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code / gocloud / 24e410efbb6add2d33ecfb6ad98b67dc8894e578 / . / aiplatform / apiv1beta1 / aiplatformpb / prediction_service.pb.go
blob: 3fad53b30f46e5b63161c0771ed0c3a79359384c [file] [log] [blame]
// Copyright 2023 Google LLC
//
// Licensed 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.
// Code generated by protoc-gen-go. DO NOT EDIT.
// versions:
// protoc-gen-go v1.31.0
// protoc v4.23.2
// source: google/cloud/aiplatform/v1beta1/prediction_service.proto
package aiplatformpb
import (
context "context"
reflect "reflect"
sync "sync"
_ "google.golang.org/genproto/googleapis/api/annotations"
httpbody "google.golang.org/genproto/googleapis/api/httpbody"
grpc "google.golang.org/grpc"
codes "google.golang.org/grpc/codes"
status "google.golang.org/grpc/status"
protoreflect "google.golang.org/protobuf/reflect/protoreflect"
protoimpl "google.golang.org/protobuf/runtime/protoimpl"
structpb "google.golang.org/protobuf/types/known/structpb"
)
const (
// Verify that this generated code is sufficiently up-to-date.
_ = protoimpl.EnforceVersion(20 - protoimpl.MinVersion)
// Verify that runtime/protoimpl is sufficiently up-to-date.
_ = protoimpl.EnforceVersion(protoimpl.MaxVersion - 20)
)
// Request message for
// [PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict].
type PredictRequest struct {
state protoimpl.MessageState
sizeCache protoimpl.SizeCache
unknownFields protoimpl.UnknownFields
// Required. The name of the Endpoint requested to serve the prediction.
// Format:
// `projects/{project}/locations/{location}/endpoints/{endpoint}`
Endpoint string `protobuf:"bytes,1,opt,name=endpoint,proto3" json:"endpoint,omitempty"`
// Required. The instances that are the input to the prediction call.
// A DeployedModel may have an upper limit on the number of instances it
// supports per request, and when it is exceeded the prediction call errors
// in case of AutoML Models, or, in case of customer created Models, the
// behaviour is as documented by that Model.
// The schema of any single instance may be specified via Endpoint's
// DeployedModels'
// [Model's][google.cloud.aiplatform.v1beta1.DeployedModel.model]
// [PredictSchemata's][google.cloud.aiplatform.v1beta1.Model.predict_schemata]
// [instance_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.instance_schema_uri].
Instances []*structpb.Value `protobuf:"bytes,2,rep,name=instances,proto3" json:"instances,omitempty"`
// The parameters that govern the prediction. The schema of the parameters may
// be specified via Endpoint's DeployedModels' [Model's
// ][google.cloud.aiplatform.v1beta1.DeployedModel.model]
// [PredictSchemata's][google.cloud.aiplatform.v1beta1.Model.predict_schemata]
// [parameters_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.parameters_schema_uri].
Parameters *structpb.Value `protobuf:"bytes,3,opt,name=parameters,proto3" json:"parameters,omitempty"`
}
func (x *PredictRequest) Reset() {
*x = PredictRequest{}
if protoimpl.UnsafeEnabled {
mi := &file_google_cloud_aiplatform_v1beta1_prediction_service_proto_msgTypes[0]
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
ms.StoreMessageInfo(mi)
}
}
func (x *PredictRequest) String() string {
return protoimpl.X.MessageStringOf(x)
}
func (*PredictRequest) ProtoMessage() {}
func (x *PredictRequest) ProtoReflect() protoreflect.Message {
mi := &file_google_cloud_aiplatform_v1beta1_prediction_service_proto_msgTypes[0]
if protoimpl.UnsafeEnabled && x != nil {
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
if ms.LoadMessageInfo() == nil {
ms.StoreMessageInfo(mi)
}
return ms
}
return mi.MessageOf(x)
}
// Deprecated: Use PredictRequest.ProtoReflect.Descriptor instead.
func (*PredictRequest) Descriptor() ([]byte, []int) {
return file_google_cloud_aiplatform_v1beta1_prediction_service_proto_rawDescGZIP(), []int{0}
}
func (x *PredictRequest) GetEndpoint() string {
if x != nil {
return x.Endpoint
}
return ""
}
func (x *PredictRequest) GetInstances() []*structpb.Value {
if x != nil {
return x.Instances
}
return nil
}
func (x *PredictRequest) GetParameters() *structpb.Value {
if x != nil {
return x.Parameters
}
return nil
}
// Response message for
// [PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict].
type PredictResponse struct {
state protoimpl.MessageState
sizeCache protoimpl.SizeCache
unknownFields protoimpl.UnknownFields
// The predictions that are the output of the predictions call.
// The schema of any single prediction may be specified via Endpoint's
// DeployedModels' [Model's
// ][google.cloud.aiplatform.v1beta1.DeployedModel.model]
// [PredictSchemata's][google.cloud.aiplatform.v1beta1.Model.predict_schemata]
// [prediction_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.prediction_schema_uri].
Predictions []*structpb.Value `protobuf:"bytes,1,rep,name=predictions,proto3" json:"predictions,omitempty"`
// ID of the Endpoint's DeployedModel that served this prediction.
DeployedModelId string `protobuf:"bytes,2,opt,name=deployed_model_id,json=deployedModelId,proto3" json:"deployed_model_id,omitempty"`
// Output only. The resource name of the Model which is deployed as the
// DeployedModel that this prediction hits.
Model string `protobuf:"bytes,3,opt,name=model,proto3" json:"model,omitempty"`
// Output only. The version ID of the Model which is deployed as the
// DeployedModel that this prediction hits.
ModelVersionId string `protobuf:"bytes,5,opt,name=model_version_id,json=modelVersionId,proto3" json:"model_version_id,omitempty"`
// Output only. The [display
// name][google.cloud.aiplatform.v1beta1.Model.display_name] of the Model
// which is deployed as the DeployedModel that this prediction hits.
ModelDisplayName string `protobuf:"bytes,4,opt,name=model_display_name,json=modelDisplayName,proto3" json:"model_display_name,omitempty"`
// Output only. Request-level metadata returned by the model. The metadata
// type will be dependent upon the model implementation.
