Returns the examples Resource.
Returns the versions Resource.
Close httplib2 connections.
create(parent, body=None, x__xgafv=None)
Creates a playbook in a specified agent.
Deletes a specified playbook.
export(name, body=None, x__xgafv=None)
Exports the specified playbook to a binary file. Note that resources (e.g. examples, tools) that the playbook references will also be exported.
Retrieves the specified Playbook.
import_(parent, body=None, x__xgafv=None)
Imports the specified playbook to the specified agent from a binary file.
list(parent, pageSize=None, pageToken=None, x__xgafv=None)
Returns a list of playbooks in the specified agent.
Retrieves the next page of results.
patch(name, body=None, updateMask=None, x__xgafv=None)
Updates the specified Playbook.
close()
Close httplib2 connections.
create(parent, body=None, x__xgafv=None)
Creates a playbook in a specified agent.
Args:
parent: string, Required. The agent to create a playbook for. Format: `projects//locations//agents/`. (required)
body: object, The request body.
The object takes the form of:
{ # Playbook is the basic building block to instruct the LLM how to execute a certain task. A playbook consists of a goal to accomplish, an optional list of step by step instructions (the step instruction may refers to name of the custom or default plugin tools to use) to perform the task, a list of contextual input data to be passed in at the beginning of the invoked, and a list of output parameters to store the playbook result.
"createTime": "A String", # Output only. The timestamp of initial playbook creation.
"displayName": "A String", # Required. The human-readable name of the playbook, unique within an agent.
"goal": "A String", # Required. High level description of the goal the playbook intend to accomplish.
"inputParameterDefinitions": [ # Optional. Defined structured input parameters for this playbook.
{ # Defines the properties of a parameter. Used to define parameters used in the agent and the input / output parameters for each fulfillment.
"description": "A String", # Human-readable description of the parameter. Limited to 300 characters.
"name": "A String", # Required. Name of parameter.
"type": "A String", # Type of parameter.
"typeSchema": { # Encapsulates different type schema variations: either a reference to an a schema that's already defined by a tool, or an inline definition. # Optional. Type schema of parameter.
"inlineSchema": { # A type schema object that's specified inline. # Set if this is an inline schema definition.
"items": # Object with schema name: GoogleCloudDialogflowCxV3beta1TypeSchema # Schema of the elements if this is an ARRAY type.
"type": "A String", # Data type of the schema.
},
"schemaReference": { # A reference to the schema of an existing tool. # Set if this is a schema reference.
"schema": "A String", # The name of the schema.
"tool": "A String", # The tool that contains this schema definition. Format: `projects//locations//agents//tools/`.
},
},
},
],
"instruction": { # Message of the Instruction of the playbook. # Instruction to accomplish target goal.
"steps": [ # Ordered list of step by step execution instructions to accomplish target goal.
{ # Message of single step execution.
"steps": [ # Sub-processing needed to execute the current step.
# Object with schema name: GoogleCloudDialogflowCxV3beta1PlaybookStep
],
"text": "A String", # Step instruction in text format.
},
],
},
"llmModelSettings": { # Settings for LLM models. # Optional. Llm model settings for the playbook.
"model": "A String", # The selected LLM model.
"promptText": "A String", # The custom prompt to use.
},
"name": "A String", # The unique identifier of the playbook. Format: `projects//locations//agents//playbooks/`.
"outputParameterDefinitions": [ # Optional. Defined structured output parameters for this playbook.
{ # Defines the properties of a parameter. Used to define parameters used in the agent and the input / output parameters for each fulfillment.
"description": "A String", # Human-readable description of the parameter. Limited to 300 characters.
"name": "A String", # Required. Name of parameter.
"type": "A String", # Type of parameter.
"typeSchema": { # Encapsulates different type schema variations: either a reference to an a schema that's already defined by a tool, or an inline definition. # Optional. Type schema of parameter.
