// Copyright 2026 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 v1.36.11
// 	protoc        v6.33.2
// source: google/cloud/aiplatform/v1/prediction_service.proto

package aiplatformpb

import (
	reflect "reflect"
	sync "sync"
	unsafe "unsafe"

	_ "google.golang.org/genproto/googleapis/api/annotations"
	httpbody "google.golang.org/genproto/googleapis/api/httpbody"
	protoreflect "google.golang.org/protobuf/reflect/protoreflect"
	protoimpl "google.golang.org/protobuf/runtime/protoimpl"
	structpb "google.golang.org/protobuf/types/known/structpb"
	timestamppb "google.golang.org/protobuf/types/known/timestamppb"
)

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)
)

// Blocked reason enumeration.
type GenerateContentResponse_PromptFeedback_BlockedReason int32

const (
	// Unspecified blocked reason.
	GenerateContentResponse_PromptFeedback_BLOCKED_REASON_UNSPECIFIED GenerateContentResponse_PromptFeedback_BlockedReason = 0
	// Candidates blocked due to safety.
	GenerateContentResponse_PromptFeedback_SAFETY GenerateContentResponse_PromptFeedback_BlockedReason = 1
	// Candidates blocked due to other reason.
	GenerateContentResponse_PromptFeedback_OTHER GenerateContentResponse_PromptFeedback_BlockedReason = 2
	// Candidates blocked due to the terms which are included from the
	// terminology blocklist.
	GenerateContentResponse_PromptFeedback_BLOCKLIST GenerateContentResponse_PromptFeedback_BlockedReason = 3
	// Candidates blocked due to prohibited content.
	GenerateContentResponse_PromptFeedback_PROHIBITED_CONTENT GenerateContentResponse_PromptFeedback_BlockedReason = 4
	// The user prompt was blocked by Model Armor.
	GenerateContentResponse_PromptFeedback_MODEL_ARMOR GenerateContentResponse_PromptFeedback_BlockedReason = 5
	// The user prompt was blocked due to jailbreak.
	GenerateContentResponse_PromptFeedback_JAILBREAK GenerateContentResponse_PromptFeedback_BlockedReason = 6
)

// Enum value maps for GenerateContentResponse_PromptFeedback_BlockedReason.
var (
	GenerateContentResponse_PromptFeedback_BlockedReason_name = map[int32]string{
		0: "BLOCKED_REASON_UNSPECIFIED",
		1: "SAFETY",
		2: "OTHER",
		3: "BLOCKLIST",
		4: "PROHIBITED_CONTENT",
		5: "MODEL_ARMOR",
		6: "JAILBREAK",
	}
	GenerateContentResponse_PromptFeedback_BlockedReason_value = map[string]int32{
		"BLOCKED_REASON_UNSPECIFIED": 0,
		"SAFETY":                     1,
		"OTHER":                      2,
		"BLOCKLIST":                  3,
		"PROHIBITED_CONTENT":         4,
		"MODEL_ARMOR":                5,
		"JAILBREAK":                  6,
	}
)

func (x GenerateContentResponse_PromptFeedback_BlockedReason) Enum() *GenerateContentResponse_PromptFeedback_BlockedReason {
	p := new(GenerateContentResponse_PromptFeedback_BlockedReason)
	*p = x
	return p
}

func (x GenerateContentResponse_PromptFeedback_BlockedReason) String() string {
	return protoimpl.X.EnumStringOf(x.Descriptor(), protoreflect.EnumNumber(x))
}

func (GenerateContentResponse_PromptFeedback_BlockedReason) Descriptor() protoreflect.EnumDescriptor {
	return file_google_cloud_aiplatform_v1_prediction_service_proto_enumTypes[0].Descriptor()
}

func (GenerateContentResponse_PromptFeedback_BlockedReason) Type() protoreflect.EnumType {
	return &file_google_cloud_aiplatform_v1_prediction_service_proto_enumTypes[0]
}

func (x GenerateContentResponse_PromptFeedback_BlockedReason) Number() protoreflect.EnumNumber {
	return protoreflect.EnumNumber(x)
}

// Deprecated: Use GenerateContentResponse_PromptFeedback_BlockedReason.Descriptor instead.
func (GenerateContentResponse_PromptFeedback_BlockedReason) EnumDescriptor() ([]byte, []int) {
	return file_google_cloud_aiplatform_v1_prediction_service_proto_rawDescGZIP(), []int{21, 0, 0}
}

// The type of traffic that this request was processed with, indicating
// which quota is consumed.
type GenerateContentResponse_UsageMetadata_TrafficType int32

const (
	// Unspecified request traffic type.
	GenerateContentResponse_UsageMetadata_TRAFFIC_TYPE_UNSPECIFIED GenerateContentResponse_UsageMetadata_TrafficType = 0
	// The request was processed using Pay-As-You-Go quota.
	GenerateContentResponse_UsageMetadata_ON_DEMAND GenerateContentResponse_UsageMetadata_TrafficType = 1
	// Type for Priority Pay-As-You-Go traffic.
	GenerateContentResponse_UsageMetadata_ON_DEMAND_PRIORITY GenerateContentResponse_UsageMetadata_TrafficType = 3
	// Type for Flex traffic.
	GenerateContentResponse_UsageMetadata_ON_DEMAND_FLEX GenerateContentResponse_UsageMetadata_TrafficType = 4
	// Type for Provisioned Throughput traffic.
	GenerateContentResponse_UsageMetadata_PROVISIONED_THROUGHPUT GenerateContentResponse_UsageMetadata_TrafficType = 2
)

// Enum value maps for GenerateContentResponse_UsageMetadata_TrafficType.
var (
	GenerateContentResponse_UsageMetadata_TrafficType_name = map[int32]string{
		0: "TRAFFIC_TYPE_UNSPECIFIED",
		1: "ON_DEMAND",
		3: "ON_DEMAND_PRIORITY",
		4: "ON_DEMAND_FLEX",
		2: "PROVISIONED_THROUGHPUT",
	}
	GenerateContentResponse_UsageMetadata_TrafficType_value = map[string]int32{
		"TRAFFIC_TYPE_UNSPECIFIED": 0,
		"ON_DEMAND":                1,
		"ON_DEMAND_PRIORITY":       3,
		"ON_DEMAND_FLEX":           4,
		"PROVISIONED_THROUGHPUT":   2,
	}
)

func (x GenerateContentResponse_UsageMetadata_TrafficType) Enum() *GenerateContentResponse_UsageMetadata_TrafficType {
	p := new(GenerateContentResponse_UsageMetadata_TrafficType)
	*p = x
	return p
}

func (x GenerateContentResponse_UsageMetadata_TrafficType) String() string {
	return protoimpl.X.EnumStringOf(x.Descriptor(), protoreflect.EnumNumber(x))
}

func (GenerateContentResponse_UsageMetadata_TrafficType) Descriptor() protoreflect.EnumDescriptor {
	return file_google_cloud_aiplatform_v1_prediction_service_proto_enumTypes[1].Descriptor()
}

func (GenerateContentResponse_UsageMetadata_TrafficType) Type() protoreflect.EnumType {
	return &file_google_cloud_aiplatform_v1_prediction_service_proto_enumTypes[1]
}

func (x GenerateContentResponse_UsageMetadata_TrafficType) Number() protoreflect.EnumNumber {
	return protoreflect.EnumNumber(x)
}

// Deprecated: Use GenerateContentResponse_UsageMetadata_TrafficType.Descriptor instead.
func (GenerateContentResponse_UsageMetadata_TrafficType) EnumDescriptor() ([]byte, []int) {
	return file_google_cloud_aiplatform_v1_prediction_service_proto_rawDescGZIP(), []int{21, 1, 0}
}

// Represents a downstream task the embeddings will be used for.
type EmbedContentRequest_EmbeddingTaskType int32

const (
	// Unset value, which will default to one of the other enum values.
	EmbedContentRequest_UNSPECIFIED EmbedContentRequest_EmbeddingTaskType = 0
	// Specifies the given text is a query in a search/retrieval setting.
	EmbedContentRequest_RETRIEVAL_QUERY EmbedContentRequest_EmbeddingTaskType = 2
	// Specifies the given text is a document from the corpus being searched.
	EmbedContentRequest_RETRIEVAL_DOCUMENT EmbedContentRequest_EmbeddingTaskType = 3
	// Specifies the given text will be used for STS.
	EmbedContentRequest_SEMANTIC_SIMILARITY EmbedContentRequest_EmbeddingTaskType = 4
	// Specifies that the given text will be classified.
	EmbedContentRequest_CLASSIFICATION EmbedContentRequest_EmbeddingTaskType = 5
	// Specifies that the embeddings will be used for clustering.
	EmbedContentRequest_CLUSTERING EmbedContentRequest_EmbeddingTaskType = 6
	// Specifies that the embeddings will be used for question answering.
	EmbedContentRequest_QUESTION_ANSWERING EmbedContentRequest_EmbeddingTaskType = 7
	// Specifies that the embeddings will be used for fact verification.
	EmbedContentRequest_FACT_VERIFICATION EmbedContentRequest_EmbeddingTaskType = 8
	// Specifies that the embeddings will be used for code retrieval.
	EmbedContentRequest_CODE_RETRIEVAL_QUERY EmbedContentRequest_EmbeddingTaskType = 9
)

// Enum value maps for EmbedContentRequest_EmbeddingTaskType.
var (
	EmbedContentRequest_EmbeddingTaskType_name = map[int32]string{
		0: "UNSPECIFIED",
		2: "RETRIEVAL_QUERY",
		3: "RETRIEVAL_DOCUMENT",
		4: "SEMANTIC_SIMILARITY",
		5: "CLASSIFICATION",
		6: "CLUSTERING",
		7: "QUESTION_ANSWERING",
		8: "FACT_VERIFICATION",
		9: "CODE_RETRIEVAL_QUERY",
	}
	EmbedContentRequest_EmbeddingTaskType_value = map[string]int32{
		"UNSPECIFIED":          0,
		"RETRIEVAL_QUERY":      2,
		"RETRIEVAL_DOCUMENT":   3,
		"SEMANTIC_SIMILARITY":  4,
		"CLASSIFICATION":       5,
		"CLUSTERING":           6,
		"QUESTION_ANSWERING":   7,
		"FACT_VERIFICATION":    8,
		"CODE_RETRIEVAL_QUERY": 9,
	}
)

func (x EmbedContentRequest_EmbeddingTaskType) Enum() *EmbedContentRequest_EmbeddingTaskType {
	p := new(EmbedContentRequest_EmbeddingTaskType)
	*p = x
	return p
}

func (x EmbedContentRequest_EmbeddingTaskType) String() string {
	return protoimpl.X.EnumStringOf(x.Descriptor(), protoreflect.EnumNumber(x))
}

func (EmbedContentRequest_EmbeddingTaskType) Descriptor() protoreflect.EnumDescriptor {
	return file_google_cloud_aiplatform_v1_prediction_service_proto_enumTypes[2].Descriptor()
}

func (EmbedContentRequest_EmbeddingTaskType) Type() protoreflect.EnumType {
	return &file_google_cloud_aiplatform_v1_prediction_service_proto_enumTypes[2]
}

func (x EmbedContentRequest_EmbeddingTaskType) Number() protoreflect.EnumNumber {
	return protoreflect.EnumNumber(x)
}

// Deprecated: Use EmbedContentRequest_EmbeddingTaskType.Descriptor instead.
func (EmbedContentRequest_EmbeddingTaskType) EnumDescriptor() ([]byte, []int) {
	return file_google_cloud_aiplatform_v1_prediction_service_proto_rawDescGZIP(), []int{22, 0}
}

// Request message for
// [PredictionService.Predict][google.cloud.aiplatform.v1.PredictionService.Predict].
type PredictRequest struct {
	state protoimpl.MessageState `protogen:"open.v1"`
	// 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.v1.DeployedModel.model]
	// [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata]
	// [instance_schema_uri][google.cloud.aiplatform.v1.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.v1.DeployedModel.model]
	// [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata]
	// [parameters_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.parameters_schema_uri].
	Parameters *structpb.Value `protobuf:"bytes,3,opt,name=parameters,proto3" json:"parameters,omitempty"`
	// Optional. The user labels for Imagen billing usage only. Only Imagen
	// supports labels. For other use cases, it will be ignored.
	Labels        map[string]string `protobuf:"bytes,4,rep,name=labels,proto3" json:"labels,omitempty" protobuf_key:"bytes,1,opt,name=key" protobuf_val:"bytes,2,opt,name=value"`
	unknownFields protoimpl.UnknownFields
	sizeCache     protoimpl.SizeCache
}

func (x *PredictRequest) Reset() {
	*x = PredictRequest{}
	mi := &file_google_cloud_aiplatform_v1_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_v1_prediction_service_proto_msgTypes[0]
	if 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_v1_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
}

func (x *PredictRequest) GetLabels() map[string]string {
	if x != nil {
		return x.Labels
	}
	return nil
}

