co.elastic.clients.elasticsearch.ml.PutTrainedModelRequest Maven / Gradle / Ivy
Show all versions of org.apache.servicemix.bundles.elasticsearch-java
/*
* Licensed to Elasticsearch B.V. under one or more contributor
* license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright
* ownership. Elasticsearch B.V. licenses this file to you under
* the Apache License, Version 2.0 (the "License"); you may
* not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing,
* software distributed under the License is distributed on an
* "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
* KIND, either express or implied. See the License for the
* specific language governing permissions and limitations
* under the License.
*/
package co.elastic.clients.elasticsearch.ml;
import co.elastic.clients.elasticsearch._types.ErrorResponse;
import co.elastic.clients.elasticsearch._types.RequestBase;
import co.elastic.clients.elasticsearch.ml.put_trained_model.Definition;
import co.elastic.clients.elasticsearch.ml.put_trained_model.Input;
import co.elastic.clients.json.JsonData;
import co.elastic.clients.json.JsonpDeserializable;
import co.elastic.clients.json.JsonpDeserializer;
import co.elastic.clients.json.JsonpMapper;
import co.elastic.clients.json.JsonpSerializable;
import co.elastic.clients.json.ObjectBuilderDeserializer;
import co.elastic.clients.json.ObjectDeserializer;
import co.elastic.clients.transport.Endpoint;
import co.elastic.clients.transport.endpoints.SimpleEndpoint;
import co.elastic.clients.util.ApiTypeHelper;
import co.elastic.clients.util.ObjectBuilder;
import jakarta.json.stream.JsonGenerator;
import java.lang.Boolean;
import java.lang.Long;
import java.lang.String;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.Objects;
import java.util.function.Function;
import javax.annotation.Nullable;
//----------------------------------------------------------------
// THIS CODE IS GENERATED. MANUAL EDITS WILL BE LOST.
//----------------------------------------------------------------
//
// This code is generated from the Elasticsearch API specification
// at https://github.com/elastic/elasticsearch-specification
//
// Manual updates to this file will be lost when the code is
// re-generated.
//
// If you find a property that is missing or wrongly typed, please
// open an issue or a PR on the API specification repository.
//
//----------------------------------------------------------------
// typedef: ml.put_trained_model.Request
/**
* Create a trained model. Enable you to supply a trained model that is not
* created by data frame analytics.
*
* @see API
* specification
*/
@JsonpDeserializable
public class PutTrainedModelRequest extends RequestBase implements JsonpSerializable {
@Nullable
private final String compressedDefinition;
@Nullable
private final Boolean deferDefinitionDecompression;
@Nullable
private final Definition definition;
@Nullable
private final String description;
@Nullable
private final InferenceConfigCreate inferenceConfig;
@Nullable
private final Input input;
@Nullable
private final JsonData metadata;
private final String modelId;
@Nullable
private final Long modelSizeBytes;
@Nullable
private final TrainedModelType modelType;
@Nullable
private final String platformArchitecture;
@Nullable
private final TrainedModelPrefixStrings prefixStrings;
private final List tags;
@Nullable
private final Boolean waitForCompletion;
// ---------------------------------------------------------------------------------------------
private PutTrainedModelRequest(Builder builder) {
this.compressedDefinition = builder.compressedDefinition;
this.deferDefinitionDecompression = builder.deferDefinitionDecompression;
this.definition = builder.definition;
this.description = builder.description;
this.inferenceConfig = builder.inferenceConfig;
this.input = builder.input;
this.metadata = builder.metadata;
this.modelId = ApiTypeHelper.requireNonNull(builder.modelId, this, "modelId");
this.modelSizeBytes = builder.modelSizeBytes;
this.modelType = builder.modelType;
this.platformArchitecture = builder.platformArchitecture;
this.prefixStrings = builder.prefixStrings;
this.tags = ApiTypeHelper.unmodifiable(builder.tags);
this.waitForCompletion = builder.waitForCompletion;
}
public static PutTrainedModelRequest of(Function> fn) {
return fn.apply(new Builder()).build();
}
/**
* The compressed (GZipped and Base64 encoded) inference definition of the
* model. If compressed_definition is specified, then definition cannot be
* specified.
*
* API name: {@code compressed_definition}
*/
@Nullable
public final String compressedDefinition() {
return this.compressedDefinition;
}
/**
* If set to true and a compressed_definition is
* provided, the request defers definition decompression and skips relevant
* validations.
*
* API name: {@code defer_definition_decompression}
*/
@Nullable
public final Boolean deferDefinitionDecompression() {
return this.deferDefinitionDecompression;
}
/**
* The inference definition for the model. If definition is specified, then
* compressed_definition cannot be specified.