"inlineSchema": { # A type schema object that's specified inline. # Set if this is an inline schema definition.
"items": # Object with schema name: GoogleCloudDialogflowCxV3beta1TypeSchema # Schema of the elements if this is an ARRAY type.
"type": "A String", # Data type of the schema.
},
"schemaReference": { # A reference to the schema of an existing tool. # Set if this is a schema reference.
"schema": "A String", # The name of the schema.
"tool": "A String", # The tool that contains this schema definition. Format: `projects//locations//agents//tools/`.
},
},
},
],
"referencedFlows": [ # Output only. The resource name of flows referenced by the current playbook in the instructions.
"A String",
],
"referencedPlaybooks": [ # Output only. The resource name of other playbooks referenced by the current playbook in the instructions.
"A String",
],
"referencedTools": [ # Optional. The resource name of tools referenced by the current playbook in the instructions. If not provided explicitly, they are will be implied using the tool being referenced in goal and steps.
"A String",
],
"tokenCount": "A String", # Output only. Estimated number of tokes current playbook takes when sent to the LLM.
"updateTime": "A String", # Output only. Last time the playbook version was updated.
}
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # Playbook is the basic building block to instruct the LLM how to execute a certain task. A playbook consists of a goal to accomplish, an optional list of step by step instructions (the step instruction may refers to name of the custom or default plugin tools to use) to perform the task, a list of contextual input data to be passed in at the beginning of the invoked, and a list of output parameters to store the playbook result.
"createTime": "A String", # Output only. The timestamp of initial playbook creation.
"displayName": "A String", # Required. The human-readable name of the playbook, unique within an agent.
"goal": "A String", # Required. High level description of the goal the playbook intend to accomplish.
"inputParameterDefinitions": [ # Optional. Defined structured input parameters for this playbook.
{ # Defines the properties of a parameter. Used to define parameters used in the agent and the input / output parameters for each fulfillment.
"description": "A String", # Human-readable description of the parameter. Limited to 300 characters.
"name": "A String", # Required. Name of parameter.
"type": "A String", # Type of parameter.
"typeSchema": { # Encapsulates different type schema variations: either a reference to an a schema that's already defined by a tool, or an inline definition. # Optional. Type schema of parameter.
"inlineSchema": { # A type schema object that's specified inline. # Set if this is an inline schema definition.
"items": # Object with schema name: GoogleCloudDialogflowCxV3beta1TypeSchema # Schema of the elements if this is an ARRAY type.
"type": "A String", # Data type of the schema.
},
"schemaReference": { # A reference to the schema of an existing tool. # Set if this is a schema reference.
"schema": "A String", # The name of the schema.
"tool": "A String", # The tool that contains this schema definition. Format: `projects//locations//agents//tools/`.
},
},
},
],
"instruction": { # Message of the Instruction of the playbook. # Instruction to accomplish target goal.
"steps": [ # Ordered list of step by step execution instructions to accomplish target goal.
{ # Message of single step execution.
"steps": [ # Sub-processing needed to execute the current step.
# Object with schema name: GoogleCloudDialogflowCxV3beta1PlaybookStep
],
"text": "A String", # Step instruction in text format.
},
],
},
"llmModelSettings": { # Settings for LLM models. # Optional. Llm model settings for the playbook.
"model": "A String", # The selected LLM model.
"promptText": "A String", # The custom prompt to use.
},
"name": "A String", # The unique identifier of the playbook. Format: `projects//locations//agents//playbooks/`.
"outputParameterDefinitions": [ # Optional. Defined structured output parameters for this playbook.
{ # Defines the properties of a parameter. Used to define parameters used in the agent and the input / output parameters for each fulfillment.
"description": "A String", # Human-readable description of the parameter. Limited to 300 characters.
"name": "A String", # Required. Name of parameter.
"type": "A String", # Type of parameter.
