Evaluate a trained model

POST /_ml/trained_models/{model_id}/_infer

Api key auth

Path Parameters

model_id string Id required: The unique identifier of the trained model.

Query Parameters

timeout string Duration · default: 10s: Controls the amount of time to wait for inference results.

Request

Response

application/json

Examples

An example body for a POST _ml/trained_models/lang_ident_model_1/_infer request.

Request Console 1 / 8 languages

Console Kibana Dev Tools

POST _ml/trained_models/lang_ident_model_1/_infer
{
  "docs":[{"text": "The fool doth think he is wise, but the wise man knows himself to be a fool."}]
}

JavaScript Elasticsearch JavaScript Client

const response = await client.ml.inferTrainedModel({
  model_id: "lang_ident_model_1",
  docs: [
    {
      text: "The fool doth think he is wise, but the wise man knows himself to be a fool.",
    },
  ],
});

Python Elasticsearch Python Client

resp = client.ml.infer_trained_model(
    model_id="lang_ident_model_1",
    docs=[
        {
            "text": "The fool doth think he is wise, but the wise man knows himself to be a fool."
        }
    ],
)

curl Shell

curl -X POST "$ELASTICSEARCH_URL/_ml/trained_models/lang_ident_model_1/_infer" \
  -H "Authorization: ApiKey $ELASTIC_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "docs": [
      {
        "text": "The fool doth think he is wise, but the wise man knows himself to be a fool."
      }
    ]
  }'

Java Elasticsearch Java Client

client.ml().inferTrainedModel(i -> i
    .docs(Map.of("text", JsonData.fromJson("\"The fool doth think he is wise, but the wise man knows himself to be a fool.\"")))
    .modelId("lang_ident_model_1")
);

C# Elasticsearch .NET Client

var response = await client.MachineLearning
    .InferTrainedModelAsync(modelId: "lang_ident_model_1", d1 => d1
        .Docs([new Dictionary<string, object>()
        {
            { "text", "The fool doth think he is wise, but the wise man knows himself to be a fool." }
        }])
    );

PHP Elasticsearch PHP Client

$resp = $client->ml()->inferTrainedModel([
    "model_id" => "lang_ident_model_1",
    "body" => [
        "docs" => array(
            [
                "text" => "The fool doth think he is wise, but the wise man knows himself to be a fool.",
            ],
        ),
    ],
]);

Ruby Elasticsearch Ruby Client

response = client.ml.infer_trained_model(
  model_id: "lang_ident_model_1",
  body: {
    "docs": [
      {
        "text": "The fool doth think he is wise, but the wise man knows himself to be a fool."
      }
    ]
  }
)

Response

No example

Path Parameters

Query Parameters

Request { docs , inference_config , }

Response

Request