/// <reference types="node" />
import { ChannelCredentials, ChannelOptions, UntypedServiceImplementation, handleUnaryCall, Client, ClientUnaryCall, Metadata, CallOptions, ServiceError } from '@grpc/grpc-js';
import _m0 from 'protobufjs/minimal';
import { MlModelType, MlModel } from '../../../../../yandex/cloud/mdb/clickhouse/v1/ml_model';
import { FieldMask } from '../../../../../google/protobuf/field_mask';
import { Operation } from '../../../../../yandex/cloud/operation/operation';
export declare const protobufPackage = "yandex.cloud.mdb.clickhouse.v1";
export interface GetMlModelRequest {
    /** ID of the cluster that the model belongs to. */
    clusterId: string;
    /**
     * Name of the model to return.
     *
     * To get a model name make a [MlModelService.List] request.
     */
    mlModelName: string;
}
export interface ListMlModelsRequest {
    /** ID of the cluster that models belongs to. */
    clusterId: string;
    /**
     * The maximum number of results per page to return. If the number of available
     * results is larger than `page_size`, the service returns a [ListMlModelsResponse.next_page_token]
     * that can be used to get the next page of results in subsequent list requests.
     * Default value: 100.
     */
    pageSize: number;
    /**
     * Page token. To get the next page of results, set `page_token` to the
     * [ListMlModelsResponse.next_page_token] returned by the previous list request.
     */
    pageToken: string;
}
export interface ListMlModelsResponse {
    /** List of models in the specified cluster. */
    mlModels: MlModel[];
    /**
     * Token for getting the next page of the list. If the number of results is greater than
     * the specified [ListMlModelsRequest.page_size], use `next_page_token` as the value
     * for the [ListMlModelsRequest.page_token] parameter in the next list request.
     *
     * Each subsequent page will have its own `next_page_token` to continue paging through the results.
     */
    nextPageToken: string;
}
export interface CreateMlModelRequest {
    /**
     * ID of the cluster to create a model in.
     *
     * To get a cluster ID make a [ClusterService.List] request.
     */
    clusterId: string;
    /** Model name. The model name is one of the arguments of the modelEvaluate() function, which is used to call the model in ClickHouse. */
    mlModelName: string;
    /** Type of the model. */
    type: MlModelType;
    /** Model file URL. You can only use models stored in Object Storage. */
    uri: string;
}
export interface CreateMlModelMetadata {
    /** ID of the cluster that a model is being added to. */
    clusterId: string;
    /** Name of the the model that is being created. */
    mlModelName: string;
}
export interface UpdateMlModelRequest {
    /**
     * ID of the cluster to update the model in.
     *
     * To get a cluster ID make a [ClusterService.List] request.
     */
    clusterId: string;
    /** Name of the the model to update. */
    mlModelName: string;
    updateMask?: FieldMask;
    /** The new model file URL. You can only use models stored in Object Storage. */
    uri: string;
}
export interface UpdateMlModelMetadata {
    /** ID of the cluster that contains the model being updated. */
    clusterId: string;
    /** Name of the the model that is being updated. */
    mlModelName: string;
}
export interface DeleteMlModelRequest {
    /**
     * ID of the cluster to delete the model in.
     *
     * To get a cluster ID make a [ClusterService.List] request.
