// Copyright 2024 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 v1.35.2
// 	protoc        v4.25.3
// source: google/ai/generativelanguage/v1beta/model_service.proto

package generativelanguagepb

import (
	context "context"
	reflect "reflect"
	sync "sync"

	longrunningpb "cloud.google.com/go/longrunning/autogen/longrunningpb"
	_ "google.golang.org/genproto/googleapis/api/annotations"
	grpc "google.golang.org/grpc"
	codes "google.golang.org/grpc/codes"
	status "google.golang.org/grpc/status"
	protoreflect "google.golang.org/protobuf/reflect/protoreflect"
	protoimpl "google.golang.org/protobuf/runtime/protoimpl"
	emptypb "google.golang.org/protobuf/types/known/emptypb"
	fieldmaskpb "google.golang.org/protobuf/types/known/fieldmaskpb"
)

const (
	// Verify that this generated code is sufficiently up-to-date.
	_ = protoimpl.EnforceVersion(20 - protoimpl.MinVersion)
	// Verify that runtime/protoimpl is sufficiently up-to-date.
	_ = protoimpl.EnforceVersion(protoimpl.MaxVersion - 20)
)

// Request for getting information about a specific Model.
type GetModelRequest struct {
	state         protoimpl.MessageState
	sizeCache     protoimpl.SizeCache
	unknownFields protoimpl.UnknownFields

	// Required. The resource name of the model.
	//
	// This name should match a model name returned by the `ListModels` method.
	//
	// Format: `models/{model}`
	Name string `protobuf:"bytes,1,opt,name=name,proto3" json:"name,omitempty"`
}

func (x *GetModelRequest) Reset() {
	*x = GetModelRequest{}
	mi := &file_google_ai_generativelanguage_v1beta_model_service_proto_msgTypes[0]
	ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
	ms.StoreMessageInfo(mi)
}

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

func (*GetModelRequest) ProtoMessage() {}

func (x *GetModelRequest) ProtoReflect() protoreflect.Message {
	mi := &file_google_ai_generativelanguage_v1beta_model_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 GetModelRequest.ProtoReflect.Descriptor instead.
func (*GetModelRequest) Descriptor() ([]byte, []int) {
	return file_google_ai_generativelanguage_v1beta_model_service_proto_rawDescGZIP(), []int{0}
}

func (x *GetModelRequest) GetName() string {
	if x != nil {
		return x.Name
	}
	return ""
}

// Request for listing all Models.
type ListModelsRequest struct {
	state         protoimpl.MessageState
	sizeCache     protoimpl.SizeCache
	unknownFields protoimpl.UnknownFields

	// The maximum number of `Models` to return (per page).
	//
	// If unspecified, 50 models will be returned per page.
	// This method returns at most 1000 models per page, even if you pass a larger
	// page_size.
	PageSize int32 `protobuf:"varint,2,opt,name=page_size,json=pageSize,proto3" json:"page_size,omitempty"`
	// A page token, received from a previous `ListModels` call.
	//
	// Provide the `page_token` returned by one request as an argument to the next
	// request to retrieve the next page.
	//
	// When paginating, all other parameters provided to `ListModels` must match
	// the call that provided the page token.
	PageToken string `protobuf:"bytes,3,opt,name=page_token,json=pageToken,proto3" json:"page_token,omitempty"`
}

func (x *ListModelsRequest) Reset() {
	*x = ListModelsRequest{}
	mi := &file_google_ai_generativelanguage_v1beta_model_service_proto_msgTypes[1]
	ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
	ms.StoreMessageInfo(mi)
}

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

func (*ListModelsRequest) ProtoMessage() {}

func (x *ListModelsRequest) ProtoReflect() protoreflect.Message {
	mi := &file_google_ai_generativelanguage_v1beta_model_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 ListModelsRequest.ProtoReflect.Descriptor instead.
func (*ListModelsRequest) Descriptor() ([]byte, []int) {
	return file_google_ai_generativelanguage_v1beta_model_service_proto_rawDescGZIP(), []int{1}
}

func (x *ListModelsRequest) GetPageSize() int32 {
	if x != nil {
		return x.PageSize
	}
	return 0
}

func (x *ListModelsRequest) GetPageToken() string {
	if x != nil {
		return x.PageToken
	}
	return ""
}

// Response from `ListModel` containing a paginated list of Models.
type ListModelsResponse struct {
	state         protoimpl.MessageState
	sizeCache     protoimpl.SizeCache
	unknownFields protoimpl.UnknownFields

	// The returned Models.
	Models []*Model `protobuf:"bytes,1,rep,name=models,proto3" json:"models,omitempty"`
	// A token, which can be sent as `page_token` to retrieve the next page.
	//
	// If this field is omitted, there are no more pages.
	NextPageToken string `protobuf:"bytes,2,opt,name=next_page_token,json=nextPageToken,proto3" json:"next_page_token,omitempty"`
}

func (x *ListModelsResponse) Reset() {
	*x = ListModelsResponse{}
	mi := &file_google_ai_generativelanguage_v1beta_model_service_proto_msgTypes[2]
	ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
	ms.StoreMessageInfo(mi)
}

