# coding: utf-8 # (C) Copyright IBM Corp. 2019, 2022. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # IBM OpenAPI SDK Code Generator Version: 3.53.0-9710cac3-20220713-193508 """ The IBM Watson™ Assistant service combines machine learning, natural language understanding, and an integrated dialog editor to create conversation flows between your apps and your users. The Assistant v1 API provides authoring methods your application can use to create or update a workspace. API Version: 1.0 See: https://cloud.ibm.com/docs/assistant """ from datetime import datetime from enum import Enum from typing import Dict, List import json import sys from ibm_cloud_sdk_core import BaseService, DetailedResponse from ibm_cloud_sdk_core.authenticators.authenticator import Authenticator from ibm_cloud_sdk_core.get_authenticator import get_authenticator_from_environment from ibm_cloud_sdk_core.utils import convert_model, datetime_to_string, string_to_datetime from .common import get_sdk_headers ############################################################################## # Service ############################################################################## class AssistantV1(BaseService): """The Assistant V1 service.""" DEFAULT_SERVICE_URL = 'https://api.us-south.assistant.watson.cloud.ibm.com' DEFAULT_SERVICE_NAME = 'assistant' def __init__( self, version: str, authenticator: Authenticator = None, service_name: str = DEFAULT_SERVICE_NAME, ) -> None: """ Construct a new client for the Assistant service. :param str version: Release date of the API version you want to use. Specify dates in YYYY-MM-DD format. The current version is `2021-11-27`. :param Authenticator authenticator: The authenticator specifies the authentication mechanism. Get up to date information from https://github.com/IBM/python-sdk-core/blob/main/README.md about initializing the authenticator of your choice. """ if version is None: raise ValueError('version must be provided') if not authenticator: authenticator = get_authenticator_from_environment(service_name) BaseService.__init__(self, service_url=self.DEFAULT_SERVICE_URL, authenticator=authenticator) self.version = version self.configure_service(service_name) ######################### # Message ######################### def message(self, workspace_id: str, *, input: 'MessageInput' = None, intents: List['RuntimeIntent'] = None, entities: List['RuntimeEntity'] = None, alternate_intents: bool = None, context: 'Context' = None, output: 'OutputData' = None, user_id: str = None, nodes_visited_details: bool = None, **kwargs) -> DetailedResponse: """ Get response to user input. Send user input to a workspace and receive a response. **Important:** This method has been superseded by the new v2 runtime API. The v2 API offers significant advantages, including ease of deployment, automatic state management, versioning, and search capabilities. For more information, see the [documentation](https://cloud.ibm.com/docs/assistant?topic=assistant-api-overview). :param str workspace_id: Unique identifier of the workspace. :param MessageInput input: (optional) An input object that includes the input text. :param List[RuntimeIntent] intents: (optional) Intents to use when evaluating the user input. Include intents from the previous response to continue using those intents rather than trying to recognize intents in the new input. :param List[RuntimeEntity] entities: (optional) Entities to use when evaluating the message. Include entities from the previous response to continue using those entities rather than detecting entities in the new input. :param bool alternate_intents: (optional) Whether to return more than one intent. A value of `true` indicates that all matching intents are returned. :param Context context: (optional) State information for the conversation. To maintain state, include the context from the previous response. :param OutputData output: (optional) An output object that includes the response to the user, the dialog nodes that were triggered, and messages from the log. :param str user_id: (optional) A string value that identifies the user who is interacting with the workspace. The client must provide a unique identifier for each individual end user who accesses the application. For user-based plans, this user ID is used to identify unique users for billing purposes. This string cannot contain carriage return, newline, or tab characters. If no value is specified in the input, **user_id** is automatically set to the value of **context.conversation_id**. **Note:** This property is the same as the **user_id** property in the context metadata. If **user_id** is specified in both locations in a message request, the value specified at the root is used. :param bool nodes_visited_details: (optional) Whether to include additional diagnostic information about the dialog nodes that were visited during processing of the message. :param dict headers: A `dict` containing the request headers :return: A `DetailedResponse` containing the result, headers and HTTP status code. :rtype: DetailedResponse with `dict` result representing a `MessageResponse` object """ if workspace_id is None: raise ValueError('workspace_id must be provided') if input is not None: input = convert_model(input) if intents is not None: intents = [convert_model(x) for x in intents] if entities is not None: entities = [convert_model(x) for x in entities] if context is not None: context = convert_model(context) if output is not None: output = convert_model(output) headers = {} sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME, service_version='V1', operation_id='message') headers.update(sdk_headers) params = { 'version': self.version, 'nodes_visited_details': nodes_visited_details } data = { 'input': input, 'intents': intents, 'entities': entities, 'alternate_intents': alternate_intents, 'context': context, 'output': output, 'user_id': user_id } data = {k: v for (k, v) in data.items() if v is not None} data = json.dumps(data) headers['content-type'] = 'application/json' if 'headers' in kwargs: headers.update(kwargs.get('headers')) del kwargs['headers'] headers['Accept'] = 'application/json' path_param_keys = ['workspace_id'] path_param_values = self.encode_path_vars(workspace_id) path_param_dict = dict(zip(path_param_keys, path_param_values)) url = '/v1/workspaces/{workspace_id}/message'.format(**path_param_dict) request = self.prepare_request(method='POST', url=url, headers=headers, params=params, data=data) response = self.send(request, **kwargs) return response ######################### # Bulk classify ######################### def bulk_classify(self, workspace_id: str, *, input: List['BulkClassifyUtterance'] = None, **kwargs) -> DetailedResponse: """ Identify intents and entities in multiple user utterances. Send multiple user inputs to a workspace in a single request and receive information about the intents and entities recognized in each input. This method is useful for testing and comparing the performance of different workspaces. This method is available only with Enterprise with Data Isolation plans. :param str workspace_id: Unique identifier of the workspace. :param List[BulkClassifyUtterance] input: (optional) An array of input utterances to classify. :param dict headers: A `dict` containing the request headers :return: A `DetailedResponse` containing the result, headers and HTTP status code. :rtype: DetailedResponse with `dict` result representing a `BulkClassifyResponse` object """ if workspace_id is None: raise ValueError('workspace_id must be provided') if input is not None: input = [convert_model(x) for x in input] headers = {} sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME, service_version='V1', operation_id='bulk_classify') headers.update(sdk_headers) params = {'version': self.version} data = {'input': input} data = {k: v for (k, v) in data.items() if v is not None} data = json.dumps(data) headers['content-type'] = 'application/json' if 'headers' in kwargs: headers.update(kwargs.get('headers')) del kwargs['headers'] headers['Accept'] = 'application/json' path_param_keys = ['workspace_id'] path_param_values = self.encode_path_vars(workspace_id) path_param_dict = dict(zip(path_param_keys, path_param_values)) url = '/v1/workspaces/{workspace_id}/bulk_classify'.format( **path_param_dict) request = self.prepare_request(method='POST', url=url, headers=headers, params=params, data=data) response = self.send(request, **kwargs) return response ######################### # Workspaces ######################### def list_workspaces(self, *, page_limit: int = None, include_count: bool = None, sort: str = None, cursor: str = None, include_audit: bool = None, **kwargs) -> DetailedResponse: """ List workspaces. List the workspaces associated with a Watson Assistant service instance. :param int page_limit: (optional) The number of records to return in each page of results. :param bool include_count: (optional) Whether to include information about the number of records that satisfy the request, regardless of the page limit. If this parameter is `true`, the `pagination` object in the response includes the `total` property. :param str sort: (optional) The attribute by which returned workspaces will be sorted. To reverse the sort order, prefix the value with a minus sign (`-`). :param str cursor: (optional) A token identifying the page of results to retrieve. :param bool include_audit: (optional) Whether to include the audit properties (`created` and `updated` timestamps) in the response. :param dict headers: A `dict` containing the request headers :return: A `DetailedResponse` containing the result, headers and HTTP status code. :rtype: DetailedResponse with `dict` result representing a `WorkspaceCollection` object """ headers = {} sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME, service_version='V1', operation_id='list_workspaces') headers.update(sdk_headers) params = { 'version': self.version, 'page_limit': page_limit, 'include_count': include_count, 'sort': sort, 'cursor': cursor, 'include_audit': include_audit } if 'headers' in kwargs: headers.update(kwargs.get('headers')) del kwargs['headers'] headers['Accept'] = 'application/json' url = '/v1/workspaces' request = self.prepare_request(method='GET', url=url, headers=headers, params=params) response = self.send(request, **kwargs) return response def create_workspace(self, *, name: str = None, description: str = None, language: str = None, dialog_nodes: List['DialogNode'] = None, counterexamples: List['Counterexample'] = None, metadata: dict = None, learning_opt_out: bool = None, system_settings: 'WorkspaceSystemSettings' = None, webhooks: List['Webhook'] = None, intents: List['CreateIntent'] = None, entities: List['CreateEntity'] = None, include_audit: bool = None, **kwargs) -> DetailedResponse: """ Create workspace. Create a workspace based on component objects. You must provide workspace components defining the content of the new workspace. **Note:** The new workspace data cannot be larger than 1.5 MB. For larger requests, use the **Create workspace asynchronously** method. :param str name: (optional) The name of the workspace. This string cannot contain carriage return, newline, or tab characters. :param str description: (optional) The description of the workspace. This string cannot contain carriage return, newline, or tab characters. :param str language: (optional) The language of the workspace. :param List[DialogNode] dialog_nodes: (optional) An array of objects describing the dialog nodes in the workspace. :param List[Counterexample] counterexamples: (optional) An array of objects defining input examples that have been marked as irrelevant input. :param dict metadata: (optional) Any metadata related to the workspace. :param bool learning_opt_out: (optional) Whether training data from the workspace (including artifacts such as intents and entities) can be used by IBM for general service improvements. `true` indicates that workspace training data is not to be used. :param WorkspaceSystemSettings system_settings: (optional) Global settings for the workspace. :param List[Webhook] webhooks: (optional) :param List[CreateIntent] intents: (optional) An array of objects defining the intents for the workspace. :param List[CreateEntity] entities: (optional) An array of objects describing the entities for the workspace. :param bool include_audit: (optional) Whether to include the audit properties (`created` and `updated` timestamps) in the response. :param dict headers: A `dict` containing the request headers :return: A `DetailedResponse` containing the result, headers and HTTP status code. :rtype: DetailedResponse with `dict` result representing a `Workspace` object """ if dialog_nodes is not None: dialog_nodes = [convert_model(x) for x in dialog_nodes] if counterexamples is not None: counterexamples = [convert_model(x) for x in counterexamples] if system_settings is not None: system_settings = convert_model(system_settings) if webhooks is not None: webhooks = [convert_model(x) for x in webhooks] if intents is not None: intents = [convert_model(x) for x in intents] if entities is not None: entities = [convert_model(x) for x in entities] headers = {} sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME, service_version='V1', operation_id='create_workspace') headers.update(sdk_headers) params = {'version': self.version, 'include_audit': include_audit} data = { 'name': name, 'description': description, 'language': language, 'dialog_nodes': dialog_nodes, 'counterexamples': counterexamples, 'metadata': metadata, 'learning_opt_out': learning_opt_out, 'system_settings': system_settings, 'webhooks': webhooks, 'intents': intents, 'entities': entities } data = {k: v for (k, v) in data.items() if v is not None} data = json.dumps(data) headers['content-type'] = 'application/json' if 'headers' in kwargs: headers.update(kwargs.get('headers')) del kwargs['headers'] headers['Accept'] = 'application/json' url = '/v1/workspaces' request = self.prepare_request(method='POST', url=url, headers=headers, params=params, data=data) response = self.send(request, **kwargs) return response def get_workspace(self, workspace_id: str, *, export: bool = None, include_audit: bool = None, sort: str = None, **kwargs) -> DetailedResponse: """ Get information about a workspace. Get information about a workspace, optionally including all workspace content. :param str workspace_id: Unique identifier of the workspace. :param bool export: (optional) Whether to include all element content in the returned data. If **export**=`false`, the returned data includes only information about the element itself. If **export**=`true`, all content, including subelements, is included. :param bool include_audit: (optional) Whether to include the audit properties (`created` and `updated` timestamps) in the response. :param str sort: (optional) Indicates how the returned workspace data will be sorted. This parameter is valid only if **export**=`true`. Specify `sort=stable` to sort all workspace objects by unique identifier, in ascending alphabetical order. :param dict headers: A `dict` containing the request headers :return: A `DetailedResponse` containing the result, headers and HTTP status code. :rtype: DetailedResponse with `dict` result representing a `Workspace` object """ if workspace_id is None: raise ValueError('workspace_id must be provided') headers = {} sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME, service_version='V1', operation_id='get_workspace') headers.update(sdk_headers) params = { 'version': self.version, 'export': export, 'include_audit': include_audit, 'sort': sort } if 'headers' in kwargs: headers.update(kwargs.get('headers')) del kwargs['headers'] headers['Accept'] = 'application/json' path_param_keys = ['workspace_id'] path_param_values = self.encode_path_vars(workspace_id) path_param_dict = dict(zip(path_param_keys, path_param_values)) url = '/v1/workspaces/{workspace_id}'.format(**path_param_dict) request = self.prepare_request(method='GET', url=url, headers=headers, params=params) response = self.send(request, **kwargs) return response def update_workspace(self, workspace_id: str, *, name: str = None, description: str = None, language: str = None, dialog_nodes: List['DialogNode'] = None, counterexamples: List['Counterexample'] = None, metadata: dict = None, learning_opt_out: bool = None, system_settings: 'WorkspaceSystemSettings' = None, webhooks: List['Webhook'] = None, intents: List['CreateIntent'] = None, entities: List['CreateEntity'] = None, append: bool = None, include_audit: bool = None, **kwargs) -> DetailedResponse: """ Update workspace. Update an existing workspace with new or modified data. You must provide component objects defining the content of the updated workspace. **Note:** The new workspace data cannot be larger than 1.5 MB. For larger requests, use the **Update workspace asynchronously** method. :param str workspace_id: Unique identifier of the workspace. :param str name: (optional) The name of the workspace. This string cannot contain carriage return, newline, or tab characters. :param str description: (optional) The description of the workspace. This string cannot contain carriage return, newline, or tab characters. :param str language: (optional) The language of the workspace. :param List[DialogNode] dialog_nodes: (optional) An array of objects describing the dialog nodes in the workspace. :param List[Counterexample] counterexamples: (optional) An array of objects defining input examples that have been marked as irrelevant input. :param dict metadata: (optional) Any metadata related to the workspace. :param bool learning_opt_out: (optional) Whether training data from the workspace (including artifacts such as intents and entities) can be used by IBM for general service improvements. `true` indicates that workspace training data is not to be used. :param WorkspaceSystemSettings system_settings: (optional) Global settings for the workspace. :param List[Webhook] webhooks: (optional) :param List[CreateIntent] intents: (optional) An array of objects defining the intents for the workspace. :param List[CreateEntity] entities: (optional) An array of objects describing the entities for the workspace. :param bool append: (optional) Whether the new data is to be appended to the existing data in the object. If **append**=`false`, elements included in the new data completely replace the corresponding existing elements, including all subelements. For example, if the new data for a workspace includes **entities** and **append**=`false`, all existing entities in the workspace are discarded and replaced with the new entities. If **append**=`true`, existing elements are preserved, and the new elements are added. If any elements in the new data collide with existing elements, the update request fails. :param bool include_audit: (optional) Whether to include the audit properties (`created` and `updated` timestamps) in the response. :param dict headers: A `dict` containing the request headers :return: A `DetailedResponse` containing the result, headers and HTTP status code. :rtype: DetailedResponse with `dict` result representing a `Workspace` object """ if workspace_id is None: raise ValueError('workspace_id must be provided') if dialog_nodes is not None: dialog_nodes = [convert_model(x) for x in dialog_nodes] if counterexamples is not None: counterexamples = [convert_model(x) for x in counterexamples] if system_settings is not None: system_settings = convert_model(system_settings) if webhooks is not None: webhooks = [convert_model(x) for x in webhooks] if intents is not None: intents = [convert_model(x) for x in intents] if entities is not None: entities = [convert_model(x) for x in entities] headers = {} sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME, service_version='V1', operation_id='update_workspace') headers.update(sdk_headers) params = { 'version': self.version, 'append': append, 'include_audit': include_audit } data = { 'name': name, 'description': description, 'language': language, 'dialog_nodes': dialog_nodes, 'counterexamples': counterexamples, 'metadata': metadata, 'learning_opt_out': learning_opt_out, 'system_settings': system_settings, 'webhooks': webhooks, 'intents': intents, 'entities': entities } data = {k: v for (k, v) in data.items() if v is not None} data = json.dumps(data) headers['content-type'] = 'application/json' if 'headers' in kwargs: headers.update(kwargs.get('headers')) del kwargs['headers'] headers['Accept'] = 'application/json' path_param_keys = ['workspace_id'] path_param_values = self.encode_path_vars(workspace_id) path_param_dict = dict(zip(path_param_keys, path_param_values)) url = '/v1/workspaces/{workspace_id}'.format(**path_param_dict) request = self.prepare_request(method='POST', url=url, headers=headers, params=params, data=data) response = self.send(request, **kwargs) return response def delete_workspace(self, workspace_id: str, **kwargs) -> DetailedResponse: """ Delete workspace. Delete a workspace from the service instance. :param str workspace_id: Unique identifier of the workspace. :param dict headers: A `dict` containing the request headers :return: A `DetailedResponse` containing the result, headers and HTTP status code. :rtype: DetailedResponse """ if workspace_id is None: raise ValueError('workspace_id must be provided') headers = {} sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME, service_version='V1', operation_id='delete_workspace') headers.update(sdk_headers) params = {'version': self.version} if 'headers' in kwargs: headers.update(kwargs.get('headers')) del kwargs['headers'] headers['Accept'] = 'application/json' path_param_keys = ['workspace_id'] path_param_values = self.encode_path_vars(workspace_id) path_param_dict = dict(zip(path_param_keys, path_param_values)) url = '/v1/workspaces/{workspace_id}'.format(**path_param_dict) request = self.prepare_request(method='DELETE', url=url, headers=headers, params=params) response = self.send(request, **kwargs) return response def create_workspace_async( self, *, name: str = None, description: str = None, language: str = None, dialog_nodes: List['DialogNode'] = None, counterexamples: List['Counterexample'] = None, metadata: dict = None, learning_opt_out: bool = None, system_settings: 'WorkspaceSystemSettings' = None, webhooks: List['Webhook'] = None, intents: List['CreateIntent'] = None, entities: List['CreateEntity'] = None, **kwargs) -> DetailedResponse: """ Create workspace asynchronously. Create a workspace asynchronously based on component objects. You must provide workspace components defining the content of the new workspace. A successful call to this method only initiates asynchronous creation of the workspace. The new workspace is not available until processing completes. To check the status of the asynchronous operation, use the **Export workspace asynchronously** method. :param str name: (optional) The name of the workspace. This string cannot contain carriage return, newline, or tab characters. :param str description: (optional) The description of the workspace. This string cannot contain carriage return, newline, or tab characters. :param str language: (optional) The language of the workspace. :param List[DialogNode] dialog_nodes: (optional) An array of objects describing the dialog nodes in the workspace. :param List[Counterexample] counterexamples: (optional) An array of objects defining input examples that have been marked as irrelevant input. :param dict metadata: (optional) Any metadata related to the workspace. :param bool learning_opt_out: (optional) Whether training data from the workspace (including artifacts such as intents and entities) can be used by IBM for general service improvements. `true` indicates that workspace training data is not to be used. :param WorkspaceSystemSettings system_settings: (optional) Global settings for the workspace. :param List[Webhook] webhooks: (optional) :param List[CreateIntent] intents: (optional) An array of objects defining the intents for the workspace. :param List[CreateEntity] entities: (optional) An array of objects describing the entities for the workspace. :param dict headers: A `dict` containing the request headers :return: A `DetailedResponse` containing the result, headers and HTTP status code. :rtype: DetailedResponse with `dict` result representing a `Workspace` object """ if dialog_nodes is not None: dialog_nodes = [convert_model(x) for x in dialog_nodes] if counterexamples is not None: counterexamples = [convert_model(x) for x in counterexamples] if system_settings is not None: system_settings = convert_model(system_settings) if webhooks is not None: webhooks = [convert_model(x) for x in webhooks] if intents is not None: intents = [convert_model(x) for x in intents] if entities is not None: entities = [convert_model(x) for x in entities] headers = {} sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME, service_version='V1', operation_id='create_workspace_async') headers.update(sdk_headers) params = {'version': self.version} data = { 'name': name, 'description': description, 'language': language, 'dialog_nodes': dialog_nodes, 'counterexamples': counterexamples, 'metadata': metadata, 'learning_opt_out': learning_opt_out, 'system_settings': system_settings, 'webhooks': webhooks, 'intents': intents, 'entities': entities } data = {k: v for (k, v) in data.items() if v is not None} data = json.dumps(data) headers['content-type'] = 'application/json' if 'headers' in kwargs: headers.update(kwargs.get('headers')) del kwargs['headers'] headers['Accept'] = 'application/json' url = '/v1/workspaces_async' request = self.prepare_request(method='POST', url=url, headers=headers, params=params, data=data) response = self.send(request, **kwargs) return response def update_workspace_async( self, workspace_id: str, *, name: str = None, description: str = None, language: str = None, dialog_nodes: List['DialogNode'] = None, counterexamples: List['Counterexample'] = None, metadata: dict = None, learning_opt_out: bool = None, system_settings: 'WorkspaceSystemSettings' = None, webhooks: List['Webhook'] = None, intents: List['CreateIntent'] = None, entities: List['CreateEntity'] = None, append: bool = None, **kwargs) -> DetailedResponse: """ Update workspace asynchronously. Update an existing workspace asynchronously with new or modified data. You must provide component objects defining the content of the updated workspace. A successful call to this method only initiates an asynchronous update of the workspace. The updated workspace is not available until processing completes. To check the status of the asynchronous operation, use the **Export workspace asynchronously** method. :param str workspace_id: Unique identifier of the workspace. :param str name: (optional) The name of the workspace. This string cannot contain carriage return, newline, or tab characters. :param str description: (optional) The description of the workspace. This string cannot contain carriage return, newline, or tab characters. :param str language: (optional) The language of the workspace. :param List[DialogNode] dialog_nodes: (optional) An array of objects describing the dialog nodes in the workspace. :param List[Counterexample] counterexamples: (optional) An array of objects defining input examples that have been marked as irrelevant input. :param dict metadata: (optional) Any metadata related to the workspace. :param bool learning_opt_out: (optional) Whether training data from the workspace (including artifacts such as intents and entities) can be used by IBM for general service improvements. `true` indicates that workspace training data is not to be used. :param WorkspaceSystemSettings system_settings: (optional) Global settings for the workspace. :param List[Webhook] webhooks: (optional) :param List[CreateIntent] intents: (optional) An array of objects defining the intents for the workspace. :param List[CreateEntity] entities: (optional) An array of objects describing the entities for the workspace. :param bool append: (optional) Whether the new data is to be appended to the existing data in the object. If **append**=`false`, elements included in the new data completely replace the corresponding existing elements, including all subelements. For example, if the new data for a workspace includes **entities** and **append**=`false`, all existing entities in the workspace are discarded and replaced with the new entities. If **append**=`true`, existing elements are preserved, and the new elements are added. If any elements in the new data collide with existing elements, the update request fails. :param dict headers: A `dict` containing the request headers :return: A `DetailedResponse` containing the result, headers and HTTP status code. :rtype: DetailedResponse with `dict` result representing a `Workspace` object """ if workspace_id is None: raise ValueError('workspace_id must be provided') if dialog_nodes is not None: dialog_nodes = [convert_model(x) for x in dialog_nodes] if counterexamples is not None: counterexamples = [convert_model(x) for x in counterexamples] if system_settings is not None: system_settings = convert_model(system_settings) if webhooks is not None: webhooks = [convert_model(x) for x in webhooks] if intents is not None: intents = [convert_model(x) for x in intents] if entities is not None: entities = [convert_model(x) for x in entities] headers = {} sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME, service_version='V1', operation_id='update_workspace_async') headers.update(sdk_headers) params = {'version': self.version, 'append': append} data = { 'name': name, 'description': description, 'language': language, 'dialog_nodes': dialog_nodes, 'counterexamples': counterexamples, 'metadata': metadata, 'learning_opt_out': learning_opt_out, 'system_settings': system_settings, 'webhooks': webhooks, 'intents': intents, 'entities': entities } data = {k: v for (k, v) in data.items() if v is not None} data = json.dumps(data) headers['content-type'] = 'application/json' if 'headers' in kwargs: headers.update(kwargs.get('headers')) del kwargs['headers'] headers['Accept'] = 'application/json' path_param_keys = ['workspace_id'] path_param_values = self.encode_path_vars(workspace_id) path_param_dict = dict(zip(path_param_keys, path_param_values)) url = '/v1/workspaces_async/{workspace_id}'.format(**path_param_dict) request = self.prepare_request(method='POST', url=url, headers=headers, params=params, data=data) response = self.send(request, **kwargs) return response def export_workspace_async(self, workspace_id: str, *, include_audit: bool = None, sort: str = None, verbose: bool = None, **kwargs) -> DetailedResponse: """ Export workspace asynchronously. Export the entire workspace asynchronously, including all workspace content. A successful call to this method only initiates an asynchronous export. The exported JSON data is not available until processing completes. After the initial request is submitted, you can continue to poll by calling the same request again and checking the value of the **status** property. When processing has completed, the request returns the exported JSON data. Remember that the usual rate limits apply. :param str workspace_id: Unique identifier of the workspace. :param bool include_audit: (optional) Whether to include the audit properties (`created` and `updated` timestamps) in the response. :param str sort: (optional) Indicates how the returned workspace data will be sorted. Specify `sort=stable` to sort all workspace objects by unique identifier, in ascending alphabetical order. :param bool verbose: (optional) Whether the response should include the `counts` property, which indicates how many of each component (such as intents and entities) the workspace contains. :param dict headers: A `dict` containing the request headers :return: A `DetailedResponse` containing the result, headers and HTTP status code. :rtype: DetailedResponse with `dict` result representing a `Workspace` object """ if workspace_id is None: raise ValueError('workspace_id must be provided') headers = {} sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME, service_version='V1', operation_id='export_workspace_async') headers.update(sdk_headers) params = { 'version': self.version, 'include_audit': include_audit, 'sort': sort, 'verbose': verbose } if 'headers' in kwargs: headers.update(kwargs.get('headers')) del kwargs['headers'] headers['Accept'] = 'application/json' path_param_keys = ['workspace_id'] path_param_values = self.encode_path_vars(workspace_id) path_param_dict = dict(zip(path_param_keys, path_param_values)) url = '/v1/workspaces_async/{workspace_id}/export'.format( **path_param_dict) request = self.prepare_request(method='GET', url=url, headers=headers, params=params) response = self.send(request, **kwargs) return response ######################### # Intents ######################### def list_intents(self, workspace_id: str, *, export: bool = None, page_limit: int = None, include_count: bool = None, sort: str = None, cursor: str = None, include_audit: bool = None, **kwargs) -> DetailedResponse: """ List intents. List the intents for a workspace. :param str workspace_id: Unique identifier of the workspace. :param bool export: (optional) Whether to include all element content in the returned data. If **export**=`false`, the returned data includes only information about the element itself. If **export**=`true`, all content, including subelements, is included. :param int page_limit: (optional) The number of records to return in each page of results. :param bool include_count: (optional) Whether to include information about the number of records that satisfy the request, regardless of the page limit. If this parameter is `true`, the `pagination` object in the response includes the `total` property. :param str sort: (optional) The attribute by which returned intents will be sorted. To reverse the sort order, prefix the value with a minus sign (`-`). :param str cursor: (optional) A token identifying the page of results to retrieve. :param bool include_audit: (optional) Whether to include the audit properties (`created` and `updated` timestamps) in the response. :param dict headers: A `dict` containing the request headers :return: A `DetailedResponse` containing the result, headers and HTTP status code. :rtype: DetailedResponse with `dict` result representing a `IntentCollection` object """ if workspace_id is None: raise ValueError('workspace_id must be provided') headers = {} sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME, service_version='V1', operation_id='list_intents') headers.update(sdk_headers) params = { 'version': self.version, 'export': export, 'page_limit': page_limit, 'include_count': include_count, 'sort': sort, 'cursor': cursor, 'include_audit': include_audit } if 'headers' in kwargs: headers.update(kwargs.get('headers')) del kwargs['headers'] headers['Accept'] = 'application/json' path_param_keys = ['workspace_id'] path_param_values = self.encode_path_vars(workspace_id) path_param_dict = dict(zip(path_param_keys, path_param_values)) url = '/v1/workspaces/{workspace_id}/intents'.format(**path_param_dict) request = self.prepare_request(method='GET', url=url, headers=headers, params=params) response = self.send(request, **kwargs) return response def create_intent(self, workspace_id: str, intent: str, *, description: str = None, examples: List['Example'] = None, include_audit: bool = None, **kwargs) -> DetailedResponse: """ Create intent. Create a new intent. If you want to create multiple intents with a single API call, consider using the **[Update workspace](#update-workspace)** method instead. :param str workspace_id: Unique identifier of the workspace. :param str intent: The name of the intent. This string must conform to the following restrictions: - It can contain only Unicode alphanumeric, underscore, hyphen, and dot characters. - It cannot begin with the reserved prefix `sys-`. :param str description: (optional) The description of the intent. This string cannot contain carriage return, newline, or tab characters. :param List[Example] examples: (optional) An array of user input examples for the intent. :param bool include_audit: (optional) Whether to include the audit properties (`created` and `updated` timestamps) in the response. :param dict headers: A `dict` containing the request headers :return: A `DetailedResponse` containing the result, headers and HTTP status code. :rtype: DetailedResponse with `dict` result representing a `Intent` object """ if workspace_id is None: raise ValueError('workspace_id must be provided') if intent is None: raise ValueError('intent must be provided') if examples is not None: examples = [convert_model(x) for x in examples] headers = {} sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME, service_version='V1', operation_id='create_intent') headers.update(sdk_headers) params = {'version': self.version, 'include_audit': include_audit} data = { 'intent': intent, 'description': description, 'examples': examples } data = {k: v for (k, v) in data.items() if v is not None} data = json.dumps(data) headers['content-type'] = 'application/json' if 'headers' in kwargs: headers.update(kwargs.get('headers')) del kwargs['headers'] headers['Accept'] = 'application/json' path_param_keys = ['workspace_id'] path_param_values = self.encode_path_vars(workspace_id) path_param_dict = dict(zip(path_param_keys, path_param_values)) url = '/v1/workspaces/{workspace_id}/intents'.format(**path_param_dict) request = self.prepare_request(method='POST', url=url, headers=headers, params=params, data=data) response = self.send(request, **kwargs) return response def get_intent(self, workspace_id: str, intent: str, *, export: bool = None, include_audit: bool = None, **kwargs) -> DetailedResponse: """ Get intent. Get information about an intent, optionally including all intent content. :param str workspace_id: Unique identifier of the workspace. :param str intent: The intent name. :param bool export: (optional) Whether to include all element content in the returned data. If **export**=`false`, the returned data includes only information about the element itself. If **export**=`true`, all content, including subelements, is included. :param bool include_audit: (optional) Whether to include the audit properties (`created` and `updated` timestamps) in the response. :param dict headers: A `dict` containing the request headers :return: A `DetailedResponse` containing the result, headers and HTTP status code. :rtype: DetailedResponse with `dict` result representing a `Intent` object """ if workspace_id is None: raise ValueError('workspace_id must be provided') if intent is None: raise ValueError('intent must be provided') headers = {} sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME, service_version='V1', operation_id='get_intent') headers.update(sdk_headers) params = { 'version': self.version, 'export': export, 'include_audit': include_audit } if 'headers' in kwargs: headers.update(kwargs.get('headers')) del kwargs['headers'] headers['Accept'] = 'application/json' path_param_keys = ['workspace_id', 'intent'] path_param_values = self.encode_path_vars(workspace_id, intent) path_param_dict = dict(zip(path_param_keys, path_param_values)) url = '/v1/workspaces/{workspace_id}/intents/{intent}'.format( **path_param_dict) request = self.prepare_request(method='GET', url=url, headers=headers, params=params) response = self.send(request, **kwargs) return response def update_intent(self, workspace_id: str, intent: str, *, new_intent: str = None, new_description: str = None, new_examples: List['Example'] = None, append: bool = None, include_audit: bool = None, **kwargs) -> DetailedResponse: """ Update intent. Update an existing intent with new or modified data. You must provide component objects defining the content of the updated intent. If you want to update multiple intents with a single API call, consider using the **[Update workspace](#update-workspace)** method instead. :param str workspace_id: Unique identifier of the workspace. :param str intent: The intent name. :param str new_intent: (optional) The name of the intent. This string must conform to the following restrictions: - It can contain only Unicode alphanumeric, underscore, hyphen, and dot characters. - It cannot begin with the reserved prefix `sys-`. :param str new_description: (optional) The description of the intent. This string cannot contain carriage return, newline, or tab characters. :param List[Example] new_examples: (optional) An array of user input examples for the intent. :param bool append: (optional) Whether the new data is to be appended to the existing data in the object. If **append**=`false`, elements included in the new data completely replace the corresponding existing elements, including all subelements. For example, if the new data for the intent includes **examples** and **append**=`false`, all existing examples for the intent are discarded and replaced with the new examples. If **append**=`true`, existing elements are preserved, and the new elements are added. If any elements in the new data collide with existing elements, the update request fails. :param bool include_audit: (optional) Whether to include the audit properties (`created` and `updated` timestamps) in the response. :param dict headers: A `dict` containing the request headers :return: A `DetailedResponse` containing the result, headers and HTTP status code. :rtype: DetailedResponse with `dict` result representing a `Intent` object """ if workspace_id is None: raise ValueError('workspace_id must be provided') if intent is None: raise ValueError('intent must be provided') if new_examples is not None: new_examples = [convert_model(x) for x in new_examples] headers = {} sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME, service_version='V1', operation_id='update_intent') headers.update(sdk_headers) params = { 'version': self.version, 'append': append, 'include_audit': include_audit } data = { 'intent': new_intent, 'description': new_description, 'examples': new_examples } data = {k: v for (k, v) in data.items() if v is not None} data = json.dumps(data) headers['content-type'] = 'application/json' if 'headers' in kwargs: headers.update(kwargs.get('headers')) del kwargs['headers'] headers['Accept'] = 'application/json' path_param_keys = ['workspace_id', 'intent'] path_param_values = self.encode_path_vars(workspace_id, intent) path_param_dict = dict(zip(path_param_keys, path_param_values)) url = '/v1/workspaces/{workspace_id}/intents/{intent}'.format( **path_param_dict) request = self.prepare_request(method='POST', url=url, headers=headers, params=params, data=data) response = self.send(request, **kwargs) return response def delete_intent(self, workspace_id: str, intent: str, **kwargs) -> DetailedResponse: """ Delete intent. Delete an intent from a workspace. :param str workspace_id: Unique identifier of the workspace. :param str intent: The intent name. :param dict headers: A `dict` containing the request headers :return: A `DetailedResponse` containing the result, headers and HTTP status code. :rtype: DetailedResponse """ if workspace_id is None: raise ValueError('workspace_id must be provided') if intent is None: raise ValueError('intent must be provided') headers = {} sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME, service_version='V1', operation_id='delete_intent') headers.update(sdk_headers) params = {'version': self.version} if 'headers' in kwargs: headers.update(kwargs.get('headers')) del kwargs['headers'] headers['Accept'] = 'application/json' path_param_keys = ['workspace_id', 'intent'] path_param_values = self.encode_path_vars(workspace_id, intent) path_param_dict = dict(zip(path_param_keys, path_param_values)) url = '/v1/workspaces/{workspace_id}/intents/{intent}'.format( **path_param_dict) request = self.prepare_request(method='DELETE', url=url, headers=headers, params=params) response = self.send(request, **kwargs) return response ######################### # Examples ######################### def list_examples(self, workspace_id: str, intent: str, *, page_limit: int = None, include_count: bool = None, sort: str = None, cursor: str = None, include_audit: bool = None, **kwargs) -> DetailedResponse: """ List user input examples. List the user input examples for an intent, optionally including contextual entity mentions. :param str workspace_id: Unique identifier of the workspace. :param str intent: The intent name. :param int page_limit: (optional) The number of records to return in each page of results. :param bool include_count: (optional) Whether to include information about the number of records that satisfy the request, regardless of the page limit. If this parameter is `true`, the `pagination` object in the response includes the `total` property. :param str sort: (optional) The attribute by which returned examples will be sorted. To reverse the sort order, prefix the value with a minus sign (`-`). :param str cursor: (optional) A token identifying the page of results to retrieve. :param bool include_audit: (optional) Whether to include the audit properties (`created` and `updated` timestamps) in the response. :param dict headers: A `dict` containing the request headers :return: A `DetailedResponse` containing the result, headers and HTTP status code. :rtype: DetailedResponse with `dict` result representing a `ExampleCollection` object """ if workspace_id is None: raise ValueError('workspace_id must be provided') if intent is None: raise ValueError('intent must be provided') headers = {} sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME, service_version='V1', operation_id='list_examples') headers.update(sdk_headers) params = { 'version': self.version, 'page_limit': page_limit, 'include_count': include_count, 'sort': sort, 'cursor': cursor, 'include_audit': include_audit } if 'headers' in kwargs: headers.update(kwargs.get('headers')) del kwargs['headers'] headers['Accept'] = 'application/json' path_param_keys = ['workspace_id', 'intent'] path_param_values = self.encode_path_vars(workspace_id, intent) path_param_dict = dict(zip(path_param_keys, path_param_values)) url = '/v1/workspaces/{workspace_id}/intents/{intent}/examples'.format( **path_param_dict) request = self.prepare_request(method='GET', url=url, headers=headers, params=params) response = self.send(request, **kwargs) return response def create_example(self, workspace_id: str, intent: str, text: str, *, mentions: List['Mention'] = None, include_audit: bool = None, **kwargs) -> DetailedResponse: """ Create user input example. Add a new user input example to an intent. If you want to add multiple examples with a single API call, consider using the **[Update intent](#update-intent)** method instead. :param str workspace_id: Unique identifier of the