     */
    clusterId: string;
    /** Name of the the model to delete. */
    mlModelName: string;
}
export interface DeleteMlModelMetadata {
    /** ID of the cluster that contains the model being deleted. */
    clusterId: string;
    /** Name of the the model that is being deleted. */
    mlModelName: string;
}
export declare const GetMlModelRequest: {
    encode(message: GetMlModelRequest, writer?: _m0.Writer): _m0.Writer;
    decode(input: _m0.Reader | Uint8Array, length?: number): GetMlModelRequest;
    fromJSON(object: any): GetMlModelRequest;
    toJSON(message: GetMlModelRequest): unknown;
    fromPartial<I extends {
        clusterId?: string | undefined;
        mlModelName?: string | undefined;
    } & {
        clusterId?: string | undefined;
        mlModelName?: string | undefined;
    } & Record<Exclude<keyof I, keyof GetMlModelRequest>, never>>(object: I): GetMlModelRequest;
};
export declare const ListMlModelsRequest: {
    encode(message: ListMlModelsRequest, writer?: _m0.Writer): _m0.Writer;
    decode(input: _m0.Reader | Uint8Array, length?: number): ListMlModelsRequest;
    fromJSON(object: any): ListMlModelsRequest;
    toJSON(message: ListMlModelsRequest): unknown;
    fromPartial<I extends {
        clusterId?: string | undefined;
        pageSize?: number | undefined;
        pageToken?: string | undefined;
    } & {
        clusterId?: string | undefined;
        pageSize?: number | undefined;
        pageToken?: string | undefined;
    } & Record<Exclude<keyof I, keyof ListMlModelsRequest>, never>>(object: I): ListMlModelsRequest;
};
export declare const ListMlModelsResponse: {
    encode(message: ListMlModelsResponse, writer?: _m0.Writer): _m0.Writer;
    decode(input: _m0.Reader | Uint8Array, length?: number): ListMlModelsResponse;
    fromJSON(object: any): ListMlModelsResponse;
    toJSON(message: ListMlModelsResponse): unknown;
    fromPartial<I extends {
        mlModels?: {
            name?: string | undefined;
            clusterId?: string | undefined;
            type?: MlModelType | undefined;
            uri?: string | undefined;
        }[] | undefined;
        nextPageToken?: string | undefined;
    } & {
        mlModels?: ({
            name?: string | undefined;
            clusterId?: string | undefined;
            type?: MlModelType | undefined;
            uri?: string | undefined;
        }[] & ({
            name?: string | undefined;
            clusterId?: string | undefined;
            type?: MlModelType | undefined;
            uri?: string | undefined;
        } & {
            name?: string | undefined;
            clusterId?: string | undefined;
            type?: MlModelType | undefined;
            uri?: string | undefined;
        } & Record<Exclude<keyof I["mlModels"][number], keyof MlModel>, never>)[] & Record<Exclude<keyof I["mlModels"], keyof {
            name?: string | undefined;
            clusterId?: string | undefined;
            type?: MlModelType | undefined;
            uri?: string | undefined;
        }[]>, never>) | undefined;
        nextPageToken?: string | undefined;
    } & Record<Exclude<keyof I, keyof ListMlModelsResponse>, never>>(object: I): ListMlModelsResponse;
};
export declare const CreateMlModelRequest: {
    encode(message: CreateMlModelRequest, writer?: _m0.Writer): _m0.Writer;
    decode(input: _m0.Reader | Uint8Array, length?: number): CreateMlModelRequest;
    fromJSON(object: any): CreateMlModelRequest;
    toJSON(message: CreateMlModelRequest): unknown;
    fromPartial<I extends {
        clusterId?: string | undefined;
        mlModelName?: string | undefined;
        type?: MlModelType | undefined;
        uri?: string | undefined;
    } & {
        clusterId?: string | undefined;
        mlModelName?: string | undefined;
        type?: MlModelType | undefined;
        uri?: string | undefined;
    } & Record<Exclude<keyof I, keyof CreateMlModelRequest>, never>>(object: I): CreateMlModelRequest;
};
export declare const CreateMlModelMetadata: {
    encode(message: CreateMlModelMetadata, writer?: _m0.Writer): _m0.Writer;
    decode(input: _m0.Reader | Uint8Array, length?: number): CreateMlModelMetadata;
    fromJSON(object: any): CreateMlModelMetadata;
    toJSON(message: CreateMlModelMetadata): unknown;
    fromPartial<I extends {
        clusterId?: string | undefined;
        mlModelName?: string | undefined;
    } & {
        clusterId?: string | undefined;
        mlModelName?: string | undefined;
    } & Record<Exclude<keyof I, keyof CreateMlModelMetadata>, never>>(object: I): CreateMlModelMetadata;
};
export declare const UpdateMlModelRequest: {
    encode(message: UpdateMlModelRequest, writer?: _m0.Writer): _m0.Writer;
    decode(input: _m0.Reader | Uint8Array, length?: number): UpdateMlModelRequest;
    fromJSON(object: any): UpdateMlModelRequest;
    toJSON(message: UpdateMlModelRequest): unknown;
    fromPartial<I extends {
        clusterId?: string | undefined;
        mlModelName?: string | undefined;
        updateMask?: {
            paths?: string[] | undefined;
        } | undefined;
        uri?: string | undefined;
    } & {
        clusterId?: string | undefined;
        mlModelName?: string | undefined;
        updateMask?: ({
            paths?: string[] | undefined;