Metadata *structpb.Value `protobuf:"bytes,6,opt,name=metadata,proto3" json:"metadata,omitempty"`
}
func (x *PredictResponse) Reset() {
*x = PredictResponse{}
if protoimpl.UnsafeEnabled {
mi := &file_google_cloud_aiplatform_v1beta1_prediction_service_proto_msgTypes[1]
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
ms.StoreMessageInfo(mi)
}
}
func (x *PredictResponse) String() string {
return protoimpl.X.MessageStringOf(x)
}
func (*PredictResponse) ProtoMessage() {}
func (x *PredictResponse) ProtoReflect() protoreflect.Message {
mi := &file_google_cloud_aiplatform_v1beta1_prediction_service_proto_msgTypes[1]
if protoimpl.UnsafeEnabled && x != nil {
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
if ms.LoadMessageInfo() == nil {
ms.StoreMessageInfo(mi)
}
return ms
}
return mi.MessageOf(x)
}
// Deprecated: Use PredictResponse.ProtoReflect.Descriptor instead.
func (*PredictResponse) Descriptor() ([]byte, []int) {
return file_google_cloud_aiplatform_v1beta1_prediction_service_proto_rawDescGZIP(), []int{1}
}
func (x *PredictResponse) GetPredictions() []*structpb.Value {
if x != nil {
return x.Predictions
}
return nil
}
func (x *PredictResponse) GetDeployedModelId() string {
if x != nil {
return x.DeployedModelId
}
return ""
}
func (x *PredictResponse) GetModel() string {
if x != nil {
return x.Model
}
return ""
}
func (x *PredictResponse) GetModelVersionId() string {
if x != nil {
return x.ModelVersionId
}
return ""
}
func (x *PredictResponse) GetModelDisplayName() string {
if x != nil {
return x.ModelDisplayName
}
return ""
}
func (x *PredictResponse) GetMetadata() *structpb.Value {
if x != nil {
return x.Metadata
}
return nil
}
// Request message for
// [PredictionService.RawPredict][google.cloud.aiplatform.v1beta1.PredictionService.RawPredict].
type RawPredictRequest struct {
state protoimpl.MessageState
sizeCache protoimpl.SizeCache
unknownFields protoimpl.UnknownFields
// Required. The name of the Endpoint requested to serve the prediction.
// Format:
// `projects/{project}/locations/{location}/endpoints/{endpoint}`
Endpoint string `protobuf:"bytes,1,opt,name=endpoint,proto3" json:"endpoint,omitempty"`
// The prediction input. Supports HTTP headers and arbitrary data payload.
//
// A [DeployedModel][google.cloud.aiplatform.v1beta1.DeployedModel] may have
// an upper limit on the number of instances it supports per request. When
// this limit it is exceeded for an AutoML model, the
// [RawPredict][google.cloud.aiplatform.v1beta1.PredictionService.RawPredict]
// method returns an error. When this limit is exceeded for a custom-trained
// model, the behavior varies depending on the model.
//
// You can specify the schema for each instance in the
// [predict_schemata.instance_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.instance_schema_uri]
// field when you create a [Model][google.cloud.aiplatform.v1beta1.Model].
// This schema applies when you deploy the `Model` as a `DeployedModel` to an
// [Endpoint][google.cloud.aiplatform.v1beta1.Endpoint] and use the
// `RawPredict` method.
HttpBody *httpbody.HttpBody `protobuf:"bytes,2,opt,name=http_body,json=httpBody,proto3" json:"http_body,omitempty"`
}
func (x *RawPredictRequest) Reset() {
*x = RawPredictRequest{}
if protoimpl.UnsafeEnabled {
mi := &file_google_cloud_aiplatform_v1beta1_prediction_service_proto_msgTypes[2]
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
ms.StoreMessageInfo(mi)
}
}
func (x *RawPredictRequest) String() string {
return protoimpl.X.MessageStringOf(x)
}
func (*RawPredictRequest) ProtoMessage() {}
func (x *RawPredictRequest) ProtoReflect() protoreflect.Message {
mi := &file_google_cloud_aiplatform_v1beta1_prediction_service_proto_msgTypes[2]
if protoimpl.UnsafeEnabled && x != nil {
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
if ms.LoadMessageInfo() == nil {
ms.StoreMessageInfo(mi)
}
return ms
}
return mi.MessageOf(x)
}
// Deprecated: Use RawPredictRequest.ProtoReflect.Descriptor instead.
func (*RawPredictRequest) Descriptor() ([]byte, []int) {
return file_google_cloud_aiplatform_v1beta1_prediction_service_proto_rawDescGZIP(), []int{2}
}
func (x *RawPredictRequest) GetEndpoint() string {
if x != nil {
return x.Endpoint
}
return ""
}
func (x *RawPredictRequest) GetHttpBody() *httpbody.HttpBody {
if x != nil {
return x.HttpBody
}
return nil
}
// Request message for
// [PredictionService.StreamingPredict][google.cloud.aiplatform.v1beta1.PredictionService.StreamingPredict].
//
// The first message must contain
// [endpoint][google.cloud.aiplatform.v1beta1.StreamingPredictRequest.endpoint]
// field and optionally [input][]. The subsequent messages must contain
// [input][].
type StreamingPredictRequest struct {
state protoimpl.MessageState
sizeCache protoimpl.SizeCache
unknownFields protoimpl.UnknownFields
// Required. The name of the Endpoint requested to serve the prediction.
// Format:
// `projects/{project}/locations/{location}/endpoints/{endpoint}`
Endpoint string `protobuf:"bytes,1,opt,name=endpoint,proto3" json:"endpoint,omitempty"`
// The prediction input.
Inputs []*Tensor `protobuf:"bytes,2,rep,name=inputs,proto3" json:"inputs,omitempty"`
// The parameters that govern the prediction.
Parameters *Tensor `protobuf:"bytes,3,opt,name=parameters,proto3" json:"parameters,omitempty"`
}
func (x *StreamingPredictRequest) Reset() {
*x = StreamingPredictRequest{}
if protoimpl.UnsafeEnabled {
mi := &file_google_cloud_aiplatform_v1beta1_prediction_service_proto_msgTypes[3]
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
ms.StoreMessageInfo(mi)
}
}
func (x *StreamingPredictRequest) String() string {
return protoimpl.X.MessageStringOf(x)
}
func (*StreamingPredictRequest) ProtoMessage() {}
func (x *StreamingPredictRequest) ProtoReflect() protoreflect.Message {
mi := &file_google_cloud_aiplatform_v1beta1_prediction_service_proto_msgTypes[3]
if protoimpl.UnsafeEnabled && x != nil {
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
if ms.LoadMessageInfo() == nil {
ms.StoreMessageInfo(mi)
}
return ms
}
return mi.MessageOf(x)
}
// Deprecated: Use StreamingPredictRequest.ProtoReflect.Descriptor instead.
func (*StreamingPredictRequest) Descriptor() ([]byte, []int) {
return file_google_cloud_aiplatform_v1beta1_prediction_service_proto_rawDescGZIP(), []int{3}
}
func (x *StreamingPredictRequest) GetEndpoint() string {
if x != nil {
return x.Endpoint
}
return ""
}
func (x *StreamingPredictRequest) GetInputs() []*Tensor {
if x != nil {
return x.Inputs
}
return nil
}
func (x *StreamingPredictRequest) GetParameters() *Tensor {
if x != nil {
return x.Parameters
}
return nil
}
// Response message for
// [PredictionService.StreamingPredict][google.cloud.aiplatform.v1beta1.PredictionService.StreamingPredict].
type StreamingPredictResponse struct {
state protoimpl.MessageState
sizeCache protoimpl.SizeCache
unknownFields protoimpl.UnknownFields
// The prediction output.
