ConversationModelsClient(*, credentials: Optional[google.auth.credentials.Credentials] = None, transport: Optional[Union[str, google.cloud.dialogflow_v2.services.conversation_models.transports.base.ConversationModelsTransport]] = None, client_options: Optional[google.api_core.client_options.ClientOptions] = None, client_info: google.api_core.gapic_v1.client_info.ClientInfo = <google.api_core.gapic_v1.client_info.ClientInfo object>)
Manages a collection of models for human agent assistant.
Inheritance
builtins.object > ConversationModelsClientProperties
transport
Returns the transport used by the client instance.
Type | Description |
ConversationModelsTransport | The transport used by the client instance. |
Methods
ConversationModelsClient
ConversationModelsClient(*, credentials: Optional[google.auth.credentials.Credentials] = None, transport: Optional[Union[str, google.cloud.dialogflow_v2.services.conversation_models.transports.base.ConversationModelsTransport]] = None, client_options: Optional[google.api_core.client_options.ClientOptions] = None, client_info: google.api_core.gapic_v1.client_info.ClientInfo = <google.api_core.gapic_v1.client_info.ClientInfo object>)
Instantiates the conversation models client.
Name | Description |
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 |
Union[str, ConversationModelsTransport]
The transport to use. If set to None, a transport is chosen automatically. |
client_options |
google.api_core.client_options.ClientOptions
Custom options for the client. It won't take effect if a |
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 |
Type | Description |
google.auth.exceptions.MutualTLSChannelError | If mutual TLS transport creation failed for any reason. |
__exit__
__exit__(type, value, traceback)
Releases underlying transport's resources.
cancel_operation
cancel_operation(request: Optional[google.longrunning.operations_pb2.CancelOperationRequest] = None, *, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
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
.
Name | Description |
request |
`.operations_pb2.CancelOperationRequest`
The request object. Request message for |
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. |
common_billing_account_path
common_billing_account_path(billing_account: str)
Returns a fully-qualified billing_account string.
common_folder_path
common_folder_path(folder: str)
Returns a fully-qualified folder string.
common_location_path
common_location_path(project: str, location: str)
Returns a fully-qualified location string.
common_organization_path
common_organization_path(organization: str)
Returns a fully-qualified organization string.
common_project_path
common_project_path(project: str)
Returns a fully-qualified project string.
conversation_dataset_path
conversation_dataset_path(project: str, location: str, conversation_dataset: str)
Returns a fully-qualified conversation_dataset string.
conversation_model_evaluation_path
conversation_model_evaluation_path(
project: str, conversation_model: str, evaluation: str
)
Returns a fully-qualified conversation_model_evaluation string.
conversation_model_path
conversation_model_path(project: str, location: str, conversation_model: str)
Returns a fully-qualified conversation_model string.
create_conversation_model
create_conversation_model(request: Optional[Union[google.cloud.dialogflow_v2.types.conversation_model.CreateConversationModelRequest, dict]] = None, *, parent: Optional[str] = None, conversation_model: Optional[google.cloud.dialogflow_v2.types.conversation_model.ConversationModel] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
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
: xref_CreateConversationModelOperationMetadataresponse
: xref_ConversationModel
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)
Name | Description |
request |
Union[google.cloud.dialogflow_v2.types.CreateConversationModelRequest, dict]
The request object. The request message for ConversationModels.CreateConversationModel |
parent |
str
The project to create conversation model for. Format: |
conversation_model |
google.cloud.dialogflow_v2.types.ConversationModel
Required. The conversation model to create. This corresponds to the |
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. |
Type | Description |
google.api_core.operation.Operation | An object representing a long-running operation. The result type for the operation will be ConversationModel Represents a conversation model. |
create_conversation_model_evaluation
create_conversation_model_evaluation(request: Optional[Union[google.cloud.dialogflow_v2.types.conversation_model.CreateConversationModelEvaluationRequest, dict]] = None, *, parent: Optional[str] = None, conversation_model_evaluation: Optional[google.cloud.dialogflow_v2.types.conversation_model.ConversationModelEvaluation] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Creates evaluation of a conversation model.
