type NewPutTrainedModel func(modelidstring) *PutTrainedModel

funcNewPutTrainedModelFunc¶

func NewPutTrainedModelFunc(tpelastictransport.Interface)NewPutTrainedModel

NewPutTrainedModelFunc returns a new instance of PutTrainedModel with the provided transport.Used in the index of the library this allows to retrieve every apis in once place.

type PutTrainedModel struct {// contains filtered or unexported fields}

funcNew¶

func New(tpelastictransport.Interface) *PutTrainedModel

Create a trained model.Enable you to supply a trained model that is not created by data frameanalytics.

https://www.elastic.co/guide/en/elasticsearch/reference/current/put-trained-models.html

func (*PutTrainedModel)CompressedDefinition¶added inv8.9.0

func (r *PutTrainedModel) CompressedDefinition(compresseddefinitionstring) *PutTrainedModel

CompressedDefinition The compressed (GZipped and Base64 encoded) inference definition of themodel. If compressed_definition is specified, then definition cannot bespecified.API name: compressed_definition

func (*PutTrainedModel)DeferDefinitionDecompression¶

func (r *PutTrainedModel) DeferDefinitionDecompression(deferdefinitiondecompressionbool) *PutTrainedModel

DeferDefinitionDecompression If set to `true` and a `compressed_definition` is provided,the request defers definition decompression and skips relevantvalidations.API name: defer_definition_decompression

func (*PutTrainedModel)Definition¶added inv8.9.0

func (r *PutTrainedModel) Definition(definition *types.Definition) *PutTrainedModel

Definition The inference definition for the model. If definition is specified, thencompressed_definition cannot be specified.API name: definition

func (*PutTrainedModel)Description¶added inv8.9.0

func (r *PutTrainedModel) Description(descriptionstring) *PutTrainedModel

Description A human-readable description of the inference trained model.API name: description

func (PutTrainedModel)Do¶

func (rPutTrainedModel) Do(providedCtxcontext.Context) (*Response,error)

Do runs the request through the transport, handle the response and returns a puttrainedmodel.Response

func (*PutTrainedModel)ErrorTrace¶added inv8.14.0

func (r *PutTrainedModel) ErrorTrace(errortracebool) *PutTrainedModel

ErrorTrace When set to `true` Elasticsearch will include the full stack trace of errorswhen they occur.API name: error_trace

func (*PutTrainedModel)FilterPath¶added inv8.14.0

func (r *PutTrainedModel) FilterPath(filterpaths ...string) *PutTrainedModel

FilterPath Comma-separated list of filters in dot notation which reduce the responsereturned by Elasticsearch.API name: filter_path

func (*PutTrainedModel)Header¶

func (r *PutTrainedModel) Header(key, valuestring) *PutTrainedModel

Header set a key, value pair in the PutTrainedModel headers map.

func (*PutTrainedModel)HttpRequest¶

func (r *PutTrainedModel) HttpRequest(ctxcontext.Context) (*http.Request,error)

HttpRequest returns the http.Request object built from thegiven parameters.

func (*PutTrainedModel)Human¶added inv8.14.0

func (r *PutTrainedModel) Human(humanbool) *PutTrainedModel

Human When set to `true` will return statistics in a format suitable for humans.For example `"exists_time": "1h"` for humans and`"eixsts_time_in_millis": 3600000` for computers. When disabled the humanreadable values will be omitted. This makes sense for responses beingconsumedonly by machines.API name: human

func (*PutTrainedModel)InferenceConfig¶added inv8.9.0

func (r *PutTrainedModel) InferenceConfig(inferenceconfig *types.InferenceConfigCreateContainer) *PutTrainedModel