Outputs []*Tensor `protobuf:"bytes,1,rep,name=outputs,proto3" json:"outputs,omitempty"`
// The parameters that govern the prediction.
Parameters *Tensor `protobuf:"bytes,2,opt,name=parameters,proto3" json:"parameters,omitempty"`
}
func (x *StreamingPredictResponse) Reset() {
*x = StreamingPredictResponse{}
if protoimpl.UnsafeEnabled {
mi := &file_google_cloud_aiplatform_v1beta1_prediction_service_proto_msgTypes[4]
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
ms.StoreMessageInfo(mi)
}
}
func (x *StreamingPredictResponse) String() string {
return protoimpl.X.MessageStringOf(x)
}
func (*StreamingPredictResponse) ProtoMessage() {}
func (x *StreamingPredictResponse) ProtoReflect() protoreflect.Message {
mi := &file_google_cloud_aiplatform_v1beta1_prediction_service_proto_msgTypes[4]
if protoimpl.UnsafeEnabled && x != nil {
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
if ms.LoadMessageInfo() == nil {
ms.StoreMessageInfo(mi)
}
return ms
}
return mi.MessageOf(x)
}
// Deprecated: Use StreamingPredictResponse.ProtoReflect.Descriptor instead.
func (*StreamingPredictResponse) Descriptor() ([]byte, []int) {
return file_google_cloud_aiplatform_v1beta1_prediction_service_proto_rawDescGZIP(), []int{4}
}
func (x *StreamingPredictResponse) GetOutputs() []*Tensor {
if x != nil {
return x.Outputs
}
return nil
}
func (x *StreamingPredictResponse) GetParameters() *Tensor {
if x != nil {
return x.Parameters
}
return nil
}
// Request message for
// [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain].
type ExplainRequest struct {
state protoimpl.MessageState
sizeCache protoimpl.SizeCache
unknownFields protoimpl.UnknownFields
// Required. The name of the Endpoint requested to serve the explanation.
// Format:
// `projects/{project}/locations/{location}/endpoints/{endpoint}`
Endpoint string `protobuf:"bytes,1,opt,name=endpoint,proto3" json:"endpoint,omitempty"`
// Required. The instances that are the input to the explanation call.
// A DeployedModel may have an upper limit on the number of instances it
// supports per request, and when it is exceeded the explanation call errors
// in case of AutoML Models, or, in case of customer created Models, the
// behaviour is as documented by that Model.
// The schema of any single instance may be specified via Endpoint's
// DeployedModels'
// [Model's][google.cloud.aiplatform.v1beta1.DeployedModel.model]
// [PredictSchemata's][google.cloud.aiplatform.v1beta1.Model.predict_schemata]
// [instance_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.instance_schema_uri].
Instances []*structpb.Value `protobuf:"bytes,2,rep,name=instances,proto3" json:"instances,omitempty"`
// The parameters that govern the prediction. The schema of the parameters may
// be specified via Endpoint's DeployedModels' [Model's
// ][google.cloud.aiplatform.v1beta1.DeployedModel.model]
// [PredictSchemata's][google.cloud.aiplatform.v1beta1.Model.predict_schemata]
// [parameters_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.parameters_schema_uri].
Parameters *structpb.Value `protobuf:"bytes,4,opt,name=parameters,proto3" json:"parameters,omitempty"`
// If specified, overrides the
// [explanation_spec][google.cloud.aiplatform.v1beta1.DeployedModel.explanation_spec]
// of the DeployedModel. Can be used for explaining prediction results with
// different configurations, such as:
// - Explaining top-5 predictions results as opposed to top-1;
// - Increasing path count or step count of the attribution methods to reduce
// approximate errors;
// - Using different baselines for explaining the prediction results.
ExplanationSpecOverride *ExplanationSpecOverride `protobuf:"bytes,5,opt,name=explanation_spec_override,json=explanationSpecOverride,proto3" json:"explanation_spec_override,omitempty"`
// Optional. This field is the same as the one above, but supports multiple
// explanations to occur in parallel. The key can be any string. Each override
// will be run against the model, then its explanations will be grouped
// together.
//
// Note - these explanations are run **In Addition** to the default
// Explanation in the deployed model.
ConcurrentExplanationSpecOverride map[string]*ExplanationSpecOverride `protobuf:"bytes,6,rep,name=concurrent_explanation_spec_override,json=concurrentExplanationSpecOverride,proto3" json:"concurrent_explanation_spec_override,omitempty" protobuf_key:"bytes,1,opt,name=key,proto3" protobuf_val:"bytes,2,opt,name=value,proto3"`
// If specified, this ExplainRequest will be served by the chosen
// DeployedModel, overriding
// [Endpoint.traffic_split][google.cloud.aiplatform.v1beta1.Endpoint.traffic_split].
DeployedModelId string `protobuf:"bytes,3,opt,name=deployed_model_id,json=deployedModelId,proto3" json:"deployed_model_id,omitempty"`
}
func (x *ExplainRequest) Reset() {
*x = ExplainRequest{}
if protoimpl.UnsafeEnabled {
mi := &file_google_cloud_aiplatform_v1beta1_prediction_service_proto_msgTypes[5]
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
ms.StoreMessageInfo(mi)
}
}
func (x *ExplainRequest) String() string {
return protoimpl.X.MessageStringOf(x)
}
func (*ExplainRequest) ProtoMessage() {}
func (x *ExplainRequest) ProtoReflect() protoreflect.Message {
mi := &file_google_cloud_aiplatform_v1beta1_prediction_service_proto_msgTypes[5]
if protoimpl.UnsafeEnabled && x != nil {
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
if ms.LoadMessageInfo() == nil {
ms.StoreMessageInfo(mi)
}
return ms
}
return mi.MessageOf(x)
}
// Deprecated: Use ExplainRequest.ProtoReflect.Descriptor instead.
func (*ExplainRequest) Descriptor() ([]byte, []int) {
return file_google_cloud_aiplatform_v1beta1_prediction_service_proto_rawDescGZIP(), []int{5}
}
func (x *ExplainRequest) GetEndpoint() string {
if x != nil {
return x.Endpoint
}
return ""
}
func (x *ExplainRequest) GetInstances() []*structpb.Value {
if x != nil {
return x.Instances
}
return nil
}
func (x *ExplainRequest) GetParameters() *structpb.Value {
if x != nil {
return x.Parameters
}
return nil
}
func (x *ExplainRequest) GetExplanationSpecOverride() *ExplanationSpecOverride {
if x != nil {
return x.ExplanationSpecOverride
}
return nil
}
func (x *ExplainRequest) GetConcurrentExplanationSpecOverride() map[string]*ExplanationSpecOverride {
if x != nil {
return x.ConcurrentExplanationSpecOverride
}
return nil
}
func (x *ExplainRequest) GetDeployedModelId() string {
if x != nil {
return x.DeployedModelId
}
return ""
}
// Response message for
// [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain].
type ExplainResponse struct {
state protoimpl.MessageState
sizeCache protoimpl.SizeCache
unknownFields protoimpl.UnknownFields
// The explanations of the Model's
// [PredictResponse.predictions][google.cloud.aiplatform.v1beta1.PredictResponse.predictions].
