IMPORTANT: No additional bug fixes or documentation updates
will be released for this version. For the latest information, see the
current release documentation.
Infer trained model deployment APIedit
Evaluates a trained model.
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.
Requestedit
POST _ml/trained_models/<model_id>/deployment/_infer
Path parametersedit
-
<model_id> - (Required, string) The unique identifier of the trained model.
Query parametersedit
-
timeout - (Optional, time) Controls the amount of time to wait for inference results. Defaults to 10 seconds.
Request bodyedit
-
docs -
(Required, array)
An array of objects to pass to the model for inference. The objects should
contain a field matching your configured trained model input. Typically, the field
name is
text_field. Currently, only a single value is allowed.
Examplesedit
The response depends on the task the model is trained for. If it is a text classification task, the response is the score. For example:
POST _ml/trained_models/model2/deployment/_infer
{
"docs": [{"text_field": "The movie was awesome!!"}]
}
The API returns the predicted label and the confidence.
{
"predicted_value" : "POSITIVE",
"prediction_probability" : 0.9998667964092964
}
For named entity recognition (NER) tasks, the response contains the annotated text output and the recognized entities.
POST _ml/trained_models/model2/deployment/_infer
{
"input": "Hi my name is Josh and I live in Berlin"
}
The API returns in this case:
{
"predicted_value" : "Hi my name is [Josh](PER&Josh) and I live in [Berlin](LOC&Berlin)",
"entities" : [
{
"entity" : "Josh",
"class_name" : "PER",
"class_probability" : 0.9977303419824,
"start_pos" : 14,
"end_pos" : 18
},
{
"entity" : "Berlin",
"class_name" : "LOC",
"class_probability" : 0.9992474323902818,
"start_pos" : 33,
"end_pos" : 39
}
]
}