// Response message for
// [PredictionService.Predict][google.cloud.aiplatform.v1.PredictionService.Predict].
type PredictResponse struct {
	state protoimpl.MessageState `protogen:"open.v1"`
	// 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.v1.DeployedModel.model]
	// [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata]
	// [prediction_schema_uri][google.cloud.aiplatform.v1.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.v1.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"`
	unknownFields protoimpl.UnknownFields
	sizeCache     protoimpl.SizeCache
}

func (x *PredictResponse) Reset() {
	*x = PredictResponse{}
	mi := &file_google_cloud_aiplatform_v1_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_v1_prediction_service_proto_msgTypes[1]
	if 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_v1_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.v1.PredictionService.RawPredict].
type RawPredictRequest struct {
	state protoimpl.MessageState `protogen:"open.v1"`
	// 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.v1.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.v1.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.v1.PredictSchemata.instance_schema_uri]
	// field when you create a [Model][google.cloud.aiplatform.v1.Model]. This
	// schema applies when you deploy the `Model` as a `DeployedModel` to an
	// [Endpoint][google.cloud.aiplatform.v1.Endpoint] and use the `RawPredict`
	// method.
	HttpBody      *httpbody.HttpBody `protobuf:"bytes,2,opt,name=http_body,json=httpBody,proto3" json:"http_body,omitempty"`
	unknownFields protoimpl.UnknownFields
	sizeCache     protoimpl.SizeCache
}

func (x *RawPredictRequest) Reset() {
	*x = RawPredictRequest{}
	mi := &file_google_cloud_aiplatform_v1_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_v1_prediction_service_proto_msgTypes[2]
	if 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_v1_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.StreamRawPredict][google.cloud.aiplatform.v1.PredictionService.StreamRawPredict].
type StreamRawPredictRequest struct {
	state protoimpl.MessageState `protogen:"open.v1"`
	// 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.
	HttpBody      *httpbody.HttpBody `protobuf:"bytes,2,opt,name=http_body,json=httpBody,proto3" json:"http_body,omitempty"`
	unknownFields protoimpl.UnknownFields
	sizeCache     protoimpl.SizeCache
}

func (x *StreamRawPredictRequest) Reset() {
	*x = StreamRawPredictRequest{}
	mi := &file_google_cloud_aiplatform_v1_prediction_service_proto_msgTypes[3]
	ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
	ms.StoreMessageInfo(mi)
}

func (x *StreamRawPredictRequest) String() string {
	return protoimpl.X.MessageStringOf(x)
}

func (*StreamRawPredictRequest) ProtoMessage() {}

func (x *StreamRawPredictRequest) ProtoReflect() protoreflect.Message {
	mi := &file_google_cloud_aiplatform_v1_prediction_service_proto_msgTypes[3]
	if x != nil {
		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
		if ms.LoadMessageInfo() == nil {
			ms.StoreMessageInfo(mi)
		}
		return ms
	}
	return mi.MessageOf(x)
}

// Deprecated: Use StreamRawPredictRequest.ProtoReflect.Descriptor instead.
func (*StreamRawPredictRequest) Descriptor() ([]byte, []int) {
	return file_google_cloud_aiplatform_v1_prediction_service_proto_rawDescGZIP(), []int{3}
}

func (x *StreamRawPredictRequest) GetEndpoint() string {
	if x != nil {
		return x.Endpoint
	}
	return ""
}

func (x *StreamRawPredictRequest) GetHttpBody() *httpbody.HttpBody {
	if x != nil {
		return x.HttpBody
	}
	return nil
}

// Request message for
// [PredictionService.DirectPredict][google.cloud.aiplatform.v1.PredictionService.DirectPredict].
type DirectPredictRequest struct {
	state protoimpl.MessageState `protogen:"open.v1"`
	// 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"`
	unknownFields protoimpl.UnknownFields
	sizeCache     protoimpl.SizeCache
}

func (x *DirectPredictRequest) Reset() {
	*x = DirectPredictRequest{}
	mi := &file_google_cloud_aiplatform_v1_prediction_service_proto_msgTypes[4]
	ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
	ms.StoreMessageInfo(mi)
}

func (x *DirectPredictRequest) String() string {
	return protoimpl.X.MessageStringOf(x)
}

func (*DirectPredictRequest) ProtoMessage() {}

func (x *DirectPredictRequest) ProtoReflect() protoreflect.Message {
	mi := &file_google_cloud_aiplatform_v1_prediction_service_proto_msgTypes[4]
	if x != nil {
		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
		if ms.LoadMessageInfo() == nil {
			ms.StoreMessageInfo(mi)
		}
		return ms
	}
	return mi.MessageOf(x)
}

// Deprecated: Use DirectPredictRequest.ProtoReflect.Descriptor instead.
func (*DirectPredictRequest) Descriptor() ([]byte, []int) {
	return file_google_cloud_aiplatform_v1_prediction_service_proto_rawDescGZIP(), []int{4}
}

func (x *DirectPredictRequest) GetEndpoint() string {
	if x != nil {
		return x.Endpoint
	}
	return ""
}

func (x *DirectPredictRequest) GetInputs() []*Tensor {
	if x != nil {
		return x.Inputs
	}
	return nil
}

func (x *DirectPredictRequest) GetParameters() *Tensor {
	if x != nil {
		return x.Parameters
	}
	return nil
}

// Response message for
// [PredictionService.DirectPredict][google.cloud.aiplatform.v1.PredictionService.DirectPredict].
type DirectPredictResponse struct {
	state protoimpl.MessageState `protogen:"open.v1"`
	// 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"`
	unknownFields protoimpl.UnknownFields
	sizeCache     protoimpl.SizeCache
}

func (x *DirectPredictResponse) Reset() {
	*x = DirectPredictResponse{}
	mi := &file_google_cloud_aiplatform_v1_prediction_service_proto_msgTypes[5]
	ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
	ms.StoreMessageInfo(mi)
}

func (x *DirectPredictResponse) String() string {
	return protoimpl.X.MessageStringOf(x)
}

func (*DirectPredictResponse) ProtoMessage() {}

func (x *DirectPredictResponse) ProtoReflect() protoreflect.Message {
	mi := &file_google_cloud_aiplatform_v1_prediction_service_proto_msgTypes[5]
	if x != nil {
		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
		if ms.LoadMessageInfo() == nil {
			ms.StoreMessageInfo(mi)
		}
		return ms
	}
	return mi.MessageOf(x)
}

// Deprecated: Use DirectPredictResponse.ProtoReflect.Descriptor instead.
func (*DirectPredictResponse) Descriptor() ([]byte, []int) {
	return file_google_cloud_aiplatform_v1_prediction_service_proto_rawDescGZIP(), []int{5}
}

func (x *DirectPredictResponse) GetOutputs() []*Tensor {
	if x != nil {
		return x.Outputs
	}
	return nil
}

func (x *DirectPredictResponse) GetParameters() *Tensor {
	if x != nil {
		return x.Parameters
	}
	return nil
}

// Request message for
// [PredictionService.DirectRawPredict][google.cloud.aiplatform.v1.PredictionService.DirectRawPredict].
type DirectRawPredictRequest struct {
	state protoimpl.MessageState `protogen:"open.v1"`
	// 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"`
	// Fully qualified name of the API method being invoked to perform
	// predictions.
	//
	// Format:
	// `/namespace.Service/Method/`
	// Example:
	// `/tensorflow.serving.PredictionService/Predict`
	MethodName string `protobuf:"bytes,2,opt,name=method_name,json=methodName,proto3" json:"method_name,omitempty"`
	// The prediction input.
	Input         []byte `protobuf:"bytes,3,opt,name=input,proto3" json:"input,omitempty"`
	unknownFields protoimpl.UnknownFields
	sizeCache     protoimpl.SizeCache
}

func (x *DirectRawPredictRequest) Reset() {
	*x = DirectRawPredictRequest{}
	mi := &file_google_cloud_aiplatform_v1_prediction_service_proto_msgTypes[6]
	ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
	ms.StoreMessageInfo(mi)
}

func (x *DirectRawPredictRequest) String() string {
	return protoimpl.X.MessageStringOf(x)
}

func (*DirectRawPredictRequest) ProtoMessage() {}

func (x *DirectRawPredictRequest) ProtoReflect() protoreflect.Message {
	mi := &file_google_cloud_aiplatform_v1_prediction_service_proto_msgTypes[6]
	if x != nil {
		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
		if ms.LoadMessageInfo() == nil {
			ms.StoreMessageInfo(mi)
		}
		return ms
	}
	return mi.MessageOf(x)
}

// Deprecated: Use DirectRawPredictRequest.ProtoReflect.Descriptor instead.
func (*DirectRawPredictRequest) Descriptor() ([]byte, []int) {
	return file_google_cloud_aiplatform_v1_prediction_service_proto_rawDescGZIP(), []int{6}
}

func (x *DirectRawPredictRequest) GetEndpoint() string {
	if x != nil {
		return x.Endpoint
	}
	return ""
}

func (x *DirectRawPredictRequest) GetMethodName() string {
	if x != nil {
		return x.MethodName
	}
	return ""
}

func (x *DirectRawPredictRequest) GetInput() []byte {
	if x != nil {
		return x.Input
	}
	return nil
}

// Response message for
// [PredictionService.DirectRawPredict][google.cloud.aiplatform.v1.PredictionService.DirectRawPredict].
type DirectRawPredictResponse struct {
	state protoimpl.MessageState `protogen:"open.v1"`
	// The prediction output.
	Output        []byte `protobuf:"bytes,1,opt,name=output,proto3" json:"output,omitempty"`
	unknownFields protoimpl.UnknownFields
	sizeCache     protoimpl.SizeCache
}

func (x *DirectRawPredictResponse) Reset() {
	*x = DirectRawPredictResponse{}
	mi := &file_google_cloud_aiplatform_v1_prediction_service_proto_msgTypes[7]
	ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
	ms.StoreMessageInfo(mi)
}

func (x *DirectRawPredictResponse) String() string {
	return protoimpl.X.MessageStringOf(x)
}

func (*DirectRawPredictResponse) ProtoMessage() {}

func (x *DirectRawPredictResponse) ProtoReflect() protoreflect.Message {
	mi := &file_google_cloud_aiplatform_v1_prediction_service_proto_msgTypes[7]
	if x != nil {
		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
		if ms.LoadMessageInfo() == nil {
			ms.StoreMessageInfo(mi)
		}
		return ms
	}
	return mi.MessageOf(x)
}

// Deprecated: Use DirectRawPredictResponse.ProtoReflect.Descriptor instead.
func (*DirectRawPredictResponse) Descriptor() ([]byte, []int) {
	return file_google_cloud_aiplatform_v1_prediction_service_proto_rawDescGZIP(), []int{7}
}

func (x *DirectRawPredictResponse) GetOutput() []byte {
	if x != nil {
		return x.Output
	}
	return nil
}

// Request message for
// [PredictionService.StreamDirectPredict][google.cloud.aiplatform.v1.PredictionService.StreamDirectPredict].
//
// The first message must contain
// [endpoint][google.cloud.aiplatform.v1.StreamDirectPredictRequest.endpoint]
// field and optionally [input][]. The subsequent messages must contain
// [input][].
type StreamDirectPredictRequest struct {
	state protoimpl.MessageState `protogen:"open.v1"`
	// 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"`
	// Optional. The prediction input.
	Inputs []*Tensor `protobuf:"bytes,2,rep,name=inputs,proto3" json:"inputs,omitempty"`
	// Optional. The parameters that govern the prediction.
	Parameters    *Tensor `protobuf:"bytes,3,opt,name=parameters,proto3" json:"parameters,omitempty"`
	unknownFields protoimpl.UnknownFields
	sizeCache     protoimpl.SizeCache
}

func (x *StreamDirectPredictRequest) Reset() {
	*x = StreamDirectPredictRequest{}
	mi := &file_google_cloud_aiplatform_v1_prediction_service_proto_msgTypes[8]
	ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
	ms.StoreMessageInfo(mi)
}

func (x *StreamDirectPredictRequest) String() string {
	return protoimpl.X.MessageStringOf(x)
}

func (*StreamDirectPredictRequest) ProtoMessage() {}

func (x *StreamDirectPredictRequest) ProtoReflect() protoreflect.Message {
	mi := &file_google_cloud_aiplatform_v1_prediction_service_proto_msgTypes[8]
	if x != nil {
		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
		if ms.LoadMessageInfo() == nil {
			ms.StoreMessageInfo(mi)
		}
		return ms
	}
	return mi.MessageOf(x)
}

// Deprecated: Use StreamDirectPredictRequest.ProtoReflect.Descriptor instead.
func (*StreamDirectPredictRequest) Descriptor() ([]byte, []int) {
	return file_google_cloud_aiplatform_v1_prediction_service_proto_rawDescGZIP(), []int{8}
}

func (x *StreamDirectPredictRequest) GetEndpoint() string {
	if x != nil {
		return x.Endpoint
	}
	return ""
}

func (x *StreamDirectPredictRequest) GetInputs() []*Tensor {
	if x != nil {
		return x.Inputs
	}
	return nil
}

func (x *StreamDirectPredictRequest) GetParameters() *Tensor {
	if x != nil {
		return x.Parameters
	}
	return nil
}

// Response message for
// [PredictionService.StreamDirectPredict][google.cloud.aiplatform.v1.PredictionService.StreamDirectPredict].
type StreamDirectPredictResponse struct {
	state protoimpl.MessageState `protogen:"open.v1"`
	// 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"`
	unknownFields protoimpl.UnknownFields
	sizeCache     protoimpl.SizeCache
}

func (x *StreamDirectPredictResponse) Reset() {
	*x = StreamDirectPredictResponse{}
	mi := &file_google_cloud_aiplatform_v1_prediction_service_proto_msgTypes[9]
	ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
	ms.StoreMessageInfo(mi)
}

func (x *StreamDirectPredictResponse) String() string {
	return protoimpl.X.MessageStringOf(x)
}

func (*StreamDirectPredictResponse) ProtoMessage() {}

func (x *StreamDirectPredictResponse) ProtoReflect() protoreflect.Message {
	mi := &file_google_cloud_aiplatform_v1_prediction_service_proto_msgTypes[9]
	if x != nil {
		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
		if ms.LoadMessageInfo() == nil {
			ms.StoreMessageInfo(mi)
		}
		return ms
	}
	return mi.MessageOf(x)
}

// Deprecated: Use StreamDirectPredictResponse.ProtoReflect.Descriptor instead.
func (*StreamDirectPredictResponse) Descriptor() ([]byte, []int) {
	return file_google_cloud_aiplatform_v1_prediction_service_proto_rawDescGZIP(), []int{9}
}

func (x *StreamDirectPredictResponse) GetOutputs() []*Tensor {
	if x != nil {
		return x.Outputs
	}
	return nil
}

func (x *StreamDirectPredictResponse) GetParameters() *Tensor {
	if x != nil {
		return x.Parameters
	}
	return nil
}