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

func (*ListModelsResponse) ProtoMessage() {}

func (x *ListModelsResponse) ProtoReflect() protoreflect.Message {
	mi := &file_google_ai_generativelanguage_v1beta_model_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 ListModelsResponse.ProtoReflect.Descriptor instead.
func (*ListModelsResponse) Descriptor() ([]byte, []int) {
	return file_google_ai_generativelanguage_v1beta_model_service_proto_rawDescGZIP(), []int{2}
}

func (x *ListModelsResponse) GetModels() []*Model {
	if x != nil {
		return x.Models
	}
	return nil
}

func (x *ListModelsResponse) GetNextPageToken() string {
	if x != nil {
		return x.NextPageToken
	}
	return ""
}

// Request for getting information about a specific Model.
type GetTunedModelRequest struct {
	state         protoimpl.MessageState
	sizeCache     protoimpl.SizeCache
	unknownFields protoimpl.UnknownFields

	// Required. The resource name of the model.
	//
	// Format: `tunedModels/my-model-id`
	Name string `protobuf:"bytes,1,opt,name=name,proto3" json:"name,omitempty"`
}

func (x *GetTunedModelRequest) Reset() {
	*x = GetTunedModelRequest{}
	mi := &file_google_ai_generativelanguage_v1beta_model_service_proto_msgTypes[3]
	ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
	ms.StoreMessageInfo(mi)
}

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

func (*GetTunedModelRequest) ProtoMessage() {}

func (x *GetTunedModelRequest) ProtoReflect() protoreflect.Message {
	mi := &file_google_ai_generativelanguage_v1beta_model_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 GetTunedModelRequest.ProtoReflect.Descriptor instead.
func (*GetTunedModelRequest) Descriptor() ([]byte, []int) {
	return file_google_ai_generativelanguage_v1beta_model_service_proto_rawDescGZIP(), []int{3}
}

func (x *GetTunedModelRequest) GetName() string {
	if x != nil {
		return x.Name
	}
	return ""
}

// Request for listing TunedModels.
type ListTunedModelsRequest struct {
	state         protoimpl.MessageState
	sizeCache     protoimpl.SizeCache
	unknownFields protoimpl.UnknownFields

	// Optional. The maximum number of `TunedModels` to return (per page).
	// The service may return fewer tuned models.
	//
	// If unspecified, at most 10 tuned models will be returned.
	// This method returns at most 1000 models per page, even if you pass a larger
	// page_size.
	PageSize int32 `protobuf:"varint,1,opt,name=page_size,json=pageSize,proto3" json:"page_size,omitempty"`
	// Optional. A page token, received from a previous `ListTunedModels` call.
	//
	// Provide the `page_token` returned by one request as an argument to the next
	// request to retrieve the next page.
	//
	// When paginating, all other parameters provided to `ListTunedModels`
	// must match the call that provided the page token.
	PageToken string `protobuf:"bytes,2,opt,name=page_token,json=pageToken,proto3" json:"page_token,omitempty"`
	// Optional. A filter is a full text search over the tuned model's description
	// and display name. By default, results will not include tuned models shared
	// with everyone.
	//
	// Additional operators:
	//   - owner:me
	//   - writers:me
	//   - readers:me
	//   - readers:everyone
	//
	// Examples:
	//
	//	"owner:me" returns all tuned models to which caller has owner role
	//	"readers:me" returns all tuned models to which caller has reader role
	//	"readers:everyone" returns all tuned models that are shared with everyone
	Filter string `protobuf:"bytes,3,opt,name=filter,proto3" json:"filter,omitempty"`
}

func (x *ListTunedModelsRequest) Reset() {
	*x = ListTunedModelsRequest{}
	mi := &file_google_ai_generativelanguage_v1beta_model_service_proto_msgTypes[4]
	ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
	ms.StoreMessageInfo(mi)
}

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

func (*ListTunedModelsRequest) ProtoMessage() {}

func (x *ListTunedModelsRequest) ProtoReflect() protoreflect.Message {
	mi := &file_google_ai_generativelanguage_v1beta_model_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 ListTunedModelsRequest.ProtoReflect.Descriptor instead.
func (*ListTunedModelsRequest) Descriptor() ([]byte, []int) {
	return file_google_ai_generativelanguage_v1beta_model_service_proto_rawDescGZIP(), []int{4}
}

func (x *ListTunedModelsRequest) GetPageSize() int32 {
	if x != nil {
		return x.PageSize
	}
	return 0
}

func (x *ListTunedModelsRequest) GetPageToken() string {
	if x != nil {
		return x.PageToken
	}
	return ""
}

func (x *ListTunedModelsRequest) GetFilter() string {
	if x != nil {
		return x.Filter
	}
	return ""
}

// Response from `ListTunedModels` containing a paginated list of Models.
type ListTunedModelsResponse struct {
	state         protoimpl.MessageState
	sizeCache     protoimpl.SizeCache
	unknownFields protoimpl.UnknownFields

	// The returned Models.
	TunedModels []*TunedModel `protobuf:"bytes,1,rep,name=tuned_models,json=tunedModels,proto3" json:"tuned_models,omitempty"`
	// A token, which can be sent as `page_token` to retrieve the next page.
	//
	// If this field is omitted, there are no more pages.
	NextPageToken string `protobuf:"bytes,2,opt,name=next_page_token,json=nextPageToken,proto3" json:"next_page_token,omitempty"`
}

func (x *ListTunedModelsResponse) Reset() {
	*x = ListTunedModelsResponse{}
	mi := &file_google_ai_generativelanguage_v1beta_model_service_proto_msgTypes[5]
	ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
	ms.StoreMessageInfo(mi)
}

