As of January 1, 2020 this library no longer supports Python 2 on the latest released version.
Library versions released prior to that date will continue to be available. For more information please
visit Python 2 support on Google Cloud.
Source code for google.cloud.dialogflow_v2.services.conversation_models.client
# -*- coding: utf-8 -*-
# Copyright 2024 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
from collections import OrderedDict
import os
import re
from typing import (
Callable,
Dict,
Mapping,
MutableMapping,
MutableSequence,
Optional,
Sequence,
Tuple,
Type,
Union,
cast,
)
import warnings
from google.api_core import client_options as client_options_lib
from google.api_core import exceptions as core_exceptions
from google.api_core import gapic_v1
from google.api_core import retry as retries
from google.auth import credentials as ga_credentials # type: ignore
from google.auth.exceptions import MutualTLSChannelError # type: ignore
from google.auth.transport import mtls # type: ignore
from google.auth.transport.grpc import SslCredentials # type: ignore
from google.oauth2 import service_account # type: ignore
from google.cloud.dialogflow_v2 import gapic_version as package_version
try:
OptionalRetry = Union[retries.Retry, gapic_v1.method._MethodDefault, None]
except AttributeError: # pragma: NO COVER
OptionalRetry = Union[retries.Retry, object, None] # type: ignore
from google.api_core import operation # type: ignore
from google.api_core import operation_async # type: ignore
from google.cloud.location import locations_pb2 # type: ignore
from google.longrunning import operations_pb2 # type: ignore
from google.protobuf import empty_pb2 # type: ignore
from google.protobuf import timestamp_pb2 # type: ignore
from google.cloud.dialogflow_v2.services.conversation_models import pagers
from google.cloud.dialogflow_v2.types import (
conversation_model as gcd_conversation_model,
)
from google.cloud.dialogflow_v2.types import conversation_model
from .transports.base import DEFAULT_CLIENT_INFO, ConversationModelsTransport
from .transports.grpc import ConversationModelsGrpcTransport
from .transports.grpc_asyncio import ConversationModelsGrpcAsyncIOTransport
from .transports.rest import ConversationModelsRestTransport
class ConversationModelsClientMeta(type):
"""Metaclass for the ConversationModels client.
This provides class-level methods for building and retrieving
support objects (e.g. transport) without polluting the client instance
objects.
"""
_transport_registry = (
OrderedDict()
) # type: Dict[str, Type[ConversationModelsTransport]]
_transport_registry["grpc"] = ConversationModelsGrpcTransport
_transport_registry["grpc_asyncio"] = ConversationModelsGrpcAsyncIOTransport
_transport_registry["rest"] = ConversationModelsRestTransport
def get_transport_class(
cls,
label: Optional[str] = None,
) -> Type[ConversationModelsTransport]:
"""Returns an appropriate transport class.
Args:
label: The name of the desired transport. If none is
provided, then the first transport in the registry is used.
Returns:
The transport class to use.
"""
# If a specific transport is requested, return that one.
if label:
return cls._transport_registry[label]
# No transport is requested; return the default (that is, the first one
# in the dictionary).
return next(iter(cls._transport_registry.values()))
[docs]class ConversationModelsClient(metaclass=ConversationModelsClientMeta):
"""Manages a collection of models for human agent assistant."""
@staticmethod
def _get_default_mtls_endpoint(api_endpoint):
"""Converts api endpoint to mTLS endpoint.
Convert "*.sandbox.googleapis.com" and "*.googleapis.com" to
"*.mtls.sandbox.googleapis.com" and "*.mtls.googleapis.com" respectively.
Args:
api_endpoint (Optional[str]): the api endpoint to convert.
Returns:
str: converted mTLS api endpoint.
"""
if not api_endpoint:
return api_endpoint
mtls_endpoint_re = re.compile(
r"(?P<name>[^.]+)(?P<mtls>\.mtls)?(?P<sandbox>\.sandbox)?(?P<googledomain>\.googleapis\.com)?"
)
m = mtls_endpoint_re.match(api_endpoint)
name, mtls, sandbox, googledomain = m.groups()
if mtls or not googledomain:
return api_endpoint
if sandbox:
return api_endpoint.replace(
"sandbox.googleapis.com", "mtls.sandbox.googleapis.com"
)
return api_endpoint.replace(".googleapis.com", ".mtls.googleapis.com")
# Note: DEFAULT_ENDPOINT is deprecated. Use _DEFAULT_ENDPOINT_TEMPLATE instead.
DEFAULT_ENDPOINT = "dialogflow.googleapis.com"
DEFAULT_MTLS_ENDPOINT = _get_default_mtls_endpoint.__func__( # type: ignore
DEFAULT_ENDPOINT
)
_DEFAULT_ENDPOINT_TEMPLATE = "dialogflow.{UNIVERSE_DOMAIN}"
_DEFAULT_UNIVERSE = "googleapis.com"
[docs] @classmethod
def from_service_account_info(cls, info: dict, *args, **kwargs):
"""Creates an instance of this client using the provided credentials
info.
Args:
info (dict): The service account private key info.
args: Additional arguments to pass to the constructor.
kwargs: Additional arguments to pass to the constructor.
Returns:
ConversationModelsClient: The constructed client.
"""
credentials = service_account.Credentials.from_service_account_info(info)
kwargs["credentials"] = credentials
return cls(*args, **kwargs)
[docs] @classmethod
def from_service_account_file(cls, filename: str, *args, **kwargs):
"""Creates an instance of this client using the provided credentials
file.
Args:
filename (str): The path to the service account private key json
file.
args: Additional arguments to pass to the constructor.
kwargs: Additional arguments to pass to the constructor.
Returns:
ConversationModelsClient: The constructed client.
"""
credentials = service_account.Credentials.from_service_account_file(filename)
kwargs["credentials"] = credentials
return cls(*args, **kwargs)
from_service_account_json = from_service_account_file
@property
def transport(self) -> ConversationModelsTransport:
"""Returns the transport used by the client instance.
Returns:
ConversationModelsTransport: The transport used by the client
instance.