"typeSchema": { # Encapsulates different type schema variations: either a reference to an a schema that's already defined by a tool, or an inline definition. # Optional. Type schema of parameter.
"inlineSchema": { # A type schema object that's specified inline. # Set if this is an inline schema definition.
"items": # Object with schema name: GoogleCloudDialogflowCxV3beta1TypeSchema # Schema of the elements if this is an ARRAY type.
"type": "A String", # Data type of the schema.
},
"schemaReference": { # A reference to the schema of an existing tool. # Set if this is a schema reference.
"schema": "A String", # The name of the schema.
"tool": "A String", # The tool that contains this schema definition. Format: `projects//locations//agents//tools/`.
},
},
},
],
"referencedFlows": [ # Output only. The resource name of flows referenced by the current playbook in the instructions.
"A String",
],
"referencedPlaybooks": [ # Output only. The resource name of other playbooks referenced by the current playbook in the instructions.
"A String",
],
"referencedTools": [ # Optional. The resource name of tools referenced by the current playbook in the instructions. If not provided explicitly, they are will be implied using the tool being referenced in goal and steps.
"A String",
],
"tokenCount": "A String", # Output only. Estimated number of tokes current playbook takes when sent to the LLM.
"updateTime": "A String", # Output only. Last time the playbook version was updated.
}
delete(name, x__xgafv=None)
Deletes a specified playbook.
Args:
name: string, Required. The name of the playbook to delete. Format: `projects//locations//agents//playbooks/`. (required)
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # 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); }
}
export(name, body=None, x__xgafv=None)
Exports the specified playbook to a binary file. Note that resources (e.g. examples, tools) that the playbook references will also be exported.
Args:
name: string, Required. The name of the playbook to export. Format: `projects//locations//agents//playbooks/`. (required)
body: object, The request body.
The object takes the form of:
{ # The request message for Playbooks.ExportPlaybook.
"dataFormat": "A String", # Optional. The data format of the exported agent. If not specified, `BLOB` is assumed.
"playbookUri": "A String", # Optional. The [Google Cloud Storage](https://cloud.google.com/storage/docs/) URI to export the playbook to. The format of this URI must be `gs:///`. If left unspecified, the serialized playbook is returned inline. Dialogflow performs a write operation for the Cloud Storage object on the caller's behalf, so your request authentication must have write permissions for the object. For more information, see [Dialogflow access control](https://cloud.google.com/dialogflow/cx/docs/concept/access-control#storage).
}
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # This resource represents a long-running operation that is the result of a network API call.
"done": True or False, # If the value is `false`, it means the operation is still in progress. If `true`, the operation is completed, and either `error` or `response` is available.
"error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # The error result of the operation in case of failure or cancellation.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
"message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
},
"metadata": { # Service-specific metadata associated with the operation. It typically contains progress information and common metadata such as create time. Some services might not provide such metadata. Any method that returns a long-running operation should document the metadata type, if any.
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
"name": "A String", # The server-assigned name, which is only unique within the same service that originally returns it. If you use the default HTTP mapping, the `name` should be a resource name ending with `operations/{unique_id}`.
"response": { # The normal, successful response of the operation. If the original method returns no data on success, such as `Delete`, the response is `google.protobuf.Empty`. If the original method is standard `Get`/`Create`/`Update`, the response should be the resource. For other methods, the response should have the type `XxxResponse`, where `Xxx` is the original method name. For example, if the original method name is `TakeSnapshot()`, the inferred response type is `TakeSnapshotResponse`.
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
}
get(name, x__xgafv=None)
Retrieves the specified Playbook.
Args:
name: string, Required. The name of the playbook. Format: `projects//locations//agents//playbooks/`. (required)
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # Playbook is the basic building block to instruct the LLM how to execute a certain task. A playbook consists of a goal to accomplish, an optional list of step by step instructions (the step instruction may refers to name of the custom or default plugin tools to use) to perform the task, a list of contextual input data to be passed in at the beginning of the invoked, and a list of output parameters to store the playbook result.
