def test_train_agent(self):
# Setup Expected Response
expected_response = {}
expected_response = empty_pb2.Empty(**expected_response)
operation = operations_pb2.Operation(
name='operations/test_train_agent', done=True)
operation.response.Pack(expected_response)
# Mock the API response
channel = ChannelStub(responses=[operation])
patch = mock.patch('google.api_core.grpc_helpers.create_channel')
with patch as create_channel:
create_channel.return_value = channel
client = dialogflow_v2.AgentsClient()
# Setup Request
parent = client.project_path('[PROJECT]')
response = client.train_agent(parent)
result = response.result()
assert expected_response == result
assert len(channel.requests) == 1
expected_request = agent_pb2.TrainAgentRequest(parent=parent)
actual_request = channel.requests[0][1]
assert expected_request == actual_request
def test_train_agent(self):
# Setup Expected Response
expected_response = {}
expected_response = empty_pb2.Empty(**expected_response)
operation = operations_pb2.Operation(
name='operations/test_train_agent', done=True)
operation.response.Pack(expected_response)
# Mock the API response
channel = ChannelStub(responses=[operation])
client = dialogflow_v2.AgentsClient(channel=channel)
# Setup Request
parent = client.project_path('[PROJECT]')
response = client.train_agent(parent)
result = response.result()
assert expected_response == result
assert len(channel.requests) == 1
expected_request = agent_pb2.TrainAgentRequest(parent=parent)
actual_request = channel.requests[0][1]
assert expected_request == actual_request
def train_agent(
self,
parent,
retry=google.api_core.gapic_v1.method.DEFAULT,
timeout=google.api_core.gapic_v1.method.DEFAULT,
metadata=None,
):
"""
Trains the specified agent.
Operation <response: ``google.protobuf.Empty``>
Example:
>>> import dialogflow_v2
>>>
>>> client = dialogflow_v2.AgentsClient()
>>>
>>> parent = client.project_path('[PROJECT]')
>>>
>>> response = client.train_agent(parent)
>>>
>>> def callback(operation_future):
... # Handle result.
... result = operation_future.result()
>>>
>>> response.add_done_callback(callback)
>>>
>>> # Handle metadata.
>>> metadata = response.metadata()
Args:
parent (str): Required. The project that the agent to train is associated with.
Format: ``projects/<Project ID>``.
retry (Optional[google.api_core.retry.Retry]): A retry object used
to retry requests. If ``None`` is specified, requests will
be retried using a default configuration.
timeout (Optional[float]): The amount of time, in seconds, to wait
for the request to complete. Note that if ``retry`` is
specified, the timeout applies to each individual attempt.
metadata (Optional[Sequence[Tuple[str, str]]]): Additional metadata
that is provided to the method.
Returns:
A :class:`~google.cloud.dialogflow_v2.types._OperationFuture` instance.
Raises:
google.api_core.exceptions.GoogleAPICallError: If the request
failed for any reason.
google.api_core.exceptions.RetryError: If the request failed due
to a retryable error and retry attempts failed.
ValueError: If the parameters are invalid.
"""
# Wrap the transport method to add retry and timeout logic.
if "train_agent" not in self._inner_api_calls:
self._inner_api_calls[
"train_agent"] = google.api_core.gapic_v1.method.wrap_method(
self.transport.train_agent,
default_retry=self._method_configs["TrainAgent"].retry,
default_timeout=self._method_configs["TrainAgent"].timeout,
client_info=self._client_info,
)
request = agent_pb2.TrainAgentRequest(parent=parent)
if metadata is None:
metadata = []
metadata = list(metadata)
try:
routing_header = [("parent", parent)]
except AttributeError:
pass
else:
routing_metadata = google.api_core.gapic_v1.routing_header.to_grpc_metadata(
routing_header)
metadata.append(routing_metadata)
operation = self._inner_api_calls["train_agent"](request,
retry=retry,
timeout=timeout,
metadata=metadata)
return google.api_core.operation.from_gapic(
operation,
self.transport._operations_client,
empty_pb2.Empty,
metadata_type=struct_pb2.Struct,
)
def train_agent(self,
parent,
retry=google.api_core.gapic_v1.method.DEFAULT,
timeout=google.api_core.gapic_v1.method.DEFAULT,
metadata=None):
"""
Trains the specified agent.
Operation <response: ``google.protobuf.Empty``,
metadata: [google.protobuf.Struct][google.protobuf.Struct]>
Example:
>>> import dialogflow_v2
>>>
>>> client = dialogflow_v2.AgentsClient()
>>>
>>> parent = client.project_path('[PROJECT]')
>>>
>>> response = client.train_agent(parent)
>>>
>>> def callback(operation_future):
... # Handle result.
... result = operation_future.result()
>>>
>>> response.add_done_callback(callback)
>>>
>>> # Handle metadata.
>>> metadata = response.metadata()
Args:
parent (str): Required. The project that the agent to train is associated with.
Format: ``projects/<Project ID>``.
retry (Optional[google.api_core.retry.Retry]): A retry object used
to retry requests. If ``None`` is specified, requests will not
be retried.
timeout (Optional[float]): The amount of time, in seconds, to wait
for the request to complete. Note that if ``retry`` is
specified, the timeout applies to each individual attempt.
metadata (Optional[Sequence[Tuple[str, str]]]): Additional metadata
that is provided to the method.
Returns:
A :class:`~google.cloud.dialogflow_v2.types._OperationFuture` instance.
Raises:
google.api_core.exceptions.GoogleAPICallError: If the request
failed for any reason.
google.api_core.exceptions.RetryError: If the request failed due
to a retryable error and retry attempts failed.
ValueError: If the parameters are invalid.
"""
if metadata is None:
metadata = []
metadata = list(metadata)
request = agent_pb2.TrainAgentRequest(parent=parent, )
operation = self._train_agent(
request, retry=retry, timeout=timeout, metadata=metadata)
return google.api_core.operation.from_gapic(
operation,
self.operations_client,
empty_pb2.Empty,
metadata_type=struct_pb2.Struct,
)