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)
Name | Description |
request |
Union[google.cloud.dialogflow_v2.types.CreateConversationModelEvaluationRequest, dict]
The request object. The request message for ConversationModels.CreateConversationModelEvaluation |
parent |
str
Required. The conversation model resource name. Format: |
conversation_model_evaluation |
google.cloud.dialogflow_v2.types.ConversationModelEvaluation
Required. The conversation model evaluation to be created. This corresponds to the |
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. |
Type | Description |
google.api_core.operation.Operation | An object representing a long-running operation. The result type for the operation will be ConversationModelEvaluation Represents evaluation result of a conversation model. |
delete_conversation_model
delete_conversation_model(request: Optional[Union[google.cloud.dialogflow_v2.types.conversation_model.DeleteConversationModelRequest, dict]] = None, *, name: Optional[str] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
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
: xref_DeleteConversationModelOperationMetadataresponse
: AnEmpty message <https://developers.google.com/protocol-buffers/docs/reference/google.protobuf#empty>
__
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)
Name | Description |
request |
Union[google.cloud.dialogflow_v2.types.DeleteConversationModelRequest, dict]
The request object. The request message for ConversationModels.DeleteConversationModel |
name |
str
Required. The conversation model to delete. Format: |
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. |
Type | Description |
google.api_core.operation.Operation | An object representing a long-running operation. The result type for the operation will be `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); } |
deploy_conversation_model
deploy_conversation_model(request: Optional[Union[google.cloud.dialogflow_v2.types.conversation_model.DeployConversationModelRequest, dict]] = None, *, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
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
: xref_DeployConversationModelOperationMetadataresponse
: AnEmpty message <https://developers.google.com/protocol-buffers/docs/reference/google.protobuf#empty>
__
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)
Name | Description |
request |
Union[google.cloud.dialogflow_v2.types.DeployConversationModelRequest, dict]
The request object. The request message for 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. |
Type | Description |
google.api_core.operation.Operation | An object representing a long-running operation. The result type for the operation will be `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); } |
document_path
document_path(project: str, knowledge_base: str, document: str)
Returns a fully-qualified document string.
from_service_account_file
from_service_account_file(filename: str, *args, **kwargs)
Creates an instance of this client using the provided credentials file.
Name | Description |
filename |
str
The path to the service account private key json file. |
Type | Description |
ConversationModelsClient | The constructed client. |
from_service_account_info
from_service_account_info(info: dict, *args, **kwargs)
Creates an instance of this client using the provided credentials info.
Name | Description |
info |
dict
The service account private key info. |
Type | Description |
ConversationModelsClient | The constructed client. |
from_service_account_json
from_service_account_json(filename: str, *args, **kwargs)
Creates an instance of this client using the provided credentials file.
Name | Description |
filename |
str
The path to the service account private key json file. |
Type | Description |
ConversationModelsClient | The constructed client. |
get_conversation_model
get_conversation_model(request: Optional[Union[google.cloud.dialogflow_v2.types.conversation_model.GetConversationModelRequest, dict]] = None, *, name: Optional[str] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Gets conversation model.
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)
Name | Description |
request |
Union[google.cloud.dialogflow_v2.types.GetConversationModelRequest, dict]
The request object. The request message for ConversationModels.GetConversationModel |
name |
str
Required. The conversation model to retrieve. Format: |
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. |
Type | Description |
google.cloud.dialogflow_v2.types.ConversationModel | Represents a conversation model. |
get_conversation_model_evaluation
get_conversation_model_evaluation(request: Optional[Union[google.cloud.dialogflow_v2.types.conversation_model.GetConversationModelEvaluationRequest, dict]] = None, *, name: Optional[str] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Gets an evaluation of conversation model.
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)
Name | Description |
request |
Union[google.cloud.dialogflow_v2.types.GetConversationModelEvaluationRequest, dict]
The request object. The request message for ConversationModels.GetConversationModelEvaluation |
name |
str
Required. The conversation model evaluation resource name. Format: |
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. |
Type | Description |
google.cloud.dialogflow_v2.types.ConversationModelEvaluation | Represents evaluation result of a conversation model. |
get_location
get_location(request: Optional[google.cloud.location.locations_pb2.GetLocationRequest] = None, *, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Gets information about a location.
Name | Description |
request |
`.location_pb2.GetLocationRequest`
The request object. Request message for |
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. |
Type | Description |
`.location_pb2.Location` | Location object. |
get_mtls_endpoint_and_cert_source
get_mtls_endpoint_and_cert_source(
client_options: Optional[google.api_core.client_options.ClientOptions] = None,
)
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 variabel 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.
