ConversationModelsClient(*, credentials: typing.Optional[google.auth.credentials.Credentials] = None, transport: typing.Optional[typing.Union[str, google.cloud.dialogflow_v2.services.conversation_models.transports.base.ConversationModelsTransport, typing.Callable[[...], google.cloud.dialogflow_v2.services.conversation_models.transports.base.ConversationModelsTransport]]] = None, client_options: typing.Optional[typing.Union[google.api_core.client_options.ClientOptions, dict]] = 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.
Properties
api_endpoint
Return the API endpoint used by the client instance.
Returns | |
---|---|
Type | Description |
str |
The API endpoint used by the client instance. |
transport
Returns the transport used by the client instance.
Returns | |
---|---|
Type | Description |
ConversationModelsTransport |
The transport used by the client instance. |
universe_domain
Return the universe domain used by the client instance.
Returns | |
---|---|
Type | Description |
str |
The universe domain used by the client instance. |
Methods
ConversationModelsClient
ConversationModelsClient(*, credentials: typing.Optional[google.auth.credentials.Credentials] = None, transport: typing.Optional[typing.Union[str, google.cloud.dialogflow_v2.services.conversation_models.transports.base.ConversationModelsTransport, typing.Callable[[...], google.cloud.dialogflow_v2.services.conversation_models.transports.base.ConversationModelsTransport]]] = None, client_options: typing.Optional[typing.Union[google.api_core.client_options.ClientOptions, dict]] = 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.
Parameters | |
---|---|
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 |
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 |
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 |
Exceptions | |
---|---|
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: typing.Optional[
google.longrunning.operations_pb2.CancelOperationRequest
] = None,
*,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary.Retry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> None
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
.
Parameters | |
---|---|
Name | Description |
request |
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) -> str
Returns a fully-qualified billing_account string.
common_folder_path
common_folder_path(folder: str) -> str
Returns a fully-qualified folder string.
common_location_path
common_location_path(project: str, location: str) -> str
Returns a fully-qualified location string.
common_organization_path
common_organization_path(organization: str) -> str
Returns a fully-qualified organization string.
common_project_path
common_project_path(project: str) -> str
Returns a fully-qualified project string.
conversation_dataset_path
conversation_dataset_path(
project: str, location: str, conversation_dataset: str
) -> str
Returns a fully-qualified conversation_dataset string.
conversation_model_evaluation_path
conversation_model_evaluation_path(
project: str, conversation_model: str, evaluation: str
) -> str
Returns a fully-qualified conversation_model_evaluation string.
conversation_model_path
conversation_model_path(
project: str, location: str, conversation_model: str
) -> str
Returns a fully-qualified conversation_model string.
create_conversation_model
create_conversation_model(
request: typing.Optional[
typing.Union[
google.cloud.dialogflow_v2.types.conversation_model.CreateConversationModelRequest,
dict,
]
] = None,
*,
parent: typing.Optional[str] = None,
conversation_model: typing.Optional[
google.cloud.dialogflow_v2.types.conversation_model.ConversationModel
] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary.Retry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.api_core.operation.Operation
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
# 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)
Parameters | |
---|---|
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. |
Returns | |
---|---|
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: typing.Optional[
typing.Union[
google.cloud.dialogflow_v2.types.conversation_model.CreateConversationModelEvaluationRequest,
dict,
]
] = None,
*,
parent: typing.Optional[str] = None,
conversation_model_evaluation: typing.Optional[
google.cloud.dialogflow_v2.types.conversation_model.ConversationModelEvaluation
] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary.Retry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.api_core.operation.Operation
Creates evaluation of a conversation model.
# 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)
Parameters | |
---|---|
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. |
Returns | |
---|---|
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: typing.Optional[
typing.Union[
google.cloud.dialogflow_v2.types.conversation_model.DeleteConversationModelRequest,
dict,
]
] = None,
*,
name: typing.Optional[str] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary.Retry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.api_core.operation.Operation
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>
__
# 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)
Parameters | |
---|---|
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. |
Returns | |
---|---|
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: typing.Optional[
typing.Union[
google.cloud.dialogflow_v2.types.conversation_model.DeployConversationModelRequest,
dict,
]
] = None,
*,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary.Retry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.api_core.operation.Operation
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>
__
# 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)
Parameters | |
---|---|
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. |
Returns | |
---|---|
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) -> 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.
Parameter | |
---|---|
Name | Description |
filename |
str
The path to the service account private key json file. |
Returns | |
---|---|
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.
Parameter | |
---|---|
Name | Description |
info |
dict
The service account private key info. |
Returns | |
---|---|
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.
Parameter | |
---|---|
Name | Description |
filename |
str
The path to the service account private key json file. |
Returns | |
---|---|
Type | Description |
ConversationModelsClient |
The constructed client. |
get_conversation_model
get_conversation_model(
request: typing.Optional[
typing.Union[
google.cloud.dialogflow_v2.types.conversation_model.GetConversationModelRequest,
dict,
]
] = None,
*,
name: typing.Optional[str] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary.Retry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.dialogflow_v2.types.conversation_model.ConversationModel
Gets conversation model.
# 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)
Parameters | |
---|---|
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. |
Returns | |
---|---|
Type | Description |
google.cloud.dialogflow_v2.types.ConversationModel |
Represents a conversation model. |
get_conversation_model_evaluation
get_conversation_model_evaluation(
request: typing.Optional[
typing.Union[
google.cloud.dialogflow_v2.types.conversation_model.GetConversationModelEvaluationRequest,
dict,
]
] = None,
*,
name: typing.Optional[str] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary.Retry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.dialogflow_v2.types.conversation_model.ConversationModelEvaluation
Gets an evaluation of conversation model.
# 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)
Parameters | |
---|---|
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. |
Returns | |
---|---|
Type | Description |
google.cloud.dialogflow_v2.types.ConversationModelEvaluation |
Represents evaluation result of a conversation model. |
get_location
get_location(
request: