Class AgentsClient (2.12.0)

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

Service for managing Agents.

Properties

transport

Returns the transport used by the client instance.

Returns
Type	Description
`AgentsTransport`	The transport used by the client instance.

Methods

AgentsClient

AgentsClient(*, credentials: Optional[google.auth.credentials.Credentials] = None, transport: Optional[Union[str, google.cloud.dialogflow_v2.services.agents.transports.base.AgentsTransport]] = 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 agents 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, AgentsTransport]` 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
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.

agent_path

agent_path(project: str)

Returns a fully-qualified agent string.

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.

delete_agent

delete_agent(request: Optional[Union[google.cloud.dialogflow_v2.types.agent.DeleteAgentRequest, 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]] = ())

Deletes the specified agent.

from google.cloud import dialogflow_v2

def sample_delete_agent():
    # Create a client
    client = dialogflow_v2.AgentsClient()

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

    # Make the request
    client.delete_agent(request=request)

Parameters
Name	Description
`request`	`Union[google.cloud.dialogflow_v2.types.DeleteAgentRequest, dict]` The request object. The request message for Agents.DeleteAgent.
`parent`	`str` Required. The project that the agent to delete is associated with. 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.

export_agent

export_agent(request: Optional[Union[google.cloud.dialogflow_v2.types.agent.ExportAgentRequest, 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]] = ())

Exports the specified agent to a ZIP file.

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 empty Struct message <https://developers.google.com/protocol-buffers/docs/reference/google.protobuf#struct>__
response: xref_ExportAgentResponse

from google.cloud import dialogflow_v2

def sample_export_agent():
    # Create a client
    client = dialogflow_v2.AgentsClient()

    # Initialize request argument(s)
    request = dialogflow_v2.ExportAgentRequest(
        parent="parent_value",
        agent_uri="agent_uri_value",
    )

    # Make the request
    operation = client.export_agent(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.ExportAgentRequest, dict]` The request object. The request message for Agents.ExportAgent.
`parent`	`str` Required. The project that the agent to export is associated with. 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
Type	Description
`google.api_core.operation.Operation`	An object representing a long-running operation. The result type for the operation will be ExportAgentResponse The response message for Agents.ExportAgent.

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
`AgentsClient`	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
`AgentsClient`	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
`AgentsClient`	The constructed client.

get_agent

get_agent(request: Optional[Union[google.cloud.dialogflow_v2.types.agent.GetAgentRequest, 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]] = ())

Retrieves the specified agent.

from google.cloud import dialogflow_v2

def sample_get_agent():
    # Create a client
    client = dialogflow_v2.AgentsClient()

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

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

    # Handle the response
    print(response)

Parameters
Name	Description
`request`	`Union[google.cloud.dialogflow_v2.types.GetAgentRequest, dict]` The request object. The request message for Agents.GetAgent.
`parent`	`str` Required. The project that the agent to fetch is associated with. 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

Type Description

google.cloud.dialogflow_v2.types.Agent A Dialogflow agent is a virtual agent that handles conversations with your end-users. It is a natural language understanding module that understands the nuances of human language. Dialogflow translates end-user text or audio during a conversation to structured data that your apps and services can understand. You design and build a Dialogflow agent to handle the types of conversations required for your system. For more information about agents, see the [Agent guide](\ https://cloud.google.com/dialogflow/docs/agents-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 `api_endpoint` and `client_cert_source` properties may be used in this method.

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_validation_result

get_validation_result(request: Optional[Union[google.cloud.dialogflow_v2.types.agent.GetValidationResultRequest, 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]] = ())

Gets agent validation result. Agent validation is performed during training time and is updated automatically when training is completed.

from google.cloud import dialogflow_v2

def sample_get_validation_result():
    # Create a client
    client = dialogflow_v2.AgentsClient()

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

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

    # Handle the response
    print(response)

Parameters
Name	Description
`request`	`Union[google.cloud.dialogflow_v2.types.GetValidationResultRequest, dict]` The request object. The request message for Agents.GetValidationResult.
`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.ValidationResult`	Represents the output of agent validation.

import_agent

import_agent(request: Optional[Union[google.cloud.dialogflow_v2.types.agent.ImportAgentRequest, 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]] = ())

Imports the specified agent from a ZIP file.

Uploads new intents and entity types without deleting the existing ones. Intents and entity types with the same name are replaced with the new versions from xref_ImportAgentRequest. After the import, the imported draft agent will be trained automatically (unless disabled in agent settings). However, once the import is done, training may not be completed yet. Please call xref_TrainAgent and wait for the operation it returns in order to train explicitly.

