.StoreError – If model does not have an ID.

update_model_version(model_version: ModelVersion) → ModelVersion

Update a model version.

Parameters:

model_version (ModelVersion) – The model version to update. Must have an ID.

Returns:

Updated model version.

Raises:

• TypeError – If model_version is not a ModelVersion instance.

• model_registry.exceptions.StoreError – If model version does not have an ID.

update_model_artifact(model_artifact: ModelArtifact) → ModelArtifact

Update a model artifact.

Parameters:

model_artifact (ModelArtifact) – The model artifact to update. Must have an ID.

Returns:

Updated model artifact.

Raises:

• TypeError – If model_artifact is not a ModelArtifact instance.

• model_registry.exceptions.StoreError – If model artifact does not have an ID.

get_model(name: str) → RegisteredModel

Get a registered model.

Parameters:

name (str) – Name of the model.

Returns:

Registered model.

Raises:

ValueError – If the model does not exist.

get_model_version(name: str, version: str) → ModelVersion

Get a model version.

Parameters:

• name (str) – Name of the model.

• version (str) – Version of the model.

Returns:

Model version.

Raises:

• model_registry.exceptions.StoreError – If the model does not exist.

• ValueError – If the version does not exist.

get_model_artifact(name: str, version: str) → ModelArtifact

Get a model artifact.

Parameters:

• name (str) – Name of the model.

• version (str) – Version of the model.

Returns:

Model artifact.

Raises:

• model_registry.exceptions.StoreError – If either the model or the version don’t exist.

• ValueError – If the artifact does not exist.

list_models() → Iterator[RegisteredModel]

Get an iterator for registered models.

Yields:

Registered models.

list_model_versions(name: str) → Iterator[ModelVersion]

Get an iterator for model versions.

Parameters:

name (str) – Name of the model.

Yields:

Model versions.

Raises:

model_registry.exceptions.StoreError – If the model does not exist.

Types

The following types are returned by the client methods. They are provided by the model-registry package.

class model_registry.types.RegisteredModel(**data: Any) → None

Bases: BaseResourceModel

Represents a registered model.

name

Registered model name.

owner

Owner of this Registered Model.

description

Description of the object.

external_id

Customizable ID. Has to be unique among instances of the same type.

name: str

owner: str | None

state: RegisteredModelState

create(**kwargs) → RegisteredModelCreate

Convert the object to a create request.

update(**kwargs) → RegisteredModelUpdate

Convert the object to an update request.

classmethod from_basemodel(source: RegisteredModel) → RegisteredModel

Create a new object from a BaseModel object.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class model_registry.types.ModelVersion(**data: Any) → None

Bases: BaseResourceModel

Represents a model version.

name

Name of this version.

author

Author of this model version.

state

Status of this model version.

description

Description of this object.

external_id

Customizable ID. Has to be unique among instances of the same type.

artifacts

Artifacts associated with this version.

name: str

author: str | None

state: ModelVersionState

registered_model_id: str | None

create(*, registered_model_id: str, **kwargs) → ModelVersionCreate

Convert the object to a create request.

update(**kwargs) → ModelVersionUpdate

Convert the object to an update request.

classmethod from_basemodel(source: ModelVersion) → ModelVersion

Create a new object from a BaseModel object.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class model_registry.types.ModelArtifact(**data: Any) → None

Bases: Artifact

Represents a Model.

name

Name of the model.

uri

URI of the model.

description

Description of the object.

external_id

Customizable ID. Has to be unique among instances of the same type.

model_format_name

Name of the model format.

model_format_version

Version of the model format.

storage_key

Storage secret name.

storage_path

Storage path of the model.

service_account_name

Name of the service account with storage secret.

model_source_kind

A string identifier describing the source kind.

model_source_class

A subgroup within the source kind.

model_source_group

This identifies a source group for models from source class.

model_source_id

A unique identifier for a source model within kind, class, and group.

model_source_name

A human-readable name for the source model.

model_format_name: str | None

model_format_version: str | None

storage_key: str | None

storage_path: str | None

service_account_name: str | None

model_source_kind: str | None

model_source_class: str | None

model_source_group: str | None

model_source_id: str | None

model_source_name: str | None

uri: str | None

create(**kwargs) → ModelArtifactCreate

Create a new ModelArtifactCreate object.

update(**kwargs) → ModelArtifactUpdate

Create a new ModelArtifactUpdate object.

as_basemodel() → ModelArtifact

Wrap the object in a BaseModel object.

classmethod from_basemodel(source: ModelArtifact) → ModelArtifact

Create a new ModelArtifact object from a BaseModel object.

model_config: ClassVar[ConfigDict] = {'protected_namespaces': ()}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_post_init(context: Any, /) → None

This function is meant to behave like a BaseModel method to initialise private attributes.

It takes context as an argument since that’s what pydantic-core passes when calling it.

Parameters:

• self (BaseModel) – The BaseModel instance.

• context (Any) – The context.