workspace. :param str intent: The intent name. :param str text: The text of a user input example. This string must conform to the following restrictions: - It cannot contain carriage return, newline, or tab characters. - It cannot consist of only whitespace characters. :param List[Mention] mentions: (optional) An array of contextual entity mentions. :param bool include_audit: (optional) Whether to include the audit properties (`created` and `updated` timestamps) in the response. :param dict headers: A `dict` containing the request headers :return: A `DetailedResponse` containing the result, headers and HTTP status code. :rtype: DetailedResponse with `dict` result representing a `Example` object """ if workspace_id is None: raise ValueError('workspace_id must be provided') if intent is None: raise ValueError('intent must be provided') if text is None: raise ValueError('text must be provided') if mentions is not None: mentions = [convert_model(x) for x in mentions] headers = {} sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME, service_version='V1', operation_id='create_example') headers.update(sdk_headers) params = {'version': self.version, 'include_audit': include_audit} data = {'text': text, 'mentions': mentions} data = {k: v for (k, v) in data.items() if v is not None} data = json.dumps(data) headers['content-type'] = 'application/json' if 'headers' in kwargs: headers.update(kwargs.get('headers')) del kwargs['headers'] headers['Accept'] = 'application/json' path_param_keys = ['workspace_id', 'intent'] path_param_values = self.encode_path_vars(workspace_id, intent) path_param_dict = dict(zip(path_param_keys, path_param_values)) url = '/v1/workspaces/{workspace_id}/intents/{intent}/examples'.format( **path_param_dict) request = self.prepare_request(method='POST', url=url, headers=headers, params=params, data=data) response = self.send(request, **kwargs) return response def get_example(self, workspace_id: str, intent: str, text: str, *, include_audit: bool = None, **kwargs) -> DetailedResponse: """ Get user input example. Get information about a user input example. :param str workspace_id: Unique identifier of the workspace. :param str intent: The intent name. :param str text: The text of the user input example. :param bool include_audit: (optional) Whether to include the audit properties (`created` and `updated` timestamps) in the response. :param dict headers: A `dict` containing the request headers :return: A `DetailedResponse` containing the result, headers and HTTP status code. :rtype: DetailedResponse with `dict` result representing a `Example` object """ if workspace_id is None: raise ValueError('workspace_id must be provided') if intent is None: raise ValueError('intent must be provided') if text is None: raise ValueError('text must be provided') headers = {} sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME, service_version='V1', operation_id='get_example') headers.update(sdk_headers) params = {'version': self.version, 'include_audit': include_audit} if 'headers' in kwargs: headers.update(kwargs.get('headers')) del kwargs['headers'] headers['Accept'] = 'application/json' path_param_keys = ['workspace_id', 'intent', 'text'] path_param_values = self.encode_path_vars(workspace_id, intent, text) path_param_dict = dict(zip(path_param_keys, path_param_values)) url = '/v1/workspaces/{workspace_id}/intents/{intent}/examples/{text}'.format( **path_param_dict) request = self.prepare_request(method='GET', url=url, headers=headers, params=params) response = self.send(request, **kwargs) return response def update_example(self, workspace_id: str, intent: str, text: str, *, new_text: str = None, new_mentions: List['Mention'] = None, include_audit: bool = None, **kwargs) -> DetailedResponse: """ Update user input example. Update the text of a user input example. If you want to update multiple examples with a single API call, consider using the **[Update intent](#update-intent)** method instead. :param str workspace_id: Unique identifier of the workspace. :param str intent: The intent name. :param str text: The text of the user input example. :param str new_text: (optional) The text of the user input example. This string must conform to the following restrictions: - It cannot contain carriage return, newline, or tab characters. - It cannot consist of only whitespace characters. :param List[Mention] new_mentions: (optional) An array of contextual entity mentions. :param bool include_audit: (optional) Whether to include the audit properties (`created` and `updated` timestamps) in the response. :param dict headers: A `dict` containing the request headers :return: A `DetailedResponse` containing the result, headers and HTTP status code. :rtype: DetailedResponse with `dict` result representing a `Example` object """ if workspace_id is None: raise ValueError('workspace_id must be provided') if intent is None: raise ValueError('intent must be provided') if text is None: raise ValueError('text must be provided') if new_mentions is not None: new_mentions = [convert_model(x) for x in new_mentions] headers = {} sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME, service_version='V1', operation_id='update_example') headers.update(sdk_headers) params = {'version': self.version, 'include_audit': include_audit} data = {'text': new_text, 'mentions': new_mentions} data = {k: v for (k, v) in data.items() if v is not None} data = json.dumps(data) headers['content-type'] = 'application/json' if 'headers' in kwargs: headers.update(kwargs.get('headers')) del kwargs['headers'] headers['Accept'] = 'application/json' path_param_keys = ['workspace_id', 'intent', 'text'] path_param_values = self.encode_path_vars(workspace_id, intent, text) path_param_dict = dict(zip(path_param_keys, path_param_values)) url = '/v1/workspaces/{workspace_id}/intents/{intent}/examples/{text}'.format( **path_param_dict) request = self.prepare_request(method='POST', url=url, headers=headers, params=params, data=data) response = self.send(request, **kwargs) return response def delete_example(self, workspace_id: str, intent: str, text: str, **kwargs) -> DetailedResponse: """ Delete user input example. Delete a user input example from an intent. :param str workspace_id: Unique identifier of the workspace. :param str intent: The intent name. :param str text: The text of the user input example. :param dict headers: A `dict` containing the request headers :return: A `DetailedResponse` containing the result, headers and HTTP status code. :rtype: DetailedResponse """ if workspace_id is None: raise ValueError('workspace_id must be provided') if intent is None: raise ValueError('intent must be provided') if text is None: raise ValueError('text must be provided') headers = {} sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME, service_version='V1', operation_id='delete_example') headers.update(sdk_headers) params = {'version': self.version} if 'headers' in kwargs: headers.update(kwargs.get('headers')) del kwargs['headers'] headers['Accept'] = 'application/json' path_param_keys = ['workspace_id', 'intent', 'text'] path_param_values = self.encode_path_vars(workspace_id, intent, text) path_param_dict = dict(zip(path_param_keys, path_param_values)) url = '/v1/workspaces/{workspace_id}/intents/{intent}/examples/{text}'.format( **path_param_dict) request = self.prepare_request(method='DELETE', url=url, headers=headers, params=params) response = self.send(request, **kwargs) return response ######################### # Counterexamples ######################### def list_counterexamples(self, workspace_id: str, *, page_limit: int = None, include_count: bool = None, sort: str = None, cursor: str = None, include_audit: bool = None, **kwargs) -> DetailedResponse: """ List counterexamples. List the counterexamples for a workspace. Counterexamples are examples that have been marked as irrelevant input. :param str workspace_id: Unique identifier of the workspace. :param int page_limit: (optional) The number of records to return in each page of results. :param bool include_count: (optional) Whether to include information about the number of records that satisfy the request, regardless of the page limit. If this parameter is `true`, the `pagination` object in the response includes the `total` property. :param str sort: (optional) The attribute by which returned counterexamples will be sorted. To reverse the sort order, prefix the value with a minus sign (`-`). :param str cursor: (optional) A token identifying the page of results to retrieve. :param bool include_audit: (optional) Whether to include the audit properties (`created` and `updated` timestamps) in the response. :param dict headers: A `dict` containing the request headers :return: A `DetailedResponse` containing the result, headers and HTTP status code. :rtype: DetailedResponse with `dict` result representing a `CounterexampleCollection` object """ if workspace_id is None: raise ValueError('workspace_id must be provided') headers = {} sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME, service_version='V1', operation_id='list_counterexamples') headers.update(sdk_headers) params = { 'version': self.version, 'page_limit': page_limit, 'include_count': include_count, 'sort': sort, 'cursor': cursor, 'include_audit': include_audit } if 'headers' in kwargs: headers.update(kwargs.get('headers')) del kwargs['headers'] headers['Accept'] = 'application/json' path_param_keys = ['workspace_id'] path_param_values = self.encode_path_vars(workspace_id) path_param_dict = dict(zip(path_param_keys, path_param_values)) url = '/v1/workspaces/{workspace_id}/counterexamples'.format( **path_param_dict) request = self.prepare_request(method='GET', url=url, headers=headers, params=params) response = self.send(request, **kwargs) return response def create_counterexample(self, workspace_id: str, text: str, *, include_audit: bool = None, **kwargs) -> DetailedResponse: """ Create counterexample. Add a new counterexample to a workspace. Counterexamples are examples that have been marked as irrelevant input. If you want to add multiple counterexamples with a single API call, consider using the **[Update workspace](#update-workspace)** method instead. :param str workspace_id: Unique identifier of the workspace. :param str text: The text of a user input marked as irrelevant input. This string must conform to the following restrictions: - It cannot contain carriage return, newline, or tab characters. - It cannot consist of only whitespace characters. :param bool include_audit: (optional) Whether to include the audit properties (`created` and `updated` timestamps) in the response. :param dict headers: A `dict` containing the request headers :return: A `DetailedResponse` containing the result, headers and HTTP status code. :rtype: DetailedResponse with `dict` result representing a `Counterexample` object """ if workspace_id is None: raise ValueError('workspace_id must be provided') if text is None: raise ValueError('text must be provided') headers = {} sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME, service_version='V1', operation_id='create_counterexample') headers.update(sdk_headers) params = {'version': self.version, 'include_audit': include_audit} data = {'text': text} data = {k: v for (k, v) in data.items() if v is not None} data = json.dumps(data) headers['content-type'] = 'application/json' if 'headers' in kwargs: headers.update(kwargs.get('headers')) del kwargs['headers'] headers['Accept'] = 'application/json' path_param_keys = ['workspace_id'] path_param_values = self.encode_path_vars(workspace_id) path_param_dict = dict(zip(path_param_keys, path_param_values)) url = '/v1/workspaces/{workspace_id}/counterexamples'.format( **path_param_dict) request = self.prepare_request(method='POST', url=url, headers=headers, params=params, data=data) response = self.send(request, **kwargs) return response def get_counterexample(self, workspace_id: str, text: str, *, include_audit: bool = None, **kwargs) -> DetailedResponse: """ Get counterexample. Get information about a counterexample. Counterexamples are examples that have been marked as irrelevant input. :param str workspace_id: Unique identifier of the workspace. :param str text: The text of a user input counterexample (for example, `What are you wearing?`). :param bool include_audit: (optional) Whether to include the audit properties (`created` and `updated` timestamps) in the response. :param dict headers: A `dict` containing the request headers :return: A `DetailedResponse` containing the result, headers and HTTP status code. :rtype: DetailedResponse with `dict` result representing a `Counterexample` object """ if workspace_id is None: raise ValueError('workspace_id must be provided') if text is None: raise ValueError('text must be provided') headers = {} sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME, service_version='V1', operation_id='get_counterexample') headers.update(sdk_headers) params = {'version': self.version, 'include_audit': include_audit} if 'headers' in kwargs: headers.update(kwargs.get('headers')) del kwargs['headers'] headers['Accept'] = 'application/json' path_param_keys = ['workspace_id', 'text'] path_param_values = self.encode_path_vars(workspace_id, text) path_param_dict = dict(zip(path_param_keys, path_param_values)) url = '/v1/workspaces/{workspace_id}/counterexamples/{text}'.format( **path_param_dict) request = self.prepare_request(method='GET', url=url, headers=headers, params=params) response = self.send(request, **kwargs) return response def update_counterexample(self, workspace_id: str, text: str, *, new_text: str = None, include_audit: bool = None, **kwargs) -> DetailedResponse: """ Update counterexample. Update the text of a counterexample. Counterexamples are examples that have been marked as irrelevant input. :param str workspace_id: Unique identifier of the workspace. :param str text: The text of a user input counterexample (for example, `What are you wearing?`). :param str new_text: (optional) The text of a user input marked as irrelevant input. This string must conform to the following restrictions: - It cannot contain carriage return, newline, or tab characters. - It cannot consist of only whitespace characters. :param bool include_audit: (optional) Whether to include the audit properties (`created` and `updated` timestamps) in the response. :param dict headers: A `dict` containing the request headers :return: A `DetailedResponse` containing the result, headers and HTTP status code. :rtype: DetailedResponse with `dict` result representing a `Counterexample` object """ if workspace_id is None: raise ValueError('workspace_id must be provided') if text is None: raise ValueError('text must be provided') headers = {} sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME, service_version='V1', operation_id='update_counterexample') headers.update(sdk_headers) params = {'version': self.version, 'include_audit': include_audit} data = {'text': new_text} data = {k: v for (k, v) in data.items() if v is not None} data = json.dumps(data) headers['content-type'] = 'application/json' if 'headers' in kwargs: headers.update(kwargs.get('headers')) del kwargs['headers'] headers['Accept'] = 'application/json' path_param_keys = ['workspace_id', 'text'] path_param_values = self.encode_path_vars(workspace_id, text) path_param_dict = dict(zip(path_param_keys, path_param_values)) url = '/v1/workspaces/{workspace_id}/counterexamples/{text}'.format( **path_param_dict) request = self.prepare_request(method='POST', url=url, headers=headers, params=params, data=data) response = self.send(request, **kwargs) return response def delete_counterexample(self, workspace_id: str, text: str, **kwargs) -> DetailedResponse: """ Delete counterexample. Delete a counterexample from a workspace. Counterexamples are examples that have been marked as irrelevant input. :param str workspace_id: Unique identifier of the workspace. :param str text: The text of a user input counterexample (for example, `What are you wearing?`). :param dict headers: A `dict` containing the request headers :return: A `DetailedResponse` containing the result, headers and HTTP status code. :rtype: DetailedResponse """ if workspace_id is None: raise ValueError('workspace_id must be provided') if text is None: raise ValueError('text must be provided') headers = {} sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME, service_version='V1', operation_id='delete_counterexample') headers.update(sdk_headers) params = {'version': self.version} if 'headers' in kwargs: headers.update(kwargs.get('headers')) del kwargs['headers'] headers['Accept'] = 'application/json' path_param_keys = ['workspace_id', 'text'] path_param_values = self.encode_path_vars(workspace_id, text) path_param_dict = dict(zip(path_param_keys, path_param_values)) url = '/v1/workspaces/{workspace_id}/counterexamples/{text}'.format( **path_param_dict) request = self.prepare_request(method='DELETE', url=url, headers=headers, params=params) response = self.send(request, **kwargs) return response ######################### # Entities ######################### def list_entities(self, workspace_id: str, *, export: bool = None, page_limit: int = None, include_count: bool = None, sort: str = None, cursor: str = None, include_audit: bool = None, **kwargs) -> DetailedResponse: """ List entities. List the entities for a workspace. :param str workspace_id: Unique identifier of the workspace. :param bool export: (optional) Whether to include all element content in the returned data. If **export**=`false`, the returned data includes only information about the element itself. If **export**=`true`, all content, including subelements, is included. :param int page_limit: (optional) The number of records to return in each page of results. :param bool include_count: (optional) Whether to include information about the number of records that satisfy the request, regardless of the page limit. If this parameter is `true`, the `pagination` object in the response includes the `total` property. :param str sort: (optional) The attribute by which returned entities will be sorted. To reverse the sort order, prefix the value with a minus sign (`-`). :param str cursor: (optional) A token identifying the page of results to retrieve. :param bool include_audit: (optional) Whether to include the audit properties (`created` and `updated` timestamps) in the response. :param dict headers: A `dict` containing the request headers :return: A `DetailedResponse` containing the result, headers and HTTP status code. :rtype: DetailedResponse with `dict` result representing a `EntityCollection` object """ if workspace_id is None: raise ValueError('workspace_id must be provided') headers = {} sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME, service_version='V1', operation_id='list_entities') headers.update(sdk_headers) params = { 'version': self.version, 'export': export, 'page_limit': page_limit, 'include_count': include_count, 'sort': sort, 'cursor': cursor, 'include_audit': include_audit } if 'headers' in kwargs: headers.update(kwargs.get('headers')) del kwargs['headers'] headers['Accept'] = 'application/json' path_param_keys = ['workspace_id'] path_param_values = self.encode_path_vars(workspace_id) path_param_dict = dict(zip(path_param_keys, path_param_values)) url = '/v1/workspaces/{workspace_id}/entities'.format(**path_param_dict) request = self.prepare_request(method='GET', url=url, headers=headers, params=params) response = self.send(request, **kwargs) return response def create_entity(self, workspace_id: str, entity: str, *, description: str = None, metadata: dict = None, fuzzy_match: bool = None, values: List['CreateValue'] = None, include_audit: bool = None, **kwargs) -> DetailedResponse: """ Create entity. Create a new entity, or enable a system entity. If you want to create multiple entities with a single API call, consider using the **[Update workspace](#update-workspace)** method instead. :param str workspace_id: Unique identifier of the workspace. :param str entity: The name of the entity. This string must conform to the following restrictions: - It can contain only Unicode alphanumeric, underscore, and hyphen characters. - If you specify an entity name beginning with the reserved prefix `sys-`, it must be the name of a system entity that you want to enable. (Any entity content specified with the request is ignored.). :param str description: (optional) The description of the entity. This string cannot contain carriage return, newline, or tab characters. :param dict metadata: (optional) Any metadata related to the entity. :param bool fuzzy_match: (optional) Whether to use fuzzy matching for the entity. :param List[CreateValue] values: (optional) An array of objects describing the entity values. :param bool include_audit: (optional) Whether to include the audit properties (`created` and `updated` timestamps) in the response. :param dict headers: A `dict` containing the request headers :return: A `DetailedResponse` containing the result, headers and HTTP status code. :rtype: DetailedResponse with `dict` result representing a `Entity` object """ if workspace_id is None: raise ValueError('workspace_id must be provided') if entity is None: raise ValueError('entity must be provided') if values is not None: values = [convert_model(x) for x in values] headers = {} sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME, service_version='V1', operation_id='create_entity') headers.update(sdk_headers) params = {'version': self.version, 'include_audit': include_audit} data = { 'entity': entity, 'description': description, 'metadata': metadata, 'fuzzy_match': fuzzy_match, 'values': values } data = {k: v for (k, v) in data.items() if v is not None} data = json.dumps(data) headers['content-type'] = 'application/json' if 'headers' in kwargs: headers.update(kwargs.get('headers')) del kwargs['headers'] headers['Accept'] = 'application/json' path_param_keys = ['workspace_id'] path_param_values = self.encode_path_vars(workspace_id) path_param_dict = dict(zip(path_param_keys, path_param_values)) url = '/v1/workspaces/{workspace_id}/entities'.format(**path_param_dict) request = self.prepare_request(method='POST', url=url, headers=headers, params=params, data=data) response = self.send(request, **kwargs) return response def get_entity(self, workspace_id: str, entity: str, *, export: bool = None, include_audit: bool = None, **kwargs) -> DetailedResponse: """ Get entity. Get information about an entity, optionally including all entity content. :param str workspace_id: Unique identifier of the workspace. :param str entity: The name of the entity. :param bool export: (optional) Whether to include all element content in the returned data. If **export**=`false`, the returned data includes only information about the element itself. If **export**=`true`, all content, including subelements, is included. :param bool include_audit: (optional) Whether to include the audit properties (`created` and `updated` timestamps) in the response. :param dict headers: A `dict` containing the request headers :return: A `DetailedResponse` containing the result, headers and HTTP status code. :rtype: DetailedResponse with `dict` result representing a `Entity` object """ if workspace_id is None: raise ValueError('workspace_id must be provided') if entity is None: raise ValueError('entity must be provided') headers = {} sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME, service_version='V1', operation_id='get_entity') headers.update(sdk_headers) params = { 'version': self.version, 'export': export, 'include_audit': include_audit } if 'headers' in kwargs: headers.update(kwargs.get('headers')) del kwargs['headers'] headers['Accept'] = 'application/json' path_param_keys = ['workspace_id', 'entity'] path_param_values = self.encode_path_vars(workspace_id, entity) path_param_dict = dict(zip(path_param_keys, path_param_values)) url = '/v1/workspaces/{workspace_id}/entities/{entity}'.format( **path_param_dict) request = self.prepare_request(method='GET', url=url, headers=headers, params=params) response = self.send(request, **kwargs) return response def update_entity(self, workspace_id: str, entity: str, *, new_entity: str = None, new_description: str = None, new_metadata: dict = None, new_fuzzy_match: bool = None, new_values: List['CreateValue'] = None, append: bool = None, include_audit: bool = None, **kwargs) -> DetailedResponse: """ Update entity. Update an existing entity with new or modified data. You must provide component objects defining the content of the updated entity. If you want to update multiple entities with a single API call, consider using the **[Update workspace](#update-workspace)** method instead. :param str workspace_id: Unique identifier of the workspace. :param str entity: The name of the entity. :param str new_entity: (optional) The name of the entity. This string must conform to the following restrictions: - It can contain only Unicode alphanumeric, underscore, and hyphen characters. - It cannot begin with the reserved prefix `sys-`. :param str new_description: (optional) The description of the entity. This string cannot contain carriage return, newline, or tab characters. :param dict new_metadata: (optional) Any metadata related to the entity. :param bool new_fuzzy_match: (optional) Whether to use fuzzy matching for the entity. :param List[CreateValue] new_values: (optional) An array of objects describing the entity values. :param bool append: (optional) Whether the new data is to be appended to the existing data in the entity. If **append**=`false`, elements included in the new data completely replace the corresponding existing elements, including all subelements. For example, if the new data for the entity includes **values** and **append**=`false`, all existing values for the entity are discarded and replaced with the new values. If **append**=`true`, existing elements are preserved, and the new elements are added. If any elements in the new data collide with existing elements, the update request fails. :param bool include_audit: (optional) Whether to include the audit properties (`created` and `updated` timestamps) in the response. :param dict headers: A `dict` containing the request headers :return: A `DetailedResponse` containing the result, headers and HTTP status code. :rtype: DetailedResponse with `dict` result representing a `Entity` object """ if workspace_id is None: raise ValueError('workspace_id must be provided') if entity is None: raise ValueError('entity must be provided') if new_values is not None: new_values = [convert_model(x) for x in new_values] headers = {} sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME, service_version='V1', operation_id='update_entity') headers.update(sdk_headers) params = { 'version': self.version, 'append': append, 'include_audit': include_audit } data = { 'entity': new_entity, 'description': new_description, 'metadata': new_metadata, 'fuzzy_match': new_fuzzy_match, 'values': new_values } data = {k: v for (k, v) in data.items() if v is not None} data = json.dumps(data) headers['content-type'] = 'application/json' if 'headers' in kwargs: headers.update(kwargs.get('headers')) del kwargs['headers'] headers['Accept'] = 'application/json' path_param_keys = ['workspace_id', 'entity'] path_param_values = self.encode_path_vars(workspace_id, entity) path_param_dict = dict(zip(path_param_keys, path_param_values)) url = '/v1/workspaces/{workspace_id}/entities/{entity}'.format( **path_param_dict) request = self.prepare_request(method='POST', url=url, headers=headers, params=params, data=data) response = self.send(request, **kwargs) return response def delete_entity(self, workspace_id: str, entity: str, **kwargs) -> DetailedResponse: """ Delete entity. Delete an entity from a workspace, or disable a system entity. :param str workspace_id: Unique identifier of the workspace. :param str entity: The name of the entity. :param dict headers: A `dict` containing the request headers :return: A `DetailedResponse` containing the result, headers and HTTP status code. :rtype: DetailedResponse """ if workspace_id is None: raise ValueError('workspace_id must be provided') if entity is None: raise ValueError('entity must be provided') headers = {} sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME, service_version='V1', operation_id='delete_entity') headers.update(sdk_headers) params = {'version': self.version} if 'headers' in kwargs: headers.update(kwargs.get('headers')) del kwargs['headers'] headers['Accept'] = 'application/json' path_param_keys = ['workspace_id', 'entity'] path_param_values = self.encode_path_vars(workspace_id, entity) path_param_dict = dict(zip(path_param_keys, path_param_values)) url = '/v1/workspaces/{workspace_id}/entities/{entity}'.format( **path_param_dict) request = self.prepare_request(method='DELETE', url=url, headers=headers, params=params) response = self.send(request, **kwargs) return response ######################### # Mentions ######################### def list_mentions(self, workspace_id: str, entity: str, *, export: bool = None, include_audit: bool = None, **kwargs) -> DetailedResponse: """ List entity mentions. List mentions for a contextual entity. An entity mention is an occurrence of a contextual entity in the context of an intent user input example. :param str workspace_id: Unique identifier of the workspace. :param str entity: The name of the entity. :param bool export: (optional) Whether to include all element content in the returned data. If **export**=`false`, the returned data includes only information about the element itself. If **export**=`true`, all content, including subelements, is included. :param bool include_audit: (optional) Whether to include the audit properties (`created` and `updated` timestamps) in the response. :param dict headers: A `dict` containing the request headers :return: A `DetailedResponse` containing the result, headers and HTTP status code. :rtype: DetailedResponse with `dict` result representing a `EntityMentionCollection` object """ if workspace_id is None: raise ValueError('workspace_id must be provided') if entity is None: raise ValueError('entity must be provided') headers = {} sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME, service_version='V1', operation_id='list_mentions') headers.update(sdk_headers) params = { 'version': self.version, 'export': export, 'include_audit': include_audit } if 'headers' in kwargs: headers.update(kwargs.get('headers')) del kwargs['headers'] headers['Accept'] = 'application/json' path_param_keys = ['workspace_id', 'entity'] path_param_values = self.encode_path_vars(workspace_id, entity) path_param_dict = dict(zip(path_param_keys, path_param_values)) url = '/v1/workspaces/{workspace_id}/entities/{entity}/mentions'.format( **path_param_dict) request = self.prepare_request(method='GET', url=url, headers=headers, params=params) response = self.send(request, **kwargs) return response ######################### # Values ######################### def list_values(self, workspace_id: str, entity: str, *, export: bool = None, page_limit: int = None, include_count: bool = None, sort: str = None, cursor: str = None, include_audit: bool = None, **kwargs) -> DetailedResponse: """ List entity values. List the values for an entity. :param str workspace_id: Unique identifier of the workspace. :param str entity: The name of the entity. :param bool export: (optional) Whether to include all element content in the returned data. If **export**=`false`, the returned data includes only information about the element itself. If **export**=`true`, all content, including subelements, is included. :param int page_limit: (optional) The number of records to return in each page of results. :param bool include_count: (optional) Whether to include information about the number of records that satisfy the request, regardless of the page limit. If this parameter is `true`, the `pagination` object in the response includes the `total` property. :param str sort: (optional) The attribute by which returned entity values will be sorted. To reverse the sort order, prefix the value with a minus sign (`-`). :param str cursor: (optional) A token identifying the page of results to retrieve. :param bool include_audit: (optional) Whether to include the audit properties (`created` and `updated` timestamps) in the response. :param dict headers: A `dict` containing the request headers :return: A `DetailedResponse` containing the result, headers and HTTP status code. :rtype: DetailedResponse with `dict` result representing a `ValueCollection` object """ if workspace_id is None: raise ValueError('workspace_id must be provided') if entity is None: raise ValueError('entity must be provided') headers = {} sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME, service_version='V1', operation_id='list_values') headers.update(sdk_headers) params = { 'version': self.version, 'export': export, 'page_limit': page_limit, 'include_count': include_count, 'sort': sort, 'cursor': cursor, 'include_audit': include_audit } if 'headers' in kwargs: headers.update(kwargs.get('headers')) del kwargs['headers'] headers['Accept'] = 'application/json' path_param_keys = ['workspace_id', 'entity'] path_param_values = self.encode_path_vars(workspace_id, entity) path_param_dict = dict(zip(path_param_keys, path_param_values)) url = '/v1/workspaces/{workspace_id}/entities/{entity}/values'.format( **path_param_dict) request = self.prepare_request(method='GET', url=url, headers=headers, params=params) response = self.send(request, **kwargs) return response def create_value(self, workspace_id: str, entity: str, value: str, *, metadata: dict = None, type: str = None, synonyms: List[str] = None, patterns: List[str] = None, include_audit: bool = None, **kwargs) -> DetailedResponse: """ Create entity value. Create a new value for an entity. If you want to create multiple entity values with a single API call, consider using the **[Update entity](#update-entity)** method instead. :param str workspace_id: Unique identifier of the workspace. :param str entity: The name of the entity. :param str value: The text of the entity value. This string must conform to the following restrictions: - It cannot contain carriage return, newline, or tab characters. - It cannot consist of only whitespace characters. :param dict metadata: (optional) Any metadata related to the entity value. :param str type: (optional) Specifies the type of entity value. :param List[str] synonyms: (optional) An array of synonyms for the entity value. A value can specify either synonyms or patterns (depending on the value type), but not both. A synonym must conform to the following resrictions: - It cannot contain carriage return, newline, or tab characters. - It cannot consist of only whitespace characters. :param List[str] patterns: (optional) An array of patterns for the entity value. A value can specify either synonyms or patterns (depending on the value type), but not both. A pattern is a regular expression; for more information about how to specify a pattern, see the [documentation](https://cloud.ibm.com/docs/assistant?topic=assistant-entities#entities-create-dictionary-based). :param bool include_audit: (optional) Whether to include the audit properties (`created` and `updated` timestamps) in the response. :param dict headers: A `dict` containing the request headers :return: A `DetailedResponse` containing the result, headers and HTTP status code. :rtype: DetailedResponse with `dict` result representing a `Value` object """ if workspace_id is None: raise ValueError('workspace_id must be provided') if entity is None: raise ValueError('entity must be provided') if value is None: raise ValueError('value must be provided') headers = {} sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME, service_version='V1', operation_id='create_value') headers.update(sdk_headers) params = {'version': self.version, 'include_audit': include_audit} data = { 'value': value, 'metadata': metadata, 'type': type, 'synonyms': synonyms, 'patterns': patterns } data = {k: v for (k, v) in data.items() if v is not None} data = json.dumps(data) headers['content-type'] = 'application/json' if 'headers' in kwargs: headers.update(kwargs.get('headers')) del kwargs['headers'] headers['Accept'] = 'application/json' path_param_keys = ['workspace_id', 'entity'] path_param_values = self.encode_path_vars(workspace_id, entity) path_param_dict = dict(zip(path_param_keys, path_param_values)) url = '/v1/workspaces/{workspace_id}/entities/{entity}/values'.format( **path_param_dict) request = self.prepare_request(method='POST', url=url, headers=headers, params=params, data=data) response = self.send(request, **kwargs) return response def get_value(self, workspace_id: str, entity: str, value: str, *, export: bool = None, include_audit: bool = None, **kwargs) -> DetailedResponse: """ Get entity value. Get information about an entity value. :param str workspace_id: Unique identifier of the workspace. :param str entity: The name of the entity. :param str value: The text of the entity value. :param bool export: (optional) Whether to include all element content in the returned data. If **export**=`false`, the returned data includes only information about the element itself. If **export**=`true`, all content, including subelements, is included. :param bool include_audit: (optional) Whether to include the audit properties (`created` and `updated` timestamps) in the response. :param dict headers: A `dict` containing the request headers :return: A `DetailedResponse` containing the result, headers and HTTP status code. :rtype: DetailedResponse with `dict` result representing a `Value` object """ if workspace_id is None: raise ValueError('workspace_id must be provided') if entity is None: raise ValueError('entity must be provided') if value is None: raise ValueError('value must be provided') headers = {} sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME, service_version='V1', operation_id='get_value') headers.update(sdk_headers) params = { 'version': self.version, 'export': export, 'include_audit': include_audit } if 'headers' in kwargs: headers.update(kwargs.get('headers')) del kwargs['headers'] headers['Accept'] = 'application/json' path_param_keys = ['workspace_id', 'entity', 'value'] path_param_values = self.encode_path_vars(workspace_id, entity, value) path_param_dict = dict(zip(path_param_keys, path_param_values)) url = '/v1/workspaces/{workspace_id}/entities/{entity}/values/{value}'.format( **path_param_dict) request = self.prepare_request(method='GET', url=url, headers=headers, params=params) response = self.send(request, **kwargs) return response def update_value(self, workspace_id: str, entity: str, value: str, *, new_value: str = None, new_metadata: dict = None, new_type: str = None, new_synonyms: List[str] = None, new_patterns: List[str] = None, append: bool = None, include_audit: bool = None, **kwargs) -> DetailedResponse: """ Update entity value. Update an existing entity value with new or modified data. You must provide component objects defining the content of the updated entity value. If you want to update multiple entity values with a single API call, consider using the **[Update entity](#update-entity)** method instead. :param str workspace_id: Unique identifier of the workspace. :param str entity: The name of the entity. :param str value: The text of the entity value. :param str new_value: (optional) The text of the entity value. This string must conform to the following restrictions: - It cannot contain carriage return, newline, or tab characters. - It cannot consist of only whitespace characters. :param dict new_metadata: (optional) Any metadata related to the entity value. :param str new_type: (optional) Specifies the type of entity value. :param List[str] new_synonyms: (optional) An array of synonyms for the entity value. A value can specify either synonyms or patterns (depending on the value type), but not both. A synonym must conform to the following resrictions: - It cannot contain carriage return, newline, or tab characters. - It cannot consist of only whitespace characters. :param List[str] new_patterns: (optional) An array of patterns for the entity value. A value can specify either synonyms or patterns (depending on the value type), but not both. A pattern is a regular expression; for more information about how to specify a pattern, see the [documentation](https://cloud.ibm.com/docs/assistant?topic=assistant-entities#entities-create-dictionary-based). :param bool append: (optional) Whether the new data is to be appended to the existing data in the entity value. If **append**=`false`, elements included in the new data completely replace the corresponding existing elements, including all subelements. For example, if the new data for the entity value includes **synonyms** and **append**=`false`, all existing synonyms for the entity value are discarded and replaced with the new synonyms. If **append**=`true`, existing elements are preserved, and the new elements are added. If any elements in the new data collide with existing elements, the update request fails. :param bool include_audit: (optional) Whether to include the audit properties (`created` and `updated` timestamps) in the response. :param dict headers: A `dict` containing the request headers :return: A `DetailedResponse` containing the result, headers and HTTP status code. :rtype: DetailedResponse with `dict` result representing a `Value` object """ if workspace_id is None: raise ValueError('workspace_id must be provided') if entity is None: raise ValueError('entity must be provided') if value is None: raise ValueError('value must be provided') headers = {} sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME, service_version='V1', operation_id='update_value') headers.update(sdk_headers) params = { 'version': self.version, 'append': append, 'include_audit': include_audit } data = { 'value': new_value, 'metadata': new_metadata, 'type': new_type, 'synonyms': new_synonyms, 'patterns': new_patterns } data = {k: v for (k, v) in data.items() if v is not None} data = json.dumps(data) headers['content-type'] = 'application/json' if 'headers' in kwargs: headers.update(kwargs.get('headers')) del kwargs['headers'] headers['Accept'] = 'application/json' path_param_keys = ['workspace_id', 'entity', 'value'] path_param_values = self.encode_path_vars(workspace_id, entity, value) path_param_dict = dict(zip(path_param_keys, path_param_values)) url = '/v1/workspaces/{workspace_id}/entities/{entity}/values/{value}'.format( **path_param_dict) request = self.prepare_request(method='POST', url=url, headers=headers, params=params, data=data) response = self.send(request, **kwargs) return response def delete_value(self, workspace_id: str, entity: str, value: str, **kwargs) -> DetailedResponse: """ Delete entity value. Delete a value from an entity. :param str workspace_id: Unique identifier of the workspace. :param str entity: The name of the entity. :param str value: The text of the entity value. :param dict headers: A `dict` containing the request headers :return: A `DetailedResponse` containing the result, headers and HTTP status code. :rtype: DetailedResponse """ if workspace_id is None: raise ValueError('workspace_id must be provided') if entity is None: raise ValueError('entity must be provided') if value is None: raise ValueError('value must be provided') headers = {} sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME, service_version='V1', operation_id='delete_value') headers.update(sdk_headers) params = {'version': self.version} if 'headers' in kwargs: headers.update(kwargs.get('headers')) del kwargs['headers'] headers['Accept'] = 'application/json' path_param_keys = ['workspace_id', 'entity', 'value'] path_param_values = self.encode_path_vars(workspace_id, entity, value) path_param_dict = dict(zip(path_param_keys, path_param_values)) url = '/v1/workspaces/{workspace_id}/entities/{entity}/values/{value}'.format( **path_param_dict) request = self.prepare_request(method='DELETE', url=url, headers=headers, params=params) response = self.send(request, **kwargs) return response ######################### # Synonyms ######################### def list_synonyms(self, workspace_id: str, entity: str, value: str, *, page_limit: int = None, include_count: bool = None, sort: str = None, cursor: str = None, include_audit: bool = None, **kwargs) -> DetailedResponse: """ List entity value synonyms. List the synonyms for an entity value. :param str workspace_id: Unique identifier of the workspace. :param str entity: The name of the entity. :param str value: The text of the entity value. :param int page_limit: (optional) The number of records to return in each page of results. :param bool include_count: (optional) Whether to include information about the number of records that satisfy the request, regardless of the page limit. If this parameter is `true`, the `pagination` object in the response includes the `total` property. :param str sort: (optional) The attribute by which returned entity value synonyms will be sorted. To reverse the sort order, prefix the value with a minus sign (`-`). :param str cursor: (optional) A token identifying the page of results to retrieve. :param bool include_audit: (optional) Whether to include the audit properties (`created` and `updated` timestamps) in the response. :param dict headers: A `dict` containing the request headers :return: A `DetailedResponse` containing the result, headers and HTTP status code. :rtype: DetailedResponse with `dict` result representing a `SynonymCollection` object """ if workspace_id is None: raise ValueError('workspace_id must be provided') if entity is None: raise ValueError('entity must be provided') if value is None: raise ValueError('value must be provided') headers = {} sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME, service_version='V1', operation_id='list_synonyms') headers.update(sdk_headers) params = { 'version': self.version, 'page_limit': page_limit, 'include_count': include_count, 'sort': sort, 'cursor': cursor, 'include_audit': include_audit } if 'headers' in kwargs: headers.update(kwargs.get('headers')) del kwargs['headers'] headers['Accept'] = 'application/json' path_param_keys = ['workspace_id', 'entity', 'value'] path_param_values = self.encode_path_vars(workspace_id, entity, value) path_param_dict = dict(zip(path_param_keys, path_param_values)) url = '/v1/workspaces/{workspace_id}/entities/{entity}/values/{value}/synonyms'.format( **path_param_dict) request = self.prepare_request(method='GET', url=url, headers=headers, params=params) response = self.send(request, **kwargs) return response def create_synonym(self, workspace_id: str, entity: str, value: str, synonym: str, *, include_audit: bool = None, **kwargs) -> DetailedResponse: """ Create entity value synonym. Add a new synonym to an entity value. If you want to create multiple synonyms with a single API call, consider using the **[Update entity](#update-entity)** or **[Update entity value](#update-entity-value)** method instead. :param str workspace_id: Unique identifier of the workspace. :param str entity: The name of the entity. :param str value: The text of the entity value. :param str synonym: The text of the synonym. This string must conform to the following restrictions: - It cannot contain carriage return, newline, or tab characters. - It cannot consist of only whitespace characters. :param bool include_audit: (optional) Whether to include the audit properties (`created` and `updated` timestamps) in the response. :param dict headers: A `dict` containing the request headers :return: A `DetailedResponse` containing the result, headers and HTTP status code. :rtype: DetailedResponse with `dict` result representing a `Synonym` object """ if workspace_id is None: raise ValueError('workspace_id must be provided') if entity is None: raise ValueError('entity must be provided') if value is None: raise ValueError('value must be provided') if synonym is None: raise ValueError('synonym must be provided') headers = {} sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME, service_version='V1', operation_id='create_synonym') headers.update(sdk_headers) params = {'version': self.version, 'include_audit': include_audit} data = {'synonym': synonym} data = {k: v for (k, v) in data.items() if v is not None} data = json.dumps(data) headers['content-type'] = 'application/json' if 'headers' in kwargs: headers.update(kwargs.get('headers')) del kwargs['headers'] headers['Accept'] = 'application/json' path_param_keys = ['workspace_id', 'entity', 'value'] path_param_values = self.encode_path_vars(workspace_id, entity, value) path_param_dict = dict(zip(path_param_keys, path_param_values)) url = '/v1/workspaces/{workspace_id}/entities/{entity}/values/{value}/synonyms'.format( **path_param_dict) request = self.prepare_request(method='POST', url=url, headers=headers, params=params, data=data) response = self.send(request, **kwargs) return response def get_synonym(self, workspace_id: str, entity: str, value: str, synonym: str, *, include_audit: bool = None, **kwargs) -> DetailedResponse: """ Get entity value synonym. Get information about a synonym of an entity value. :param str workspace_id: Unique identifier of the workspace. :param str entity: The name of the entity. :param str value: The text of the entity value. :param str synonym: The text of the synonym. :param bool include_audit: (optional) Whether to include the audit properties (`created` and `updated` timestamps) in the response. :param dict headers: A `dict` containing the request headers :return: A `DetailedResponse` containing the result, headers and HTTP status code. :rtype: DetailedResponse with `dict` result representing a `Synonym` object """ if workspace_id is None: raise ValueError('workspace_id must be provided') if entity is None: raise ValueError('entity must be provided') if value is None: raise ValueError('value must be provided') if synonym is None: raise ValueError('synonym must be provided') headers = {} sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME, service_version='V1', operation_id='get_synonym') headers.update(sdk_headers) params = {'version': self.version, 'include_audit': include_audit} if 'headers' in kwargs: headers.update(kwargs.get('headers')) del kwargs['headers'] headers['Accept'] = 'application/json' path_param_keys = ['workspace_id', 'entity', 'value', 'synonym'] path_param_values = self.encode_path_vars(workspace_id, entity, value, synonym) path_param_dict = dict(zip(path_param_keys, path_param_values)) url = '/v1/workspaces/{workspace_id}/entities/{entity}/values/{value}/synonyms/{synonym}'.format( **path_param_dict) request = self.prepare_request(method='GET', url=url, headers=headers, params=params) response = self.send(request, **kwargs) return response def update_synonym(self, workspace_id: str, entity: str, value: str, synonym: str, *, new_synonym: str = None, include_audit: bool = None, **kwargs) -> DetailedResponse: """ Update entity value synonym. Update an existing entity value synonym with new text. If you want to update multiple synonyms with a single API call, consider using the **[Update entity](#update-entity)** or **[Update entity value](#update-entity-value)** method instead. :param str workspace_id: Unique identifier of the workspace. :param str entity: The name of the entity. :param str value: The text of the entity value. :param str synonym: The text of the synonym. :param str new_synonym: (optional) The text of the synonym. This string must conform to the following restrictions: - It cannot contain carriage return, newline, or tab characters. - It cannot consist of only whitespace characters. :param bool include_audit: (optional) Whether to include the audit properties (`created` and `updated` timestamps) in the response. :param dict headers: A `dict` containing the request headers :return: A `DetailedResponse` containing the result, headers and HTTP status code. :rtype: DetailedResponse with `dict` result representing a `Synonym` object """ if workspace_id is None: raise ValueError('workspace_id must be provided') if entity is None: raise ValueError('entity must be provided') if value is None: raise ValueError('value must be provided') if synonym is None: raise ValueError('synonym must be provided') headers = {} sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME, service_version='V1', operation_id='update_synonym') headers.update(sdk_headers) params = {'version': self.version, 'include_audit': include_audit} data = {'synonym': new_synonym} data = {k: v for (k, v) in data.items() if v is not None} data = json.dumps(data) headers['content-type'] = 'application/json' if 'headers' in kwargs: headers.update(kwargs.get('headers')) del kwargs['headers'] headers['Accept'] = 'application/json' path_param_keys = ['workspace_id', 'entity', 'value', 'synonym'] path_param_values = self.encode_path_vars(workspace_id, entity, value, synonym) path_param_dict = dict(zip(path_param_keys, path_param_values)) url = '/v1/workspaces/{workspace_id}/entities/{entity}/values/{value}/synonyms/{synonym}'.format( **path_param_dict) request = self.prepare_request(method='POST', url=url, headers=headers, params=params, data=data) response = self.send(request, **kwargs) return response def delete_synonym(self, workspace_id: str, entity: str, value: str, synonym: str, **kwargs) -> DetailedResponse: """ Delete entity value synonym. Delete a synonym from an entity value. :param str workspace_id: Unique identifier of the workspace. :param str entity: The name of the entity. :param str value: The text of the entity value. :param str synonym: The text of the synonym. :param dict headers: A `dict` containing the request headers :return: A `DetailedResponse` containing the result, headers and HTTP status code. :rtype: DetailedResponse """ if workspace_id is None: raise ValueError('workspace_id must be provided') if entity is None: raise ValueError('entity must be provided') if value is None: raise ValueError('value must be provided') if synonym is None: raise ValueError('synonym must be provided') headers = {} sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME, service_version='V1', operation_id='delete_synonym') headers.update(sdk_headers) params = {'version': self.version} if 'headers' in kwargs: headers.update(kwargs.get('headers')) del kwargs['headers'] headers['Accept'] = 'application/json' path_param_keys = ['workspace_id', 'entity', 'value', 'synonym'] path_param_values = self.encode_path_vars(workspace_id, entity, value, synonym) path_param_dict = dict(zip(path_param_keys, path_param_values)) url = '/v1/workspaces/{workspace_id}/entities/{entity}/values/{value}/synonyms/{synonym}'.format( **path_param_dict) request = self.prepare_request(method='DELETE', url=url, headers=headers, params=params) response = self.send(request, **kwargs) return response ######################### # Dialog nodes ######################### def list_dialog_nodes(self, workspace_id: str, *, page_limit: int = None, include_count: bool = None, sort: str = None, cursor: str = None, include_audit: bool = None, **kwargs) -> DetailedResponse: """ List dialog nodes. List the dialog nodes for a workspace. :param str workspace_id: Unique identifier of the workspace. :param int page_limit: (optional) The number of records to return in each page of results. :param bool include_count: (optional) Whether to include information about the number of records that satisfy the request, regardless of the page limit. If this parameter is `true`, the `pagination` object in the response includes the `total` property. :param str sort: (optional) The attribute by which returned dialog nodes will be sorted. To reverse the sort order, prefix the value with a minus sign (`-`). :param str cursor: (optional) A token identifying the page of results to retrieve. :param bool include_audit: (optional) Whether to include the audit properties (`created` and `updated` timestamps) in the response. :param dict headers: A `dict` containing the request headers :return: A `DetailedResponse` containing the result, headers and HTTP status code. :rtype: DetailedResponse with `dict` result representing a `DialogNodeCollection` object """ if workspace_id is None: raise ValueError('workspace_id must be provided') headers = {} sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME, service_version='V1', operation_id='list_dialog_nodes') headers.update(sdk_headers) params = { 'version': self.version, 'page_limit': page_limit, 'include_count': include_count, 'sort': sort, 'cursor': cursor, 'include_audit': include_audit } if 'headers' in kwargs: headers.update(kwargs.get('headers')) del kwargs['headers'] headers['Accept'] = 'application/json' path_param_keys = ['workspace_id'] path_param_values = self.encode_path_vars(workspace_id) path_param_dict = dict(zip(path_param_keys, path_param_values)) url = '/v1/workspaces/{workspace_id}/dialog_nodes'.format( **path_param_dict) request = self.prepare_request(method='GET', url=url, headers=headers, params=params) response = self.send(request, **kwargs) return response def create_dialog_node(self, workspace_id: str, dialog_node: str, *, description: str = None, conditions: str = None, parent: str = None, previous_sibling: str = None, output: 'DialogNodeOutput' = None, context: 'DialogNodeContext' = None, metadata: dict = None, next_step: 'DialogNodeNextStep' = None, title: str = None, type: str = None, event_name: str = None, variable: str = None, actions: List['DialogNodeAction'] = None, digress_in: str = None, digress_out: str = None, digress_out_slots: str = None, user_label: str = None, disambiguation_opt_out: bool = None, include_audit: bool = None, **kwargs) -> DetailedResponse: """ Create dialog node. Create a new dialog node. If you want to create multiple dialog nodes with a single API call, consider using the **[Update workspace](#update-workspace)** method instead. :param str workspace_id: Unique identifier of the workspace. :param str dialog_node: The unique ID of the dialog node. This is an internal identifier used to refer to the dialog node from other dialog nodes and in the diagnostic information included with message responses. This string can contain only Unicode alphanumeric, space, underscore, hyphen, and dot characters. :param str description: (optional) The description of the dialog node. This string cannot contain carriage return, newline, or tab characters. :param str conditions: (optional) The condition that will trigger the dialog node. This string cannot contain carriage return, newline, or tab characters. :param str parent: (optional) The unique ID of the parent dialog node. This property is omitted if the dialog node has no parent. :param str previous_sibling: (optional) The unique ID of the previous sibling dialog node. This property is omitted if the dialog node has no previous sibling. :param DialogNodeOutput output: (optional) The output of the dialog node. For more information about how to specify dialog node output, see the [documentation](https://cloud.ibm.com/docs/assistant?topic=assistant-dialog-overview#dialog-overview-responses). :param DialogNodeContext context: (optional) The context for the dialog node. :param dict metadata: (optional) The metadata for the dialog node. :param DialogNodeNextStep next_step: (optional) The next step to execute following this dialog node. :param str title: (optional) A human-readable name for the dialog node. If the node is included in disambiguation, this title is used to populate the **label** property of the corresponding suggestion in the `suggestion` response type (unless it is overridden by the **user_label** property). The title is also used to populate the **topic** property in the `connect_to_agent` response type. This string can contain only Unicode alphanumeric, space, underscore, hyphen, and dot characters. :param str type: (optional) How the dialog node is processed. :param str event_name: (optional) How an `event_handler` node is processed. :param str variable: (optional) The location in the dialog context where output is stored. :param List[DialogNodeAction] actions: (optional) An array of objects describing any actions to be invoked by the dialog node. :param str digress_in: (optional) Whether this top-level dialog node can be digressed into. :param str digress_out: (optional) Whether this dialog node can be returned to after a digression. :param str digress_out_slots: (optional) Whether the user can digress to top-level nodes while filling out slots. :param str user_label: (optional) A label that can be displayed externally to describe the purpose of the node to users. If set, this label is used to identify the node in disambiguation responses (overriding the value of the **title** property). :param bool disambiguation_opt_out: (optional) Whether the dialog node should be excluded from disambiguation suggestions. Valid only when **type**=`standard` or `frame`. :param bool include_audit: (optional) Whether to include the audit properties (`created` and `updated` timestamps) in the response. :param dict headers: A `dict` containing the request headers :return: A `DetailedResponse` containing the result, headers and HTTP status code. :rtype: DetailedResponse with `dict` result representing a `DialogNode` object """ if workspace_id is None: raise ValueError('workspace_id must be provided') if dialog_node is None: raise ValueError('dialog_node must be provided') if output is not None: output = convert_model(output) if context is not None: context = convert_model(context) if next_step is not None: next_step = convert_model(next_step) if actions is not None: actions = [convert_model(x) for x in actions] headers = {} sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME, service_version='V1', operation_id='create_dialog_node') headers.update(sdk_headers) params = {'version': self.version, 'include_audit': include_audit} data = { 'dialog_node': dialog_node, 'description': description, 'conditions': conditions, 'parent': parent, 'previous_sibling': previous_sibling, 'output': output, 'context': context, 'metadata': metadata, 'next_step': next_step, 'title': title, 'type': type, 'event_name': event_name, 'variable': variable, 'actions': actions, 'digress_in': digress_in, 'digress_out': digress_out, 'digress_out_slots': digress_out_slots, 'user_label': user_label, 'disambiguation_opt_out': disambiguation_opt_out } data = {k: v for (k, v) in data.items() if v is not None} data = json.dumps(data) headers['content-type'] = 'application/json' if 'headers' in kwargs: headers.update(kwargs.get('headers')) del kwargs['headers'] headers['Accept'] = 'application/json' path_param_keys = ['workspace_id'] path_param_values = self.encode_path_vars(workspace_id) path_param_dict = dict(zip(path_param_keys, path_param_values)) url = '/v1/workspaces/{workspace_id}/dialog_nodes'.format( **path_param_dict) request = self.prepare_request(method='POST', url=url, headers=headers, params=params, data=data) response = self.send(request, **kwargs) return response def get_dialog_node(self, workspace_id: str, dialog_node: str, *, include_audit: bool = None, **kwargs) -> DetailedResponse: """ Get dialog node. Get information about a dialog node. :param str workspace_id: Unique identifier of the workspace. :param str dialog_node: The dialog node ID (for example, `node_1_1479323581900`). :param bool include_audit: (optional) Whether to include the audit properties (`created` and `updated` timestamps) in the response. :param dict headers: A `dict` containing the request headers :return: A `DetailedResponse` containing the result, headers and HTTP status code. :rtype: DetailedResponse with `dict` result representing a `DialogNode` object """ if workspace_id is None: raise ValueError('workspace_id must be provided') if dialog_node is None: raise ValueError('dialog_node must be provided') headers = {} sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME, service_version='V1', operation_id='get_dialog_node') headers.update(sdk_headers) params = {'version': self.version, 'include_audit': include_audit} if 'headers' in kwargs: headers.update(kwargs.get('headers')) del kwargs['headers'] headers['Accept'] = 'application/json' path_param_keys = ['workspace_id', 'dialog_node'] path_param_values = self.encode_path_vars(workspace_id, dialog_node) path_param_dict = dict(zip(path_param_keys, path_param_values)) url = '/v1/workspaces/{workspace_id}/dialog_nodes/{dialog_node}'.format( **path_param_dict) request = self.prepare_request(method='GET', url=url, headers=headers, params=params) response = self.send(request, **kwargs) return response def update_dialog_node(self, workspace_id: str, dialog_node: str, *, new_dialog_node: str = None, new_description: str = None, new_conditions: str = None, new_parent: str = None, new_previous_sibling: str = None, new_output: 'DialogNodeOutput' = None, new_context: 'DialogNodeContext' = None, new_metadata: dict = None, new_next_step: 'DialogNodeNextStep' = None, new_title: str = None, new_type: str = None, new_event_name: str = None, new_variable: str = None, new_actions: List['DialogNodeAction'] = None, new_digress_in: str = None, new_digress_out: str = None, new_digress_out_slots: str = None, new_user_label: str = None, new_disambiguation_opt_out: bool = None, include_audit: bool = None, **kwargs) -> DetailedResponse: """ Update dialog node. Update an existing dialog node with new or modified data. If you want to update multiple dialog nodes with a single API call, consider using the **[Update workspace](#update-workspace)** method instead. :param str workspace_id: Unique identifier of the workspace. :param str dialog_node: The dialog node ID (for example, `node_1_1479323581900`). :param str new_dialog_node: (optional) The unique ID of the dialog node. This is an internal identifier used to refer to the dialog node from other dialog nodes and in the diagnostic information included with message responses. This string can contain only Unicode alphanumeric, space, underscore, hyphen, and dot characters. :param str new_description: (optional) The description of the dialog node. This string cannot contain carriage return, newline, or tab characters. :param str new_conditions: (optional) The condition that will trigger the dialog node. This string cannot contain carriage return, newline, or tab characters. :param str new_parent: (optional) The unique ID of the parent dialog node. This property is omitted if the dialog node has no parent. :param str new_previous_sibling: (optional) The unique ID of the previous sibling dialog node. This property is omitted if the dialog node has no previous sibling. :param DialogNodeOutput new_output: (optional) The output of the dialog node. For more information about how to specify dialog node output, see the [documentation](https://cloud.ibm.com/docs/assistant?topic=assistant-dialog-overview#dialog-overview-responses). :param DialogNodeContext new_context: (optional) The context for the dialog node. :param dict new_metadata: (optional) The metadata for the dialog node. :param DialogNodeNextStep new_next_step: (optional) The next step to execute following this dialog node. :param str new_title: (optional) A human-readable name for the dialog node. If the node is included in disambiguation, this title is used to populate the **label** property of the corresponding suggestion in the `suggestion` response type (unless it is overridden by the **user_label** property). The title is also used to populate the **topic** property in the `connect_to_agent` response type. This string can contain only Unicode alphanumeric, space, underscore, hyphen, and dot characters. :param str new_type: (optional) How the dialog node is processed. :param str new_event_name: (optional) How an `event_handler` node is processed. :param str new_variable: (optional) The location in the dialog context where output is stored. :param List[DialogNodeAction] new_actions: (optional) An array of objects describing any actions to be invoked by the dialog node. :param str new_digress_in: (optional) Whether this top-level dialog node can be digressed into. :param str new_digress_out: (optional) Whether this dialog node can be returned to after a digression. :param str new_digress_out_slots: (optional) Whether the user can digress to top-level nodes while filling out slots. :param str new_user_label: (optional) A label that can be displayed externally to describe the purpose of the node to users. If set, this label is used to identify the node in disambiguation responses (overriding the value of the **title** property). :param bool new_disambiguation_opt_out: (optional) Whether the dialog node should be excluded from disambiguation suggestions. Valid only when **type**=`standard` or `frame`. :param bool include_audit: (optional) Whether to include the audit properties (`created` and `updated` timestamps) in the response. :param dict headers: A `dict` containing the request headers :return: A `DetailedResponse` containing the result, headers and HTTP status code. :rtype: DetailedResponse with `dict` result representing a `DialogNode` object """ if workspace_id is None: raise ValueError('workspace_id must be provided') if dialog_node is None: raise ValueError('dialog_node must be provided') if new_output is not None: new_output = convert_model(new_output) if new_context is not None: new_context = convert_model(new_context) if new_next_step is not None: new_next_step = convert_model(new_next_step) if new_actions is not None: new_actions = [convert_model(x) for x in new_actions] headers = {} sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME, service_version='V1', operation_id='update_dialog_node') headers.update(sdk_headers) params = {'version': self.version, 'include_audit': include_audit} data = { 'dialog_node': new_dialog_node, 'description': new_description, 'conditions': new_conditions, 'parent': new_parent, 'previous_sibling': new_previous_sibling, 'output': new_output, 'context': new_context, 'metadata': new_metadata, 'next_step': new_next_step, 'title': new_title, 'type': new_type, 'event_name': new_event_name, 'variable': new_variable, 'actions': new_actions, 'digress_in': new_digress_in, 'digress_out': new_digress_out, 'digress_out_slots': new_digress_out_slots, 'user_label': new_user_label, 'disambiguation_opt_out': new_disambiguation_opt_out } data = {k: v for (k, v) in data.items() if v is not None} data = json.dumps(data) headers['content-type'] = 'application/json' if 'headers' in kwargs: headers.update(kwargs.get('headers')) del kwargs['headers'] headers['Accept'] = 'application/json' path_param_keys = ['workspace_id', 'dialog_node'] path_param_values = self.encode_path_vars(workspace_id, dialog_node) path_param_dict = dict(zip(path_param_keys, path_param_values)) url = '/v1/workspaces/{workspace_id}/dialog_nodes/{dialog_node}'.format( **path_param_dict) request = self.prepare_request(method='POST', url=url, headers=headers, params=params, data=data) response = self.send(request, **kwargs) return response def delete_dialog_node(self, workspace_id: str, dialog_node: str, **kwargs) -> DetailedResponse: """ Delete dialog node. Delete a dialog node from a workspace. :param str workspace_id: Unique identifier of the workspace. :param str dialog_node: The dialog node ID (for example, `node_1_1479323581900`). :param dict headers: A `dict` containing the request headers :return: A `DetailedResponse` containing the result, headers and HTTP status code. :rtype: DetailedResponse """ if workspace_id is None: raise ValueError('workspace_id must be provided') if dialog_node is None: raise ValueError('dialog_node must be provided') headers = {} sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME, service_version='V1', operation_id='delete_dialog_node') headers.update(sdk_headers) params = {'version': self.version} if 'headers' in kwargs: headers.update(kwargs.get('headers')) del kwargs['headers'] headers['Accept'] = 'application/json' path_param_keys = ['workspace_id', 'dialog_node'] path_param_values = self.encode_path_vars(workspace_id, dialog_node) path_param_dict = dict(zip(path_param_keys, path_param_values)) url = '/v1/workspaces/{workspace_id}/dialog_nodes/{dialog_node}'.format( **path_param_dict) request = self.prepare_request(method='DELETE', url=url, headers=headers, params=params) response = self.send(request, **kwargs) return response ######################### # Logs ######################### def list_logs(self, workspace_id: str, *, sort: str = None, filter: str = None, page_limit: int = None, cursor: str = None, **kwargs) -> DetailedResponse: """ List log events in a workspace. List the events from the log of a specific workspace. This method requires Manager access. **Note:** If you use the **cursor** parameter to retrieve results one page at a time, subsequent requests must be no more than 5 minutes apart. Any returned value for the **cursor** parameter becomes invalid after 5 minutes. For more information about using pagination, see [Pagination](#pagination). :param str workspace_id: Unique identifier of the workspace. :param str sort: (optional) How to sort the returned log events. You can sort by **request_timestamp**. To reverse the sort order, prefix the parameter value with a minus sign (`-`). :param str filter: (optional) A cacheable parameter that limits the results to those matching the specified filter. For more information, see the [documentation](https://cloud.ibm.com/docs/assistant?topic=assistant-filter-reference#filter-reference). :param int page_limit: (optional) The number of records to return in each page of results. :param str cursor: (optional) A token identifying the page of results to retrieve. :param dict headers: A `dict` containing the request headers :return: A `DetailedResponse` containing the result, headers and HTTP status code. :rtype: DetailedResponse with `dict` result representing a `LogCollection` object """ if workspace_id is None: raise ValueError('workspace_id must be provided') headers = {} sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME, service_version='V1', operation_id='list_logs') headers.update(sdk_headers) params = { 'version': self.version, 'sort': sort, 'filter': filter, 'page_limit': page_limit, 'cursor': cursor } if 'headers' in kwargs: headers.update(kwargs.get('headers')) del kwargs['headers'] headers['Accept'] = 'application/json' path_param_keys = ['workspace_id'] path_param_values = self.encode_path_vars(workspace_id) path_param_dict = dict(zip(path_param_keys, path_param_values)) url = '/v1/workspaces/{workspace_id}/logs'.format(**path_param_dict) request = self.prepare_request(method='GET', url=url, headers=headers, params=params) response = self.send(request, **kwargs) return response def list_all_logs(self, filter: str, *, sort: str = None, page_limit: int = None, cursor: str = None, **kwargs) -> DetailedResponse: """ List log events in all workspaces. List the events from the logs of all workspaces in the service instance. **Note:** If you use the **cursor** parameter to retrieve results one page at a time, subsequent requests must be no more than 5 minutes apart. Any returned value for the **cursor** parameter becomes invalid after 5 minutes. For more information about using pagination, see [Pagination](#pagination). :param str filter: A cacheable parameter that limits the results to those matching the specified filter. You must specify a filter query that includes a value for `language`, as well as a value for `request.context.system.assistant_id`, `workspace_id`, or `request.context.metadata.deployment`. These required filters must be specified using the exact match (`::`) operator. For more information, see the [documentation](https://cloud.ibm.com/docs/assistant?topic=assistant-filter-reference#filter-reference). :param str sort: (optional) How to sort the returned log events. You can sort by **request_timestamp**. To reverse the sort order, prefix the parameter value with a minus sign (`-`). :param int page_limit: (optional) The number of records to return in each page of results. :param str cursor: (optional) A token identifying the page of results to retrieve. :param dict headers: A `dict` containing the request headers :return: A `DetailedResponse` containing the result, headers and HTTP status code. :rtype: DetailedResponse with `dict` result representing a `LogCollection` object """ if filter is None: raise ValueError('filter must be provided') headers = {} sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME, service_version='V1', operation_id='list_all_logs') headers.update(sdk_headers) params = { 'version': self.version, 'filter': filter, 'sort': sort, 'page_limit': page_limit, 'cursor': cursor } if 'headers' in kwargs: headers.update(kwargs.get('headers')) del kwargs['headers'] headers['Accept'] = 'application/json' url = '/v1/logs' request = self.prepare_request(method='GET', url=url, headers=headers, params=params) response = self.send(request, **kwargs) return response ######################### # User data ######################### def delete_user_data(self, customer_id: str, **kwargs) -> DetailedResponse: """ Delete labeled data. Deletes all data associated with a specified customer ID. The method has no effect if no data is associated with the customer ID. You associate a customer ID with data by passing the `X-Watson-Metadata` header with a request that passes data. For more information about personal data and customer IDs, see [Information security](https://cloud.ibm.com/docs/assistant?topic=assistant-information-security#information-security). **Note:** This operation is intended only for deleting data associated with a single specific customer, not for deleting data associated with multiple customers or for any other purpose. For more information, see [Labeling and deleting data in Watson Assistant](https://cloud.ibm.com/docs/assistant?topic=assistant-information-security#information-security-gdpr-wa). :param str customer_id: The customer ID for which all data is to be deleted. :param dict headers: A `dict` containing the request headers :return: A `DetailedResponse` containing the result, headers and HTTP status code. :rtype: DetailedResponse """ if customer_id is None: raise ValueError('customer_id must be provided') headers = {} sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME, service_version='V1', operation_id='delete_user_data') headers.update(sdk_headers) params = {'version': self.version, 'customer_id': customer_id} if 'headers' in kwargs: headers.update(kwargs.get('headers')) del kwargs['headers'] headers['Accept'] = 'application/json' url = '/v1/user_data' request = self.prepare_request(method='DELETE', url=url, headers=headers, params=params) response = self.send(request, **kwargs) return response class ListWorkspacesEnums: """ Enums for list_workspaces parameters. """ class Sort(str, Enum): """ The attribute by which returned workspaces will be sorted. To reverse the sort order, prefix the value with a minus sign (`-`). """ NAME = 'name' UPDATED = 'updated' class GetWorkspaceEnums: """ Enums for get_workspace parameters. """ class Sort(str, Enum): """ Indicates how the returned workspace data will be sorted. This parameter is valid only if **export**=`true`. Specify `sort=stable` to sort all workspace objects by unique identifier, in ascending alphabetical order. """ STABLE = 'stable' class ExportWorkspaceAsyncEnums: """ Enums for export_workspace_async parameters. """ class Sort(str, Enum): """ Indicates how the returned workspace data will be sorted. Specify `sort=stable` to sort all workspace objects by unique identifier, in ascending alphabetical order. """ STABLE = 'stable' class ListIntentsEnums: """ Enums for list_intents parameters. """ class Sort(str, Enum): """ The attribute by which returned intents will be sorted. To reverse the sort order, prefix the value with a minus sign (`-`). """ INTENT = 'intent' UPDATED = 'updated' class ListExamplesEnums: """ Enums for list_examples parameters. """ class Sort(str, Enum): """ The attribute by which returned examples will be sorted. To reverse the sort order, prefix the value with a minus sign (`-`). """ TEXT = 'text' UPDATED = 'updated' class ListCounterexamplesEnums: """ Enums for list_counterexamples parameters. """ class Sort(str, Enum): """ The attribute by which returned counterexamples will be sorted. To reverse the sort order, prefix the value with a minus sign (`-`). """ TEXT = 'text' UPDATED = 'updated' class ListEntitiesEnums: """ Enums for list_entities parameters. """ class Sort(str, Enum): """ The attribute by which returned entities will be sorted. To reverse the sort order, prefix the value with a minus sign (`-`). """ ENTITY = 'entity' UPDATED = 'updated' class ListValuesEnums: """ Enums for list_values parameters. """ class Sort(str, Enum): """ The attribute by which returned entity values will be sorted. To reverse the sort order, prefix the value with a minus sign (`-`). """ VALUE = 'value' UPDATED = 'updated' class ListSynonymsEnums: """ Enums for list_synonyms parameters. """ class Sort(str, Enum): """ The attribute by which returned entity value synonyms will be sorted. To reverse the sort order, prefix the value with a minus sign (`-`). """ SYNONYM = 'synonym' UPDATED = 'updated' class ListDialogNodesEnums: """ Enums for list_dialog_nodes parameters. """ class Sort(str, Enum): """ The attribute by which returned dialog nodes will be sorted. To reverse the sort order, prefix the value with a minus sign (`-`). """ DIALOG_NODE = 'dialog_node' UPDATED = 'updated' ############################################################################## # Models ############################################################################## class AgentAvailabilityMessage(): """ AgentAvailabilityMessage. :attr str message: (optional) The text of the message. """ def __init__(self, *, message: str = None) -> None: """ Initialize a AgentAvailabilityMessage object. :param str message: (optional) The text of the message. """ self.message = message @classmethod def from_dict(cls, _dict: Dict) -> 'AgentAvailabilityMessage': """Initialize a AgentAvailabilityMessage object from a json dictionary.""" args = {} if 'message' in _dict: args['message'] = _dict.get('message') return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a AgentAvailabilityMessage object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'message') and self.message is not None: _dict['message'] = self.message return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this AgentAvailabilityMessage object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'AgentAvailabilityMessage') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'AgentAvailabilityMessage') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class BulkClassifyOutput(): """ BulkClassifyOutput. :attr BulkClassifyUtterance input: (optional) The user input utterance to classify. :attr List[RuntimeEntity] entities: (optional) An array of entities identified in the utterance. :attr List[RuntimeIntent] intents: (optional) An array of intents recognized in the utterance. """ def __init__(self, *, input: 'BulkClassifyUtterance' = None, entities: List['RuntimeEntity'] = None, intents: List['RuntimeIntent'] = None) -> None: """ Initialize a BulkClassifyOutput object. :param BulkClassifyUtterance input: (optional) The user input utterance to classify. :param List[RuntimeEntity] entities: (optional) An array of entities identified in the utterance. :param List[RuntimeIntent] intents: (optional) An array of intents recognized in the utterance. """ self.input = input self.entities = entities self.intents = intents @classmethod def from_dict(cls, _dict: Dict) -> 'BulkClassifyOutput': """Initialize a BulkClassifyOutput object from a json dictionary.""" args = {} if 'input' in _dict: args['input'] = BulkClassifyUtterance.from_dict(_dict.get('input')) if 'entities' in _dict: args['entities'] = [ RuntimeEntity.from_dict(x) for x in _dict.get('entities') ] if 'intents' in _dict: args['intents'] = [ RuntimeIntent.from_dict(x) for x in _dict.get('intents') ] return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a BulkClassifyOutput object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'input') and self.input is not None: _dict['input'] = self.input.to_dict() if hasattr(self, 'entities') and self.entities is not None: _dict['entities'] = [x.to_dict() for x in self.entities] if hasattr(self, 'intents') and self.intents is not None: _dict['intents'] = [x.to_dict() for x in self.intents] return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this BulkClassifyOutput object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'BulkClassifyOutput') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'BulkClassifyOutput') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class BulkClassifyResponse(): """ BulkClassifyResponse. :attr List[BulkClassifyOutput] output: (optional) An array of objects that contain classification information for the submitted input utterances. """ def __init__(self, *, output: List['BulkClassifyOutput'] = None) -> None: """ Initialize a BulkClassifyResponse object. :param List[BulkClassifyOutput] output: (optional) An array of objects that contain classification information for the submitted input utterances. """ self.output = output @classmethod def from_dict(cls, _dict: Dict) -> 'BulkClassifyResponse': """Initialize a BulkClassifyResponse object from a json dictionary.""" args = {} if 'output' in _dict: args['output'] = [ BulkClassifyOutput.from_dict(x) for x in _dict.get('output') ] return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a BulkClassifyResponse object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'output') and self.output is not None: _dict['output'] = [x.to_dict() for x in self.output] return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this BulkClassifyResponse object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'BulkClassifyResponse') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'BulkClassifyResponse') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class BulkClassifyUtterance(): """ The user input utterance to classify. :attr str text: The text of the input utterance. """ def __init__(self, text: str) -> None: """ Initialize a BulkClassifyUtterance object. :param str text: The text of the input utterance. """ self.text = text @classmethod def from_dict(cls, _dict: Dict) -> 'BulkClassifyUtterance': """Initialize a BulkClassifyUtterance object from a json dictionary.""" args = {} if 'text' in _dict: args['text'] = _dict.get('text') else: raise ValueError( 'Required property \'text\' not present in BulkClassifyUtterance JSON' ) return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a BulkClassifyUtterance object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'text') and self.text is not None: _dict['text'] = self.text return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this BulkClassifyUtterance object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'BulkClassifyUtterance') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'BulkClassifyUtterance') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class CaptureGroup(): """ A recognized capture group for a pattern-based entity. :attr str group: A recognized capture group for the entity. :attr List[int] location: (optional) Zero-based character offsets that indicate where the entity value begins and ends in the input text. """ def __init__(self, group: str, *, location: List[int] = None) -> None: """ Initialize a CaptureGroup object. :param str group: A recognized capture group for the entity. :param List[int] location: (optional) Zero-based character offsets that indicate where the entity value begins and ends in the input text. """ self.group = group self.location = location @classmethod def from_dict(cls, _dict: Dict) -> 'CaptureGroup': """Initialize a CaptureGroup object from a json dictionary.""" args = {} if 'group' in _dict: args['group'] = _dict.get('group') else: raise ValueError( 'Required property \'group\' not present in CaptureGroup JSON') if 'location' in _dict: args['location'] = _dict.get('location') return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a CaptureGroup object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'group') and self.group is not None: _dict['group'] = self.group if hasattr(self, 'location') and self.location is not None: _dict['location'] = self.location return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this CaptureGroup object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'CaptureGroup') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'CaptureGroup') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class ChannelTransferInfo(): """ Information used by an integration to transfer the conversation to a different channel. :attr ChannelTransferTarget target: An object specifying target channels available for the transfer. Each property of this object represents an available transfer target. Currently, the only supported property is **chat**, representing the web chat integration. """ def __init__(self, target: 'ChannelTransferTarget') -> None: """ Initialize a ChannelTransferInfo object. :param ChannelTransferTarget target: An object specifying target channels available for the transfer. Each property of this object represents an available transfer target. Currently, the only supported property is **chat**, representing the web chat integration. """ self.target = target @classmethod def from_dict(cls, _dict: Dict) -> 'ChannelTransferInfo': """Initialize a ChannelTransferInfo object from a json dictionary.""" args = {} if 'target' in _dict: args['target'] = ChannelTransferTarget.from_dict( _dict.get('target')) else: raise ValueError( 'Required property \'target\' not present in ChannelTransferInfo JSON' ) return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a ChannelTransferInfo object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'target') and self.target is not None: _dict['target'] = self.target.to_dict() return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this ChannelTransferInfo object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'ChannelTransferInfo') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'ChannelTransferInfo') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class ChannelTransferTarget(): """ An object specifying target channels available for the transfer. Each property of this object represents an available transfer target. Currently, the only supported property is **chat**, representing the web chat integration. :attr ChannelTransferTargetChat chat: (optional) Information for transferring to the web chat integration. """ def __init__(self, *, chat: 'ChannelTransferTargetChat' = None) -> None: """ Initialize a ChannelTransferTarget object. :param ChannelTransferTargetChat chat: (optional) Information for transferring to the web chat integration. """ self.chat = chat @classmethod def from_dict(cls, _dict: Dict) -> 'ChannelTransferTarget': """Initialize a ChannelTransferTarget object from a json dictionary.""" args = {} if 'chat' in _dict: args['chat'] = ChannelTransferTargetChat.from_dict( _dict.get('chat')) return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a ChannelTransferTarget object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'chat') and self.chat is not None: _dict['chat'] = self.chat.to_dict() return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this ChannelTransferTarget object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'ChannelTransferTarget') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'ChannelTransferTarget') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class ChannelTransferTargetChat(): """ Information for transferring to the web chat integration. :attr str url: (optional) The URL of the target web chat. """ def __init__(self, *, url: str = None) -> None: """ Initialize a ChannelTransferTargetChat object. :param str url: (optional) The URL of the target web chat. """ self.url = url @classmethod def from_dict(cls, _dict: Dict) -> 'ChannelTransferTargetChat': """Initialize a ChannelTransferTargetChat object from a json dictionary.""" args = {} if 'url' in _dict: args['url'] = _dict.get('url') return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a ChannelTransferTargetChat object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'url') and self.url is not None: _dict['url'] = self.url return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this ChannelTransferTargetChat object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'ChannelTransferTargetChat') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'ChannelTransferTargetChat') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class Context(): """ State information for the conversation. To maintain state, include the context from the previous response. :attr str conversation_id: (optional) The unique identifier of the conversation. :attr dict system: (optional) For internal use only. :attr MessageContextMetadata metadata: (optional) Metadata related to the message. """ # The set of defined properties for the class _properties = frozenset(['conversation_id', 'system', 'metadata']) def __init__(self, *, conversation_id: str = None, system: dict = None, metadata: 'MessageContextMetadata' = None, **kwargs) -> None: """ Initialize a Context object. :param str conversation_id: (optional) The unique identifier of the conversation. :param dict system: (optional) For internal use only. :param MessageContextMetadata metadata: (optional) Metadata related to the message. :param **kwargs: (optional) Any additional properties. """ self.conversation_id = conversation_id self.system = system self.metadata = metadata for _key, _value in kwargs.items(): setattr(self, _key, _value) @classmethod def from_dict(cls, _dict: Dict) -> 'Context': """Initialize a Context object from a json dictionary.""" args = {} if 'conversation_id' in _dict: args['conversation_id'] = _dict.get('conversation_id') if 'system' in _dict: args['system'] = _dict.get('system') if 'metadata' in _dict: args['metadata'] = MessageContextMetadata.from_dict( _dict.get('metadata')) args.update( {k: v for (k, v) in _dict.items() if k not in cls._properties}) return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a Context object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'conversation_id') and self.conversation_id is not None: _dict['conversation_id'] = self.conversation_id if hasattr(self, 'system') and self.system is not None: _dict['system'] = self.system if hasattr(self, 'metadata') and self.metadata is not None: _dict['metadata'] = self.metadata.to_dict() for _key in [ k for k in vars(self).keys() if k not in Context._properties ]: if getattr(self, _key, None) is not None: _dict[_key] = getattr(self, _key) return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def get_properties(self) -> Dict: """Return a dictionary of arbitrary properties from this instance of Context""" _dict = {} for _key in [ k for k in vars(self).keys() if k not in Context._properties ]: _dict[_key] = getattr(self, _key) return _dict def set_properties(self, _dict: dict): """Set a dictionary of arbitrary properties to this instance of Context""" for _key in [ k for k in vars(self).keys() if k not in Context._properties ]: delattr(self, _key) for _key, _value in _dict.items(): if _key not in Context._properties: setattr(self, _key, _value) def __str__(self) -> str: """Return a `str` version of this Context object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'Context') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'Context') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class Counterexample(): """ Counterexample. :attr str text: The text of a user input marked as irrelevant input. This string must conform to the following restrictions: - It cannot contain carriage return, newline, or tab characters. - It cannot consist of only whitespace characters. :attr datetime created: (optional) The timestamp for creation of the object. :attr datetime updated: (optional) The timestamp for the most recent update to the object. """ def __init__(self, text: str, *, created: datetime = None, updated: datetime = None) -> None: """ Initialize a Counterexample object. :param str text: The text of a user input marked as irrelevant input. This string must conform to the following restrictions: - It cannot contain carriage return, newline, or tab characters. - It cannot consist of only whitespace characters. """ self.text = text self.created = created self.updated = updated @classmethod def from_dict(cls, _dict: Dict) -> 'Counterexample': """Initialize a Counterexample object from a json dictionary.""" args = {} if 'text' in _dict: args['text'] = _dict.get('text') else: raise ValueError( 'Required property \'text\' not present in Counterexample JSON') if 'created' in _dict: args['created'] = string_to_datetime(_dict.get('created')) if 'updated' in _dict: args['updated'] = string_to_datetime(_dict.get('updated')) return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a Counterexample object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'text') and self.text is not None: _dict['text'] = self.text if hasattr(self, 'created') and getattr(self, 'created') is not None: _dict['created'] = datetime_to_string(getattr(self, 'created')) if hasattr(self, 'updated') and getattr(self, 'updated') is not None: _dict['updated'] = datetime_to_string(getattr(self, 'updated')) return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this Counterexample object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'Counterexample') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'Counterexample') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class CounterexampleCollection(): """ CounterexampleCollection. :attr List[Counterexample] counterexamples: An array of objects describing the examples marked as irrelevant input. :attr Pagination pagination: The pagination data for the returned objects. """ def __init__(self, counterexamples: List['Counterexample'], pagination: 'Pagination') -> None: """ Initialize a CounterexampleCollection object. :param List[Counterexample] counterexamples: An array of objects describing the examples marked as irrelevant input. :param Pagination pagination: The pagination data for the returned objects. """ self.counterexamples = counterexamples self.pagination = pagination @classmethod def from_dict(cls, _dict: Dict) -> 'CounterexampleCollection': """Initialize a CounterexampleCollection object from a json dictionary.""" args = {} if 'counterexamples' in _dict: args['counterexamples'] = [ Counterexample.from_dict(x) for x in _dict.get('counterexamples') ] else: raise ValueError( 'Required property \'counterexamples\' not present in CounterexampleCollection JSON' ) if 'pagination' in _dict: args['pagination'] = Pagination.from_dict(_dict.get('pagination')) else: raise ValueError( 'Required property \'pagination\' not present in CounterexampleCollection JSON' ) return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a CounterexampleCollection object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'counterexamples') and self.counterexamples is not None: _dict['counterexamples'] = [ x.to_dict() for x in self.counterexamples ] if hasattr(self, 'pagination') and self.pagination is not None: _dict['pagination'] = self.pagination.to_dict() return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this CounterexampleCollection object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'CounterexampleCollection') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'CounterexampleCollection') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class CreateEntity(): """ CreateEntity. :attr str entity: The name of the entity. This string must conform to the following restrictions: - It can contain only Unicode alphanumeric, underscore, and hyphen characters. - If you specify an entity name beginning with the reserved prefix `sys-`, it must be the name of a system entity that you want to enable. (Any entity content specified with the request is ignored.). :attr str description: (optional) The description of the entity. This string cannot contain carriage return, newline, or tab characters. :attr dict metadata: (optional) Any metadata related to the entity. :attr bool fuzzy_match: (optional) Whether to use fuzzy matching for the entity. :attr datetime created: (optional) The timestamp for creation of the object. :attr datetime updated: (optional) The timestamp for the most recent update to the object. :attr List[CreateValue] values: (optional) An array of objects describing the entity values. """ def __init__(self, entity: str, *, description: str = None, metadata: dict = None, fuzzy_match: bool = None, created: datetime = None, updated: datetime = None, values: List['CreateValue'] = None) -> None: """ Initialize a CreateEntity object. :param str entity: The name of the entity. This string must conform to the following restrictions: - It can contain only Unicode alphanumeric, underscore, and hyphen characters. - If you specify an entity name beginning with the reserved prefix `sys-`, it must be the name of a system entity that you want to enable. (Any entity content specified with the request is ignored.). :param str description: (optional) The description of the entity. This string cannot contain carriage return, newline, or tab characters. :param dict metadata: (optional) Any metadata related to the entity. :param bool fuzzy_match: (optional) Whether to use fuzzy matching for the entity. :param List[CreateValue] values: (optional) An array of objects describing the entity values. """ self.entity = entity self.description = description self.metadata = metadata self.fuzzy_match = fuzzy_match self.created = created self.updated = updated self.values = values @classmethod def from_dict(cls, _dict: Dict) -> 'CreateEntity': """Initialize a CreateEntity object from a json dictionary.""" args = {} if 'entity' in _dict: args['entity'] = _dict.get('entity') else: raise ValueError( 'Required property \'entity\' not present in CreateEntity JSON') if 'description' in _dict: args['description'] = _dict.get('description') if 'metadata' in _dict: args['metadata'] = _dict.get('metadata') if 'fuzzy_match' in _dict: args['fuzzy_match'] = _dict.get('fuzzy_match') if 'created' in _dict: args['created'] = string_to_datetime(_dict.get('created')) if 'updated' in _dict: args['updated'] = string_to_datetime(_dict.get('updated')) if 'values' in _dict: args['values'] = [ CreateValue.from_dict(x) for x in _dict.get('values') ] return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a CreateEntity object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'entity') and self.entity is not None: _dict['entity'] = self.entity if hasattr(self, 'description') and self.description is not None: _dict['description'] = self.description if hasattr(self, 'metadata') and self.metadata is not None: _dict['metadata'] = self.metadata if hasattr(self, 'fuzzy_match') and self.fuzzy_match is not None: _dict['fuzzy_match'] = self.fuzzy_match if hasattr(self, 'created') and getattr(self, 'created') is not None: _dict['created'] = datetime_to_string(getattr(self, 'created')) if hasattr(self, 'updated') and getattr(self, 'updated') is not None: _dict['updated'] = datetime_to_string(getattr(self, 'updated')) if hasattr(self, 'values') and self.values is not None: _dict['values'] = [x.to_dict() for x in self.values] return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this CreateEntity object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'CreateEntity') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'CreateEntity') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class CreateIntent(): """ CreateIntent. :attr str intent: The name of the intent. This string must conform to the following restrictions: - It can contain only Unicode alphanumeric, underscore, hyphen, and dot characters. - It cannot begin with the reserved prefix `sys-`. :attr str description: (optional) The description of the intent. This string cannot contain carriage return, newline, or tab characters. :attr datetime created: (optional) The timestamp for creation of the object. :attr datetime updated: (optional) The timestamp for the most recent update to the object. :attr List[Example] examples: (optional) An array of user input examples for the intent. """ def __init__(self, intent: str, *, description: str = None, created: datetime = None, updated: datetime = None, examples: List['Example'] = None) -> None: """ Initialize a CreateIntent object. :param str intent: The name of the intent. This string must conform to the following restrictions: - It can contain only Unicode alphanumeric, underscore, hyphen, and dot characters. - It cannot begin with the reserved prefix `sys-`. :param str description: (optional) The description of the intent. This string cannot contain carriage return, newline, or tab characters. :param List[Example] examples: (optional) An array of user input examples for the intent. """ self.intent = intent self.description = description self.created = created self.updated = updated self.examples = examples @classmethod def from_dict(cls, _dict: Dict) -> 'CreateIntent': """Initialize a CreateIntent object from a json dictionary.""" args = {} if 'intent' in _dict: args['intent'] = _dict.get('intent') else: raise ValueError( 'Required property \'intent\' not present in CreateIntent JSON') if 'description' in _dict: args['description'] = _dict.get('description') if 'created' in _dict: args['created'] = string_to_datetime(_dict.get('created')) if 'updated' in _dict: args['updated'] = string_to_datetime(_dict.get('updated')) if 'examples' in _dict: args['examples'] = [ Example.from_dict(x) for x in _dict.get('examples') ] return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a CreateIntent object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'intent') and self.intent is not None: _dict['intent'] = self.intent if hasattr(self, 'description') and self.description is not None: _dict['description'] = self.description if hasattr(self, 'created') and getattr(self, 'created') is not None: _dict['created'] = datetime_to_string(getattr(self, 'created')) if hasattr(self, 'updated') and getattr(self, 'updated') is not None: _dict['updated'] = datetime_to_string(getattr(self, 'updated')) if hasattr(self, 'examples') and self.examples is not None: _dict['examples'] = [x.to_dict() for x in self.examples] return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this CreateIntent object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'CreateIntent') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'CreateIntent') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class CreateValue(): """ CreateValue. :attr str value: The text of the entity value. This string must conform to the following restrictions: - It cannot contain carriage return, newline, or tab characters. - It cannot consist of only whitespace characters. :attr dict metadata: (optional) Any metadata related to the entity value. :attr str type: (optional) Specifies the type of entity value. :attr List[str] synonyms: (optional) An array of synonyms for the entity value. A value can specify either synonyms or patterns (depending on the value type), but not both. A synonym must conform to the following resrictions: - It cannot contain carriage return, newline, or tab characters. - It cannot consist of only whitespace characters. :attr List[str] patterns: (optional) An array of patterns for the entity value. A value can specify either synonyms or patterns (depending on the value type), but not both. A pattern is a regular expression; for more information about how to specify a pattern, see the [documentation](https://cloud.ibm.com/docs/assistant?topic=assistant-entities#entities-create-dictionary-based). :attr datetime created: (optional) The timestamp for creation of the object. :attr datetime updated: (optional) The timestamp for the most recent update to the object. """ def __init__(self, value: str, *, metadata: dict = None, type: str = None, synonyms: List[str] = None, patterns: List[str] = None, created: datetime = None, updated: datetime = None) -> None: """ Initialize a CreateValue object. :param str value: The text of the entity value. This string must conform to the following restrictions: - It cannot contain carriage return, newline, or tab characters. - It cannot consist of only whitespace characters. :param dict metadata: (optional) Any metadata related to the entity value. :param str type: (optional) Specifies the type of entity value. :param List[str] synonyms: (optional) An array of synonyms for the entity value. A value can specify either synonyms or patterns (depending on the value type), but not both. A synonym must conform to the following resrictions: - It cannot contain carriage return, newline, or tab characters. - It cannot consist of only whitespace characters. :param List[str] patterns: (optional) An array of patterns for the entity value. A value can specify either synonyms or patterns (depending on the value type), but not both. A pattern is a regular expression; for more information about how to specify a pattern, see the [documentation](https://cloud.ibm.com/docs/assistant?topic=assistant-entities#entities-create-dictionary-based). """ self.value = value self.metadata = metadata self.type = type self.synonyms = synonyms self.patterns = patterns self.created = created self.updated = updated @classmethod def from_dict(cls, _dict: Dict) -> 'CreateValue': """Initialize a CreateValue object from a json dictionary.""" args = {} if 'value' in _dict: args['value'] = _dict.get('value') else: raise ValueError( 'Required property \'value\' not present in CreateValue JSON') if 'metadata' in _dict: args['metadata'] = _dict.get('metadata') if 'type' in _dict: args['type'] = _dict.get('type') if 'synonyms' in _dict: args['synonyms'] = _dict.get('synonyms') if 'patterns' in _dict: args['patterns'] = _dict.get('patterns') if 'created' in _dict: args['created'] = string_to_datetime(_dict.get('created')) if 'updated' in _dict: args['updated'] = string_to_datetime(_dict.get('updated')) return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a CreateValue object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'value') and self.value is not None: _dict['value'] = self.value if hasattr(self, 'metadata') and self.metadata is not None: _dict['metadata'] = self.metadata if hasattr(self, 'type') and self.type is not None: _dict['type'] = self.type if hasattr(self, 'synonyms') and self.synonyms is not None: _dict['synonyms'] = self.synonyms if hasattr(self, 'patterns') and self.patterns is not None: _dict['patterns'] = self.patterns if hasattr(self, 'created') and getattr(self, 'created') is not None: _dict['created'] = datetime_to_string(getattr(self, 'created')) if hasattr(self, 'updated') and getattr(self, 'updated') is not None: _dict['updated'] = datetime_to_string(getattr(self, 'updated')) return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this CreateValue object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'CreateValue') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'CreateValue') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class TypeEnum(str, Enum): """ Specifies the type of entity value. """ SYNONYMS = 'synonyms' PATTERNS = 'patterns' class DialogNode(): """ DialogNode. :attr str dialog_node: The unique ID of the dialog node. This is an internal identifier used to refer to the dialog node from other dialog nodes and in the diagnostic information included with message responses. This string can contain only Unicode alphanumeric, space, underscore, hyphen, and dot characters. :attr str description: (optional) The description of the dialog node. This string cannot contain carriage return, newline, or tab characters. :attr str conditions: (optional) The condition that will trigger the dialog node. This string cannot contain carriage return, newline, or tab characters. :attr str parent: (optional) The unique ID of the parent dialog node. This property is omitted if the dialog node has no parent. :attr str previous_sibling: (optional) The unique ID of the previous sibling dialog node. This property is omitted if the dialog node has no previous sibling. :attr DialogNodeOutput output: (optional) The output of the dialog node. For more information about how to specify dialog node output, see the [documentation](https://cloud.ibm.com/docs/assistant?topic=assistant-dialog-overview#dialog-overview-responses). :attr DialogNodeContext context: (optional) The context for the dialog node. :attr dict metadata: (optional) The metadata for the dialog node. :attr DialogNodeNextStep next_step: (optional) The next step to execute following this dialog node. :attr str title: (optional) A human-readable name for the dialog node. If the node is included in disambiguation, this title is used to populate the **label** property of the corresponding suggestion in the `suggestion` response type (unless it is overridden by the **user_label** property). The title is also used to populate the **topic** property in the `connect_to_agent` response type. This string can contain only Unicode alphanumeric, space, underscore, hyphen, and dot characters. :attr str type: (optional) How the dialog node is processed. :attr str event_name: (optional) How an `event_handler` node is processed. :attr str variable: (optional) The location in the dialog context where output is stored. :attr List[DialogNodeAction] actions: (optional) An array of objects describing any actions to be invoked by the dialog node. :attr str digress_in: (optional) Whether this top-level dialog node can be digressed into. :attr str digress_out: (optional) Whether this dialog node can be returned to after a digression. :attr str digress_out_slots: (optional) Whether the user can digress to top-level nodes while filling out slots. :attr str user_label: (optional) A label that can be displayed externally to describe the purpose of the node to users. If set, this label is used to identify the node in disambiguation responses (overriding the value of the **title** property). :attr bool disambiguation_opt_out: (optional) Whether the dialog node should be excluded from disambiguation suggestions. Valid only when **type**=`standard` or `frame`. :attr bool disabled: (optional) For internal use only. :attr datetime created: (optional) The timestamp for creation of the object. :attr datetime updated: (optional) The timestamp for the most recent update to the object. """ def __init__(self, dialog_node: str, *, description: str = None, conditions: str = None, parent: str = None, previous_sibling: str = None, output: 'DialogNodeOutput' = None, context: 'DialogNodeContext' = None, metadata: dict = None, next_step: 'DialogNodeNextStep' = None, title: str = None, type: str = None, event_name: str = None, variable: str = None, actions: List['DialogNodeAction'] = None, digress_in: str = None, digress_out: str = None, digress_out_slots: str = None, user_label: str = None, disambiguation_opt_out: bool = None, disabled: bool = None, created: datetime = None, updated: datetime = None) -> None: """ Initialize a DialogNode object. :param str dialog_node: The unique ID of the dialog node. This is an internal identifier used to refer to the dialog node from other dialog nodes and in the diagnostic information included with message responses. This string can contain only Unicode alphanumeric, space, underscore, hyphen, and dot characters. :param str description: (optional) The description of the dialog node. This string cannot contain carriage return, newline, or tab characters. :param str conditions: (optional) The condition that will trigger the dialog node. This string cannot contain carriage return, newline, or tab characters. :param str parent: (optional) The unique ID of the parent dialog node. This property is omitted if the dialog node has no parent. :param str previous_sibling: (optional) The unique ID of the previous sibling dialog node. This property is omitted if the dialog node has no previous sibling. :param DialogNodeOutput output: (optional) The output of the dialog node. For more information about how to specify dialog node output, see the [documentation](https://cloud.ibm.com/docs/assistant?topic=assistant-dialog-overview#dialog-overview-responses). :param DialogNodeContext context: (optional) The context for the dialog node. :param dict metadata: (optional) The metadata for the dialog node. :param DialogNodeNextStep next_step: (optional) The next step to execute following this dialog node. :param str title: (optional) A human-readable name for the dialog node. If the node is included in disambiguation, this title is used to populate the **label** property of the corresponding suggestion in the `suggestion` response type (unless it is overridden by the **user_label** property). The title is also used to populate the **topic** property in the `connect_to_agent` response type. This string can contain only Unicode alphanumeric, space, underscore, hyphen, and dot characters. :param str type: (optional) How the dialog node is processed. :param str event_name: (optional) How an `event_handler` node is processed. :param str variable: (optional) The location in the dialog context where output is stored. :param List[DialogNodeAction] actions: (optional) An array of objects describing any actions to be invoked by the dialog node. :param str digress_in: (optional) Whether this top-level dialog node can be digressed into. :param str digress_out: (optional) Whether this dialog node can be returned to after a digression. :param str digress_out_slots: (optional) Whether the user can digress to top-level nodes while filling out slots. :param str user_label: (optional) A label that can be displayed externally to describe the purpose of the node to users. If set, this label is used to identify the node in disambiguation responses (overriding the value of the **title** property). :param bool disambiguation_opt_out: (optional) Whether the dialog node should be excluded from disambiguation suggestions. Valid only when **type**=`standard` or `frame`. """ self.dialog_node = dialog_node self.description = description self.conditions = conditions self.parent = parent self.previous_sibling = previous_sibling self.output = output self.context = context self.metadata = metadata self.next_step = next_step self.title = title self.type = type self.event_name = event_name self.variable = variable self.actions = actions self.digress_in = digress_in self.digress_out = digress_out self.digress_out_slots = digress_out_slots self.user_label = user_label self.disambiguation_opt_out = disambiguation_opt_out self.disabled = disabled self.created = created self.updated = updated @classmethod def from_dict(cls, _dict: Dict) -> 'DialogNode': """Initialize a DialogNode object from a json dictionary.""" args = {} if 'dialog_node' in _dict: args['dialog_node'] = _dict.get('dialog_node') else: raise ValueError( 'Required property \'dialog_node\' not present in DialogNode JSON' ) if 'description' in _dict: args['description'] = _dict.get('description') if 'conditions' in _dict: args['conditions'] = _dict.get('conditions') if 'parent' in _dict: args['parent'] = _dict.get('parent') if 'previous_sibling' in _dict: args['previous_sibling'] = _dict.get('previous_sibling') if 'output' in _dict: args['output'] = DialogNodeOutput.from_dict(_dict.get('output')) if 'context' in _dict: args['context'] = DialogNodeContext.from_dict(_dict.get('context')) if 'metadata' in _dict: args['metadata'] = _dict.get('metadata') if 'next_step' in _dict: args['next_step'] = DialogNodeNextStep.from_dict( _dict.get('next_step')) if 'title' in _dict: args['title'] = _dict.get('title') if 'type' in _dict: args['type'] = _dict.get('type') if 'event_name' in _dict: args['event_name'] = _dict.get('event_name') if 'variable' in _dict: args['variable'] = _dict.get('variable') if 'actions' in _dict: args['actions'] = [ DialogNodeAction.from_dict(x) for x in _dict.get('actions') ] if 'digress_in' in _dict: args['digress_in'] = _dict.get('digress_in') if 'digress_out' in _dict: args['digress_out'] = _dict.get('digress_out') if 'digress_out_slots' in _dict: args['digress_out_slots'] = _dict.get('digress_out_slots') if 'user_label' in _dict: args['user_label'] = _dict.get('user_label') if 'disambiguation_opt_out' in _dict: args['disambiguation_opt_out'] = _dict.get('disambiguation_opt_out') if 'disabled' in _dict: args['disabled'] = _dict.get('disabled') if 'created' in _dict: args['created'] = string_to_datetime(_dict.get('created')) if 'updated' in _dict: args['updated'] = string_to_datetime(_dict.get('updated')) return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a DialogNode object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'dialog_node') and self.dialog_node is not None: _dict['dialog_node'] = self.dialog_node if hasattr(self, 'description') and self.description is not None: _dict['description'] = self.description if hasattr(self, 'conditions') and self.conditions is not None: _dict['conditions'] = self.conditions if hasattr(self, 'parent') and self.parent is not None: _dict['parent'] = self.parent if hasattr(self, 'previous_sibling') and self.previous_sibling is not None: _dict['previous_sibling'] = self.previous_sibling if hasattr(self, 'output') and self.output is not None: _dict['output'] = self.output.to_dict() if hasattr(self, 'context') and self.context is not None: _dict['context'] = self.context.to_dict() if hasattr(self, 'metadata') and self.metadata is not None: _dict['metadata'] = self.metadata if hasattr(self, 'next_step') and self.next_step is not None: _dict['next_step'] = self.next_step.to_dict() if hasattr(self, 'title') and self.title is not None: _dict['title'] = self.title if hasattr(self, 'type') and self.type is not None: _dict['type'] = self.type if hasattr(self, 'event_name') and self.event_name is not None: _dict['event_name'] = self.event_name if hasattr(self, 'variable') and self.variable is not None: _dict['variable'] = self.variable if hasattr(self, 'actions') and self.actions is not None: _dict['actions'] = [x.to_dict() for x in self.actions] if hasattr(self, 'digress_in') and self.digress_in is not None: _dict['digress_in'] = self.digress_in if hasattr(self, 'digress_out') and self.digress_out is not None: _dict['digress_out'] = self.digress_out if hasattr(self, 'digress_out_slots') and self.digress_out_slots is not None: _dict['digress_out_slots'] = self.digress_out_slots if hasattr(self, 'user_label') and self.user_label is not None: _dict['user_label'] = self.user_label if hasattr(self, 'disambiguation_opt_out' ) and self.disambiguation_opt_out is not None: _dict['disambiguation_opt_out'] = self.disambiguation_opt_out if hasattr(self, 'disabled') and getattr(self, 'disabled') is not None: _dict['disabled'] = getattr(self, 'disabled') if hasattr(self, 'created') and getattr(self, 'created') is not None: _dict['created'] = datetime_to_string(getattr(self, 'created')) if hasattr(self, 'updated') and getattr(self, 'updated') is not None: _dict['updated'] = datetime_to_string(getattr(self, 'updated')) return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this DialogNode object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'DialogNode') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'DialogNode') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class TypeEnum(str, Enum): """ How the dialog node is processed. """ STANDARD = 'standard' EVENT_HANDLER = 'event_handler' FRAME = 'frame' SLOT = 'slot' RESPONSE_CONDITION = 'response_condition' FOLDER = 'folder' class EventNameEnum(str, Enum): """ How an `event_handler` node is processed. """ FOCUS = 'focus' INPUT = 'input' FILLED = 'filled' VALIDATE = 'validate' FILLED_MULTIPLE = 'filled_multiple' GENERIC = 'generic' NOMATCH = 'nomatch' NOMATCH_RESPONSES_DEPLETED = 'nomatch_responses_depleted' DIGRESSION_RETURN_PROMPT = 'digression_return_prompt' class DigressInEnum(str, Enum): """ Whether this top-level dialog node can be digressed into. """ NOT_AVAILABLE = 'not_available' RETURNS = 'returns' DOES_NOT_RETURN = 'does_not_return' class DigressOutEnum(str, Enum): """ Whether this dialog node can be returned to after a digression. """ ALLOW_RETURNING = 'allow_returning' ALLOW_ALL = 'allow_all' ALLOW_ALL_NEVER_RETURN = 'allow_all_never_return' class DigressOutSlotsEnum(str, Enum): """ Whether the user can digress to top-level nodes while filling out slots. """ NOT_ALLOWED = 'not_allowed' ALLOW_RETURNING = 'allow_returning' ALLOW_ALL = 'allow_all' class DialogNodeAction(): """ DialogNodeAction. :attr str name: The name of the action. :attr str type: (optional) The type of action to invoke. :attr dict parameters: (optional) A map of key/value pairs to be provided to the action. :attr str result_variable: The location in the dialog context where the result of the action is stored. :attr str credentials: (optional) The name of the context variable that the client application will use to pass in credentials for the action. """ def __init__(self, name: str, result_variable: str, *, type: str = None, parameters: dict = None, credentials: str = None) -> None: """ Initialize a DialogNodeAction object. :param str name: The name of the action. :param str result_variable: The location in the dialog context where the result of the action is stored. :param str type: (optional) The type of action to invoke. :param dict parameters: (optional) A map of key/value pairs to be provided to the action. :param str credentials: (optional) The name of the context variable that the client application will use to pass in credentials for the action. """ self.name = name self.type = type self.parameters = parameters self.result_variable = result_variable self.credentials = credentials @classmethod def from_dict(cls, _dict: Dict) -> 'DialogNodeAction': """Initialize a DialogNodeAction object from a json dictionary.""" args = {} if 'name' in _dict: args['name'] = _dict.get('name') else: raise ValueError( 'Required property \'name\' not present in DialogNodeAction JSON' ) if 'type' in _dict: args['type'] = _dict.get('type') if 'parameters' in _dict: args['parameters'] = _dict.get('parameters') if 'result_variable' in _dict: args['result_variable'] = _dict.get('result_variable') else: raise ValueError( 'Required property \'result_variable\' not present in DialogNodeAction JSON' ) if 'credentials' in _dict: args['credentials'] = _dict.get('credentials') return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a DialogNodeAction object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'name') and self.name is not None: _dict['name'] = self.name if hasattr(self, 'type') and self.type is not None: _dict['type'] = self.type if hasattr(self, 'parameters') and self.parameters is not None: _dict['parameters'] = self.parameters if hasattr(self, 'result_variable') and self.result_variable is not None: _dict['result_variable'] = self.result_variable if hasattr(self, 'credentials') and self.credentials is not None: _dict['credentials'] = self.credentials return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this DialogNodeAction object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'DialogNodeAction') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'DialogNodeAction') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class TypeEnum(str, Enum): """ The type of action to invoke. """ CLIENT = 'client' SERVER = 'server' CLOUD_FUNCTION = 'cloud_function' WEB_ACTION = 'web_action' WEBHOOK = 'webhook' class DialogNodeCollection(): """ An array of dialog nodes. :attr List[DialogNode] dialog_nodes: An array of objects describing the dialog nodes defined for the workspace. :attr Pagination pagination: The pagination data for the returned objects. """ def __init__(self, dialog_nodes: List['DialogNode'], pagination: 'Pagination') -> None: """ Initialize a DialogNodeCollection object. :param List[DialogNode] dialog_nodes: An array of objects describing the dialog nodes defined for the workspace. :param Pagination pagination: The pagination data for the returned objects. """ self.dialog_nodes = dialog_nodes self.pagination = pagination @classmethod def from_dict(cls, _dict: Dict) -> 'DialogNodeCollection': """Initialize a DialogNodeCollection object from a json dictionary.""" args = {} if 'dialog_nodes' in _dict: args['dialog_nodes'] = [ DialogNode.from_dict(x) for x in _dict.get('dialog_nodes') ] else: raise ValueError( 'Required property \'dialog_nodes\' not present in DialogNodeCollection JSON' ) if 'pagination' in _dict: args['pagination'] = Pagination.from_dict(_dict.get('pagination')) else: raise ValueError( 'Required property \'pagination\' not present in DialogNodeCollection JSON' ) return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a DialogNodeCollection object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'dialog_nodes') and self.dialog_nodes is not None: _dict['dialog_nodes'] = [x.to_dict() for x in self.dialog_nodes] if hasattr(self, 'pagination') and self.pagination is not None: _dict['pagination'] = self.pagination.to_dict() return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this DialogNodeCollection object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'DialogNodeCollection') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'DialogNodeCollection') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class DialogNodeContext(): """ The context for the dialog node. :attr dict integrations: (optional) Context data intended for specific integrations. """ # The set of defined properties for the class _properties = frozenset(['integrations']) def __init__(self, *, integrations: dict = None, **kwargs) -> None: """ Initialize a DialogNodeContext object. :param dict integrations: (optional) Context data intended for specific integrations. :param **kwargs: (optional) Any additional properties. """ self.integrations = integrations for _key, _value in kwargs.items(): setattr(self, _key, _value) @classmethod def from_dict(cls, _dict: Dict) -> 'DialogNodeContext': """Initialize a DialogNodeContext object from a json dictionary.""" args = {} if 'integrations' in _dict: args['integrations'] = _dict.get('integrations') args.update( {k: v for (k, v) in _dict.items() if k not in cls._properties}) return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a DialogNodeContext object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'integrations') and self.integrations is not None: _dict['integrations'] = self.integrations for _key in [ k for k in vars(self).keys() if k not in DialogNodeContext._properties ]: if getattr(self, _key, None) is not None: _dict[_key] = getattr(self, _key) return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def get_properties(self) -> Dict: """Return a dictionary of arbitrary properties from this instance of DialogNodeContext""" _dict = {} for _key in [ k for k in vars(self).keys() if k not in DialogNodeContext._properties ]: _dict[_key] = getattr(self, _key) return _dict def set_properties(self, _dict: dict): """Set a dictionary of arbitrary properties to this instance of DialogNodeContext""" for _key in [ k for k in vars(self).keys() if k not in DialogNodeContext._properties ]: delattr(self, _key) for _key, _value in _dict.items(): if _key not in DialogNodeContext._properties: setattr(self, _key, _value) def __str__(self) -> str: """Return a `str` version of this DialogNodeContext object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'DialogNodeContext') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'DialogNodeContext') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class DialogNodeNextStep(): """ The next step to execute following this dialog node. :attr str behavior: What happens after the dialog node completes. The valid values depend on the node type: - The following values are valid for any node: - `get_user_input` - `skip_user_input` - `jump_to` - If the node is of type `event_handler` and its parent node is of type `slot` or `frame`, additional values are also valid: - if **event_name**=`filled` and the type of the parent node is `slot`: - `reprompt` - `skip_all_slots` - if **event_name**=`nomatch` and the type of the parent node is `slot`: - `reprompt` - `skip_slot` - `skip_all_slots` - if **event_name**=`generic` and the type of the parent node is `frame`: - `reprompt` - `skip_slot` - `skip_all_slots` If you specify `jump_to`, then you must also specify a value for the `dialog_node` property. :attr str dialog_node: (optional) The unique ID of the dialog node to process next. This parameter is required if **behavior**=`jump_to`. :attr str selector: (optional) Which part of the dialog node to process next. """ def __init__(self, behavior: str, *, dialog_node: str = None, selector: str = None) -> None: """ Initialize a DialogNodeNextStep object. :param str behavior: What happens after the dialog node completes. The valid values depend on the node type: - The following values are valid for any node: - `get_user_input` - `skip_user_input` - `jump_to` - If the node is of type `event_handler` and its parent node is of type `slot` or `frame`, additional values are also valid: - if **event_name**=`filled` and the type of the parent node is `slot`: - `reprompt` - `skip_all_slots` - if **event_name**=`nomatch` and the type of the parent node is `slot`: - `reprompt` - `skip_slot` - `skip_all_slots` - if **event_name**=`generic` and the type of the parent node is `frame`: - `reprompt` - `skip_slot` - `skip_all_slots` If you specify `jump_to`, then you must also specify a value for the `dialog_node` property. :param str dialog_node: (optional) The unique ID of the dialog node to process next. This parameter is required if **behavior**=`jump_to`. :param str selector: (optional) Which part of the dialog node to process next. """ self.behavior = behavior self.dialog_node = dialog_node self.selector = selector @classmethod def from_dict(cls, _dict: Dict) -> 'DialogNodeNextStep': """Initialize a DialogNodeNextStep object from a json dictionary.""" args = {} if 'behavior' in _dict: args['behavior'] = _dict.get('behavior') else: raise ValueError( 'Required property \'behavior\' not present in DialogNodeNextStep JSON' ) if 'dialog_node' in _dict: args['dialog_node'] = _dict.get('dialog_node') if 'selector' in _dict: args['selector'] = _dict.get('selector') return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a DialogNodeNextStep object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'behavior') and self.behavior is not None: _dict['behavior'] = self.behavior if hasattr(self, 'dialog_node') and self.dialog_node is not None: _dict['dialog_node'] = self.dialog_node if hasattr(self, 'selector') and self.selector is not None: _dict['selector'] = self.selector return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this DialogNodeNextStep object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'DialogNodeNextStep') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'DialogNodeNextStep') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class BehaviorEnum(str, Enum): """ What happens after the dialog node completes. The valid values depend on the node type: - The following values are valid for any node: - `get_user_input` - `skip_user_input` - `jump_to` - If the node is of type `event_handler` and its parent node is of type `slot` or `frame`, additional values are also valid: - if **event_name**=`filled` and the type of the parent node is `slot`: - `reprompt` - `skip_all_slots` - if **event_name**=`nomatch` and the type of the parent node is `slot`: - `reprompt` - `skip_slot` - `skip_all_slots` - if **event_name**=`generic` and the type of the parent node is `frame`: - `reprompt` - `skip_slot` - `skip_all_slots` If you specify `jump_to`, then you must also specify a value for the `dialog_node` property. """ GET_USER_INPUT = 'get_user_input' SKIP_USER_INPUT = 'skip_user_input' JUMP_TO = 'jump_to' REPROMPT = 'reprompt' SKIP_SLOT = 'skip_slot' SKIP_ALL_SLOTS = 'skip_all_slots' class SelectorEnum(str, Enum): """ Which part of the dialog node to process next. """ CONDITION = 'condition' CLIENT = 'client' USER_INPUT = 'user_input' BODY = 'body' class DialogNodeOutput(): """ The output of the dialog node. For more information about how to specify dialog node output, see the [documentation](https://cloud.ibm.com/docs/assistant?topic=assistant-dialog-overview#dialog-overview-responses). :attr List[DialogNodeOutputGeneric] generic: (optional) An array of objects describing the output defined for the dialog node. :attr dict integrations: (optional) Output intended for specific integrations. For more information, see the [documentation](https://cloud.ibm.com/docs/assistant?topic=assistant-dialog-responses-json). :attr DialogNodeOutputModifiers modifiers: (optional) Options that modify how specified output is handled. """ # The set of defined properties for the class _properties = frozenset(['generic', 'integrations', 'modifiers']) def __init__(self, *, generic: List['DialogNodeOutputGeneric'] = None, integrations: dict = None, modifiers: 'DialogNodeOutputModifiers' = None, **kwargs) -> None: """ Initialize a DialogNodeOutput object. :param List[DialogNodeOutputGeneric] generic: (optional) An array of objects describing the output defined for the dialog node. :param dict integrations: (optional) Output intended for specific integrations. For more information, see the [documentation](https://cloud.ibm.com/docs/assistant?topic=assistant-dialog-responses-json). :param DialogNodeOutputModifiers modifiers: (optional) Options that modify how specified output is handled. :param **kwargs: (optional) Any additional properties. """ self.generic = generic self.integrations = integrations self.modifiers = modifiers for _key, _value in kwargs.items(): setattr(self, _key, _value) @classmethod def from_dict(cls, _dict: Dict) -> 'DialogNodeOutput': """Initialize a DialogNodeOutput object from a json dictionary.""" args = {} if 'generic' in _dict: args['generic'] = [ DialogNodeOutputGeneric.from_dict(x) for x in _dict.get('generic') ] if 'integrations' in _dict: args['integrations'] = _dict.get('integrations') if 'modifiers' in _dict: args['modifiers'] = DialogNodeOutputModifiers.from_dict( _dict.get('modifiers')) args.update( {k: v for (k, v) in _dict.items() if k not in cls._properties}) return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a DialogNodeOutput object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'generic') and self.generic is not None: _dict['generic'] = [x.to_dict() for x in self.generic] if hasattr(self, 'integrations') and self.integrations is not None: _dict['integrations'] = self.integrations if hasattr(self, 'modifiers') and self.modifiers is not None: _dict['modifiers'] = self.modifiers.to_dict() for _key in [ k for k in vars(self).keys() if k not in DialogNodeOutput._properties ]: if getattr(self, _key, None) is not None: _dict[_key] = getattr(self, _key) return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def get_properties(self) -> Dict: """Return a dictionary of arbitrary properties from this instance of DialogNodeOutput""" _dict = {} for _key in [ k for k in vars(self).keys() if k not in DialogNodeOutput._properties ]: _dict[_key] = getattr(self, _key) return _dict def set_properties(self, _dict: dict): """Set a dictionary of arbitrary properties to this instance of DialogNodeOutput""" for _key in [ k for k in vars(self).keys() if k not in DialogNodeOutput._properties ]: delattr(self, _key) for _key, _value in _dict.items(): if _key not in DialogNodeOutput._properties: setattr(self, _key, _value) def __str__(self) -> str: """Return a `str` version of this DialogNodeOutput object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'DialogNodeOutput') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'DialogNodeOutput') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class DialogNodeOutputConnectToAgentTransferInfo(): """ Routing or other contextual information to be used by target service desk systems. :attr dict target: (optional) """ def __init__(self, *, target: dict = None) -> None: """ Initialize a DialogNodeOutputConnectToAgentTransferInfo object. :param dict target: (optional) """ self.target = target @classmethod def from_dict(cls, _dict: Dict) -> 'DialogNodeOutputConnectToAgentTransferInfo': """Initialize a DialogNodeOutputConnectToAgentTransferInfo object from a json dictionary.""" args = {} if 'target' in _dict: args['target'] = _dict.get('target') return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a DialogNodeOutputConnectToAgentTransferInfo object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'target') and self.target is not None: _dict['target'] = self.target return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this DialogNodeOutputConnectToAgentTransferInfo object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'DialogNodeOutputConnectToAgentTransferInfo') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'DialogNodeOutputConnectToAgentTransferInfo') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class DialogNodeOutputGeneric(): """ DialogNodeOutputGeneric. """ def __init__(self) -> None: """ Initialize a DialogNodeOutputGeneric object. """ msg = "Cannot instantiate base class. Instead, instantiate one of the defined subclasses: {0}".format( ", ".join([ 'DialogNodeOutputGenericDialogNodeOutputResponseTypeText', 'DialogNodeOutputGenericDialogNodeOutputResponseTypePause', 'DialogNodeOutputGenericDialogNodeOutputResponseTypeImage', 'DialogNodeOutputGenericDialogNodeOutputResponseTypeOption', 'DialogNodeOutputGenericDialogNodeOutputResponseTypeConnectToAgent', 'DialogNodeOutputGenericDialogNodeOutputResponseTypeSearchSkill', 'DialogNodeOutputGenericDialogNodeOutputResponseTypeChannelTransfer', 'DialogNodeOutputGenericDialogNodeOutputResponseTypeUserDefined', 'DialogNodeOutputGenericDialogNodeOutputResponseTypeVideo', 'DialogNodeOutputGenericDialogNodeOutputResponseTypeAudio', 'DialogNodeOutputGenericDialogNodeOutputResponseTypeIframe' ])) raise Exception(msg) @classmethod def from_dict(cls, _dict: Dict) -> 'DialogNodeOutputGeneric': """Initialize a DialogNodeOutputGeneric object from a json dictionary.""" disc_class = cls._get_class_by_discriminator(_dict) if disc_class != cls: return disc_class.from_dict(_dict) msg = ( "Cannot convert dictionary into an instance of base class 'DialogNodeOutputGeneric'. " + "The discriminator value should map to a valid subclass: {1}" ).format(", ".join([ 'DialogNodeOutputGenericDialogNodeOutputResponseTypeText', 'DialogNodeOutputGenericDialogNodeOutputResponseTypePause', 'DialogNodeOutputGenericDialogNodeOutputResponseTypeImage', 'DialogNodeOutputGenericDialogNodeOutputResponseTypeOption', 'DialogNodeOutputGenericDialogNodeOutputResponseTypeConnectToAgent', 'DialogNodeOutputGenericDialogNodeOutputResponseTypeSearchSkill', 'DialogNodeOutputGenericDialogNodeOutputResponseTypeChannelTransfer', 'DialogNodeOutputGenericDialogNodeOutputResponseTypeUserDefined', 'DialogNodeOutputGenericDialogNodeOutputResponseTypeVideo', 'DialogNodeOutputGenericDialogNodeOutputResponseTypeAudio', 'DialogNodeOutputGenericDialogNodeOutputResponseTypeIframe' ])) raise Exception(msg) @classmethod def _from_dict(cls, _dict: Dict): """Initialize a DialogNodeOutputGeneric object from a json dictionary.""" return cls.from_dict(_dict) @classmethod def _get_class_by_discriminator(cls, _dict: Dict) -> object: mapping = {} mapping[ 'audio'] = 'DialogNodeOutputGenericDialogNodeOutputResponseTypeAudio' mapping[ 'channel_transfer'] = 'DialogNodeOutputGenericDialogNodeOutputResponseTypeChannelTransfer' mapping[ 'connect_to_agent'] = 'DialogNodeOutputGenericDialogNodeOutputResponseTypeConnectToAgent' mapping[ 'iframe'] = 'DialogNodeOutputGenericDialogNodeOutputResponseTypeIframe' mapping[ 'image'] = 'DialogNodeOutputGenericDialogNodeOutputResponseTypeImage' mapping[ 'option'] = 'DialogNodeOutputGenericDialogNodeOutputResponseTypeOption' mapping[ 'pause'] = 'DialogNodeOutputGenericDialogNodeOutputResponseTypePause' mapping[ 'search_skill'] = 'DialogNodeOutputGenericDialogNodeOutputResponseTypeSearchSkill' mapping[ 'text'] = 'DialogNodeOutputGenericDialogNodeOutputResponseTypeText' mapping[ 'user_defined'] = 'DialogNodeOutputGenericDialogNodeOutputResponseTypeUserDefined' mapping[ 'video'] = 'DialogNodeOutputGenericDialogNodeOutputResponseTypeVideo' disc_value = _dict.get('response_type') if disc_value is None: raise ValueError( 'Discriminator property \'response_type\' not found in DialogNodeOutputGeneric JSON' ) class_name = mapping.get(disc_value, disc_value) try: disc_class = getattr(sys.modules[__name__], class_name) except AttributeError: disc_class = cls if isinstance(disc_class, object): return disc_class raise TypeError('%s is not a discriminator class' % class_name) class DialogNodeOutputModifiers(): """ Options that modify how specified output is handled. :attr bool overwrite: (optional) Whether values in the output will overwrite output values in an array specified by previously executed dialog nodes. If this option is set to `false`, new values will be appended to previously specified values. """ def __init__(self, *, overwrite: bool = None) -> None: """ Initialize a DialogNodeOutputModifiers object. :param bool overwrite: (optional) Whether values in the output will overwrite output values in an array specified by previously executed dialog nodes. If this option is set to `false`, new values will be appended to previously specified values. """ self.overwrite = overwrite @classmethod def from_dict(cls, _dict: Dict) -> 'DialogNodeOutputModifiers': """Initialize a DialogNodeOutputModifiers object from a json dictionary.""" args = {} if 'overwrite' in _dict: args['overwrite'] = _dict.get('overwrite') return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a DialogNodeOutputModifiers object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'overwrite') and self.overwrite is not None: _dict['overwrite'] = self.overwrite return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this DialogNodeOutputModifiers object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'DialogNodeOutputModifiers') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'DialogNodeOutputModifiers') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class DialogNodeOutputOptionsElement(): """ DialogNodeOutputOptionsElement. :attr str label: The user-facing label for the option. :attr DialogNodeOutputOptionsElementValue value: An object defining the message input to be sent to the Watson Assistant service if the user selects the corresponding option. """ def __init__(self, label: str, value: 'DialogNodeOutputOptionsElementValue') -> None: """ Initialize a DialogNodeOutputOptionsElement object. :param str label: The user-facing label for the option. :param DialogNodeOutputOptionsElementValue value: An object defining the message input to be sent to the Watson Assistant service if the user selects the corresponding option. """ self.label = label self.value = value @classmethod def from_dict(cls, _dict: Dict) -> 'DialogNodeOutputOptionsElement': """Initialize a DialogNodeOutputOptionsElement object from a json dictionary.""" args = {} if 'label' in _dict: args['label'] = _dict.get('label') else: raise ValueError( 'Required property \'label\' not present in DialogNodeOutputOptionsElement JSON' ) if 'value' in _dict: args['value'] = DialogNodeOutputOptionsElementValue.from_dict( _dict.get('value')) else: raise ValueError( 'Required property \'value\' not present in DialogNodeOutputOptionsElement JSON' ) return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a DialogNodeOutputOptionsElement object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'label') and self.label is not None: _dict['label'] = self.label if hasattr(self, 'value') and self.value is not None: _dict['value'] = self.value.to_dict() return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this DialogNodeOutputOptionsElement object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'DialogNodeOutputOptionsElement') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'DialogNodeOutputOptionsElement') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class DialogNodeOutputOptionsElementValue(): """ An object defining the message input to be sent to the Watson Assistant service if the user selects the corresponding option. :attr MessageInput input: (optional) An input object that includes the input text. :attr List[RuntimeIntent] intents: (optional) An array of intents to be used while processing the input. **Note:** This property is supported for backward compatibility with applications that use the v1 **Get response to user input** method. :attr List[RuntimeEntity] entities: (optional) An array of entities to be used while processing the user input. **Note:** This property is supported for backward compatibility with applications that use the v1 **Get response to user input** method. """ def __init__(self, *, input: 'MessageInput' = None, intents: List['RuntimeIntent'] = None, entities: List['RuntimeEntity'] = None) -> None: """ Initialize a DialogNodeOutputOptionsElementValue object. :param MessageInput input: (optional) An input object that includes the input text. :param List[RuntimeIntent] intents: (optional) An array of intents to be used while processing the input. **Note:** This property is supported for backward compatibility with applications that use the v1 **Get response to user input** method. :param List[RuntimeEntity] entities: (optional) An array of entities to be used while processing the user input. **Note:** This property is supported for backward compatibility with applications that use the v1 **Get response to user input** method. """ self.input = input self.intents = intents self.entities = entities @classmethod def from_dict(cls, _dict: Dict) -> 'DialogNodeOutputOptionsElementValue': """Initialize a DialogNodeOutputOptionsElementValue object from a json dictionary.""" args = {} if 'input' in _dict: args['input'] = MessageInput.from_dict(_dict.get('input')) if 'intents' in _dict: args['intents'] = [ RuntimeIntent.from_dict(x) for x in _dict.get('intents') ] if 'entities' in _dict: args['entities'] = [ RuntimeEntity.from_dict(x) for x in _dict.get('entities') ] return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a DialogNodeOutputOptionsElementValue object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'input') and self.input is not None: _dict['input'] = self.input.to_dict() if hasattr(self, 'intents') and self.intents is not None: _dict['intents'] = [x.to_dict() for x in self.intents] if hasattr(self, 'entities') and self.entities is not None: _dict['entities'] = [x.to_dict() for x in self.entities] return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this DialogNodeOutputOptionsElementValue object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'DialogNodeOutputOptionsElementValue') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'DialogNodeOutputOptionsElementValue') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class DialogNodeOutputTextValuesElement(): """ DialogNodeOutputTextValuesElement. :attr str text: (optional) The text of a response. This string can include newline characters (`\n`), Markdown tagging, or other special characters, if supported by the channel. """ def __init__(self, *, text: str = None) -> None: """ Initialize a DialogNodeOutputTextValuesElement object. :param str text: (optional) The text of a response. This string can include newline characters (`\n`), Markdown tagging, or other special characters, if supported by the channel. """ self.text = text @classmethod def from_dict(cls, _dict: Dict) -> 'DialogNodeOutputTextValuesElement': """Initialize a DialogNodeOutputTextValuesElement object from a json dictionary.""" args = {} if 'text' in _dict: args['text'] = _dict.get('text') return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a DialogNodeOutputTextValuesElement object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'text') and self.text is not None: _dict['text'] = self.text return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this DialogNodeOutputTextValuesElement object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'DialogNodeOutputTextValuesElement') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'DialogNodeOutputTextValuesElement') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class DialogNodeVisitedDetails(): """ DialogNodeVisitedDetails. :attr str dialog_node: (optional) The unique ID of a dialog node that was triggered during processing of the input message. :attr str title: (optional) The title of the dialog node. :attr str conditions: (optional) The conditions that trigger the dialog node. """ def __init__(self, *, dialog_node: str = None, title: str = None, conditions: str = None) -> None: """ Initialize a DialogNodeVisitedDetails object. :param str dialog_node: (optional) The unique ID of a dialog node that was triggered during processing of the input message. :param str title: (optional) The title of the dialog node. :param str conditions: (optional) The conditions that trigger the dialog node. """ self.dialog_node = dialog_node self.title = title self.conditions = conditions @classmethod def from_dict(cls, _dict: Dict) -> 'DialogNodeVisitedDetails': """Initialize a DialogNodeVisitedDetails object from a json dictionary.""" args = {} if 'dialog_node' in _dict: args['dialog_node'] = _dict.get('dialog_node') if 'title' in _dict: args['title'] = _dict.get('title') if 'conditions' in _dict: args['conditions'] = _dict.get('conditions') return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a DialogNodeVisitedDetails object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'dialog_node') and self.dialog_node is not None: _dict['dialog_node'] = self.dialog_node if hasattr(self, 'title') and self.title is not None: _dict['title'] = self.title if hasattr(self, 'conditions') and self.conditions is not None: _dict['conditions'] = self.conditions return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this DialogNodeVisitedDetails object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'DialogNodeVisitedDetails') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'DialogNodeVisitedDetails') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class DialogSuggestion(): """ DialogSuggestion. :attr str label: The user-facing label for the disambiguation option. This label is taken from the **title** or **user_label** property of the corresponding dialog node. :attr DialogSuggestionValue value: An object defining the message input, intents, and entities to be sent to the Watson Assistant service if the user selects the corresponding disambiguation option. :attr dict output: (optional) The dialog output that will be returned from the Watson Assistant service if the user selects the corresponding option. :attr str dialog_node: (optional) The unique ID of the dialog node that the **label** property is taken from. The **label** property is populated using the value of the dialog node's **title** or **user_label** property. """ def __init__(self, label: str, value: 'DialogSuggestionValue', *, output: dict = None, dialog_node: str = None) -> None: """ Initialize a DialogSuggestion object. :param str label: The user-facing label for the disambiguation option. This label is taken from the **title** or **user_label** property of the corresponding dialog node. :param DialogSuggestionValue value: An object defining the message input, intents, and entities to be sent to the Watson Assistant service if the user selects the corresponding disambiguation option. :param dict output: (optional) The dialog output that will be returned from the Watson Assistant service if the user selects the corresponding option. :param str dialog_node: (optional) The unique ID of the dialog node that the **label** property is taken from. The **label** property is populated using the value of the dialog node's **title** or **user_label** property. """ self.label = label self.value = value self.output = output self.dialog_node = dialog_node @classmethod def from_dict(cls, _dict: Dict) -> 'DialogSuggestion': """Initialize a DialogSuggestion object from a json dictionary.""" args = {} if 'label' in _dict: args['label'] = _dict.get('label') else: raise ValueError( 'Required property \'label\' not present in DialogSuggestion JSON' ) if 'value' in _dict: args['value'] = DialogSuggestionValue.from_dict(_dict.get('value')) else: raise ValueError( 'Required property \'value\' not present in DialogSuggestion JSON' ) if 'output' in _dict: args['output'] = _dict.get('output') if 'dialog_node' in _dict: args['dialog_node'] = _dict.get('dialog_node') return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a DialogSuggestion object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'label') and self.label is not None: _dict['label'] = self.label if hasattr(self, 'value') and self.value is not None: _dict['value'] = self.value.to_dict() if hasattr(self, 'output') and self.output is not None: _dict['output'] = self.output if hasattr(self, 'dialog_node') and self.dialog_node is not None: _dict['dialog_node'] = self.dialog_node return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this DialogSuggestion object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'DialogSuggestion') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'DialogSuggestion') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class DialogSuggestionValue(): """ An object defining the message input, intents, and entities to be sent to the Watson Assistant service if the user selects the corresponding disambiguation option. :attr MessageInput input: (optional) An input object that includes the input text. :attr List[RuntimeIntent] intents: (optional) An array of intents to be sent along with the user input. :attr List[RuntimeEntity] entities: (optional) An array of entities to be sent along with the user input. """ def __init__(self, *, input: 'MessageInput' = None, intents: List['RuntimeIntent'] = None, entities: List['RuntimeEntity'] = None) -> None: """ Initialize a DialogSuggestionValue object. :param MessageInput input: (optional) An input object that includes the input text. :param List[RuntimeIntent] intents: (optional) An array of intents to be sent along with the user input. :param List[RuntimeEntity] entities: (optional) An array of entities to be sent along with the user input. """ self.input = input self.intents = intents self.entities = entities @classmethod def from_dict(cls, _dict: Dict) -> 'DialogSuggestionValue': """Initialize a DialogSuggestionValue object from a json dictionary.""" args = {} if 'input' in _dict: args['input'] = MessageInput.from_dict(_dict.get('input')) if 'intents' in _dict: args['intents'] = [ RuntimeIntent.from_dict(x) for x in _dict.get('intents') ] if 'entities' in _dict: args['entities'] = [ RuntimeEntity.from_dict(x) for x in _dict.get('entities') ] return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a DialogSuggestionValue object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'input') and self.input is not None: _dict['input'] = self.input.to_dict() if hasattr(self, 'intents') and self.intents is not None: _dict['intents'] = [x.to_dict() for x in self.intents] if hasattr(self, 'entities') and self.entities is not None: _dict['entities'] = [x.to_dict() for x in self.entities] return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this DialogSuggestionValue object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'DialogSuggestionValue') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'DialogSuggestionValue') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class Entity(): """ Entity. :attr str entity: The name of the entity. This string must conform to the following restrictions: - It can contain only Unicode alphanumeric, underscore, and hyphen characters. - If you specify an entity name beginning with the reserved prefix `sys-`, it must be the name of a system entity that you want to enable. (Any entity content specified with the request is ignored.). :attr str description: (optional) The description of the entity. This string cannot contain carriage return, newline, or tab characters. :attr dict metadata: (optional) Any metadata related to the entity. :attr bool fuzzy_match: (optional) Whether to use fuzzy matching for the entity. :attr datetime created: (optional) The timestamp for creation of the object. :attr datetime updated: (optional) The timestamp for the most recent update to the object. :attr List[Value] values: (optional) An array of objects describing the entity values. """ def __init__(self, entity: str, *, description: str = None, metadata: dict = None, fuzzy_match: bool = None, created: datetime = None, updated: datetime = None, values: List['Value'] = None) -> None: """ Initialize a Entity object. :param str entity: The name of the entity. This string must conform to the following restrictions: - It can contain only Unicode alphanumeric, underscore, and hyphen characters. - If you specify an entity name beginning with the reserved prefix `sys-`, it must be the name of a system entity that you want to enable. (Any entity content specified with the request is ignored.). :param str description: (optional) The description of the entity. This string cannot contain carriage return, newline, or tab characters. :param dict metadata: (optional) Any metadata related to the entity. :param bool fuzzy_match: (optional) Whether to use fuzzy matching for the entity. :param List[Value] values: (optional) An array of objects describing the entity values. """ self.entity = entity self.description = description self.metadata = metadata self.fuzzy_match = fuzzy_match self.created = created self.updated = updated self.values = values @classmethod def from_dict(cls, _dict: Dict) -> 'Entity': """Initialize a Entity object from a json dictionary.""" args = {} if 'entity' in _dict: args['entity'] = _dict.get('entity') else: raise ValueError( 'Required property \'entity\' not present in Entity JSON') if 'description' in _dict: args['description'] = _dict.get('description') if 'metadata' in _dict: args['metadata'] = _dict.get('metadata') if 'fuzzy_match' in _dict: args['fuzzy_match'] = _dict.get('fuzzy_match') if 'created' in _dict: args['created'] = string_to_datetime(_dict.get('created')) if 'updated' in _dict: args['updated'] = string_to_datetime(_dict.get('updated')) if 'values' in _dict: args['values'] = [Value.from_dict(x) for x in _dict.get('values')] return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a Entity object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'entity') and self.entity is not None: _dict['entity'] = self.entity if hasattr(self, 'description') and self.description is not None: _dict['description'] = self.description if hasattr(self, 'metadata') and self.metadata is not None: _dict['metadata'] = self.metadata if hasattr(self, 'fuzzy_match') and self.fuzzy_match is not None: _dict['fuzzy_match'] = self.fuzzy_match if hasattr(self, 'created') and getattr(self, 'created') is not None: _dict['created'] = datetime_to_string(getattr(self, 'created')) if hasattr(self, 'updated') and getattr(self, 'updated') is not None: _dict['updated'] = datetime_to_string(getattr(self, 'updated')) if hasattr(self, 'values') and self.values is not None: _dict['values'] = [x.to_dict() for x in self.values] return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this Entity object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'Entity') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'Entity') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class EntityCollection(): """ An array of objects describing the entities for the workspace. :attr List[Entity] entities: An array of objects describing the entities defined for the workspace. :attr Pagination pagination: The pagination data for the returned objects. """ def __init__(self, entities: List['Entity'], pagination: 'Pagination') -> None: """ Initialize a EntityCollection object. :param List[Entity] entities: An array of objects describing the entities defined for the workspace. :param Pagination pagination: The pagination data for the returned objects. """ self.entities = entities self.pagination = pagination @classmethod def from_dict(cls, _dict: Dict) -> 'EntityCollection': """Initialize a EntityCollection object from a json dictionary.""" args = {} if 'entities' in _dict: args['entities'] = [ Entity.from_dict(x) for x in _dict.get('entities') ] else: raise ValueError( 'Required property \'entities\' not present in EntityCollection JSON' ) if 'pagination' in _dict: args['pagination'] = Pagination.from_dict(_dict.get('pagination')) else: raise ValueError( 'Required property \'pagination\' not present in EntityCollection JSON' ) return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a EntityCollection object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'entities') and self.entities is not None: _dict['entities'] = [x.to_dict() for x in self.entities] if hasattr(self, 'pagination') and self.pagination is not None: _dict['pagination'] = self.pagination.to_dict() return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this EntityCollection object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'EntityCollection') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'EntityCollection') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class EntityMention(): """ An object describing a contextual entity mention. :attr str text: The text of the user input example. :attr str intent: The name of the intent. :attr List[int] location: An array of zero-based character offsets that indicate where the entity mentions begin and end in the input text. """ def __init__(self, text: str, intent: str, location: List[int]) -> None: """ Initialize a EntityMention object. :param str text: The text of the user input example. :param str intent: The name of the intent. :param List[int] location: An array of zero-based character offsets that indicate where the entity mentions begin and end in the input text. """ self.text = text self.intent = intent self.location = location @classmethod def from_dict(cls, _dict: Dict) -> 'EntityMention': """Initialize a EntityMention object from a json dictionary.""" args = {} if 'text' in _dict: args['text'] = _dict.get('text') else: raise ValueError( 'Required property \'text\' not present in EntityMention JSON') if 'intent' in _dict: args['intent'] = _dict.get('intent') else: raise ValueError( 'Required property \'intent\' not present in EntityMention JSON' ) if 'location' in _dict: args['location'] = _dict.get('location') else: raise ValueError( 'Required property \'location\' not present in EntityMention JSON' ) return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a EntityMention object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'text') and self.text is not None: _dict['text'] = self.text if hasattr(self, 'intent') and self.intent is not None: _dict['intent'] = self.intent if hasattr(self, 'location') and self.location is not None: _dict['location'] = self.location return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this EntityMention object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'EntityMention') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'EntityMention') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class EntityMentionCollection(): """ EntityMentionCollection. :attr List[EntityMention] examples: An array of objects describing the entity mentions defined for an entity. :attr Pagination pagination: The pagination data for the returned objects. """ def __init__(self, examples: List['EntityMention'], pagination: 'Pagination') -> None: """ Initialize a EntityMentionCollection object. :param List[EntityMention] examples: An array of objects describing the entity mentions defined for an entity. :param Pagination pagination: The pagination data for the returned objects. """ self.examples = examples self.pagination = pagination @classmethod def from_dict(cls, _dict: Dict) -> 'EntityMentionCollection': """Initialize a EntityMentionCollection object from a json dictionary.""" args = {} if 'examples' in _dict: args['examples'] = [ EntityMention.from_dict(x) for x in _dict.get('examples') ] else: raise ValueError( 'Required property \'examples\' not present in EntityMentionCollection JSON' ) if 'pagination' in _dict: args['pagination'] = Pagination.from_dict(_dict.get('pagination')) else: raise ValueError( 'Required property \'pagination\' not present in EntityMentionCollection JSON' ) return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a EntityMentionCollection object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'examples') and self.examples is not None: _dict['examples'] = [x.to_dict() for x in self.examples] if hasattr(self, 'pagination') and self.pagination is not None: _dict['pagination'] = self.pagination.to_dict() return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this EntityMentionCollection object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'EntityMentionCollection') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'EntityMentionCollection') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class Example(): """ Example. :attr str text: The text of a user input example. This string must conform to the following restrictions: - It cannot contain carriage return, newline, or tab characters. - It cannot consist of only whitespace characters. :attr List[Mention] mentions: (optional) An array of contextual entity mentions. :attr datetime created: (optional) The timestamp for creation of the object. :attr datetime updated: (optional) The timestamp for the most recent update to the object. """ def __init__(self, text: str, *, mentions: List['Mention'] = None, created: datetime = None, updated: datetime = None) -> None: """ Initialize a Example object. :param str text: The text of a user input example. This string must conform to the following restrictions: - It cannot contain carriage return, newline, or tab characters. - It cannot consist of only whitespace characters. :param List[Mention] mentions: (optional) An array of contextual entity mentions. """ self.text = text self.mentions = mentions self.created = created self.updated = updated @classmethod def from_dict(cls, _dict: Dict) -> 'Example': """Initialize a Example object from a json dictionary.""" args = {} if 'text' in _dict: args['text'] = _dict.get('text') else: raise ValueError( 'Required property \'text\' not present in Example JSON') if 'mentions' in _dict: args['mentions'] = [ Mention.from_dict(x) for x in _dict.get('mentions') ] if 'created' in _dict: args['created'] = string_to_datetime(_dict.get('created')) if 'updated' in _dict: args['updated'] = string_to_datetime(_dict.get('updated')) return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a Example object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'text') and self.text is not None: _dict['text'] = self.text if hasattr(self, 'mentions') and self.mentions is not None: _dict['mentions'] = [x.to_dict() for x in self.mentions] if hasattr(self, 'created') and getattr(self, 'created') is not None: _dict['created'] = datetime_to_string(getattr(self, 'created')) if hasattr(self, 'updated') and getattr(self, 'updated') is not None: _dict['updated'] = datetime_to_string(getattr(self, 'updated')) return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this Example object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'Example') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'Example') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class ExampleCollection(): """ ExampleCollection. :attr List[Example] examples: An array of objects describing the examples defined for the intent. :attr Pagination pagination: The pagination data for the returned objects. """ def __init__(self, examples: List['Example'], pagination: 'Pagination') -> None: """ Initialize a ExampleCollection object. :param List[Example] examples: An array of objects describing the examples defined for the intent. :param Pagination pagination: The pagination data for the returned objects. """ self.examples = examples self.pagination = pagination @classmethod def from_dict(cls, _dict: Dict) -> 'ExampleCollection': """Initialize a ExampleCollection object from a json dictionary.""" args = {} if 'examples' in _dict: args['examples'] = [ Example.from_dict(x) for x in _dict.get('examples') ] else: raise ValueError( 'Required property \'examples\' not present in ExampleCollection JSON' ) if 'pagination' in _dict: args['pagination'] = Pagination.from_dict(_dict.get('pagination')) else: raise ValueError( 'Required property \'pagination\' not present in ExampleCollection JSON' ) return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a ExampleCollection object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'examples') and self.examples is not None: _dict['examples'] = [x.to_dict() for x in self.examples] if hasattr(self, 'pagination') and self.pagination is not None: _dict['pagination'] = self.pagination.to_dict() return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this ExampleCollection object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'ExampleCollection') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'ExampleCollection') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class Intent(): """ Intent. :attr str intent: The name of the intent. This string must conform to the following restrictions: - It can contain only Unicode alphanumeric, underscore, hyphen, and dot characters. - It cannot begin with the reserved prefix `sys-`. :attr str description: (optional) The description of the intent. This string cannot contain carriage return, newline, or tab characters. :attr datetime created: (optional) The timestamp for creation of the object. :attr datetime updated: (optional) The timestamp for the most recent update to the object. :attr List[Example] examples: (optional) An array of user input examples for the intent. """ def __init__(self, intent: str, *, description: str = None, created: datetime = None, updated: datetime = None, examples: List['Example'] = None) -> None: """ Initialize a Intent object. :param str intent: The name of the intent. This string must conform to the following restrictions: - It can contain only Unicode alphanumeric, underscore, hyphen, and dot characters. - It cannot begin with the reserved prefix `sys-`. :param str description: (optional) The description of the intent. This string cannot contain carriage return, newline, or tab characters. :param List[Example] examples: (optional) An array of user input examples for the intent. """ self.intent = intent self.description = description self.created = created self.updated = updated self.examples = examples @classmethod def from_dict(cls, _dict: Dict) -> 'Intent': """Initialize a Intent object from a json dictionary.""" args = {} if 'intent' in _dict: args['intent'] = _dict.get('intent') else: raise ValueError( 'Required property \'intent\' not present in Intent JSON') if 'description' in _dict: args['description'] = _dict.get('description') if 'created' in _dict: args['created'] = string_to_datetime(_dict.get('created')) if 'updated' in _dict: args['updated'] = string_to_datetime(_dict.get('updated')) if 'examples' in _dict: args['examples'] = [ Example.from_dict(x) for x in _dict.get('examples') ] return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a Intent object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'intent') and self.intent is not None: _dict['intent'] = self.intent if hasattr(self, 'description') and self.description is not None: _dict['description'] = self.description if hasattr(self, 'created') and getattr(self, 'created') is not None: _dict['created'] = datetime_to_string(getattr(self, 'created')) if hasattr(self, 'updated') and getattr(self, 'updated') is not None: _dict['updated'] = datetime_to_string(getattr(self, 'updated')) if hasattr(self, 'examples') and self.examples is not None: _dict['examples'] = [x.to_dict() for x in self.examples] return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this Intent object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'Intent') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'Intent') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class IntentCollection(): """ IntentCollection. :attr List[Intent] intents: An array of objects describing the intents defined for the workspace. :attr Pagination pagination: The pagination data for the returned objects. """ def __init__(self, intents: List['Intent'], pagination: 'Pagination') -> None: """ Initialize a IntentCollection object. :param List[Intent] intents: An array of objects describing the intents defined for the workspace. :param Pagination pagination: The pagination data for the returned objects. """ self.intents = intents self.pagination = pagination @classmethod def from_dict(cls, _dict: Dict) -> 'IntentCollection': """Initialize a IntentCollection object from a json dictionary.""" args = {} if 'intents' in _dict: args['intents'] = [ Intent.from_dict(x) for x in _dict.get('intents') ] else: raise ValueError( 'Required property \'intents\' not present in IntentCollection JSON' ) if 'pagination' in _dict: args['pagination'] = Pagination.from_dict(_dict.get('pagination')) else: raise ValueError( 'Required property \'pagination\' not present in IntentCollection JSON' ) return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a IntentCollection object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'intents') and self.intents is not None: _dict['intents'] = [x.to_dict() for x in self.intents] if hasattr(self, 'pagination') and self.pagination is not None: _dict['pagination'] = self.pagination.to_dict() return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this IntentCollection object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'IntentCollection') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'IntentCollection') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class Log(): """ Log. :attr MessageRequest request: A request sent to the workspace, including the user input and context. :attr MessageResponse response: The response sent by the workspace, including the output text, detected intents and entities, and context. :attr str log_id: A unique identifier for the logged event. :attr str request_timestamp: The timestamp for receipt of the message. :attr str response_timestamp: The timestamp for the system response to the message. :attr str workspace_id: The unique identifier of the workspace where the request was made. :attr str language: The language of the workspace where the message request was made. """ def __init__(self, request: 'MessageRequest', response: 'MessageResponse', log_id: str, request_timestamp: str, response_timestamp: str, workspace_id: str, language: str) -> None: """ Initialize a Log object. :param MessageRequest request: A request sent to the workspace, including the user input and context. :param MessageResponse response: The response sent by the workspace, including the output text, detected intents and entities, and context. :param str log_id: A unique identifier for the logged event. :param str request_timestamp: The timestamp for receipt of the message. :param str response_timestamp: The timestamp for the system response to the message. :param str workspace_id: The unique identifier of the workspace where the request was made. :param str language: The language of the workspace where the message request was made. """ self.request = request self.response = response self.log_id = log_id self.request_timestamp = request_timestamp self.response_timestamp = response_timestamp self.workspace_id = workspace_id self.language = language @classmethod def from_dict(cls, _dict: Dict) -> 'Log': """Initialize a Log object from a json dictionary.""" args = {} if 'request' in _dict: args['request'] = MessageRequest.from_dict(_dict.get('request')) else: raise ValueError( 'Required property \'request\' not present in Log JSON') if 'response' in _dict: args['response'] = MessageResponse.from_dict(_dict.get('response')) else: raise ValueError( 'Required property \'response\' not present in Log JSON') if 'log_id' in _dict: args['log_id'] = _dict.get('log_id') else: raise ValueError( 'Required property \'log_id\' not present in Log JSON') if 'request_timestamp' in _dict: args['request_timestamp'] = _dict.get('request_timestamp') else: raise ValueError( 'Required property \'request_timestamp\' not present in Log JSON' ) if 'response_timestamp' in _dict: args['response_timestamp'] = _dict.get('response_timestamp') else: raise ValueError( 'Required property \'response_timestamp\' not present in Log JSON' ) if 'workspace_id' in _dict: args['workspace_id'] = _dict.get('workspace_id') else: raise ValueError( 'Required property \'workspace_id\' not present in Log JSON') if 'language' in _dict: args['language'] = _dict.get('language') else: raise ValueError( 'Required property \'language\' not present in Log JSON') return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a Log object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'request') and self.request is not None: _dict['request'] = self.request.to_dict() if hasattr(self, 'response') and self.response is not None: _dict['response'] = self.response.to_dict() if hasattr(self, 'log_id') and self.log_id is not None: _dict['log_id'] = self.log_id if hasattr(self, 'request_timestamp') and self.request_timestamp is not None: _dict['request_timestamp'] = self.request_timestamp if hasattr( self, 'response_timestamp') and self.response_timestamp is not None: _dict['response_timestamp'] = self.response_timestamp if hasattr(self, 'workspace_id') and self.workspace_id is not None: _dict['workspace_id'] = self.workspace_id if hasattr(self, 'language') and self.language is not None: _dict['language'] = self.language return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this Log object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'Log') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'Log') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class LogCollection(): """ LogCollection. :attr List[Log] logs: An array of objects describing log events. :attr LogPagination pagination: The pagination data for the returned objects. """ def __init__(self, logs: List['Log'], pagination: 'LogPagination') -> None: """ Initialize a LogCollection object. :param List[Log] logs: An array of objects describing log events. :param LogPagination pagination: The pagination data for the returned objects. """ self.logs = logs self.pagination = pagination @classmethod def from_dict(cls, _dict: Dict) -> 'LogCollection': """Initialize a LogCollection object from a json dictionary.""" args = {} if 'logs' in _dict: args['logs'] = [Log.from_dict(x) for x in _dict.get('logs')] else: raise ValueError( 'Required property \'logs\' not present in LogCollection JSON') if 'pagination' in _dict: args['pagination'] = LogPagination.from_dict( _dict.get('pagination')) else: raise ValueError( 'Required property \'pagination\' not present in LogCollection JSON' ) return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a LogCollection object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'logs') and self.logs is not None: _dict['logs'] = [x.to_dict() for x in self.logs] if hasattr(self, 'pagination') and self.pagination is not None: _dict['pagination'] = self.pagination.to_dict() return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this LogCollection object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'LogCollection') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'LogCollection') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class LogMessage(): """ Log message details. :attr str level: The severity of the log message. :attr str msg: The text of the log message. :attr str code: A code that indicates the category to which the error message belongs. :attr LogMessageSource source: (optional) An object that identifies the dialog element that generated the error message. """ def __init__(self, level: str, msg: str, code: str, *, source: 'LogMessageSource' = None) -> None: """ Initialize a LogMessage object. :param str level: The severity of the log message. :param str msg: The text of the log message. :param str code: A code that indicates the category to which the error message belongs. :param LogMessageSource source: (optional) An object that identifies the dialog element that generated the error message. """ self.level = level self.msg = msg self.code = code self.source = source @classmethod def from_dict(cls, _dict: Dict) -> 'LogMessage': """Initialize a LogMessage object from a json dictionary.""" args = {} if 'level' in _dict: args['level'] = _dict.get('level') else: raise ValueError( 'Required property \'level\' not present in LogMessage JSON') if 'msg' in _dict: args['msg'] = _dict.get('msg') else: raise ValueError( 'Required property \'msg\' not present in LogMessage JSON') if 'code' in _dict: args['code'] = _dict.get('code') else: raise ValueError( 'Required property \'code\' not present in LogMessage JSON') if 'source' in _dict: args['source'] = LogMessageSource.from_dict(_dict.get('source')) return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a LogMessage object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'level') and self.level is not None: _dict['level'] = self.level if hasattr(self, 'msg') and self.msg is not None: _dict['msg'] = self.msg if hasattr(self, 'code') and self.code is not None: _dict['code'] = self.code if hasattr(self, 'source') and self.source is not None: _dict['source'] = self.source.to_dict() return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this LogMessage object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'LogMessage') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'LogMessage') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class LevelEnum(str, Enum): """ The severity of the log message. """ INFO = 'info' ERROR = 'error' WARN = 'warn' class LogMessageSource(): """ An object that identifies the dialog element that generated the error message. :attr str type: (optional) A string that indicates the type of dialog element that generated the error message. :attr str dialog_node: (optional) The unique identifier of the dialog node that generated the error message. """ def __init__(self, *, type: str = None, dialog_node: str = None) -> None: """ Initialize a LogMessageSource object. :param str type: (optional) A string that indicates the type of dialog element that generated the error message. :param str dialog_node: (optional) The unique identifier of the dialog node that generated the error message. """ self.type = type self.dialog_node = dialog_node @classmethod def from_dict(cls, _dict: Dict) -> 'LogMessageSource': """Initialize a LogMessageSource object from a json dictionary.""" args = {} if 'type' in _dict: args['type'] = _dict.get('type') if 'dialog_node' in _dict: args['dialog_node'] = _dict.get('dialog_node') return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a LogMessageSource object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'type') and self.type is not None: _dict['type'] = self.type if hasattr(self, 'dialog_node') and self.dialog_node is not None: _dict['dialog_node'] = self.dialog_node return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this LogMessageSource object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'LogMessageSource') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'LogMessageSource') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class TypeEnum(str, Enum): """ A string that indicates the type of dialog element that generated the error message. """ DIALOG_NODE = 'dialog_node' class LogPagination(): """ The pagination data for the returned objects. :attr str next_url: (optional) The URL that will return the next page of results, if any. :attr int matched: (optional) Reserved for future use. :attr str next_cursor: (optional) A token identifying the next page of results. """ def __init__(self, *, next_url: str = None, matched: int = None, next_cursor: str = None) -> None: """ Initialize a LogPagination object. :param str next_url: (optional) The URL that will return the next page of results, if any. :param int matched: (optional) Reserved for future use. :param str next_cursor: (optional) A token identifying the next page of results. """ self.next_url = next_url self.matched = matched self.next_cursor = next_cursor @classmethod def from_dict(cls, _dict: Dict) -> 'LogPagination': """Initialize a LogPagination object from a json dictionary.""" args = {} if 'next_url' in _dict: args['next_url'] = _dict.get('next_url') if 'matched' in _dict: args['matched'] = _dict.get('matched') if 'next_cursor' in _dict: args['next_cursor'] = _dict.get('next_cursor') return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a LogPagination object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'next_url') and self.next_url is not None: _dict['next_url'] = self.next_url if hasattr(self, 'matched') and self.matched is not None: _dict['matched'] = self.matched if hasattr(self, 'next_cursor') and self.next_cursor is not None: _dict['next_cursor'] = self.next_cursor return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this LogPagination object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'LogPagination') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'LogPagination') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class Mention(): """ A mention of a contextual entity. :attr str entity: The name of the entity. :attr List[int] location: An array of zero-based character offsets that indicate where the entity mentions begin and end in the input text. """ def __init__(self, entity: str, location: List[int]) -> None: """ Initialize a Mention object. :param str entity: The name of the entity. :param List[int] location: An array of zero-based character offsets that indicate where the entity mentions begin and end in the input text. """ self.entity = entity self.location = location @classmethod def from_dict(cls, _dict: Dict) -> 'Mention': """Initialize a Mention object from a json dictionary.""" args = {} if 'entity' in _dict: args['entity'] = _dict.get('entity') else: raise ValueError( 'Required property \'entity\' not present in Mention JSON') if 'location' in _dict: args['location'] = _dict.get('location') else: raise ValueError( 'Required property \'location\' not present in Mention JSON') return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a Mention object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'entity') and self.entity is not None: _dict['entity'] = self.entity if hasattr(self, 'location') and self.location is not None: _dict['location'] = self.location return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this Mention object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'Mention') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'Mention') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class MessageContextMetadata(): """ Metadata related to the message. :attr str deployment: (optional) A label identifying the deployment environment, used for filtering log data. This string cannot contain carriage return, newline, or tab characters. :attr str user_id: (optional) A string value that identifies the user who is interacting with the workspace. The client must provide a unique identifier for each individual end user who accesses the application. For user-based plans, this user ID is used to identify unique users for billing purposes. This string cannot contain carriage return, newline, or tab characters. If no value is specified in the input, **user_id** is automatically set to the value of **context.conversation_id**. **Note:** This property is the same as the **user_id** property at the root of the message body. If **user_id** is specified in both locations in a message request, the value specified at the root is used. """ def __init__(self, *, deployment: str = None, user_id: str = None) -> None: """ Initialize a MessageContextMetadata object. :param str deployment: (optional) A label identifying the deployment environment, used for filtering log data. This string cannot contain carriage return, newline, or tab characters. :param str user_id: (optional) A string value that identifies the user who is interacting with the workspace. The client must provide a unique identifier for each individual end user who accesses the application. For user-based plans, this user ID is used to identify unique users for billing purposes. This string cannot contain carriage return, newline, or tab characters. If no value is specified in the input, **user_id** is automatically set to the value of **context.conversation_id**. **Note:** This property is the same as the **user_id** property at the root of the message body. If **user_id** is specified in both locations in a message request, the value specified at the root is used. """ self.deployment = deployment self.user_id = user_id @classmethod def from_dict(cls, _dict: Dict) -> 'MessageContextMetadata': """Initialize a MessageContextMetadata object from a json dictionary.""" args = {} if 'deployment' in _dict: args['deployment'] = _dict.get('deployment') if 'user_id' in _dict: args['user_id'] = _dict.get('user_id') return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a MessageContextMetadata object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'deployment') and self.deployment is not None: _dict['deployment'] = self.deployment if hasattr(self, 'user_id') and self.user_id is not None: _dict['user_id'] = self.user_id return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this MessageContextMetadata object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'MessageContextMetadata') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'MessageContextMetadata') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class MessageInput(): """ An input object that includes the input text. :attr str text: (optional) The text of the user input. This string cannot contain carriage return, newline, or tab characters. :attr bool spelling_suggestions: (optional) Whether to use spelling correction when processing the input. This property overrides the value of the **spelling_suggestions** property in the workspace settings. :attr bool spelling_auto_correct: (optional) Whether to use autocorrection when processing the input. If spelling correction is used and this property is `false`, any suggested corrections are returned in the **suggested_text** property of the message response. If this property is `true`, any corrections are automatically applied to the user input, and the original text is returned in the **original_text** property of the message response. This property overrides the value of the **spelling_auto_correct** property in the workspace settings. :attr str suggested_text: (optional) Any suggested corrections of the input text. This property is returned only if spelling correction is enabled and autocorrection is disabled. :attr str original_text: (optional) The original user input text. This property is returned only if autocorrection is enabled and the user input was corrected. """ # The set of defined properties for the class _properties = frozenset([ 'text', 'spelling_suggestions', 'spelling_auto_correct', 'suggested_text', 'original_text' ]) def __init__(self, *, text: str = None, spelling_suggestions: bool = None, spelling_auto_correct: bool = None, suggested_text: str = None, original_text: str = None, **kwargs) -> None: """ Initialize a MessageInput object. :param str text: (optional) The text of the user input. This string cannot contain carriage return, newline, or tab characters. :param bool spelling_suggestions: (optional) Whether to use spelling correction when processing the input. This property overrides the value of the **spelling_suggestions** property in the workspace settings. :param bool spelling_auto_correct: (optional) Whether to use autocorrection when processing the input. If spelling correction is used and this property is `false`, any suggested corrections are returned in the **suggested_text** property of the message response. If this property is `true`, any corrections are automatically applied to the user input, and the original text is returned in the **original_text** property of the message response. This property overrides the value of the **spelling_auto_correct** property in the workspace settings. :param **kwargs: (optional) Any additional properties. """ self.text = text self.spelling_suggestions = spelling_suggestions self.spelling_auto_correct = spelling_auto_correct self.suggested_text = suggested_text self.original_text = original_text for _key, _value in kwargs.items(): setattr(self, _key, _value) @classmethod def from_dict(cls, _dict: Dict) -> 'MessageInput': """Initialize a MessageInput object from a json dictionary.""" args = {} if 'text' in _dict: args['text'] = _dict.get('text') if 'spelling_suggestions' in _dict: args['spelling_suggestions'] = _dict.get('spelling_suggestions') if 'spelling_auto_correct' in _dict: args['spelling_auto_correct'] = _dict.get('spelling_auto_correct') if 'suggested_text' in _dict: args['suggested_text'] = _dict.get('suggested_text') if 'original_text' in _dict: args['original_text'] = _dict.get('original_text') args.update( {k: v for (k, v) in _dict.items() if k not in cls._properties}) return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a MessageInput object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'text') and self.text is not None: _dict['text'] = self.text if hasattr(self, 'spelling_suggestions' ) and self.spelling_suggestions is not None: _dict['spelling_suggestions'] = self.spelling_suggestions if hasattr(self, 'spelling_auto_correct' ) and self.spelling_auto_correct is not None: _dict['spelling_auto_correct'] = self.spelling_auto_correct if hasattr(self, 'suggested_text') and getattr( self, 'suggested_text') is not None: _dict['suggested_text'] = getattr(self, 'suggested_text') if hasattr(self, 'original_text') and getattr( self, 'original_text') is not None: _dict['original_text'] = getattr(self, 'original_text') for _key in [ k for k in vars(self).keys() if k not in MessageInput._properties ]: if getattr(self, _key, None) is not None: _dict[_key] = getattr(self, _key) return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def get_properties(self) -> Dict: """Return a dictionary of arbitrary properties from this instance of MessageInput""" _dict = {} for _key in [ k for k in vars(self).keys() if k not in MessageInput._properties ]: _dict[_key] = getattr(self, _key) return _dict def set_properties(self, _dict: dict): """Set a dictionary of arbitrary properties to this instance of MessageInput""" for _key in [ k for k in vars(self).keys() if k not in MessageInput._properties ]: delattr(self, _key) for _key, _value in _dict.items(): if _key not in MessageInput._properties: setattr(self, _key, _value) def __str__(self) -> str: """Return a `str` version of this MessageInput object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'MessageInput') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'MessageInput') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class MessageRequest(): """ A request sent to the workspace, including the user input and context. :attr MessageInput input: (optional) An input object that includes the input text. :attr List[RuntimeIntent] intents: (optional) Intents to use when evaluating the user input. Include intents from the previous response to continue using those intents rather than trying to recognize intents in the new input. :attr List[RuntimeEntity] entities: (optional) Entities to use when evaluating the message. Include entities from the previous response to continue using those entities rather than detecting entities in the new input. :attr bool alternate_intents: (optional) Whether to return more than one intent. A value of `true` indicates that all matching intents are returned. :attr Context context: (optional) State information for the conversation. To maintain state, include the context from the previous response. :attr OutputData output: (optional) An output object that includes the response to the user, the dialog nodes that were triggered, and messages from the log. :attr List[DialogNodeAction] actions: (optional) An array of objects describing any actions requested by the dialog node. :attr str user_id: (optional) A string value that identifies the user who is interacting with the workspace. The client must provide a unique identifier for each individual end user who accesses the application. For user-based plans, this user ID is used to identify unique users for billing purposes. This string cannot contain carriage return, newline, or tab characters. If no value is specified in the input, **user_id** is automatically set to the value of **context.conversation_id**. **Note:** This property is the same as the **user_id** property in the context metadata. If **user_id** is specified in both locations in a message request, the value specified at the root is used. """ def __init__(self, *, input: 'MessageInput' = None, intents: List['RuntimeIntent'] = None, entities: List['RuntimeEntity'] = None, alternate_intents: bool = None, context: 'Context' = None, output: 'OutputData' = None, actions: List['DialogNodeAction'] = None, user_id: str = None) -> None: """ Initialize a MessageRequest object. :param MessageInput input: (optional) An input object that includes the input text. :param List[RuntimeIntent] intents: (optional) Intents to use when evaluating the user input. Include intents from the previous response to continue using those intents rather than trying to recognize intents in the new input. :param List[RuntimeEntity] entities: (optional) Entities to use when evaluating the message. Include entities from the previous response to continue using those entities rather than detecting entities in the new input. :param bool alternate_intents: (optional) Whether to return more than one intent. A value of `true` indicates that all matching intents are returned. :param Context context: (optional) State information for the conversation. To maintain state, include the context from the previous response. :param OutputData output: (optional) An output object that includes the response to the user, the dialog nodes that were triggered, and messages from the log. :param str user_id: (optional) A string value that identifies the user who is interacting with the workspace. The client must provide a unique identifier for each individual end user who accesses the application. For user-based plans, this user ID is used to identify unique users for billing purposes. This string cannot contain carriage return, newline, or tab characters. If no value is specified in the input, **user_id** is automatically set to the value of **context.conversation_id**. **Note:** This property is the same as the **user_id** property in the context metadata. If **user_id** is specified in both locations in a message request, the value specified at the root is used. """ self.input = input self.intents = intents self.entities = entities self.alternate_intents = alternate_intents self.context = context self.output = output self.actions = actions self.user_id = user_id @classmethod def from_dict(cls, _dict: Dict) -> 'MessageRequest': """Initialize a MessageRequest object from a json dictionary.""" args = {} if 'input' in _dict: args['input'] = MessageInput.from_dict(_dict.get('input')) if 'intents' in _dict: args['intents'] = [ RuntimeIntent.from_dict(x) for x in _dict.get('intents') ] if 'entities' in _dict: args['entities'] = [ RuntimeEntity.from_dict(x) for x in _dict.get('entities') ] if 'alternate_intents' in _dict: args['alternate_intents'] = _dict.get('alternate_intents') if 'context' in _dict: args['context'] = Context.from_dict(_dict.get('context')) if 'output' in _dict: args['output'] = OutputData.from_dict(_dict.get('output')) if 'actions' in _dict: args['actions'] = [ DialogNodeAction.from_dict(x) for x in _dict.get('actions') ] if 'user_id' in _dict: args['user_id'] = _dict.get('user_id') return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a MessageRequest object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'input') and self.input is not None: _dict['input'] = self.input.to_dict() if hasattr(self, 'intents') and self.intents is not None: _dict['intents'] = [x.to_dict() for x in self.intents] if hasattr(self, 'entities') and self.entities is not None: _dict['entities'] = [x.to_dict() for x in self.entities] if hasattr(self, 'alternate_intents') and self.alternate_intents is not None: _dict['alternate_intents'] = self.alternate_intents if hasattr(self, 'context') and self.context is not None: _dict['context'] = self.context.to_dict() if hasattr(self, 'output') and self.output is not None: _dict['output'] = self.output.to_dict() if hasattr(self, 'actions') and getattr(self, 'actions') is not None: _dict['actions'] = [x.to_dict() for x in getattr(self, 'actions')] if hasattr(self, 'user_id') and self.user_id is not None: _dict['user_id'] = self.user_id return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this MessageRequest object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'MessageRequest') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'MessageRequest') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class MessageResponse(): """ The response sent by the workspace, including the output text, detected intents and entities, and context. :attr MessageInput input: An input object that includes the input text. :attr List[RuntimeIntent] intents: An array of intents recognized in the user input, sorted in descending order of confidence. :attr List[RuntimeEntity] entities: An array of entities identified in the user input. :attr bool alternate_intents: (optional) Whether to return more than one intent. A value of `true` indicates that all matching intents are returned. :attr Context context: State information for the conversation. To maintain state, include the context from the previous response. :attr OutputData output: An output object that includes the response to the user, the dialog nodes that were triggered, and messages from the log. :attr List[DialogNodeAction] actions: (optional) An array of objects describing any actions requested by the dialog node. :attr str user_id: A string value that identifies the user who is interacting with the workspace. The client must provide a unique identifier for each individual end user who accesses the application. For user-based plans, this user ID is used to identify unique users for billing purposes. This string cannot contain carriage return, newline, or tab characters. If no value is specified in the input, **user_id** is automatically set to the value of **context.conversation_id**. **Note:** This property is the same as the **user_id** property in the context metadata. If **user_id** is specified in both locations in a message request, the value specified at the root is used. """ def __init__(self, input: 'MessageInput', intents: List['RuntimeIntent'], entities: List['RuntimeEntity'], context: 'Context', output: 'OutputData', user_id: str, *, alternate_intents: bool = None, actions: List['DialogNodeAction'] = None) -> None: """ Initialize a MessageResponse object. :param MessageInput input: An input object that includes the input text. :param List[RuntimeIntent] intents: An array of intents recognized in the user input, sorted in descending order of confidence. :param List[RuntimeEntity] entities: An array of entities identified in the user input. :param Context context: State information for the conversation. To maintain state, include the context from the previous response. :param OutputData output: An output object that includes the response to the user, the dialog nodes that were triggered, and messages from the log. :param str user_id: A string value that identifies the user who is interacting with the workspace. The client must provide a unique identifier for each individual end user who accesses the application. For user-based plans, this user ID is used to identify unique users for billing purposes. This string cannot contain carriage return, newline, or tab characters. If no value is specified in the input, **user_id** is automatically set to the value of **context.conversation_id**. **Note:** This property is the same as the **user_id** property in the context metadata. If **user_id** is specified in both locations in a message request, the value specified at the root is used. :param bool alternate_intents: (optional) Whether to return more than one intent. A value of `true` indicates that all matching intents are returned. """ self.input = input self.intents = intents self.entities = entities self.alternate_intents = alternate_intents self.context = context self.output = output self.actions = actions self.user_id = user_id @classmethod def from_dict(cls, _dict: Dict) -> 'MessageResponse': """Initialize a MessageResponse object from a json dictionary.""" args = {} if 'input' in _dict: args['input'] = MessageInput.from_dict(_dict.get('input')) else: raise ValueError( 'Required property \'input\' not present in MessageResponse JSON' ) if 'intents' in _dict: args['intents'] = [ RuntimeIntent.from_dict(x) for x in _dict.get('intents') ] else: raise ValueError( 'Required property \'intents\' not present in MessageResponse JSON' ) if 'entities' in _dict: args['entities'] = [ RuntimeEntity.from_dict(x) for x in _dict.get('entities') ] else: raise ValueError( 'Required property \'entities\' not present in MessageResponse JSON' ) if 'alternate_intents' in _dict: args['alternate_intents'] = _dict.get('alternate_intents') if 'context' in _dict: args['context'] = Context.from_dict(_dict.get('context')) else: raise ValueError( 'Required property \'context\' not present in MessageResponse JSON' ) if 'output' in _dict: args['output'] = OutputData.from_dict(_dict.get('output')) else: raise ValueError( 'Required property \'output\' not present in MessageResponse JSON' ) if 'actions' in _dict: args['actions'] = [ DialogNodeAction.from_dict(x) for x in _dict.get('actions') ] if 'user_id' in _dict: args['user_id'] = _dict.get('user_id') else: raise ValueError( 'Required property \'user_id\' not present in MessageResponse JSON' ) return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a MessageResponse object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'input') and self.input is not None: _dict['input'] = self.input.to_dict() if hasattr(self, 'intents') and self.intents is not None: _dict['intents'] = [x.to_dict() for x in self.intents] if hasattr(self, 'entities') and self.entities is not None: _dict['entities'] = [x.to_dict() for x in self.entities] if hasattr(self, 'alternate_intents') and self.alternate_intents is not None: _dict['alternate_intents'] = self.alternate_intents if hasattr(self, 'context') and self.context is not None: _dict['context'] = self.context.to_dict() if hasattr(self, 'output') and self.output is not None: _dict['output'] = self.output.to_dict() if hasattr(self, 'actions') and getattr(self, 'actions') is not None: _dict['actions'] = [x.to_dict() for x in getattr(self, 'actions')] if hasattr(self, 'user_id') and self.user_id is not None: _dict['user_id'] = self.user_id return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this MessageResponse object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'MessageResponse') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'MessageResponse') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class OutputData(): """ An output object that includes the response to the user, the dialog nodes that were triggered, and messages from the log. :attr List[str] nodes_visited: (optional) An array of the nodes that were triggered to create the response, in the order in which they were visited. This information is useful for debugging and for tracing the path taken through the node tree. :attr List[DialogNodeVisitedDetails] nodes_visited_details: (optional) An array of objects containing detailed diagnostic information about the nodes that were triggered during processing of the input message. Included only if **nodes_visited_details** is set to `true` in the message request. :attr List[LogMessage] log_messages: An array of up to 50 messages logged with the request. :attr List[RuntimeResponseGeneric] generic: (optional) Output intended for any channel. It is the responsibility of the client application to implement the supported response types. """ # The set of defined properties for the class _properties = frozenset( ['nodes_visited', 'nodes_visited_details', 'log_messages', 'generic']) def __init__(self, log_messages: List['LogMessage'], *, nodes_visited: List[str] = None, nodes_visited_details: List['DialogNodeVisitedDetails'] = None, generic: List['RuntimeResponseGeneric'] = None, **kwargs) -> None: """ Initialize a OutputData object. :param List[LogMessage] log_messages: An array of up to 50 messages logged with the request. :param List[str] nodes_visited: (optional) An array of the nodes that were triggered to create the response, in the order in which they were visited. This information is useful for debugging and for tracing the path taken through the node tree. :param List[DialogNodeVisitedDetails] nodes_visited_details: (optional) An array of objects containing detailed diagnostic information about the nodes that were triggered during processing of the input message. Included only if **nodes_visited_details** is set to `true` in the message request. :param List[RuntimeResponseGeneric] generic: (optional) Output intended for any channel. It is the responsibility of the client application to implement the supported response types. :param **kwargs: (optional) Any additional properties. """ self.nodes_visited = nodes_visited self.nodes_visited_details = nodes_visited_details self.log_messages = log_messages self.generic = generic for _key, _value in kwargs.items(): setattr(self, _key, _value) @classmethod def from_dict(cls, _dict: Dict) -> 'OutputData': """Initialize a OutputData object from a json dictionary.""" args = {} if 'nodes_visited' in _dict: args['nodes_visited'] = _dict.get('nodes_visited') if 'nodes_visited_details' in _dict: args['nodes_visited_details'] = [ DialogNodeVisitedDetails.from_dict(x) for x in _dict.get('nodes_visited_details') ] if 'log_messages' in _dict: args['log_messages'] = [ LogMessage.from_dict(x) for x in _dict.get('log_messages') ] else: raise ValueError( 'Required property \'log_messages\' not present in OutputData JSON' ) if 'generic' in _dict: args['generic'] = [ RuntimeResponseGeneric.from_dict(x) for x in _dict.get('generic') ] args.update( {k: v for (k, v) in _dict.items() if k not in cls._properties}) return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a OutputData object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'nodes_visited') and self.nodes_visited is not None: _dict['nodes_visited'] = self.nodes_visited if hasattr(self, 'nodes_visited_details' ) and self.nodes_visited_details is not None: _dict['nodes_visited_details'] = [ x.to_dict() for x in self.nodes_visited_details ] if hasattr(self, 'log_messages') and self.log_messages is not None: _dict['log_messages'] = [x.to_dict() for x in self.log_messages] if hasattr(self, 'generic') and self.generic is not None: _dict['generic'] = [x.to_dict() for x in self.generic] for _key in [ k for k in vars(self).keys() if k not in OutputData._properties ]: if getattr(self, _key, None) is not None: _dict[_key] = getattr(self, _key) return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def get_properties(self) -> Dict: """Return a dictionary of arbitrary properties from this instance of OutputData""" _dict = {} for _key in [ k for k in vars(self).keys() if k not in OutputData._properties ]: _dict[_key] = getattr(self, _key) return _dict def set_properties(self, _dict: dict): """Set a dictionary of arbitrary properties to this instance of OutputData""" for _key in [ k for k in vars(self).keys() if k not in OutputData._properties ]: delattr(self, _key) for _key, _value in _dict.items(): if _key not in OutputData._properties: setattr(self, _key, _value) def __str__(self) -> str: """Return a `str` version of this OutputData object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'OutputData') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'OutputData') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class Pagination(): """ The pagination data for the returned objects. :attr str refresh_url: The URL that will return the same page of results. :attr str next_url: (optional) The URL that will return the next page of results. :attr int total: (optional) The total number of objects that satisfy the request. This total includes all results, not just those included in the current page. :attr int matched: (optional) Reserved for future use. :attr str refresh_cursor: (optional) A token identifying the current page of results. :attr str next_cursor: (optional) A token identifying the next page of results. """ def __init__(self, refresh_url: str, *, next_url: str = None, total: int = None, matched: int = None, refresh_cursor: str = None, next_cursor: str = None) -> None: """ Initialize a Pagination object. :param str refresh_url: The URL that will return the same page of results. :param str next_url: (optional) The URL that will return the next page of results. :param int total: (optional) The total number of objects that satisfy the request. This total includes all results, not just those included in the current page. :param int matched: (optional) Reserved for future use. :param str refresh_cursor: (optional) A token identifying the current page of results. :param str next_cursor: (optional) A token identifying the next page of results. """ self.refresh_url = refresh_url self.next_url = next_url self.total = total self.matched = matched self.refresh_cursor = refresh_cursor self.next_cursor = next_cursor @classmethod def from_dict(cls, _dict: Dict) -> 'Pagination': """Initialize a Pagination object from a json dictionary.""" args = {} if 'refresh_url' in _dict: args['refresh_url'] = _dict.get('refresh_url') else: raise ValueError( 'Required property \'refresh_url\' not present in Pagination JSON' ) if 'next_url' in _dict: args['next_url'] = _dict.get('next_url') if 'total' in _dict: args['total'] = _dict.get('total') if 'matched' in _dict: args['matched'] = _dict.get('matched') if 'refresh_cursor' in _dict: args['refresh_cursor'] = _dict.get('refresh_cursor') if 'next_cursor' in _dict: args['next_cursor'] = _dict.get('next_cursor') return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a Pagination object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'refresh_url') and self.refresh_url is not None: _dict['refresh_url'] = self.refresh_url if hasattr(self, 'next_url') and self.next_url is not None: _dict['next_url'] = self.next_url if hasattr(self, 'total') and self.total is not None: _dict['total'] = self.total if hasattr(self, 'matched') and self.matched is not None: _dict['matched'] = self.matched if hasattr(self, 'refresh_cursor') and self.refresh_cursor is not None: _dict['refresh_cursor'] = self.refresh_cursor if hasattr(self, 'next_cursor') and self.next_cursor is not None: _dict['next_cursor'] = self.next_cursor return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this Pagination object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'Pagination') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'Pagination') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class ResponseGenericChannel(): """ ResponseGenericChannel. :attr str channel: (optional) A channel for which the response is intended. """ def __init__(self, *, channel: str = None) -> None: """ Initialize a ResponseGenericChannel object. :param str channel: (optional) A channel for which the response is intended. """ self.channel = channel @classmethod def from_dict(cls, _dict: Dict) -> 'ResponseGenericChannel': """Initialize a ResponseGenericChannel object from a json dictionary.""" args = {} if 'channel' in _dict: args['channel'] = _dict.get('channel') return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a ResponseGenericChannel object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'channel') and self.channel is not None: _dict['channel'] = self.channel return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this ResponseGenericChannel object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'ResponseGenericChannel') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'ResponseGenericChannel') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class ChannelEnum(str, Enum): """ A channel for which the response is intended. """ CHAT = 'chat' FACEBOOK = 'facebook' INTERCOM = 'intercom' SLACK = 'slack' TEXT_MESSAGING = 'text_messaging' VOICE_TELEPHONY = 'voice_telephony' WHATSAPP = 'whatsapp' class RuntimeEntity(): """ A term from the request that was identified as an entity. :attr str entity: An entity detected in the input. :attr List[int] location: (optional) An array of zero-based character offsets that indicate where the detected entity values begin and end in the input text. :attr str value: The entity value that was recognized in the user input. :attr float confidence: (optional) A decimal percentage that represents Watson's confidence in the recognized entity. :attr List[CaptureGroup] groups: (optional) The recognized capture groups for the entity, as defined by the entity pattern. :attr RuntimeEntityInterpretation interpretation: (optional) An object containing detailed information about the entity recognized in the user input. For more information about how system entities are interpreted, see the [documentation](https://cloud.ibm.com/docs/assistant?topic=assistant-system-entities). :attr List[RuntimeEntityAlternative] alternatives: (optional) An array of possible alternative values that the user might have intended instead of the value returned in the **value** property. This property is returned only for `@sys-time` and `@sys-date` entities when the user's input is ambiguous. This property is included only if the new system entities are enabled for the workspace. :attr RuntimeEntityRole role: (optional) An object describing the role played by a system entity that is specifies the beginning or end of a range recognized in the user input. This property is included only if the new system entities are enabled for the workspace. """ def __init__(self, entity: str, value: str, *, location: List[int] = None, confidence: float = None, groups: List['CaptureGroup'] = None, interpretation: 'RuntimeEntityInterpretation' = None, alternatives: List['RuntimeEntityAlternative'] = None, role: 'RuntimeEntityRole' = None) -> None: """ Initialize a RuntimeEntity object. :param str entity: An entity detected in the input. :param str value: The entity value that was recognized in the user input. :param List[int] location: (optional) An array of zero-based character offsets that indicate where the detected entity values begin and end in the input text. :param float confidence: (optional) A decimal percentage that represents Watson's confidence in the recognized entity. :param List[CaptureGroup] groups: (optional) The recognized capture groups for the entity, as defined by the entity pattern. :param RuntimeEntityInterpretation interpretation: (optional) An object containing detailed information about the entity recognized in the user input. For more information about how system entities are interpreted, see the [documentation](https://cloud.ibm.com/docs/assistant?topic=assistant-system-entities). :param List[RuntimeEntityAlternative] alternatives: (optional) An array of possible alternative values that the user might have intended instead of the value returned in the **value** property. This property is returned only for `@sys-time` and `@sys-date` entities when the user's input is ambiguous. This property is included only if the new system entities are enabled for the workspace. :param RuntimeEntityRole role: (optional) An object describing the role played by a system entity that is specifies the beginning or end of a range recognized in the user input. This property is included only if the new system entities are enabled for the workspace. """ self.entity = entity self.location = location self.value = value self.confidence = confidence self.groups = groups self.interpretation = interpretation self.alternatives = alternatives self.role = role @classmethod def from_dict(cls, _dict: Dict) -> 'RuntimeEntity': """Initialize a RuntimeEntity object from a json dictionary.""" args = {} if 'entity' in _dict: args['entity'] = _dict.get('entity') else: raise ValueError( 'Required property \'entity\' not present in RuntimeEntity JSON' ) if 'location' in _dict: args['location'] = _dict.get('location') if 'value' in _dict: args['value'] = _dict.get('value') else: raise ValueError( 'Required property \'value\' not present in RuntimeEntity JSON') if 'confidence' in _dict: args['confidence'] = _dict.get('confidence') if 'groups' in _dict: args['groups'] = [ CaptureGroup.from_dict(x) for x in _dict.get('groups') ] if 'interpretation' in _dict: args['interpretation'] = RuntimeEntityInterpretation.from_dict( _dict.get('interpretation')) if 'alternatives' in _dict: args['alternatives'] = [ RuntimeEntityAlternative.from_dict(x) for x in _dict.get('alternatives') ] if 'role' in _dict: args['role'] = RuntimeEntityRole.from_dict(_dict.get('role')) return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a RuntimeEntity object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'entity') and self.entity is not None: _dict['entity'] = self.entity if hasattr(self, 'location') and self.location is not None: _dict['location'] = self.location if hasattr(self, 'value') and self.value is not None: _dict['value'] = self.value if hasattr(self, 'confidence') and self.confidence is not None: _dict['confidence'] = self.confidence if hasattr(self, 'groups') and self.groups is not None: _dict['groups'] = [x.to_dict() for x in self.groups] if hasattr(self, 'interpretation') and self.interpretation is not None: _dict['interpretation'] = self.interpretation.to_dict() if hasattr(self, 'alternatives') and self.alternatives is not None: _dict['alternatives'] = [x.to_dict() for x in self.alternatives] if hasattr(self, 'role') and self.role is not None: _dict['role'] = self.role.to_dict() return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this RuntimeEntity object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'RuntimeEntity') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'RuntimeEntity') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class RuntimeEntityAlternative(): """ An alternative value for the recognized entity. :attr str value: (optional) The entity value that was recognized in the user input. :attr float confidence: (optional) A decimal percentage that represents Watson's confidence in the recognized entity. """ def __init__(self, *, value: str = None, confidence: float = None) -> None: """ Initialize a RuntimeEntityAlternative object. :param str value: (optional) The entity value that was recognized in the user input. :param float confidence: (optional) A decimal percentage that represents Watson's confidence in the recognized entity. """ self.value = value self.confidence = confidence @classmethod def from_dict(cls, _dict: Dict) -> 'RuntimeEntityAlternative': """Initialize a RuntimeEntityAlternative object from a json dictionary.""" args = {} if 'value' in _dict: args['value'] = _dict.get('value') if 'confidence' in _dict: args['confidence'] = _dict.get('confidence') return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a RuntimeEntityAlternative object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'value') and self.value is not None: _dict['value'] = self.value if hasattr(self, 'confidence') and self.confidence is not None: _dict['confidence'] = self.confidence return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this RuntimeEntityAlternative object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'RuntimeEntityAlternative') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'RuntimeEntityAlternative') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class RuntimeEntityInterpretation(): """ RuntimeEntityInterpretation. :attr str calendar_type: (optional) The calendar used to represent a recognized date (for example, `Gregorian`). :attr str datetime_link: (optional) A unique identifier used to associate a recognized time and date. If the user input contains a date and time that are mentioned together (for example, `Today at 5`, the same **datetime_link** value is returned for both the `@sys-date` and `@sys-time` entities). :attr str festival: (optional) A locale-specific holiday name (such as `thanksgiving` or `christmas`). This property is included when a `@sys-date` entity is recognized based on a holiday name in the user input. :attr str granularity: (optional) The precision or duration of a time range specified by a recognized `@sys-time` or `@sys-date` entity. :attr str range_link: (optional) A unique identifier used to associate multiple recognized `@sys-date`, `@sys-time`, or `@sys-number` entities that are recognized as a range of values in the user's input (for example, `from July 4 until July 14` or `from 20 to 25`). :attr str range_modifier: (optional) The word in the user input that indicates that a `sys-date` or `sys-time` entity is part of an implied range where only one date or time is specified (for example, `since` or `until`). :attr float relative_day: (optional) A recognized mention of a relative day, represented numerically as an offset from the current date (for example, `-1` for `yesterday` or `10` for `in ten days`). :attr float relative_month: (optional) A recognized mention of a relative month, represented numerically as an offset from the current month (for example, `1` for `next month` or `-3` for `three months ago`). :attr float relative_week: (optional) A recognized mention of a relative week, represented numerically as an offset from the current week (for example, `2` for `in two weeks` or `-1` for `last week). :attr float relative_weekend: (optional) A recognized mention of a relative date range for a weekend, represented numerically as an offset from the current weekend (for example, `0` for `this weekend` or `-1` for `last weekend`). :attr float relative_year: (optional) A recognized mention of a relative year, represented numerically as an offset from the current year (for example, `1` for `next year` or `-5` for `five years ago`). :attr float specific_day: (optional) A recognized mention of a specific date, represented numerically as the date within the month (for example, `30` for `June 30`.). :attr str specific_day_of_week: (optional) A recognized mention of a specific day of the week as a lowercase string (for example, `monday`). :attr float specific_month: (optional) A recognized mention of a specific month, represented numerically (for example, `7` for `July`). :attr float specific_quarter: (optional) A recognized mention of a specific quarter, represented numerically (for example, `3` for `the third quarter`). :attr float specific_year: (optional) A recognized mention of a specific year (for example, `2016`). :attr float numeric_value: (optional) A recognized numeric value, represented as an integer or double. :attr str subtype: (optional) The type of numeric value recognized in the user input (`integer` or `rational`). :attr str part_of_day: (optional) A recognized term for a time that was mentioned as a part of the day in the user's input (for example, `morning` or `afternoon`). :attr float relative_hour: (optional) A recognized mention of a relative hour, represented numerically as an offset from the current hour (for example, `3` for `in three hours` or `-1` for `an hour ago`). :attr float relative_minute: (optional) A recognized mention of a relative time, represented numerically as an offset in minutes from the current time (for example, `5` for `in five minutes` or `-15` for `fifteen minutes ago`). :attr float relative_second: (optional) A recognized mention of a relative time, represented numerically as an offset in seconds from the current time (for example, `10` for `in ten seconds` or `-30` for `thirty seconds ago`). :attr float specific_hour: (optional) A recognized specific hour mentioned as part of a time value (for example, `10` for `10:15 AM`.). :attr float specific_minute: (optional) A recognized specific minute mentioned as part of a time value (for example, `15` for `10:15 AM`.). :attr float specific_second: (optional) A recognized specific second mentioned as part of a time value (for example, `30` for `10:15:30 AM`.). :attr str timezone: (optional) A recognized time zone mentioned as part of a time value (for example, `EST`). """ def __init__(self, *, calendar_type: str = None, datetime_link: str = None, festival: str = None, granularity: str = None, range_link: str = None, range_modifier: str = None, relative_day: float = None, relative_month: float = None, relative_week: float = None, relative_weekend: float = None, relative_year: float = None, specific_day: float = None, specific_day_of_week: str = None, specific_month: float = None, specific_quarter: float = None, specific_year: float = None, numeric_value: float = None, subtype: str = None, part_of_day: str = None, relative_hour: float = None, relative_minute: float = None, relative_second: float = None, specific_hour: float = None, specific_minute: float = None, specific_second: float = None, timezone: str = None) -> None: """ Initialize a RuntimeEntityInterpretation object. :param str calendar_type: (optional) The calendar used to represent a recognized date (for example, `Gregorian`). :param str datetime_link: (optional) A unique identifier used to associate a recognized time and date. If the user input contains a date and time that are mentioned together (for example, `Today at 5`, the same **datetime_link** value is returned for both the `@sys-date` and `@sys-time` entities). :param str festival: (optional) A locale-specific holiday name (such as `thanksgiving` or `christmas`). This property is included when a `@sys-date` entity is recognized based on a holiday name in the user input. :param str granularity: (optional) The precision or duration of a time range specified by a recognized `@sys-time` or `@sys-date` entity. :param str range_link: (optional) A unique identifier used to associate multiple recognized `@sys-date`, `@sys-time`, or `@sys-number` entities that are recognized as a range of values in the user's input (for example, `from July 4 until July 14` or `from 20 to 25`). :param str range_modifier: (optional) The word in the user input that indicates that a `sys-date` or `sys-time` entity is part of an implied range where only one date or time is specified (for example, `since` or `until`). :param float relative_day: (optional) A recognized mention of a relative day, represented numerically as an offset from the current date (for example, `-1` for `yesterday` or `10` for `in ten days`). :param float relative_month: (optional) A recognized mention of a relative month, represented numerically as an offset from the current month (for example, `1` for `next month` or `-3` for `three months ago`). :param float relative_week: (optional) A recognized mention of a relative week, represented numerically as an offset from the current week (for example, `2` for `in two weeks` or `-1` for `last week). :param float relative_weekend: (optional) A recognized mention of a relative date range for a weekend, represented numerically as an offset from the current weekend (for example, `0` for `this weekend` or `-1` for `last weekend`). :param float relative_year: (optional) A recognized mention of a relative year, represented numerically as an offset from the current year (for example, `1` for `next year` or `-5` for `five years ago`). :param float specific_day: (optional) A recognized mention of a specific date, represented numerically as the date within the month (for example, `30` for `June 30`.). :param str specific_day_of_week: (optional) A recognized mention of a specific day of the week as a lowercase string (for example, `monday`). :param float specific_month: (optional) A recognized mention of a specific month, represented numerically (for example, `7` for `July`). :param float specific_quarter: (optional) A recognized mention of a specific quarter, represented numerically (for example, `3` for `the third quarter`). :param float specific_year: (optional) A recognized mention of a specific year (for example, `2016`). :param float numeric_value: (optional) A recognized numeric value, represented as an integer or double. :param str subtype: (optional) The type of numeric value recognized in the user input (`integer` or `rational`). :param str part_of_day: (optional) A recognized term for a time that was mentioned as a part of the day in the user's input (for example, `morning` or `afternoon`). :param float relative_hour: (optional) A recognized mention of a relative hour, represented numerically as an offset from the current hour (for example, `3` for `in three hours` or `-1` for `an hour ago`). :param float relative_minute: (optional) A recognized mention of a relative time, represented numerically as an offset in minutes from the current time (for example, `5` for `in five minutes` or `-15` for `fifteen minutes ago`). :param float relative_second: (optional) A recognized mention of a relative time, represented numerically as an offset in seconds from the current time (for example, `10` for `in ten seconds` or `-30` for `thirty seconds ago`). :param float specific_hour: (optional) A recognized specific hour mentioned as part of a time value (for example, `10` for `10:15 AM`.). :param float specific_minute: (optional) A recognized specific minute mentioned as part of a time value (for example, `15` for `10:15 AM`.). :param float specific_second: (optional) A recognized specific second mentioned as part of a time value (for example, `30` for `10:15:30 AM`.). :param str timezone: (optional) A recognized time zone mentioned as part of a time value (for example, `EST`). """ self.calendar_type = calendar_type self.datetime_link = datetime_link self.festival = festival self.granularity = granularity self.range_link = range_link self.range_modifier = range_modifier self.relative_day = relative_day self.relative_month = relative_month self.relative_week = relative_week self.relative_weekend = relative_weekend self.relative_year = relative_year self.specific_day = specific_day self.specific_day_of_week = specific_day_of_week self.specific_month = specific_month self.specific_quarter = specific_quarter self.specific_year = specific_year self.numeric_value = numeric_value self.subtype = subtype self.part_of_day = part_of_day self.relative_hour = relative_hour self.relative_minute = relative_minute self.relative_second = relative_second self.specific_hour = specific_hour self.specific_minute = specific_minute self.specific_second = specific_second self.timezone = timezone @classmethod def from_dict(cls, _dict: Dict) -> 'RuntimeEntityInterpretation': """Initialize a RuntimeEntityInterpretation object from a json dictionary.""" args = {} if 'calendar_type' in _dict: args['calendar_type'] = _dict.get('calendar_type') if 'datetime_link' in _dict: args['datetime_link'] = _dict.get('datetime_link') if 'festival' in _dict: args['festival'] = _dict.get('festival') if 'granularity' in _dict: args['granularity'] = _dict.get('granularity') if 'range_link' in _dict: args['range_link'] = _dict.get('range_link') if 'range_modifier' in _dict: args['range_modifier'] = _dict.get('range_modifier') if 'relative_day' in _dict: args['relative_day'] = _dict.get('relative_day') if 'relative_month' in _dict: args['relative_month'] = _dict.get('relative_month') if 'relative_week' in _dict: args['relative_week'] = _dict.get('relative_week') if 'relative_weekend' in _dict: args['relative_weekend'] = _dict.get('relative_weekend') if 'relative_year' in _dict: args['relative_year'] = _dict.get('relative_year') if 'specific_day' in _dict: args['specific_day'] = _dict.get('specific_day') if 'specific_day_of_week' in _dict: args['specific_day_of_week'] = _dict.get('specific_day_of_week') if 'specific_month' in _dict: args['specific_month'] = _dict.get('specific_month') if 'specific_quarter' in _dict: args['specific_quarter'] = _dict.get('specific_quarter') if 'specific_year' in _dict: args['specific_year'] = _dict.get('specific_year') if 'numeric_value' in _dict: args['numeric_value'] = _dict.get('numeric_value') if 'subtype' in _dict: args['subtype'] = _dict.get('subtype') if 'part_of_day' in _dict: args['part_of_day'] = _dict.get('part_of_day') if 'relative_hour' in _dict: args['relative_hour'] = _dict.get('relative_hour') if 'relative_minute' in _dict: args['relative_minute'] = _dict.get('relative_minute') if 'relative_second' in _dict: args['relative_second'] = _dict.get('relative_second') if 'specific_hour' in _dict: args['specific_hour'] = _dict.get('specific_hour') if 'specific_minute' in _dict: args['specific_minute'] = _dict.get('specific_minute') if 'specific_second' in _dict: args['specific_second'] = _dict.get('specific_second') if 'timezone' in _dict: args['timezone'] = _dict.get('timezone') return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a RuntimeEntityInterpretation object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'calendar_type') and self.calendar_type is not None: _dict['calendar_type'] = self.calendar_type if hasattr(self, 'datetime_link') and self.datetime_link is not None: _dict['datetime_link'] = self.datetime_link if hasattr(self, 'festival') and self.festival is not None: _dict['festival'] = self.festival if hasattr(self, 'granularity') and self.granularity is not None: _dict['granularity'] = self.granularity if hasattr(self, 'range_link') and self.range_link is not None: _dict['range_link'] = self.range_link if hasattr(self, 'range_modifier') and self.range_modifier is not None: _dict['range_modifier'] = self.range_modifier if hasattr(self, 'relative_day') and self.relative_day is not None: _dict['relative_day'] = self.relative_day if hasattr(self, 'relative_month') and self.relative_month is not None: _dict['relative_month'] = self.relative_month if hasattr(self, 'relative_week') and self.relative_week is not None: _dict['relative_week'] = self.relative_week if hasattr(self, 'relative_weekend') and self.relative_weekend is not None: _dict['relative_weekend'] = self.relative_weekend if hasattr(self, 'relative_year') and self.relative_year is not None: _dict['relative_year'] = self.relative_year if hasattr(self, 'specific_day') and self.specific_day is not None: _dict['specific_day'] = self.specific_day if hasattr(self, 'specific_day_of_week' ) and self.specific_day_of_week is not None: _dict['specific_day_of_week'] = self.specific_day_of_week if hasattr(self, 'specific_month') and self.specific_month is not None: _dict['specific_month'] = self.specific_month if hasattr(self, 'specific_quarter') and self.specific_quarter is not None: _dict['specific_quarter'] = self.specific_quarter if hasattr(self, 'specific_year') and self.specific_year is not None: _dict['specific_year'] = self.specific_year if hasattr(self, 'numeric_value') and self.numeric_value is not None: _dict['numeric_value'] = self.numeric_value if hasattr(self, 'subtype') and self.subtype is not None: _dict['subtype'] = self.subtype if hasattr(self, 'part_of_day') and self.part_of_day is not None: _dict['part_of_day'] = self.part_of_day if hasattr(self, 'relative_hour') and self.relative_hour is not None: _dict['relative_hour'] = self.relative_hour if hasattr(self, 'relative_minute') and self.relative_minute is not None: _dict['relative_minute'] = self.relative_minute if hasattr(self, 'relative_second') and self.relative_second is not None: _dict['relative_second'] = self.relative_second if hasattr(self, 'specific_hour') and self.specific_hour is not None: _dict['specific_hour'] = self.specific_hour if hasattr(self, 'specific_minute') and self.specific_minute is not None: _dict['specific_minute'] = self.specific_minute if hasattr(self, 'specific_second') and self.specific_second is not None: _dict['specific_second'] = self.specific_second if hasattr(self, 'timezone') and self.timezone is not None: _dict['timezone'] = self.timezone return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this RuntimeEntityInterpretation object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'RuntimeEntityInterpretation') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'RuntimeEntityInterpretation') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class GranularityEnum(str, Enum): """ The precision or duration of a time range specified by a recognized `@sys-time` or `@sys-date` entity. """ DAY = 'day' FORTNIGHT = 'fortnight' HOUR = 'hour' INSTANT = 'instant' MINUTE = 'minute' MONTH = 'month' QUARTER = 'quarter' SECOND = 'second' WEEK = 'week' WEEKEND = 'weekend' YEAR = 'year' class RuntimeEntityRole(): """ An object describing the role played by a system entity that is specifies the beginning or end of a range recognized in the user input. This property is included only if the new system entities are enabled for the workspace. :attr str type: (optional) The relationship of the entity to the range. """ def __init__(self, *, type: str = None) -> None: """ Initialize a RuntimeEntityRole object. :param str type: (optional) The relationship of the entity to the range. """ self.type = type @classmethod def from_dict(cls, _dict: Dict) -> 'RuntimeEntityRole': """Initialize a RuntimeEntityRole object from a json dictionary.""" args = {} if 'type' in _dict: args['type'] = _dict.get('type') return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a RuntimeEntityRole object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'type') and self.type is not None: _dict['type'] = self.type return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this RuntimeEntityRole object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'RuntimeEntityRole') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'RuntimeEntityRole') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class TypeEnum(str, Enum): """ The relationship of the entity to the range. """ DATE_FROM = 'date_from' DATE_TO = 'date_to' NUMBER_FROM = 'number_from' NUMBER_TO = 'number_to' TIME_FROM = 'time_from' TIME_TO = 'time_to' class RuntimeIntent(): """ An intent identified in the user input. :attr str intent: The name of the recognized intent. :attr float confidence: (optional) A decimal percentage that represents Watson's confidence in the intent. If you are specifying an intent as part of a request, but you do not have a calculated confidence value, specify `1`. """ def __init__(self, intent: str, *, confidence: float = None) -> None: """ Initialize a RuntimeIntent object. :param str intent: The name of the recognized intent. :param float confidence: (optional) A decimal percentage that represents Watson's confidence in the intent. If you are specifying an intent as part of a request, but you do not have a calculated confidence value, specify `1`. """ self.intent = intent self.confidence = confidence @classmethod def from_dict(cls, _dict: Dict) -> 'RuntimeIntent': """Initialize a RuntimeIntent object from a json dictionary.""" args = {} if 'intent' in _dict: args['intent'] = _dict.get('intent') else: raise ValueError( 'Required property \'intent\' not present in RuntimeIntent JSON' ) if 'confidence' in _dict: args['confidence'] = _dict.get('confidence') return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a RuntimeIntent object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'intent') and self.intent is not None: _dict['intent'] = self.intent if hasattr(self, 'confidence') and self.confidence is not None: _dict['confidence'] = self.confidence return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this RuntimeIntent object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'RuntimeIntent') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'RuntimeIntent') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class RuntimeResponseGeneric(): """ RuntimeResponseGeneric. """ def __init__(self) -> None: """ Initialize a RuntimeResponseGeneric object. """ msg = "Cannot instantiate base class. Instead, instantiate one of the defined subclasses: {0}".format( ", ".join([ 'RuntimeResponseGenericRuntimeResponseTypeText', 'RuntimeResponseGenericRuntimeResponseTypePause', 'RuntimeResponseGenericRuntimeResponseTypeImage', 'RuntimeResponseGenericRuntimeResponseTypeOption', 'RuntimeResponseGenericRuntimeResponseTypeConnectToAgent', 'RuntimeResponseGenericRuntimeResponseTypeSuggestion', 'RuntimeResponseGenericRuntimeResponseTypeChannelTransfer', 'RuntimeResponseGenericRuntimeResponseTypeUserDefined', 'RuntimeResponseGenericRuntimeResponseTypeVideo', 'RuntimeResponseGenericRuntimeResponseTypeAudio', 'RuntimeResponseGenericRuntimeResponseTypeIframe' ])) raise Exception(msg) @classmethod def from_dict(cls, _dict: Dict) -> 'RuntimeResponseGeneric': """Initialize a RuntimeResponseGeneric object from a json dictionary.""" disc_class = cls._get_class_by_discriminator(_dict) if disc_class != cls: return disc_class.from_dict(_dict) msg = ( "Cannot convert dictionary into an instance of base class 'RuntimeResponseGeneric'. " + "The discriminator value should map to a valid subclass: {1}" ).format(", ".join([ 'RuntimeResponseGenericRuntimeResponseTypeText', 'RuntimeResponseGenericRuntimeResponseTypePause', 'RuntimeResponseGenericRuntimeResponseTypeImage', 'RuntimeResponseGenericRuntimeResponseTypeOption', 'RuntimeResponseGenericRuntimeResponseTypeConnectToAgent', 'RuntimeResponseGenericRuntimeResponseTypeSuggestion', 'RuntimeResponseGenericRuntimeResponseTypeChannelTransfer', 'RuntimeResponseGenericRuntimeResponseTypeUserDefined', 'RuntimeResponseGenericRuntimeResponseTypeVideo', 'RuntimeResponseGenericRuntimeResponseTypeAudio', 'RuntimeResponseGenericRuntimeResponseTypeIframe' ])) raise Exception(msg) @classmethod def _from_dict(cls, _dict: Dict): """Initialize a RuntimeResponseGeneric object from a json dictionary.""" return cls.from_dict(_dict) @classmethod def _get_class_by_discriminator(cls, _dict: Dict) -> object: mapping = {} mapping['audio'] = 'RuntimeResponseGenericRuntimeResponseTypeAudio' mapping[ 'channel_transfer'] = 'RuntimeResponseGenericRuntimeResponseTypeChannelTransfer' mapping[ 'connect_to_agent'] = 'RuntimeResponseGenericRuntimeResponseTypeConnectToAgent' mapping['iframe'] = 'RuntimeResponseGenericRuntimeResponseTypeIframe' mapping['image'] = 'RuntimeResponseGenericRuntimeResponseTypeImage' mapping['option'] = 'RuntimeResponseGenericRuntimeResponseTypeOption' mapping[ 'suggestion'] = 'RuntimeResponseGenericRuntimeResponseTypeSuggestion' mapping['pause'] = 'RuntimeResponseGenericRuntimeResponseTypePause' mapping['text'] = 'RuntimeResponseGenericRuntimeResponseTypeText' mapping[ 'user_defined'] = 'RuntimeResponseGenericRuntimeResponseTypeUserDefined' mapping['video'] = 'RuntimeResponseGenericRuntimeResponseTypeVideo' disc_value = _dict.get('response_type') if disc_value is None: raise ValueError( 'Discriminator property \'response_type\' not found in RuntimeResponseGeneric JSON' ) class_name = mapping.get(disc_value, disc_value) try: disc_class = getattr(sys.modules[__name__], class_name) except AttributeError: disc_class = cls if isinstance(disc_class, object): return disc_class raise TypeError('%s is not a discriminator class' % class_name) class StatusError(): """ An object describing an error that occurred during processing of an asynchronous operation. :attr str message: (optional) The text of the error message. """ def __init__(self, *, message: str = None) -> None: """ Initialize a StatusError object. :param str message: (optional) The text of the error message. """ self.message = message @classmethod def from_dict(cls, _dict: Dict) -> 'StatusError': """Initialize a StatusError object from a json dictionary.""" args = {} if 'message' in _dict: args['message'] = _dict.get('message') return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a StatusError object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'message') and self.message is not None: _dict['message'] = self.message return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this StatusError object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'StatusError') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'StatusError') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class Synonym(): """ Synonym. :attr str synonym: The text of the synonym. This string must conform to the following restrictions: - It cannot contain carriage return, newline, or tab characters. - It cannot consist of only whitespace characters. :attr datetime created: (optional) The timestamp for creation of the object. :attr datetime updated: (optional) The timestamp for the most recent update to the object. """ def __init__(self, synonym: str, *, created: datetime = None, updated: datetime = None) -> None: """ Initialize a Synonym object. :param str synonym: The text of the synonym. This string must conform to the following restrictions: - It cannot contain carriage return, newline, or tab characters. - It cannot consist of only whitespace characters. """ self.synonym = synonym self.created = created self.updated = updated @classmethod def from_dict(cls, _dict: Dict) -> 'Synonym': """Initialize a Synonym object from a json dictionary.""" args = {} if 'synonym' in _dict: args['synonym'] = _dict.get('synonym') else: raise ValueError( 'Required property \'synonym\' not present in Synonym JSON') if 'created' in _dict: args['created'] = string_to_datetime(_dict.get('created')) if 'updated' in _dict: args['updated'] = string_to_datetime(_dict.get('updated')) return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a Synonym object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'synonym') and self.synonym is not None: _dict['synonym'] = self.synonym if hasattr(self, 'created') and getattr(self, 'created') is not None: _dict['created'] = datetime_to_string(getattr(self, 'created')) if hasattr(self, 'updated') and getattr(self, 'updated') is not None: _dict['updated'] = datetime_to_string(getattr(self, 'updated')) return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this Synonym object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'Synonym') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'Synonym') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class SynonymCollection(): """ SynonymCollection. :attr List[Synonym] synonyms: An array of synonyms. :attr Pagination pagination: The pagination data for the returned objects. """ def __init__(self, synonyms: List['Synonym'], pagination: 'Pagination') -> None: """ Initialize a SynonymCollection object. :param List[Synonym] synonyms: An array of synonyms. :param Pagination pagination: The pagination data for the returned objects. """ self.synonyms = synonyms self.pagination = pagination @classmethod def from_dict(cls, _dict: Dict) -> 'SynonymCollection': """Initialize a SynonymCollection object from a json dictionary.""" args = {} if 'synonyms' in _dict: args['synonyms'] = [ Synonym.from_dict(x) for x in _dict.get('synonyms') ] else: raise ValueError( 'Required property \'synonyms\' not present in SynonymCollection JSON' ) if 'pagination' in _dict: args['pagination'] = Pagination.from_dict(_dict.get('pagination')) else: raise ValueError( 'Required property \'pagination\' not present in SynonymCollection JSON' ) return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a SynonymCollection object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'synonyms') and self.synonyms is not None: _dict['synonyms'] = [x.to_dict() for x in self.synonyms] if hasattr(self, 'pagination') and self.pagination is not None: _dict['pagination'] = self.pagination.to_dict() return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this SynonymCollection object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'SynonymCollection') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'SynonymCollection') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class Value(): """ Value. :attr str value: The text of the entity value. This string must conform to the following restrictions: - It cannot contain carriage return, newline, or tab characters. - It cannot consist of only whitespace characters. :attr dict metadata: (optional) Any metadata related to the entity value. :attr str type: Specifies the type of entity value. :attr List[str] synonyms: (optional) An array of synonyms for the entity value. A value can specify either synonyms or patterns (depending on the value type), but not both. A synonym must conform to the following resrictions: - It cannot contain carriage return, newline, or tab characters. - It cannot consist of only whitespace characters. :attr List[str] patterns: (optional) An array of patterns for the entity value. A value can specify either synonyms or patterns (depending on the value type), but not both. A pattern is a regular expression; for more information about how to specify a pattern, see the [documentation](https://cloud.ibm.com/docs/assistant?topic=assistant-entities#entities-create-dictionary-based). :attr datetime created: (optional) The timestamp for creation of the object. :attr datetime updated: (optional) The timestamp for the most recent update to the object. """ def __init__(self, value: str, type: str, *, metadata: dict = None, synonyms: List[str] = None, patterns: List[str] = None, created: datetime = None, updated: datetime = None) -> None: """ Initialize a Value object. :param str value: The text of the entity value. This string must conform to the following restrictions: - It cannot contain carriage return, newline, or tab characters. - It cannot consist of only whitespace characters. :param str type: Specifies the type of entity value. :param dict metadata: (optional) Any metadata related to the entity value. :param List[str] synonyms: (optional) An array of synonyms for the entity value. A value can specify either synonyms or patterns (depending on the value type), but not both. A synonym must conform to the following resrictions: - It cannot contain carriage return, newline, or tab characters. - It cannot consist of only whitespace characters. :param List[str] patterns: (optional) An array of patterns for the entity value. A value can specify either synonyms or patterns (depending on the value type), but not both. A pattern is a regular expression; for more information about how to specify a pattern, see the [documentation](https://cloud.ibm.com/docs/assistant?topic=assistant-entities#entities-create-dictionary-based). """ self.value = value self.metadata = metadata self.type = type self.synonyms = synonyms self.patterns = patterns self.created = created self.updated = updated @classmethod def from_dict(cls, _dict: Dict) -> 'Value': """Initialize a Value object from a json dictionary.""" args = {} if 'value' in _dict: args['value'] = _dict.get('value') else: raise ValueError( 'Required property \'value\' not present in Value JSON') if 'metadata' in _dict: args['metadata'] = _dict.get('metadata') if 'type' in _dict: args['type'] = _dict.get('type') else: raise ValueError( 'Required property \'type\' not present in Value JSON') if 'synonyms' in _dict: args['synonyms'] = _dict.get('synonyms') if 'patterns' in _dict: args['patterns'] = _dict.get('patterns') if 'created' in _dict: args['created'] = string_to_datetime(_dict.get('created')) if 'updated' in _dict: args['updated'] = string_to_datetime(_dict.get('updated')) return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a Value object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'value') and self.value is not None: _dict['value'] = self.value if hasattr(self, 'metadata') and self.metadata is not None: _dict['metadata'] = self.metadata if hasattr(self, 'type') and self.type is not None: _dict['type'] = self.type if hasattr(self, 'synonyms') and self.synonyms is not None: _dict['synonyms'] = self.synonyms if hasattr(self, 'patterns') and self.patterns is not None: _dict['patterns'] = self.patterns if hasattr(self, 'created') and getattr(self, 'created') is not None: _dict['created'] = datetime_to_string(getattr(self, 'created')) if hasattr(self, 'updated') and getattr(self, 'updated') is not None: _dict['updated'] = datetime_to_string(getattr(self, 'updated')) return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this Value object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'Value') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'Value') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class TypeEnum(str, Enum): """ Specifies the type of entity value. """ SYNONYMS = 'synonyms' PATTERNS = 'patterns' class ValueCollection(): """ ValueCollection. :attr List[Value] values: An array of entity values. :attr Pagination pagination: The pagination data for the returned objects. """ def __init__(self, values: List['Value'], pagination: 'Pagination') -> None: """ Initialize a ValueCollection object. :param List[Value] values: An array of entity values. :param Pagination pagination: The pagination data for the returned objects. """ self.values = values self.pagination = pagination @classmethod def from_dict(cls, _dict: Dict) -> 'ValueCollection': """Initialize a ValueCollection object from a json dictionary.""" args = {} if 'values' in _dict: args['values'] = [Value.from_dict(x) for x in _dict.get('values')] else: raise ValueError( 'Required property \'values\' not present in ValueCollection JSON' ) if 'pagination' in _dict: args['pagination'] = Pagination.from_dict(_dict.get('pagination')) else: raise ValueError( 'Required property \'pagination\' not present in ValueCollection JSON' ) return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a ValueCollection object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'values') and self.values is not None: _dict['values'] = [x.to_dict() for x in self.values] if hasattr(self, 'pagination') and self.pagination is not None: _dict['pagination'] = self.pagination.to_dict() return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this ValueCollection object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'ValueCollection') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'ValueCollection') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class Webhook(): """ A webhook that can be used by dialog nodes to make programmatic calls to an external function. **Note:** Currently, only a single webhook named `main_webhook` is supported. :attr str url: The URL for the external service or application to which you want to send HTTP POST requests. :attr str name: The name of the webhook. Currently, `main_webhook` is the only supported value. :attr List[WebhookHeader] headers_: (optional) An optional array of HTTP headers to pass with the HTTP request. """ def __init__(self, url: str, name: str, *, headers_: List['WebhookHeader'] = None) -> None: """ Initialize a Webhook object. :param str url: The URL for the external service or application to which you want to send HTTP POST requests. :param str name: The name of the webhook. Currently, `main_webhook` is the only supported value. :param List[WebhookHeader] headers_: (optional) An optional array of HTTP headers to pass with the HTTP request. """ self.url = url self.name = name self.headers_ = headers_ @classmethod def from_dict(cls, _dict: Dict) -> 'Webhook': """Initialize a Webhook object from a json dictionary.""" args = {} if 'url' in _dict: args['url'] = _dict.get('url') else: raise ValueError( 'Required property \'url\' not present in Webhook JSON') if 'name' in _dict: args['name'] = _dict.get('name') else: raise ValueError( 'Required property \'name\' not present in Webhook JSON') if 'headers' in _dict: args['headers_'] = [ WebhookHeader.from_dict(x) for x in _dict.get('headers') ] return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a Webhook object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'url') and self.url is not None: _dict['url'] = self.url if hasattr(self, 'name') and self.name is not None: _dict['name'] = self.name if hasattr(self, 'headers_') and self.headers_ is not None: _dict['headers'] = [x.to_dict() for x in self.headers_] return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this Webhook object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'Webhook') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'Webhook') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class WebhookHeader(): """ A key/value pair defining an HTTP header and a value. :attr str name: The name of an HTTP header (for example, `Authorization`). :attr str value: The value of an HTTP header. """ def __init__(self, name: str, value: str) -> None: """ Initialize a WebhookHeader object. :param str name: The name of an HTTP header (for example, `Authorization`). :param str value: The value of an HTTP header. """ self.name = name self.value = value @classmethod def from_dict(cls, _dict: Dict) -> 'WebhookHeader': """Initialize a WebhookHeader object from a json dictionary.""" args = {} if 'name' in _dict: args['name'] = _dict.get('name') else: raise ValueError( 'Required property \'name\' not present in WebhookHeader JSON') if 'value' in _dict: args['value'] = _dict.get('value') else: raise ValueError( 'Required property \'value\' not present in WebhookHeader JSON') return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a WebhookHeader object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'name') and self.name is not None: _dict['name'] = self.name if hasattr(self, 'value') and self.value is not None: _dict['value'] = self.value return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this WebhookHeader object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'WebhookHeader') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'WebhookHeader') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class Workspace(): """ Workspace. :attr str name: The name of the workspace. This string cannot contain carriage return, newline, or tab characters. :attr str description: (optional) The description of the workspace. This string cannot contain carriage return, newline, or tab characters. :attr str language: The language of the workspace. :attr str workspace_id: (optional) The workspace ID of the workspace. :attr List[DialogNode] dialog_nodes: (optional) An array of objects describing the dialog nodes in the workspace. :attr List[Counterexample] counterexamples: (optional) An array of objects defining input examples that have been marked as irrelevant input. :attr datetime created: (optional) The timestamp for creation of the object. :attr datetime updated: (optional) The timestamp for the most recent update to the object. :attr dict metadata: (optional) Any metadata related to the workspace. :attr bool learning_opt_out: Whether training data from the workspace (including artifacts such as intents and entities) can be used by IBM for general service improvements. `true` indicates that workspace training data is not to be used. :attr WorkspaceSystemSettings system_settings: (optional) Global settings for the workspace. :attr str status: (optional) The current status of the workspace: - **Available**: The workspace is available and ready to process messages. - **Failed**: An asynchronous operation has failed. See the **status_errors** property for more information about the cause of the failure. Returned only by the **Export workspace asynchronously** method. - **Non Existent**: The workspace does not exist. - **Processing**: An asynchronous operation has not yet completed. Returned only by the **Export workspace asynchronously** method. - **Training**: The workspace is training based on new data such as intents or examples. :attr List[StatusError] status_errors: (optional) An array of messages about errors that caused an asynchronous operation to fail. :attr List[Webhook] webhooks: (optional) :attr List[Intent] intents: (optional) An array of intents. :attr List[Entity] entities: (optional) An array of objects describing the entities for the workspace. :attr WorkspaceCounts counts: (optional) An object containing properties that indicate how many intents, entities, and dialog nodes are defined in the workspace. This property is included only in responses from the **Export workspace asynchronously** method, and only when the **verbose** query parameter is set to `true`. """ def __init__(self, name: str, language: str, learning_opt_out: bool, *, description: str = None, workspace_id: str = None, dialog_nodes: List['DialogNode'] = None, counterexamples: List['Counterexample'] = None, created: datetime = None, updated: datetime = None, metadata: dict = None, system_settings: 'WorkspaceSystemSettings' = None, status: str = None, status_errors: List['StatusError'] = None, webhooks: List['Webhook'] = None, intents: List['Intent'] = None, entities: List['Entity'] = None, counts: 'WorkspaceCounts' = None) -> None: """ Initialize a Workspace object. :param str name: The name of the workspace. This string cannot contain carriage return, newline, or tab characters. :param str language: The language of the workspace. :param bool learning_opt_out: Whether training data from the workspace (including artifacts such as intents and entities) can be used by IBM for general service improvements. `true` indicates that workspace training data is not to be used. :param str description: (optional) The description of the workspace. This string cannot contain carriage return, newline, or tab characters. :param List[DialogNode] dialog_nodes: (optional) An array of objects describing the dialog nodes in the workspace. :param List[Counterexample] counterexamples: (optional) An array of objects defining input examples that have been marked as irrelevant input. :param dict metadata: (optional) Any metadata related to the workspace. :param WorkspaceSystemSettings system_settings: (optional) Global settings for the workspace. :param List[Webhook] webhooks: (optional) :param List[Intent] intents: (optional) An array of intents. :param List[Entity] entities: (optional) An array of objects describing the entities for the workspace. :param WorkspaceCounts counts: (optional) An object containing properties that indicate how many intents, entities, and dialog nodes are defined in the workspace. This property is included only in responses from the **Export workspace asynchronously** method, and only when the **verbose** query parameter is set to `true`. """ self.name = name self.description = description self.language = language self.workspace_id = workspace_id self.dialog_nodes = dialog_nodes self.counterexamples = counterexamples self.created = created self.updated = updated self.metadata = metadata self.learning_opt_out = learning_opt_out self.system_settings = system_settings self.status = status self.status_errors = status_errors self.webhooks = webhooks self.intents = intents self.entities = entities self.counts = counts @classmethod def from_dict(cls, _dict: Dict) -> 'Workspace': """Initialize a Workspace object from a json dictionary.""" args = {} if 'name' in _dict: args['name'] = _dict.get('name') else: raise ValueError( 'Required property \'name\' not present in Workspace JSON') if 'description' in _dict: args['description'] = _dict.get('description') if 'language' in _dict: args['language'] = _dict.get('language') else: raise ValueError( 'Required property \'language\' not present in Workspace JSON') if 'workspace_id' in _dict: args['workspace_id'] = _dict.get('workspace_id') if 'dialog_nodes' in _dict: args['dialog_nodes'] = [ DialogNode.from_dict(x) for x in _dict.get('dialog_nodes') ] if 'counterexamples' in _dict: args['counterexamples'] = [ Counterexample.from_dict(x) for x in _dict.get('counterexamples') ] if 'created' in _dict: args['created'] = string_to_datetime(_dict.get('created')) if 'updated' in _dict: args['updated'] = string_to_datetime(_dict.get('updated')) if 'metadata' in _dict: args['metadata'] = _dict.get('metadata') if 'learning_opt_out' in _dict: args['learning_opt_out'] = _dict.get('learning_opt_out') else: raise ValueError( 'Required property \'learning_opt_out\' not present in Workspace JSON' ) if 'system_settings' in _dict: args['system_settings'] = WorkspaceSystemSettings.from_dict( _dict.get('system_settings')) if 'status' in _dict: args['status'] = _dict.get('status') if 'status_errors' in _dict: args['status_errors'] = [ StatusError.from_dict(x) for x in _dict.get('status_errors') ] if 'webhooks' in _dict: args['webhooks'] = [ Webhook.from_dict(x) for x in _dict.get('webhooks') ] if 'intents' in _dict: args['intents'] = [ Intent.from_dict(x) for x in _dict.get('intents') ] if 'entities' in _dict: args['entities'] = [ Entity.from_dict(x) for x in _dict.get('entities') ] if 'counts' in _dict: args['counts'] = WorkspaceCounts.from_dict(_dict.get('counts')) return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a Workspace object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'name') and self.name is not None: _dict['name'] = self.name if hasattr(self, 'description') and self.description is not None: _dict['description'] = self.description if hasattr(self, 'language') and self.language is not None: _dict['language'] = self.language if hasattr(self, 'workspace_id') and getattr( self, 'workspace_id') is not None: _dict['workspace_id'] = getattr(self, 'workspace_id') if hasattr(self, 'dialog_nodes') and self.dialog_nodes is not None: _dict['dialog_nodes'] = [x.to_dict() for x in self.dialog_nodes] if hasattr(self, 'counterexamples') and self.counterexamples is not None: _dict['counterexamples'] = [ x.to_dict() for x in self.counterexamples ] if hasattr(self, 'created') and getattr(self, 'created') is not None: _dict['created'] = datetime_to_string(getattr(self, 'created')) if hasattr(self, 'updated') and getattr(self, 'updated') is not None: _dict['updated'] = datetime_to_string(getattr(self, 'updated')) if hasattr(self, 'metadata') and self.metadata is not None: _dict['metadata'] = self.metadata if hasattr(self, 'learning_opt_out') and self.learning_opt_out is not None: _dict['learning_opt_out'] = self.learning_opt_out if hasattr(self, 'system_settings') and self.system_settings is not None: _dict['system_settings'] = self.system_settings.to_dict() if hasattr(self, 'status') and getattr(self, 'status') is not None: _dict['status'] = getattr(self, 'status') if hasattr(self, 'status_errors') and getattr( self, 'status_errors') is not None: _dict['status_errors'] = [ x.to_dict() for x in getattr(self, 'status_errors') ] if hasattr(self, 'webhooks') and self.webhooks is not None: _dict['webhooks'] = [x.to_dict() for x in self.webhooks] if hasattr(self, 'intents') and self.intents is not None: _dict['intents'] = [x.to_dict() for x in self.intents] if hasattr(self, 'entities') and self.entities is not None: _dict['entities'] = [x.to_dict() for x in self.entities] if hasattr(self, 'counts') and self.counts is not None: _dict['counts'] = self.counts.to_dict() return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this Workspace object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'Workspace') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'Workspace') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class StatusEnum(str, Enum): """ The current status of the workspace: - **Available**: The workspace is available and ready to process messages. - **Failed**: An asynchronous operation has failed. See the **status_errors** property for more information about the cause of the failure. Returned only by the **Export workspace asynchronously** method. - **Non Existent**: The workspace does not exist. - **Processing**: An asynchronous operation has not yet completed. Returned only by the **Export workspace asynchronously** method. - **Training**: The workspace is training based on new data such as intents or examples. """ AVAILABLE = 'Available' FAILED = 'Failed' NON_EXISTENT = 'Non Existent' PROCESSING = 'Processing' TRAINING = 'Training' UNAVAILABLE = 'Unavailable' class WorkspaceCollection(): """ WorkspaceCollection. :attr List[Workspace] workspaces: An array of objects describing the workspaces associated with the service instance. :attr Pagination pagination: The pagination data for the returned objects. """ def __init__(self, workspaces: List['Workspace'], pagination: 'Pagination') -> None: """ Initialize a WorkspaceCollection object. :param List[Workspace] workspaces: An array of objects describing the workspaces associated with the service instance. :param Pagination pagination: The pagination data for the returned objects. """ self.workspaces = workspaces self.pagination = pagination @classmethod def from_dict(cls, _dict: Dict) -> 'WorkspaceCollection': """Initialize a WorkspaceCollection object from a json dictionary.""" args = {} if 'workspaces' in _dict: args['workspaces'] = [ Workspace.from_dict(x) for x in _dict.get('workspaces') ] else: raise ValueError( 'Required property \'workspaces\' not present in WorkspaceCollection JSON' ) if 'pagination' in _dict: args['pagination'] = Pagination.from_dict(_dict.get('pagination')) else: raise ValueError( 'Required property \'pagination\' not present in WorkspaceCollection JSON' ) return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a WorkspaceCollection object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'workspaces') and self.workspaces is not None: _dict['workspaces'] = [x.to_dict() for x in self.workspaces] if hasattr(self, 'pagination') and self.pagination is not None: _dict['pagination'] = self.pagination.to_dict() return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this WorkspaceCollection object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'WorkspaceCollection') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'WorkspaceCollection') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class WorkspaceCounts(): """ An object containing properties that indicate how many intents, entities, and dialog nodes are defined in the workspace. This property is included only in responses from the **Export workspace asynchronously** method, and only when the **verbose** query parameter is set to `true`. :attr int intent: (optional) The number of intents defined in the workspace. :attr int entity: (optional) The number of entities defined in the workspace. :attr int node: (optional) The number of nodes defined in the workspace. """ def __init__(self, *, intent: int = None, entity: int = None, node: int = None) -> None: """ Initialize a WorkspaceCounts object. :param int intent: (optional) The number of intents defined in the workspace. :param int entity: (optional) The number of entities defined in the workspace. :param int node: (optional) The number of nodes defined in the workspace. """ self.intent = intent self.entity = entity self.node = node @classmethod def from_dict(cls, _dict: Dict) -> 'WorkspaceCounts': """Initialize a WorkspaceCounts object from a json dictionary.""" args = {} if 'intent' in _dict: args['intent'] = _dict.get('intent') if 'entity' in _dict: args['entity'] = _dict.get('entity') if 'node' in _dict: args['node'] = _dict.get('node') return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a WorkspaceCounts object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'intent') and self.intent is not None: _dict['intent'] = self.intent if hasattr(self, 'entity') and self.entity is not None: _dict['entity'] = self.entity if hasattr(self, 'node') and self.node is not None: _dict['node'] = self.node return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this WorkspaceCounts object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'WorkspaceCounts') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'WorkspaceCounts') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class WorkspaceSystemSettings(): """ Global settings for the workspace. :attr WorkspaceSystemSettingsTooling tooling: (optional) Workspace settings related to the Watson Assistant user interface. :attr WorkspaceSystemSettingsDisambiguation disambiguation: (optional) Workspace settings related to the disambiguation feature. :attr dict