*
* API name: {@code definition}
*/
@Nullable
public final Definition definition() {
return this.definition;
}
/**
* A human-readable description of the inference trained model.
*
* API name: {@code description}
*/
@Nullable
public final String description() {
return this.description;
}
/**
* The default configuration for inference. This can be either a regression or
* classification configuration. It must match the underlying
* definition.trained_model's target_type. For pre-packaged models such as ELSER
* the config is not required.
*
* API name: {@code inference_config}
*/
@Nullable
public final InferenceConfigCreate inferenceConfig() {
return this.inferenceConfig;
}
/**
* The input field names for the model definition.
*
* API name: {@code input}
*/
@Nullable
public final Input input() {
return this.input;
}
/**
* An object map that contains metadata about the model.
*
* API name: {@code metadata}
*/
@Nullable
public final JsonData metadata() {
return this.metadata;
}
/**
* Required - The unique identifier of the trained model.
*
* API name: {@code model_id}
*/
public final String modelId() {
return this.modelId;
}
/**
* The estimated memory usage in bytes to keep the trained model in memory. This
* property is supported only if defer_definition_decompression is true or the
* model definition is not supplied.
*
* API name: {@code model_size_bytes}
*/
@Nullable
public final Long modelSizeBytes() {
return this.modelSizeBytes;
}
/**
* The model type.
*
* API name: {@code model_type}
*/
@Nullable
public final TrainedModelType modelType() {
return this.modelType;
}
/**
* The platform architecture (if applicable) of the trained mode. If the model
* only works on one platform, because it is heavily optimized for a particular
* processor architecture and OS combination, then this field specifies which.
* The format of the string must match the platform identifiers used by
* Elasticsearch, so one of, linux-x86_64,
* linux-aarch64, darwin-x86_64,
* darwin-aarch64, or windows-x86_64. For portable
* models (those that work independent of processor architecture or OS
* features), leave this field unset.
*
* API name: {@code platform_architecture}
*/
@Nullable
public final String platformArchitecture() {
return this.platformArchitecture;
}
/**
* Optional prefix strings applied at inference
*
* API name: {@code prefix_strings}
*/
@Nullable
public final TrainedModelPrefixStrings prefixStrings() {
return this.prefixStrings;
}
/**
* An array of tags to organize the model.
*
* API name: {@code tags}
*/
public final List tags() {
return this.tags;
}
/**
* Whether to wait for all child operations (e.g. model download) to complete.
*
* API name: {@code wait_for_completion}
*/
@Nullable
public final Boolean waitForCompletion() {
return this.waitForCompletion;
}
/**
* Serialize this object to JSON.
*/
public void serialize(JsonGenerator generator, JsonpMapper mapper) {
generator.writeStartObject();
serializeInternal(generator, mapper);
generator.writeEnd();
}
protected void serializeInternal(JsonGenerator generator, JsonpMapper mapper) {
if (this.compressedDefinition != null) {
generator.writeKey("compressed_definition");
generator.write(this.compressedDefinition);
}
if (this.definition != null) {
generator.writeKey("definition");
this.definition.serialize(generator, mapper);
}
if (this.description != null) {
generator.writeKey("description");
generator.write(this.description);
}
if (this.inferenceConfig != null) {
generator.writeKey("inference_config");
this.inferenceConfig.serialize(generator, mapper);
}
if (this.input != null) {
generator.writeKey("input");
this.input.serialize(generator, mapper);
}
if (this.metadata != null) {
generator.writeKey("metadata");
this.metadata.serialize(generator, mapper);
}
if (this.modelSizeBytes != null) {
generator.writeKey("model_size_bytes");
generator.write(this.modelSizeBytes);
}
if (this.modelType != null) {
generator.writeKey("model_type");
this.modelType.serialize(generator, mapper);
}
if (this.platformArchitecture != null) {
generator.writeKey("platform_architecture");
generator.write(this.platformArchitecture);
}
if (this.prefixStrings != null) {
generator.writeKey("prefix_strings");
this.prefixStrings.serialize(generator, mapper);
}
if (ApiTypeHelper.isDefined(this.tags)) {
generator.writeKey("tags");
generator.writeStartArray();
for (String item0 : this.tags) {
generator.write(item0);
}
generator.writeEnd();
}
}
// ---------------------------------------------------------------------------------------------
/**
* Builder for {@link PutTrainedModelRequest}.