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

func (*ListTunedModelsResponse) ProtoMessage() {}

func (x *ListTunedModelsResponse) ProtoReflect() protoreflect.Message {
	mi := &file_google_ai_generativelanguage_v1beta_model_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 ListTunedModelsResponse.ProtoReflect.Descriptor instead.
func (*ListTunedModelsResponse) Descriptor() ([]byte, []int) {
	return file_google_ai_generativelanguage_v1beta_model_service_proto_rawDescGZIP(), []int{5}
}

func (x *ListTunedModelsResponse) GetTunedModels() []*TunedModel {
	if x != nil {
		return x.TunedModels
	}
	return nil
}

func (x *ListTunedModelsResponse) GetNextPageToken() string {
	if x != nil {
		return x.NextPageToken
	}
	return ""
}

// Request to create a TunedModel.
type CreateTunedModelRequest struct {
	state         protoimpl.MessageState
	sizeCache     protoimpl.SizeCache
	unknownFields protoimpl.UnknownFields

	// Optional. The unique id for the tuned model if specified.
	// This value should be up to 40 characters, the first character must be a
	// letter, the last could be a letter or a number. The id must match the
	// regular expression: `[a-z]([a-z0-9-]{0,38}[a-z0-9])?`.
	TunedModelId *string `protobuf:"bytes,1,opt,name=tuned_model_id,json=tunedModelId,proto3,oneof" json:"tuned_model_id,omitempty"`
	// Required. The tuned model to create.
	TunedModel *TunedModel `protobuf:"bytes,2,opt,name=tuned_model,json=tunedModel,proto3" json:"tuned_model,omitempty"`
}

func (x *CreateTunedModelRequest) Reset() {
	*x = CreateTunedModelRequest{}
	mi := &file_google_ai_generativelanguage_v1beta_model_service_proto_msgTypes[6]
	ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
	ms.StoreMessageInfo(mi)
}

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

func (*CreateTunedModelRequest) ProtoMessage() {}

func (x *CreateTunedModelRequest) ProtoReflect() protoreflect.Message {
	mi := &file_google_ai_generativelanguage_v1beta_model_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 CreateTunedModelRequest.ProtoReflect.Descriptor instead.
func (*CreateTunedModelRequest) Descriptor() ([]byte, []int) {
	return file_google_ai_generativelanguage_v1beta_model_service_proto_rawDescGZIP(), []int{6}
}

func (x *CreateTunedModelRequest) GetTunedModelId() string {
	if x != nil && x.TunedModelId != nil {
		return *x.TunedModelId
	}
	return ""
}

func (x *CreateTunedModelRequest) GetTunedModel() *TunedModel {
	if x != nil {
		return x.TunedModel
	}
	return nil
}

// Metadata about the state and progress of creating a tuned model returned from
// the long-running operation
type CreateTunedModelMetadata struct {
	state         protoimpl.MessageState
	sizeCache     protoimpl.SizeCache
	unknownFields protoimpl.UnknownFields

	// Name of the tuned model associated with the tuning operation.
	TunedModel string `protobuf:"bytes,5,opt,name=tuned_model,json=tunedModel,proto3" json:"tuned_model,omitempty"`
	// The total number of tuning steps.
	TotalSteps int32 `protobuf:"varint,1,opt,name=total_steps,json=totalSteps,proto3" json:"total_steps,omitempty"`
	// The number of steps completed.
	CompletedSteps int32 `protobuf:"varint,2,opt,name=completed_steps,json=completedSteps,proto3" json:"completed_steps,omitempty"`
	// The completed percentage for the tuning operation.
	CompletedPercent float32 `protobuf:"fixed32,3,opt,name=completed_percent,json=completedPercent,proto3" json:"completed_percent,omitempty"`
	// Metrics collected during tuning.
	Snapshots []*TuningSnapshot `protobuf:"bytes,4,rep,name=snapshots,proto3" json:"snapshots,omitempty"`
}

func (x *CreateTunedModelMetadata) Reset() {
	*x = CreateTunedModelMetadata{}
	mi := &file_google_ai_generativelanguage_v1beta_model_service_proto_msgTypes[7]
	ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
	ms.StoreMessageInfo(mi)
}

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

func (*CreateTunedModelMetadata) ProtoMessage() {}

func (x *CreateTunedModelMetadata) ProtoReflect() protoreflect.Message {
	mi := &file_google_ai_generativelanguage_v1beta_model_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 CreateTunedModelMetadata.ProtoReflect.Descriptor instead.
func (*CreateTunedModelMetadata) Descriptor() ([]byte, []int) {
	return file_google_ai_generativelanguage_v1beta_model_service_proto_rawDescGZIP(), []int{7}
}

func (x *CreateTunedModelMetadata) GetTunedModel() string {
	if x != nil {
		return x.TunedModel
	}
	return ""
}

func (x *CreateTunedModelMetadata) GetTotalSteps() int32 {
	if x != nil {
		return x.TotalSteps
	}
	return 0
}

func (x *CreateTunedModelMetadata) GetCompletedSteps() int32 {
	if x != nil {
		return x.CompletedSteps
	}
	return 0
}

func (x *CreateTunedModelMetadata) GetCompletedPercent() float32 {
	if x != nil {
		return x.CompletedPercent
	}
	return 0
}

func (x *CreateTunedModelMetadata) GetSnapshots() []*TuningSnapshot {
	if x != nil {
		return x.Snapshots
	}
	return nil
}