// Request message for
// [PredictionService.StreamDirectRawPredict][google.cloud.aiplatform.v1.PredictionService.StreamDirectRawPredict].
//
// The first message must contain
// [endpoint][google.cloud.aiplatform.v1.StreamDirectRawPredictRequest.endpoint]
// and
// [method_name][google.cloud.aiplatform.v1.StreamDirectRawPredictRequest.method_name]
// fields and optionally
// [input][google.cloud.aiplatform.v1.StreamDirectRawPredictRequest.input]. The
// subsequent messages must contain
// [input][google.cloud.aiplatform.v1.StreamDirectRawPredictRequest.input].
// [method_name][google.cloud.aiplatform.v1.StreamDirectRawPredictRequest.method_name]
// in the subsequent messages have no effect.
type StreamDirectRawPredictRequest struct {
	state protoimpl.MessageState `protogen:"open.v1"`
	// 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"`
	// Optional. Fully qualified name of the API method being invoked to perform
	// predictions.
	//
	// Format:
	// `/namespace.Service/Method/`
	// Example:
	// `/tensorflow.serving.PredictionService/Predict`
	MethodName string `protobuf:"bytes,2,opt,name=method_name,json=methodName,proto3" json:"method_name,omitempty"`
	// Optional. The prediction input.
	Input         []byte `protobuf:"bytes,3,opt,name=input,proto3" json:"input,omitempty"`
	unknownFields protoimpl.UnknownFields
	sizeCache     protoimpl.SizeCache
}

func (x *StreamDirectRawPredictRequest) Reset() {
	*x = StreamDirectRawPredictRequest{}
	mi := &file_google_cloud_aiplatform_v1_prediction_service_proto_msgTypes[10]
	ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
	ms.StoreMessageInfo(mi)
}

func (x *StreamDirectRawPredictRequest) String() string {
	return protoimpl.X.MessageStringOf(x)
}

func (*StreamDirectRawPredictRequest) ProtoMessage() {}

func (x *StreamDirectRawPredictRequest) ProtoReflect() protoreflect.Message {
	mi := &file_google_cloud_aiplatform_v1_prediction_service_proto_msgTypes[10]
	if x != nil {
		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
		if ms.LoadMessageInfo() == nil {
			ms.StoreMessageInfo(mi)
		}
		return ms
	}
	return mi.MessageOf(x)
}

// Deprecated: Use StreamDirectRawPredictRequest.ProtoReflect.Descriptor instead.
func (*StreamDirectRawPredictRequest) Descriptor() ([]byte, []int) {
	return file_google_cloud_aiplatform_v1_prediction_service_proto_rawDescGZIP(), []int{10}
}

func (x *StreamDirectRawPredictRequest) GetEndpoint() string {
	if x != nil {
		return x.Endpoint
	}
	return ""
}

func (x *StreamDirectRawPredictRequest) GetMethodName() string {
	if x != nil {
		return x.MethodName
	}
	return ""
}

func (x *StreamDirectRawPredictRequest) GetInput() []byte {
	if x != nil {
		return x.Input
	}
	return nil
}

// Response message for
// [PredictionService.StreamDirectRawPredict][google.cloud.aiplatform.v1.PredictionService.StreamDirectRawPredict].
type StreamDirectRawPredictResponse struct {
	state protoimpl.MessageState `protogen:"open.v1"`
	// The prediction output.
	Output        []byte `protobuf:"bytes,1,opt,name=output,proto3" json:"output,omitempty"`
	unknownFields protoimpl.UnknownFields
	sizeCache     protoimpl.SizeCache
}

func (x *StreamDirectRawPredictResponse) Reset() {
	*x = StreamDirectRawPredictResponse{}
	mi := &file_google_cloud_aiplatform_v1_prediction_service_proto_msgTypes[11]
	ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
	ms.StoreMessageInfo(mi)
}

func (x *StreamDirectRawPredictResponse) String() string {
	return protoimpl.X.MessageStringOf(x)
}

func (*StreamDirectRawPredictResponse) ProtoMessage() {}

func (x *StreamDirectRawPredictResponse) ProtoReflect() protoreflect.Message {
	mi := &file_google_cloud_aiplatform_v1_prediction_service_proto_msgTypes[11]
	if x != nil {
		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
		if ms.LoadMessageInfo() == nil {
			ms.StoreMessageInfo(mi)
		}
		return ms
	}
	return mi.MessageOf(x)
}

// Deprecated: Use StreamDirectRawPredictResponse.ProtoReflect.Descriptor instead.
func (*StreamDirectRawPredictResponse) Descriptor() ([]byte, []int) {
	return file_google_cloud_aiplatform_v1_prediction_service_proto_rawDescGZIP(), []int{11}
}

func (x *StreamDirectRawPredictResponse) GetOutput() []byte {
	if x != nil {
		return x.Output
	}
	return nil
}

// Request message for
// [PredictionService.StreamingPredict][google.cloud.aiplatform.v1.PredictionService.StreamingPredict].
//
// The first message must contain
// [endpoint][google.cloud.aiplatform.v1.StreamingPredictRequest.endpoint] field
// and optionally [input][]. The subsequent messages must contain [input][].
type StreamingPredictRequest struct {
	state protoimpl.MessageState `protogen:"open.v1"`
	// 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"`
	unknownFields protoimpl.UnknownFields
	sizeCache     protoimpl.SizeCache
}

func (x *StreamingPredictRequest) Reset() {
	*x = StreamingPredictRequest{}
	mi := &file_google_cloud_aiplatform_v1_prediction_service_proto_msgTypes[12]
	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_v1_prediction_service_proto_msgTypes[12]
	if 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_v1_prediction_service_proto_rawDescGZIP(), []int{12}
}

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.v1.PredictionService.StreamingPredict].
type StreamingPredictResponse struct {
	state protoimpl.MessageState `protogen:"open.v1"`
	// 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"`
	unknownFields protoimpl.UnknownFields
	sizeCache     protoimpl.SizeCache
}

func (x *StreamingPredictResponse) Reset() {
	*x = StreamingPredictResponse{}
	mi := &file_google_cloud_aiplatform_v1_prediction_service_proto_msgTypes[13]
	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_v1_prediction_service_proto_msgTypes[13]
	if 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_v1_prediction_service_proto_rawDescGZIP(), []int{13}
}

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.StreamingRawPredict][google.cloud.aiplatform.v1.PredictionService.StreamingRawPredict].
//
// The first message must contain
// [endpoint][google.cloud.aiplatform.v1.StreamingRawPredictRequest.endpoint]
// and
// [method_name][google.cloud.aiplatform.v1.StreamingRawPredictRequest.method_name]
// fields and optionally
// [input][google.cloud.aiplatform.v1.StreamingRawPredictRequest.input]. The
// subsequent messages must contain
// [input][google.cloud.aiplatform.v1.StreamingRawPredictRequest.input].
// [method_name][google.cloud.aiplatform.v1.StreamingRawPredictRequest.method_name]
// in the subsequent messages have no effect.
type StreamingRawPredictRequest struct {
	state protoimpl.MessageState `protogen:"open.v1"`
	// 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"`
	// Fully qualified name of the API method being invoked to perform
	// predictions.
	//
	// Format:
	// `/namespace.Service/Method/`
	// Example:
	// `/tensorflow.serving.PredictionService/Predict`
	MethodName string `protobuf:"bytes,2,opt,name=method_name,json=methodName,proto3" json:"method_name,omitempty"`
	// The prediction input.
	Input         []byte `protobuf:"bytes,3,opt,name=input,proto3" json:"input,omitempty"`
	unknownFields protoimpl.UnknownFields
	sizeCache     protoimpl.SizeCache
}

func (x *StreamingRawPredictRequest) Reset() {
	*x = StreamingRawPredictRequest{}
	mi := &file_google_cloud_aiplatform_v1_prediction_service_proto_msgTypes[14]
	ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
	ms.StoreMessageInfo(mi)
}

func (x *StreamingRawPredictRequest) String() string {
	return protoimpl.X.MessageStringOf(x)
}

func (*StreamingRawPredictRequest) ProtoMessage() {}

func (x *StreamingRawPredictRequest) ProtoReflect() protoreflect.Message {
	mi := &file_google_cloud_aiplatform_v1_prediction_service_proto_msgTypes[14]
	if x != nil {
		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
		if ms.LoadMessageInfo() == nil {
			ms.StoreMessageInfo(mi)
		}
		return ms
	}
	return mi.MessageOf(x)
}

// Deprecated: Use StreamingRawPredictRequest.ProtoReflect.Descriptor instead.
func (*StreamingRawPredictRequest) Descriptor() ([]byte, []int) {
	return file_google_cloud_aiplatform_v1_prediction_service_proto_rawDescGZIP(), []int{14}
}

func (x *StreamingRawPredictRequest) GetEndpoint() string {
	if x != nil {
		return x.Endpoint
	}
	return ""
}

func (x *StreamingRawPredictRequest) GetMethodName() string {
	if x != nil {
		return x.MethodName
	}
	return ""
}

func (x *StreamingRawPredictRequest) GetInput() []byte {
	if x != nil {
		return x.Input
	}
	return nil
}

// Response message for
// [PredictionService.StreamingRawPredict][google.cloud.aiplatform.v1.PredictionService.StreamingRawPredict].
type StreamingRawPredictResponse struct {
	state protoimpl.MessageState `protogen:"open.v1"`
	// The prediction output.
	Output        []byte `protobuf:"bytes,1,opt,name=output,proto3" json:"output,omitempty"`
	unknownFields protoimpl.UnknownFields
	sizeCache     protoimpl.SizeCache
}

func (x *StreamingRawPredictResponse) Reset() {
	*x = StreamingRawPredictResponse{}
	mi := &file_google_cloud_aiplatform_v1_prediction_service_proto_msgTypes[15]
	ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
	ms.StoreMessageInfo(mi)
}

func (x *StreamingRawPredictResponse) String() string {
	return protoimpl.X.MessageStringOf(x)
}

func (*StreamingRawPredictResponse) ProtoMessage() {}

func (x *StreamingRawPredictResponse) ProtoReflect() protoreflect.Message {
	mi := &file_google_cloud_aiplatform_v1_prediction_service_proto_msgTypes[15]
	if x != nil {
		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
		if ms.LoadMessageInfo() == nil {
			ms.StoreMessageInfo(mi)
		}
		return ms
	}
	return mi.MessageOf(x)
}

// Deprecated: Use StreamingRawPredictResponse.ProtoReflect.Descriptor instead.
func (*StreamingRawPredictResponse) Descriptor() ([]byte, []int) {
	return file_google_cloud_aiplatform_v1_prediction_service_proto_rawDescGZIP(), []int{15}
}

func (x *StreamingRawPredictResponse) GetOutput() []byte {
	if x != nil {
		return x.Output
	}
	return nil
}

// Request message for
// [PredictionService.Explain][google.cloud.aiplatform.v1.PredictionService.Explain].
type ExplainRequest struct {
	state protoimpl.MessageState `protogen:"open.v1"`
	// 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.v1.DeployedModel.model]
	// [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata]
	// [instance_schema_uri][google.cloud.aiplatform.v1.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.v1.DeployedModel.model]
	// [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata]
	// [parameters_schema_uri][google.cloud.aiplatform.v1.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.v1.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.v1.Endpoint.traffic_split].
	DeployedModelId string `protobuf:"bytes,3,opt,name=deployed_model_id,json=deployedModelId,proto3" json:"deployed_model_id,omitempty"`
	unknownFields   protoimpl.UnknownFields
	sizeCache       protoimpl.SizeCache
}

func (x *ExplainRequest) Reset() {
	*x = ExplainRequest{}
	mi := &file_google_cloud_aiplatform_v1_prediction_service_proto_msgTypes[16]
	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_v1_prediction_service_proto_msgTypes[16]
	if 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_v1_prediction_service_proto_rawDescGZIP(), []int{16}
}

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.v1.PredictionService.Explain].
type ExplainResponse struct {
	state protoimpl.MessageState `protogen:"open.v1"`
	// The explanations of the Model's
	// [PredictResponse.predictions][google.cloud.aiplatform.v1.PredictResponse.predictions].
	//
	// It has the same number of elements as
	// [instances][google.cloud.aiplatform.v1.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.v1.PredictResponse.predictions].
	Predictions   []*structpb.Value `protobuf:"bytes,3,rep,name=predictions,proto3" json:"predictions,omitempty"`
	unknownFields protoimpl.UnknownFields
	sizeCache     protoimpl.SizeCache
}

func (x *ExplainResponse) Reset() {
	*x = ExplainResponse{}
	mi := &file_google_cloud_aiplatform_v1_prediction_service_proto_msgTypes[17]
	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_v1_prediction_service_proto_msgTypes[17]
	if 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_v1_prediction_service_proto_rawDescGZIP(), []int{17}
}

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][].
type CountTokensRequest struct {
	state protoimpl.MessageState `protogen:"open.v1"`
	// 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"`
	// Optional. The name of the publisher model requested to serve the
	// prediction. Format:
	// `projects/{project}/locations/{location}/publishers/*/models/*`
	Model string `protobuf:"bytes,3,opt,name=model,proto3" json:"model,omitempty"`
	// Optional. 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"`
	// Optional. Input content.
	Contents []*Content `protobuf:"bytes,4,rep,name=contents,proto3" json:"contents,omitempty"`
	// Optional. The user provided system instructions for the model.
	// Note: only text should be used in parts and content in each part will be in
	// a separate paragraph.
	SystemInstruction *Content `protobuf:"bytes,5,opt,name=system_instruction,json=systemInstruction,proto3,oneof" json:"system_instruction,omitempty"`
	// Optional. A list of `Tools` the model may use to generate the next
	// response.
	//
	// A `Tool` is a piece of code that enables the system to interact with
	// external systems to perform an action, or set of actions, outside of
	// knowledge and scope of the model.
	Tools []*Tool `protobuf:"bytes,6,rep,name=tools,proto3" json:"tools,omitempty"`
	// Optional. Generation config that the model will use to generate the
	// response.
	GenerationConfig *GenerationConfig `protobuf:"bytes,7,opt,name=generation_config,json=generationConfig,proto3,oneof" json:"generation_config,omitempty"`
	unknownFields    protoimpl.UnknownFields
	sizeCache        protoimpl.SizeCache
}

func (x *CountTokensRequest) Reset() {
	*x = CountTokensRequest{}
	mi := &file_google_cloud_aiplatform_v1_prediction_service_proto_msgTypes[18]
	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_v1_prediction_service_proto_msgTypes[18]
	if 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_v1_prediction_service_proto_rawDescGZIP(), []int{18}
}

func (x *CountTokensRequest) GetEndpoint() string {
	if x != nil {
		return x.Endpoint
	}
	return ""
}

func (x *CountTokensRequest) GetModel() string {
	if x != nil {
		return x.Model
	}
	return ""
}

func (x *CountTokensRequest) GetInstances() []*structpb.Value {
	if x != nil {
		return x.Instances
	}
	return nil
}

func (x *CountTokensRequest) GetContents() []*Content {
	if x != nil {
		return x.Contents
	}
	return nil
}

func (x *CountTokensRequest) GetSystemInstruction() *Content {
	if x != nil {
		return x.SystemInstruction
	}
	return nil
}

func (x *CountTokensRequest) GetTools() []*Tool {
	if x != nil {
		return x.Tools
	}
	return nil
}

func (x *CountTokensRequest) GetGenerationConfig() *GenerationConfig {
	if x != nil {
		return x.GenerationConfig
	}
	return nil
}

