def update_agent(
self,
request: gcdc_agent.UpdateAgentRequest = None,
*,
agent: gcdc_agent.Agent = None,
update_mask: field_mask.FieldMask = None,
retry: retries.Retry = gapic_v1.method.DEFAULT,
timeout: float = None,
metadata: Sequence[Tuple[str, str]] = (),
) -> gcdc_agent.Agent:
r"""Updates the specified agent.
Args:
request (:class:`~.gcdc_agent.UpdateAgentRequest`):
The request object. The request message for
[Agents.UpdateAgent][google.cloud.dialogflow.cx.v3.Agents.UpdateAgent].
agent (:class:`~.gcdc_agent.Agent`):
Required. The agent to update.
This corresponds to the ``agent`` field
on the ``request`` instance; if ``request`` is provided, this
should not be set.
update_mask (:class:`~.field_mask.FieldMask`):
The mask to control which fields get
updated. If the mask is not present, all
fields will be updated.
This corresponds to the ``update_mask`` field
on the ``request`` instance; if ``request`` is provided, this
should not be set.
retry (google.api_core.retry.Retry): Designation of what errors, if any,
should be retried.
timeout (float): The timeout for this request.
metadata (Sequence[Tuple[str, str]]): Strings which should be
sent along with the request as metadata.
Returns:
~.gcdc_agent.Agent:
Agents are best described as Natural Language
Understanding (NLU) modules that transform user requests
into actionable data. You can include agents in your
app, product, or service to determine user intent and
respond to the user in a natural way.
After you create an agent, you can add
[Intents][google.cloud.dialogflow.cx.v3.Intent], [Entity
Types][google.cloud.dialogflow.cx.v3.EntityType],
[Flows][google.cloud.dialogflow.cx.v3.Flow],
[Fulfillments][google.cloud.dialogflow.cx.v3.Fulfillment],
[Webhooks][google.cloud.dialogflow.cx.v3.Webhook], and
so on to manage the conversation flows..
"""
# Create or coerce a protobuf request object.
# Sanity check: If we got a request object, we should *not* have
# gotten any keyword arguments that map to the request.
has_flattened_params = any([agent, update_mask])
if request is not None and has_flattened_params:
raise ValueError("If the `request` argument is set, then none of "
"the individual field arguments should be set.")
# Minor optimization to avoid making a copy if the user passes
# in a gcdc_agent.UpdateAgentRequest.
# There's no risk of modifying the input as we've already verified
# there are no flattened fields.
if not isinstance(request, gcdc_agent.UpdateAgentRequest):
request = gcdc_agent.UpdateAgentRequest(request)
# If we have keyword arguments corresponding to fields on the
# request, apply these.
if agent is not None:
request.agent = agent
if update_mask is not None:
request.update_mask = update_mask
# Wrap the RPC method; this adds retry and timeout information,
# and friendly error handling.
rpc = self._transport._wrapped_methods[self._transport.update_agent]
# Certain fields should be provided within the metadata header;
# add these here.
metadata = tuple(metadata) + (gapic_v1.routing_header.to_grpc_metadata(
(("agent.name", request.agent.name), )), )
# Send the request.
response = rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# Done; return the response.
return response
async def update_agent(
self,
request: Union[gcdc_agent.UpdateAgentRequest, dict] = None,
*,
agent: gcdc_agent.Agent = None,
update_mask: field_mask_pb2.FieldMask = None,
retry: OptionalRetry = gapic_v1.method.DEFAULT,
timeout: float = None,
metadata: Sequence[Tuple[str, str]] = (),
) -> gcdc_agent.Agent:
r"""Updates the specified agent.
Note: You should always train flows prior to sending them
queries. See the `training
documentation <https://cloud.google.com/dialogflow/cx/docs/concept/training>`__.
.. code-block::
from google.cloud import dialogflowcx_v3
def sample_update_agent():
# Create a client
client = dialogflowcx_v3.AgentsClient()
# Initialize request argument(s)
agent = dialogflowcx_v3.Agent()
agent.display_name = "display_name_value"
agent.default_language_code = "default_language_code_value"
agent.time_zone = "time_zone_value"
request = dialogflowcx_v3.UpdateAgentRequest(
agent=agent,
)
# Make the request
response = client.update_agent(request=request)
# Handle the response
print(response)
Args:
request (Union[google.cloud.dialogflowcx_v3.types.UpdateAgentRequest, dict]):
The request object. The request message for
[Agents.UpdateAgent][google.cloud.dialogflow.cx.v3.Agents.UpdateAgent].
agent (:class:`google.cloud.dialogflowcx_v3.types.Agent`):
Required. The agent to update.
This corresponds to the ``agent`` field
on the ``request`` instance; if ``request`` is provided, this
should not be set.
update_mask (:class:`google.protobuf.field_mask_pb2.FieldMask`):
The mask to control which fields get
updated. If the mask is not present, all
fields will be updated.
This corresponds to the ``update_mask`` field
on the ``request`` instance; if ``request`` is provided, this
should not be set.
retry (google.api_core.retry.Retry): Designation of what errors, if any,
should be retried.
timeout (float): The timeout for this request.
metadata (Sequence[Tuple[str, str]]): Strings which should be
sent along with the request as metadata.
Returns:
google.cloud.dialogflowcx_v3.types.Agent:
Agents are best described as Natural Language Understanding (NLU) modules
that transform user requests into actionable data.
You can include agents in your app, product, or
service to determine user intent and respond to the
user in a natural way.
After you create an agent, you can add
[Intents][google.cloud.dialogflow.cx.v3.Intent],
[Entity
Types][google.cloud.dialogflow.cx.v3.EntityType],
[Flows][google.cloud.dialogflow.cx.v3.Flow],
[Fulfillments][google.cloud.dialogflow.cx.v3.Fulfillment],
[Webhooks][google.cloud.dialogflow.cx.v3.Webhook],
and so on to manage the conversation flows..
"""
# Create or coerce a protobuf request object.
# Quick check: If we got a request object, we should *not* have
# gotten any keyword arguments that map to the request.
has_flattened_params = any([agent, update_mask])
if request is not None and has_flattened_params:
raise ValueError(
"If the `request` argument is set, then none of "
"the individual field arguments should be set."
)
request = gcdc_agent.UpdateAgentRequest(request)
# If we have keyword arguments corresponding to fields on the
# request, apply these.
if agent is not None:
request.agent = agent
if update_mask is not None:
request.update_mask = update_mask
# Wrap the RPC method; this adds retry and timeout information,
# and friendly error handling.
rpc = gapic_v1.method_async.wrap_method(
self._client._transport.update_agent,
default_timeout=None,
client_info=DEFAULT_CLIENT_INFO,
)
# Certain fields should be provided within the metadata header;
# add these here.
metadata = tuple(metadata) + (
gapic_v1.routing_header.to_grpc_metadata(
(("agent.name", request.agent.name),)
),
)
# Send the request.
response = await rpc(request, retry=retry, timeout=timeout, metadata=metadata,)
# Done; return the response.
return response