"""
return self._transport
[docs] @staticmethod
def conversation_dataset_path(
project: str,
location: str,
conversation_dataset: str,
) -> str:
"""Returns a fully-qualified conversation_dataset string."""
return "projects/{project}/locations/{location}/conversationDatasets/{conversation_dataset}".format(
project=project,
location=location,
conversation_dataset=conversation_dataset,
)
[docs] @staticmethod
def parse_conversation_dataset_path(path: str) -> Dict[str, str]:
"""Parses a conversation_dataset path into its component segments."""
m = re.match(
r"^projects/(?P<project>.+?)/locations/(?P<location>.+?)/conversationDatasets/(?P<conversation_dataset>.+?)$",
path,
)
return m.groupdict() if m else {}
[docs] @staticmethod
def conversation_model_path(
project: str,
location: str,
conversation_model: str,
) -> str:
"""Returns a fully-qualified conversation_model string."""
return "projects/{project}/locations/{location}/conversationModels/{conversation_model}".format(
project=project,
location=location,
conversation_model=conversation_model,
)
[docs] @staticmethod
def parse_conversation_model_path(path: str) -> Dict[str, str]:
"""Parses a conversation_model path into its component segments."""
m = re.match(
r"^projects/(?P<project>.+?)/locations/(?P<location>.+?)/conversationModels/(?P<conversation_model>.+?)$",
path,
)
return m.groupdict() if m else {}
[docs] @staticmethod
def conversation_model_evaluation_path(
project: str,
conversation_model: str,
evaluation: str,
) -> str:
"""Returns a fully-qualified conversation_model_evaluation string."""
return "projects/{project}/conversationModels/{conversation_model}/evaluations/{evaluation}".format(
project=project,
conversation_model=conversation_model,
evaluation=evaluation,
)
[docs] @staticmethod
def parse_conversation_model_evaluation_path(path: str) -> Dict[str, str]:
"""Parses a conversation_model_evaluation path into its component segments."""
m = re.match(
r"^projects/(?P<project>.+?)/conversationModels/(?P<conversation_model>.+?)/evaluations/(?P<evaluation>.+?)$",
path,
)
return m.groupdict() if m else {}
[docs] @staticmethod
def document_path(
project: str,
knowledge_base: str,
document: str,
) -> str:
"""Returns a fully-qualified document string."""
return "projects/{project}/knowledgeBases/{knowledge_base}/documents/{document}".format(
project=project,
knowledge_base=knowledge_base,
document=document,
)
[docs] @staticmethod
def parse_document_path(path: str) -> Dict[str, str]:
"""Parses a document path into its component segments."""
m = re.match(
r"^projects/(?P<project>.+?)/knowledgeBases/(?P<knowledge_base>.+?)/documents/(?P<document>.+?)$",
path,
)
return m.groupdict() if m else {}
[docs] @staticmethod
def common_billing_account_path(
billing_account: str,
) -> str:
"""Returns a fully-qualified billing_account string."""
return "billingAccounts/{billing_account}".format(
billing_account=billing_account,
)
[docs] @staticmethod
def parse_common_billing_account_path(path: str) -> Dict[str, str]:
"""Parse a billing_account path into its component segments."""
m = re.match(r"^billingAccounts/(?P<billing_account>.+?)$", path)
return m.groupdict() if m else {}
[docs] @staticmethod
def common_folder_path(
folder: str,
) -> str:
"""Returns a fully-qualified folder string."""
return "folders/{folder}".format(
folder=folder,
)
[docs] @staticmethod
def parse_common_folder_path(path: str) -> Dict[str, str]:
"""Parse a folder path into its component segments."""
m = re.match(r"^folders/(?P<folder>.+?)$", path)
return m.groupdict() if m else {}
[docs] @staticmethod
def common_organization_path(
organization: str,
) -> str:
"""Returns a fully-qualified organization string."""
return "organizations/{organization}".format(
organization=organization,
)
[docs] @staticmethod
def parse_common_organization_path(path: str) -> Dict[str, str]:
"""Parse a organization path into its component segments."""
m = re.match(r"^organizations/(?P<organization>.+?)$", path)
return m.groupdict() if m else {}
[docs] @staticmethod
def common_project_path(
project: str,
) -> str:
"""Returns a fully-qualified project string."""
return "projects/{project}".format(
project=project,
)
[docs] @staticmethod
def parse_common_project_path(path: str) -> Dict[str, str]:
"""Parse a project path into its component segments."""
m = re.match(r"^projects/(?P<project>.+?)$", path)
return m.groupdict() if m else {}
[docs] @staticmethod
def common_location_path(
project: str,
location: str,
) -> str:
"""Returns a fully-qualified location string."""
return "projects/{project}/locations/{location}".format(
project=project,
location=location,
)
[docs] @staticmethod
def parse_common_location_path(path: str) -> Dict[str, str]:
"""Parse a location path into its component segments."""
m = re.match(r"^projects/(?P<project>.+?)/locations/(?P<location>.+?)$", path)
return m.groupdict() if m else {}
[docs] @classmethod
def get_mtls_endpoint_and_cert_source(
cls, client_options: Optional[client_options_lib.ClientOptions] = None
):
"""Deprecated. Return the API endpoint and client cert source for mutual TLS.
The client cert source is determined in the following order:
(1) if `GOOGLE_API_USE_CLIENT_CERTIFICATE` environment variable is not "true", the
client cert source is None.
(2) if `client_options.client_cert_source` is provided, use the provided one; if the
default client cert source exists, use the default one; otherwise the client cert
source is None.
The API endpoint is determined in the following order:
(1) if `client_options.api_endpoint` if provided, use the provided one.
(2) if `GOOGLE_API_USE_CLIENT_CERTIFICATE` environment variable is "always", use the
default mTLS endpoint; if the environment variable is "never", use the default API
endpoint; otherwise if client cert source exists, use the default mTLS endpoint, otherwise
use the default API endpoint.
More details can be found at https://google.aip.dev/auth/4114.
Args:
client_options (google.api_core.client_options.ClientOptions): Custom options for the
client. Only the `api_endpoint` and `client_cert_source` properties may be used
in this method.
Returns:
Tuple[str, Callable[[], Tuple[bytes, bytes]]]: returns the API endpoint and the
client cert source to use.
Raises:
google.auth.exceptions.MutualTLSChannelError: If any errors happen.
"""
warnings.warn(
"get_mtls_endpoint_and_cert_source is deprecated. Use the api_endpoint property instead.",
DeprecationWarning,
)
if client_options is None:
client_options = client_options_lib.ClientOptions()
use_client_cert = os.getenv("GOOGLE_API_USE_CLIENT_CERTIFICATE", "false")
use_mtls_endpoint = os.getenv("GOOGLE_API_USE_MTLS_ENDPOINT", "auto")
if use_client_cert not in ("true", "false"):
raise ValueError(
"Environment variable `GOOGLE_API_USE_CLIENT_CERTIFICATE` must be either `true` or `false`"
)
if use_mtls_endpoint not in ("auto", "never", "always"):
raise MutualTLSChannelError(
"Environment variable `GOOGLE_API_USE_MTLS_ENDPOINT` must be `never`, `auto` or `always`"
)
# Figure out the client cert source to use.
client_cert_source = None
if use_client_cert == "true":
if client_options.client_cert_source:
client_cert_source = client_options.client_cert_source
elif mtls.has_default_client_cert_source():
client_cert_source = mtls.default_client_cert_source()
# Figure out which api endpoint to use.
if client_options.api_endpoint is not None:
api_endpoint = client_options.api_endpoint
elif use_mtls_endpoint == "always" or (
use_mtls_endpoint == "auto" and client_cert_source
):
api_endpoint = cls.DEFAULT_MTLS_ENDPOINT
else:
api_endpoint = cls.DEFAULT_ENDPOINT
return api_endpoint, client_cert_source
@staticmethod
def _read_environment_variables():
"""Returns the environment variables used by the client.