//
// It has the same number of elements as
// [instances][google.cloud.aiplatform.v1beta1.ExplainRequest.instances] to be
// explained.
Explanations []*Explanation `protobuf:"bytes,1,rep,name=explanations,proto3" json:"explanations,omitempty"`
// This field stores the results of the explanations run in parallel with
// the default explanation strategy/method.
ConcurrentExplanations map[string]*ExplainResponse_ConcurrentExplanation `protobuf:"bytes,4,rep,name=concurrent_explanations,json=concurrentExplanations,proto3" json:"concurrent_explanations,omitempty" protobuf_key:"bytes,1,opt,name=key,proto3" protobuf_val:"bytes,2,opt,name=value,proto3"`
// ID of the Endpoint's DeployedModel that served this explanation.
DeployedModelId string `protobuf:"bytes,2,opt,name=deployed_model_id,json=deployedModelId,proto3" json:"deployed_model_id,omitempty"`
// The predictions that are the output of the predictions call.
// Same as
// [PredictResponse.predictions][google.cloud.aiplatform.v1beta1.PredictResponse.predictions].
Predictions []*structpb.Value `protobuf:"bytes,3,rep,name=predictions,proto3" json:"predictions,omitempty"`
}
func (x *ExplainResponse) Reset() {
*x = ExplainResponse{}
if protoimpl.UnsafeEnabled {
mi := &file_google_cloud_aiplatform_v1beta1_prediction_service_proto_msgTypes[6]
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
ms.StoreMessageInfo(mi)
}
}
func (x *ExplainResponse) String() string {
return protoimpl.X.MessageStringOf(x)
}
func (*ExplainResponse) ProtoMessage() {}
func (x *ExplainResponse) ProtoReflect() protoreflect.Message {
mi := &file_google_cloud_aiplatform_v1beta1_prediction_service_proto_msgTypes[6]
if protoimpl.UnsafeEnabled && x != nil {
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
if ms.LoadMessageInfo() == nil {
ms.StoreMessageInfo(mi)
}
return ms
}
return mi.MessageOf(x)
}
// Deprecated: Use ExplainResponse.ProtoReflect.Descriptor instead.
func (*ExplainResponse) Descriptor() ([]byte, []int) {
return file_google_cloud_aiplatform_v1beta1_prediction_service_proto_rawDescGZIP(), []int{6}
}
func (x *ExplainResponse) GetExplanations() []*Explanation {
if x != nil {
return x.Explanations
}
return nil
}
func (x *ExplainResponse) GetConcurrentExplanations() map[string]*ExplainResponse_ConcurrentExplanation {
if x != nil {
return x.ConcurrentExplanations
}
return nil
}
func (x *ExplainResponse) GetDeployedModelId() string {
if x != nil {
return x.DeployedModelId
}
return ""
}
func (x *ExplainResponse) GetPredictions() []*structpb.Value {
if x != nil {
return x.Predictions
}
return nil
}
// Request message for
// [PredictionService.CountTokens][google.cloud.aiplatform.v1beta1.PredictionService.CountTokens].
type CountTokensRequest struct {
state protoimpl.MessageState
sizeCache protoimpl.SizeCache
unknownFields protoimpl.UnknownFields
// Required. The name of the Endpoint requested to perform token counting.
// Format:
// `projects/{project}/locations/{location}/endpoints/{endpoint}`
Endpoint string `protobuf:"bytes,1,opt,name=endpoint,proto3" json:"endpoint,omitempty"`
// Required. The instances that are the input to token counting call.
// Schema is identical to the prediction schema of the underlying model.
Instances []*structpb.Value `protobuf:"bytes,2,rep,name=instances,proto3" json:"instances,omitempty"`
}
func (x *CountTokensRequest) Reset() {
*x = CountTokensRequest{}
if protoimpl.UnsafeEnabled {
mi := &file_google_cloud_aiplatform_v1beta1_prediction_service_proto_msgTypes[7]
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
ms.StoreMessageInfo(mi)
}
}
func (x *CountTokensRequest) String() string {
return protoimpl.X.MessageStringOf(x)
}
func (*CountTokensRequest) ProtoMessage() {}
func (x *CountTokensRequest) ProtoReflect() protoreflect.Message {
mi := &file_google_cloud_aiplatform_v1beta1_prediction_service_proto_msgTypes[7]
if protoimpl.UnsafeEnabled && x != nil {
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
if ms.LoadMessageInfo() == nil {
ms.StoreMessageInfo(mi)
}
return ms
}
return mi.MessageOf(x)
}
// Deprecated: Use CountTokensRequest.ProtoReflect.Descriptor instead.
func (*CountTokensRequest) Descriptor() ([]byte, []int) {
return file_google_cloud_aiplatform_v1beta1_prediction_service_proto_rawDescGZIP(), []int{7}
}
func (x *CountTokensRequest) GetEndpoint() string {
if x != nil {
return x.Endpoint
}
return ""
}
func (x *CountTokensRequest) GetInstances() []*structpb.Value {
if x != nil {
return x.Instances
}
return nil
}
// Response message for
// [PredictionService.CountTokens][google.cloud.aiplatform.v1beta1.PredictionService.CountTokens].
type CountTokensResponse struct {
state protoimpl.MessageState
sizeCache protoimpl.SizeCache
unknownFields protoimpl.UnknownFields
// The total number of tokens counted across all instances from the request.
TotalTokens int32 `protobuf:"varint,1,opt,name=total_tokens,json=totalTokens,proto3" json:"total_tokens,omitempty"`
// The total number of billable characters counted across all instances from
// the request.
TotalBillableCharacters int32 `protobuf:"varint,2,opt,name=total_billable_characters,json=totalBillableCharacters,proto3" json:"total_billable_characters,omitempty"`
}
func (x *CountTokensResponse) Reset() {
*x = CountTokensResponse{}
if protoimpl.UnsafeEnabled {
mi := &file_google_cloud_aiplatform_v1beta1_prediction_service_proto_msgTypes[8]
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
ms.StoreMessageInfo(mi)
}
}
func (x *CountTokensResponse) String() string {
return protoimpl.X.MessageStringOf(x)
}
func (*CountTokensResponse) ProtoMessage() {}
func (x *CountTokensResponse) ProtoReflect() protoreflect.Message {
mi := &file_google_cloud_aiplatform_v1beta1_prediction_service_proto_msgTypes[8]
if protoimpl.UnsafeEnabled && x != nil {
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
if ms.LoadMessageInfo() == nil {
ms.StoreMessageInfo(mi)
}
return ms
}
return mi.MessageOf(x)
}
// Deprecated: Use CountTokensResponse.ProtoReflect.Descriptor instead.
func (*CountTokensResponse) Descriptor() ([]byte, []int) {
return file_google_cloud_aiplatform_v1beta1_prediction_service_proto_rawDescGZIP(), []int{8}
}
func (x *CountTokensResponse) GetTotalTokens() int32 {
if x != nil {
return x.TotalTokens
}
return 0
}
func (x *CountTokensResponse) GetTotalBillableCharacters() int32 {
if x != nil {
return x.TotalBillableCharacters
}
return 0
}
// This message is a wrapper grouping Concurrent Explanations.
type ExplainResponse_ConcurrentExplanation struct {
state protoimpl.MessageState
sizeCache protoimpl.SizeCache
unknownFields protoimpl.UnknownFields
// The explanations of the Model's
// [PredictResponse.predictions][google.cloud.aiplatform.v1beta1.PredictResponse.predictions].
