Exemple #1
0
    async def create_conversation(
        self,
        request: Union[gcd_conversation.CreateConversationRequest, dict] = None,
        *,
        parent: str = None,
        conversation: gcd_conversation.Conversation = None,
        retry: OptionalRetry = gapic_v1.method.DEFAULT,
        timeout: float = None,
        metadata: Sequence[Tuple[str, str]] = (),
    ) -> gcd_conversation.Conversation:
        r"""Creates a new conversation. Conversations are auto-completed
        after 24 hours.

        Conversation Lifecycle: There are two stages during a
        conversation: Automated Agent Stage and Assist Stage.

        For Automated Agent Stage, there will be a dialogflow agent
        responding to user queries.

        For Assist Stage, there's no dialogflow agent responding to user
        queries. But we will provide suggestions which are generated
        from conversation.

        If
        [Conversation.conversation_profile][google.cloud.dialogflow.v2.Conversation.conversation_profile]
        is configured for a dialogflow agent, conversation will start
        from ``Automated Agent Stage``, otherwise, it will start from
        ``Assist Stage``. And during ``Automated Agent Stage``, once an
        [Intent][google.cloud.dialogflow.v2.Intent] with
        [Intent.live_agent_handoff][google.cloud.dialogflow.v2.Intent.live_agent_handoff]
        is triggered, conversation will transfer to Assist Stage.

        .. code-block:: python

            from google.cloud import dialogflow_v2

            async def sample_create_conversation():
                # Create a client
                client = dialogflow_v2.ConversationsAsyncClient()

                # Initialize request argument(s)
                conversation = dialogflow_v2.Conversation()
                conversation.conversation_profile = "conversation_profile_value"

                request = dialogflow_v2.CreateConversationRequest(
                    parent="parent_value",
                    conversation=conversation,
                )

                # Make the request
                response = await client.create_conversation(request=request)

                # Handle the response
                print(response)

        Args:
            request (Union[google.cloud.dialogflow_v2.types.CreateConversationRequest, dict]):
                The request object. The request message for
                [Conversations.CreateConversation][google.cloud.dialogflow.v2.Conversations.CreateConversation].
            parent (:class:`str`):
                Required. Resource identifier of the project creating
                the conversation. Format:
                ``projects/<Project ID>/locations/<Location ID>``.

                This corresponds to the ``parent`` field
                on the ``request`` instance; if ``request`` is provided, this
                should not be set.
            conversation (:class:`google.cloud.dialogflow_v2.types.Conversation`):
                Required. The conversation to create.
                This corresponds to the ``conversation`` 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.Conversation:
                Represents a conversation.
                A conversation is an interaction between
                an agent, including live agents and
                Dialogflow agents, and a support
                customer. Conversations can include
                phone calls and text-based chat
                sessions.

        """
        # 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([parent, conversation])
        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_conversation.CreateConversationRequest(request)

        # If we have keyword arguments corresponding to fields on the
        # request, apply these.
        if parent is not None:
            request.parent = parent
        if conversation is not None:
            request.conversation = conversation

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = gapic_v1.method_async.wrap_method(
            self._client._transport.create_conversation,
            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((("parent", request.parent),)),
        )

        # Send the request.
        response = await rpc(
            request,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

        # Done; return the response.
        return response
    def create_conversation(
        self,
        request: gcd_conversation.CreateConversationRequest = None,
        *,
        parent: str = None,
        conversation: gcd_conversation.Conversation = None,
        retry: retries.Retry = gapic_v1.method.DEFAULT,
        timeout: float = None,
        metadata: Sequence[Tuple[str, str]] = (),
    ) -> gcd_conversation.Conversation:
        r"""Creates a new conversation. Conversations are auto-completed
        after 24 hours.

        Conversation Lifecycle: There are two stages during a
        conversation: Automated Agent Stage and Assist Stage.

        For Automated Agent Stage, there will be a dialogflow agent
        responding to user queries.

        For Assist Stage, there's no dialogflow agent responding to user
        queries. But we will provide suggestions which are generated
        from conversation.

        If
        [Conversation.conversation_profile][google.cloud.dialogflow.v2.Conversation.conversation_profile]
        is configured for a dialogflow agent, conversation will start
        from ``Automated Agent Stage``, otherwise, it will start from
        ``Assist Stage``. And during ``Automated Agent Stage``, once an
        [Intent][google.cloud.dialogflow.v2.Intent] with
        [Intent.live_agent_handoff][google.cloud.dialogflow.v2.Intent.live_agent_handoff]
        is triggered, conversation will transfer to Assist Stage.

        Args:
            request (google.cloud.dialogflow_v2.types.CreateConversationRequest):
                The request object. The request message for
                [Conversations.CreateConversation][google.cloud.dialogflow.v2.Conversations.CreateConversation].
            parent (str):
                Required. Resource identifier of the project creating
                the conversation. Format:
                ``projects/<Project ID>/locations/<Location ID>``.

                This corresponds to the ``parent`` field
                on the ``request`` instance; if ``request`` is provided, this
                should not be set.
            conversation (google.cloud.dialogflow_v2.types.Conversation):
                Required. The conversation to create.
                This corresponds to the ``conversation`` 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.Conversation:
                Represents a conversation.
                A conversation is an interaction between
                an agent, including live agents and
                Dialogflow agents, and a support
                customer. Conversations can include
                phone calls and text-based chat
                sessions.

        """
        # 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([parent, conversation])
        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_conversation.CreateConversationRequest.
        # There's no risk of modifying the input as we've already verified
        # there are no flattened fields.
        if not isinstance(request, gcd_conversation.CreateConversationRequest):
            request = gcd_conversation.CreateConversationRequest(request)

            # If we have keyword arguments corresponding to fields on the
            # request, apply these.

            if parent is not None:
                request.parent = parent
            if conversation is not None:
                request.conversation = conversation

        # Wrap the RPC method; this adds retry and timeout information,
        # and friendly error handling.
        rpc = self._transport._wrapped_methods[
            self._transport.create_conversation]

        # Certain fields should be provided within the metadata header;
        # add these here.
        metadata = tuple(metadata) + (gapic_v1.routing_header.to_grpc_metadata(
            (("parent", request.parent), )), )

        # Send the request.
        response = rpc(
            request,
            retry=retry,
            timeout=timeout,
            metadata=metadata,
        )

        # Done; return the response.
        return response