--
:api: put-trained-model
:request: PutTrainedModelRequest
:response: PutTrainedModelResponse
--
[role="xpack"]
[id="{upid}-{api}"]
=== Create trained models API


Creates a new trained model for inference.
The API accepts a +{request}+ object as a request and returns a +{response}+.

[id="{upid}-{api}-request"]
==== Request

A +{request}+ requires the following argument:

["source","java",subs="attributes,callouts,macros"]
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<1> The configuration of the {infer} trained model to create

[id="{upid}-{api}-config"]
==== Trained model configuration

The `TrainedModelConfig` object contains all the details about the trained model
configuration and contains the following arguments:

["source","java",subs="attributes,callouts,macros"]
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<1> The {infer} definition for the model
<2> Optionally, if the {infer} definition is large, you may choose to compress it for transport.
    Do not supply both the compressed and uncompressed definitions.
<3> The unique model id
<4> The input field names for the model definition
<5> Optionally, a human-readable description
<6> Optionally, an object map contain metadata about the model
<7> Optionally, an array of tags to organize the model
<8> The default inference config to use with the model. Must match the underlying
    definition target_type.

include::../execution.asciidoc[]

[id="{upid}-{api}-response"]
==== Response

The returned +{response}+ contains the newly created trained model.
The +{response}+ will omit the model definition as a precaution against
streaming large model definitions back to the client.

["source","java",subs="attributes,callouts,macros"]
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include-tagged::{doc-tests-file}[{api}-response]
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