InferenceConfig The default configuration for inference. This can be either a regressionor classification configuration. It must match the underlyingdefinition.trained_model's target_type. For pre-packaged models such asELSER the config is not required.API name: inference_config

func (*PutTrainedModel)Input¶added inv8.9.0

func (r *PutTrainedModel) Input(input *types.Input) *PutTrainedModel

Input The input field names for the model definition.API name: input

func (*PutTrainedModel)Metadata¶added inv8.9.0

func (r *PutTrainedModel) Metadata(metadataany) *PutTrainedModel

Metadata An object map that contains metadata about the model.API name: metadata

metadata should be a json.RawMessage or a structureif a structure is provided, the client will defer a json serializationprior to sending the payload to Elasticsearch.

func (*PutTrainedModel)ModelSizeBytes¶added inv8.9.0

func (r *PutTrainedModel) ModelSizeBytes(modelsizebytesint64) *PutTrainedModel

ModelSizeBytes The estimated memory usage in bytes to keep the trained model in memory.This property is supported only if defer_definition_decompression is trueor the model definition is not supplied.API name: model_size_bytes

func (*PutTrainedModel)ModelType¶added inv8.9.0

func (r *PutTrainedModel) ModelType(modeltypetrainedmodeltype.TrainedModelType) *PutTrainedModel

ModelType The model type.API name: model_type

func (PutTrainedModel)Perform¶added inv8.7.0

func (rPutTrainedModel) Perform(providedCtxcontext.Context) (*http.Response,error)

Perform runs the http.Request through the provided transport and returns an http.Response.

func (*PutTrainedModel)PlatformArchitecture¶added inv8.11.0

func (r *PutTrainedModel) PlatformArchitecture(platformarchitecturestring) *PutTrainedModel

PlatformArchitecture The platform architecture (if applicable) of the trained mode. If the modelonly works on one platform, because it is heavily optimized for a particularprocessor architecture and OS combination, then this field specifies which.The format of the string must match the platform identifiers used byElasticsearch,so one of, `linux-x86_64`, `linux-aarch64`, `darwin-x86_64`,`darwin-aarch64`,or `windows-x86_64`. For portable models (those that work independent ofprocessorarchitecture or OS features), leave this field unset.API name: platform_architecture

func (*PutTrainedModel)PrefixStrings¶added inv8.13.0

func (r *PutTrainedModel) PrefixStrings(prefixstrings *types.TrainedModelPrefixStrings) *PutTrainedModel

PrefixStrings Optional prefix strings applied at inferenceAPI name: prefix_strings

func (*PutTrainedModel)Pretty¶added inv8.14.0

func (r *PutTrainedModel) Pretty(prettybool) *PutTrainedModel

Pretty If set to `true` the returned JSON will be "pretty-formatted". Only usethis option for debugging only.API name: pretty

func (*PutTrainedModel)Raw¶

func (r *PutTrainedModel) Raw(rawio.Reader) *PutTrainedModel

Raw takes a json payload as input which is then passed to the http.RequestIf specified Raw takes precedence on Request method.

func (*PutTrainedModel)Request¶

func (r *PutTrainedModel) Request(req *Request) *PutTrainedModel

Request allows to set the request property with the appropriate payload.

func (*PutTrainedModel)Tags¶added inv8.9.0

func (r *PutTrainedModel) Tags(tags ...string) *PutTrainedModel

Tags An array of tags to organize the model.API name: tags

func (*PutTrainedModel)WaitForCompletion¶added inv8.13.0

func (r *PutTrainedModel) WaitForCompletion(waitforcompletionbool) *PutTrainedModel

