[role="xpack"] [testenv="basic"] [[get-inference]] === Get {infer} trained model API [subs="attributes"] ++++ Get {infer} trained model ++++ Retrieves configuration information for a trained {infer} model. experimental[] [[ml-get-inference-request]] ==== {api-request-title} `GET _ml/inference/` + `GET _ml/inference/` + `GET _ml/inference/_all` + `GET _ml/inference/,` + `GET _ml/inference/` [[ml-get-inference-prereq]] ==== {api-prereq-title} Required privileges which should be added to a custom role: * cluster: `monitor_ml` For more information, see <> and <>. [[ml-get-inference-desc]] ==== {api-description-title} 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. [[ml-get-inference-path-params]] ==== {api-path-parms-title} ``:: (Optional, string) include::{docdir}/ml/ml-shared.asciidoc[tag=model-id] [[ml-get-inference-query-params]] ==== {api-query-parms-title} `allow_no_match`:: (Optional, boolean) include::{docdir}/ml/ml-shared.asciidoc[tag=allow-no-match] `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) include::{docdir}/ml/ml-shared.asciidoc[tag=from] `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) include::{docdir}/ml/ml-shared.asciidoc[tag=size] `tags`:: (Optional, string) include::{docdir}/ml/ml-shared.asciidoc[tag=tags] [role="child_attributes"] [[ml-get-inference-results]] ==== {api-response-body-title} `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 [%collapsible%open] ==== `created_by`::: (string) Information on the creator of the trained model. `create_time`::: (<>) 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 {dfanalytics} contain `analysis_config` and `input` objects. `model_id`::: (string) Idetifier for the trained model. `tags`::: (string) A comma delimited string of tags. A {infer} model can have many tags, or none. `version`::: (string) The {es} version number in which the trained model was created. ==== [[ml-get-inference-response-codes]] ==== {api-response-codes-title} `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. [[ml-get-inference-example]] ==== {api-examples-title} The following example gets configuration information for all the trained models: [source,console] -------------------------------------------------- GET _ml/inference/ -------------------------------------------------- // TEST[skip:TBD]