EntityTypesAsyncClient(*, credentials: Optional[google.auth.credentials.Credentials] = None, transport: Union[str, google.cloud.dialogflow_v2beta1.services.entity_types.transports.base.EntityTypesTransport] = 'grpc_asyncio', 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>)
Service for managing EntityTypes.
Properties
transport
Returns the transport used by the client instance.
Returns | |
---|---|
Type | Description |
EntityTypesTransport | The transport used by the client instance. |
Methods
EntityTypesAsyncClient
EntityTypesAsyncClient(*, credentials: Optional[google.auth.credentials.Credentials] = None, transport: Union[str, google.cloud.dialogflow_v2beta1.services.entity_types.transports.base.EntityTypesTransport] = 'grpc_asyncio', 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 entity types 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 |
Union[str,
The transport to use. If set to None, a transport is chosen automatically. |
client_options |
ClientOptions
Custom options for the client. It won't take effect if a |
Exceptions | |
---|---|
Type | Description |
google.auth.exceptions.MutualTlsChannelError | If mutual TLS transport creation failed for any reason. |
batch_create_entities
batch_create_entities(request: Optional[Union[google.cloud.dialogflow_v2beta1.types.entity_type.BatchCreateEntitiesRequest, dict]] = None, *, parent: Optional[str] = None, entities: Optional[Sequence[google.cloud.dialogflow_v2beta1.types.entity_type.EntityType.Entity]] = None, language_code: 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]] = ())
Creates multiple new entities in the specified entity type.
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
: An emptyStruct message <https://developers.google.com/protocol-buffers/docs/reference/google.protobuf#struct>
__response
: AnEmpty message <https://developers.google.com/protocol-buffers/docs/reference/google.protobuf#empty>
__
Note: You should always train an agent prior to sending it
queries. See the training
documentation <https://cloud.google.com/dialogflow/es/docs/training>
__.
from google.cloud import dialogflow_v2beta1
def sample_batch_create_entities():
# Create a client
client = dialogflow_v2beta1.EntityTypesClient()
# Initialize request argument(s)
entities = dialogflow_v2beta1.Entity()
entities.value = "value_value"
request = dialogflow_v2beta1.BatchCreateEntitiesRequest(
parent="parent_value",
entities=entities,
)
# Make the request
operation = client.batch_create_entities(request=request)
print("Waiting for operation to complete...")
response = operation.result()
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Union[google.cloud.dialogflow_v2beta1.types.BatchCreateEntitiesRequest, dict]
The request object. The request message for EntityTypes.BatchCreateEntities. |
parent |
Required. The name of the entity type to create entities in. Supported formats: - |
entities |
:class:
Required. The entities to create. This corresponds to the |
language_code |
Optional. The language used to access language-specific data. If not specified, the agent's default language is used. For more information, see |
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_async.AsyncOperation | 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); } The JSON representation for Empty is empty JSON object {}. |
batch_delete_entities
batch_delete_entities(request: Optional[Union[google.cloud.dialogflow_v2beta1.types.entity_type.BatchDeleteEntitiesRequest, dict]] = None, *, parent: Optional[str] = None, entity_values: Optional[Sequence[str]] = None, language_code: 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 entities in the specified entity type.
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
: An emptyStruct message <https://developers.google.com/protocol-buffers/docs/reference/google.protobuf#struct>
__response
: AnEmpty message <https://developers.google.com/protocol-buffers/docs/reference/google.protobuf#empty>
__
Note: You should always train an agent prior to sending it
queries. See the training
documentation <https://cloud.google.com/dialogflow/es/docs/training>
__.
from google.cloud import dialogflow_v2beta1
def sample_batch_delete_entities():
# Create a client
client = dialogflow_v2beta1.EntityTypesClient()
# Initialize request argument(s)
request = dialogflow_v2beta1.BatchDeleteEntitiesRequest(
parent="parent_value",
entity_values=['entity_values_value_1', 'entity_values_value_2'],
)
# Make the request
operation = client.batch_delete_entities(request=request)
print("Waiting for operation to complete...")
response = operation.result()
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Union[google.cloud.dialogflow_v2beta1.types.BatchDeleteEntitiesRequest, dict]
The request object. The request message for EntityTypes.BatchDeleteEntities. |
parent |
Required. The name of the entity type to delete entries for. Supported formats: - |
entity_values |
:class:
Required. The reference |
language_code |
Optional. The language used to access language-specific data. If not specified, the agent's default language is used. For more information, see |
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_async.AsyncOperation | 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); } The JSON representation for Empty is empty JSON object {}. |
batch_delete_entity_types
batch_delete_entity_types(request: Optional[Union[google.cloud.dialogflow_v2beta1.types.entity_type.BatchDeleteEntityTypesRequest, dict]] = None, *, parent: Optional[str] = None, entity_type_names: Optional[Sequence[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 entity types in the specified agent.
