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Get inference trained model API

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Get inference trained model API

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Retrieves configuration information for a trained inference 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 Built-in roles.

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 inference 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 data frame analytics jobs 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 data_frame_analytics 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.

from

(Optional, integer) Skips the specified number of data frame analytics jobs. The default value is 0.

include_model_definition

(Optional, boolean) Specifies if the model definition should be 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 data frame analytics jobs to obtain. The default value is 100.

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.

model_id: (string) Idetifier for the trained model.
created_by: (string) Information on the creator of the trained model.
version: (string) The Elasticsearch version number in which the trained model was created.
create_time: (time units) The time when the trained model was created.
tags: (string) A comma delimited string of tags. A inference model can have many tags, or none.
metadata: (object) An object containing metadata about the trained model. For example, models created by data frame analytics contain an analysis_config and an input object.
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.

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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