Name | Description |
client_options |
google.api_core.client_options.ClientOptions
Custom options for the client. Only the |
Type | Description |
google.auth.exceptions.MutualTLSChannelError | If any errors happen. |
Type | Description |
Tuple[str, Callable[[], Tuple[bytes, bytes]]] | returns the API endpoint and the client cert source to use. |
get_operation
get_operation(request: Optional[google.longrunning.operations_pb2.GetOperationRequest] = None, *, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Gets the latest state of a long-running operation.
Name | Description |
request |
`.operations_pb2.GetOperationRequest`
The request object. Request message for |
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. |
Type | Description |
`.operations_pb2.Operation` | An ``Operation`` object. |
list_conversation_model_evaluations
list_conversation_model_evaluations(request: Optional[Union[google.cloud.dialogflow_v2.types.conversation_model.ListConversationModelEvaluationsRequest, dict]] = None, *, parent: Optional[str] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Lists evaluations of a conversation model.
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)
Name | Description |
request |
Union[google.cloud.dialogflow_v2.types.ListConversationModelEvaluationsRequest, dict]
The request object. The request message for ConversationModels.ListConversationModelEvaluations |
parent |
str
Required. The conversation model resource name. Format: |
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. |
Type | Description |
google.cloud.dialogflow_v2.services.conversation_models.pagers.ListConversationModelEvaluationsPager | The response message for ConversationModels.ListConversationModelEvaluations Iterating over this object will yield results and resolve additional pages automatically. |
list_conversation_models
list_conversation_models(request: Optional[Union[google.cloud.dialogflow_v2.types.conversation_model.ListConversationModelsRequest, dict]] = None, *, parent: Optional[str] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Lists conversation models.
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)
Name | Description |
request |
Union[google.cloud.dialogflow_v2.types.ListConversationModelsRequest, dict]
The request object. The request message for ConversationModels.ListConversationModels |
parent |
str
Required. The project to list all conversation models for. Format: |
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. |
Type | Description |
google.cloud.dialogflow_v2.services.conversation_models.pagers.ListConversationModelsPager | The response message for ConversationModels.ListConversationModels Iterating over this object will yield results and resolve additional pages automatically. |
list_locations
list_locations(request: Optional[google.cloud.location.locations_pb2.ListLocationsRequest] = None, *, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Lists information about the supported locations for this service.
Name | Description |
request |
`.location_pb2.ListLocationsRequest`
The request object. Request message for |
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. |
Type | Description |
`.location_pb2.ListLocationsResponse` | Response message for ``ListLocations`` method. |
list_operations
list_operations(request: Optional[google.longrunning.operations_pb2.ListOperationsRequest] = None, *, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Lists operations that match the specified filter in the request.
Name | Description |
request |
`.operations_pb2.ListOperationsRequest`
The request object. Request message for |
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. |
Type | Description |
`.operations_pb2.ListOperationsResponse` | Response message for ``ListOperations`` method. |
parse_common_billing_account_path
parse_common_billing_account_path(path: str)
Parse a billing_account path into its component segments.
parse_common_folder_path
parse_common_folder_path(path: str)
Parse a folder path into its component segments.
parse_common_location_path
parse_common_location_path(path: str)
Parse a location path into its component segments.
parse_common_organization_path
parse_common_organization_path(path: str)
Parse a organization path into its component segments.
parse_common_project_path
parse_common_project_path(path: str)
Parse a project path into its component segments.
parse_conversation_dataset_path
parse_conversation_dataset_path(path: str)
Parses a conversation_dataset path into its component segments.
parse_conversation_model_evaluation_path
parse_conversation_model_evaluation_path(path: str)
Parses a conversation_model_evaluation path into its component segments.
parse_conversation_model_path
parse_conversation_model_path(path: str)
Parses a conversation_model path into its component segments.
parse_document_path
parse_document_path(path: str)
Parses a document path into its component segments.
undeploy_conversation_model
undeploy_conversation_model(request: Optional[Union[google.cloud.dialogflow_v2.types.conversation_model.UndeployConversationModelRequest, dict]] = None, *, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
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
: xref_UndeployConversationModelOperationMetadataresponse
: AnEmpty message <https://developers.google.com/protocol-buffers/docs/reference/google.protobuf#empty>
__
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)
Name | Description |
request |
Union[google.cloud.dialogflow_v2.types.UndeployConversationModelRequest, dict]
The request object. The request message for 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. |
Type | Description |
google.api_core.operation.Operation | An object representing a long-running operation. The result type for the operation will be `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); } |