Returns:
Tuple[bool, str, str]: returns the GOOGLE_API_USE_CLIENT_CERTIFICATE,
GOOGLE_API_USE_MTLS_ENDPOINT, and GOOGLE_CLOUD_UNIVERSE_DOMAIN environment variables.
Raises:
ValueError: If GOOGLE_API_USE_CLIENT_CERTIFICATE is not
any of ["true", "false"].
google.auth.exceptions.MutualTLSChannelError: If GOOGLE_API_USE_MTLS_ENDPOINT
is not any of ["auto", "never", "always"].
"""
use_client_cert = os.getenv(
"GOOGLE_API_USE_CLIENT_CERTIFICATE", "false"
).lower()
use_mtls_endpoint = os.getenv("GOOGLE_API_USE_MTLS_ENDPOINT", "auto").lower()
universe_domain_env = os.getenv("GOOGLE_CLOUD_UNIVERSE_DOMAIN")
if use_client_cert not in ("true", "false"):
raise ValueError(
"Environment variable `GOOGLE_API_USE_CLIENT_CERTIFICATE` must be either `true` or `false`"
)
if use_mtls_endpoint not in ("auto", "never", "always"):
raise MutualTLSChannelError(
"Environment variable `GOOGLE_API_USE_MTLS_ENDPOINT` must be `never`, `auto` or `always`"
)
return use_client_cert == "true", use_mtls_endpoint, universe_domain_env
@staticmethod
def _get_client_cert_source(provided_cert_source, use_cert_flag):
"""Return the client cert source to be used by the client.
Args:
provided_cert_source (bytes): The client certificate source provided.
use_cert_flag (bool): A flag indicating whether to use the client certificate.
Returns:
bytes or None: The client cert source to be used by the client.
"""
client_cert_source = None
if use_cert_flag:
if provided_cert_source:
client_cert_source = provided_cert_source
elif mtls.has_default_client_cert_source():
client_cert_source = mtls.default_client_cert_source()
return client_cert_source
@staticmethod
def _get_api_endpoint(
api_override, client_cert_source, universe_domain, use_mtls_endpoint
):
"""Return the API endpoint used by the client.
Args:
api_override (str): The API endpoint override. If specified, this is always
the return value of this function and the other arguments are not used.
client_cert_source (bytes): The client certificate source used by the client.
universe_domain (str): The universe domain used by the client.
use_mtls_endpoint (str): How to use the mTLS endpoint, which depends also on the other parameters.
Possible values are "always", "auto", or "never".
Returns:
str: The API endpoint to be used by the client.
"""
if api_override is not None:
api_endpoint = api_override
elif use_mtls_endpoint == "always" or (
use_mtls_endpoint == "auto" and client_cert_source
):
_default_universe = ConversationModelsClient._DEFAULT_UNIVERSE
if universe_domain != _default_universe:
raise MutualTLSChannelError(
f"mTLS is not supported in any universe other than {_default_universe}."
)
api_endpoint = ConversationModelsClient.DEFAULT_MTLS_ENDPOINT
else:
api_endpoint = ConversationModelsClient._DEFAULT_ENDPOINT_TEMPLATE.format(
UNIVERSE_DOMAIN=universe_domain
)
return api_endpoint
@staticmethod
def _get_universe_domain(
client_universe_domain: Optional[str], universe_domain_env: Optional[str]
) -> str:
"""Return the universe domain used by the client.
Args:
client_universe_domain (Optional[str]): The universe domain configured via the client options.
universe_domain_env (Optional[str]): The universe domain configured via the "GOOGLE_CLOUD_UNIVERSE_DOMAIN" environment variable.
Returns:
str: The universe domain to be used by the client.
Raises:
ValueError: If the universe domain is an empty string.
"""
universe_domain = ConversationModelsClient._DEFAULT_UNIVERSE
if client_universe_domain is not None:
universe_domain = client_universe_domain
elif universe_domain_env is not None:
universe_domain = universe_domain_env
if len(universe_domain.strip()) == 0:
raise ValueError("Universe Domain cannot be an empty string.")
return universe_domain
def _validate_universe_domain(self):
"""Validates client's and credentials' universe domains are consistent.
Returns:
bool: True iff the configured universe domain is valid.
Raises:
ValueError: If the configured universe domain is not valid.
"""
# NOTE (b/349488459): universe validation is disabled until further notice.
return True
@property
def api_endpoint(self):
"""Return the API endpoint used by the client instance.
Returns:
str: The API endpoint used by the client instance.
"""
return self._api_endpoint
@property
def universe_domain(self) -> str:
"""Return the universe domain used by the client instance.
Returns:
str: The universe domain used by the client instance.
"""
return self._universe_domain
def __init__(
self,
*,
credentials: Optional[ga_credentials.Credentials] = None,
transport: Optional[
Union[
str,
ConversationModelsTransport,
Callable[..., ConversationModelsTransport],
]
] = None,
client_options: Optional[Union[client_options_lib.ClientOptions, dict]] = None,
client_info: gapic_v1.client_info.ClientInfo = DEFAULT_CLIENT_INFO,
) -> None:
"""Instantiates the conversation models client.
Args:
credentials (Optional[google.auth.credentials.Credentials]): The
authorization credentials to attach to requests. These
credentials identify the application to the service; if none
are specified, the client will attempt to ascertain the
credentials from the environment.
transport (Optional[Union[str,ConversationModelsTransport,Callable[..., ConversationModelsTransport]]]):
The transport to use, or a Callable that constructs and returns a new transport.
If a Callable is given, it will be called with the same set of initialization
arguments as used in the ConversationModelsTransport constructor.
If set to None, a transport is chosen automatically.
client_options (Optional[Union[google.api_core.client_options.ClientOptions, dict]]):
Custom options for the client.
1. The ``api_endpoint`` property can be used to override the
default endpoint provided by the client when ``transport`` is
not explicitly provided. Only if this property is not set and
``transport`` was not explicitly provided, the endpoint is
determined by the GOOGLE_API_USE_MTLS_ENDPOINT environment
variable, which have one of the following values:
"always" (always use the default mTLS endpoint), "never" (always
use the default regular endpoint) and "auto" (auto-switch to the
default mTLS endpoint if client certificate is present; this is
the default value).
2. If the GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable
is "true", then the ``client_cert_source`` property can be used
to provide a client certificate for mTLS transport. If
not provided, the default SSL client certificate will be used if
present. If GOOGLE_API_USE_CLIENT_CERTIFICATE is "false" or not
set, no client certificate will be used.
3. The ``universe_domain`` property can be used to override the
default "googleapis.com" universe. Note that the ``api_endpoint``
property still takes precedence; and ``universe_domain`` is
currently not supported for mTLS.
client_info (google.api_core.gapic_v1.client_info.ClientInfo):
The client info used to send a user-agent string along with
API requests. If ``None``, then default info will be used.