*/
public static class Builder extends RequestBase.AbstractBuilder
implements
ObjectBuilder {
@Nullable
private String compressedDefinition;
@Nullable
private Boolean deferDefinitionDecompression;
@Nullable
private Definition definition;
@Nullable
private String description;
@Nullable
private InferenceConfigCreate inferenceConfig;
@Nullable
private Input input;
@Nullable
private JsonData metadata;
private String modelId;
@Nullable
private Long modelSizeBytes;
@Nullable
private TrainedModelType modelType;
@Nullable
private String platformArchitecture;
@Nullable
private TrainedModelPrefixStrings prefixStrings;
@Nullable
private List tags;
@Nullable
private Boolean waitForCompletion;
/**
* The compressed (GZipped and Base64 encoded) inference definition of the
* model. If compressed_definition is specified, then definition cannot be
* specified.
*
* API name: {@code compressed_definition}
*/
public final Builder compressedDefinition(@Nullable String value) {
this.compressedDefinition = value;
return this;
}
/**
* If set to true and a compressed_definition is
* provided, the request defers definition decompression and skips relevant
* validations.
*
* API name: {@code defer_definition_decompression}
*/
public final Builder deferDefinitionDecompression(@Nullable Boolean value) {
this.deferDefinitionDecompression = value;
return this;
}
/**
* The inference definition for the model. If definition is specified, then
* compressed_definition cannot be specified.
*
* API name: {@code definition}
*/
public final Builder definition(@Nullable Definition value) {
this.definition = value;
return this;
}
/**
* The inference definition for the model. If definition is specified, then
* compressed_definition cannot be specified.
*
* API name: {@code definition}
*/
public final Builder definition(Function> fn) {
return this.definition(fn.apply(new Definition.Builder()).build());
}
/**
* A human-readable description of the inference trained model.
*
* API name: {@code description}
*/
public final Builder description(@Nullable String value) {
this.description = value;
return this;
}
/**
* The default configuration for inference. This can be either a regression or
* classification configuration. It must match the underlying
* definition.trained_model's target_type. For pre-packaged models such as ELSER
* the config is not required.
*
* API name: {@code inference_config}
*/
public final Builder inferenceConfig(@Nullable InferenceConfigCreate value) {
this.inferenceConfig = value;
return this;
}
/**
* The default configuration for inference. This can be either a regression or
* classification configuration. It must match the underlying
* definition.trained_model's target_type. For pre-packaged models such as ELSER
* the config is not required.
*
* API name: {@code inference_config}
*/
public final Builder inferenceConfig(
Function> fn) {
return this.inferenceConfig(fn.apply(new InferenceConfigCreate.Builder()).build());
}
/**
* The default configuration for inference. This can be either a regression or
* classification configuration. It must match the underlying
* definition.trained_model's target_type. For pre-packaged models such as ELSER
* the config is not required.
*
* API name: {@code inference_config}
*/
public final Builder inferenceConfig(InferenceConfigCreateVariant value) {
this.inferenceConfig = value._toInferenceConfigCreate();
return this;
}
/**
* The input field names for the model definition.
*
* API name: {@code input}
*/
public final Builder input(@Nullable Input value) {
this.input = value;
return this;
}
/**
* The input field names for the model definition.
*
* API name: {@code input}
*/
public final Builder input(Function> fn) {
return this.input(fn.apply(new Input.Builder()).build());
}
/**
* An object map that contains metadata about the model.
*
* API name: {@code metadata}
*/
public final Builder metadata(@Nullable JsonData value) {
this.metadata = value;
return this;
}
/**
* Required - The unique identifier of the trained model.
*
* API name: {@code model_id}
*/
public final Builder modelId(String value) {
this.modelId = value;
return this;
}
/**
* The estimated memory usage in bytes to keep the trained model in memory. This
* property is supported only if defer_definition_decompression is true or the
* model definition is not supplied.
*
* API name: {@code model_size_bytes}
*/
public final Builder modelSizeBytes(@Nullable Long value) {
this.modelSizeBytes = value;
return this;
}
/**
* The model type.
*
* API name: {@code model_type}
*/
public final Builder modelType(@Nullable TrainedModelType value) {
this.modelType = value;
return this;
}
/**
* The platform architecture (if applicable) of the trained mode. If the model
* only works on one platform, because it is heavily optimized for a particular
* processor architecture and OS combination, then this field specifies which.
* The format of the string must match the platform identifiers used by
* Elasticsearch, so one of, linux-x86_64,
* linux-aarch64, darwin-x86_64,
* darwin-aarch64, or windows-x86_64. For portable
* models (those that work independent of processor architecture or OS
* features), leave this field unset.
