Class ElasticsearchServiceSettings
java.lang.Object
co.elastic.clients.elasticsearch.inference.ElasticsearchServiceSettings
- All Implemented Interfaces:
JsonpSerializable
@JsonpDeserializable
public class ElasticsearchServiceSettings
extends Object
implements JsonpSerializable
- See Also:
-
Nested Class Summary
Nested Classes -
Field Summary
FieldsModifier and TypeFieldDescriptionstatic final JsonpDeserializer<ElasticsearchServiceSettings>Json deserializer forElasticsearchServiceSettings -
Method Summary
Modifier and TypeMethodDescriptionfinal AdaptiveAllocationsAdaptive allocations configuration details.final StringThe deployment identifier for a trained model deployment.final StringmodelId()Required - The name of the model to use for the inference task.final IntegerThe total number of allocations that are assigned to the model across machine learning nodes.final intRequired - The number of threads used by each model allocation during inference.static ElasticsearchServiceSettingsvoidserialize(jakarta.json.stream.JsonGenerator generator, JsonpMapper mapper) Serialize this object to JSON.protected voidserializeInternal(jakarta.json.stream.JsonGenerator generator, JsonpMapper mapper) protected static voidsetupElasticsearchServiceSettingsDeserializer(ObjectDeserializer<ElasticsearchServiceSettings.Builder> op) toString()
-
Field Details
-
_DESERIALIZER
Json deserializer forElasticsearchServiceSettings
-
-
Method Details
-
of
-
adaptiveAllocations
Adaptive allocations configuration details. Ifenabledis true, the number of allocations of the model is set based on the current load the process gets. When the load is high, a new model allocation is automatically created, respecting the value ofmax_number_of_allocationsif it's set. When the load is low, a model allocation is automatically removed, respecting the value ofmin_number_of_allocationsif it's set. Ifenabledis true, do not set the number of allocations manually.API name:
adaptive_allocations -
deploymentId
The deployment identifier for a trained model deployment. Whendeployment_idis used themodel_idis optional.API name:
deployment_id -
modelId
Required - The name of the model to use for the inference task. It can be the ID of a built-in model (for example,.multilingual-e5-smallfor E5) or a text embedding model that was uploaded by using the Eland client.API name:
model_id -
numAllocations
The total number of allocations that are assigned to the model across machine learning nodes. Increasing this value generally increases the throughput. If adaptive allocations are enabled, do not set this value because it's automatically set.API name:
num_allocations -
numThreads
public final int numThreads()Required - The number of threads used by each model allocation during inference. This setting generally increases the speed per inference request. The inference process is a compute-bound process;threads_per_allocationsmust not exceed the number of available allocated processors per node. The value must be a power of 2. The maximum value is 32.API name:
num_threads -
serialize
Serialize this object to JSON.- Specified by:
serializein interfaceJsonpSerializable
-
serializeInternal
-
toString
-
setupElasticsearchServiceSettingsDeserializer
protected static void setupElasticsearchServiceSettingsDeserializer(ObjectDeserializer<ElasticsearchServiceSettings.Builder> op)
-