Generally, you only need to set this if you're developing
your own client library.
Raises:
google.auth.exceptions.MutualTLSChannelError: If mutual TLS transport
creation failed for any reason.
"""
self._client_options = client_options
if isinstance(self._client_options, dict):
self._client_options = client_options_lib.from_dict(self._client_options)
if self._client_options is None:
self._client_options = client_options_lib.ClientOptions()
self._client_options = cast(
client_options_lib.ClientOptions, self._client_options
)
universe_domain_opt = getattr(self._client_options, "universe_domain", None)
(
self._use_client_cert,
self._use_mtls_endpoint,
self._universe_domain_env,
) = ConversationModelsClient._read_environment_variables()
self._client_cert_source = ConversationModelsClient._get_client_cert_source(
self._client_options.client_cert_source, self._use_client_cert
)
self._universe_domain = ConversationModelsClient._get_universe_domain(
universe_domain_opt, self._universe_domain_env
)
self._api_endpoint = None # updated below, depending on `transport`
# Initialize the universe domain validation.
self._is_universe_domain_valid = False
api_key_value = getattr(self._client_options, "api_key", None)
if api_key_value and credentials:
raise ValueError(
"client_options.api_key and credentials are mutually exclusive"
)
# Save or instantiate the transport.
# Ordinarily, we provide the transport, but allowing a custom transport
# instance provides an extensibility point for unusual situations.
transport_provided = isinstance(transport, ConversationModelsTransport)
if transport_provided:
# transport is a ConversationModelsTransport instance.
if credentials or self._client_options.credentials_file or api_key_value:
raise ValueError(
"When providing a transport instance, "
"provide its credentials directly."
)
if self._client_options.scopes:
raise ValueError(
"When providing a transport instance, provide its scopes "
"directly."
)
self._transport = cast(ConversationModelsTransport, transport)
self._api_endpoint = self._transport.host
self._api_endpoint = (
self._api_endpoint
or ConversationModelsClient._get_api_endpoint(
self._client_options.api_endpoint,
self._client_cert_source,
self._universe_domain,
self._use_mtls_endpoint,
)
)
if not transport_provided:
import google.auth._default # type: ignore
if api_key_value and hasattr(
google.auth._default, "get_api_key_credentials"
):
credentials = google.auth._default.get_api_key_credentials(
api_key_value
)
transport_init: Union[
Type[ConversationModelsTransport],
Callable[..., ConversationModelsTransport],
] = (
ConversationModelsClient.get_transport_class(transport)
if isinstance(transport, str) or transport is None
else cast(Callable[..., ConversationModelsTransport], transport)
)
# initialize with the provided callable or the passed in class
self._transport = transport_init(
credentials=credentials,
credentials_file=self._client_options.credentials_file,
host=self._api_endpoint,
scopes=self._client_options.scopes,
client_cert_source_for_mtls=self._client_cert_source,
quota_project_id=self._client_options.quota_project_id,
client_info=client_info,
always_use_jwt_access=True,
api_audience=self._client_options.api_audience,
)
[docs] def create_conversation_model(
self,
request: Optional[
Union[gcd_conversation_model.CreateConversationModelRequest, dict]
] = None,
*,
parent: Optional[str] = None,
conversation_model: Optional[gcd_conversation_model.ConversationModel] = None,
retry: OptionalRetry = gapic_v1.method.DEFAULT,
timeout: Union[float, object] = gapic_v1.method.DEFAULT,
metadata: Sequence[Tuple[str, str]] = (),
) -> operation.Operation:
r"""Creates a model.
This method is a `long-running
operation <https://cloud.google.com/dialogflow/es/docs/how/long-running-operations>`__.
The returned ``Operation`` type has the following
method-specific fields:
- ``metadata``:
[CreateConversationModelOperationMetadata][google.cloud.dialogflow.v2.CreateConversationModelOperationMetadata]
- ``response``:
[ConversationModel][google.cloud.dialogflow.v2.ConversationModel]
.. code-block:: python
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import dialogflow_v2
def sample_create_conversation_model():
# Create a client
client = dialogflow_v2.ConversationModelsClient()
# Initialize request argument(s)
conversation_model = dialogflow_v2.ConversationModel()
conversation_model.display_name = "display_name_value"
conversation_model.datasets.dataset = "dataset_value"
request = dialogflow_v2.CreateConversationModelRequest(
conversation_model=conversation_model,
)
# Make the request
operation = client.create_conversation_model(request=request)
print("Waiting for operation to complete...")
response = operation.result()
# Handle the response
print(response)
Args:
request (Union[google.cloud.dialogflow_v2.types.CreateConversationModelRequest, dict]):
The request object. The request message for
[ConversationModels.CreateConversationModel][google.cloud.dialogflow.v2.ConversationModels.CreateConversationModel]
parent (str):
The project to create conversation model for. Format:
``projects/<Project ID>``
This corresponds to the ``parent`` field
on the ``request`` instance; if ``request`` is provided, this
should not be set.
conversation_model (google.cloud.dialogflow_v2.types.ConversationModel):
Required. The conversation model to
create.
This corresponds to the ``conversation_model`` 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.api_core.operation.Operation:
An object representing a long-running operation.
The result type for the operation will be
:class:`google.cloud.dialogflow_v2.types.ConversationModel`
Represents a conversation model.
"""
# 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_model])
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."
)
# - Use the request object if provided (there's no risk of modifying the input as
# there are no flattened fields), or create one.
if not isinstance(
request, gcd_conversation_model.CreateConversationModelRequest
):
request = gcd_conversation_model.CreateConversationModelRequest(request)
# If we have keyword arguments corresponding to fields on the
# request, apply these.
if parent is not None:
request.parent = parent
if conversation_model is not None:
request.conversation_model = conversation_model
# Wrap the RPC method; this adds retry and timeout information,
# and friendly error handling.
rpc = self._transport._wrapped_methods[
self._transport.create_conversation_model
]
# 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),)),
)
# Validate the universe domain.
self._validate_universe_domain()
# Send the request.
response = rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# Wrap the response in an operation future.
response = operation.from_gapic(
response,
self._transport.operations_client,
gcd_conversation_model.ConversationModel,
metadata_type=gcd_conversation_model.CreateConversationModelOperationMetadata,
)
# Done; return the response.
return response
[docs] def get_conversation_model(
self,
request: Optional[
Union[conversation_model.GetConversationModelRequest, dict]
] = None,
*,
name: Optional[str] = None,
retry: OptionalRetry = gapic_v1.method.DEFAULT,
timeout: Union[float, object] = gapic_v1.method.DEFAULT,
metadata: Sequence[Tuple[str, str]] = (),
) -> conversation_model.ConversationModel:
r"""Gets conversation model.