"createTime": "A String", # Output only. The timestamp of initial playbook creation.
"displayName": "A String", # Required. The human-readable name of the playbook, unique within an agent.
"goal": "A String", # Required. High level description of the goal the playbook intend to accomplish.
"inputParameterDefinitions": [ # Optional. Defined structured input parameters for this playbook.
{ # Defines the properties of a parameter. Used to define parameters used in the agent and the input / output parameters for each fulfillment.
"description": "A String", # Human-readable description of the parameter. Limited to 300 characters.
"name": "A String", # Required. Name of parameter.
"type": "A String", # Type of parameter.
"typeSchema": { # Encapsulates different type schema variations: either a reference to an a schema that's already defined by a tool, or an inline definition. # Optional. Type schema of parameter.
"inlineSchema": { # A type schema object that's specified inline. # Set if this is an inline schema definition.
"items": # Object with schema name: GoogleCloudDialogflowCxV3beta1TypeSchema # Schema of the elements if this is an ARRAY type.
"type": "A String", # Data type of the schema.
},
"schemaReference": { # A reference to the schema of an existing tool. # Set if this is a schema reference.
"schema": "A String", # The name of the schema.
"tool": "A String", # The tool that contains this schema definition. Format: `projects//locations//agents//tools/`.
},
},
},
],
"instruction": { # Message of the Instruction of the playbook. # Instruction to accomplish target goal.
"steps": [ # Ordered list of step by step execution instructions to accomplish target goal.
{ # Message of single step execution.
"steps": [ # Sub-processing needed to execute the current step.
# Object with schema name: GoogleCloudDialogflowCxV3beta1PlaybookStep
],
"text": "A String", # Step instruction in text format.
},
],
},
"llmModelSettings": { # Settings for LLM models. # Optional. Llm model settings for the playbook.
"model": "A String", # The selected LLM model.
"promptText": "A String", # The custom prompt to use.
},
"name": "A String", # The unique identifier of the playbook. Format: `projects//locations//agents//playbooks/`.
"outputParameterDefinitions": [ # Optional. Defined structured output parameters for this playbook.
{ # Defines the properties of a parameter. Used to define parameters used in the agent and the input / output parameters for each fulfillment.
"description": "A String", # Human-readable description of the parameter. Limited to 300 characters.
"name": "A String", # Required. Name of parameter.
"type": "A String", # Type of parameter.
"typeSchema": { # Encapsulates different type schema variations: either a reference to an a schema that's already defined by a tool, or an inline definition. # Optional. Type schema of parameter.
"inlineSchema": { # A type schema object that's specified inline. # Set if this is an inline schema definition.
"items": # Object with schema name: GoogleCloudDialogflowCxV3beta1TypeSchema # Schema of the elements if this is an ARRAY type.
"type": "A String", # Data type of the schema.
},
"schemaReference": { # A reference to the schema of an existing tool. # Set if this is a schema reference.
"schema": "A String", # The name of the schema.
"tool": "A String", # The tool that contains this schema definition. Format: `projects//locations//agents//tools/`.
},
},
},
],
"referencedFlows": [ # Output only. The resource name of flows referenced by the current playbook in the instructions.
"A String",
],
"referencedPlaybooks": [ # Output only. The resource name of other playbooks referenced by the current playbook in the instructions.
"A String",
],
"referencedTools": [ # Optional. The resource name of tools referenced by the current playbook in the instructions. If not provided explicitly, they are will be implied using the tool being referenced in goal and steps.
"A String",
],
"tokenCount": "A String", # Output only. Estimated number of tokes current playbook takes when sent to the LLM.
"updateTime": "A String", # Output only. Last time the playbook version was updated.
}
import_(parent, body=None, x__xgafv=None)
Imports the specified playbook to the specified agent from a binary file.