// Request to update a TunedModel.
type UpdateTunedModelRequest struct {
	state         protoimpl.MessageState
	sizeCache     protoimpl.SizeCache
	unknownFields protoimpl.UnknownFields

	// Required. The tuned model to update.
	TunedModel *TunedModel `protobuf:"bytes,1,opt,name=tuned_model,json=tunedModel,proto3" json:"tuned_model,omitempty"`
	// Optional. The list of fields to update.
	UpdateMask *fieldmaskpb.FieldMask `protobuf:"bytes,2,opt,name=update_mask,json=updateMask,proto3" json:"update_mask,omitempty"`
}

func (x *UpdateTunedModelRequest) Reset() {
	*x = UpdateTunedModelRequest{}
	mi := &file_google_ai_generativelanguage_v1beta_model_service_proto_msgTypes[8]
	ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
	ms.StoreMessageInfo(mi)
}

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

func (*UpdateTunedModelRequest) ProtoMessage() {}

func (x *UpdateTunedModelRequest) ProtoReflect() protoreflect.Message {
	mi := &file_google_ai_generativelanguage_v1beta_model_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 UpdateTunedModelRequest.ProtoReflect.Descriptor instead.
func (*UpdateTunedModelRequest) Descriptor() ([]byte, []int) {
	return file_google_ai_generativelanguage_v1beta_model_service_proto_rawDescGZIP(), []int{8}
}

func (x *UpdateTunedModelRequest) GetTunedModel() *TunedModel {
	if x != nil {
		return x.TunedModel
	}
	return nil
}

func (x *UpdateTunedModelRequest) GetUpdateMask() *fieldmaskpb.FieldMask {
	if x != nil {
		return x.UpdateMask
	}
	return nil
}

// Request to delete a TunedModel.
type DeleteTunedModelRequest struct {
	state         protoimpl.MessageState
	sizeCache     protoimpl.SizeCache
	unknownFields protoimpl.UnknownFields

	// Required. The resource name of the model.
	// Format: `tunedModels/my-model-id`
	Name string `protobuf:"bytes,1,opt,name=name,proto3" json:"name,omitempty"`
}

func (x *DeleteTunedModelRequest) Reset() {
	*x = DeleteTunedModelRequest{}
	mi := &file_google_ai_generativelanguage_v1beta_model_service_proto_msgTypes[9]
	ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
	ms.StoreMessageInfo(mi)
}

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

func (*DeleteTunedModelRequest) ProtoMessage() {}

func (x *DeleteTunedModelRequest) ProtoReflect() protoreflect.Message {
	mi := &file_google_ai_generativelanguage_v1beta_model_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 DeleteTunedModelRequest.ProtoReflect.Descriptor instead.
func (*DeleteTunedModelRequest) Descriptor() ([]byte, []int) {
	return file_google_ai_generativelanguage_v1beta_model_service_proto_rawDescGZIP(), []int{9}
}

func (x *DeleteTunedModelRequest) GetName() string {
	if x != nil {
		return x.Name
	}
	return ""
}

var File_google_ai_generativelanguage_v1beta_model_service_proto protoreflect.FileDescriptor

var file_google_ai_generativelanguage_v1beta_model_service_proto_rawDesc = []byte{
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}

var (
	file_google_ai_generativelanguage_v1beta_model_service_proto_rawDescOnce sync.Once
	file_google_ai_generativelanguage_v1beta_model_service_proto_rawDescData = file_google_ai_generativelanguage_v1beta_model_service_proto_rawDesc
)

func file_google_ai_generativelanguage_v1beta_model_service_proto_rawDescGZIP() []byte {
	file_google_ai_generativelanguage_v1beta_model_service_proto_rawDescOnce.Do(func() {
		file_google_ai_generativelanguage_v1beta_model_service_proto_rawDescData = protoimpl.X.CompressGZIP(file_google_ai_generativelanguage_v1beta_model_service_proto_rawDescData)
	})
	return file_google_ai_generativelanguage_v1beta_model_service_proto_rawDescData
}

