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

import warnings

import grpc
from google.protobuf import empty_pb2 as google_dot_protobuf_dot_empty__pb2

from lumen_app.proto import ml_service_pb2 as proto_dot_ml__service__pb2

GRPC_GENERATED_VERSION = "1.76.0"
GRPC_VERSION = grpc.__version__
_version_not_supported = False

try:
    from grpc._utilities import first_version_is_lower

    _version_not_supported = first_version_is_lower(
        GRPC_VERSION, GRPC_GENERATED_VERSION
    )
except ImportError:
    _version_not_supported = True

if _version_not_supported:
    raise RuntimeError(
        f"The grpc package installed is at version {GRPC_VERSION},"
        + " but the generated code in proto/ml_service_pb2_grpc.py depends on"
        + f" grpcio>={GRPC_GENERATED_VERSION}."
        + f" Please upgrade your grpc module to grpcio>={GRPC_GENERATED_VERSION}"
        + f" or downgrade your generated code using grpcio-tools<={GRPC_VERSION}."
    )


class InferenceStub(object):
    """---- Service contract ----"""

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

        Args:
            channel: A grpc.Channel.
        """
        self.Infer = channel.stream_stream(
            "/home_native.v1.Inference/Infer",
            request_serializer=proto_dot_ml__service__pb2.InferRequest.SerializeToString,
            response_deserializer=proto_dot_ml__service__pb2.InferResponse.FromString,
            _registered_method=True,
        )
        self.GetCapabilities = channel.unary_unary(
            "/home_native.v1.Inference/GetCapabilities",
            request_serializer=google_dot_protobuf_dot_empty__pb2.Empty.SerializeToString,
            response_deserializer=proto_dot_ml__service__pb2.Capability.FromString,
            _registered_method=True,
        )
        self.StreamCapabilities = channel.unary_stream(
            "/home_native.v1.Inference/StreamCapabilities",
            request_serializer=google_dot_protobuf_dot_empty__pb2.Empty.SerializeToString,
            response_deserializer=proto_dot_ml__service__pb2.Capability.FromString,
            _registered_method=True,
        )
        self.Health = channel.unary_unary(
            "/home_native.v1.Inference/Health",
            request_serializer=google_dot_protobuf_dot_empty__pb2.Empty.SerializeToString,
            response_deserializer=google_dot_protobuf_dot_empty__pb2.Empty.FromString,
            _registered_method=True,
        )


class InferenceServicer(object):
    """---- Service contract ----"""

    def Infer(self, request_iterator, context):
        """Bidirectional stream: client sends chunks; server returns incremental/final results; ordered but non-blocking"""
        context.set_code(grpc.StatusCode.UNIMPLEMENTED)
        context.set_details("Method not implemented!")
        raise NotImplementedError("Method not implemented!")

    def GetCapabilities(self, request, context):
        """Capability declaration (backward compatibility: single capability; use StreamCapabilities for multiple)"""
        context.set_code(grpc.StatusCode.UNIMPLEMENTED)
        context.set_details("Method not implemented!")
        raise NotImplementedError("Method not implemented!")

    def StreamCapabilities(self, request, context):
        """Recommended: server stream returns all capabilities (call at startup or after hot-reload)"""
        context.set_code(grpc.StatusCode.UNIMPLEMENTED)
        context.set_details("Method not implemented!")
        raise NotImplementedError("Method not implemented!")

    def Health(self, request, context):
        """Health probe"""
        context.set_code(grpc.StatusCode.UNIMPLEMENTED)
        context.set_details("Method not implemented!")
        raise NotImplementedError("Method not implemented!")


def add_InferenceServicer_to_server(servicer, server):
    rpc_method_handlers = {
        "Infer": grpc.stream_stream_rpc_method_handler(
            servicer.Infer,
            request_deserializer=proto_dot_ml__service__pb2.InferRequest.FromString,
            response_serializer=proto_dot_ml__service__pb2.InferResponse.SerializeToString,
        ),
        "GetCapabilities": grpc.unary_unary_rpc_method_handler(
            servicer.GetCapabilities,
            request_deserializer=google_dot_protobuf_dot_empty__pb2.Empty.FromString,
            response_serializer=proto_dot_ml__service__pb2.Capability.SerializeToString,
        ),
        "StreamCapabilities": grpc.unary_stream_rpc_method_handler(
            servicer.StreamCapabilities,
            request_deserializer=google_dot_protobuf_dot_empty__pb2.Empty.FromString,
            response_serializer=proto_dot_ml__service__pb2.Capability.SerializeToString,
        ),
        "Health": grpc.unary_unary_rpc_method_handler(
            servicer.Health,
            request_deserializer=google_dot_protobuf_dot_empty__pb2.Empty.FromString,
            response_serializer=google_dot_protobuf_dot_empty__pb2.Empty.SerializeToString,
        ),
    }
    generic_handler = grpc.method_handlers_generic_handler(
        "home_native.v1.Inference", rpc_method_handlers
    )
    server.add_generic_rpc_handlers((generic_handler,))
    server.add_registered_method_handlers(
        "home_native.v1.Inference", rpc_method_handlers
    )


# This class is part of an EXPERIMENTAL API.
class Inference(object):
    """---- Service contract ----"""

    @staticmethod
    def Infer(
        request_iterator,
        target,
        options=(),
        channel_credentials=None,
        call_credentials=None,
        insecure=False,
        compression=None,
        wait_for_ready=None,
        timeout=None,
        metadata=None,
    ):
        return grpc.experimental.stream_stream(
            request_iterator,
            target,
            "/home_native.v1.Inference/Infer",
            proto_dot_ml__service__pb2.InferRequest.SerializeToString,
            proto_dot_ml__service__pb2.InferResponse.FromString,
            options,
            channel_credentials,
            insecure,
            call_credentials,
            compression,
            wait_for_ready,
            timeout,
            metadata,
            _registered_method=True,
        )

    @staticmethod
    def GetCapabilities(
        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,
            "/home_native.v1.Inference/GetCapabilities",
            google_dot_protobuf_dot_empty__pb2.Empty.SerializeToString,
            proto_dot_ml__service__pb2.Capability.FromString,
            options,
            channel_credentials,
            insecure,
            call_credentials,
            compression,
            wait_for_ready,
            timeout,
            metadata,
            _registered_method=True,
        )

    @staticmethod
    def StreamCapabilities(
        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_stream(
            request,
            target,
            "/home_native.v1.Inference/StreamCapabilities",
            google_dot_protobuf_dot_empty__pb2.Empty.SerializeToString,
            proto_dot_ml__service__pb2.Capability.FromString,
            options,
            channel_credentials,
            insecure,
            call_credentials,
            compression,
            wait_for_ready,
            timeout,
            metadata,
            _registered_method=True,
        )

    @staticmethod
    def Health(
        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,
            "/home_native.v1.Inference/Health",
            google_dot_protobuf_dot_empty__pb2.Empty.SerializeToString,
            google_dot_protobuf_dot_empty__pb2.Empty.FromString,
            options,
            channel_credentials,
            insecure,
            call_credentials,
            compression,
            wait_for_ready,
            timeout,
            metadata,
            _registered_method=True,
        )