Args:
parent: string, Required. The agent to import the playbook into. Format: `projects//locations//agents/`. (required)
body: object, The request body.
The object takes the form of:
{ # The request message for Playbooks.ImportPlaybook.
"importStrategy": { # The playbook import strategy used for resource conflict resolution associated with an ImportPlaybookRequest. # Optional. Specifies the import strategy used when resolving resource conflicts.
"mainPlaybookImportStrategy": "A String", # Optional. Specifies the import strategy used when resolving conflicts with the main playbook. If not specified, 'CREATE_NEW' is assumed.
"nestedResourceImportStrategy": "A String", # Optional. Specifies the import strategy used when resolving referenced playbook/flow conflicts. If not specified, 'CREATE_NEW' is assumed.
"toolImportStrategy": "A String", # Optional. Specifies the import strategy used when resolving tool conflicts. If not specified, 'CREATE_NEW' is assumed. This will be applied after the main playbook and nested resource import strategies, meaning if the playbook that references the tool is skipped, the tool will also be skipped.
},
"playbookContent": "A String", # Uncompressed raw byte content for playbook.
"playbookUri": "A String", # [Dialogflow access control] (https://cloud.google.com/dialogflow/cx/docs/concept/access-control#storage).
}
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # This resource represents a long-running operation that is the result of a network API call.
"done": True or False, # If the value is `false`, it means the operation is still in progress. If `true`, the operation is completed, and either `error` or `response` is available.
"error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # The error result of the operation in case of failure or cancellation.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
"message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
},
"metadata": { # Service-specific metadata associated with the operation. It typically contains progress information and common metadata such as create time. Some services might not provide such metadata. Any method that returns a long-running operation should document the metadata type, if any.
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
"name": "A String", # The server-assigned name, which is only unique within the same service that originally returns it. If you use the default HTTP mapping, the `name` should be a resource name ending with `operations/{unique_id}`.
"response": { # The normal, successful response of the operation. If the original method returns no data on success, such as `Delete`, the response is `google.protobuf.Empty`. If the original method is standard `Get`/`Create`/`Update`, the response should be the resource. For other methods, the response should have the type `XxxResponse`, where `Xxx` is the original method name. For example, if the original method name is `TakeSnapshot()`, the inferred response type is `TakeSnapshotResponse`.
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
}
list(parent, pageSize=None, pageToken=None, x__xgafv=None)
Returns a list of playbooks in the specified agent.
Args:
parent: string, Required. The agent to list playbooks from. Format: `projects//locations//agents/`. (required)
pageSize: integer, The maximum number of items to return in a single page. By default 100 and at most 1000.
pageToken: string, The next_page_token value returned from a previous list request.
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # The response message for Playbooks.ListPlaybooks.
"nextPageToken": "A String", # Token to retrieve the next page of results, or empty if there are no more results in the list.
"playbooks": [ # The list of playbooks. There will be a maximum number of items returned based on the page_size field in the request.
{ # Playbook is the basic building block to instruct the LLM how to execute a certain task. A playbook consists of a goal to accomplish, an optional list of step by step instructions (the step instruction may refers to name of the custom or default plugin tools to use) to perform the task, a list of contextual input data to be passed in at the beginning of the invoked, and a list of output parameters to store the playbook result.
"createTime": "A String", # Output only. The timestamp of initial playbook creation.
"displayName": "A String", # Required. The human-readable name of the playbook, unique within an agent.
"goal": "A String", # Required. High level description of the goal the playbook intend to accomplish.
"inputParameterDefinitions": [ # Optional. Defined structured input parameters for this playbook.
{ # Defines the properties of a parameter. Used to define parameters used in the agent and the input / output parameters for each fulfillment.
"description": "A String", # Human-readable description of the parameter. Limited to 300 characters.
"name": "A String", # Required. Name of parameter.
"type": "A String", # Type of parameter.