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 empty Struct message <https://developers.google.com/protocol-buffers/docs/reference/google.protobuf#struct>__
response: An Empty message <https://developers.google.com/protocol-buffers/docs/reference/google.protobuf#empty>__

The operation only tracks when importing is complete, not when it is done training.

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_v2

def sample_import_agent():
    # Create a client
    client = dialogflow_v2.AgentsClient()

    # Initialize request argument(s)
    request = dialogflow_v2.ImportAgentRequest(
        agent_uri="agent_uri_value",
        parent="parent_value",
    )

    # Make the request
    operation = client.import_agent(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.ImportAgentRequest, dict]` The request object. The request message for Agents.ImportAgent.
`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); } The JSON representation for Empty is empty JSON object {}.

parse_agent_path

parse_agent_path(path: str)

Parses a agent path into its component segments.

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.

restore_agent

restore_agent(request: Optional[Union[google.cloud.dialogflow_v2.types.agent.RestoreAgentRequest, 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]] = ())

Restores the specified agent from a ZIP file.

Replaces the current agent version with a new one. All the intents and entity types in the older version are deleted. After the restore, the restored draft agent will be trained automatically (unless disabled in agent settings). However, once the restore is done, training may not be completed yet. Please call xref_TrainAgent and wait for the operation it returns in order to train explicitly.

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 empty Struct message <https://developers.google.com/protocol-buffers/docs/reference/google.protobuf#struct>__
response: An Empty message <https://developers.google.com/protocol-buffers/docs/reference/google.protobuf#empty>__

The operation only tracks when restoring is complete, not when it is done training.

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_v2

def sample_restore_agent():
    # Create a client
    client = dialogflow_v2.AgentsClient()

    # Initialize request argument(s)
    request = dialogflow_v2.RestoreAgentRequest(
        agent_uri="agent_uri_value",
        parent="parent_value",
    )

    # Make the request
    operation = client.restore_agent(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.RestoreAgentRequest, dict]` The request object. The request message for Agents.RestoreAgent.
`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

search_agents

search_agents(request: Optional[Union[google.cloud.dialogflow_v2.types.agent.SearchAgentsRequest, 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 agents.

Since there is at most one conversational agent per project, this method is useful primarily for listing all agents across projects the caller has access to. One can achieve that with a wildcard project collection id "-". Refer to List Sub-Collections <https://cloud.google.com/apis/design/design_patterns#list_sub-collections>__.

from google.cloud import dialogflow_v2

def sample_search_agents():
    # Create a client
    client = dialogflow_v2.AgentsClient()

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

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

    # Handle the response
    for response in page_result:
        print(response)

Parameters
Name	Description
`request`	`Union[google.cloud.dialogflow_v2.types.SearchAgentsRequest, dict]` The request object. The request message for Agents.SearchAgents.
`parent`	`str` Required. The project to list agents from. Format: `projects/<Project ID or '-'>`. 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
Type	Description
`google.cloud.dialogflow_v2.services.agents.pagers.SearchAgentsPager`	The response message for Agents.SearchAgents. Iterating over this object will yield results and resolve additional pages automatically.

set_agent

set_agent(request: Optional[Union[google.cloud.dialogflow_v2.types.agent.SetAgentRequest, dict]] = None, *, agent: Optional[google.cloud.dialogflow_v2.types.agent.Agent] = 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/updates 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_v2

def sample_set_agent():
    # Create a client
    client = dialogflow_v2.AgentsClient()

    # Initialize request argument(s)
    agent = dialogflow_v2.Agent()
    agent.parent = "parent_value"
    agent.display_name = "display_name_value"
    agent.default_language_code = "default_language_code_value"
    agent.time_zone = "time_zone_value"

    request = dialogflow_v2.SetAgentRequest(
        agent=agent,
    )

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

    # Handle the response
    print(response)

Parameters
Name	Description
`request`	`Union[google.cloud.dialogflow_v2.types.SetAgentRequest, dict]` The request object. The request message for Agents.SetAgent.
`agent`	`google.cloud.dialogflow_v2.types.Agent` Required. The agent to update. This corresponds to the `agent` 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

Type Description

train_agent

train_agent(request: Optional[Union[google.cloud.dialogflow_v2.types.agent.TrainAgentRequest, 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]] = ())

Trains 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 empty Struct message <https://developers.google.com/protocol-buffers/docs/reference/google.protobuf#struct>__
response: An Empty 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_v2

def sample_train_agent():
    # Create a client
    client = dialogflow_v2.AgentsClient()

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

    # Make the request
    operation = client.train_agent(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.TrainAgentRequest, dict]` The request object. The request message for Agents.TrainAgent.
`parent`	`str` Required. The project that the agent to train is associated with. 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

Type Description