        } & {
            paths?: (string[] & string[] & Record<Exclude<keyof I["updateMask"]["paths"], keyof string[]>, never>) | undefined;
        } & Record<Exclude<keyof I["updateMask"], "paths">, never>) | undefined;
        uri?: string | undefined;
    } & Record<Exclude<keyof I, keyof UpdateMlModelRequest>, never>>(object: I): UpdateMlModelRequest;
};
export declare const UpdateMlModelMetadata: {
    encode(message: UpdateMlModelMetadata, writer?: _m0.Writer): _m0.Writer;
    decode(input: _m0.Reader | Uint8Array, length?: number): UpdateMlModelMetadata;
    fromJSON(object: any): UpdateMlModelMetadata;
    toJSON(message: UpdateMlModelMetadata): unknown;
    fromPartial<I extends {
        clusterId?: string | undefined;
        mlModelName?: string | undefined;
    } & {
        clusterId?: string | undefined;
        mlModelName?: string | undefined;
    } & Record<Exclude<keyof I, keyof UpdateMlModelMetadata>, never>>(object: I): UpdateMlModelMetadata;
};
export declare const DeleteMlModelRequest: {
    encode(message: DeleteMlModelRequest, writer?: _m0.Writer): _m0.Writer;
    decode(input: _m0.Reader | Uint8Array, length?: number): DeleteMlModelRequest;
    fromJSON(object: any): DeleteMlModelRequest;
    toJSON(message: DeleteMlModelRequest): unknown;
    fromPartial<I extends {
        clusterId?: string | undefined;
        mlModelName?: string | undefined;
    } & {
        clusterId?: string | undefined;
        mlModelName?: string | undefined;
    } & Record<Exclude<keyof I, keyof DeleteMlModelRequest>, never>>(object: I): DeleteMlModelRequest;
};
export declare const DeleteMlModelMetadata: {
    encode(message: DeleteMlModelMetadata, writer?: _m0.Writer): _m0.Writer;
    decode(input: _m0.Reader | Uint8Array, length?: number): DeleteMlModelMetadata;
    fromJSON(object: any): DeleteMlModelMetadata;
    toJSON(message: DeleteMlModelMetadata): unknown;
    fromPartial<I extends {
        clusterId?: string | undefined;
        mlModelName?: string | undefined;
    } & {
        clusterId?: string | undefined;
        mlModelName?: string | undefined;
    } & Record<Exclude<keyof I, keyof DeleteMlModelMetadata>, never>>(object: I): DeleteMlModelMetadata;
};
/** A set of methods for managing machine learning models. */
export declare const MlModelServiceService: {
    /**
     * Returns the specified machine learning model.
     *
     * To get the list of all available models, make a [List] request.
     */
    readonly get: {
        readonly path: "/yandex.cloud.mdb.clickhouse.v1.MlModelService/Get";
        readonly requestStream: false;
        readonly responseStream: false;
        readonly requestSerialize: (value: GetMlModelRequest) => Buffer;
        readonly requestDeserialize: (value: Buffer) => GetMlModelRequest;
        readonly responseSerialize: (value: MlModel) => Buffer;
        readonly responseDeserialize: (value: Buffer) => MlModel;
    };
    /** Retrieves the list of machine learning models in the specified cluster. */
    readonly list: {
        readonly path: "/yandex.cloud.mdb.clickhouse.v1.MlModelService/List";
        readonly requestStream: false;
        readonly responseStream: false;
        readonly requestSerialize: (value: ListMlModelsRequest) => Buffer;
        readonly requestDeserialize: (value: Buffer) => ListMlModelsRequest;
        readonly responseSerialize: (value: ListMlModelsResponse) => Buffer;
        readonly responseDeserialize: (value: Buffer) => ListMlModelsResponse;
    };
    /** Creates a machine learning model in the specified cluster. */
    readonly create: {
        readonly path: "/yandex.cloud.mdb.clickhouse.v1.MlModelService/Create";
        readonly requestStream: false;
        readonly responseStream: false;
        readonly requestSerialize: (value: CreateMlModelRequest) => Buffer;
        readonly requestDeserialize: (value: Buffer) => CreateMlModelRequest;
        readonly responseSerialize: (value: Operation) => Buffer;
        readonly responseDeserialize: (value: Buffer) => Operation;
    };
    /** Updates the specified machine learning model. */
    readonly update: {
        readonly path: "/yandex.cloud.mdb.clickhouse.v1.MlModelService/Update";
        readonly requestStream: false;
        readonly responseStream: false;
        readonly requestSerialize: (value: UpdateMlModelRequest) => Buffer;
        readonly requestDeserialize: (value: Buffer) => UpdateMlModelRequest;
        readonly responseSerialize: (value: Operation) => Buffer;
        readonly responseDeserialize: (value: Buffer) => Operation;
    };
    /** Deletes the specified machine learning model. */
    readonly delete: {
        readonly path: "/yandex.cloud.mdb.clickhouse.v1.MlModelService/Delete";
        readonly requestStream: false;
        readonly responseStream: false;
        readonly requestSerialize: (value: DeleteMlModelRequest) => Buffer;
        readonly requestDeserialize: (value: Buffer) => DeleteMlModelRequest;
        readonly responseSerialize: (value: Operation) => Buffer;
        readonly responseDeserialize: (value: Buffer) => Operation;
    };
};
export interface MlModelServiceServer extends UntypedServiceImplementation {
    /**
     * Returns the specified machine learning model.
