Model

Get GA

GET /api/2.0/mlflow/databricks/registered-models/get

Get the details of a model. This is a <Databricks> workspace version of the MLflow endpoint that also returns the model's <Databricks> workspace ID and the permission level of the requesting user on the model.

API scopes: mlflow

Parameters

namestringquery: Registered model unique name identifier.

Response

registered_model_databricksobject

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namestring: Name of the model.
Example: search_ads_model
Constraints: [ 1 .. 100 ] characters

creation_timestampint64: Creation time of the object, as a Unix timestamp in milliseconds.
Example: 1594437249910

last_updated_timestampint64: Last update time of the object, as a Unix timestamp in milliseconds.
Example: 1594437549910

user_idstring: The username of the user that created the object.
Example: jane.doe@example.com

descriptionstring: User-specified description for the object.
Example: Here's some extra info.
Constraints: <= 65535 characters

latest_versionsarray of object

Array of model versions, each the latest version for its stage.

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namestring: Unique name of the model

versionstring: Model's version number.

creation_timestampint64: Timestamp recorded when this model_version was created.

last_updated_timestampint64: Timestamp recorded when metadata for this model_version was last updated.

user_idstring: User that created this model_version.

current_stagestring: Current stage for this model_version.

descriptionstring: Description of this model_version.

sourcestring: URI indicating the location of the source model artifacts, used when creating model_version

run_idstring: MLflow run ID used when creating model_version, if source was generated by an experiment run stored in MLflow tracking server.

statusstring: Current status of model_version
Values: PENDING_REGISTRATION, FAILED_REGISTRATION, READY

status_messagestring: Details on current status, if it is pending or failed.

tagsarray of object

Tags: Additional metadata key-value pairs for this model_version.

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keystring: The tag key.

valuestring: The tag value.

run_linkstring: Run Link: Direct link to the run that generated this version

idstring: Unique identifier for the object.
Example: 6fc74c92704341aaa49e74dcc6031057

permission_levelstring: Permission level granted for the requesting user on this registered model
Values: CAN_MANAGE, CAN_EDIT, CAN_READ, CAN_MANAGE_STAGING_VERSIONS, CAN_MANAGE_PRODUCTION_VERSIONS, CAN_CREATE_REGISTERED_MODEL

tagsarray of object

Array of tags associated with the model.

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keystring: The tag key.

valuestring: The tag value.

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Response

{
  "registered_model_databricks": {
    "name": "search_ads_model",
    "creation_timestamp": 1594437249910,
    "last_updated_timestamp": 1594437549910,
    "user_id": "jane.doe@example.com",
    "description": "Here's some extra info.",
    "latest_versions": [
      {}
    ],
    "id": "6fc74c92704341aaa49e74dcc6031057",
    "permission_level": "string",
    "tags": [
      {}
    ]
  }
}

Create GA

POST /api/2.0/mlflow/registered-models/create

Creates a new registered model with the name specified in the request body. Throws RESOURCE_ALREADY_EXISTS if a registered model with the given name exists.

API scopes: mlflow

Request body

namestring: Register models under this name

tagsarray of object

Additional metadata for registered model.

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keystring: The tag key.

valuestring: The tag value.

descriptionstring: Optional description for registered model.

Response

registered_modelobject

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namestring: Unique name for the model.

creation_timestampint64: Timestamp recorded when this registered_model was created.

last_updated_timestampint64: Timestamp recorded when metadata for this registered_model was last updated.

user_idstring: User that created this registered_model

descriptionstring: Description of this registered_model.

latest_versionsarray of object

Collection of latest model versions for each stage. Only contains models with current READY status.

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namestring: Unique name of the model

versionstring: Model's version number.

creation_timestampint64: Timestamp recorded when this model_version was created.

last_updated_timestampint64: Timestamp recorded when metadata for this model_version was last updated.

user_idstring: User that created this model_version.

current_stagestring: Current stage for this model_version.

descriptionstring: Description of this model_version.

sourcestring: URI indicating the location of the source model artifacts, used when creating model_version

run_idstring: MLflow run ID used when creating model_version, if source was generated by an experiment run stored in MLflow tracking server.

statusstring: Current status of model_version
Values: PENDING_REGISTRATION, FAILED_REGISTRATION, READY

status_messagestring: Details on current status, if it is pending or failed.

tagsarray of object

Tags: Additional metadata key-value pairs for this model_version.

Show child attributesHide child attributes

keystring: The tag key.

valuestring: The tag value.

run_linkstring: Run Link: Direct link to the run that generated this version

tagsarray of object

Tags: Additional metadata key-value pairs for this registered_model.

Show child attributesHide child attributes

keystring: The tag key.

valuestring: The tag value.

View as Markdown

Request

{
  "name": "string",
  "tags": [
    {
      "key": "string",
      "value": "string"
    }
  ],
  "description": "string"
}

Response

{
  "registered_model": {
    "name": "string",
    "creation_timestamp": 0,
    "last_updated_timestamp": 0,
    "user_id": "string",
    "description": "string",
    "latest_versions": [
      {}
    ],
    "tags": [
      {}
    ]
  }
}

Update GA

PATCH /api/2.0/mlflow/registered-models/update

Updates a registered model.

API scopes: mlflow

Request body

namestring: Registered model unique name identifier.

descriptionstring: If provided, updates the description for this registered_model.

Response

registered_modelobject

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namestring: Unique name for the model.

creation_timestampint64: Timestamp recorded when this registered_model was created.

last_updated_timestampint64: Timestamp recorded when metadata for this registered_model was last updated.

user_idstring: User that created this registered_model

descriptionstring: Description of this registered_model.

latest_versionsarray of object

Collection of latest model versions for each stage. Only contains models with current READY status.

Show child attributesHide child attributes

namestring: Unique name of the model

versionstring: Model's version number.

creation_timestampint64: Timestamp recorded when this model_version was created.

last_updated_timestampint64: Timestamp recorded when metadata for this model_version was last updated.

user_idstring: User that created this model_version.

current_stagestring: Current stage for this model_version.

descriptionstring: Description of this model_version.

sourcestring: URI indicating the location of the source model artifacts, used when creating model_version

run_idstring: MLflow run ID used when creating model_version, if source was generated by an experiment run stored in MLflow tracking server.

statusstring: Current status of model_version
Values: PENDING_REGISTRATION, FAILED_REGISTRATION, READY

status_messagestring: Details on current status, if it is pending or failed.

tagsarray of object

Tags: Additional metadata key-value pairs for this model_version.

Show child attributesHide child attributes

keystring: The tag key.

valuestring: The tag value.

run_linkstring: Run Link: Direct link to the run that generated this version

tagsarray of object

Tags: Additional metadata key-value pairs for this registered_model.

Show child attributesHide child attributes

keystring: The tag key.

valuestring: The tag value.

View as Markdown

Request

{
  "name": "string",
  "description": "string"
}

Response

{
  "registered_model": {
    "name": "string",
    "creation_timestamp": 0,
    "last_updated_timestamp": 0,
    "user_id": "string",
    "description": "string",
    "latest_versions": [
      {}
    ],
    "tags": [
      {}
    ]
  }
}

Delete GA

DELETE /api/2.0/mlflow/registered-models/delete

Deletes a registered model.

API scopes: mlflow

Parameters

namestringquery: Registered model unique name identifier.

Get GA​

Parameters​

Response​

Create GA​

Request body​

Response​

Update GA​

Request body​

Response​

Delete GA​

Parameters​

Get GA

Parameters

Response

Create GA

Request body

Response

Update GA

Request body

Response

Delete GA

Parameters