.. code-block:: python
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import dialogflow_v2
def sample_get_conversation_model():
# Create a client
client = dialogflow_v2.ConversationModelsClient()
# Initialize request argument(s)
request = dialogflow_v2.GetConversationModelRequest(
name="name_value",
)
# Make the request
response = client.get_conversation_model(request=request)
# Handle the response
print(response)
Args:
request (Union[google.cloud.dialogflow_v2.types.GetConversationModelRequest, dict]):
The request object. The request message for
[ConversationModels.GetConversationModel][google.cloud.dialogflow.v2.ConversationModels.GetConversationModel]
name (str):
Required. The conversation model to retrieve. Format:
``projects/<Project ID>/conversationModels/<Conversation Model ID>``
This corresponds to the ``name`` 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.ConversationModel:
Represents a conversation model.
"""
# 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([name])
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."
)
# - Use the request object if provided (there's no risk of modifying the input as
# there are no flattened fields), or create one.
if not isinstance(request, conversation_model.GetConversationModelRequest):
request = conversation_model.GetConversationModelRequest(request)
# If we have keyword arguments corresponding to fields on the
# request, apply these.
if name is not None:
request.name = name
# Wrap the RPC method; this adds retry and timeout information,
# and friendly error handling.
rpc = self._transport._wrapped_methods[self._transport.get_conversation_model]
# Certain fields should be provided within the metadata header;
# add these here.
metadata = tuple(metadata) + (
gapic_v1.routing_header.to_grpc_metadata((("name", request.name),)),
)
# Validate the universe domain.
self._validate_universe_domain()
# Send the request.
response = rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# Done; return the response.
return response
[docs] def list_conversation_models(
self,
request: Optional[
Union[conversation_model.ListConversationModelsRequest, dict]
] = None,
*,
parent: Optional[str] = None,
retry: OptionalRetry = gapic_v1.method.DEFAULT,
timeout: Union[float, object] = gapic_v1.method.DEFAULT,
metadata: Sequence[Tuple[str, str]] = (),
) -> pagers.ListConversationModelsPager:
r"""Lists conversation models.
.. code-block:: python
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import dialogflow_v2
def sample_list_conversation_models():
# Create a client
client = dialogflow_v2.ConversationModelsClient()
# Initialize request argument(s)
request = dialogflow_v2.ListConversationModelsRequest(
parent="parent_value",
)
# Make the request
page_result = client.list_conversation_models(request=request)
# Handle the response
for response in page_result:
print(response)
Args:
request (Union[google.cloud.dialogflow_v2.types.ListConversationModelsRequest, dict]):
The request object. The request message for
[ConversationModels.ListConversationModels][google.cloud.dialogflow.v2.ConversationModels.ListConversationModels]
parent (str):
Required. The project to list all conversation models
for. Format: ``projects/<Project ID>``
This corresponds to the ``parent`` 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.services.conversation_models.pagers.ListConversationModelsPager:
The response message for
[ConversationModels.ListConversationModels][google.cloud.dialogflow.v2.ConversationModels.ListConversationModels]
Iterating over this object will yield results and
resolve additional pages automatically.
"""
# 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])
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."
)
# - Use the request object if provided (there's no risk of modifying the input as
# there are no flattened fields), or create one.
if not isinstance(request, conversation_model.ListConversationModelsRequest):
request = conversation_model.ListConversationModelsRequest(request)
# If we have keyword arguments corresponding to fields on the
# request, apply these.
if parent is not None:
request.parent = parent
# Wrap the RPC method; this adds retry and timeout information,
# and friendly error handling.
rpc = self._transport._wrapped_methods[self._transport.list_conversation_models]
# 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),)),
)
# Validate the universe domain.
self._validate_universe_domain()
# Send the request.
response = rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# This method is paged; wrap the response in a pager, which provides
# an `__iter__` convenience method.
response = pagers.ListConversationModelsPager(
method=rpc,
request=request,
response=response,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# Done; return the response.
return response
[docs] def delete_conversation_model(
self,
request: Optional[
Union[conversation_model.DeleteConversationModelRequest, dict]
] = None,
*,
name: Optional[str] = None,
retry: OptionalRetry = gapic_v1.method.DEFAULT,
timeout: Union[float, object] = gapic_v1.method.DEFAULT,
metadata: Sequence[Tuple[str, str]] = (),
) -> operation.Operation:
r"""Deletes a model.
This method is a `long-running
operation <https://cloud.google.com/dialogflow/es/docs/how/long-running-operations>`__.
The returned ``Operation`` type has the following
method-specific fields:
- ``metadata``:
[DeleteConversationModelOperationMetadata][google.cloud.dialogflow.v2.DeleteConversationModelOperationMetadata]
- ``response``: An `Empty
message <https://developers.google.com/protocol-buffers/docs/reference/google.protobuf#empty>`__
.. code-block:: python
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import dialogflow_v2
def sample_delete_conversation_model():
# Create a client
client = dialogflow_v2.ConversationModelsClient()
# Initialize request argument(s)
request = dialogflow_v2.DeleteConversationModelRequest(
name="name_value",
)
# Make the request
operation = client.delete_conversation_model(request=request)
print("Waiting for operation to complete...")
response = operation.result()
# Handle the response
print(response)
Args:
request (Union[google.cloud.dialogflow_v2.types.DeleteConversationModelRequest, dict]):
The request object. The request message for
[ConversationModels.DeleteConversationModel][google.cloud.dialogflow.v2.ConversationModels.DeleteConversationModel]
name (str):
Required. The conversation model to delete. Format:
``projects/<Project ID>/conversationModels/<Conversation Model ID>``
This corresponds to the ``name`` 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.api_core.operation.Operation:
An object representing a long-running operation.
The result type for the operation will be :class:`google.protobuf.empty_pb2.Empty` A generic empty message that you can re-use to avoid defining duplicated
empty messages in your APIs. A typical example is to
use it as the request or the response type of an API
method. For instance:
service Foo {
rpc Bar(google.protobuf.Empty) returns
(google.protobuf.Empty);
}
"""
# 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([name])
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."
)
# - Use the request object if provided (there's no risk of modifying the input as
# there are no flattened fields), or create one.
if not isinstance(request, conversation_model.DeleteConversationModelRequest):
request = conversation_model.DeleteConversationModelRequest(request)
# If we have keyword arguments corresponding to fields on the
# request, apply these.
if name is not None:
request.name = name
# Wrap the RPC method; this adds retry and timeout information,
# and friendly error handling.
rpc = self._transport._wrapped_methods[
self._transport.delete_conversation_model
]
# Certain fields should be provided within the metadata header;
# add these here.
metadata = tuple(metadata) + (
gapic_v1.routing_header.to_grpc_metadata((("name", request.name),)),
)
# Validate the universe domain.
self._validate_universe_domain()
# Send the request.
response = rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# Wrap the response in an operation future.
response = operation.from_gapic(
response,
self._transport.operations_client,
empty_pb2.Empty,
metadata_type=conversation_model.DeleteConversationModelOperationMetadata,
)
# Done; return the response.
return response
[docs] def deploy_conversation_model(
self,
request: Optional[
Union[conversation_model.DeployConversationModelRequest, dict]
] = None,
*,
retry: OptionalRetry = gapic_v1.method.DEFAULT,
timeout: Union[float, object] = gapic_v1.method.DEFAULT,
metadata: Sequence[Tuple[str, str]] = (),
) -> operation.Operation:
r"""Deploys a model. If a model is already deployed, deploying it
has no effect. A model can only serve prediction requests after
it gets deployed. For article suggestion, custom model will not
be used unless it is deployed.