"typeSchema": { # Encapsulates different type schema variations: either a reference to an a schema that's already defined by a tool, or an inline definition. # Optional. Type schema of parameter.
"inlineSchema": { # A type schema object that's specified inline. # Set if this is an inline schema definition.
"items": # Object with schema name: GoogleCloudDialogflowCxV3beta1TypeSchema # Schema of the elements if this is an ARRAY type.
"type": "A String", # Data type of the schema.
},
"schemaReference": { # A reference to the schema of an existing tool. # Set if this is a schema reference.
"schema": "A String", # The name of the schema.
"tool": "A String", # The tool that contains this schema definition. Format: `projects//locations//agents//tools/`.
},
},
},
],
"instruction": { # Message of the Instruction of the playbook. # Instruction to accomplish target goal.
"steps": [ # Ordered list of step by step execution instructions to accomplish target goal.
{ # Message of single step execution.
"steps": [ # Sub-processing needed to execute the current step.
# Object with schema name: GoogleCloudDialogflowCxV3beta1PlaybookStep
],
"text": "A String", # Step instruction in text format.
},
],
},
"llmModelSettings": { # Settings for LLM models. # Optional. Llm model settings for the playbook.
"model": "A String", # The selected LLM model.
"promptText": "A String", # The custom prompt to use.
},
"name": "A String", # The unique identifier of the playbook. Format: `projects//locations//agents//playbooks/`.
"outputParameterDefinitions": [ # Optional. Defined structured output parameters for this playbook.
{ # Defines the properties of a parameter. Used to define parameters used in the agent and the input / output parameters for each fulfillment.
"description": "A String", # Human-readable description of the parameter. Limited to 300 characters.
"name": "A String", # Required. Name of parameter.
"type": "A String", # Type of parameter.
"typeSchema": { # Encapsulates different type schema variations: either a reference to an a schema that's already defined by a tool, or an inline definition. # Optional. Type schema of parameter.
"inlineSchema": { # A type schema object that's specified inline. # Set if this is an inline schema definition.
"items": # Object with schema name: GoogleCloudDialogflowCxV3beta1TypeSchema # Schema of the elements if this is an ARRAY type.
"type": "A String", # Data type of the schema.
},
"schemaReference": { # A reference to the schema of an existing tool. # Set if this is a schema reference.
"schema": "A String", # The name of the schema.
"tool": "A String", # The tool that contains this schema definition. Format: `projects//locations//agents//tools/`.
},
},
},
],
"referencedFlows": [ # Output only. The resource name of flows referenced by the current playbook in the instructions.
"A String",
],
"referencedPlaybooks": [ # Output only. The resource name of other playbooks referenced by the current playbook in the instructions.
"A String",
],
"referencedTools": [ # Optional. The resource name of tools referenced by the current playbook in the instructions. If not provided explicitly, they are will be implied using the tool being referenced in goal and steps.
"A String",
],
"tokenCount": "A String", # Output only. Estimated number of tokes current playbook takes when sent to the LLM.
"updateTime": "A String", # Output only. Last time the playbook version was updated.
},
],
}
list_next()
Retrieves the next page of results.
Args:
previous_request: The request for the previous page. (required)
previous_response: The response from the request for the previous page. (required)
Returns:
A request object that you can call 'execute()' on to request the next
page. Returns None if there are no more items in the collection.
patch(name, body=None, updateMask=None, x__xgafv=None)
Updates the specified Playbook.
Args:
name: string, The unique identifier of the playbook. Format: `projects//locations//agents//playbooks/`. (required)
body: object, The request body.
The object takes the form of:
{ # Playbook is the basic building block to instruct the LLM how to execute a certain task. A playbook consists of a goal to accomplish, an optional list of step by step instructions (the step instruction may refers to name of the custom or default plugin tools to use) to perform the task, a list of contextual input data to be passed in at the beginning of the invoked, and a list of output parameters to store the playbook result.
"createTime": "A String", # Output only. The timestamp of initial playbook creation.
"displayName": "A String", # Required. The human-readable name of the playbook, unique within an agent.
"goal": "A String", # Required. High level description of the goal the playbook intend to accomplish.
"inputParameterDefinitions": [ # Optional. Defined structured input parameters for this playbook.
{ # Defines the properties of a parameter. Used to define parameters used in the agent and the input / output parameters for each fulfillment.
"description": "A String", # Human-readable description of the parameter. Limited to 300 characters.
"name": "A String", # Required. Name of parameter.
"type": "A String", # Type of parameter.
"typeSchema": { # Encapsulates different type schema variations: either a reference to an a schema that's already defined by a tool, or an inline definition. # Optional. Type schema of parameter.
"inlineSchema": { # A type schema object that's specified inline. # Set if this is an inline schema definition.
"items": # Object with schema name: GoogleCloudDialogflowCxV3beta1TypeSchema # Schema of the elements if this is an ARRAY type.
"type": "A String", # Data type of the schema.
},
"schemaReference": { # A reference to the schema of an existing tool. # Set if this is a schema reference.
"schema": "A String", # The name of the schema.
"tool": "A String", # The tool that contains this schema definition. Format: `projects//locations//agents//tools/`.
},
},
},
],
"instruction": { # Message of the Instruction of the playbook. # Instruction to accomplish target goal.
"steps": [ # Ordered list of step by step execution instructions to accomplish target goal.
{ # Message of single step execution.
"steps": [ # Sub-processing needed to execute the current step.
# Object with schema name: GoogleCloudDialogflowCxV3beta1PlaybookStep
],
"text": "A String", # Step instruction in text format.
},
],
},
"llmModelSettings": { # Settings for LLM models. # Optional. Llm model settings for the playbook.
"model": "A String", # The selected LLM model.
"promptText": "A String", # The custom prompt to use.
},
"name": "A String", # The unique identifier of the playbook. Format: `projects//locations//agents//playbooks/`.
"outputParameterDefinitions": [ # Optional. Defined structured output parameters for this playbook.
{ # Defines the properties of a parameter. Used to define parameters used in the agent and the input / output parameters for each fulfillment.
"description": "A String", # Human-readable description of the parameter. Limited to 300 characters.
"name": "A String", # Required. Name of parameter.
"type": "A String", # Type of parameter.
"typeSchema": { # Encapsulates different type schema variations: either a reference to an a schema that's already defined by a tool, or an inline definition. # Optional. Type schema of parameter.
"inlineSchema": { # A type schema object that's specified inline. # Set if this is an inline schema definition.
"items": # Object with schema name: GoogleCloudDialogflowCxV3beta1TypeSchema # Schema of the elements if this is an ARRAY type.
"type": "A String", # Data type of the schema.
},
"schemaReference": { # A reference to the schema of an existing tool. # Set if this is a schema reference.
"schema": "A String", # The name of the schema.
"tool": "A String", # The tool that contains this schema definition. Format: `projects//locations//agents//tools/`.
},
},
},
],
"referencedFlows": [ # Output only. The resource name of flows referenced by the current playbook in the instructions.
"A String",
],
"referencedPlaybooks": [ # Output only. The resource name of other playbooks referenced by the current playbook in the instructions.
"A String",
],
"referencedTools": [ # Optional. The resource name of tools referenced by the current playbook in the instructions. If not provided explicitly, they are will be implied using the tool being referenced in goal and steps.
"A String",
],
"tokenCount": "A String", # Output only. Estimated number of tokes current playbook takes when sent to the LLM.
"updateTime": "A String", # Output only. Last time the playbook version was updated.
}
updateMask: string, The mask to control which fields get updated. If the mask is not present, all fields will be updated.