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
: An emptyStruct message <https://developers.google.com/protocol-buffers/docs/reference/google.protobuf#struct>
__response
: AnEmpty message <https://developers.google.com/protocol-buffers/docs/reference/google.protobuf#empty>
__
Note: You should always train an agent prior to sending it
queries. See the training
documentation <https://cloud.google.com/dialogflow/es/docs/training>
__.
from google.cloud import dialogflow_v2beta1
def sample_batch_delete_entity_types():
# Create a client
client = dialogflow_v2beta1.EntityTypesClient()
# Initialize request argument(s)
request = dialogflow_v2beta1.BatchDeleteEntityTypesRequest(
parent="parent_value",
entity_type_names=['entity_type_names_value_1', 'entity_type_names_value_2'],
)
# Make the request
operation = client.batch_delete_entity_types(request=request)
print("Waiting for operation to complete...")
response = operation.result()
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Union[google.cloud.dialogflow_v2beta1.types.BatchDeleteEntityTypesRequest, dict]
The request object. The request message for EntityTypes.BatchDeleteEntityTypes. |
parent |
Required. The name of the agent to delete all entities types for. Supported formats: - |
entity_type_names |
:class:
Required. The names entity types to delete. All names must point to the same agent as |
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_async.AsyncOperation | 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); } The JSON representation for Empty is empty JSON object {}. |
batch_update_entities
batch_update_entities(request: Optional[Union[google.cloud.dialogflow_v2beta1.types.entity_type.BatchUpdateEntitiesRequest, dict]] = None, *, parent: Optional[str] = None, entities: Optional[Sequence[google.cloud.dialogflow_v2beta1.types.entity_type.EntityType.Entity]] = None, language_code: 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]] = ())
Updates or creates multiple entities in the specified entity type. This method does not affect entities in the entity type that aren't explicitly specified in the request.
Note: You should always train an agent prior to sending it
queries. See the training
documentation <https://cloud.google.com/dialogflow/es/docs/training>
__.
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
: An emptyStruct message <https://developers.google.com/protocol-buffers/docs/reference/google.protobuf#struct>
__response
: AnEmpty message <https://developers.google.com/protocol-buffers/docs/reference/google.protobuf#empty>
__
from google.cloud import dialogflow_v2beta1
def sample_batch_update_entities():
# Create a client
client = dialogflow_v2beta1.EntityTypesClient()
# Initialize request argument(s)
entities = dialogflow_v2beta1.Entity()
entities.value = "value_value"
request = dialogflow_v2beta1.BatchUpdateEntitiesRequest(
parent="parent_value",
entities=entities,
)
# Make the request
operation = client.batch_update_entities(request=request)
print("Waiting for operation to complete...")
response = operation.result()
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Union[google.cloud.dialogflow_v2beta1.types.BatchUpdateEntitiesRequest, dict]
The request object. The request message for EntityTypes.BatchUpdateEntities. |
parent |
Required. The name of the entity type to update or create entities in. Supported formats: - |
entities |
:class:
Required. The entities to update or create. This corresponds to the |
language_code |
Optional. The language used to access language-specific data. If not specified, the agent's default language is used. For more information, see |
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_async.AsyncOperation | 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); } The JSON representation for Empty is empty JSON object {}. |
batch_update_entity_types
batch_update_entity_types(request: Optional[Union[google.cloud.dialogflow_v2beta1.types.entity_type.BatchUpdateEntityTypesRequest, 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]] = ())
Updates/Creates multiple entity types in the specified agent.