var file_google_ai_generativelanguage_v1beta_model_service_proto_msgTypes = make([]protoimpl.MessageInfo, 10)
var file_google_ai_generativelanguage_v1beta_model_service_proto_goTypes = []any{
	(*GetModelRequest)(nil),          // 0: google.ai.generativelanguage.v1beta.GetModelRequest
	(*ListModelsRequest)(nil),        // 1: google.ai.generativelanguage.v1beta.ListModelsRequest
	(*ListModelsResponse)(nil),       // 2: google.ai.generativelanguage.v1beta.ListModelsResponse
	(*GetTunedModelRequest)(nil),     // 3: google.ai.generativelanguage.v1beta.GetTunedModelRequest
	(*ListTunedModelsRequest)(nil),   // 4: google.ai.generativelanguage.v1beta.ListTunedModelsRequest
	(*ListTunedModelsResponse)(nil),  // 5: google.ai.generativelanguage.v1beta.ListTunedModelsResponse
	(*CreateTunedModelRequest)(nil),  // 6: google.ai.generativelanguage.v1beta.CreateTunedModelRequest
	(*CreateTunedModelMetadata)(nil), // 7: google.ai.generativelanguage.v1beta.CreateTunedModelMetadata
	(*UpdateTunedModelRequest)(nil),  // 8: google.ai.generativelanguage.v1beta.UpdateTunedModelRequest
	(*DeleteTunedModelRequest)(nil),  // 9: google.ai.generativelanguage.v1beta.DeleteTunedModelRequest
	(*Model)(nil),                    // 10: google.ai.generativelanguage.v1beta.Model
	(*TunedModel)(nil),               // 11: google.ai.generativelanguage.v1beta.TunedModel
	(*TuningSnapshot)(nil),           // 12: google.ai.generativelanguage.v1beta.TuningSnapshot
	(*fieldmaskpb.FieldMask)(nil),    // 13: google.protobuf.FieldMask
	(*longrunningpb.Operation)(nil),  // 14: google.longrunning.Operation
	(*emptypb.Empty)(nil),            // 15: google.protobuf.Empty
}
var file_google_ai_generativelanguage_v1beta_model_service_proto_depIdxs = []int32{
	10, // 0: google.ai.generativelanguage.v1beta.ListModelsResponse.models:type_name -> google.ai.generativelanguage.v1beta.Model
	11, // 1: google.ai.generativelanguage.v1beta.ListTunedModelsResponse.tuned_models:type_name -> google.ai.generativelanguage.v1beta.TunedModel
	11, // 2: google.ai.generativelanguage.v1beta.CreateTunedModelRequest.tuned_model:type_name -> google.ai.generativelanguage.v1beta.TunedModel
	12, // 3: google.ai.generativelanguage.v1beta.CreateTunedModelMetadata.snapshots:type_name -> google.ai.generativelanguage.v1beta.TuningSnapshot
	11, // 4: google.ai.generativelanguage.v1beta.UpdateTunedModelRequest.tuned_model:type_name -> google.ai.generativelanguage.v1beta.TunedModel
	13, // 5: google.ai.generativelanguage.v1beta.UpdateTunedModelRequest.update_mask:type_name -> google.protobuf.FieldMask
	0,  // 6: google.ai.generativelanguage.v1beta.ModelService.GetModel:input_type -> google.ai.generativelanguage.v1beta.GetModelRequest
	1,  // 7: google.ai.generativelanguage.v1beta.ModelService.ListModels:input_type -> google.ai.generativelanguage.v1beta.ListModelsRequest
	3,  // 8: google.ai.generativelanguage.v1beta.ModelService.GetTunedModel:input_type -> google.ai.generativelanguage.v1beta.GetTunedModelRequest
	4,  // 9: google.ai.generativelanguage.v1beta.ModelService.ListTunedModels:input_type -> google.ai.generativelanguage.v1beta.ListTunedModelsRequest
	6,  // 10: google.ai.generativelanguage.v1beta.ModelService.CreateTunedModel:input_type -> google.ai.generativelanguage.v1beta.CreateTunedModelRequest
	8,  // 11: google.ai.generativelanguage.v1beta.ModelService.UpdateTunedModel:input_type -> google.ai.generativelanguage.v1beta.UpdateTunedModelRequest
	9,  // 12: google.ai.generativelanguage.v1beta.ModelService.DeleteTunedModel:input_type -> google.ai.generativelanguage.v1beta.DeleteTunedModelRequest
	10, // 13: google.ai.generativelanguage.v1beta.ModelService.GetModel:output_type -> google.ai.generativelanguage.v1beta.Model
	2,  // 14: google.ai.generativelanguage.v1beta.ModelService.ListModels:output_type -> google.ai.generativelanguage.v1beta.ListModelsResponse
	11, // 15: google.ai.generativelanguage.v1beta.ModelService.GetTunedModel:output_type -> google.ai.generativelanguage.v1beta.TunedModel
	5,  // 16: google.ai.generativelanguage.v1beta.ModelService.ListTunedModels:output_type -> google.ai.generativelanguage.v1beta.ListTunedModelsResponse
	14, // 17: google.ai.generativelanguage.v1beta.ModelService.CreateTunedModel:output_type -> google.longrunning.Operation
	11, // 18: google.ai.generativelanguage.v1beta.ModelService.UpdateTunedModel:output_type -> google.ai.generativelanguage.v1beta.TunedModel
	15, // 19: google.ai.generativelanguage.v1beta.ModelService.DeleteTunedModel:output_type -> google.protobuf.Empty
	13, // [13:20] is the sub-list for method output_type
	6,  // [6:13] is the sub-list for method input_type
	6,  // [6:6] is the sub-list for extension type_name
	6,  // [6:6] is the sub-list for extension extendee
	0,  // [0:6] is the sub-list for field type_name
}