This method is a `long-running
operation <https://cloud.google.com/dialogflow/es/docs/how/long-running-operations>`__.
The returned ``Operation`` type has the following
method-specific fields:
- ``metadata``:
[DeployConversationModelOperationMetadata][google.cloud.dialogflow.v2.DeployConversationModelOperationMetadata]
- ``response``: An `Empty
message <https://developers.google.com/protocol-buffers/docs/reference/google.protobuf#empty>`__
.. code-block:: python
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import dialogflow_v2
def sample_deploy_conversation_model():
# Create a client
client = dialogflow_v2.ConversationModelsClient()
# Initialize request argument(s)
request = dialogflow_v2.DeployConversationModelRequest(
name="name_value",
)
# Make the request
operation = client.deploy_conversation_model(request=request)
print("Waiting for operation to complete...")
response = operation.result()
# Handle the response
print(response)
Args:
request (Union[google.cloud.dialogflow_v2.types.DeployConversationModelRequest, dict]):
The request object. The request message for
[ConversationModels.DeployConversationModel][google.cloud.dialogflow.v2.ConversationModels.DeployConversationModel]
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.api_core.operation.Operation:
An object representing a long-running operation.
The result type for the operation will be :class:`google.protobuf.empty_pb2.Empty` A generic empty message that you can re-use to avoid defining duplicated
empty messages in your APIs. A typical example is to
use it as the request or the response type of an API
method. For instance:
service Foo {
rpc Bar(google.protobuf.Empty) returns
(google.protobuf.Empty);
}
"""
# Create or coerce a protobuf request object.
# - Use the request object if provided (there's no risk of modifying the input as
# there are no flattened fields), or create one.
if not isinstance(request, conversation_model.DeployConversationModelRequest):
request = conversation_model.DeployConversationModelRequest(request)
# Wrap the RPC method; this adds retry and timeout information,
# and friendly error handling.
rpc = self._transport._wrapped_methods[
self._transport.deploy_conversation_model
]
# Certain fields should be provided within the metadata header;
# add these here.
metadata = tuple(metadata) + (
gapic_v1.routing_header.to_grpc_metadata((("name", request.name),)),
)
# Validate the universe domain.
self._validate_universe_domain()
# Send the request.
response = rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# Wrap the response in an operation future.
response = operation.from_gapic(
response,
self._transport.operations_client,
empty_pb2.Empty,
metadata_type=conversation_model.DeployConversationModelOperationMetadata,
)
# Done; return the response.
return response
[docs] def undeploy_conversation_model(
self,
request: Optional[
Union[conversation_model.UndeployConversationModelRequest, dict]
] = None,
*,
retry: OptionalRetry = gapic_v1.method.DEFAULT,
timeout: Union[float, object] = gapic_v1.method.DEFAULT,
metadata: Sequence[Tuple[str, str]] = (),
) -> operation.Operation:
r"""Undeploys a model. If the model is not deployed this method has
no effect. If the model is currently being used:
- For article suggestion, article suggestion will fallback to
the default model if model is undeployed.
This method is a `long-running
operation <https://cloud.google.com/dialogflow/es/docs/how/long-running-operations>`__.
The returned ``Operation`` type has the following
method-specific fields:
- ``metadata``:
[UndeployConversationModelOperationMetadata][google.cloud.dialogflow.v2.UndeployConversationModelOperationMetadata]
- ``response``: An `Empty
message <https://developers.google.com/protocol-buffers/docs/reference/google.protobuf#empty>`__
.. code-block:: python
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import dialogflow_v2
def sample_undeploy_conversation_model():
# Create a client
client = dialogflow_v2.ConversationModelsClient()
# Initialize request argument(s)
request = dialogflow_v2.UndeployConversationModelRequest(
name="name_value",
)
# Make the request
operation = client.undeploy_conversation_model(request=request)
print("Waiting for operation to complete...")
response = operation.result()
# Handle the response
print(response)
Args:
request (Union[google.cloud.dialogflow_v2.types.UndeployConversationModelRequest, dict]):
The request object. The request message for
[ConversationModels.UndeployConversationModel][google.cloud.dialogflow.v2.ConversationModels.UndeployConversationModel]
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.api_core.operation.Operation:
An object representing a long-running operation.
The result type for the operation will be :class:`google.protobuf.empty_pb2.Empty` A generic empty message that you can re-use to avoid defining duplicated
empty messages in your APIs. A typical example is to
use it as the request or the response type of an API
method. For instance:
service Foo {
rpc Bar(google.protobuf.Empty) returns
(google.protobuf.Empty);
}
"""
# Create or coerce a protobuf request object.
# - Use the request object if provided (there's no risk of modifying the input as
# there are no flattened fields), or create one.
if not isinstance(request, conversation_model.UndeployConversationModelRequest):
request = conversation_model.UndeployConversationModelRequest(request)
# Wrap the RPC method; this adds retry and timeout information,
# and friendly error handling.
rpc = self._transport._wrapped_methods[
self._transport.undeploy_conversation_model
]
# Certain fields should be provided within the metadata header;
# add these here.
metadata = tuple(metadata) + (
gapic_v1.routing_header.to_grpc_metadata((("name", request.name),)),
)
# Validate the universe domain.
self._validate_universe_domain()
# Send the request.
response = rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# Wrap the response in an operation future.
response = operation.from_gapic(
response,
self._transport.operations_client,
empty_pb2.Empty,
metadata_type=conversation_model.UndeployConversationModelOperationMetadata,
)
# Done; return the response.
return response
[docs] def get_conversation_model_evaluation(
self,
request: Optional[
Union[conversation_model.GetConversationModelEvaluationRequest, dict]
] = None,
*,
name: Optional[str] = None,
retry: OptionalRetry = gapic_v1.method.DEFAULT,
timeout: Union[float, object] = gapic_v1.method.DEFAULT,
metadata: Sequence[Tuple[str, str]] = (),
) -> conversation_model.ConversationModelEvaluation:
r"""Gets an evaluation of conversation model.
.. code-block:: python
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import dialogflow_v2
def sample_get_conversation_model_evaluation():
# Create a client
client = dialogflow_v2.ConversationModelsClient()
# Initialize request argument(s)
request = dialogflow_v2.GetConversationModelEvaluationRequest(
name="name_value",
)
# Make the request
response = client.get_conversation_model_evaluation(request=request)
# Handle the response
print(response)
Args:
request (Union[google.cloud.dialogflow_v2.types.GetConversationModelEvaluationRequest, dict]):
The request object. The request message for
[ConversationModels.GetConversationModelEvaluation][google.cloud.dialogflow.v2.ConversationModels.GetConversationModelEvaluation]
name (str):
Required. The conversation model evaluation resource
name. Format:
``projects/<Project ID>/conversationModels/<Conversation Model ID>/evaluations/<Evaluation ID>``
This corresponds to the ``name`` 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.ConversationModelEvaluation:
Represents evaluation result of a
conversation model.