//
// It has the same number of elements as
// [instances][google.cloud.aiplatform.v1beta1.ExplainRequest.instances] to
// be explained.
Explanations []*Explanation `protobuf:"bytes,1,rep,name=explanations,proto3" json:"explanations,omitempty"`
}
func (x *ExplainResponse_ConcurrentExplanation) Reset() {
*x = ExplainResponse_ConcurrentExplanation{}
if protoimpl.UnsafeEnabled {
mi := &file_google_cloud_aiplatform_v1beta1_prediction_service_proto_msgTypes[10]
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
ms.StoreMessageInfo(mi)
}
}
func (x *ExplainResponse_ConcurrentExplanation) String() string {
return protoimpl.X.MessageStringOf(x)
}
func (*ExplainResponse_ConcurrentExplanation) ProtoMessage() {}
func (x *ExplainResponse_ConcurrentExplanation) ProtoReflect() protoreflect.Message {
mi := &file_google_cloud_aiplatform_v1beta1_prediction_service_proto_msgTypes[10]
if protoimpl.UnsafeEnabled && x != nil {
ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
if ms.LoadMessageInfo() == nil {
ms.StoreMessageInfo(mi)
}
return ms
}
return mi.MessageOf(x)
}
// Deprecated: Use ExplainResponse_ConcurrentExplanation.ProtoReflect.Descriptor instead.
func (*ExplainResponse_ConcurrentExplanation) Descriptor() ([]byte, []int) {
return file_google_cloud_aiplatform_v1beta1_prediction_service_proto_rawDescGZIP(), []int{6, 0}
}
func (x *ExplainResponse_ConcurrentExplanation) GetExplanations() []*Explanation {
if x != nil {
return x.Explanations
}
return nil
}
var File_google_cloud_aiplatform_v1beta1_prediction_service_proto protoreflect.FileDescriptor
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}
var (
file_google_cloud_aiplatform_v1beta1_prediction_service_proto_rawDescOnce sync.Once
file_google_cloud_aiplatform_v1beta1_prediction_service_proto_rawDescData = file_google_cloud_aiplatform_v1beta1_prediction_service_proto_rawDesc
)
func file_google_cloud_aiplatform_v1beta1_prediction_service_proto_rawDescGZIP() []byte {
file_google_cloud_aiplatform_v1beta1_prediction_service_proto_rawDescOnce.Do(func() {
file_google_cloud_aiplatform_v1beta1_prediction_service_proto_rawDescData = protoimpl.X.CompressGZIP(file_google_cloud_aiplatform_v1beta1_prediction_service_proto_rawDescData)
})
return file_google_cloud_aiplatform_v1beta1_prediction_service_proto_rawDescData
}
var file_google_cloud_aiplatform_v1beta1_prediction_service_proto_msgTypes = make([]protoimpl.MessageInfo, 12)
var file_google_cloud_aiplatform_v1beta1_prediction_service_proto_goTypes = []interface{}{
(*PredictRequest)(nil), // 0: google.cloud.aiplatform.v1beta1.PredictRequest
(*PredictResponse)(nil), // 1: google.cloud.aiplatform.v1beta1.PredictResponse
(*RawPredictRequest)(nil), // 2: google.cloud.aiplatform.v1beta1.RawPredictRequest
(*StreamingPredictRequest)(nil), // 3: google.cloud.aiplatform.v1beta1.StreamingPredictRequest
(*StreamingPredictResponse)(nil), // 4: google.cloud.aiplatform.v1beta1.StreamingPredictResponse
(*ExplainRequest)(nil), // 5: google.cloud.aiplatform.v1beta1.ExplainRequest
(*ExplainResponse)(nil), // 6: google.cloud.aiplatform.v1beta1.ExplainResponse
(*CountTokensRequest)(nil), // 7: google.cloud.aiplatform.v1beta1.CountTokensRequest
(*CountTokensResponse)(nil), // 8: google.cloud.aiplatform.v1beta1.CountTokensResponse
nil, // 9: google.cloud.aiplatform.v1beta1.ExplainRequest.ConcurrentExplanationSpecOverrideEntry
(*ExplainResponse_ConcurrentExplanation)(nil), // 10: google.cloud.aiplatform.v1beta1.ExplainResponse.ConcurrentExplanation
nil, // 11: google.cloud.aiplatform.v1beta1.ExplainResponse.ConcurrentExplanationsEntry
(*structpb.Value)(nil), // 12: google.protobuf.Value
(*httpbody.HttpBody)(nil), // 13: google.api.HttpBody
(*Tensor)(nil), // 14: google.cloud.aiplatform.v1beta1.Tensor
(*ExplanationSpecOverride)(nil), // 15: google.cloud.aiplatform.v1beta1.ExplanationSpecOverride
(*Explanation)(nil), // 16: google.cloud.aiplatform.v1beta1.Explanation
}
var file_google_cloud_aiplatform_v1beta1_prediction_service_proto_depIdxs = []int32{
12, // 0: google.cloud.aiplatform.v1beta1.PredictRequest.instances:type_name -> google.protobuf.Value
12, // 1: google.cloud.aiplatform.v1beta1.PredictRequest.parameters:type_name -> google.protobuf.Value
12, // 2: google.cloud.aiplatform.v1beta1.PredictResponse.predictions:type_name -> google.protobuf.Value
12, // 3: google.cloud.aiplatform.v1beta1.PredictResponse.metadata:type_name -> google.protobuf.Value
13, // 4: google.cloud.aiplatform.v1beta1.RawPredictRequest.http_body:type_name -> google.api.HttpBody
14, // 5: google.cloud.aiplatform.v1beta1.StreamingPredictRequest.inputs:type_name -> google.cloud.aiplatform.v1beta1.Tensor
14, // 6: google.cloud.aiplatform.v1beta1.StreamingPredictRequest.parameters:type_name -> google.cloud.aiplatform.v1beta1.Tensor
14, // 7: google.cloud.aiplatform.v1beta1.StreamingPredictResponse.outputs:type_name -> google.cloud.aiplatform.v1beta1.Tensor
14, // 8: google.cloud.aiplatform.v1beta1.StreamingPredictResponse.parameters:type_name -> google.cloud.aiplatform.v1beta1.Tensor
12, // 9: google.cloud.aiplatform.v1beta1.ExplainRequest.instances:type_name -> google.protobuf.Value
12, // 10: google.cloud.aiplatform.v1beta1.ExplainRequest.parameters:type_name -> google.protobuf.Value
15, // 11: google.cloud.aiplatform.v1beta1.ExplainRequest.explanation_spec_override:type_name -> google.cloud.aiplatform.v1beta1.ExplanationSpecOverride
9, // 12: google.cloud.aiplatform.v1beta1.ExplainRequest.concurrent_explanation_spec_override:type_name -> google.cloud.aiplatform.v1beta1.ExplainRequest.ConcurrentExplanationSpecOverrideEntry
16, // 13: google.cloud.aiplatform.v1beta1.ExplainResponse.explanations:type_name -> google.cloud.aiplatform.v1beta1.Explanation
11, // 14: google.cloud.aiplatform.v1beta1.ExplainResponse.concurrent_explanations:type_name -> google.cloud.aiplatform.v1beta1.ExplainResponse.ConcurrentExplanationsEntry
12, // 15: google.cloud.aiplatform.v1beta1.ExplainResponse.predictions:type_name -> google.protobuf.Value
12, // 16: google.cloud.aiplatform.v1beta1.CountTokensRequest.instances:type_name -> google.protobuf.Value