// Response message for [PredictionService.CountTokens][].
type CountTokensResponse struct {
	state protoimpl.MessageState `protogen:"open.v1"`
	// 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"`
	// Output only. List of modalities that were processed in the request input.
	PromptTokensDetails []*ModalityTokenCount `protobuf:"bytes,3,rep,name=prompt_tokens_details,json=promptTokensDetails,proto3" json:"prompt_tokens_details,omitempty"`
	unknownFields       protoimpl.UnknownFields
	sizeCache           protoimpl.SizeCache
}

func (x *CountTokensResponse) Reset() {
	*x = CountTokensResponse{}
	mi := &file_google_cloud_aiplatform_v1_prediction_service_proto_msgTypes[19]
	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_v1_prediction_service_proto_msgTypes[19]
	if 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_v1_prediction_service_proto_rawDescGZIP(), []int{19}
}

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
}

func (x *CountTokensResponse) GetPromptTokensDetails() []*ModalityTokenCount {
	if x != nil {
		return x.PromptTokensDetails
	}
	return nil
}

// Request message for [PredictionService.GenerateContent].
type GenerateContentRequest struct {
	state protoimpl.MessageState `protogen:"open.v1"`
	// Required. The fully qualified name of the publisher model or tuned model
	// endpoint to use.
	//
	// Publisher model format:
	// `projects/{project}/locations/{location}/publishers/*/models/*`
	//
	// Tuned model endpoint format:
	// `projects/{project}/locations/{location}/endpoints/{endpoint}`
	Model string `protobuf:"bytes,5,opt,name=model,proto3" json:"model,omitempty"`
	// Required. The content of the current conversation with the model.
	//
	// For single-turn queries, this is a single instance. For multi-turn queries,
	// this is a repeated field that contains conversation history + latest
	// request.
	Contents []*Content `protobuf:"bytes,2,rep,name=contents,proto3" json:"contents,omitempty"`
	// Optional. The user provided system instructions for the model.
	// Note: only text should be used in parts and content in each part will be in
	// a separate paragraph.
	SystemInstruction *Content `protobuf:"bytes,8,opt,name=system_instruction,json=systemInstruction,proto3,oneof" json:"system_instruction,omitempty"`
	// Optional. The name of the cached content used as context to serve the
	// prediction. Note: only used in explicit caching, where users can have
	// control over caching (e.g. what content to cache) and enjoy guaranteed cost
	// savings. Format:
	// `projects/{project}/locations/{location}/cachedContents/{cachedContent}`
	CachedContent string `protobuf:"bytes,9,opt,name=cached_content,json=cachedContent,proto3" json:"cached_content,omitempty"`
	// Optional. A list of `Tools` the model may use to generate the next
	// response.
	//
	// A `Tool` is a piece of code that enables the system to interact with
	// external systems to perform an action, or set of actions, outside of
	// knowledge and scope of the model.
	Tools []*Tool `protobuf:"bytes,6,rep,name=tools,proto3" json:"tools,omitempty"`
	// Optional. Tool config. This config is shared for all tools provided in the
	// request.
	ToolConfig *ToolConfig `protobuf:"bytes,7,opt,name=tool_config,json=toolConfig,proto3" json:"tool_config,omitempty"`
	// Optional. The labels with user-defined metadata for the request. It is used
	// for billing and reporting only.
	//
	// Label keys and values can be no longer than 63 characters
	// (Unicode codepoints) and can only contain lowercase letters, numeric
	// characters, underscores, and dashes. International characters are allowed.
	// Label values are optional. Label keys must start with a letter.
	Labels map[string]string `protobuf:"bytes,10,rep,name=labels,proto3" json:"labels,omitempty" protobuf_key:"bytes,1,opt,name=key" protobuf_val:"bytes,2,opt,name=value"`
	// Optional. Per request settings for blocking unsafe content.
	// Enforced on GenerateContentResponse.candidates.
	SafetySettings []*SafetySetting `protobuf:"bytes,3,rep,name=safety_settings,json=safetySettings,proto3" json:"safety_settings,omitempty"`
	// Optional. Settings for prompt and response sanitization using the Model
	// Armor service. If supplied, safety_settings must not be supplied.
	ModelArmorConfig *ModelArmorConfig `protobuf:"bytes,11,opt,name=model_armor_config,json=modelArmorConfig,proto3" json:"model_armor_config,omitempty"`
	// Optional. Generation config.
	GenerationConfig *GenerationConfig `protobuf:"bytes,4,opt,name=generation_config,json=generationConfig,proto3" json:"generation_config,omitempty"`
	unknownFields    protoimpl.UnknownFields
	sizeCache        protoimpl.SizeCache
}

func (x *GenerateContentRequest) Reset() {
	*x = GenerateContentRequest{}
	mi := &file_google_cloud_aiplatform_v1_prediction_service_proto_msgTypes[20]
	ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
	ms.StoreMessageInfo(mi)
}

func (x *GenerateContentRequest) String() string {
	return protoimpl.X.MessageStringOf(x)
}

func (*GenerateContentRequest) ProtoMessage() {}

func (x *GenerateContentRequest) ProtoReflect() protoreflect.Message {
	mi := &file_google_cloud_aiplatform_v1_prediction_service_proto_msgTypes[20]
	if x != nil {
		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
		if ms.LoadMessageInfo() == nil {
			ms.StoreMessageInfo(mi)
		}
		return ms
	}
	return mi.MessageOf(x)
}

// Deprecated: Use GenerateContentRequest.ProtoReflect.Descriptor instead.
func (*GenerateContentRequest) Descriptor() ([]byte, []int) {
	return file_google_cloud_aiplatform_v1_prediction_service_proto_rawDescGZIP(), []int{20}
}

func (x *GenerateContentRequest) GetModel() string {
	if x != nil {
		return x.Model
	}
	return ""
}

func (x *GenerateContentRequest) GetContents() []*Content {
	if x != nil {
		return x.Contents
	}
	return nil
}

func (x *GenerateContentRequest) GetSystemInstruction() *Content {
	if x != nil {
		return x.SystemInstruction
	}
	return nil
}

func (x *GenerateContentRequest) GetCachedContent() string {
	if x != nil {
		return x.CachedContent
	}
	return ""
}

func (x *GenerateContentRequest) GetTools() []*Tool {
	if x != nil {
		return x.Tools
	}
	return nil
}

func (x *GenerateContentRequest) GetToolConfig() *ToolConfig {
	if x != nil {
		return x.ToolConfig
	}
	return nil
}

func (x *GenerateContentRequest) GetLabels() map[string]string {
	if x != nil {
		return x.Labels
	}
	return nil
}

func (x *GenerateContentRequest) GetSafetySettings() []*SafetySetting {
	if x != nil {
		return x.SafetySettings
	}
	return nil
}

func (x *GenerateContentRequest) GetModelArmorConfig() *ModelArmorConfig {
	if x != nil {
		return x.ModelArmorConfig
	}
	return nil
}

func (x *GenerateContentRequest) GetGenerationConfig() *GenerationConfig {
	if x != nil {
		return x.GenerationConfig
	}
	return nil
}

// Response message for [PredictionService.GenerateContent].
type GenerateContentResponse struct {
	state protoimpl.MessageState `protogen:"open.v1"`
	// Output only. Generated candidates.
	Candidates []*Candidate `protobuf:"bytes,2,rep,name=candidates,proto3" json:"candidates,omitempty"`
	// Output only. The model version used to generate the response.
	ModelVersion string `protobuf:"bytes,11,opt,name=model_version,json=modelVersion,proto3" json:"model_version,omitempty"`
	// Output only. Timestamp when the request is made to the server.
	CreateTime *timestamppb.Timestamp `protobuf:"bytes,12,opt,name=create_time,json=createTime,proto3" json:"create_time,omitempty"`
	// Output only. response_id is used to identify each response. It is the
	// encoding of the event_id.
	ResponseId string `protobuf:"bytes,13,opt,name=response_id,json=responseId,proto3" json:"response_id,omitempty"`
	// Output only. Content filter results for a prompt sent in the request.
	// Note: Sent only in the first stream chunk.
	// Only happens when no candidates were generated due to content violations.
	PromptFeedback *GenerateContentResponse_PromptFeedback `protobuf:"bytes,3,opt,name=prompt_feedback,json=promptFeedback,proto3" json:"prompt_feedback,omitempty"`
	// Usage metadata about the response(s).
	UsageMetadata *GenerateContentResponse_UsageMetadata `protobuf:"bytes,4,opt,name=usage_metadata,json=usageMetadata,proto3" json:"usage_metadata,omitempty"`
	unknownFields protoimpl.UnknownFields
	sizeCache     protoimpl.SizeCache
}

func (x *GenerateContentResponse) Reset() {
	*x = GenerateContentResponse{}
	mi := &file_google_cloud_aiplatform_v1_prediction_service_proto_msgTypes[21]
	ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
	ms.StoreMessageInfo(mi)
}

func (x *GenerateContentResponse) String() string {
	return protoimpl.X.MessageStringOf(x)
}

func (*GenerateContentResponse) ProtoMessage() {}

func (x *GenerateContentResponse) ProtoReflect() protoreflect.Message {
	mi := &file_google_cloud_aiplatform_v1_prediction_service_proto_msgTypes[21]
	if x != nil {
		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
		if ms.LoadMessageInfo() == nil {
			ms.StoreMessageInfo(mi)
		}
		return ms
	}
	return mi.MessageOf(x)
}

// Deprecated: Use GenerateContentResponse.ProtoReflect.Descriptor instead.
func (*GenerateContentResponse) Descriptor() ([]byte, []int) {
	return file_google_cloud_aiplatform_v1_prediction_service_proto_rawDescGZIP(), []int{21}
}

func (x *GenerateContentResponse) GetCandidates() []*Candidate {
	if x != nil {
		return x.Candidates
	}
	return nil
}

func (x *GenerateContentResponse) GetModelVersion() string {
	if x != nil {
		return x.ModelVersion
	}
	return ""
}

func (x *GenerateContentResponse) GetCreateTime() *timestamppb.Timestamp {
	if x != nil {
		return x.CreateTime
	}
	return nil
}

func (x *GenerateContentResponse) GetResponseId() string {
	if x != nil {
		return x.ResponseId
	}
	return ""
}

func (x *GenerateContentResponse) GetPromptFeedback() *GenerateContentResponse_PromptFeedback {
	if x != nil {
		return x.PromptFeedback
	}
	return nil
}

func (x *GenerateContentResponse) GetUsageMetadata() *GenerateContentResponse_UsageMetadata {
	if x != nil {
		return x.UsageMetadata
	}
	return nil
}

// Request message for
// [PredictionService.EmbedContent][google.cloud.aiplatform.v1.PredictionService.EmbedContent].
type EmbedContentRequest struct {
	state protoimpl.MessageState `protogen:"open.v1"`
	// Required. The name of the publisher model requested to serve the
	// prediction. Format:
	// `projects/{project}/locations/{location}/publishers/*/models/*`
	Model *string `protobuf:"bytes,1,opt,name=model,proto3,oneof" json:"model,omitempty"`
	// Required. Input content to be embedded.
	Content *Content `protobuf:"bytes,2,opt,name=content,proto3,oneof" json:"content,omitempty"`
	// Optional. Deprecated: Please use EmbedContentConfig.title instead.
	// The title for the text.
	//
	// Deprecated: Marked as deprecated in google/cloud/aiplatform/v1/prediction_service.proto.
	Title *string `protobuf:"bytes,4,opt,name=title,proto3,oneof" json:"title,omitempty"`
	// Optional. Deprecated: Please use EmbedContentConfig.task_type instead.
	// The task type of the embedding.
	//
	// Deprecated: Marked as deprecated in google/cloud/aiplatform/v1/prediction_service.proto.
	TaskType *EmbedContentRequest_EmbeddingTaskType `protobuf:"varint,5,opt,name=task_type,json=taskType,proto3,enum=google.cloud.aiplatform.v1.EmbedContentRequest_EmbeddingTaskType,oneof" json:"task_type,omitempty"`
	// Optional. Deprecated: Please use EmbedContentConfig.output_dimensionality
	// instead. Reduced dimension for the output embedding. If set, excessive
	// values in the output embedding are truncated from the end.
	//
	// Deprecated: Marked as deprecated in google/cloud/aiplatform/v1/prediction_service.proto.
	OutputDimensionality *int32 `protobuf:"varint,6,opt,name=output_dimensionality,json=outputDimensionality,proto3,oneof" json:"output_dimensionality,omitempty"`
	// Optional. Deprecated: Please use EmbedContentConfig.auto_truncate instead.
	// Whether to silently truncate the input content if it's longer
	// than the maximum sequence length.
	//
	// Deprecated: Marked as deprecated in google/cloud/aiplatform/v1/prediction_service.proto.
	AutoTruncate *bool `protobuf:"varint,7,opt,name=auto_truncate,json=autoTruncate,proto3,oneof" json:"auto_truncate,omitempty"`
	// Optional. Configuration for the EmbedContent request.
	EmbedContentConfig *EmbedContentRequest_EmbedContentConfig `protobuf:"bytes,8,opt,name=embed_content_config,json=embedContentConfig,proto3,oneof" json:"embed_content_config,omitempty"`
	unknownFields      protoimpl.UnknownFields
	sizeCache          protoimpl.SizeCache
}

func (x *EmbedContentRequest) Reset() {
	*x = EmbedContentRequest{}
	mi := &file_google_cloud_aiplatform_v1_prediction_service_proto_msgTypes[22]
	ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
	ms.StoreMessageInfo(mi)
}

func (x *EmbedContentRequest) String() string {
	return protoimpl.X.MessageStringOf(x)
}

func (*EmbedContentRequest) ProtoMessage() {}

func (x *EmbedContentRequest) ProtoReflect() protoreflect.Message {
	mi := &file_google_cloud_aiplatform_v1_prediction_service_proto_msgTypes[22]
	if x != nil {
		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
		if ms.LoadMessageInfo() == nil {
			ms.StoreMessageInfo(mi)
		}
		return ms
	}
	return mi.MessageOf(x)
}

