Class ConversationDatasetsClient (2.13.0)

ConversationDatasetsClient(*, credentials: Optional[google.auth.credentials.Credentials] = None, transport: Optional[Union[str, google.cloud.dialogflow_v2.services.conversation_datasets.transports.base.ConversationDatasetsTransport]] = 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>)

Conversation datasets. Conversation datasets contain raw conversation files and their customizable metadata that can be used for model training.

Properties

transport

Returns the transport used by the client instance.

Returns
TypeDescription
ConversationDatasetsTransportThe transport used by the client instance.

Methods

ConversationDatasetsClient

ConversationDatasetsClient(*, credentials: Optional[google.auth.credentials.Credentials] = None, transport: Optional[Union[str, google.cloud.dialogflow_v2.services.conversation_datasets.transports.base.ConversationDatasetsTransport]] = 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 datasets client.

Parameters
NameDescription
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, ConversationDatasetsTransport]

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 transport instance is provided. (1) The api_endpoint property can be used to override the default endpoint provided by the client. GOOGLE_API_USE_MTLS_ENDPOINT environment variable can also be used to override the endpoint: "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). However, the api_endpoint property takes precedence if provided. (2) If GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable is "true", then the client_cert_source property can be used to provide client certificate for mutual TLS 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.

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.

Exceptions
TypeDescription
google.auth.exceptions.MutualTLSChannelErrorIf mutual TLS transport creation failed for any reason.

__exit__

__exit__(type, value, traceback)

Releases underlying transport's resources.

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.

create_conversation_dataset

create_conversation_dataset(request: Optional[Union[google.cloud.dialogflow_v2.types.conversation_dataset.CreateConversationDatasetRequest, dict]] = None, *, parent: Optional[str] = None, conversation_dataset: Optional[google.cloud.dialogflow_v2.types.conversation_dataset.ConversationDataset] = 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 new conversation dataset.

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_CreateConversationDatasetOperationMetadata
  • response: xref_ConversationDataset
from google.cloud import dialogflow_v2

def sample_create_conversation_dataset():
    # Create a client
    client = dialogflow_v2.ConversationDatasetsClient()

    # Initialize request argument(s)
    conversation_dataset = dialogflow_v2.ConversationDataset()
    conversation_dataset.display_name = "display_name_value"

    request = dialogflow_v2.CreateConversationDatasetRequest(
        parent="parent_value",
        conversation_dataset=conversation_dataset,
    )

    # Make the request
    operation = client.create_conversation_dataset(request=request)

    print("Waiting for operation to complete...")

    response = operation.result()

    # Handle the response
    print(response)
Parameters
NameDescription
request Union[google.cloud.dialogflow_v2.types.CreateConversationDatasetRequest, dict]

The request object. The request message for ConversationDatasets.CreateConversationDataset.

parent str

Required. The project to create conversation dataset for. Format: projects/ This corresponds to the parent field on the request instance; if request is provided, this should not be set.

conversation_dataset google.cloud.dialogflow_v2.types.ConversationDataset

Required. The conversation dataset to create. This corresponds to the conversation_dataset 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
TypeDescription
google.api_core.operation.OperationAn object representing a long-running operation. The result type for the operation will be ConversationDataset Represents a conversation dataset that a user imports raw data into. The data inside ConversationDataset can not be changed after ImportConversationData finishes (and calling ImportConversationData on a dataset that already has data is not allowed).

delete_conversation_dataset

delete_conversation_dataset(request: Optional[Union[google.cloud.dialogflow_v2.types.conversation_dataset.DeleteConversationDatasetRequest, 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 the specified conversation dataset.

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_DeleteConversationDatasetOperationMetadata
  • response: An Empty message <https://developers.google.com/protocol-buffers/docs/reference/google.protobuf#empty>__
from google.cloud import dialogflow_v2

def sample_delete_conversation_dataset():
    # Create a client
    client = dialogflow_v2.ConversationDatasetsClient()

    # Initialize request argument(s)
    request = dialogflow_v2.DeleteConversationDatasetRequest(
        name="name_value",
    )

    # Make the request
    operation = client.delete_conversation_dataset(request=request)

    print("Waiting for operation to complete...")

    response = operation.result()

    # Handle the response
    print(response)
Parameters
NameDescription
request Union[google.cloud.dialogflow_v2.types.DeleteConversationDatasetRequest, dict]

The request object. The request message for ConversationDatasets.DeleteConversationDataset.

name str

Required. The conversation dataset to delete. Format: projects/ 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
TypeDescription
google.api_core.operation.OperationAn 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); } The JSON representation for Empty is empty JSON object {}.

from_service_account_file

from_service_account_file(filename: str, *args, **kwargs)

Creates an instance of this client using the provided credentials file.