"""
# 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([name])
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."
)
# - Use the request object if provided (there's no risk of modifying the input as
# there are no flattened fields), or create one.
if not isinstance(
request, conversation_model.GetConversationModelEvaluationRequest
):
request = conversation_model.GetConversationModelEvaluationRequest(request)
# If we have keyword arguments corresponding to fields on the
# request, apply these.
if name is not None:
request.name = name
# Wrap the RPC method; this adds retry and timeout information,
# and friendly error handling.
rpc = self._transport._wrapped_methods[
self._transport.get_conversation_model_evaluation
]
# Certain fields should be provided within the metadata header;
# add these here.
metadata = tuple(metadata) + (
gapic_v1.routing_header.to_grpc_metadata((("name", request.name),)),
)
# Validate the universe domain.
self._validate_universe_domain()
# Send the request.
response = rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# Done; return the response.
return response
[docs] def list_conversation_model_evaluations(
self,
request: Optional[
Union[conversation_model.ListConversationModelEvaluationsRequest, dict]
] = None,
*,
parent: Optional[str] = None,
retry: OptionalRetry = gapic_v1.method.DEFAULT,
timeout: Union[float, object] = gapic_v1.method.DEFAULT,
metadata: Sequence[Tuple[str, str]] = (),
) -> pagers.ListConversationModelEvaluationsPager:
r"""Lists evaluations of a conversation model.
.. code-block:: python
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import dialogflow_v2
def sample_list_conversation_model_evaluations():
# Create a client
client = dialogflow_v2.ConversationModelsClient()
# Initialize request argument(s)
request = dialogflow_v2.ListConversationModelEvaluationsRequest(
parent="parent_value",
)
# Make the request
page_result = client.list_conversation_model_evaluations(request=request)
# Handle the response
for response in page_result:
print(response)
Args:
request (Union[google.cloud.dialogflow_v2.types.ListConversationModelEvaluationsRequest, dict]):
The request object. The request message for
[ConversationModels.ListConversationModelEvaluations][google.cloud.dialogflow.v2.ConversationModels.ListConversationModelEvaluations]
parent (str):
Required. The conversation model resource name. Format:
``projects/<Project ID>/conversationModels/<Conversation Model ID>``
This corresponds to the ``parent`` 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.services.conversation_models.pagers.ListConversationModelEvaluationsPager:
The response message for
[ConversationModels.ListConversationModelEvaluations][google.cloud.dialogflow.v2.ConversationModels.ListConversationModelEvaluations]
Iterating over this object will yield results and
resolve additional pages automatically.
"""
# 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])
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."
)
# - Use the request object if provided (there's no risk of modifying the input as
# there are no flattened fields), or create one.
if not isinstance(
request, conversation_model.ListConversationModelEvaluationsRequest
):
request = conversation_model.ListConversationModelEvaluationsRequest(
request
)
# If we have keyword arguments corresponding to fields on the
# request, apply these.
if parent is not None:
request.parent = parent
# Wrap the RPC method; this adds retry and timeout information,
# and friendly error handling.
rpc = self._transport._wrapped_methods[
self._transport.list_conversation_model_evaluations
]
# 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),)),
)
# Validate the universe domain.
self._validate_universe_domain()
# Send the request.
response = rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# This method is paged; wrap the response in a pager, which provides
# an `__iter__` convenience method.
response = pagers.ListConversationModelEvaluationsPager(
method=rpc,
request=request,
response=response,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# Done; return the response.
return response
[docs] def create_conversation_model_evaluation(
self,
request: Optional[
Union[conversation_model.CreateConversationModelEvaluationRequest, dict]
] = None,
*,
parent: Optional[str] = None,
conversation_model_evaluation: Optional[
conversation_model.ConversationModelEvaluation
] = None,
retry: OptionalRetry = gapic_v1.method.DEFAULT,
timeout: Union[float, object] = gapic_v1.method.DEFAULT,
metadata: Sequence[Tuple[str, str]] = (),
) -> operation.Operation:
r"""Creates evaluation of a conversation model.
.. code-block:: python
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import dialogflow_v2
def sample_create_conversation_model_evaluation():
# Create a client
client = dialogflow_v2.ConversationModelsClient()
# Initialize request argument(s)
request = dialogflow_v2.CreateConversationModelEvaluationRequest(
parent="parent_value",
)
# Make the request
operation = client.create_conversation_model_evaluation(request=request)
print("Waiting for operation to complete...")
response = operation.result()
# Handle the response
print(response)
Args:
request (Union[google.cloud.dialogflow_v2.types.CreateConversationModelEvaluationRequest, dict]):
The request object. The request message for
[ConversationModels.CreateConversationModelEvaluation][google.cloud.dialogflow.v2.ConversationModels.CreateConversationModelEvaluation]
parent (str):
Required. The conversation model resource name. Format:
``projects/<Project ID>/locations/<Location ID>/conversationModels/<Conversation Model ID>``
This corresponds to the ``parent`` field
on the ``request`` instance; if ``request`` is provided, this
should not be set.
conversation_model_evaluation (google.cloud.dialogflow_v2.types.ConversationModelEvaluation):
Required. The conversation model
evaluation to be created.
This corresponds to the ``conversation_model_evaluation`` 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.api_core.operation.Operation:
An object representing a long-running operation.
The result type for the operation will be
:class:`google.cloud.dialogflow_v2.types.ConversationModelEvaluation`
Represents evaluation result of a conversation model.
"""
# 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_model_evaluation])
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."
)
# - Use the request object if provided (there's no risk of modifying the input as
# there are no flattened fields), or create one.
if not isinstance(
request, conversation_model.CreateConversationModelEvaluationRequest
):
request = conversation_model.CreateConversationModelEvaluationRequest(
request
)
# If we have keyword arguments corresponding to fields on the
# request, apply these.
if parent is not None:
request.parent = parent
if conversation_model_evaluation is not None:
request.conversation_model_evaluation = conversation_model_evaluation
# Wrap the RPC method; this adds retry and timeout information,
# and friendly error handling.
rpc = self._transport._wrapped_methods[
self._transport.create_conversation_model_evaluation
]
# 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),)),
)
# Validate the universe domain.
self._validate_universe_domain()
# Send the request.
response = rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# Wrap the response in an operation future.
response = operation.from_gapic(
response,
self._transport.operations_client,
conversation_model.ConversationModelEvaluation,
metadata_type=conversation_model.CreateConversationModelEvaluationOperationMetadata,
)
# Done; return the response.
return response
def __enter__(self) -> "ConversationModelsClient":
return self
[docs] def __exit__(self, type, value, traceback):
"""Releases underlying transport's resources.