// Deprecated: Use EmbedContentRequest.ProtoReflect.Descriptor instead.
func (*EmbedContentRequest) Descriptor() ([]byte, []int) {
	return file_google_cloud_aiplatform_v1_prediction_service_proto_rawDescGZIP(), []int{22}
}

func (x *EmbedContentRequest) GetModel() string {
	if x != nil && x.Model != nil {
		return *x.Model
	}
	return ""
}

func (x *EmbedContentRequest) GetContent() *Content {
	if x != nil {
		return x.Content
	}
	return nil
}

// Deprecated: Marked as deprecated in google/cloud/aiplatform/v1/prediction_service.proto.
func (x *EmbedContentRequest) GetTitle() string {
	if x != nil && x.Title != nil {
		return *x.Title
	}
	return ""
}

// Deprecated: Marked as deprecated in google/cloud/aiplatform/v1/prediction_service.proto.
func (x *EmbedContentRequest) GetTaskType() EmbedContentRequest_EmbeddingTaskType {
	if x != nil && x.TaskType != nil {
		return *x.TaskType
	}
	return EmbedContentRequest_UNSPECIFIED
}

// Deprecated: Marked as deprecated in google/cloud/aiplatform/v1/prediction_service.proto.
func (x *EmbedContentRequest) GetOutputDimensionality() int32 {
	if x != nil && x.OutputDimensionality != nil {
		return *x.OutputDimensionality
	}
	return 0
}

// Deprecated: Marked as deprecated in google/cloud/aiplatform/v1/prediction_service.proto.
func (x *EmbedContentRequest) GetAutoTruncate() bool {
	if x != nil && x.AutoTruncate != nil {
		return *x.AutoTruncate
	}
	return false
}

func (x *EmbedContentRequest) GetEmbedContentConfig() *EmbedContentRequest_EmbedContentConfig {
	if x != nil {
		return x.EmbedContentConfig
	}
	return nil
}

// Response message for
// [PredictionService.EmbedContent][google.cloud.aiplatform.v1.PredictionService.EmbedContent].
type EmbedContentResponse struct {
	state protoimpl.MessageState `protogen:"open.v1"`
	// The embedding generated from the input content.
	Embedding *EmbedContentResponse_Embedding `protobuf:"bytes,1,opt,name=embedding,proto3" json:"embedding,omitempty"`
	// Usage metadata about the response(s).
	UsageMetadata *UsageMetadata `protobuf:"bytes,2,opt,name=usage_metadata,json=usageMetadata,proto3" json:"usage_metadata,omitempty"`
	// Whether the input content was truncated before generating the embedding.
	Truncated     bool `protobuf:"varint,4,opt,name=truncated,proto3" json:"truncated,omitempty"`
	unknownFields protoimpl.UnknownFields
	sizeCache     protoimpl.SizeCache
}

func (x *EmbedContentResponse) Reset() {
	*x = EmbedContentResponse{}
	mi := &file_google_cloud_aiplatform_v1_prediction_service_proto_msgTypes[23]
	ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
	ms.StoreMessageInfo(mi)
}

func (x *EmbedContentResponse) String() string {
	return protoimpl.X.MessageStringOf(x)
}

func (*EmbedContentResponse) ProtoMessage() {}

func (x *EmbedContentResponse) ProtoReflect() protoreflect.Message {
	mi := &file_google_cloud_aiplatform_v1_prediction_service_proto_msgTypes[23]
	if x != nil {
		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
		if ms.LoadMessageInfo() == nil {
			ms.StoreMessageInfo(mi)
		}
		return ms
	}
	return mi.MessageOf(x)
}

// Deprecated: Use EmbedContentResponse.ProtoReflect.Descriptor instead.
func (*EmbedContentResponse) Descriptor() ([]byte, []int) {
	return file_google_cloud_aiplatform_v1_prediction_service_proto_rawDescGZIP(), []int{23}
}

func (x *EmbedContentResponse) GetEmbedding() *EmbedContentResponse_Embedding {
	if x != nil {
		return x.Embedding
	}
	return nil
}

func (x *EmbedContentResponse) GetUsageMetadata() *UsageMetadata {
	if x != nil {
		return x.UsageMetadata
	}
	return nil
}

func (x *EmbedContentResponse) GetTruncated() bool {
	if x != nil {
		return x.Truncated
	}
	return false
}

// Content filter results for a prompt sent in the request.
type GenerateContentResponse_PromptFeedback struct {
	state protoimpl.MessageState `protogen:"open.v1"`
	// Output only. Blocked reason.
	BlockReason GenerateContentResponse_PromptFeedback_BlockedReason `protobuf:"varint,1,opt,name=block_reason,json=blockReason,proto3,enum=google.cloud.aiplatform.v1.GenerateContentResponse_PromptFeedback_BlockedReason" json:"block_reason,omitempty"`
	// Output only. Safety ratings.
	SafetyRatings []*SafetyRating `protobuf:"bytes,2,rep,name=safety_ratings,json=safetyRatings,proto3" json:"safety_ratings,omitempty"`
	// Output only. A readable block reason message.
	BlockReasonMessage string `protobuf:"bytes,3,opt,name=block_reason_message,json=blockReasonMessage,proto3" json:"block_reason_message,omitempty"`
	unknownFields      protoimpl.UnknownFields
	sizeCache          protoimpl.SizeCache
}

func (x *GenerateContentResponse_PromptFeedback) Reset() {
	*x = GenerateContentResponse_PromptFeedback{}
	mi := &file_google_cloud_aiplatform_v1_prediction_service_proto_msgTypes[26]
	ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
	ms.StoreMessageInfo(mi)
}

func (x *GenerateContentResponse_PromptFeedback) String() string {
	return protoimpl.X.MessageStringOf(x)
}

func (*GenerateContentResponse_PromptFeedback) ProtoMessage() {}

func (x *GenerateContentResponse_PromptFeedback) ProtoReflect() protoreflect.Message {
	mi := &file_google_cloud_aiplatform_v1_prediction_service_proto_msgTypes[26]
	if x != nil {
		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
		if ms.LoadMessageInfo() == nil {
			ms.StoreMessageInfo(mi)
		}
		return ms
	}
	return mi.MessageOf(x)
}

// Deprecated: Use GenerateContentResponse_PromptFeedback.ProtoReflect.Descriptor instead.
func (*GenerateContentResponse_PromptFeedback) Descriptor() ([]byte, []int) {
	return file_google_cloud_aiplatform_v1_prediction_service_proto_rawDescGZIP(), []int{21, 0}
}

func (x *GenerateContentResponse_PromptFeedback) GetBlockReason() GenerateContentResponse_PromptFeedback_BlockedReason {
	if x != nil {
		return x.BlockReason
	}
	return GenerateContentResponse_PromptFeedback_BLOCKED_REASON_UNSPECIFIED
}

func (x *GenerateContentResponse_PromptFeedback) GetSafetyRatings() []*SafetyRating {
	if x != nil {
		return x.SafetyRatings
	}
	return nil
}

func (x *GenerateContentResponse_PromptFeedback) GetBlockReasonMessage() string {
	if x != nil {
		return x.BlockReasonMessage
	}
	return ""
}

// Usage metadata about response(s).
type GenerateContentResponse_UsageMetadata struct {
	state protoimpl.MessageState `protogen:"open.v1"`
	// Number of tokens in the request. When `cached_content` is set, this is
	// still the total effective prompt size meaning this includes the number of
	// tokens in the cached content.
	PromptTokenCount int32 `protobuf:"varint,1,opt,name=prompt_token_count,json=promptTokenCount,proto3" json:"prompt_token_count,omitempty"`
	// Number of tokens in the response(s).
	CandidatesTokenCount int32 `protobuf:"varint,2,opt,name=candidates_token_count,json=candidatesTokenCount,proto3" json:"candidates_token_count,omitempty"`
	// Output only. Number of tokens present in thoughts output.
	ThoughtsTokenCount int32 `protobuf:"varint,14,opt,name=thoughts_token_count,json=thoughtsTokenCount,proto3" json:"thoughts_token_count,omitempty"`
	// Total token count for prompt and response candidates.
	TotalTokenCount int32 `protobuf:"varint,3,opt,name=total_token_count,json=totalTokenCount,proto3" json:"total_token_count,omitempty"`
	// Output only. Number of tokens in the cached part in the input (the cached
	// content).
	CachedContentTokenCount int32 `protobuf:"varint,5,opt,name=cached_content_token_count,json=cachedContentTokenCount,proto3" json:"cached_content_token_count,omitempty"`
	// Output only. List of modalities that were processed in the request input.
	PromptTokensDetails []*ModalityTokenCount `protobuf:"bytes,9,rep,name=prompt_tokens_details,json=promptTokensDetails,proto3" json:"prompt_tokens_details,omitempty"`
	// Output only. List of modalities of the cached content in the request
	// input.
	CacheTokensDetails []*ModalityTokenCount `protobuf:"bytes,10,rep,name=cache_tokens_details,json=cacheTokensDetails,proto3" json:"cache_tokens_details,omitempty"`
	// Output only. List of modalities that were returned in the response.
	CandidatesTokensDetails []*ModalityTokenCount `protobuf:"bytes,11,rep,name=candidates_tokens_details,json=candidatesTokensDetails,proto3" json:"candidates_tokens_details,omitempty"`
	// Output only. A detailed breakdown by modality of the token counts from
	// the results of tool executions, which are provided back to the model as
	// input.
	ToolUsePromptTokensDetails []*ModalityTokenCount `protobuf:"bytes,12,rep,name=tool_use_prompt_tokens_details,json=toolUsePromptTokensDetails,proto3" json:"tool_use_prompt_tokens_details,omitempty"`
	// Output only. The traffic type for this request.
	TrafficType   GenerateContentResponse_UsageMetadata_TrafficType `protobuf:"varint,8,opt,name=traffic_type,json=trafficType,proto3,enum=google.cloud.aiplatform.v1.GenerateContentResponse_UsageMetadata_TrafficType" json:"traffic_type,omitempty"`
	unknownFields protoimpl.UnknownFields
	sizeCache     protoimpl.SizeCache
}

func (x *GenerateContentResponse_UsageMetadata) Reset() {
	*x = GenerateContentResponse_UsageMetadata{}
	mi := &file_google_cloud_aiplatform_v1_prediction_service_proto_msgTypes[27]
	ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
	ms.StoreMessageInfo(mi)
}

func (x *GenerateContentResponse_UsageMetadata) String() string {
	return protoimpl.X.MessageStringOf(x)
}

func (*GenerateContentResponse_UsageMetadata) ProtoMessage() {}

func (x *GenerateContentResponse_UsageMetadata) ProtoReflect() protoreflect.Message {
	mi := &file_google_cloud_aiplatform_v1_prediction_service_proto_msgTypes[27]
	if x != nil {
		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
		if ms.LoadMessageInfo() == nil {
			ms.StoreMessageInfo(mi)
		}
		return ms
	}
	return mi.MessageOf(x)
}

// Deprecated: Use GenerateContentResponse_UsageMetadata.ProtoReflect.Descriptor instead.
func (*GenerateContentResponse_UsageMetadata) Descriptor() ([]byte, []int) {
	return file_google_cloud_aiplatform_v1_prediction_service_proto_rawDescGZIP(), []int{21, 1}
}

func (x *GenerateContentResponse_UsageMetadata) GetPromptTokenCount() int32 {
	if x != nil {
		return x.PromptTokenCount
	}
	return 0
}

func (x *GenerateContentResponse_UsageMetadata) GetCandidatesTokenCount() int32 {
	if x != nil {
		return x.CandidatesTokenCount
	}
	return 0
}

func (x *GenerateContentResponse_UsageMetadata) GetThoughtsTokenCount() int32 {
	if x != nil {
		return x.ThoughtsTokenCount
	}
	return 0
}

func (x *GenerateContentResponse_UsageMetadata) GetTotalTokenCount() int32 {
	if x != nil {
		return x.TotalTokenCount
	}
	return 0
}

func (x *GenerateContentResponse_UsageMetadata) GetCachedContentTokenCount() int32 {
	if x != nil {
		return x.CachedContentTokenCount
	}
	return 0
}

func (x *GenerateContentResponse_UsageMetadata) GetPromptTokensDetails() []*ModalityTokenCount {
	if x != nil {
		return x.PromptTokensDetails
	}
	return nil
}

func (x *GenerateContentResponse_UsageMetadata) GetCacheTokensDetails() []*ModalityTokenCount {
	if x != nil {
		return x.CacheTokensDetails
	}
	return nil
}

func (x *GenerateContentResponse_UsageMetadata) GetCandidatesTokensDetails() []*ModalityTokenCount {
	if x != nil {
		return x.CandidatesTokensDetails
	}
	return nil
}

func (x *GenerateContentResponse_UsageMetadata) GetToolUsePromptTokensDetails() []*ModalityTokenCount {
	if x != nil {
		return x.ToolUsePromptTokensDetails
	}
	return nil
}

func (x *GenerateContentResponse_UsageMetadata) GetTrafficType() GenerateContentResponse_UsageMetadata_TrafficType {
	if x != nil {
		return x.TrafficType
	}
	return GenerateContentResponse_UsageMetadata_TRAFFIC_TYPE_UNSPECIFIED
}