Parameter
NameDescription
filename str

The path to the service account private key json file.

Returns
TypeDescription
ConversationDatasetsClientThe 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
NameDescription
info dict

The service account private key info.

Returns
TypeDescription
ConversationDatasetsClientThe 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
NameDescription
filename str

The path to the service account private key json file.

Returns
TypeDescription
ConversationDatasetsClientThe constructed client.

get_conversation_dataset

get_conversation_dataset(request: Optional[Union[google.cloud.dialogflow_v2.types.conversation_dataset.GetConversationDatasetRequest, 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]] = ())

Retrieves the specified conversation dataset.

from google.cloud import dialogflow_v2

def sample_get_conversation_dataset():
    # Create a client
    client = dialogflow_v2.ConversationDatasetsClient()

    # Initialize request argument(s)
    request = dialogflow_v2.GetConversationDatasetRequest(
        name="name_value",
    )

    # Make the request
    response = client.get_conversation_dataset(request=request)

    # Handle the response
    print(response)
Parameters
NameDescription
request Union[google.cloud.dialogflow_v2.types.GetConversationDatasetRequest, dict]

The request object. The request message for ConversationDatasets.GetConversationDataset.

name str

Required. The conversation dataset to retrieve. Format: projects/ 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
TypeDescription
google.cloud.dialogflow_v2.types.ConversationDatasetRepresents a conversation dataset that a user imports raw data into. The data inside ConversationDataset can not be changed after ImportConversationData finishes (and calling ImportConversationData on a dataset that already has data is not allowed).

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.

Parameter
NameDescription
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.

Exceptions
TypeDescription
google.auth.exceptions.MutualTLSChannelErrorIf any errors happen.
Returns
TypeDescription
Tuple[str, Callable[[], Tuple[bytes, bytes]]]returns the API endpoint and the client cert source to use.

import_conversation_data

import_conversation_data(request: Optional[Union[google.cloud.dialogflow_v2.types.conversation_dataset.ImportConversationDataRequest, 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]] = ())

Import data into the specified conversation dataset. Note that it is not allowed to import data to a conversation dataset that already has data in it.

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_ImportConversationDataOperationMetadata
  • response: xref_ImportConversationDataOperationResponse
from google.cloud import dialogflow_v2

def sample_import_conversation_data():
    # Create a client
    client = dialogflow_v2.ConversationDatasetsClient()

    # Initialize request argument(s)
    input_config = dialogflow_v2.InputConfig()
    input_config.gcs_source.uris = ['uris_value_1', 'uris_value_2']

    request = dialogflow_v2.ImportConversationDataRequest(
        name="name_value",
        input_config=input_config,
    )

    # Make the request
    operation = client.import_conversation_data(request=request)

    print("Waiting for operation to complete...")

    response = operation.result()

    # Handle the response
    print(response)
Parameters
NameDescription
request Union[google.cloud.dialogflow_v2.types.ImportConversationDataRequest, dict]

The request object. The request message for ConversationDatasets.ImportConversationData.

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
TypeDescription
google.api_core.operation.OperationAn object representing a long-running operation. The result type for the operation will be ImportConversationDataOperationResponse Response used for ConversationDatasets.ImportConversationData long running operation.

list_conversation_datasets

list_conversation_datasets(request: Optional[Union[google.cloud.dialogflow_v2.types.conversation_dataset.ListConversationDatasetsRequest, 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]] = ())

Returns the list of all conversation datasets in the specified project and location.

from google.cloud import dialogflow_v2

def sample_list_conversation_datasets():
    # Create a client
    client = dialogflow_v2.ConversationDatasetsClient()

    # Initialize request argument(s)
    request = dialogflow_v2.ListConversationDatasetsRequest(
        parent="parent_value",
    )

    # Make the request
    page_result = client.list_conversation_datasets(request=request)

    # Handle the response
    for response in page_result:
        print(response)
Parameters
NameDescription
request Union[google.cloud.dialogflow_v2.types.ListConversationDatasetsRequest, dict]

The request object. The request message for ConversationDatasets.ListConversationDatasets.

parent str

Required. The project and location name to list all conversation datasets for. Format: projects/ 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
TypeDescription
google.cloud.dialogflow_v2.services.conversation_datasets.pagers.ListConversationDatasetsPagerThe response message for ConversationDatasets.ListConversationDatasets. Iterating over this object will yield results and resolve additional pages automatically.

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.