15, // 17: google.cloud.aiplatform.v1beta1.ExplainRequest.ConcurrentExplanationSpecOverrideEntry.value:type_name -> google.cloud.aiplatform.v1beta1.ExplanationSpecOverride
16, // 18: google.cloud.aiplatform.v1beta1.ExplainResponse.ConcurrentExplanation.explanations:type_name -> google.cloud.aiplatform.v1beta1.Explanation
10, // 19: google.cloud.aiplatform.v1beta1.ExplainResponse.ConcurrentExplanationsEntry.value:type_name -> google.cloud.aiplatform.v1beta1.ExplainResponse.ConcurrentExplanation
0, // 20: google.cloud.aiplatform.v1beta1.PredictionService.Predict:input_type -> google.cloud.aiplatform.v1beta1.PredictRequest
2, // 21: google.cloud.aiplatform.v1beta1.PredictionService.RawPredict:input_type -> google.cloud.aiplatform.v1beta1.RawPredictRequest
3, // 22: google.cloud.aiplatform.v1beta1.PredictionService.ServerStreamingPredict:input_type -> google.cloud.aiplatform.v1beta1.StreamingPredictRequest
5, // 23: google.cloud.aiplatform.v1beta1.PredictionService.Explain:input_type -> google.cloud.aiplatform.v1beta1.ExplainRequest
7, // 24: google.cloud.aiplatform.v1beta1.PredictionService.CountTokens:input_type -> google.cloud.aiplatform.v1beta1.CountTokensRequest
1, // 25: google.cloud.aiplatform.v1beta1.PredictionService.Predict:output_type -> google.cloud.aiplatform.v1beta1.PredictResponse
13, // 26: google.cloud.aiplatform.v1beta1.PredictionService.RawPredict:output_type -> google.api.HttpBody
4, // 27: google.cloud.aiplatform.v1beta1.PredictionService.ServerStreamingPredict:output_type -> google.cloud.aiplatform.v1beta1.StreamingPredictResponse
6, // 28: google.cloud.aiplatform.v1beta1.PredictionService.Explain:output_type -> google.cloud.aiplatform.v1beta1.ExplainResponse
8, // 29: google.cloud.aiplatform.v1beta1.PredictionService.CountTokens:output_type -> google.cloud.aiplatform.v1beta1.CountTokensResponse
25, // [25:30] is the sub-list for method output_type
20, // [20:25] is the sub-list for method input_type
20, // [20:20] is the sub-list for extension type_name
20, // [20:20] is the sub-list for extension extendee
0, // [0:20] is the sub-list for field type_name
}
func init() { file_google_cloud_aiplatform_v1beta1_prediction_service_proto_init() }
func file_google_cloud_aiplatform_v1beta1_prediction_service_proto_init() {
if File_google_cloud_aiplatform_v1beta1_prediction_service_proto != nil {
return
}
file_google_cloud_aiplatform_v1beta1_explanation_proto_init()
file_google_cloud_aiplatform_v1beta1_types_proto_init()
if !protoimpl.UnsafeEnabled {
file_google_cloud_aiplatform_v1beta1_prediction_service_proto_msgTypes[0].Exporter = func(v interface{}, i int) interface{} {
switch v := v.(*PredictRequest); i {
case 0:
return &v.state
case 1:
return &v.sizeCache
case 2:
return &v.unknownFields
default:
return nil
}
}
file_google_cloud_aiplatform_v1beta1_prediction_service_proto_msgTypes[1].Exporter = func(v interface{}, i int) interface{} {
switch v := v.(*PredictResponse); i {
case 0:
return &v.state
case 1:
return &v.sizeCache
case 2:
return &v.unknownFields
default:
return nil
}
}
file_google_cloud_aiplatform_v1beta1_prediction_service_proto_msgTypes[2].Exporter = func(v interface{}, i int) interface{} {
switch v := v.(*RawPredictRequest); i {
case 0:
return &v.state
case 1:
return &v.sizeCache
case 2:
return &v.unknownFields
default:
return nil
}
}
file_google_cloud_aiplatform_v1beta1_prediction_service_proto_msgTypes[3].Exporter = func(v interface{}, i int) interface{} {
switch v := v.(*StreamingPredictRequest); i {
case 0:
return &v.state
case 1:
return &v.sizeCache
case 2:
return &v.unknownFields
default:
return nil
}
}
file_google_cloud_aiplatform_v1beta1_prediction_service_proto_msgTypes[4].Exporter = func(v interface{}, i int) interface{} {
switch v := v.(*StreamingPredictResponse); i {
case 0:
return &v.state
case 1:
return &v.sizeCache
case 2:
return &v.unknownFields
default:
return nil
}
}
file_google_cloud_aiplatform_v1beta1_prediction_service_proto_msgTypes[5].Exporter = func(v interface{}, i int) interface{} {
switch v := v.(*ExplainRequest); i {
case 0:
return &v.state
case 1:
return &v.sizeCache
case 2:
return &v.unknownFields
default:
return nil
}
}
file_google_cloud_aiplatform_v1beta1_prediction_service_proto_msgTypes[6].Exporter = func(v interface{}, i int) interface{} {
switch v := v.(*ExplainResponse); i {
case 0:
return &v.state
case 1:
return &v.sizeCache
case 2:
return &v.unknownFields
default:
return nil
}
}
file_google_cloud_aiplatform_v1beta1_prediction_service_proto_msgTypes[7].Exporter = func(v interface{}, i int) interface{} {
switch v := v.(*CountTokensRequest); i {
case 0:
return &v.state
case 1:
return &v.sizeCache
case 2:
return &v.unknownFields
default:
return nil
}
}
file_google_cloud_aiplatform_v1beta1_prediction_service_proto_msgTypes[8].Exporter = func(v interface{}, i int) interface{} {
switch v := v.(*CountTokensResponse); i {
case 0:
return &v.state
case 1:
return &v.sizeCache
case 2:
return &v.unknownFields
default:
return nil
}
}
file_google_cloud_aiplatform_v1beta1_prediction_service_proto_msgTypes[10].Exporter = func(v interface{}, i int) interface{} {
switch v := v.(*ExplainResponse_ConcurrentExplanation); i {
case 0:
return &v.state
case 1:
return &v.sizeCache
case 2:
return &v.unknownFields
default:
return nil
}
}
}
type x struct{}
out := protoimpl.TypeBuilder{
File: protoimpl.DescBuilder{
GoPackagePath: reflect.TypeOf(x{}).PkgPath(),
RawDescriptor: file_google_cloud_aiplatform_v1beta1_prediction_service_proto_rawDesc,
NumEnums: 0,
NumMessages: 12,
NumExtensions: 0,
NumServices: 1,
},
GoTypes: file_google_cloud_aiplatform_v1beta1_prediction_service_proto_goTypes,
DependencyIndexes: file_google_cloud_aiplatform_v1beta1_prediction_service_proto_depIdxs,
MessageInfos: file_google_cloud_aiplatform_v1beta1_prediction_service_proto_msgTypes,
}.Build()
File_google_cloud_aiplatform_v1beta1_prediction_service_proto = out.File
file_google_cloud_aiplatform_v1beta1_prediction_service_proto_rawDesc = nil
file_google_cloud_aiplatform_v1beta1_prediction_service_proto_goTypes = nil
file_google_cloud_aiplatform_v1beta1_prediction_service_proto_depIdxs = nil
}
// Reference imports to suppress errors if they are not otherwise used.