func init() { file_google_ai_generativelanguage_v1beta_model_service_proto_init() }
func file_google_ai_generativelanguage_v1beta_model_service_proto_init() {
	if File_google_ai_generativelanguage_v1beta_model_service_proto != nil {
		return
	}
	file_google_ai_generativelanguage_v1beta_model_proto_init()
	file_google_ai_generativelanguage_v1beta_tuned_model_proto_init()
	file_google_ai_generativelanguage_v1beta_model_service_proto_msgTypes[6].OneofWrappers = []any{}
	type x struct{}
	out := protoimpl.TypeBuilder{
		File: protoimpl.DescBuilder{
			GoPackagePath: reflect.TypeOf(x{}).PkgPath(),
			RawDescriptor: file_google_ai_generativelanguage_v1beta_model_service_proto_rawDesc,
			NumEnums:      0,
			NumMessages:   10,
			NumExtensions: 0,
			NumServices:   1,
		},
		GoTypes:           file_google_ai_generativelanguage_v1beta_model_service_proto_goTypes,
		DependencyIndexes: file_google_ai_generativelanguage_v1beta_model_service_proto_depIdxs,
		MessageInfos:      file_google_ai_generativelanguage_v1beta_model_service_proto_msgTypes,
	}.Build()
	File_google_ai_generativelanguage_v1beta_model_service_proto = out.File
	file_google_ai_generativelanguage_v1beta_model_service_proto_rawDesc = nil
	file_google_ai_generativelanguage_v1beta_model_service_proto_goTypes = nil
	file_google_ai_generativelanguage_v1beta_model_service_proto_depIdxs = nil
}

// Reference imports to suppress errors if they are not otherwise used.
var _ context.Context
var _ grpc.ClientConnInterface

// This is a compile-time assertion to ensure that this generated file
// is compatible with the grpc package it is being compiled against.
const _ = grpc.SupportPackageIsVersion6

// ModelServiceClient is the client API for ModelService service.
//
// For semantics around ctx use and closing/ending streaming RPCs, please refer to https://godoc.org/google.golang.org/grpc#ClientConn.NewStream.
type ModelServiceClient interface {
	// Gets information about a specific `Model` such as its version number, token
	// limits,
	// [parameters](https://ai.google.dev/gemini-api/docs/models/generative-models#model-parameters)
	// and other metadata. Refer to the [Gemini models
	// guide](https://ai.google.dev/gemini-api/docs/models/gemini) for detailed
	// model information.
	GetModel(ctx context.Context, in *GetModelRequest, opts ...grpc.CallOption) (*Model, error)
	// Lists the [`Model`s](https://ai.google.dev/gemini-api/docs/models/gemini)
	// available through the Gemini API.
	ListModels(ctx context.Context, in *ListModelsRequest, opts ...grpc.CallOption) (*ListModelsResponse, error)
	// Gets information about a specific TunedModel.
	GetTunedModel(ctx context.Context, in *GetTunedModelRequest, opts ...grpc.CallOption) (*TunedModel, error)
	// Lists created tuned models.
	ListTunedModels(ctx context.Context, in *ListTunedModelsRequest, opts ...grpc.CallOption) (*ListTunedModelsResponse, error)
	// Creates a tuned model.
	// Check intermediate tuning progress (if any) through the
	// [google.longrunning.Operations] service.
	//
	// Access status and results through the Operations service.
	// Example:
	//
	//	GET /v1/tunedModels/az2mb0bpw6i/operations/000-111-222
	CreateTunedModel(ctx context.Context, in *CreateTunedModelRequest, opts ...grpc.CallOption) (*longrunningpb.Operation, error)
	// Updates a tuned model.
	UpdateTunedModel(ctx context.Context, in *UpdateTunedModelRequest, opts ...grpc.CallOption) (*TunedModel, error)
	// Deletes a tuned model.
	DeleteTunedModel(ctx context.Context, in *DeleteTunedModelRequest, opts ...grpc.CallOption) (*emptypb.Empty, error)
}

type modelServiceClient struct {
	cc grpc.ClientConnInterface
}

func NewModelServiceClient(cc grpc.ClientConnInterface) ModelServiceClient {
	return &modelServiceClient{cc}
}

func (c *modelServiceClient) GetModel(ctx context.Context, in *GetModelRequest, opts ...grpc.CallOption) (*Model, error) {
	out := new(Model)
	err := c.cc.Invoke(ctx, "/google.ai.generativelanguage.v1beta.ModelService/GetModel", in, out, opts...)
	if err != nil {
		return nil, err
	}
	return out, nil
}

func (c *modelServiceClient) ListModels(ctx context.Context, in *ListModelsRequest, opts ...grpc.CallOption) (*ListModelsResponse, error) {
	out := new(ListModelsResponse)
	err := c.cc.Invoke(ctx, "/google.ai.generativelanguage.v1beta.ModelService/ListModels", in, out, opts...)
	if err != nil {
		return nil, err
	}
	return out, nil
}

func (c *modelServiceClient) GetTunedModel(ctx context.Context, in *GetTunedModelRequest, opts ...grpc.CallOption) (*TunedModel, error) {
	out := new(TunedModel)
	err := c.cc.Invoke(ctx, "/google.ai.generativelanguage.v1beta.ModelService/GetTunedModel", in, out, opts...)
	if err != nil {
		return nil, err
	}
	return out, nil
}

func (c *modelServiceClient) ListTunedModels(ctx context.Context, in *ListTunedModelsRequest, opts ...grpc.CallOption) (*ListTunedModelsResponse, error) {
	out := new(ListTunedModelsResponse)
	err := c.cc.Invoke(ctx, "/google.ai.generativelanguage.v1beta.ModelService/ListTunedModels", in, out, opts...)
	if err != nil {
		return nil, err
	}
	return out, nil
}