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # Playbook is the basic building block to instruct the LLM how to execute a certain task. A playbook consists of a goal to accomplish, an optional list of step by step instructions (the step instruction may refers to name of the custom or default plugin tools to use) to perform the task, a list of contextual input data to be passed in at the beginning of the invoked, and a list of output parameters to store the playbook result.
"createTime": "A String", # Output only. The timestamp of initial playbook creation.
"displayName": "A String", # Required. The human-readable name of the playbook, unique within an agent.
"goal": "A String", # Required. High level description of the goal the playbook intend to accomplish.
"inputParameterDefinitions": [ # Optional. Defined structured input parameters for this playbook.
{ # Defines the properties of a parameter. Used to define parameters used in the agent and the input / output parameters for each fulfillment.
"description": "A String", # Human-readable description of the parameter. Limited to 300 characters.
"name": "A String", # Required. Name of parameter.
"type": "A String", # Type of parameter.
"typeSchema": { # Encapsulates different type schema variations: either a reference to an a schema that's already defined by a tool, or an inline definition. # Optional. Type schema of parameter.
"inlineSchema": { # A type schema object that's specified inline. # Set if this is an inline schema definition.
"items": # Object with schema name: GoogleCloudDialogflowCxV3beta1TypeSchema # Schema of the elements if this is an ARRAY type.
"type": "A String", # Data type of the schema.
},
"schemaReference": { # A reference to the schema of an existing tool. # Set if this is a schema reference.
"schema": "A String", # The name of the schema.
"tool": "A String", # The tool that contains this schema definition. Format: `projects//locations//agents//tools/`.
},
},
},
],
"instruction": { # Message of the Instruction of the playbook. # Instruction to accomplish target goal.
"steps": [ # Ordered list of step by step execution instructions to accomplish target goal.
{ # Message of single step execution.
"steps": [ # Sub-processing needed to execute the current step.
# Object with schema name: GoogleCloudDialogflowCxV3beta1PlaybookStep
],
"text": "A String", # Step instruction in text format.
},
],
},
"llmModelSettings": { # Settings for LLM models. # Optional. Llm model settings for the playbook.
"model": "A String", # The selected LLM model.
"promptText": "A String", # The custom prompt to use.
},
"name": "A String", # The unique identifier of the playbook. Format: `projects//locations//agents//playbooks/`.
"outputParameterDefinitions": [ # Optional. Defined structured output parameters for this playbook.
{ # Defines the properties of a parameter. Used to define parameters used in the agent and the input / output parameters for each fulfillment.
"description": "A String", # Human-readable description of the parameter. Limited to 300 characters.
"name": "A String", # Required. Name of parameter.
"type": "A String", # Type of parameter.
"typeSchema": { # Encapsulates different type schema variations: either a reference to an a schema that's already defined by a tool, or an inline definition. # Optional. Type schema of parameter.
"inlineSchema": { # A type schema object that's specified inline. # Set if this is an inline schema definition.
"items": # Object with schema name: GoogleCloudDialogflowCxV3beta1TypeSchema # Schema of the elements if this is an ARRAY type.
"type": "A String", # Data type of the schema.
},
"schemaReference": { # A reference to the schema of an existing tool. # Set if this is a schema reference.
"schema": "A String", # The name of the schema.
"tool": "A String", # The tool that contains this schema definition. Format: `projects//locations//agents//tools/`.
},
},
},
],
"referencedFlows": [ # Output only. The resource name of flows referenced by the current playbook in the instructions.
"A String",
],
"referencedPlaybooks": [ # Output only. The resource name of other playbooks referenced by the current playbook in the instructions.
"A String",
],
"referencedTools": [ # Optional. The resource name of tools referenced by the current playbook in the instructions. If not provided explicitly, they are will be implied using the tool being referenced in goal and steps.
"A String",
],
"tokenCount": "A String", # Output only. Estimated number of tokes current playbook takes when sent to the LLM.
"updateTime": "A String", # Output only. Last time the playbook version was updated.
}