*
* API name: {@code platform_architecture}
*/
public final Builder platformArchitecture(@Nullable String value) {
this.platformArchitecture = value;
return this;
}
/**
* Optional prefix strings applied at inference
*
* API name: {@code prefix_strings}
*/
public final Builder prefixStrings(@Nullable TrainedModelPrefixStrings value) {
this.prefixStrings = value;
return this;
}
/**
* Optional prefix strings applied at inference
*
* API name: {@code prefix_strings}
*/
public final Builder prefixStrings(
Function> fn) {
return this.prefixStrings(fn.apply(new TrainedModelPrefixStrings.Builder()).build());
}
/**
* An array of tags to organize the model.
*
* API name: {@code tags}
*
* Adds all elements of list to tags.
*/
public final Builder tags(List list) {
this.tags = _listAddAll(this.tags, list);
return this;
}
/**
* An array of tags to organize the model.
*
* API name: {@code tags}
*
* Adds one or more values to tags.
*/
public final Builder tags(String value, String... values) {
this.tags = _listAdd(this.tags, value, values);
return this;
}
/**
* Whether to wait for all child operations (e.g. model download) to complete.
*
* API name: {@code wait_for_completion}
*/
public final Builder waitForCompletion(@Nullable Boolean value) {
this.waitForCompletion = value;
return this;
}
@Override
protected Builder self() {
return this;
}
/**
* Builds a {@link PutTrainedModelRequest}.
*
* @throws NullPointerException
* if some of the required fields are null.
*/
public PutTrainedModelRequest build() {
_checkSingleUse();
return new PutTrainedModelRequest(this);
}
}
// ---------------------------------------------------------------------------------------------
/**
* Json deserializer for {@link PutTrainedModelRequest}
*/
public static final JsonpDeserializer _DESERIALIZER = ObjectBuilderDeserializer
.lazy(Builder::new, PutTrainedModelRequest::setupPutTrainedModelRequestDeserializer);
protected static void setupPutTrainedModelRequestDeserializer(
ObjectDeserializer op) {
op.add(Builder::compressedDefinition, JsonpDeserializer.stringDeserializer(), "compressed_definition");
op.add(Builder::definition, Definition._DESERIALIZER, "definition");
op.add(Builder::description, JsonpDeserializer.stringDeserializer(), "description");
op.add(Builder::inferenceConfig, InferenceConfigCreate._DESERIALIZER, "inference_config");
op.add(Builder::input, Input._DESERIALIZER, "input");
op.add(Builder::metadata, JsonData._DESERIALIZER, "metadata");
op.add(Builder::modelSizeBytes, JsonpDeserializer.longDeserializer(), "model_size_bytes");
op.add(Builder::modelType, TrainedModelType._DESERIALIZER, "model_type");
op.add(Builder::platformArchitecture, JsonpDeserializer.stringDeserializer(), "platform_architecture");
op.add(Builder::prefixStrings, TrainedModelPrefixStrings._DESERIALIZER, "prefix_strings");
op.add(Builder::tags, JsonpDeserializer.arrayDeserializer(JsonpDeserializer.stringDeserializer()), "tags");
}
// ---------------------------------------------------------------------------------------------
/**
* Endpoint "{@code ml.put_trained_model}".
*/
public static final Endpoint _ENDPOINT = new SimpleEndpoint<>(
"es/ml.put_trained_model",
// Request method
request -> {
return "PUT";
},
// Request path
request -> {
final int _modelId = 1 << 0;
int propsSet = 0;
propsSet |= _modelId;
if (propsSet == (_modelId)) {
StringBuilder buf = new StringBuilder();
buf.append("/_ml");
buf.append("/trained_models");
buf.append("/");
SimpleEndpoint.pathEncode(request.modelId, buf);
return buf.toString();
}
throw SimpleEndpoint.noPathTemplateFound("path");
},
// Path parameters
request -> {
Map params = new HashMap<>();
final int _modelId = 1 << 0;
int propsSet = 0;
propsSet |= _modelId;
if (propsSet == (_modelId)) {
params.put("modelId", request.modelId);
}
return params;
},
// Request parameters
request -> {
Map params = new HashMap<>();
if (request.waitForCompletion != null) {
params.put("wait_for_completion", String.valueOf(request.waitForCompletion));
}
if (request.deferDefinitionDecompression != null) {
params.put("defer_definition_decompression", String.valueOf(request.deferDefinitionDecompression));
}
return params;
}, SimpleEndpoint.emptyMap(), true, PutTrainedModelResponse._DESERIALIZER);
}