Get trained models

GET /_cat/ml/trained_models/{model_id}
GET /_cat/ml/trained_models

Get configuration and usage information about inference trained models.

Important

CAT APIs are only intended for human consumption using the Kibana console or command line. They are not intended for use by applications. For application consumption, use the get trained models statistics API.

Required authorization

Authentication

Api key

Authorization: <value>

Elasticsearch APIs support key-based authentication. You must create an API key and use the encoded value in the request header. For example:

		curl -X GET "${ES_URL}/_cat/indices?v=true" \
  -H "Authorization: ApiKey ${API_KEY}"

To get API keys, use the /_security/api_key APIs.

Basic

Authorization: Basic <credentials>

Bearer

Authorization: Bearer <token>

Elasticsearch APIs support the use of bearer tokens in the Authorization HTTP header to authenticate with the API. For examples, refer to Token-based authentication services

Path parameters

Query parameters

allow_no_match boolean · default: true

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. If true, the API returns an empty array when there are no matches and the subset of results when there are partial matches. If false, the API returns a 404 status code when there are no matches or only partial matches.

h union oneOf

A comma-separated list of column names to display.

Supported values include:

create_time (or ct): The time when the trained model was created.
created_by (or c, createdBy): Information on the creator of the trained model.
data_frame_analytics_id (or df, dataFrameAnalytics, dfid): Identifier for the data frame analytics job that created the model. Only displayed if it is still available.
description (or d): The description of the trained model.
heap_size (or hs, modelHeapSize): The estimated heap size to keep the trained model in memory.
id: Identifier for the trained model.
ingest.count (or ic, ingestCount): The total number of documents that are processed by the model.
ingest.current (or icurr, ingestCurrent): The total number of document that are currently being handled by the trained model.
ingest.failed (or if, ingestFailed): The total number of failed ingest attempts with the trained model.
ingest.pipelines (or ip, ingestPipelines): The total number of ingest pipelines that are referencing the trained model.
ingest.time (or it, ingestTime): The total time that is spent processing documents with the trained model.
license (or l): The license level of the trained model.
operations (or o, modelOperations): The estimated number of operations to use the trained model. This number helps measuring the computational complexity of the model.
version (or v): The Elasticsearch version number in which the trained model was created.

One of: string[] or string

s union oneOf

A comma-separated list of column names or aliases used to sort the response.

Supported values include:

create_time (or ct): The time when the trained model was created.
created_by (or c, createdBy): Information on the creator of the trained model.
data_frame_analytics_id (or df, dataFrameAnalytics, dfid): Identifier for the data frame analytics job that created the model. Only displayed if it is still available.
description (or d): The description of the trained model.
heap_size (or hs, modelHeapSize): The estimated heap size to keep the trained model in memory.
id: Identifier for the trained model.
ingest.count (or ic, ingestCount): The total number of documents that are processed by the model.
ingest.current (or icurr, ingestCurrent): The total number of document that are currently being handled by the trained model.
ingest.failed (or if, ingestFailed): The total number of failed ingest attempts with the trained model.
ingest.pipelines (or ip, ingestPipelines): The total number of ingest pipelines that are referencing the trained model.
ingest.time (or it, ingestTime): The total time that is spent processing documents with the trained model.
license (or l): The license level of the trained model.
operations (or o, modelOperations): The estimated number of operations to use the trained model. This number helps measuring the computational complexity of the model.
version (or v): The Elasticsearch version number in which the trained model was created.

One of: string[] or string

from number · default: 0

Skips the specified number of transforms.

size number · default: 100

The maximum number of transforms to display.

Response

application/json

<array> object[]