func (c *modelServiceClient) CreateTunedModel(ctx context.Context, in *CreateTunedModelRequest, opts ...grpc.CallOption) (*longrunningpb.Operation, error) {
	out := new(longrunningpb.Operation)
	err := c.cc.Invoke(ctx, "/google.ai.generativelanguage.v1beta.ModelService/CreateTunedModel", in, out, opts...)
	if err != nil {
		return nil, err
	}
	return out, nil
}

func (c *modelServiceClient) UpdateTunedModel(ctx context.Context, in *UpdateTunedModelRequest, opts ...grpc.CallOption) (*TunedModel, error) {
	out := new(TunedModel)
	err := c.cc.Invoke(ctx, "/google.ai.generativelanguage.v1beta.ModelService/UpdateTunedModel", in, out, opts...)
	if err != nil {
		return nil, err
	}
	return out, nil
}

func (c *modelServiceClient) DeleteTunedModel(ctx context.Context, in *DeleteTunedModelRequest, opts ...grpc.CallOption) (*emptypb.Empty, error) {
	out := new(emptypb.Empty)
	err := c.cc.Invoke(ctx, "/google.ai.generativelanguage.v1beta.ModelService/DeleteTunedModel", in, out, opts...)
	if err != nil {
		return nil, err
	}
	return out, nil
}

// ModelServiceServer is the server API for ModelService service.
type ModelServiceServer interface {
	// Gets information about a specific `Model` such as its version number, token
	// limits,
	// [parameters](https://ai.google.dev/gemini-api/docs/models/generative-models#model-parameters)
	// and other metadata. Refer to the [Gemini models
	// guide](https://ai.google.dev/gemini-api/docs/models/gemini) for detailed
	// model information.
	GetModel(context.Context, *GetModelRequest) (*Model, error)
	// Lists the [`Model`s](https://ai.google.dev/gemini-api/docs/models/gemini)
	// available through the Gemini API.
	ListModels(context.Context, *ListModelsRequest) (*ListModelsResponse, error)
	// Gets information about a specific TunedModel.
	GetTunedModel(context.Context, *GetTunedModelRequest) (*TunedModel, error)
	// Lists created tuned models.
	ListTunedModels(context.Context, *ListTunedModelsRequest) (*ListTunedModelsResponse, error)
	// Creates a tuned model.
	// Check intermediate tuning progress (if any) through the
	// [google.longrunning.Operations] service.
	//
	// Access status and results through the Operations service.
	// Example:
	//
	//	GET /v1/tunedModels/az2mb0bpw6i/operations/000-111-222
	CreateTunedModel(context.Context, *CreateTunedModelRequest) (*longrunningpb.Operation, error)
	// Updates a tuned model.
	UpdateTunedModel(context.Context, *UpdateTunedModelRequest) (*TunedModel, error)
	// Deletes a tuned model.
	DeleteTunedModel(context.Context, *DeleteTunedModelRequest) (*emptypb.Empty, error)
}

// UnimplementedModelServiceServer can be embedded to have forward compatible implementations.
type UnimplementedModelServiceServer struct {
}

func (*UnimplementedModelServiceServer) GetModel(context.Context, *GetModelRequest) (*Model, error) {
	return nil, status.Errorf(codes.Unimplemented, "method GetModel not implemented")
}
func (*UnimplementedModelServiceServer) ListModels(context.Context, *ListModelsRequest) (*ListModelsResponse, error) {
	return nil, status.Errorf(codes.Unimplemented, "method ListModels not implemented")
}
func (*UnimplementedModelServiceServer) GetTunedModel(context.Context, *GetTunedModelRequest) (*TunedModel, error) {
	return nil, status.Errorf(codes.Unimplemented, "method GetTunedModel not implemented")
}
func (*UnimplementedModelServiceServer) ListTunedModels(context.Context, *ListTunedModelsRequest) (*ListTunedModelsResponse, error) {
	return nil, status.Errorf(codes.Unimplemented, "method ListTunedModels not implemented")
}
func (*UnimplementedModelServiceServer) CreateTunedModel(context.Context, *CreateTunedModelRequest) (*longrunningpb.Operation, error) {
	return nil, status.Errorf(codes.Unimplemented, "method CreateTunedModel not implemented")
}
func (*UnimplementedModelServiceServer) UpdateTunedModel(context.Context, *UpdateTunedModelRequest) (*TunedModel, error) {
	return nil, status.Errorf(codes.Unimplemented, "method UpdateTunedModel not implemented")
}
func (*UnimplementedModelServiceServer) DeleteTunedModel(context.Context, *DeleteTunedModelRequest) (*emptypb.Empty, error) {
	return nil, status.Errorf(codes.Unimplemented, "method DeleteTunedModel not implemented")
}

func RegisterModelServiceServer(s *grpc.Server, srv ModelServiceServer) {
	s.RegisterService(&_ModelService_serviceDesc, srv)
}

func _ModelService_GetModel_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
	in := new(GetModelRequest)
	if err := dec(in); err != nil {
		return nil, err
	}
	if interceptor == nil {
		return srv.(ModelServiceServer).GetModel(ctx, in)
	}
	info := &grpc.UnaryServerInfo{
		Server:     srv,
		FullMethod: "/google.ai.generativelanguage.v1beta.ModelService/GetModel",
	}
	handler := func(ctx context.Context, req interface{}) (interface{}, error) {
		return srv.(ModelServiceServer).GetModel(ctx, req.(*GetModelRequest))
	}
	return interceptor(ctx, in, info, handler)
}