.. warning::
ONLY use as a context manager if the transport is NOT shared
with other clients! Exiting the with block will CLOSE the transport
and may cause errors in other clients!
"""
self.transport.close()
[docs] def list_operations(
self,
request: Optional[operations_pb2.ListOperationsRequest] = None,
*,
retry: OptionalRetry = gapic_v1.method.DEFAULT,
timeout: Union[float, object] = gapic_v1.method.DEFAULT,
metadata: Sequence[Tuple[str, str]] = (),
) -> operations_pb2.ListOperationsResponse:
r"""Lists operations that match the specified filter in the request.
Args:
request (:class:`~.operations_pb2.ListOperationsRequest`):
The request object. Request message for
`ListOperations` method.
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:
~.operations_pb2.ListOperationsResponse:
Response message for ``ListOperations`` method.
"""
# Create or coerce a protobuf request object.
# The request isn't a proto-plus wrapped type,
# so it must be constructed via keyword expansion.
if isinstance(request, dict):
request = operations_pb2.ListOperationsRequest(**request)
# Wrap the RPC method; this adds retry and timeout information,
# and friendly error handling.
rpc = self._transport._wrapped_methods[self._transport.list_operations]
# Certain fields should be provided within the metadata header;
# add these here.
metadata = tuple(metadata) + (
gapic_v1.routing_header.to_grpc_metadata((("name", request.name),)),
)
# Validate the universe domain.
self._validate_universe_domain()
# Send the request.
response = rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# Done; return the response.
return response
[docs] def get_operation(
self,
request: Optional[operations_pb2.GetOperationRequest] = None,
*,
retry: OptionalRetry = gapic_v1.method.DEFAULT,
timeout: Union[float, object] = gapic_v1.method.DEFAULT,
metadata: Sequence[Tuple[str, str]] = (),
) -> operations_pb2.Operation:
r"""Gets the latest state of a long-running operation.
Args:
request (:class:`~.operations_pb2.GetOperationRequest`):
The request object. Request message for
`GetOperation` method.
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:
~.operations_pb2.Operation:
An ``Operation`` object.
"""
# Create or coerce a protobuf request object.
# The request isn't a proto-plus wrapped type,
# so it must be constructed via keyword expansion.
if isinstance(request, dict):
request = operations_pb2.GetOperationRequest(**request)
# Wrap the RPC method; this adds retry and timeout information,
# and friendly error handling.
rpc = self._transport._wrapped_methods[self._transport.get_operation]
# Certain fields should be provided within the metadata header;
# add these here.
metadata = tuple(metadata) + (
gapic_v1.routing_header.to_grpc_metadata((("name", request.name),)),
)
# Validate the universe domain.
self._validate_universe_domain()
# Send the request.
response = rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# Done; return the response.
return response
[docs] def cancel_operation(
self,
request: Optional[operations_pb2.CancelOperationRequest] = None,
*,
retry: OptionalRetry = gapic_v1.method.DEFAULT,
timeout: Union[float, object] = gapic_v1.method.DEFAULT,
metadata: Sequence[Tuple[str, str]] = (),
) -> None:
r"""Starts asynchronous cancellation on a long-running operation.
The server makes a best effort to cancel the operation, but success
is not guaranteed. If the server doesn't support this method, it returns
`google.rpc.Code.UNIMPLEMENTED`.
Args:
request (:class:`~.operations_pb2.CancelOperationRequest`):
The request object. Request message for
`CancelOperation` method.
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:
None
"""
# Create or coerce a protobuf request object.
# The request isn't a proto-plus wrapped type,
# so it must be constructed via keyword expansion.
if isinstance(request, dict):
request = operations_pb2.CancelOperationRequest(**request)
# Wrap the RPC method; this adds retry and timeout information,
# and friendly error handling.
rpc = self._transport._wrapped_methods[self._transport.cancel_operation]
# Certain fields should be provided within the metadata header;
# add these here.
metadata = tuple(metadata) + (
gapic_v1.routing_header.to_grpc_metadata((("name", request.name),)),
)
# Validate the universe domain.
self._validate_universe_domain()
# Send the request.
rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
[docs] def get_location(
self,
request: Optional[locations_pb2.GetLocationRequest] = None,
*,
retry: OptionalRetry = gapic_v1.method.DEFAULT,
timeout: Union[float, object] = gapic_v1.method.DEFAULT,
metadata: Sequence[Tuple[str, str]] = (),
) -> locations_pb2.Location:
r"""Gets information about a location.
Args:
request (:class:`~.location_pb2.GetLocationRequest`):
The request object. Request message for
`GetLocation` method.
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:
~.location_pb2.Location:
Location object.
"""
# Create or coerce a protobuf request object.
# The request isn't a proto-plus wrapped type,
# so it must be constructed via keyword expansion.
if isinstance(request, dict):
request = locations_pb2.GetLocationRequest(**request)
# Wrap the RPC method; this adds retry and timeout information,
# and friendly error handling.
rpc = self._transport._wrapped_methods[self._transport.get_location]
# Certain fields should be provided within the metadata header;
# add these here.
metadata = tuple(metadata) + (
gapic_v1.routing_header.to_grpc_metadata((("name", request.name),)),
)
# Validate the universe domain.
self._validate_universe_domain()
# Send the request.
response = rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# Done; return the response.
return response
[docs] def list_locations(
self,
request: Optional[locations_pb2.ListLocationsRequest] = None,
*,
retry: OptionalRetry = gapic_v1.method.DEFAULT,
timeout: Union[float, object] = gapic_v1.method.DEFAULT,
metadata: Sequence[Tuple[str, str]] = (),
) -> locations_pb2.ListLocationsResponse:
r"""Lists information about the supported locations for this service.
Args:
request (:class:`~.location_pb2.ListLocationsRequest`):
The request object. Request message for
`ListLocations` method.
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:
~.location_pb2.ListLocationsResponse:
Response message for ``ListLocations`` method.
"""
# Create or coerce a protobuf request object.
# The request isn't a proto-plus wrapped type,
# so it must be constructed via keyword expansion.
if isinstance(request, dict):
request = locations_pb2.ListLocationsRequest(**request)
# Wrap the RPC method; this adds retry and timeout information,
# and friendly error handling.
rpc = self._transport._wrapped_methods[self._transport.list_locations]
# Certain fields should be provided within the metadata header;
# add these here.
metadata = tuple(metadata) + (
gapic_v1.routing_header.to_grpc_metadata((("name", request.name),)),
)
# Validate the universe domain.
self._validate_universe_domain()
# Send the request.
response = rpc(
request,
retry=retry,
timeout=timeout,
metadata=metadata,
)
# Done; return the response.
return response
DEFAULT_CLIENT_INFO = gapic_v1.client_info.ClientInfo(
gapic_version=package_version.__version__
)
__all__ = ("ConversationModelsClient",)
