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