var _ context.Context
var _ grpc.ClientConnInterface
// This is a compile-time assertion to ensure that this generated file
// is compatible with the grpc package it is being compiled against.
const _ = grpc.SupportPackageIsVersion6
// PredictionServiceClient is the client API for PredictionService service.
//
// For semantics around ctx use and closing/ending streaming RPCs, please refer to https://godoc.org/google.golang.org/grpc#ClientConn.NewStream.
type PredictionServiceClient interface {
// Perform an online prediction.
Predict(ctx context.Context, in *PredictRequest, opts ...grpc.CallOption) (*PredictResponse, error)
// Perform an online prediction with an arbitrary HTTP payload.
//
// The response includes the following HTTP headers:
//
// * `X-Vertex-AI-Endpoint-Id`: ID of the
// [Endpoint][google.cloud.aiplatform.v1beta1.Endpoint] that served this
// prediction.
//
// * `X-Vertex-AI-Deployed-Model-Id`: ID of the Endpoint's
// [DeployedModel][google.cloud.aiplatform.v1beta1.DeployedModel] that served
// this prediction.
RawPredict(ctx context.Context, in *RawPredictRequest, opts ...grpc.CallOption) (*httpbody.HttpBody, error)
// Perform a server-side streaming online prediction request for Vertex
// LLM streaming.
ServerStreamingPredict(ctx context.Context, in *StreamingPredictRequest, opts ...grpc.CallOption) (PredictionService_ServerStreamingPredictClient, error)
// Perform an online explanation.
//
// If
// [deployed_model_id][google.cloud.aiplatform.v1beta1.ExplainRequest.deployed_model_id]
// is specified, the corresponding DeployModel must have
// [explanation_spec][google.cloud.aiplatform.v1beta1.DeployedModel.explanation_spec]
// populated. If
// [deployed_model_id][google.cloud.aiplatform.v1beta1.ExplainRequest.deployed_model_id]
// is not specified, all DeployedModels must have
// [explanation_spec][google.cloud.aiplatform.v1beta1.DeployedModel.explanation_spec]
// populated.
Explain(ctx context.Context, in *ExplainRequest, opts ...grpc.CallOption) (*ExplainResponse, error)
// Perform a token counting.
CountTokens(ctx context.Context, in *CountTokensRequest, opts ...grpc.CallOption) (*CountTokensResponse, error)
}
type predictionServiceClient struct {
cc grpc.ClientConnInterface
}
func NewPredictionServiceClient(cc grpc.ClientConnInterface) PredictionServiceClient {
return &predictionServiceClient{cc}
}
func (c *predictionServiceClient) Predict(ctx context.Context, in *PredictRequest, opts ...grpc.CallOption) (*PredictResponse, error) {
out := new(PredictResponse)
err := c.cc.Invoke(ctx, "/google.cloud.aiplatform.v1beta1.PredictionService/Predict", in, out, opts...)
if err != nil {
return nil, err
}
return out, nil
}
func (c *predictionServiceClient) RawPredict(ctx context.Context, in *RawPredictRequest, opts ...grpc.CallOption) (*httpbody.HttpBody, error) {
out := new(httpbody.HttpBody)
err := c.cc.Invoke(ctx, "/google.cloud.aiplatform.v1beta1.PredictionService/RawPredict", in, out, opts...)
if err != nil {
return nil, err
}
return out, nil
}
func (c *predictionServiceClient) ServerStreamingPredict(ctx context.Context, in *StreamingPredictRequest, opts ...grpc.CallOption) (PredictionService_ServerStreamingPredictClient, error) {
stream, err := c.cc.NewStream(ctx, &_PredictionService_serviceDesc.Streams[0], "/google.cloud.aiplatform.v1beta1.PredictionService/ServerStreamingPredict", opts...)
if err != nil {
return nil, err
}
x := &predictionServiceServerStreamingPredictClient{stream}
if err := x.ClientStream.SendMsg(in); err != nil {
return nil, err
}
if err := x.ClientStream.CloseSend(); err != nil {
return nil, err
}
return x, nil
}
type PredictionService_ServerStreamingPredictClient interface {
Recv() (*StreamingPredictResponse, error)
grpc.ClientStream
}
type predictionServiceServerStreamingPredictClient struct {
grpc.ClientStream
}
func (x *predictionServiceServerStreamingPredictClient) Recv() (*StreamingPredictResponse, error) {
m := new(StreamingPredictResponse)
if err := x.ClientStream.RecvMsg(m); err != nil {
return nil, err
}
return m, nil
}
func (c *predictionServiceClient) Explain(ctx context.Context, in *ExplainRequest, opts ...grpc.CallOption) (*ExplainResponse, error) {
out := new(ExplainResponse)
err := c.cc.Invoke(ctx, "/google.cloud.aiplatform.v1beta1.PredictionService/Explain", in, out, opts...)
if err != nil {
return nil, err
}
return out, nil
}
func (c *predictionServiceClient) CountTokens(ctx context.Context, in *CountTokensRequest, opts ...grpc.CallOption) (*CountTokensResponse, error) {
out := new(CountTokensResponse)
err := c.cc.Invoke(ctx, "/google.cloud.aiplatform.v1beta1.PredictionService/CountTokens", in, out, opts...)
if err != nil {
return nil, err
}
return out, nil
}
// PredictionServiceServer is the server API for PredictionService service.
type PredictionServiceServer interface {
// Perform an online prediction.
Predict(context.Context, *PredictRequest) (*PredictResponse, error)
// Perform an online prediction with an arbitrary HTTP payload.