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
: An emptyStruct message <https://developers.google.com/protocol-buffers/docs/reference/google.protobuf#struct>
__response
: xref_BatchUpdateEntityTypesResponse
Note: You should always train an agent prior to sending it
queries. See the training
documentation <https://cloud.google.com/dialogflow/es/docs/training>
__.
from google.cloud import dialogflow_v2beta1
def sample_batch_update_entity_types():
# Create a client
client = dialogflow_v2beta1.EntityTypesClient()
# Initialize request argument(s)
request = dialogflow_v2beta1.BatchUpdateEntityTypesRequest(
entity_type_batch_uri="entity_type_batch_uri_value",
parent="parent_value",
)
# Make the request
operation = client.batch_update_entity_types(request=request)
print("Waiting for operation to complete...")
response = operation.result()
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Union[google.cloud.dialogflow_v2beta1.types.BatchUpdateEntityTypesRequest, dict]
The request object. The request message for EntityTypes.BatchUpdateEntityTypes. |
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_async.AsyncOperation | An object representing a long-running operation. The result type for the operation will be BatchUpdateEntityTypesResponse The response message for EntityTypes.BatchUpdateEntityTypes. |
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.
create_entity_type
create_entity_type(request: Optional[Union[google.cloud.dialogflow_v2beta1.types.entity_type.CreateEntityTypeRequest, dict]] = None, *, parent: Optional[str] = None, entity_type: Optional[google.cloud.dialogflow_v2beta1.types.entity_type.EntityType] = None, language_code: 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]] = ())
Creates an entity type in the specified agent.
Note: You should always train an agent prior to sending it
queries. See the training
documentation <https://cloud.google.com/dialogflow/es/docs/training>
__.
from google.cloud import dialogflow_v2beta1
def sample_create_entity_type():
# Create a client
client = dialogflow_v2beta1.EntityTypesClient()
# Initialize request argument(s)
entity_type = dialogflow_v2beta1.EntityType()
entity_type.display_name = "display_name_value"
entity_type.kind = "KIND_REGEXP"
request = dialogflow_v2beta1.CreateEntityTypeRequest(
parent="parent_value",
entity_type=entity_type,
)
# Make the request
response = client.create_entity_type(request=request)
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Union[google.cloud.dialogflow_v2beta1.types.CreateEntityTypeRequest, dict]
The request object. The request message for EntityTypes.CreateEntityType. |
parent |
Required. The agent to create a entity type for. Supported formats: - |
entity_type |
EntityType
Required. The entity type to create. This corresponds to the |
language_code |
Optional. The language used to access language-specific data. If not specified, the agent's default language is used. For more information, see |
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_v2beta1.types.EntityType | Each intent parameter has a type, called the entity type, which dictates exactly how data from an end-user expression is extracted. Dialogflow provides predefined system entities that can match many common types of data. For example, there are system entities for matching dates, times, colors, email addresses, and so on. You can also create your own custom entities for matching custom data. For example, you could define a vegetable entity that can match the types of vegetables available for purchase with a grocery store agent. For more information, see the [Entity guide](\ https://cloud.google.com/dialogflow/docs/entities-overview). |
delete_entity_type
delete_entity_type(request: Optional[Union[google.cloud.dialogflow_v2beta1.types.entity_type.DeleteEntityTypeRequest, 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 entity type.
Note: You should always train an agent prior to sending it
queries. See the training
documentation <https://cloud.google.com/dialogflow/es/docs/training>
__.
from google.cloud import dialogflow_v2beta1
def sample_delete_entity_type():
# Create a client
client = dialogflow_v2beta1.EntityTypesClient()
# Initialize request argument(s)
request = dialogflow_v2beta1.DeleteEntityTypeRequest(
name="name_value",
)
# Make the request
client.delete_entity_type(request=request)
Parameters | |
---|---|
Name | Description |
request |
Union[google.cloud.dialogflow_v2beta1.types.DeleteEntityTypeRequest, dict]
The request object. The request message for EntityTypes.DeleteEntityType. |
name |
Required. The name of the entity type to delete. Supported formats: - |
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. |
entity_type_path
entity_type_path(project: str, entity_type: str)
Returns a fully-qualified entity_type 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 |
EntityTypesAsyncClient | 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 |
EntityTypesAsyncClient | 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 |
EntityTypesAsyncClient | The constructed client. |
get_entity_type
get_entity_type(request: Optional[Union[google.cloud.dialogflow_v2beta1.types.entity_type.GetEntityTypeRequest, dict]] = None, *, name: Optional[str] = None, language_code: 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 entity type.
