// 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"`
	// 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) 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"`
	// 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) 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
}

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, 9)
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
	(*structpb.Value)(nil),           // 9: google.protobuf.Value
	(*httpbody.HttpBody)(nil),        // 10: google.api.HttpBody
	(*Tensor)(nil),                   // 11: google.cloud.aiplatform.v1beta1.Tensor
	(*ExplanationSpecOverride)(nil),  // 12: google.cloud.aiplatform.v1beta1.ExplanationSpecOverride
	(*Explanation)(nil),              // 13: google.cloud.aiplatform.v1beta1.Explanation
}
var file_google_cloud_aiplatform_v1beta1_prediction_service_proto_depIdxs = []int32{
	9,  // 0: google.cloud.aiplatform.v1beta1.PredictRequest.instances:type_name -> google.protobuf.Value
	9,  // 1: google.cloud.aiplatform.v1beta1.PredictRequest.parameters:type_name -> google.protobuf.Value
	9,  // 2: google.cloud.aiplatform.v1beta1.PredictResponse.predictions:type_name -> google.protobuf.Value
	9,  // 3: google.cloud.aiplatform.v1beta1.PredictResponse.metadata:type_name -> google.protobuf.Value
	10, // 4: google.cloud.aiplatform.v1beta1.RawPredictRequest.http_body:type_name -> google.api.HttpBody
	11, // 5: google.cloud.aiplatform.v1beta1.StreamingPredictRequest.inputs:type_name -> google.cloud.aiplatform.v1beta1.Tensor
	11, // 6: google.cloud.aiplatform.v1beta1.StreamingPredictRequest.parameters:type_name -> google.cloud.aiplatform.v1beta1.Tensor
	11, // 7: google.cloud.aiplatform.v1beta1.StreamingPredictResponse.outputs:type_name -> google.cloud.aiplatform.v1beta1.Tensor
	11, // 8: google.cloud.aiplatform.v1beta1.StreamingPredictResponse.parameters:type_name -> google.cloud.aiplatform.v1beta1.Tensor
	9,  // 9: google.cloud.aiplatform.v1beta1.ExplainRequest.instances:type_name -> google.protobuf.Value
	9,  // 10: google.cloud.aiplatform.v1beta1.ExplainRequest.parameters:type_name -> google.protobuf.Value
	12, // 11: google.cloud.aiplatform.v1beta1.ExplainRequest.explanation_spec_override:type_name -> google.cloud.aiplatform.v1beta1.ExplanationSpecOverride
	13, // 12: google.cloud.aiplatform.v1beta1.ExplainResponse.explanations:type_name -> google.cloud.aiplatform.v1beta1.Explanation
	9,  // 13: google.cloud.aiplatform.v1beta1.ExplainResponse.predictions:type_name -> google.protobuf.Value
	9,  // 14: google.cloud.aiplatform.v1beta1.CountTokensRequest.instances:type_name -> google.protobuf.Value
	0,  // 15: google.cloud.aiplatform.v1beta1.PredictionService.Predict:input_type -> google.cloud.aiplatform.v1beta1.PredictRequest
	2,  // 16: google.cloud.aiplatform.v1beta1.PredictionService.RawPredict:input_type -> google.cloud.aiplatform.v1beta1.RawPredictRequest
	3,  // 17: google.cloud.aiplatform.v1beta1.PredictionService.ServerStreamingPredict:input_type -> google.cloud.aiplatform.v1beta1.StreamingPredictRequest
	5,  // 18: google.cloud.aiplatform.v1beta1.PredictionService.Explain:input_type -> google.cloud.aiplatform.v1beta1.ExplainRequest
	7,  // 19: google.cloud.aiplatform.v1beta1.PredictionService.CountTokens:input_type -> google.cloud.aiplatform.v1beta1.CountTokensRequest
	1,  // 20: google.cloud.aiplatform.v1beta1.PredictionService.Predict:output_type -> google.cloud.aiplatform.v1beta1.PredictResponse
	10, // 21: google.cloud.aiplatform.v1beta1.PredictionService.RawPredict:output_type -> google.api.HttpBody
	4,  // 22: google.cloud.aiplatform.v1beta1.PredictionService.ServerStreamingPredict:output_type -> google.cloud.aiplatform.v1beta1.StreamingPredictResponse
	6,  // 23: google.cloud.aiplatform.v1beta1.PredictionService.Explain:output_type -> google.cloud.aiplatform.v1beta1.ExplainResponse
	8,  // 24: google.cloud.aiplatform.v1beta1.PredictionService.CountTokens:output_type -> google.cloud.aiplatform.v1beta1.CountTokensResponse
	20, // [20:25] is the sub-list for method output_type
	15, // [15:20] is the sub-list for method input_type
	15, // [15:15] is the sub-list for extension type_name
	15, // [15:15] is the sub-list for extension extendee
	0,  // [0:15] 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
			}
		}
	}
	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:   9,
			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",
}