func _ModelService_ListModels_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
	in := new(ListModelsRequest)
	if err := dec(in); err != nil {
		return nil, err
	}
	if interceptor == nil {
		return srv.(ModelServiceServer).ListModels(ctx, in)
	}
	info := &grpc.UnaryServerInfo{
		Server:     srv,
		FullMethod: "/google.ai.generativelanguage.v1beta.ModelService/ListModels",
	}
	handler := func(ctx context.Context, req interface{}) (interface{}, error) {
		return srv.(ModelServiceServer).ListModels(ctx, req.(*ListModelsRequest))
	}
	return interceptor(ctx, in, info, handler)
}

func _ModelService_GetTunedModel_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
	in := new(GetTunedModelRequest)
	if err := dec(in); err != nil {
		return nil, err
	}
	if interceptor == nil {
		return srv.(ModelServiceServer).GetTunedModel(ctx, in)
	}
	info := &grpc.UnaryServerInfo{
		Server:     srv,
		FullMethod: "/google.ai.generativelanguage.v1beta.ModelService/GetTunedModel",
	}
	handler := func(ctx context.Context, req interface{}) (interface{}, error) {
		return srv.(ModelServiceServer).GetTunedModel(ctx, req.(*GetTunedModelRequest))
	}
	return interceptor(ctx, in, info, handler)
}

func _ModelService_ListTunedModels_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
	in := new(ListTunedModelsRequest)
	if err := dec(in); err != nil {
		return nil, err
	}
	if interceptor == nil {
		return srv.(ModelServiceServer).ListTunedModels(ctx, in)
	}
	info := &grpc.UnaryServerInfo{
		Server:     srv,
		FullMethod: "/google.ai.generativelanguage.v1beta.ModelService/ListTunedModels",
	}
	handler := func(ctx context.Context, req interface{}) (interface{}, error) {
		return srv.(ModelServiceServer).ListTunedModels(ctx, req.(*ListTunedModelsRequest))
	}
	return interceptor(ctx, in, info, handler)
}

func _ModelService_CreateTunedModel_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
	in := new(CreateTunedModelRequest)
	if err := dec(in); err != nil {
		return nil, err
	}
	if interceptor == nil {
		return srv.(ModelServiceServer).CreateTunedModel(ctx, in)
	}
	info := &grpc.UnaryServerInfo{
		Server:     srv,
		FullMethod: "/google.ai.generativelanguage.v1beta.ModelService/CreateTunedModel",
	}
	handler := func(ctx context.Context, req interface{}) (interface{}, error) {
		return srv.(ModelServiceServer).CreateTunedModel(ctx, req.(*CreateTunedModelRequest))
	}
	return interceptor(ctx, in, info, handler)
}

func _ModelService_UpdateTunedModel_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
	in := new(UpdateTunedModelRequest)
	if err := dec(in); err != nil {
		return nil, err
	}
	if interceptor == nil {
		return srv.(ModelServiceServer).UpdateTunedModel(ctx, in)
	}
	info := &grpc.UnaryServerInfo{
		Server:     srv,
		FullMethod: "/google.ai.generativelanguage.v1beta.ModelService/UpdateTunedModel",
	}
	handler := func(ctx context.Context, req interface{}) (interface{}, error) {
		return srv.(ModelServiceServer).UpdateTunedModel(ctx, req.(*UpdateTunedModelRequest))
	}
	return interceptor(ctx, in, info, handler)
}

func _ModelService_DeleteTunedModel_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
	in := new(DeleteTunedModelRequest)
	if err := dec(in); err != nil {
		return nil, err
	}
	if interceptor == nil {
		return srv.(ModelServiceServer).DeleteTunedModel(ctx, in)
	}
	info := &grpc.UnaryServerInfo{
		Server:     srv,
		FullMethod: "/google.ai.generativelanguage.v1beta.ModelService/DeleteTunedModel",
	}
	handler := func(ctx context.Context, req interface{}) (interface{}, error) {
		return srv.(ModelServiceServer).DeleteTunedModel(ctx, req.(*DeleteTunedModelRequest))
	}
	return interceptor(ctx, in, info, handler)
}

var _ModelService_serviceDesc = grpc.ServiceDesc{
	ServiceName: "google.ai.generativelanguage.v1beta.ModelService",
	HandlerType: (*ModelServiceServer)(nil),
	Methods: []grpc.MethodDesc{
		{
			MethodName: "GetModel",
			Handler:    _ModelService_GetModel_Handler,
		},
		{
			MethodName: "ListModels",
			Handler:    _ModelService_ListModels_Handler,
		},
		{
			MethodName: "GetTunedModel",
			Handler:    _ModelService_GetTunedModel_Handler,
		},
		{
			MethodName: "ListTunedModels",
			Handler:    _ModelService_ListTunedModels_Handler,
		},
		{
			MethodName: "CreateTunedModel",
			Handler:    _ModelService_CreateTunedModel_Handler,
		},
		{
			MethodName: "UpdateTunedModel",
			Handler:    _ModelService_UpdateTunedModel_Handler,
		},
		{
			MethodName: "DeleteTunedModel",
			Handler:    _ModelService_DeleteTunedModel_Handler,
		},
	},
	Streams:  []grpc.StreamDesc{},
	Metadata: "google/ai/generativelanguage/v1beta/model_service.proto",
}
