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v3.12.0: gRPC auto-fallback for Antigravity (PR #13)

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Roman | RyzenAdvanced
2026-05-27 10:42:35 +04:00
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parent d17afaa8d7
commit 622beceb59
14 changed files with 1878 additions and 9 deletions
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275
src/antigravity_grpc/cloudcode_pb2_grpc.py Normal file
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# Generated by the gRPC Python protocol compiler plugin. DO NOT EDIT!
"""Client and server classes corresponding to protobuf-defined services."""
import grpc
import warnings
from antigravity_grpc import cloudcode_pb2 as cloudcode__pb2
GRPC_GENERATED_VERSION = '1.80.0'
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 cloudcode_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 PredictionServiceStub(object):
"""─── Service ──────────────────────────────────────────────────────────
"""
def __init__(self, channel):
"""Constructor.
Args:
channel: A grpc.Channel.
"""
self.GenerateContent = channel.unary_unary(
'/google.internal.cloud.code.v1internal.PredictionService/GenerateContent',
request_serializer=cloudcode__pb2.GenerateContentRequest.SerializeToString,
response_deserializer=cloudcode__pb2.GenerateContentResponse.FromString,
_registered_method=True)
self.StreamGenerateContent = channel.unary_stream(
'/google.internal.cloud.code.v1internal.PredictionService/StreamGenerateContent',
request_serializer=cloudcode__pb2.GenerateContentRequest.SerializeToString,
response_deserializer=cloudcode__pb2.StreamGenerateContentChunk.FromString,
_registered_method=True)
self.FetchAvailableModels = channel.unary_unary(
'/google.internal.cloud.code.v1internal.PredictionService/FetchAvailableModels',
request_serializer=cloudcode__pb2.FetchAvailableModelsRequest.SerializeToString,
response_deserializer=cloudcode__pb2.FetchAvailableModelsResponse.FromString,
_registered_method=True)
self.CountTokens = channel.unary_unary(
'/google.internal.cloud.code.v1internal.PredictionService/CountTokens',
request_serializer=cloudcode__pb2.CountTokensRequest.SerializeToString,
response_deserializer=cloudcode__pb2.CountTokensResponse.FromString,
_registered_method=True)
self.RetrieveUserQuota = channel.unary_unary(
'/google.internal.cloud.code.v1internal.PredictionService/RetrieveUserQuota',
request_serializer=cloudcode__pb2.RetrieveUserQuotaRequest.SerializeToString,
response_deserializer=cloudcode__pb2.RetrieveUserQuotaResponse.FromString,
_registered_method=True)
class PredictionServiceServicer(object):
"""─── Service ──────────────────────────────────────────────────────────
"""
def GenerateContent(self, request, context):
"""Missing associated documentation comment in .proto file."""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
def StreamGenerateContent(self, request, context):
"""Missing associated documentation comment in .proto file."""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
def FetchAvailableModels(self, request, context):
"""Missing associated documentation comment in .proto file."""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
def CountTokens(self, request, context):
"""Missing associated documentation comment in .proto file."""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
def RetrieveUserQuota(self, request, context):
"""Missing associated documentation comment in .proto file."""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
def add_PredictionServiceServicer_to_server(servicer, server):
rpc_method_handlers = {
'GenerateContent': grpc.unary_unary_rpc_method_handler(
servicer.GenerateContent,
request_deserializer=cloudcode__pb2.GenerateContentRequest.FromString,
response_serializer=cloudcode__pb2.GenerateContentResponse.SerializeToString,
),
'StreamGenerateContent': grpc.unary_stream_rpc_method_handler(
servicer.StreamGenerateContent,
request_deserializer=cloudcode__pb2.GenerateContentRequest.FromString,
response_serializer=cloudcode__pb2.StreamGenerateContentChunk.SerializeToString,
),
'FetchAvailableModels': grpc.unary_unary_rpc_method_handler(
servicer.FetchAvailableModels,
request_deserializer=cloudcode__pb2.FetchAvailableModelsRequest.FromString,
response_serializer=cloudcode__pb2.FetchAvailableModelsResponse.SerializeToString,
),
'CountTokens': grpc.unary_unary_rpc_method_handler(
servicer.CountTokens,
request_deserializer=cloudcode__pb2.CountTokensRequest.FromString,
response_serializer=cloudcode__pb2.CountTokensResponse.SerializeToString,
),
'RetrieveUserQuota': grpc.unary_unary_rpc_method_handler(
servicer.RetrieveUserQuota,
request_deserializer=cloudcode__pb2.RetrieveUserQuotaRequest.FromString,
response_serializer=cloudcode__pb2.RetrieveUserQuotaResponse.SerializeToString,
),
}
generic_handler = grpc.method_handlers_generic_handler(
'google.internal.cloud.code.v1internal.PredictionService', rpc_method_handlers)
server.add_generic_rpc_handlers((generic_handler,))
server.add_registered_method_handlers('google.internal.cloud.code.v1internal.PredictionService', rpc_method_handlers)
# This class is part of an EXPERIMENTAL API.
class PredictionService(object):
"""─── Service ──────────────────────────────────────────────────────────
"""
@staticmethod
def GenerateContent(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.internal.cloud.code.v1internal.PredictionService/GenerateContent',
cloudcode__pb2.GenerateContentRequest.SerializeToString,
cloudcode__pb2.GenerateContentResponse.FromString,
options,
channel_credentials,
insecure,
call_credentials,
compression,
wait_for_ready,
timeout,
metadata,
_registered_method=True)
@staticmethod
def StreamGenerateContent(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,
'/google.internal.cloud.code.v1internal.PredictionService/StreamGenerateContent',
cloudcode__pb2.GenerateContentRequest.SerializeToString,
cloudcode__pb2.StreamGenerateContentChunk.FromString,
options,
channel_credentials,
insecure,
call_credentials,
compression,
wait_for_ready,
timeout,
metadata,
_registered_method=True)
@staticmethod
def FetchAvailableModels(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.internal.cloud.code.v1internal.PredictionService/FetchAvailableModels',
cloudcode__pb2.FetchAvailableModelsRequest.SerializeToString,
cloudcode__pb2.FetchAvailableModelsResponse.FromString,
options,
channel_credentials,
insecure,
call_credentials,
compression,
wait_for_ready,
timeout,
metadata,
_registered_method=True)
@staticmethod
def CountTokens(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.internal.cloud.code.v1internal.PredictionService/CountTokens',
cloudcode__pb2.CountTokensRequest.SerializeToString,
cloudcode__pb2.CountTokensResponse.FromString,
options,
channel_credentials,
insecure,
call_credentials,
compression,
wait_for_ready,
timeout,
metadata,
_registered_method=True)
@staticmethod
def RetrieveUserQuota(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.internal.cloud.code.v1internal.PredictionService/RetrieveUserQuota',
cloudcode__pb2.RetrieveUserQuotaRequest.SerializeToString,
cloudcode__pb2.RetrieveUserQuotaResponse.FromString,
options,
channel_credentials,
insecure,
call_credentials,
compression,
wait_for_ready,
timeout,
metadata,
_registered_method=True)