// Configurations for the EmbedContent API.
type EmbedContentRequest_EmbedContentConfig struct {
	state protoimpl.MessageState `protogen:"open.v1"`
	// Optional. The title for the text.
	//
	// Only applicable to text-only embedding models.
	Title *string `protobuf:"bytes,1,opt,name=title,proto3,oneof" json:"title,omitempty"`
	// Optional. The task type of the embedding.
	//
	// Only applicable to text-only embedding models.
	TaskType *EmbedContentRequest_EmbeddingTaskType `protobuf:"varint,2,opt,name=task_type,json=taskType,proto3,enum=google.cloud.aiplatform.v1.EmbedContentRequest_EmbeddingTaskType,oneof" json:"task_type,omitempty"`
	// Optional. Whether to silently truncate the input content if it's longer
	// than the maximum sequence length.
	//
	// Only applicable to text-only embedding models.
	AutoTruncate *bool `protobuf:"varint,3,opt,name=auto_truncate,json=autoTruncate,proto3,oneof" json:"auto_truncate,omitempty"`
	// Optional. Reduced dimension for the output embedding. If set, excessive
	// values in the output embedding are truncated from the end.
	OutputDimensionality *int32 `protobuf:"varint,4,opt,name=output_dimensionality,json=outputDimensionality,proto3,oneof" json:"output_dimensionality,omitempty"`
	// Optional. Whether to enable OCR for document content.
	DocumentOcr *bool `protobuf:"varint,5,opt,name=document_ocr,json=documentOcr,proto3,oneof" json:"document_ocr,omitempty"`
	// Optional. Whether to extract audio from video content.
	AudioTrackExtraction *bool `protobuf:"varint,6,opt,name=audio_track_extraction,json=audioTrackExtraction,proto3,oneof" json:"audio_track_extraction,omitempty"`
	unknownFields        protoimpl.UnknownFields
	sizeCache            protoimpl.SizeCache
}

func (x *EmbedContentRequest_EmbedContentConfig) Reset() {
	*x = EmbedContentRequest_EmbedContentConfig{}
	mi := &file_google_cloud_aiplatform_v1_prediction_service_proto_msgTypes[28]
	ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
	ms.StoreMessageInfo(mi)
}

func (x *EmbedContentRequest_EmbedContentConfig) String() string {
	return protoimpl.X.MessageStringOf(x)
}

func (*EmbedContentRequest_EmbedContentConfig) ProtoMessage() {}

func (x *EmbedContentRequest_EmbedContentConfig) ProtoReflect() protoreflect.Message {
	mi := &file_google_cloud_aiplatform_v1_prediction_service_proto_msgTypes[28]
	if x != nil {
		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
		if ms.LoadMessageInfo() == nil {
			ms.StoreMessageInfo(mi)
		}
		return ms
	}
	return mi.MessageOf(x)
}

// Deprecated: Use EmbedContentRequest_EmbedContentConfig.ProtoReflect.Descriptor instead.
func (*EmbedContentRequest_EmbedContentConfig) Descriptor() ([]byte, []int) {
	return file_google_cloud_aiplatform_v1_prediction_service_proto_rawDescGZIP(), []int{22, 0}
}

func (x *EmbedContentRequest_EmbedContentConfig) GetTitle() string {
	if x != nil && x.Title != nil {
		return *x.Title
	}
	return ""
}

func (x *EmbedContentRequest_EmbedContentConfig) GetTaskType() EmbedContentRequest_EmbeddingTaskType {
	if x != nil && x.TaskType != nil {
		return *x.TaskType
	}
	return EmbedContentRequest_UNSPECIFIED
}

func (x *EmbedContentRequest_EmbedContentConfig) GetAutoTruncate() bool {
	if x != nil && x.AutoTruncate != nil {
		return *x.AutoTruncate
	}
	return false
}

func (x *EmbedContentRequest_EmbedContentConfig) GetOutputDimensionality() int32 {
	if x != nil && x.OutputDimensionality != nil {
		return *x.OutputDimensionality
	}
	return 0
}

func (x *EmbedContentRequest_EmbedContentConfig) GetDocumentOcr() bool {
	if x != nil && x.DocumentOcr != nil {
		return *x.DocumentOcr
	}
	return false
}

func (x *EmbedContentRequest_EmbedContentConfig) GetAudioTrackExtraction() bool {
	if x != nil && x.AudioTrackExtraction != nil {
		return *x.AudioTrackExtraction
	}
	return false
}

// A list of floats representing an embedding.
type EmbedContentResponse_Embedding struct {
	state protoimpl.MessageState `protogen:"open.v1"`
	// Embedding vector values.
	Values        []float32 `protobuf:"fixed32,1,rep,packed,name=values,proto3" json:"values,omitempty"`
	unknownFields protoimpl.UnknownFields
	sizeCache     protoimpl.SizeCache
}

func (x *EmbedContentResponse_Embedding) Reset() {
	*x = EmbedContentResponse_Embedding{}
	mi := &file_google_cloud_aiplatform_v1_prediction_service_proto_msgTypes[29]
	ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
	ms.StoreMessageInfo(mi)
}

func (x *EmbedContentResponse_Embedding) String() string {
	return protoimpl.X.MessageStringOf(x)
}

func (*EmbedContentResponse_Embedding) ProtoMessage() {}

func (x *EmbedContentResponse_Embedding) ProtoReflect() protoreflect.Message {
	mi := &file_google_cloud_aiplatform_v1_prediction_service_proto_msgTypes[29]
	if x != nil {
		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
		if ms.LoadMessageInfo() == nil {
			ms.StoreMessageInfo(mi)
		}
		return ms
	}
	return mi.MessageOf(x)
}

// Deprecated: Use EmbedContentResponse_Embedding.ProtoReflect.Descriptor instead.
func (*EmbedContentResponse_Embedding) Descriptor() ([]byte, []int) {
	return file_google_cloud_aiplatform_v1_prediction_service_proto_rawDescGZIP(), []int{23, 0}
}

func (x *EmbedContentResponse_Embedding) GetValues() []float32 {
	if x != nil {
		return x.Values
	}
	return nil
}

var File_google_cloud_aiplatform_v1_prediction_service_proto protoreflect.FileDescriptor

const file_google_cloud_aiplatform_v1_prediction_service_proto_rawDesc = "" +
	"\n" +
	"3google/cloud/aiplatform/v1/prediction_service.proto\x12\x1agoogle.cloud.aiplatform.v1\x1a\x1cgoogle/api/annotations.proto\x1a\x17google/api/client.proto\x1a\x1fgoogle/api/field_behavior.proto\x1a\x19google/api/httpbody.proto\x1a\x19google/api/resource.proto\x1a(google/cloud/aiplatform/v1/content.proto\x1a,google/cloud/aiplatform/v1/explanation.proto\x1a%google/cloud/aiplatform/v1/tool.proto\x1a&google/cloud/aiplatform/v1/types.proto\x1a/google/cloud/aiplatform/v1/usage_metadata.proto\x1a\x1cgoogle/protobuf/struct.proto\x1a\x1fgoogle/protobuf/timestamp.proto\"\xdb\x02\n" +
	"\x0ePredictRequest\x12F\n" +
	"\bendpoint\x18\x01 \x01(\tB*\xe0A\x02\xfaA$\n" +
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	"\tinstances\x18\x02 \x03(\v2\x16.google.protobuf.ValueB\x03\xe0A\x02R\tinstances\x126\n" +
	"\n" +
	"parameters\x18\x03 \x01(\v2\x16.google.protobuf.ValueR\n" +
	"parameters\x12S\n" +
	"\x06labels\x18\x04 \x03(\v26.google.cloud.aiplatform.v1.PredictRequest.LabelsEntryB\x03\xe0A\x01R\x06labels\x1a9\n" +
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	"methodName\x12\x14\n" +
	"\x05input\x18\x03 \x01(\fR\x05input\"5\n" +
	"\x1bStreamingRawPredictResponse\x12\x16\n" +
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	"\"aiplatform.googleapis.com/EndpointR\bendpoint\x129\n" +
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	"\n" +
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	"\x19explanation_spec_override\x18\x05 \x01(\v23.google.cloud.aiplatform.v1.ExplanationSpecOverrideR\x17explanationSpecOverride\x12*\n" +
	"\x11deployed_model_id\x18\x03 \x01(\tR\x0fdeployedModelId\"\xc4\x01\n" +
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	"\x11deployed_model_id\x18\x02 \x01(\tR\x0fdeployedModelId\x128\n" +
	"\vpredictions\x18\x03 \x03(\v2\x16.google.protobuf.ValueR\vpredictions\"\xa5\x04\n" +
	"\x12CountTokensRequest\x12F\n" +
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	"\"aiplatform.googleapis.com/EndpointR\bendpoint\x12\x19\n" +
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	"\x13_system_instructionB\x14\n" +
	"\x12_generation_config\"\xdd\x01\n" +
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	"\x19total_billable_characters\x18\x02 \x01(\x05R\x17totalBillableCharacters\x12g\n" +
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	"toolConfig\x12[\n" +
	"\x06labels\x18\n" +
	" \x03(\v2>.google.cloud.aiplatform.v1.GenerateContentRequest.LabelsEntryB\x03\xe0A\x01R\x06labels\x12W\n" +
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	"\tBLOCKLIST\x10\x03\x12\x16\n" +
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	"\vMODEL_ARMOR\x10\x05\x12\r\n" +
	"\tJAILBREAK\x10\x06\x1a\xce\a\n" +
	"\rUsageMetadata\x12,\n" +
	"\x12prompt_token_count\x18\x01 \x01(\x05R\x10promptTokenCount\x124\n" +
	"\x16candidates_token_count\x18\x02 \x01(\x05R\x14candidatesTokenCount\x125\n" +
	"\x14thoughts_token_count\x18\x0e \x01(\x05B\x03\xe0A\x03R\x12thoughtsTokenCount\x12*\n" +
	"\x11total_token_count\x18\x03 \x01(\x05R\x0ftotalTokenCount\x12@\n" +
	"\x1acached_content_token_count\x18\x05 \x01(\x05B\x03\xe0A\x03R\x17cachedContentTokenCount\x12g\n" +
	"\x15prompt_tokens_details\x18\t \x03(\v2..google.cloud.aiplatform.v1.ModalityTokenCountB\x03\xe0A\x03R\x13promptTokensDetails\x12e\n" +
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	"\x1etool_use_prompt_tokens_details\x18\f \x03(\v2..google.cloud.aiplatform.v1.ModalityTokenCountB\x03\xe0A\x03R\x1atoolUsePromptTokensDetails\x12u\n" +
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	"\vTrafficType\x12\x1c\n" +
	"\x18TRAFFIC_TYPE_UNSPECIFIED\x10\x00\x12\r\n" +
	"\tON_DEMAND\x10\x01\x12\x16\n" +
	"\x12ON_DEMAND_PRIORITY\x10\x03\x12\x12\n" +
	"\x0eON_DEMAND_FLEX\x10\x04\x12\x1a\n" +
	"\x16PROVISIONED_THROUGHPUT\x10\x02\"\xd6\n" +
	"\n" +
	"\x13EmbedContentRequest\x12B\n" +
	"\x05model\x18\x01 \x01(\tB'\xfaA$\n" +
	"\"aiplatform.googleapis.com/EndpointH\x00R\x05model\x88\x01\x01\x12B\n" +
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	"\x12EmbedContentConfig\x12\x1e\n" +
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	"\x06_titleB\f\n" +
	"\n" +
	"_task_typeB\x10\n" +
	"\x0e_auto_truncateB\x18\n" +
	"\x16_output_dimensionalityB\x0f\n" +
	"\r_document_ocrB\x19\n" +
	"\x17_audio_track_extraction\"\xd7\x01\n" +
	"\x11EmbeddingTaskType\x12\x0f\n" +
	"\vUNSPECIFIED\x10\x00\x12\x13\n" +
	"\x0fRETRIEVAL_QUERY\x10\x02\x12\x16\n" +
	"\x12RETRIEVAL_DOCUMENT\x10\x03\x12\x17\n" +
	"\x13SEMANTIC_SIMILARITY\x10\x04\x12\x12\n" +
	"\x0eCLASSIFICATION\x10\x05\x12\x0e\n" +
	"\n" +
	"CLUSTERING\x10\x06\x12\x16\n" +
	"\x12QUESTION_ANSWERING\x10\a\x12\x15\n" +
	"\x11FACT_VERIFICATION\x10\b\x12\x18\n" +
	"\x14CODE_RETRIEVAL_QUERY\x10\tB\b\n" +
	"\x06_modelB\n" +
	"\n" +
	"\b_contentB\b\n" +
	"\x06_titleB\f\n" +
	"\n" +
	"_task_typeB\x18\n" +
	"\x16_output_dimensionalityB\x10\n" +
	"\x0e_auto_truncateB\x17\n" +
	"\x15_embed_content_config\"\x85\x02\n" +
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	"\ttruncated\x18\x04 \x01(\bR\ttruncated\x1a#\n" +
	"\tEmbedding\x12\x16\n" +
	"\x06values\x18\x01 \x03(\x02R\x06values2\xc8\x1b\n" +
	"\x11PredictionService\x12\x94\x02\n" +
	"\aPredict\x12*.google.cloud.aiplatform.v1.PredictRequest\x1a+.google.cloud.aiplatform.v1.PredictResponse\"\xaf\x01\xdaA\x1dendpoint,instances,parameters\x82\xd3\xe4\x93\x02\x88\x01:\x01*ZH:\x01*\"C/v1/{endpoint=projects/*/locations/*/publishers/*/models/*}:predict\"9/v1/{endpoint=projects/*/locations/*/endpoints/*}:predict\x12\xfe\x01\n" +
	"\n" +
	"RawPredict\x12-.google.cloud.aiplatform.v1.RawPredictRequest\x1a\x14.google.api.HttpBody\"\xaa\x01\xdaA\x12endpoint,http_body\x82\xd3\xe4\x93\x02\x8e\x01:\x01*ZK:\x01*\"F/v1/{endpoint=projects/*/locations/*/publishers/*/models/*}:rawPredict\"</v1/{endpoint=projects/*/locations/*/endpoints/*}:rawPredict\x12\x98\x02\n" +
	"\x10StreamRawPredict\x123.google.cloud.aiplatform.v1.StreamRawPredictRequest\x1a\x14.google.api.HttpBody\"\xb6\x01\xdaA\x12endpoint,http_body\x82\xd3\xe4\x93\x02\x9a\x01:\x01*ZQ:\x01*\"L/v1/{endpoint=projects/*/locations/*/publishers/*/models/*}:streamRawPredict\"B/v1/{endpoint=projects/*/locations/*/endpoints/*}:streamRawPredict0\x01\x12\xc0\x01\n" +
	"\rDirectPredict\x120.google.cloud.aiplatform.v1.DirectPredictRequest\x1a1.google.cloud.aiplatform.v1.DirectPredictResponse\"J\x82\xd3\xe4\x93\x02D:\x01*\"?/v1/{endpoint=projects/*/locations/*/endpoints/*}:directPredict\x12\xcc\x01\n" +
	"\x10DirectRawPredict\x123.google.cloud.aiplatform.v1.DirectRawPredictRequest\x1a4.google.cloud.aiplatform.v1.DirectRawPredictResponse\"M\x82\xd3\xe4\x93\x02G:\x01*\"B/v1/{endpoint=projects/*/locations/*/endpoints/*}:directRawPredict\x12\x8c\x01\n" +
	"\x13StreamDirectPredict\x126.google.cloud.aiplatform.v1.StreamDirectPredictRequest\x1a7.google.cloud.aiplatform.v1.StreamDirectPredictResponse\"\x00(\x010\x01\x12\x95\x01\n" +
	"\x16StreamDirectRawPredict\x129.google.cloud.aiplatform.v1.StreamDirectRawPredictRequest\x1a:.google.cloud.aiplatform.v1.StreamDirectRawPredictResponse\"\x00(\x010\x01\x12\x83\x01\n" +
	"\x10StreamingPredict\x123.google.cloud.aiplatform.v1.StreamingPredictRequest\x1a4.google.cloud.aiplatform.v1.StreamingPredictResponse\"\x00(\x010\x01\x12\xb5\x02\n" +
	"\x16ServerStreamingPredict\x123.google.cloud.aiplatform.v1.StreamingPredictRequest\x1a4.google.cloud.aiplatform.v1.StreamingPredictResponse\"\xad\x01\x82\xd3\xe4\x93\x02\xa6\x01:\x01*ZW:\x01*\"R/v1/{endpoint=projects/*/locations/*/publishers/*/models/*}:serverStreamingPredict\"H/v1/{endpoint=projects/*/locations/*/endpoints/*}:serverStreamingPredict0\x01\x12\x8c\x01\n" +
	"\x13StreamingRawPredict\x126.google.cloud.aiplatform.v1.StreamingRawPredictRequest\x1a7.google.cloud.aiplatform.v1.StreamingRawPredictResponse\"\x00(\x010\x01\x12\xda\x01\n" +
	"\aExplain\x12*.google.cloud.aiplatform.v1.ExplainRequest\x1a+.google.cloud.aiplatform.v1.ExplainResponse\"v\xdaA/endpoint,instances,parameters,deployed_model_id\x82\xd3\xe4\x93\x02>:\x01*\"9/v1/{endpoint=projects/*/locations/*/endpoints/*}:explain\x12\x8d\x03\n" +
	"\x0fGenerateContent\x122.google.cloud.aiplatform.v1.GenerateContentRequest\x1a3.google.cloud.aiplatform.v1.GenerateContentResponse\"\x90\x02\xdaA\x0emodel,contents\x82\xd3\xe4\x93\x02\xf8\x01:\x01*ZM:\x01*\"H/v1/{model=projects/*/locations/*/publishers/*/models/*}:generateContentZ,:\x01*\"'/v1/{model=endpoints/*}:generateContentZ6:\x01*\"1/v1/{model=publishers/*/models/*}:generateContent\">/v1/{model=projects/*/locations/*/endpoints/*}:generateContent\x12\xad\x03\n" +
	"\x15StreamGenerateContent\x122.google.cloud.aiplatform.v1.GenerateContentRequest\x1a3.google.cloud.aiplatform.v1.GenerateContentResponse\"\xa8\x02\xdaA\x0emodel,contents\x82\xd3\xe4\x93\x02\x90\x02:\x01*ZS:\x01*\"N/v1/{model=projects/*/locations/*/publishers/*/models/*}:streamGenerateContentZ2:\x01*\"-/v1/{model=endpoints/*}:streamGenerateContentZ<:\x01*\"7/v1/{model=publishers/*/models/*}:streamGenerateContent\"D/v1/{model=projects/*/locations/*/endpoints/*}:streamGenerateContent0\x01\x12\xd3\x01\n" +
	"\fEmbedContent\x12/.google.cloud.aiplatform.v1.EmbedContentRequest\x1a0.google.cloud.aiplatform.v1.EmbedContentResponse\"`\xdaA\rmodel,content\x82\xd3\xe4\x93\x02J:\x01*\"E/v1/{model=projects/*/locations/*/publishers/*/models/*}:embedContent\x1a\x86\x01\xcaA\x19aiplatform.googleapis.com\xd2Aghttps://www.googleapis.com/auth/cloud-platform,https://www.googleapis.com/auth/cloud-platform.read-onlyB\xd4\x01\n" +
	"\x1ecom.google.cloud.aiplatform.v1B\x16PredictionServiceProtoP\x01Z>cloud.google.com/go/aiplatform/apiv1/aiplatformpb;aiplatformpb\xaa\x02\x1aGoogle.Cloud.AIPlatform.V1\xca\x02\x1aGoogle\\Cloud\\AIPlatform\\V1\xea\x02\x1dGoogle::Cloud::AIPlatform::V1b\x06proto3"

