retail/recommendation-system/bqml-scann/ann_grpc/match_pb2_grpc.py

# Generated by the gRPC Python protocol compiler plugin. DO NOT EDIT!
"""Client and server classes corresponding to protobuf-defined services."""
import grpc

import match_pb2 as match__pb2


class MatchServiceStub(object):
    """MatchService is a Google managed service for efficient vector similarity
    search at scale.
    """

    def __init__(self, channel):
        """Constructor.

        Args:
            channel: A grpc.Channel.
        """
        self.Match = channel.unary_unary(
                '/google.cloud.aiplatform.container.v1alpha1.MatchService/Match',
                request_serializer=match__pb2.MatchRequest.SerializeToString,
                response_deserializer=match__pb2.MatchResponse.FromString,
                )
        self.BatchMatch = channel.unary_unary(
                '/google.cloud.aiplatform.container.v1alpha1.MatchService/BatchMatch',
                request_serializer=match__pb2.BatchMatchRequest.SerializeToString,
                response_deserializer=match__pb2.BatchMatchResponse.FromString,
                )


class MatchServiceServicer(object):
    """MatchService is a Google managed service for efficient vector similarity
    search at scale.
    """

    def Match(self, request, context):
        """Returns the nearest neighbors for the query. If it is a sharded
        deployment, calls the other shards and aggregates the responses.
        """
        context.set_code(grpc.StatusCode.UNIMPLEMENTED)
        context.set_details('Method not implemented!')
        raise NotImplementedError('Method not implemented!')

    def BatchMatch(self, request, context):
        """Returns the nearest neighbors for batch queries. If it is a sharded
        deployment, calls the other shards and aggregates the responses.
        """
        context.set_code(grpc.StatusCode.UNIMPLEMENTED)
        context.set_details('Method not implemented!')
        raise NotImplementedError('Method not implemented!')


def add_MatchServiceServicer_to_server(servicer, server):
    rpc_method_handlers = {
            'Match': grpc.unary_unary_rpc_method_handler(
                    servicer.Match,
                    request_deserializer=match__pb2.MatchRequest.FromString,
                    response_serializer=match__pb2.MatchResponse.SerializeToString,
            ),
            'BatchMatch': grpc.unary_unary_rpc_method_handler(
                    servicer.BatchMatch,
                    request_deserializer=match__pb2.BatchMatchRequest.FromString,
                    response_serializer=match__pb2.BatchMatchResponse.SerializeToString,
            ),
    }
    generic_handler = grpc.method_handlers_generic_handler(
            'google.cloud.aiplatform.container.v1alpha1.MatchService', rpc_method_handlers)
    server.add_generic_rpc_handlers((generic_handler,))


 # This class is part of an EXPERIMENTAL API.
class MatchService(object):
    """MatchService is a Google managed service for efficient vector similarity
    search at scale.
    """

    @staticmethod
    def Match(request,
            target,
            options=(),
            channel_credentials=None,
            call_credentials=None,
            insecure=False,
            compression=None,
            wait_for_ready=None,
            timeout=None,
            metadata=None):
        return grpc.experimental.unary_unary(request, target, '/google.cloud.aiplatform.container.v1alpha1.MatchService/Match',
            match__pb2.MatchRequest.SerializeToString,
            match__pb2.MatchResponse.FromString,
            options, channel_credentials,
            insecure, call_credentials, compression, wait_for_ready, timeout, metadata)

    @staticmethod
    def BatchMatch(request,
            target,
            options=(),
            channel_credentials=None,
            call_credentials=None,
            insecure=False,
            compression=None,
            wait_for_ready=None,
            timeout=None,
            metadata=None):
        return grpc.experimental.unary_unary(request, target, '/google.cloud.aiplatform.container.v1alpha1.MatchService/BatchMatch',
            match__pb2.BatchMatchRequest.SerializeToString,
            match__pb2.BatchMatchResponse.FromString,
            options, channel_credentials,
            insecure, call_credentials, compression, wait_for_ready, timeout, metadata)