     *
     * To get the list of all available models, make a [List] request.
     */
    get: handleUnaryCall<GetMlModelRequest, MlModel>;
    /** Retrieves the list of machine learning models in the specified cluster. */
    list: handleUnaryCall<ListMlModelsRequest, ListMlModelsResponse>;
    /** Creates a machine learning model in the specified cluster. */
    create: handleUnaryCall<CreateMlModelRequest, Operation>;
    /** Updates the specified machine learning model. */
    update: handleUnaryCall<UpdateMlModelRequest, Operation>;
    /** Deletes the specified machine learning model. */
    delete: handleUnaryCall<DeleteMlModelRequest, Operation>;
}
export interface MlModelServiceClient extends Client {
    /**
     * Returns the specified machine learning model.
     *
     * To get the list of all available models, make a [List] request.
     */
    get(request: GetMlModelRequest, callback: (error: ServiceError | null, response: MlModel) => void): ClientUnaryCall;
    get(request: GetMlModelRequest, metadata: Metadata, callback: (error: ServiceError | null, response: MlModel) => void): ClientUnaryCall;
    get(request: GetMlModelRequest, metadata: Metadata, options: Partial<CallOptions>, callback: (error: ServiceError | null, response: MlModel) => void): ClientUnaryCall;
    /** Retrieves the list of machine learning models in the specified cluster. */
    list(request: ListMlModelsRequest, callback: (error: ServiceError | null, response: ListMlModelsResponse) => void): ClientUnaryCall;
    list(request: ListMlModelsRequest, metadata: Metadata, callback: (error: ServiceError | null, response: ListMlModelsResponse) => void): ClientUnaryCall;
    list(request: ListMlModelsRequest, metadata: Metadata, options: Partial<CallOptions>, callback: (error: ServiceError | null, response: ListMlModelsResponse) => void): ClientUnaryCall;
    /** Creates a machine learning model in the specified cluster. */
    create(request: CreateMlModelRequest, callback: (error: ServiceError | null, response: Operation) => void): ClientUnaryCall;
    create(request: CreateMlModelRequest, metadata: Metadata, callback: (error: ServiceError | null, response: Operation) => void): ClientUnaryCall;
    create(request: CreateMlModelRequest, metadata: Metadata, options: Partial<CallOptions>, callback: (error: ServiceError | null, response: Operation) => void): ClientUnaryCall;
    /** Updates the specified machine learning model. */
    update(request: UpdateMlModelRequest, callback: (error: ServiceError | null, response: Operation) => void): ClientUnaryCall;
    update(request: UpdateMlModelRequest, metadata: Metadata, callback: (error: ServiceError | null, response: Operation) => void): ClientUnaryCall;
    update(request: UpdateMlModelRequest, metadata: Metadata, options: Partial<CallOptions>, callback: (error: ServiceError | null, response: Operation) => void): ClientUnaryCall;
    /** Deletes the specified machine learning model. */
    delete(request: DeleteMlModelRequest, callback: (error: ServiceError | null, response: Operation) => void): ClientUnaryCall;
    delete(request: DeleteMlModelRequest, metadata: Metadata, callback: (error: ServiceError | null, response: Operation) => void): ClientUnaryCall;
    delete(request: DeleteMlModelRequest, metadata: Metadata, options: Partial<CallOptions>, callback: (error: ServiceError | null, response: Operation) => void): ClientUnaryCall;
}
export declare const MlModelServiceClient: {
    new (address: string, credentials: ChannelCredentials, options?: Partial<ChannelOptions>): MlModelServiceClient;
    service: typeof MlModelServiceService;
};
type Builtin = Date | Function | Uint8Array | string | number | boolean | undefined;
export type DeepPartial<T> = T extends Builtin ? T : T extends Array<infer U> ? Array<DeepPartial<U>> : T extends ReadonlyArray<infer U> ? ReadonlyArray<DeepPartial<U>> : T extends {} ? {
    [K in keyof T]?: DeepPartial<T[K]>;
} : Partial<T>;
type KeysOfUnion<T> = T extends T ? keyof T : never;
export type Exact<P, I extends P> = P extends Builtin ? P : P & {
    [K in keyof P]: Exact<P[K], I[K]>;
} & Record<Exclude<keyof I, KeysOfUnion<P>>, never>;
export {};