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Get trained model API

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Get trained model API

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Retrieves configuration information for a trained model.

This functionality is in technical preview and may be changed or removed in a future release. Elastic will work to fix any issues, but features in technical preview are not subject to the support SLA of official GA features.

Request

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GET _ml/inference/

GET _ml/inference/<model_id>

GET _ml/inference/_all

GET _ml/inference/<model_id1>,<model_id2>

GET _ml/inference/<model_id_pattern*>

Prerequisites

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Required privileges which should be added to a custom role:

  • cluster: monitor_ml

For more information, see Security privileges and Machine learning security privileges.

Description

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You can get information for multiple trained models in a single API request by using a comma-separated list of model IDs or a wildcard expression.

Path parameters

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<model_id>
(Optional, string) The unique identifier of the trained model.

Query parameters

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allow_no_match

(Optional, Boolean) Specifies what to do when the request:

  • Contains wildcard expressions and there are no models that match.
  • Contains the _all string or no identifiers and there are no matches.
  • Contains wildcard expressions and there are only partial matches.

The default value is true, which returns an empty array when there are no matches and the subset of results when there are partial matches. If this parameter is false, the request returns a 404 status code when there are no matches or only partial matches.

decompress_definition
(Optional, Boolean) Specifies whether the included model definition should be returned as a JSON map (true) or in a custom compressed format (false). Defaults to true.
for_export
(Optional, Boolean) Indicates if certain fields should be removed from the model configuration on retrieval. This allows the model to be in an acceptable format to be retrieved and then added to another cluster. Default is false.
from
(Optional, integer) Skips the specified number of models. The default value is 0.
include_model_definition
(Optional, Boolean) Specifies whether the model definition is returned in the response. Defaults to false. When true, only a single model must match the ID patterns provided. Otherwise, a bad request is returned.
size
(Optional, integer) Specifies the maximum number of models to obtain. The default value is 100.
tags
(Optional, string) A comma delimited string of tags. A trained model can have many tags, or none. When supplied, only trained models that contain all the supplied tags are returned.

Response body

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trained_model_configs

(array) An array of trained model resources, which are sorted by the model_id value in ascending order.

Properties of trained model resources
created_by
(string) Information on the creator of the trained model.
create_time
(time units) The time when the trained model was created.
default_field_map

(object) A string to string object that contains the default field map to use when inferring against the model. For example, data frame analytics may train the model on a specific multi-field foo.keyword. The analytics job would then supply a default field map entry for "foo" : "foo.keyword".

Any field map described in the inference configuration takes precedence.

estimated_heap_memory_usage_bytes
(integer) The estimated heap usage in bytes to keep the trained model in memory.
estimated_operations
(integer) The estimated number of operations to use the trained model.
license_level
(string) The license level of the trained model.
metadata
(object) An object containing metadata about the trained model. For example, models created by data frame analytics contain analysis_config and input objects.
model_id
(string) Idetifier for the trained model.
tags
(string) A comma delimited string of tags. A trained model can have many tags, or none.
version
(string) The Elasticsearch version number in which the trained model was created.

Response codes

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400
If include_model_definition is true, this code indicates that more than one models match the ID pattern.
404 (Missing resources)
If allow_no_match is false, this code indicates that there are no resources that match the request or only partial matches for the request.

Examples

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The following example gets configuration information for all the trained models:

GET _ml/inference/
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