from google.cloud import dialogflow_v2beta1
def sample_get_entity_type():
# Create a client
client = dialogflow_v2beta1.EntityTypesClient()
# Initialize request argument(s)
request = dialogflow_v2beta1.GetEntityTypeRequest(
name="name_value",
)
# Make the request
response = client.get_entity_type(request=request)
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Union[google.cloud.dialogflow_v2beta1.types.GetEntityTypeRequest, dict]
The request object. The request message for EntityTypes.GetEntityType. |
name |
Required. The name of the entity type. Supported formats: - |
language_code |
Optional. The language used to access language-specific data. If not specified, the agent's default language is used. For more information, see |
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_v2beta1.types.EntityType | Each intent parameter has a type, called the entity type, which dictates exactly how data from an end-user expression is extracted. Dialogflow provides predefined system entities that can match many common types of data. For example, there are system entities for matching dates, times, colors, email addresses, and so on. You can also create your own custom entities for matching custom data. For example, you could define a vegetable entity that can match the types of vegetables available for purchase with a grocery store agent. For more information, see the [Entity guide](\ https://cloud.google.com/dialogflow/docs/entities-overview). |
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 | |
---|---|
Name | Description |
client_options |
google.api_core.client_options.ClientOptions
Custom options for the client. Only the |
Exceptions | |
---|---|
Type | Description |
google.auth.exceptions.MutualTLSChannelError | If any errors happen. |
Returns | |
---|---|
Type | Description |
Tuple[str, Callable[[], Tuple[bytes, bytes]]] | returns the API endpoint and the client cert source to use. |
get_transport_class
get_transport_class()
Returns an appropriate transport class.
list_entity_types
list_entity_types(request: Optional[Union[google.cloud.dialogflow_v2beta1.types.entity_type.ListEntityTypesRequest, dict]] = None, *, parent: Optional[str] = None, language_code: 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 entity types in the specified agent.
from google.cloud import dialogflow_v2beta1
def sample_list_entity_types():
# Create a client
client = dialogflow_v2beta1.EntityTypesClient()
# Initialize request argument(s)
request = dialogflow_v2beta1.ListEntityTypesRequest(
parent="parent_value",
)
# Make the request
page_result = client.list_entity_types(request=request)
# Handle the response
for response in page_result:
print(response)
Parameters | |
---|---|
Name | Description |
request |
Union[google.cloud.dialogflow_v2beta1.types.ListEntityTypesRequest, dict]
The request object. The request message for EntityTypes.ListEntityTypes. |
parent |
Required. The agent to list all entity types from. Supported formats: - |
language_code |
Optional. The language used to access language-specific data. If not specified, the agent's default language is used. For more information, see |
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_v2beta1.services.entity_types.pagers.ListEntityTypesAsyncPager | The response message for EntityTypes.ListEntityTypes. 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_entity_type_path
parse_entity_type_path(path: str)
Parses a entity_type path into its component segments.
update_entity_type
update_entity_type(request: Optional[Union[google.cloud.dialogflow_v2beta1.types.entity_type.UpdateEntityTypeRequest, dict]] = None, *, entity_type: Optional[google.cloud.dialogflow_v2beta1.types.entity_type.EntityType] = None, language_code: Optional[str] = None, update_mask: Optional[google.protobuf.field_mask_pb2.FieldMask] = 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]] = ())
Updates the specified entity type.
Note: You should always train an agent prior to sending it
queries. See the training
documentation <https://cloud.google.com/dialogflow/es/docs/training>
__.
from google.cloud import dialogflow_v2beta1
def sample_update_entity_type():
# Create a client
client = dialogflow_v2beta1.EntityTypesClient()
# Initialize request argument(s)
entity_type = dialogflow_v2beta1.EntityType()
entity_type.display_name = "display_name_value"
entity_type.kind = "KIND_REGEXP"
request = dialogflow_v2beta1.UpdateEntityTypeRequest(
entity_type=entity_type,
)
# Make the request
response = client.update_entity_type(request=request)
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Union[google.cloud.dialogflow_v2beta1.types.UpdateEntityTypeRequest, dict]
The request object. The request message for EntityTypes.UpdateEntityType. |
entity_type |
EntityType
Required. The entity type to update. This corresponds to the |
language_code |
Optional. The language used to access language-specific data. If not specified, the agent's default language is used. For more information, see |
update_mask |
Optional. The mask to control which fields get updated. 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.cloud.dialogflow_v2beta1.types.EntityType | Each intent parameter has a type, called the entity type, which dictates exactly how data from an end-user expression is extracted. Dialogflow provides predefined system entities that can match many common types of data. For example, there are system entities for matching dates, times, colors, email addresses, and so on. You can also create your own custom entities for matching custom data. For example, you could define a vegetable entity that can match the types of vegetables available for purchase with a grocery store agent. For more information, see the [Entity guide](\ https://cloud.google.com/dialogflow/docs/entities-overview). |