Registered Model

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RegisteredModel object

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.

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The RegisteredModel object

{
  "name": "string",
  "creation_timestamp": 0,
  "last_updated_timestamp": 0,
  "user_id": "string",
  "description": "string",
  "latest_versions": [
    {
      "name": "string",
      "version": "string",
      "creation_timestamp": 0,
      "last_updated_timestamp": 0,
      "user_id": "string",
      "current_stage": "string",
      "description": "string",
      "source": "string",
      "run_id": "string",
      "status": "PENDING_REGISTRATION",
      "status_message": "string",
      "tags": [
        {}
      ],
      "run_link": "string"
    }
  ],
  "tags": [
    {
      "key": "string",
      "value": "string"
    }
  ]
}

Get model 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

namestringRequiredquery: Registered model unique name identifier.

Response

registered_model_databricksobject

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

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

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

latest_versionsarray of object

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

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

idstringuuid: 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.

Show child attributesHide child attributes

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": "CAN_MANAGE",
    "tags": [
      {}
    ]
  }
}

List models GA

GET /api/2.0/mlflow/registered-models/list

Lists all available registered models, up to the limit specified in max_results.

API scopes: mlflow

Parameters

max_resultsint64<= 1000query: Maximum number of registered models desired. Max threshold is 1000.
Default: 100

page_tokenstringquery: Pagination token to go to the next page based on a previous query.

Response

Returns a list of RegisteredModel objects.

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Response

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

Create a model 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

namestringRequired: Register models under this name

tagsarray of object

Additional metadata for registered model.

Show child attributesHide child attributes

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.

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.

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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 model GA

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

Updates a registered model.

API scopes: mlflow

Request body

namestringRequired: 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.

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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 a model GA

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

Deletes a registered model.

API scopes: mlflow

Parameters

namestringRequiredquery: Registered model unique name identifier.

Rename a model GA

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

Renames a registered model.

API scopes: mlflow

Request body

namestringRequired: Registered model unique name identifier.

new_namestring: If provided, updates the name 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.

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Request

{
  "name": "string",
  "new_name": "string"
}

Response

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

Search models GA

GET /api/2.0/mlflow/registered-models/search

Search for registered models based on the specified filter.

API scopes: mlflow

Parameters

filterstringquery: String filter condition, like "name LIKE 'my-model-name'". Interpreted in the backend automatically as "name LIKE '%my-model-name%'". Single boolean condition, with string values wrapped in single quotes.

max_resultsint64<= 1000query: Maximum number of models desired. Default is 100. Max threshold is 1000.
Default: 100

order_byarray of stringquery: List of columns for ordering search results, which can include model name and last updated timestamp with an optional "DESC" or "ASC" annotation, where "ASC" is the default. Tiebreaks are done by model name ASC.

page_tokenstringquery: Pagination token to go to the next page based on a previous search query.

Response

Returns a list of RegisteredModel objects.

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Response

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

Get the latest version GA

POST /api/2.0/mlflow/registered-models/get-latest-versions

Gets the latest version of a registered model.

API scopes: mlflow

Request body

namestringRequired: Registered model unique name identifier.

stagesarray of string: List of stages.

Response

model_versionsarray of object

Latest version models for each requests stage. Only return models with current READY status. If no stages provided, returns the latest version for each stage, including "None".

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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

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Request

{
  "name": "string",
  "stages": [
    "string"
  ]
}

Response

{
  "model_versions": [
    {
      "name": "string",
      "version": "string",
      "creation_timestamp": 0,
      "last_updated_timestamp": 0,
      "user_id": "string",
      "current_stage": "string",
      "description": "string",
      "source": "string",
      "run_id": "string",
      "status": "PENDING_REGISTRATION",
      "status_message": "string",
      "tags": [
        {}
      ],
      "run_link": "string"
    }
  ]
}

Set a tag GA

POST /api/2.0/mlflow/registered-models/set-tag

Sets a tag on a registered model.

API scopes: mlflow

Request body

namestringRequired: Unique name of the model.

keystringRequired: Name of the tag. Maximum size depends on storage backend. If a tag with this name already exists, its preexisting value will be replaced by the specified value. All storage backends are guaranteed to support key values up to 250 bytes in size.

valuestringRequired: String value of the tag being logged. Maximum size depends on storage backend. All storage backends are guaranteed to support key values up to 5000 bytes in size.

Delete a model tag GA

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

Deletes the tag for a registered model.

API scopes: mlflow

Parameters

namestringRequiredquery: Name of the registered model that the tag was logged under.

keystringRequiredquery: Name of the tag. The name must be an exact match; wild-card deletion is not supported. Maximum size is 250 bytes.