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Elastic Docs ›Java REST Client [7.10] ›Java High Level REST Client ›Machine Learning APIs

Get trained models API

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Get trained models API

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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.

Retrieves one or more trained models. The API accepts a GetTrainedModelsRequest object and returns a GetTrainedModelsResponse.

Get trained models request

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A GetTrainedModelsRequest requires either a trained model ID, a comma-separated list of IDs, or the special wildcard _all to get all trained models.

GetTrainedModelsRequest request = new GetTrainedModelsRequest("my-trained-model") 
    .setPageParams(new PageParams(0, 1)) 
    .includeDefinition() 
    .includeTotalFeatureImportance() 
    .includeFeatureImportanceBaseline() 
    .setDecompressDefinition(false) 
    .setAllowNoMatch(true) 
    .setTags("regression") 
    .setForExport(false);

Constructing a new GET request referencing an existing trained model.

Set the paging parameters.

Indicate if the complete model definition should be included.

Indicate if the total feature importance for the features used in training should is included in the metadata.

Indicate if the feature importance baselines that were used in training are included in the metadata.

Should the definition be fully decompressed on GET.

Allow empty response if no trained models match the provided ID patterns. If false, an error will be thrown if no trained models match the ID patterns.

An optional list of tags used to narrow the model search. A trained model can have many tags or none. The trained models in the response will contain all the provided tags.

Optional boolean value for requesting the trained model in a format that can then be put into another cluster. Certain fields that can only be set when the model is imported are removed.

Synchronous execution

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When executing a GetTrainedModelsRequest in the following manner, the client waits for the GetTrainedModelsResponse to be returned before continuing with code execution:

GetTrainedModelsResponse response = client.machineLearning().getTrainedModels(request, RequestOptions.DEFAULT);

Synchronous calls may throw an IOException in case of either failing to parse the REST response in the high-level REST client, the request times out or similar cases where there is no response coming back from the server.

In cases where the server returns a 4xx or 5xx error code, the high-level client tries to parse the response body error details instead and then throws a generic ElasticsearchException and adds the original ResponseException as a suppressed exception to it.

Asynchronous execution

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Executing a GetTrainedModelsRequest can also be done in an asynchronous fashion so that the client can return directly. Users need to specify how the response or potential failures will be handled by passing the request and a listener to the asynchronous get-trained-models method:

client.machineLearning().getTrainedModelsAsync(request, RequestOptions.DEFAULT, listener);

The GetTrainedModelsRequest to execute and the ActionListener to use when the execution completes

The asynchronous method does not block and returns immediately. Once it is completed the ActionListener is called back using the onResponse method if the execution successfully completed or using the onFailure method if it failed. Failure scenarios and expected exceptions are the same as in the synchronous execution case.

A typical listener for get-trained-models looks like:

ActionListener<GetTrainedModelsResponse> listener = new ActionListener<GetTrainedModelsResponse>() {
    @Override
    public void onResponse(GetTrainedModelsResponse response) {
        
    }

    @Override
    public void onFailure(Exception e) {
        
    }
};

Called when the execution is successfully completed.

Called when the whole GetTrainedModelsRequest fails.

Response

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The returned GetTrainedModelsResponse contains the requested trained model.

List<TrainedModelConfig> models = response.getTrainedModels();
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