def set_agent(
self,
request: gcd_agent.SetAgentRequest = None,
*,
agent: gcd_agent.Agent = None,
retry: retries.Retry = gapic_v1.method.DEFAULT,
timeout: float = None,
metadata: Sequence[Tuple[str, str]] = (),
) -> gcd_agent.Agent:
r"""Creates/updates the specified agent.
Args:
request (:class:`~.gcd_agent.SetAgentRequest`):
The request object. The request message for
[Agents.SetAgent][google.cloud.dialogflow.v2.Agents.SetAgent].
agent (:class:`~.gcd_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.
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:
~.gcd_agent.Agent:
A Dialogflow agent is a virtual agent that handles
conversations with your end-users. It is a natural
language understanding module that understands the
nuances of human language. Dialogflow translates
end-user text or audio during a conversation to
structured data that your apps and services can
understand. You design and build a Dialogflow agent to
handle the types of conversations required for your
system.
For more information about agents, see the `Agent
guide <https://cloud.google.com/dialogflow/docs/agents-overview>`__.
"""
# 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])
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 gcd_agent.SetAgentRequest.
# There's no risk of modifying the input as we've already verified
# there are no flattened fields.
if not isinstance(request, gcd_agent.SetAgentRequest):
request = gcd_agent.SetAgentRequest(request)
# If we have keyword arguments corresponding to fields on the
# request, apply these.
if agent is not None:
request.agent = agent
# Wrap the RPC method; this adds retry and timeout information,
# and friendly error handling.
rpc = self._transport._wrapped_methods[self._transport.set_agent]
# Certain fields should be provided within the metadata header;
# add these here.
metadata = tuple(metadata) + (
gapic_v1.routing_header.to_grpc_metadata(
(("agent.parent", request.agent.parent),)
),
)
# Send the request.
response = rpc(request, retry=retry, timeout=timeout, metadata=metadata,)
# Done; return the response.
return response
async def set_agent(
self,
request: Union[gcd_agent.SetAgentRequest, dict] = None,
*,
agent: gcd_agent.Agent = None,
retry: OptionalRetry = gapic_v1.method.DEFAULT,
timeout: float = None,
metadata: Sequence[Tuple[str, str]] = (),
) -> gcd_agent.Agent:
r"""Creates/updates the specified agent.
Note: You should always train an agent prior to sending it
queries. See the `training
documentation <https://cloud.google.com/dialogflow/es/docs/training>`__.
.. code-block:: python
from google.cloud import dialogflow_v2
async def sample_set_agent():
# Create a client
client = dialogflow_v2.AgentsAsyncClient()
# Initialize request argument(s)
agent = dialogflow_v2.Agent()
agent.parent = "parent_value"
agent.display_name = "display_name_value"
agent.default_language_code = "default_language_code_value"
agent.time_zone = "time_zone_value"
request = dialogflow_v2.SetAgentRequest(
agent=agent,
)
# Make the request
response = await client.set_agent(request=request)
# Handle the response
print(response)
Args:
request (Union[google.cloud.dialogflow_v2.types.SetAgentRequest, dict]):
The request object. The request message for
[Agents.SetAgent][google.cloud.dialogflow.v2.Agents.SetAgent].
agent (:class:`google.cloud.dialogflow_v2.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.
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.dialogflow_v2.types.Agent:
A Dialogflow agent is a virtual agent that handles conversations with your
end-users. It is a natural language understanding
module that understands the nuances of human
language. Dialogflow translates end-user text or
audio during a conversation to structured data that
your apps and services can understand. You design and
build a Dialogflow agent to handle the types of
conversations required for your system.
For more information about agents, see the [Agent
guide](\ https://cloud.google.com/dialogflow/docs/agents-overview).
"""
# 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])
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 = gcd_agent.SetAgentRequest(request)
# If we have keyword arguments corresponding to fields on the
# request, apply these.
if agent is not None:
request.agent = agent
# Wrap the RPC method; this adds retry and timeout information,
# and friendly error handling.
rpc = gapic_v1.method_async.wrap_method(
self._client._transport.set_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.parent", request.agent.parent),)
),
)
# Send the request.
response = await rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# Done; return the response.
return response
