// Copyright 2025 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/v1/model_service.proto

package generativelanguagepb

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

	_ "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"
)

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_v1_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_v1_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_v1_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_v1_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_v1_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_v1_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_v1_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_v1_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_v1_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 ""
}

var File_google_ai_generativelanguage_v1_model_service_proto protoreflect.FileDescriptor

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}

var (
	file_google_ai_generativelanguage_v1_model_service_proto_rawDescOnce sync.Once
	file_google_ai_generativelanguage_v1_model_service_proto_rawDescData = file_google_ai_generativelanguage_v1_model_service_proto_rawDesc
)

func file_google_ai_generativelanguage_v1_model_service_proto_rawDescGZIP() []byte {
	file_google_ai_generativelanguage_v1_model_service_proto_rawDescOnce.Do(func() {
		file_google_ai_generativelanguage_v1_model_service_proto_rawDescData = protoimpl.X.CompressGZIP(file_google_ai_generativelanguage_v1_model_service_proto_rawDescData)
	})
	return file_google_ai_generativelanguage_v1_model_service_proto_rawDescData
}

var file_google_ai_generativelanguage_v1_model_service_proto_msgTypes = make([]protoimpl.MessageInfo, 3)
var file_google_ai_generativelanguage_v1_model_service_proto_goTypes = []any{
	(*GetModelRequest)(nil),    // 0: google.ai.generativelanguage.v1.GetModelRequest
	(*ListModelsRequest)(nil),  // 1: google.ai.generativelanguage.v1.ListModelsRequest
	(*ListModelsResponse)(nil), // 2: google.ai.generativelanguage.v1.ListModelsResponse
	(*Model)(nil),              // 3: google.ai.generativelanguage.v1.Model
}
var file_google_ai_generativelanguage_v1_model_service_proto_depIdxs = []int32{
	3, // 0: google.ai.generativelanguage.v1.ListModelsResponse.models:type_name -> google.ai.generativelanguage.v1.Model
	0, // 1: google.ai.generativelanguage.v1.ModelService.GetModel:input_type -> google.ai.generativelanguage.v1.GetModelRequest
	1, // 2: google.ai.generativelanguage.v1.ModelService.ListModels:input_type -> google.ai.generativelanguage.v1.ListModelsRequest
	3, // 3: google.ai.generativelanguage.v1.ModelService.GetModel:output_type -> google.ai.generativelanguage.v1.Model
	2, // 4: google.ai.generativelanguage.v1.ModelService.ListModels:output_type -> google.ai.generativelanguage.v1.ListModelsResponse
	3, // [3:5] is the sub-list for method output_type
	1, // [1:3] is the sub-list for method input_type
	1, // [1:1] is the sub-list for extension type_name
	1, // [1:1] is the sub-list for extension extendee
	0, // [0:1] is the sub-list for field type_name
}

func init() { file_google_ai_generativelanguage_v1_model_service_proto_init() }
func file_google_ai_generativelanguage_v1_model_service_proto_init() {
	if File_google_ai_generativelanguage_v1_model_service_proto != nil {
		return
	}
	file_google_ai_generativelanguage_v1_model_proto_init()
	type x struct{}
	out := protoimpl.TypeBuilder{
		File: protoimpl.DescBuilder{
			GoPackagePath: reflect.TypeOf(x{}).PkgPath(),
			RawDescriptor: file_google_ai_generativelanguage_v1_model_service_proto_rawDesc,
			NumEnums:      0,
			NumMessages:   3,
			NumExtensions: 0,
			NumServices:   1,
		},
		GoTypes:           file_google_ai_generativelanguage_v1_model_service_proto_goTypes,
		DependencyIndexes: file_google_ai_generativelanguage_v1_model_service_proto_depIdxs,
		MessageInfos:      file_google_ai_generativelanguage_v1_model_service_proto_msgTypes,
	}.Build()
	File_google_ai_generativelanguage_v1_model_service_proto = out.File
	file_google_ai_generativelanguage_v1_model_service_proto_rawDesc = nil
	file_google_ai_generativelanguage_v1_model_service_proto_goTypes = nil
	file_google_ai_generativelanguage_v1_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)
}

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.v1.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.v1.ModelService/ListModels", 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)
}

// 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 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.v1.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.v1.ModelService/ListModels",
	}
	handler := func(ctx context.Context, req interface{}) (interface{}, error) {
		return srv.(ModelServiceServer).ListModels(ctx, req.(*ListModelsRequest))
	}
	return interceptor(ctx, in, info, handler)
}

var _ModelService_serviceDesc = grpc.ServiceDesc{
	ServiceName: "google.ai.generativelanguage.v1.ModelService",
	HandlerType: (*ModelServiceServer)(nil),
	Methods: []grpc.MethodDesc{
		{
			MethodName: "GetModel",
			Handler:    _ModelService_GetModel_Handler,
		},
		{
			MethodName: "ListModels",
			Handler:    _ModelService_ListModels_Handler,
		},
	},
	Streams:  []grpc.StreamDesc{},
	Metadata: "google/ai/generativelanguage/v1/model_service.proto",
}