var (
	file_google_cloud_aiplatform_v1_prediction_service_proto_rawDescOnce sync.Once
	file_google_cloud_aiplatform_v1_prediction_service_proto_rawDescData []byte
)

func file_google_cloud_aiplatform_v1_prediction_service_proto_rawDescGZIP() []byte {
	file_google_cloud_aiplatform_v1_prediction_service_proto_rawDescOnce.Do(func() {
		file_google_cloud_aiplatform_v1_prediction_service_proto_rawDescData = protoimpl.X.CompressGZIP(unsafe.Slice(unsafe.StringData(file_google_cloud_aiplatform_v1_prediction_service_proto_rawDesc), len(file_google_cloud_aiplatform_v1_prediction_service_proto_rawDesc)))
	})
	return file_google_cloud_aiplatform_v1_prediction_service_proto_rawDescData
}

var file_google_cloud_aiplatform_v1_prediction_service_proto_enumTypes = make([]protoimpl.EnumInfo, 3)
var file_google_cloud_aiplatform_v1_prediction_service_proto_msgTypes = make([]protoimpl.MessageInfo, 30)
var file_google_cloud_aiplatform_v1_prediction_service_proto_goTypes = []any{
	(GenerateContentResponse_PromptFeedback_BlockedReason)(0), // 0: google.cloud.aiplatform.v1.GenerateContentResponse.PromptFeedback.BlockedReason
	(GenerateContentResponse_UsageMetadata_TrafficType)(0),    // 1: google.cloud.aiplatform.v1.GenerateContentResponse.UsageMetadata.TrafficType
	(EmbedContentRequest_EmbeddingTaskType)(0),                // 2: google.cloud.aiplatform.v1.EmbedContentRequest.EmbeddingTaskType
	(*PredictRequest)(nil),                                    // 3: google.cloud.aiplatform.v1.PredictRequest
	(*PredictResponse)(nil),                                   // 4: google.cloud.aiplatform.v1.PredictResponse
	(*RawPredictRequest)(nil),                                 // 5: google.cloud.aiplatform.v1.RawPredictRequest
	(*StreamRawPredictRequest)(nil),                           // 6: google.cloud.aiplatform.v1.StreamRawPredictRequest
	(*DirectPredictRequest)(nil),                              // 7: google.cloud.aiplatform.v1.DirectPredictRequest
	(*DirectPredictResponse)(nil),                             // 8: google.cloud.aiplatform.v1.DirectPredictResponse
	(*DirectRawPredictRequest)(nil),                           // 9: google.cloud.aiplatform.v1.DirectRawPredictRequest
	(*DirectRawPredictResponse)(nil),                          // 10: google.cloud.aiplatform.v1.DirectRawPredictResponse
	(*StreamDirectPredictRequest)(nil),                        // 11: google.cloud.aiplatform.v1.StreamDirectPredictRequest
	(*StreamDirectPredictResponse)(nil),                       // 12: google.cloud.aiplatform.v1.StreamDirectPredictResponse
	(*StreamDirectRawPredictRequest)(nil),                     // 13: google.cloud.aiplatform.v1.StreamDirectRawPredictRequest
	(*StreamDirectRawPredictResponse)(nil),                    // 14: google.cloud.aiplatform.v1.StreamDirectRawPredictResponse
	(*StreamingPredictRequest)(nil),                           // 15: google.cloud.aiplatform.v1.StreamingPredictRequest
	(*StreamingPredictResponse)(nil),                          // 16: google.cloud.aiplatform.v1.StreamingPredictResponse
	(*StreamingRawPredictRequest)(nil),                        // 17: google.cloud.aiplatform.v1.StreamingRawPredictRequest
	(*StreamingRawPredictResponse)(nil),                       // 18: google.cloud.aiplatform.v1.StreamingRawPredictResponse
	(*ExplainRequest)(nil),                                    // 19: google.cloud.aiplatform.v1.ExplainRequest
	(*ExplainResponse)(nil),                                   // 20: google.cloud.aiplatform.v1.ExplainResponse
	(*CountTokensRequest)(nil),                                // 21: google.cloud.aiplatform.v1.CountTokensRequest
	(*CountTokensResponse)(nil),                               // 22: google.cloud.aiplatform.v1.CountTokensResponse
	(*GenerateContentRequest)(nil),                            // 23: google.cloud.aiplatform.v1.GenerateContentRequest
	(*GenerateContentResponse)(nil),                           // 24: google.cloud.aiplatform.v1.GenerateContentResponse
	(*EmbedContentRequest)(nil),                               // 25: google.cloud.aiplatform.v1.EmbedContentRequest
	(*EmbedContentResponse)(nil),                              // 26: google.cloud.aiplatform.v1.EmbedContentResponse
	nil,                                                       // 27: google.cloud.aiplatform.v1.PredictRequest.LabelsEntry
	nil,                                                       // 28: google.cloud.aiplatform.v1.GenerateContentRequest.LabelsEntry
	(*GenerateContentResponse_PromptFeedback)(nil),            // 29: google.cloud.aiplatform.v1.GenerateContentResponse.PromptFeedback
	(*GenerateContentResponse_UsageMetadata)(nil),             // 30: google.cloud.aiplatform.v1.GenerateContentResponse.UsageMetadata
	(*EmbedContentRequest_EmbedContentConfig)(nil),            // 31: google.cloud.aiplatform.v1.EmbedContentRequest.EmbedContentConfig
	(*EmbedContentResponse_Embedding)(nil),                    // 32: google.cloud.aiplatform.v1.EmbedContentResponse.Embedding
	(*structpb.Value)(nil),                                    // 33: google.protobuf.Value
	(*httpbody.HttpBody)(nil),                                 // 34: google.api.HttpBody
	(*Tensor)(nil),                                            // 35: google.cloud.aiplatform.v1.Tensor
	(*ExplanationSpecOverride)(nil),                           // 36: google.cloud.aiplatform.v1.ExplanationSpecOverride
	(*Explanation)(nil),                                       // 37: google.cloud.aiplatform.v1.Explanation
	(*Content)(nil),                                           // 38: google.cloud.aiplatform.v1.Content
	(*Tool)(nil),                                              // 39: google.cloud.aiplatform.v1.Tool
	(*GenerationConfig)(nil),                                  // 40: google.cloud.aiplatform.v1.GenerationConfig
	(*ModalityTokenCount)(nil),                                // 41: google.cloud.aiplatform.v1.ModalityTokenCount
	(*ToolConfig)(nil),                                        // 42: google.cloud.aiplatform.v1.ToolConfig
	(*SafetySetting)(nil),                                     // 43: google.cloud.aiplatform.v1.SafetySetting
	(*ModelArmorConfig)(nil),                                  // 44: google.cloud.aiplatform.v1.ModelArmorConfig
	(*Candidate)(nil),                                         // 45: google.cloud.aiplatform.v1.Candidate
	(*timestamppb.Timestamp)(nil),                             // 46: google.protobuf.Timestamp
	(*UsageMetadata)(nil),                                     // 47: google.cloud.aiplatform.v1.UsageMetadata
	(*SafetyRating)(nil),                                      // 48: google.cloud.aiplatform.v1.SafetyRating
}
var file_google_cloud_aiplatform_v1_prediction_service_proto_depIdxs = []int32{
	33, // 0: google.cloud.aiplatform.v1.PredictRequest.instances:type_name -> google.protobuf.Value
	33, // 1: google.cloud.aiplatform.v1.PredictRequest.parameters:type_name -> google.protobuf.Value
	27, // 2: google.cloud.aiplatform.v1.PredictRequest.labels:type_name -> google.cloud.aiplatform.v1.PredictRequest.LabelsEntry
	33, // 3: google.cloud.aiplatform.v1.PredictResponse.predictions:type_name -> google.protobuf.Value
	33, // 4: google.cloud.aiplatform.v1.PredictResponse.metadata:type_name -> google.protobuf.Value
	34, // 5: google.cloud.aiplatform.v1.RawPredictRequest.http_body:type_name -> google.api.HttpBody
	34, // 6: google.cloud.aiplatform.v1.StreamRawPredictRequest.http_body:type_name -> google.api.HttpBody
	35, // 7: google.cloud.aiplatform.v1.DirectPredictRequest.inputs:type_name -> google.cloud.aiplatform.v1.Tensor
	35, // 8: google.cloud.aiplatform.v1.DirectPredictRequest.parameters:type_name -> google.cloud.aiplatform.v1.Tensor
	35, // 9: google.cloud.aiplatform.v1.DirectPredictResponse.outputs:type_name -> google.cloud.aiplatform.v1.Tensor
	35, // 10: google.cloud.aiplatform.v1.DirectPredictResponse.parameters:type_name -> google.cloud.aiplatform.v1.Tensor
	35, // 11: google.cloud.aiplatform.v1.StreamDirectPredictRequest.inputs:type_name -> google.cloud.aiplatform.v1.Tensor
	35, // 12: google.cloud.aiplatform.v1.StreamDirectPredictRequest.parameters:type_name -> google.cloud.aiplatform.v1.Tensor
	35, // 13: google.cloud.aiplatform.v1.StreamDirectPredictResponse.outputs:type_name -> google.cloud.aiplatform.v1.Tensor
	35, // 14: google.cloud.aiplatform.v1.StreamDirectPredictResponse.parameters:type_name -> google.cloud.aiplatform.v1.Tensor
	35, // 15: google.cloud.aiplatform.v1.StreamingPredictRequest.inputs:type_name -> google.cloud.aiplatform.v1.Tensor
	35, // 16: google.cloud.aiplatform.v1.StreamingPredictRequest.parameters:type_name -> google.cloud.aiplatform.v1.Tensor
	35, // 17: google.cloud.aiplatform.v1.StreamingPredictResponse.outputs:type_name -> google.cloud.aiplatform.v1.Tensor
	35, // 18: google.cloud.aiplatform.v1.StreamingPredictResponse.parameters:type_name -> google.cloud.aiplatform.v1.Tensor
	33, // 19: google.cloud.aiplatform.v1.ExplainRequest.instances:type_name -> google.protobuf.Value
	33, // 20: google.cloud.aiplatform.v1.ExplainRequest.parameters:type_name -> google.protobuf.Value
	36, // 21: google.cloud.aiplatform.v1.ExplainRequest.explanation_spec_override:type_name -> google.cloud.aiplatform.v1.ExplanationSpecOverride
	37, // 22: google.cloud.aiplatform.v1.ExplainResponse.explanations:type_name -> google.cloud.aiplatform.v1.Explanation
	33, // 23: google.cloud.aiplatform.v1.ExplainResponse.predictions:type_name -> google.protobuf.Value
	33, // 24: google.cloud.aiplatform.v1.CountTokensRequest.instances:type_name -> google.protobuf.Value
	38, // 25: google.cloud.aiplatform.v1.CountTokensRequest.contents:type_name -> google.cloud.aiplatform.v1.Content
	38, // 26: google.cloud.aiplatform.v1.CountTokensRequest.system_instruction:type_name -> google.cloud.aiplatform.v1.Content
	39, // 27: google.cloud.aiplatform.v1.CountTokensRequest.tools:type_name -> google.cloud.aiplatform.v1.Tool