WaitForCompletion Whether to wait for all child operations (e.g. model download)to complete.API name: wait_for_completion

type Request struct {// CompressedDefinition The compressed (GZipped and Base64 encoded) inference definition of the// model. If compressed_definition is specified, then definition cannot be// specified.CompressedDefinition *string `json:"compressed_definition,omitempty"`// Definition The inference definition for the model. If definition is specified, then// compressed_definition cannot be specified.Definition *types.Definition `json:"definition,omitempty"`// Description A human-readable description of the inference trained model.Description *string `json:"description,omitempty"`// InferenceConfig 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.InferenceConfig *types.InferenceConfigCreateContainer `json:"inference_config,omitempty"`// Input The input field names for the model definition.Input *types.Input `json:"input,omitempty"`// Metadata An object map that contains metadata about the model.Metadatajson.RawMessage `json:"metadata,omitempty"`// ModelSizeBytes 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.ModelSizeBytes *int64 `json:"model_size_bytes,omitempty"`// ModelType The model type.ModelType *trainedmodeltype.TrainedModelType `json:"model_type,omitempty"`// PlatformArchitecture 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.PlatformArchitecture *string `json:"platform_architecture,omitempty"`// PrefixStrings Optional prefix strings applied at inferencePrefixStrings *types.TrainedModelPrefixStrings `json:"prefix_strings,omitempty"`// Tags An array of tags to organize the model.Tags []string `json:"tags,omitempty"`}

funcNewRequest¶added inv8.5.0

func NewRequest() *Request

NewRequest returns a Request

func (*Request)FromJSON¶added inv8.5.0

func (r *Request) FromJSON(datastring) (*Request,error)

FromJSON allows to load an arbitrary json into the request structure

type Response struct {CompressedDefinition *string `json:"compressed_definition,omitempty"`// CreateTime The time when the trained model was created.CreateTimetypes.DateTime `json:"create_time,omitempty"`// CreatedBy Information on the creator of the trained model.CreatedBy *string `json:"created_by,omitempty"`// DefaultFieldMap Any field map described in the inference configuration takes precedence.DefaultFieldMap map[string]string `json:"default_field_map,omitempty"`// Description The free-text description of the trained model.Description *string `json:"description,omitempty"`// EstimatedHeapMemoryUsageBytes The estimated heap usage in bytes to keep the trained model in memory.EstimatedHeapMemoryUsageBytes *int `json:"estimated_heap_memory_usage_bytes,omitempty"`// EstimatedOperations The estimated number of operations to use the trained model.EstimatedOperations *int `json:"estimated_operations,omitempty"`// FullyDefined True if the full model definition is present.FullyDefined *bool `json:"fully_defined,omitempty"`// InferenceConfig The default configuration for inference. This can be either a regression,// classification, or one of the many NLP focused configurations. It must match// the underlying definition.trained_model's target_type. For pre-packaged// models such as ELSER the config is not required.InferenceConfig *types.InferenceConfigCreateContainer `json:"inference_config,omitempty"`// Input The input field names for the model definition.Inputtypes.TrainedModelConfigInput `json:"input"`// LicenseLevel The license level of the trained model.LicenseLevel *string                     `json:"license_level,omitempty"`Location     *types.TrainedModelLocation `json:"location,omitempty"`// Metadata An object containing metadata about the trained model. For example, models// created by data frame analytics contain analysis_config and input objects.Metadata *types.TrainedModelConfigMetadata `json:"metadata,omitempty"`// ModelId Identifier for the trained model.ModelIdstring                    `json:"model_id"`ModelPackage   *types.ModelPackageConfig `json:"model_package,omitempty"`ModelSizeBytestypes.ByteSize            `json:"model_size_bytes,omitempty"`// ModelType The model typeModelType            *trainedmodeltype.TrainedModelType `json:"model_type,omitempty"`PlatformArchitecture *string                            `json:"platform_architecture,omitempty"`PrefixStrings        *types.TrainedModelPrefixStrings   `json:"prefix_strings,omitempty"`// Tags A comma delimited string of tags. A trained model can have many tags, or// none.Tags []string `json:"tags"`// Version The Elasticsearch version number in which the trained model was created.Version *string `json:"version,omitempty"`}

funcNewResponse¶added inv8.7.0

func NewResponse() *Response

NewResponse returns a Response

func (*Response)UnmarshalJSON¶added inv8.15.0

func (s *Response) UnmarshalJSON(data []byte)error