//
// The response includes the following HTTP headers:
//
// * `X-Vertex-AI-Endpoint-Id`: ID of the
// [Endpoint][google.cloud.aiplatform.v1beta1.Endpoint] that served this
// prediction.
//
// * `X-Vertex-AI-Deployed-Model-Id`: ID of the Endpoint's
// [DeployedModel][google.cloud.aiplatform.v1beta1.DeployedModel] that served
// this prediction.
RawPredict(context.Context, *RawPredictRequest) (*httpbody.HttpBody, error)
// Perform a server-side streaming online prediction request for Vertex
// LLM streaming.
ServerStreamingPredict(*StreamingPredictRequest, PredictionService_ServerStreamingPredictServer) error
// Perform an online explanation.
//
// If
// [deployed_model_id][google.cloud.aiplatform.v1beta1.ExplainRequest.deployed_model_id]
// is specified, the corresponding DeployModel must have
// [explanation_spec][google.cloud.aiplatform.v1beta1.DeployedModel.explanation_spec]
// populated. If
// [deployed_model_id][google.cloud.aiplatform.v1beta1.ExplainRequest.deployed_model_id]
// is not specified, all DeployedModels must have
// [explanation_spec][google.cloud.aiplatform.v1beta1.DeployedModel.explanation_spec]
// populated.
Explain(context.Context, *ExplainRequest) (*ExplainResponse, error)
// Perform a token counting.
CountTokens(context.Context, *CountTokensRequest) (*CountTokensResponse, error)
}
// UnimplementedPredictionServiceServer can be embedded to have forward compatible implementations.
type UnimplementedPredictionServiceServer struct {
}
func (*UnimplementedPredictionServiceServer) Predict(context.Context, *PredictRequest) (*PredictResponse, error) {
return nil, status.Errorf(codes.Unimplemented, "method Predict not implemented")
}
func (*UnimplementedPredictionServiceServer) RawPredict(context.Context, *RawPredictRequest) (*httpbody.HttpBody, error) {
return nil, status.Errorf(codes.Unimplemented, "method RawPredict not implemented")
}
func (*UnimplementedPredictionServiceServer) ServerStreamingPredict(*StreamingPredictRequest, PredictionService_ServerStreamingPredictServer) error {
return status.Errorf(codes.Unimplemented, "method ServerStreamingPredict not implemented")
}
func (*UnimplementedPredictionServiceServer) Explain(context.Context, *ExplainRequest) (*ExplainResponse, error) {
return nil, status.Errorf(codes.Unimplemented, "method Explain not implemented")
}
func (*UnimplementedPredictionServiceServer) CountTokens(context.Context, *CountTokensRequest) (*CountTokensResponse, error) {
return nil, status.Errorf(codes.Unimplemented, "method CountTokens not implemented")
}
func RegisterPredictionServiceServer(s *grpc.Server, srv PredictionServiceServer) {
s.RegisterService(&_PredictionService_serviceDesc, srv)
}
func _PredictionService_Predict_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
in := new(PredictRequest)
if err := dec(in); err != nil {
return nil, err
}
if interceptor == nil {
return srv.(PredictionServiceServer).Predict(ctx, in)
}
info := &grpc.UnaryServerInfo{
Server: srv,
FullMethod: "/google.cloud.aiplatform.v1beta1.PredictionService/Predict",
}
handler := func(ctx context.Context, req interface{}) (interface{}, error) {
return srv.(PredictionServiceServer).Predict(ctx, req.(*PredictRequest))
}
return interceptor(ctx, in, info, handler)
}
func _PredictionService_RawPredict_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
in := new(RawPredictRequest)
if err := dec(in); err != nil {
return nil, err
}
if interceptor == nil {
return srv.(PredictionServiceServer).RawPredict(ctx, in)
}
info := &grpc.UnaryServerInfo{
Server: srv,
FullMethod: "/google.cloud.aiplatform.v1beta1.PredictionService/RawPredict",
}
handler := func(ctx context.Context, req interface{}) (interface{}, error) {
return srv.(PredictionServiceServer).RawPredict(ctx, req.(*RawPredictRequest))
}
return interceptor(ctx, in, info, handler)
}
func _PredictionService_ServerStreamingPredict_Handler(srv interface{}, stream grpc.ServerStream) error {
m := new(StreamingPredictRequest)
if err := stream.RecvMsg(m); err != nil {
return err
}
return srv.(PredictionServiceServer).ServerStreamingPredict(m, &predictionServiceServerStreamingPredictServer{stream})
}
type PredictionService_ServerStreamingPredictServer interface {
Send(*StreamingPredictResponse) error
grpc.ServerStream
}
type predictionServiceServerStreamingPredictServer struct {
grpc.ServerStream
}
func (x *predictionServiceServerStreamingPredictServer) Send(m *StreamingPredictResponse) error {
return x.ServerStream.SendMsg(m)
}
func _PredictionService_Explain_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
in := new(ExplainRequest)
if err := dec(in); err != nil {
return nil, err
}
if interceptor == nil {
return srv.(PredictionServiceServer).Explain(ctx, in)
}
info := &grpc.UnaryServerInfo{
Server: srv,
FullMethod: "/google.cloud.aiplatform.v1beta1.PredictionService/Explain",
}
handler := func(ctx context.Context, req interface{}) (interface{}, error) {
return srv.(PredictionServiceServer).Explain(ctx, req.(*ExplainRequest))
}
return interceptor(ctx, in, info, handler)
}
func _PredictionService_CountTokens_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
in := new(CountTokensRequest)
if err := dec(in); err != nil {
return nil, err
}
if interceptor == nil {
return srv.(PredictionServiceServer).CountTokens(ctx, in)
}
info := &grpc.UnaryServerInfo{
Server: srv,
FullMethod: "/google.cloud.aiplatform.v1beta1.PredictionService/CountTokens",
}
handler := func(ctx context.Context, req interface{}) (interface{}, error) {
return srv.(PredictionServiceServer).CountTokens(ctx, req.(*CountTokensRequest))
}
return interceptor(ctx, in, info, handler)
}
var _PredictionService_serviceDesc = grpc.ServiceDesc{
ServiceName: "google.cloud.aiplatform.v1beta1.PredictionService",
HandlerType: (*PredictionServiceServer)(nil),
Methods: []grpc.MethodDesc{
{
MethodName: "Predict",
Handler: _PredictionService_Predict_Handler,
},
{
MethodName: "RawPredict",
Handler: _PredictionService_RawPredict_Handler,
},
{
MethodName: "Explain",
Handler: _PredictionService_Explain_Handler,
},
{
MethodName: "CountTokens",
Handler: _PredictionService_CountTokens_Handler,
},
},
Streams: []grpc.StreamDesc{
{
StreamName: "ServerStreamingPredict",
Handler: _PredictionService_ServerStreamingPredict_Handler,
ServerStreams: true,
},
},
Metadata: "google/cloud/aiplatform/v1beta1/prediction_service.proto",
}