	40, // 28: google.cloud.aiplatform.v1.CountTokensRequest.generation_config:type_name -> google.cloud.aiplatform.v1.GenerationConfig
	41, // 29: google.cloud.aiplatform.v1.CountTokensResponse.prompt_tokens_details:type_name -> google.cloud.aiplatform.v1.ModalityTokenCount
	38, // 30: google.cloud.aiplatform.v1.GenerateContentRequest.contents:type_name -> google.cloud.aiplatform.v1.Content
	38, // 31: google.cloud.aiplatform.v1.GenerateContentRequest.system_instruction:type_name -> google.cloud.aiplatform.v1.Content
	39, // 32: google.cloud.aiplatform.v1.GenerateContentRequest.tools:type_name -> google.cloud.aiplatform.v1.Tool
	42, // 33: google.cloud.aiplatform.v1.GenerateContentRequest.tool_config:type_name -> google.cloud.aiplatform.v1.ToolConfig
	28, // 34: google.cloud.aiplatform.v1.GenerateContentRequest.labels:type_name -> google.cloud.aiplatform.v1.GenerateContentRequest.LabelsEntry
	43, // 35: google.cloud.aiplatform.v1.GenerateContentRequest.safety_settings:type_name -> google.cloud.aiplatform.v1.SafetySetting
	44, // 36: google.cloud.aiplatform.v1.GenerateContentRequest.model_armor_config:type_name -> google.cloud.aiplatform.v1.ModelArmorConfig
	40, // 37: google.cloud.aiplatform.v1.GenerateContentRequest.generation_config:type_name -> google.cloud.aiplatform.v1.GenerationConfig
	45, // 38: google.cloud.aiplatform.v1.GenerateContentResponse.candidates:type_name -> google.cloud.aiplatform.v1.Candidate
	46, // 39: google.cloud.aiplatform.v1.GenerateContentResponse.create_time:type_name -> google.protobuf.Timestamp
	29, // 40: google.cloud.aiplatform.v1.GenerateContentResponse.prompt_feedback:type_name -> google.cloud.aiplatform.v1.GenerateContentResponse.PromptFeedback
	30, // 41: google.cloud.aiplatform.v1.GenerateContentResponse.usage_metadata:type_name -> google.cloud.aiplatform.v1.GenerateContentResponse.UsageMetadata
	38, // 42: google.cloud.aiplatform.v1.EmbedContentRequest.content:type_name -> google.cloud.aiplatform.v1.Content
	2,  // 43: google.cloud.aiplatform.v1.EmbedContentRequest.task_type:type_name -> google.cloud.aiplatform.v1.EmbedContentRequest.EmbeddingTaskType
	31, // 44: google.cloud.aiplatform.v1.EmbedContentRequest.embed_content_config:type_name -> google.cloud.aiplatform.v1.EmbedContentRequest.EmbedContentConfig
	32, // 45: google.cloud.aiplatform.v1.EmbedContentResponse.embedding:type_name -> google.cloud.aiplatform.v1.EmbedContentResponse.Embedding
	47, // 46: google.cloud.aiplatform.v1.EmbedContentResponse.usage_metadata:type_name -> google.cloud.aiplatform.v1.UsageMetadata
	0,  // 47: google.cloud.aiplatform.v1.GenerateContentResponse.PromptFeedback.block_reason:type_name -> google.cloud.aiplatform.v1.GenerateContentResponse.PromptFeedback.BlockedReason
	48, // 48: google.cloud.aiplatform.v1.GenerateContentResponse.PromptFeedback.safety_ratings:type_name -> google.cloud.aiplatform.v1.SafetyRating
	41, // 49: google.cloud.aiplatform.v1.GenerateContentResponse.UsageMetadata.prompt_tokens_details:type_name -> google.cloud.aiplatform.v1.ModalityTokenCount
	41, // 50: google.cloud.aiplatform.v1.GenerateContentResponse.UsageMetadata.cache_tokens_details:type_name -> google.cloud.aiplatform.v1.ModalityTokenCount
	41, // 51: google.cloud.aiplatform.v1.GenerateContentResponse.UsageMetadata.candidates_tokens_details:type_name -> google.cloud.aiplatform.v1.ModalityTokenCount
	41, // 52: google.cloud.aiplatform.v1.GenerateContentResponse.UsageMetadata.tool_use_prompt_tokens_details:type_name -> google.cloud.aiplatform.v1.ModalityTokenCount
	1,  // 53: google.cloud.aiplatform.v1.GenerateContentResponse.UsageMetadata.traffic_type:type_name -> google.cloud.aiplatform.v1.GenerateContentResponse.UsageMetadata.TrafficType
	2,  // 54: google.cloud.aiplatform.v1.EmbedContentRequest.EmbedContentConfig.task_type:type_name -> google.cloud.aiplatform.v1.EmbedContentRequest.EmbeddingTaskType
	3,  // 55: google.cloud.aiplatform.v1.PredictionService.Predict:input_type -> google.cloud.aiplatform.v1.PredictRequest
	5,  // 56: google.cloud.aiplatform.v1.PredictionService.RawPredict:input_type -> google.cloud.aiplatform.v1.RawPredictRequest
	6,  // 57: google.cloud.aiplatform.v1.PredictionService.StreamRawPredict:input_type -> google.cloud.aiplatform.v1.StreamRawPredictRequest
	7,  // 58: google.cloud.aiplatform.v1.PredictionService.DirectPredict:input_type -> google.cloud.aiplatform.v1.DirectPredictRequest
	9,  // 59: google.cloud.aiplatform.v1.PredictionService.DirectRawPredict:input_type -> google.cloud.aiplatform.v1.DirectRawPredictRequest
	11, // 60: google.cloud.aiplatform.v1.PredictionService.StreamDirectPredict:input_type -> google.cloud.aiplatform.v1.StreamDirectPredictRequest
	13, // 61: google.cloud.aiplatform.v1.PredictionService.StreamDirectRawPredict:input_type -> google.cloud.aiplatform.v1.StreamDirectRawPredictRequest
	15, // 62: google.cloud.aiplatform.v1.PredictionService.StreamingPredict:input_type -> google.cloud.aiplatform.v1.StreamingPredictRequest
	15, // 63: google.cloud.aiplatform.v1.PredictionService.ServerStreamingPredict:input_type -> google.cloud.aiplatform.v1.StreamingPredictRequest
	17, // 64: google.cloud.aiplatform.v1.PredictionService.StreamingRawPredict:input_type -> google.cloud.aiplatform.v1.StreamingRawPredictRequest
	19, // 65: google.cloud.aiplatform.v1.PredictionService.Explain:input_type -> google.cloud.aiplatform.v1.ExplainRequest
	23, // 66: google.cloud.aiplatform.v1.PredictionService.GenerateContent:input_type -> google.cloud.aiplatform.v1.GenerateContentRequest
	23, // 67: google.cloud.aiplatform.v1.PredictionService.StreamGenerateContent:input_type -> google.cloud.aiplatform.v1.GenerateContentRequest
	25, // 68: google.cloud.aiplatform.v1.PredictionService.EmbedContent:input_type -> google.cloud.aiplatform.v1.EmbedContentRequest
	4,  // 69: google.cloud.aiplatform.v1.PredictionService.Predict:output_type -> google.cloud.aiplatform.v1.PredictResponse
	34, // 70: google.cloud.aiplatform.v1.PredictionService.RawPredict:output_type -> google.api.HttpBody
	34, // 71: google.cloud.aiplatform.v1.PredictionService.StreamRawPredict:output_type -> google.api.HttpBody
	8,  // 72: google.cloud.aiplatform.v1.PredictionService.DirectPredict:output_type -> google.cloud.aiplatform.v1.DirectPredictResponse
	10, // 73: google.cloud.aiplatform.v1.PredictionService.DirectRawPredict:output_type -> google.cloud.aiplatform.v1.DirectRawPredictResponse
	12, // 74: google.cloud.aiplatform.v1.PredictionService.StreamDirectPredict:output_type -> google.cloud.aiplatform.v1.StreamDirectPredictResponse
	14, // 75: google.cloud.aiplatform.v1.PredictionService.StreamDirectRawPredict:output_type -> google.cloud.aiplatform.v1.StreamDirectRawPredictResponse
	16, // 76: google.cloud.aiplatform.v1.PredictionService.StreamingPredict:output_type -> google.cloud.aiplatform.v1.StreamingPredictResponse
	16, // 77: google.cloud.aiplatform.v1.PredictionService.ServerStreamingPredict:output_type -> google.cloud.aiplatform.v1.StreamingPredictResponse
	18, // 78: google.cloud.aiplatform.v1.PredictionService.StreamingRawPredict:output_type -> google.cloud.aiplatform.v1.StreamingRawPredictResponse
	20, // 79: google.cloud.aiplatform.v1.PredictionService.Explain:output_type -> google.cloud.aiplatform.v1.ExplainResponse
	24, // 80: google.cloud.aiplatform.v1.PredictionService.GenerateContent:output_type -> google.cloud.aiplatform.v1.GenerateContentResponse
	24, // 81: google.cloud.aiplatform.v1.PredictionService.StreamGenerateContent:output_type -> google.cloud.aiplatform.v1.GenerateContentResponse
	26, // 82: google.cloud.aiplatform.v1.PredictionService.EmbedContent:output_type -> google.cloud.aiplatform.v1.EmbedContentResponse
	69, // [69:83] is the sub-list for method output_type
	55, // [55:69] is the sub-list for method input_type
	55, // [55:55] is the sub-list for extension type_name
	55, // [55:55] is the sub-list for extension extendee
	0,  // [0:55] is the sub-list for field type_name
}

func init() { file_google_cloud_aiplatform_v1_prediction_service_proto_init() }
func file_google_cloud_aiplatform_v1_prediction_service_proto_init() {
	if File_google_cloud_aiplatform_v1_prediction_service_proto != nil {
		return
	}
	file_google_cloud_aiplatform_v1_content_proto_init()
	file_google_cloud_aiplatform_v1_explanation_proto_init()
	file_google_cloud_aiplatform_v1_tool_proto_init()
	file_google_cloud_aiplatform_v1_types_proto_init()
	file_google_cloud_aiplatform_v1_usage_metadata_proto_init()
	file_google_cloud_aiplatform_v1_prediction_service_proto_msgTypes[18].OneofWrappers = []any{}
	file_google_cloud_aiplatform_v1_prediction_service_proto_msgTypes[20].OneofWrappers = []any{}
	file_google_cloud_aiplatform_v1_prediction_service_proto_msgTypes[22].OneofWrappers = []any{}
	file_google_cloud_aiplatform_v1_prediction_service_proto_msgTypes[28].OneofWrappers = []any{}
	type x struct{}
	out := protoimpl.TypeBuilder{
		File: protoimpl.DescBuilder{
			GoPackagePath: reflect.TypeOf(x{}).PkgPath(),
			RawDescriptor: unsafe.Slice(unsafe.StringData(file_google_cloud_aiplatform_v1_prediction_service_proto_rawDesc), len(file_google_cloud_aiplatform_v1_prediction_service_proto_rawDesc)),
			NumEnums:      3,
			NumMessages:   30,
			NumExtensions: 0,
			NumServices:   1,
		},
		GoTypes:           file_google_cloud_aiplatform_v1_prediction_service_proto_goTypes,
		DependencyIndexes: file_google_cloud_aiplatform_v1_prediction_service_proto_depIdxs,
		EnumInfos:         file_google_cloud_aiplatform_v1_prediction_service_proto_enumTypes,
		MessageInfos:      file_google_cloud_aiplatform_v1_prediction_service_proto_msgTypes,
	}.Build()
	File_google_cloud_aiplatform_v1_prediction_service_proto = out.File
	file_google_cloud_aiplatform_v1_prediction_service_proto_goTypes = nil
	file_google_cloud_aiplatform_v1_prediction_service_proto_depIdxs = nil
}