human_agent_assist: (optional) For internal use only. :attr bool spelling_suggestions: (optional) Whether spelling correction is enabled for the workspace. :attr bool spelling_auto_correct: (optional) Whether autocorrection is enabled for the workspace. If spelling correction is enabled and this property is `false`, any suggested corrections are returned in the **suggested_text** property of the message response. If this property is `true`, any corrections are automatically applied to the user input, and the original text is returned in the **original_text** property of the message response. :attr WorkspaceSystemSettingsSystemEntities system_entities: (optional) Workspace settings related to the behavior of system entities. :attr WorkspaceSystemSettingsOffTopic off_topic: (optional) Workspace settings related to detection of irrelevant input. :attr WorkspaceSystemSettingsNlp nlp: (optional) Workspace settings related to the version of the training algorithms currently used by the skill. """ # The set of defined properties for the class _properties = frozenset([ 'tooling', 'disambiguation', 'human_agent_assist', 'spelling_suggestions', 'spelling_auto_correct', 'system_entities', 'off_topic', 'nlp' ]) def __init__( self, *, tooling: 'WorkspaceSystemSettingsTooling' = None, disambiguation: 'WorkspaceSystemSettingsDisambiguation' = None, human_agent_assist: dict = None, spelling_suggestions: bool = None, spelling_auto_correct: bool = None, system_entities: 'WorkspaceSystemSettingsSystemEntities' = None, off_topic: 'WorkspaceSystemSettingsOffTopic' = None, nlp: 'WorkspaceSystemSettingsNlp' = None, **kwargs) -> None: """ Initialize a WorkspaceSystemSettings object. :param WorkspaceSystemSettingsTooling tooling: (optional) Workspace settings related to the Watson Assistant user interface. :param WorkspaceSystemSettingsDisambiguation disambiguation: (optional) Workspace settings related to the disambiguation feature. :param dict human_agent_assist: (optional) For internal use only. :param bool spelling_suggestions: (optional) Whether spelling correction is enabled for the workspace. :param bool spelling_auto_correct: (optional) Whether autocorrection is enabled for the workspace. If spelling correction is enabled and this property is `false`, any suggested corrections are returned in the **suggested_text** property of the message response. If this property is `true`, any corrections are automatically applied to the user input, and the original text is returned in the **original_text** property of the message response. :param WorkspaceSystemSettingsSystemEntities system_entities: (optional) Workspace settings related to the behavior of system entities. :param WorkspaceSystemSettingsOffTopic off_topic: (optional) Workspace settings related to detection of irrelevant input. :param WorkspaceSystemSettingsNlp nlp: (optional) Workspace settings related to the version of the training algorithms currently used by the skill. :param **kwargs: (optional) Any additional properties. """ self.tooling = tooling self.disambiguation = disambiguation self.human_agent_assist = human_agent_assist self.spelling_suggestions = spelling_suggestions self.spelling_auto_correct = spelling_auto_correct self.system_entities = system_entities self.off_topic = off_topic self.nlp = nlp for _key, _value in kwargs.items(): setattr(self, _key, _value) @classmethod def from_dict(cls, _dict: Dict) -> 'WorkspaceSystemSettings': """Initialize a WorkspaceSystemSettings object from a json dictionary.""" args = {} if 'tooling' in _dict: args['tooling'] = WorkspaceSystemSettingsTooling.from_dict( _dict.get('tooling')) if 'disambiguation' in _dict: args[ 'disambiguation'] = WorkspaceSystemSettingsDisambiguation.from_dict( _dict.get('disambiguation')) if 'human_agent_assist' in _dict: args['human_agent_assist'] = _dict.get('human_agent_assist') if 'spelling_suggestions' in _dict: args['spelling_suggestions'] = _dict.get('spelling_suggestions') if 'spelling_auto_correct' in _dict: args['spelling_auto_correct'] = _dict.get('spelling_auto_correct') if 'system_entities' in _dict: args[ 'system_entities'] = WorkspaceSystemSettingsSystemEntities.from_dict( _dict.get('system_entities')) if 'off_topic' in _dict: args['off_topic'] = WorkspaceSystemSettingsOffTopic.from_dict( _dict.get('off_topic')) if 'nlp' in _dict: args['nlp'] = WorkspaceSystemSettingsNlp.from_dict(_dict.get('nlp')) args.update( {k: v for (k, v) in _dict.items() if k not in cls._properties}) return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a WorkspaceSystemSettings object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'tooling') and self.tooling is not None: _dict['tooling'] = self.tooling.to_dict() if hasattr(self, 'disambiguation') and self.disambiguation is not None: _dict['disambiguation'] = self.disambiguation.to_dict() if hasattr( self, 'human_agent_assist') and self.human_agent_assist is not None: _dict['human_agent_assist'] = self.human_agent_assist if hasattr(self, 'spelling_suggestions' ) and self.spelling_suggestions is not None: _dict['spelling_suggestions'] = self.spelling_suggestions if hasattr(self, 'spelling_auto_correct' ) and self.spelling_auto_correct is not None: _dict['spelling_auto_correct'] = self.spelling_auto_correct if hasattr(self, 'system_entities') and self.system_entities is not None: _dict['system_entities'] = self.system_entities.to_dict() if hasattr(self, 'off_topic') and self.off_topic is not None: _dict['off_topic'] = self.off_topic.to_dict() if hasattr(self, 'nlp') and self.nlp is not None: _dict['nlp'] = self.nlp.to_dict() for _key in [ k for k in vars(self).keys() if k not in WorkspaceSystemSettings._properties ]: if getattr(self, _key, None) is not None: _dict[_key] = getattr(self, _key) return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def get_properties(self) -> Dict: """Return a dictionary of arbitrary properties from this instance of WorkspaceSystemSettings""" _dict = {} for _key in [ k for k in vars(self).keys() if k not in WorkspaceSystemSettings._properties ]: _dict[_key] = getattr(self, _key) return _dict def set_properties(self, _dict: dict): """Set a dictionary of arbitrary properties to this instance of WorkspaceSystemSettings""" for _key in [ k for k in vars(self).keys() if k not in WorkspaceSystemSettings._properties ]: delattr(self, _key) for _key, _value in _dict.items(): if _key not in WorkspaceSystemSettings._properties: setattr(self, _key, _value) def __str__(self) -> str: """Return a `str` version of this WorkspaceSystemSettings object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'WorkspaceSystemSettings') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'WorkspaceSystemSettings') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class WorkspaceSystemSettingsDisambiguation(): """ Workspace settings related to the disambiguation feature. :attr str prompt: (optional) The text of the introductory prompt that accompanies disambiguation options presented to the user. :attr str none_of_the_above_prompt: (optional) The user-facing label for the option users can select if none of the suggested options is correct. If no value is specified for this property, this option does not appear. :attr bool enabled: (optional) Whether the disambiguation feature is enabled for the workspace. :attr str sensitivity: (optional) The sensitivity of the disambiguation feature to intent detection uncertainty. Higher sensitivity means that the disambiguation feature is triggered more often and includes more choices. :attr bool randomize: (optional) Whether the order in which disambiguation suggestions are presented should be randomized (but still influenced by relative confidence). :attr int max_suggestions: (optional) The maximum number of disambigation suggestions that can be included in a `suggestion` response. :attr str suggestion_text_policy: (optional) For internal use only. """ def __init__(self, *, prompt: str = None, none_of_the_above_prompt: str = None, enabled: bool = None, sensitivity: str = None, randomize: bool = None, max_suggestions: int = None, suggestion_text_policy: str = None) -> None: """ Initialize a WorkspaceSystemSettingsDisambiguation object. :param str prompt: (optional) The text of the introductory prompt that accompanies disambiguation options presented to the user. :param str none_of_the_above_prompt: (optional) The user-facing label for the option users can select if none of the suggested options is correct. If no value is specified for this property, this option does not appear. :param bool enabled: (optional) Whether the disambiguation feature is enabled for the workspace. :param str sensitivity: (optional) The sensitivity of the disambiguation feature to intent detection uncertainty. Higher sensitivity means that the disambiguation feature is triggered more often and includes more choices. :param bool randomize: (optional) Whether the order in which disambiguation suggestions are presented should be randomized (but still influenced by relative confidence). :param int max_suggestions: (optional) The maximum number of disambigation suggestions that can be included in a `suggestion` response. :param str suggestion_text_policy: (optional) For internal use only. """ self.prompt = prompt self.none_of_the_above_prompt = none_of_the_above_prompt self.enabled = enabled self.sensitivity = sensitivity self.randomize = randomize self.max_suggestions = max_suggestions self.suggestion_text_policy = suggestion_text_policy @classmethod def from_dict(cls, _dict: Dict) -> 'WorkspaceSystemSettingsDisambiguation': """Initialize a WorkspaceSystemSettingsDisambiguation object from a json dictionary.""" args = {} if 'prompt' in _dict: args['prompt'] = _dict.get('prompt') if 'none_of_the_above_prompt' in _dict: args['none_of_the_above_prompt'] = _dict.get( 'none_of_the_above_prompt') if 'enabled' in _dict: args['enabled'] = _dict.get('enabled') if 'sensitivity' in _dict: args['sensitivity'] = _dict.get('sensitivity') if 'randomize' in _dict: args['randomize'] = _dict.get('randomize') if 'max_suggestions' in _dict: args['max_suggestions'] = _dict.get('max_suggestions') if 'suggestion_text_policy' in _dict: args['suggestion_text_policy'] = _dict.get('suggestion_text_policy') return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a WorkspaceSystemSettingsDisambiguation object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'prompt') and self.prompt is not None: _dict['prompt'] = self.prompt if hasattr(self, 'none_of_the_above_prompt' ) and self.none_of_the_above_prompt is not None: _dict['none_of_the_above_prompt'] = self.none_of_the_above_prompt if hasattr(self, 'enabled') and self.enabled is not None: _dict['enabled'] = self.enabled if hasattr(self, 'sensitivity') and self.sensitivity is not None: _dict['sensitivity'] = self.sensitivity if hasattr(self, 'randomize') and self.randomize is not None: _dict['randomize'] = self.randomize if hasattr(self, 'max_suggestions') and self.max_suggestions is not None: _dict['max_suggestions'] = self.max_suggestions if hasattr(self, 'suggestion_text_policy' ) and self.suggestion_text_policy is not None: _dict['suggestion_text_policy'] = self.suggestion_text_policy return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this WorkspaceSystemSettingsDisambiguation object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'WorkspaceSystemSettingsDisambiguation') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'WorkspaceSystemSettingsDisambiguation') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class SensitivityEnum(str, Enum): """ The sensitivity of the disambiguation feature to intent detection uncertainty. Higher sensitivity means that the disambiguation feature is triggered more often and includes more choices. """ AUTO = 'auto' HIGH = 'high' MEDIUM_HIGH = 'medium_high' MEDIUM = 'medium' MEDIUM_LOW = 'medium_low' LOW = 'low' class WorkspaceSystemSettingsNlp(): """ Workspace settings related to the version of the training algorithms currently used by the skill. :attr str model: (optional) The policy the skill follows for selecting the algorithm version to use: - `baseline`: the latest mature version - `beta`: the latest beta version. """ def __init__(self, *, model: str = None) -> None: """ Initialize a WorkspaceSystemSettingsNlp object. :param str model: (optional) The policy the skill follows for selecting the algorithm version to use: - `baseline`: the latest mature version - `beta`: the latest beta version. """ self.model = model @classmethod def from_dict(cls, _dict: Dict) -> 'WorkspaceSystemSettingsNlp': """Initialize a WorkspaceSystemSettingsNlp object from a json dictionary.""" args = {} if 'model' in _dict: args['model'] = _dict.get('model') return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a WorkspaceSystemSettingsNlp object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'model') and self.model is not None: _dict['model'] = self.model return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this WorkspaceSystemSettingsNlp object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'WorkspaceSystemSettingsNlp') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'WorkspaceSystemSettingsNlp') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class ModelEnum(str, Enum): """ The policy the skill follows for selecting the algorithm version to use: - `baseline`: the latest mature version - `beta`: the latest beta version. """ BASELINE = 'baseline' BETA = 'beta' class WorkspaceSystemSettingsOffTopic(): """ Workspace settings related to detection of irrelevant input. :attr bool enabled: (optional) Whether enhanced irrelevance detection is enabled for the workspace. """ def __init__(self, *, enabled: bool = None) -> None: """ Initialize a WorkspaceSystemSettingsOffTopic object. :param bool enabled: (optional) Whether enhanced irrelevance detection is enabled for the workspace. """ self.enabled = enabled @classmethod def from_dict(cls, _dict: Dict) -> 'WorkspaceSystemSettingsOffTopic': """Initialize a WorkspaceSystemSettingsOffTopic object from a json dictionary.""" args = {} if 'enabled' in _dict: args['enabled'] = _dict.get('enabled') return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a WorkspaceSystemSettingsOffTopic object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'enabled') and self.enabled is not None: _dict['enabled'] = self.enabled return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this WorkspaceSystemSettingsOffTopic object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'WorkspaceSystemSettingsOffTopic') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'WorkspaceSystemSettingsOffTopic') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class WorkspaceSystemSettingsSystemEntities(): """ Workspace settings related to the behavior of system entities. :attr bool enabled: (optional) Whether the new system entities are enabled for the workspace. """ def __init__(self, *, enabled: bool = None) -> None: """ Initialize a WorkspaceSystemSettingsSystemEntities object. :param bool enabled: (optional) Whether the new system entities are enabled for the workspace. """ self.enabled = enabled @classmethod def from_dict(cls, _dict: Dict) -> 'WorkspaceSystemSettingsSystemEntities': """Initialize a WorkspaceSystemSettingsSystemEntities object from a json dictionary.""" args = {} if 'enabled' in _dict: args['enabled'] = _dict.get('enabled') return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a WorkspaceSystemSettingsSystemEntities object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'enabled') and self.enabled is not None: _dict['enabled'] = self.enabled return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this WorkspaceSystemSettingsSystemEntities object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'WorkspaceSystemSettingsSystemEntities') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'WorkspaceSystemSettingsSystemEntities') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class WorkspaceSystemSettingsTooling(): """ Workspace settings related to the Watson Assistant user interface. :attr bool store_generic_responses: (optional) Whether the dialog JSON editor displays text responses within the `output.generic` object. """ def __init__(self, *, store_generic_responses: bool = None) -> None: """ Initialize a WorkspaceSystemSettingsTooling object. :param bool store_generic_responses: (optional) Whether the dialog JSON editor displays text responses within the `output.generic` object. """ self.store_generic_responses = store_generic_responses @classmethod def from_dict(cls, _dict: Dict) -> 'WorkspaceSystemSettingsTooling': """Initialize a WorkspaceSystemSettingsTooling object from a json dictionary.""" args = {} if 'store_generic_responses' in _dict: args['store_generic_responses'] = _dict.get( 'store_generic_responses') return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a WorkspaceSystemSettingsTooling object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'store_generic_responses' ) and self.store_generic_responses is not None: _dict['store_generic_responses'] = self.store_generic_responses return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this WorkspaceSystemSettingsTooling object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'WorkspaceSystemSettingsTooling') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'WorkspaceSystemSettingsTooling') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class DialogNodeOutputGenericDialogNodeOutputResponseTypeAudio( DialogNodeOutputGeneric): """ DialogNodeOutputGenericDialogNodeOutputResponseTypeAudio. :attr str response_type: The type of response returned by the dialog node. The specified response type must be supported by the client application or channel. :attr str source: The `https:` URL of the audio clip. :attr str title: (optional) An optional title to show before the response. :attr str description: (optional) An optional description to show with the response. :attr List[ResponseGenericChannel] channels: (optional) An array of objects specifying channels for which the response is intended. If **channels** is present, the response is intended for a built-in integration and should not be handled by an API client. :attr object channel_options: (optional) For internal use only. :attr str alt_text: (optional) Descriptive text that can be used for screen readers or other situations where the audio player cannot be seen. """ def __init__(self, response_type: str, source: str, *, title: str = None, description: str = None, channels: List['ResponseGenericChannel'] = None, channel_options: object = None, alt_text: str = None) -> None: """ Initialize a DialogNodeOutputGenericDialogNodeOutputResponseTypeAudio object. :param str response_type: The type of response returned by the dialog node. The specified response type must be supported by the client application or channel. :param str source: The `https:` URL of the audio clip. :param str title: (optional) An optional title to show before the response. :param str description: (optional) An optional description to show with the response. :param List[ResponseGenericChannel] channels: (optional) An array of objects specifying channels for which the response is intended. If **channels** is present, the response is intended for a built-in integration and should not be handled by an API client. :param object channel_options: (optional) For internal use only. :param str alt_text: (optional) Descriptive text that can be used for screen readers or other situations where the audio player cannot be seen. """ # pylint: disable=super-init-not-called self.response_type = response_type self.source = source self.title = title self.description = description self.channels = channels self.channel_options = channel_options self.alt_text = alt_text @classmethod def from_dict( cls, _dict: Dict ) -> 'DialogNodeOutputGenericDialogNodeOutputResponseTypeAudio': """Initialize a DialogNodeOutputGenericDialogNodeOutputResponseTypeAudio object from a json dictionary.""" args = {} if 'response_type' in _dict: args['response_type'] = _dict.get('response_type') else: raise ValueError( 'Required property \'response_type\' not present in DialogNodeOutputGenericDialogNodeOutputResponseTypeAudio JSON' ) if 'source' in _dict: args['source'] = _dict.get('source') else: raise ValueError( 'Required property \'source\' not present in DialogNodeOutputGenericDialogNodeOutputResponseTypeAudio JSON' ) if 'title' in _dict: args['title'] = _dict.get('title') if 'description' in _dict: args['description'] = _dict.get('description') if 'channels' in _dict: args['channels'] = [ ResponseGenericChannel.from_dict(x) for x in _dict.get('channels') ] if 'channel_options' in _dict: args['channel_options'] = _dict.get('channel_options') if 'alt_text' in _dict: args['alt_text'] = _dict.get('alt_text') return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a DialogNodeOutputGenericDialogNodeOutputResponseTypeAudio object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'response_type') and self.response_type is not None: _dict['response_type'] = self.response_type if hasattr(self, 'source') and self.source is not None: _dict['source'] = self.source if hasattr(self, 'title') and self.title is not None: _dict['title'] = self.title if hasattr(self, 'description') and self.description is not None: _dict['description'] = self.description if hasattr(self, 'channels') and self.channels is not None: _dict['channels'] = [x.to_dict() for x in self.channels] if hasattr(self, 'channel_options') and self.channel_options is not None: _dict['channel_options'] = self.channel_options if hasattr(self, 'alt_text') and self.alt_text is not None: _dict['alt_text'] = self.alt_text return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this DialogNodeOutputGenericDialogNodeOutputResponseTypeAudio object.""" return json.dumps(self.to_dict(), indent=2) def __eq__( self, other: 'DialogNodeOutputGenericDialogNodeOutputResponseTypeAudio' ) -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__( self, other: 'DialogNodeOutputGenericDialogNodeOutputResponseTypeAudio' ) -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class DialogNodeOutputGenericDialogNodeOutputResponseTypeChannelTransfer( DialogNodeOutputGeneric): """ DialogNodeOutputGenericDialogNodeOutputResponseTypeChannelTransfer. :attr str response_type: The type of response returned by the dialog node. The specified response type must be supported by the client application or channel. :attr str message_to_user: The message to display to the user when initiating a channel transfer. :attr ChannelTransferInfo transfer_info: Information used by an integration to transfer the conversation to a different channel. :attr List[ResponseGenericChannel] channels: (optional) An array of objects specifying channels for which the response is intended. """ def __init__(self, response_type: str, message_to_user: str, transfer_info: 'ChannelTransferInfo', *, channels: List['ResponseGenericChannel'] = None) -> None: """ Initialize a DialogNodeOutputGenericDialogNodeOutputResponseTypeChannelTransfer object. :param str response_type: The type of response returned by the dialog node. The specified response type must be supported by the client application or channel. :param str message_to_user: The message to display to the user when initiating a channel transfer. :param ChannelTransferInfo transfer_info: Information used by an integration to transfer the conversation to a different channel. :param List[ResponseGenericChannel] channels: (optional) An array of objects specifying channels for which the response is intended. """ # pylint: disable=super-init-not-called self.response_type = response_type self.message_to_user = message_to_user self.transfer_info = transfer_info self.channels = channels @classmethod def from_dict( cls, _dict: Dict ) -> 'DialogNodeOutputGenericDialogNodeOutputResponseTypeChannelTransfer': """Initialize a DialogNodeOutputGenericDialogNodeOutputResponseTypeChannelTransfer object from a json dictionary.""" args = {} if 'response_type' in _dict: args['response_type'] = _dict.get('response_type') else: raise ValueError( 'Required property \'response_type\' not present in DialogNodeOutputGenericDialogNodeOutputResponseTypeChannelTransfer JSON' ) if 'message_to_user' in _dict: args['message_to_user'] = _dict.get('message_to_user') else: raise ValueError( 'Required property \'message_to_user\' not present in DialogNodeOutputGenericDialogNodeOutputResponseTypeChannelTransfer JSON' ) if 'transfer_info' in _dict: args['transfer_info'] = ChannelTransferInfo.from_dict( _dict.get('transfer_info')) else: raise ValueError( 'Required property \'transfer_info\' not present in DialogNodeOutputGenericDialogNodeOutputResponseTypeChannelTransfer JSON' ) if 'channels' in _dict: args['channels'] = [ ResponseGenericChannel.from_dict(x) for x in _dict.get('channels') ] return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a DialogNodeOutputGenericDialogNodeOutputResponseTypeChannelTransfer object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'response_type') and self.response_type is not None: _dict['response_type'] = self.response_type if hasattr(self, 'message_to_user') and self.message_to_user is not None: _dict['message_to_user'] = self.message_to_user if hasattr(self, 'transfer_info') and self.transfer_info is not None: _dict['transfer_info'] = self.transfer_info.to_dict() if hasattr(self, 'channels') and self.channels is not None: _dict['channels'] = [x.to_dict() for x in self.channels] return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this DialogNodeOutputGenericDialogNodeOutputResponseTypeChannelTransfer object.""" return json.dumps(self.to_dict(), indent=2) def __eq__( self, other: 'DialogNodeOutputGenericDialogNodeOutputResponseTypeChannelTransfer' ) -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__( self, other: 'DialogNodeOutputGenericDialogNodeOutputResponseTypeChannelTransfer' ) -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class DialogNodeOutputGenericDialogNodeOutputResponseTypeConnectToAgent( DialogNodeOutputGeneric): """ DialogNodeOutputGenericDialogNodeOutputResponseTypeConnectToAgent. :attr str response_type: The type of response returned by the dialog node. The specified response type must be supported by the client application or channel. :attr str message_to_human_agent: (optional) An optional message to be sent to the human agent who will be taking over the conversation. :attr AgentAvailabilityMessage agent_available: (optional) An optional message to be displayed to the user to indicate that the conversation will be transferred to the next available agent. :attr AgentAvailabilityMessage agent_unavailable: (optional) An optional message to be displayed to the user to indicate that no online agent is available to take over the conversation. :attr DialogNodeOutputConnectToAgentTransferInfo transfer_info: (optional) Routing or other contextual information to be used by target service desk systems. :attr List[ResponseGenericChannel] channels: (optional) An array of objects specifying channels for which the response is intended. """ def __init__( self, response_type: str, *, message_to_human_agent: str = None, agent_available: 'AgentAvailabilityMessage' = None, agent_unavailable: 'AgentAvailabilityMessage' = None, transfer_info: 'DialogNodeOutputConnectToAgentTransferInfo' = None, channels: List['ResponseGenericChannel'] = None) -> None: """ Initialize a DialogNodeOutputGenericDialogNodeOutputResponseTypeConnectToAgent object. :param str response_type: The type of response returned by the dialog node. The specified response type must be supported by the client application or channel. :param str message_to_human_agent: (optional) An optional message to be sent to the human agent who will be taking over the conversation. :param AgentAvailabilityMessage agent_available: (optional) An optional message to be displayed to the user to indicate that the conversation will be transferred to the next available agent. :param AgentAvailabilityMessage agent_unavailable: (optional) An optional message to be displayed to the user to indicate that no online agent is available to take over the conversation. :param DialogNodeOutputConnectToAgentTransferInfo transfer_info: (optional) Routing or other contextual information to be used by target service desk systems. :param List[ResponseGenericChannel] channels: (optional) An array of objects specifying channels for which the response is intended. """ # pylint: disable=super-init-not-called self.response_type = response_type self.message_to_human_agent = message_to_human_agent self.agent_available = agent_available self.agent_unavailable = agent_unavailable self.transfer_info = transfer_info self.channels = channels @classmethod def from_dict( cls, _dict: Dict ) -> 'DialogNodeOutputGenericDialogNodeOutputResponseTypeConnectToAgent': """Initialize a DialogNodeOutputGenericDialogNodeOutputResponseTypeConnectToAgent object from a json dictionary.""" args = {} if 'response_type' in _dict: args['response_type'] = _dict.get('response_type') else: raise ValueError( 'Required property \'response_type\' not present in DialogNodeOutputGenericDialogNodeOutputResponseTypeConnectToAgent JSON' ) if 'message_to_human_agent' in _dict: args['message_to_human_agent'] = _dict.get('message_to_human_agent') if 'agent_available' in _dict: args['agent_available'] = AgentAvailabilityMessage.from_dict( _dict.get('agent_available')) if 'agent_unavailable' in _dict: args['agent_unavailable'] = AgentAvailabilityMessage.from_dict( _dict.get('agent_unavailable')) if 'transfer_info' in _dict: args[ 'transfer_info'] = DialogNodeOutputConnectToAgentTransferInfo.from_dict( _dict.get('transfer_info')) if 'channels' in _dict: args['channels'] = [ ResponseGenericChannel.from_dict(x) for x in _dict.get('channels') ] return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a DialogNodeOutputGenericDialogNodeOutputResponseTypeConnectToAgent object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'response_type') and self.response_type is not None: _dict['response_type'] = self.response_type if hasattr(self, 'message_to_human_agent' ) and self.message_to_human_agent is not None: _dict['message_to_human_agent'] = self.message_to_human_agent if hasattr(self, 'agent_available') and self.agent_available is not None: _dict['agent_available'] = self.agent_available.to_dict() if hasattr(self, 'agent_unavailable') and self.agent_unavailable is not None: _dict['agent_unavailable'] = self.agent_unavailable.to_dict() if hasattr(self, 'transfer_info') and self.transfer_info is not None: _dict['transfer_info'] = self.transfer_info.to_dict() if hasattr(self, 'channels') and self.channels is not None: _dict['channels'] = [x.to_dict() for x in self.channels] return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this DialogNodeOutputGenericDialogNodeOutputResponseTypeConnectToAgent object.""" return json.dumps(self.to_dict(), indent=2) def __eq__( self, other: 'DialogNodeOutputGenericDialogNodeOutputResponseTypeConnectToAgent' ) -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__( self, other: 'DialogNodeOutputGenericDialogNodeOutputResponseTypeConnectToAgent' ) -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class DialogNodeOutputGenericDialogNodeOutputResponseTypeIframe( DialogNodeOutputGeneric): """ DialogNodeOutputGenericDialogNodeOutputResponseTypeIframe. :attr str response_type: The type of response returned by the dialog node. The specified response type must be supported by the client application or channel. :attr str source: The `https:` URL of the embeddable content. :attr str title: (optional) An optional title to show before the response. :attr str description: (optional) An optional description to show with the response. :attr str image_url: (optional) The URL of an image that shows a preview of the embedded content. :attr List[ResponseGenericChannel] channels: (optional) An array of objects specifying channels for which the response is intended. If **channels** is present, the response is intended for a built-in integration and should not be handled by an API client. """ def __init__(self, response_type: str, source: str, *, title: str = None, description: str = None, image_url: str = None, channels: List['ResponseGenericChannel'] = None) -> None: """ Initialize a DialogNodeOutputGenericDialogNodeOutputResponseTypeIframe object. :param str response_type: The type of response returned by the dialog node. The specified response type must be supported by the client application or channel. :param str source: The `https:` URL of the embeddable content. :param str title: (optional) An optional title to show before the response. :param str description: (optional) An optional description to show with the response. :param str image_url: (optional) The URL of an image that shows a preview of the embedded content. :param List[ResponseGenericChannel] channels: (optional) An array of objects specifying channels for which the response is intended. If **channels** is present, the response is intended for a built-in integration and should not be handled by an API client. """ # pylint: disable=super-init-not-called self.response_type = response_type self.source = source self.title = title self.description = description self.image_url = image_url self.channels = channels @classmethod def from_dict( cls, _dict: Dict ) -> 'DialogNodeOutputGenericDialogNodeOutputResponseTypeIframe': """Initialize a DialogNodeOutputGenericDialogNodeOutputResponseTypeIframe object from a json dictionary.""" args = {} if 'response_type' in _dict: args['response_type'] = _dict.get('response_type') else: raise ValueError( 'Required property \'response_type\' not present in DialogNodeOutputGenericDialogNodeOutputResponseTypeIframe JSON' ) if 'source' in _dict: args['source'] = _dict.get('source') else: raise ValueError( 'Required property \'source\' not present in DialogNodeOutputGenericDialogNodeOutputResponseTypeIframe JSON' ) if 'title' in _dict: args['title'] = _dict.get('title') if 'description' in _dict: args['description'] = _dict.get('description') if 'image_url' in _dict: args['image_url'] = _dict.get('image_url') if 'channels' in _dict: args['channels'] = [ ResponseGenericChannel.from_dict(x) for x in _dict.get('channels') ] return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a DialogNodeOutputGenericDialogNodeOutputResponseTypeIframe object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'response_type') and self.response_type is not None: _dict['response_type'] = self.response_type if hasattr(self, 'source') and self.source is not None: _dict['source'] = self.source if hasattr(self, 'title') and self.title is not None: _dict['title'] = self.title if hasattr(self, 'description') and self.description is not None: _dict['description'] = self.description if hasattr(self, 'image_url') and self.image_url is not None: _dict['image_url'] = self.image_url if hasattr(self, 'channels') and self.channels is not None: _dict['channels'] = [x.to_dict() for x in self.channels] return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this DialogNodeOutputGenericDialogNodeOutputResponseTypeIframe object.""" return json.dumps(self.to_dict(), indent=2) def __eq__( self, other: 'DialogNodeOutputGenericDialogNodeOutputResponseTypeIframe' ) -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__( self, other: 'DialogNodeOutputGenericDialogNodeOutputResponseTypeIframe' ) -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class DialogNodeOutputGenericDialogNodeOutputResponseTypeImage( DialogNodeOutputGeneric): """ DialogNodeOutputGenericDialogNodeOutputResponseTypeImage. :attr str response_type: The type of response returned by the dialog node. The specified response type must be supported by the client application or channel. :attr str source: The `https:` URL of the image. :attr str title: (optional) An optional title to show before the response. :attr str description: (optional) An optional description to show with the response. :attr List[ResponseGenericChannel] channels: (optional) An array of objects specifying channels for which the response is intended. :attr str alt_text: (optional) Descriptive text that can be used for screen readers or other situations where the image cannot be seen. """ def __init__(self, response_type: str, source: str, *, title: str = None, description: str = None, channels: List['ResponseGenericChannel'] = None, alt_text: str = None) -> None: """ Initialize a DialogNodeOutputGenericDialogNodeOutputResponseTypeImage object. :param str response_type: The type of response returned by the dialog node. The specified response type must be supported by the client application or channel. :param str source: The `https:` URL of the image. :param str title: (optional) An optional title to show before the response. :param str description: (optional) An optional description to show with the response. :param List[ResponseGenericChannel] channels: (optional) An array of objects specifying channels for which the response is intended. :param str alt_text: (optional) Descriptive text that can be used for screen readers or other situations where the image cannot be seen. """ # pylint: disable=super-init-not-called self.response_type = response_type self.source = source self.title = title self.description = description self.channels = channels self.alt_text = alt_text @classmethod def from_dict( cls, _dict: Dict ) -> 'DialogNodeOutputGenericDialogNodeOutputResponseTypeImage': """Initialize a DialogNodeOutputGenericDialogNodeOutputResponseTypeImage object from a json dictionary.""" args = {} if 'response_type' in _dict: args['response_type'] = _dict.get('response_type') else: raise ValueError( 'Required property \'response_type\' not present in DialogNodeOutputGenericDialogNodeOutputResponseTypeImage JSON' ) if 'source' in _dict: args['source'] = _dict.get('source') else: raise ValueError( 'Required property \'source\' not present in DialogNodeOutputGenericDialogNodeOutputResponseTypeImage JSON' ) if 'title' in _dict: args['title'] = _dict.get('title') if 'description' in _dict: args['description'] = _dict.get('description') if 'channels' in _dict: args['channels'] = [ ResponseGenericChannel.from_dict(x) for x in _dict.get('channels') ] if 'alt_text' in _dict: args['alt_text'] = _dict.get('alt_text') return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a DialogNodeOutputGenericDialogNodeOutputResponseTypeImage object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'response_type') and self.response_type is not None: _dict['response_type'] = self.response_type if hasattr(self, 'source') and self.source is not None: _dict['source'] = self.source if hasattr(self, 'title') and self.title is not None: _dict['title'] = self.title if hasattr(self, 'description') and self.description is not None: _dict['description'] = self.description if hasattr(self, 'channels') and self.channels is not None: _dict['channels'] = [x.to_dict() for x in self.channels] if hasattr(self, 'alt_text') and self.alt_text is not None: _dict['alt_text'] = self.alt_text return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this DialogNodeOutputGenericDialogNodeOutputResponseTypeImage object.""" return json.dumps(self.to_dict(), indent=2) def __eq__( self, other: 'DialogNodeOutputGenericDialogNodeOutputResponseTypeImage' ) -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__( self, other: 'DialogNodeOutputGenericDialogNodeOutputResponseTypeImage' ) -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class DialogNodeOutputGenericDialogNodeOutputResponseTypeOption( DialogNodeOutputGeneric): """ DialogNodeOutputGenericDialogNodeOutputResponseTypeOption. :attr str response_type: The type of response returned by the dialog node. The specified response type must be supported by the client application or channel. :attr str title: An optional title to show before the response. :attr str description: (optional) An optional description to show with the response. :attr str preference: (optional) The preferred type of control to display, if supported by the channel. :attr List[DialogNodeOutputOptionsElement] options: An array of objects describing the options from which the user can choose. You can include up to 20 options. :attr List[ResponseGenericChannel] channels: (optional) An array of objects specifying channels for which the response is intended. """ def __init__(self, response_type: str, title: str, options: List['DialogNodeOutputOptionsElement'], *, description: str = None, preference: str = None, channels: List['ResponseGenericChannel'] = None) -> None: """ Initialize a DialogNodeOutputGenericDialogNodeOutputResponseTypeOption object. :param str response_type: The type of response returned by the dialog node. The specified response type must be supported by the client application or channel. :param str title: An optional title to show before the response. :param List[DialogNodeOutputOptionsElement] options: An array of objects describing the options from which the user can choose. You can include up to 20 options. :param str description: (optional) An optional description to show with the response. :param str preference: (optional) The preferred type of control to display, if supported by the channel. :param List[ResponseGenericChannel] channels: (optional) An array of objects specifying channels for which the response is intended. """ # pylint: disable=super-init-not-called self.response_type = response_type self.title = title self.description = description self.preference = preference self.options = options self.channels = channels @classmethod def from_dict( cls, _dict: Dict ) -> 'DialogNodeOutputGenericDialogNodeOutputResponseTypeOption': """Initialize a DialogNodeOutputGenericDialogNodeOutputResponseTypeOption object from a json dictionary.""" args = {} if 'response_type' in _dict: args['response_type'] = _dict.get('response_type') else: raise ValueError( 'Required property \'response_type\' not present in DialogNodeOutputGenericDialogNodeOutputResponseTypeOption JSON' ) if 'title' in _dict: args['title'] = _dict.get('title') else: raise ValueError( 'Required property \'title\' not present in DialogNodeOutputGenericDialogNodeOutputResponseTypeOption JSON' ) if 'description' in _dict: args['description'] = _dict.get('description') if 'preference' in _dict: args['preference'] = _dict.get('preference') if 'options' in _dict: args['options'] = [ DialogNodeOutputOptionsElement.from_dict(x) for x in _dict.get('options') ] else: raise ValueError( 'Required property \'options\' not present in DialogNodeOutputGenericDialogNodeOutputResponseTypeOption JSON' ) if 'channels' in _dict: args['channels'] = [ ResponseGenericChannel.from_dict(x) for x in _dict.get('channels') ] return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a DialogNodeOutputGenericDialogNodeOutputResponseTypeOption object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'response_type') and self.response_type is not None: _dict['response_type'] = self.response_type if hasattr(self, 'title') and self.title is not None: _dict['title'] = self.title if hasattr(self, 'description') and self.description is not None: _dict['description'] = self.description if hasattr(self, 'preference') and self.preference is not None: _dict['preference'] = self.preference if hasattr(self, 'options') and self.options is not None: _dict['options'] = [x.to_dict() for x in self.options] if hasattr(self, 'channels') and self.channels is not None: _dict['channels'] = [x.to_dict() for x in self.channels] return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this DialogNodeOutputGenericDialogNodeOutputResponseTypeOption object.""" return json.dumps(self.to_dict(), indent=2) def __eq__( self, other: 'DialogNodeOutputGenericDialogNodeOutputResponseTypeOption' ) -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__( self, other: 'DialogNodeOutputGenericDialogNodeOutputResponseTypeOption' ) -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class PreferenceEnum(str, Enum): """ The preferred type of control to display, if supported by the channel. """ DROPDOWN = 'dropdown' BUTTON = 'button' class DialogNodeOutputGenericDialogNodeOutputResponseTypePause( DialogNodeOutputGeneric): """ DialogNodeOutputGenericDialogNodeOutputResponseTypePause. :attr str response_type: The type of response returned by the dialog node. The specified response type must be supported by the client application or channel. :attr int time: How long to pause, in milliseconds. The valid values are from 0 to 10000. :attr bool typing: (optional) Whether to send a "user is typing" event during the pause. Ignored if the channel does not support this event. :attr List[ResponseGenericChannel] channels: (optional) An array of objects specifying channels for which the response is intended. """ def __init__(self, response_type: str, time: int, *, typing: bool = None, channels: List['ResponseGenericChannel'] = None) -> None: """ Initialize a DialogNodeOutputGenericDialogNodeOutputResponseTypePause object. :param str response_type: The type of response returned by the dialog node. The specified response type must be supported by the client application or channel. :param int time: How long to pause, in milliseconds. The valid values are from 0 to 10000. :param bool typing: (optional) Whether to send a "user is typing" event during the pause. Ignored if the channel does not support this event. :param List[ResponseGenericChannel] channels: (optional) An array of objects specifying channels for which the response is intended. """ # pylint: disable=super-init-not-called self.response_type = response_type self.time = time self.typing = typing self.channels = channels @classmethod def from_dict( cls, _dict: Dict ) -> 'DialogNodeOutputGenericDialogNodeOutputResponseTypePause': """Initialize a DialogNodeOutputGenericDialogNodeOutputResponseTypePause object from a json dictionary.""" args = {} if 'response_type' in _dict: args['response_type'] = _dict.get('response_type') else: raise ValueError( 'Required property \'response_type\' not present in DialogNodeOutputGenericDialogNodeOutputResponseTypePause JSON' ) if 'time' in _dict: args['time'] = _dict.get('time') else: raise ValueError( 'Required property \'time\' not present in DialogNodeOutputGenericDialogNodeOutputResponseTypePause JSON' ) if 'typing' in _dict: args['typing'] = _dict.get('typing') if 'channels' in _dict: args['channels'] = [ ResponseGenericChannel.from_dict(x) for x in _dict.get('channels') ] return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a DialogNodeOutputGenericDialogNodeOutputResponseTypePause object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'response_type') and self.response_type is not None: _dict['response_type'] = self.response_type if hasattr(self, 'time') and self.time is not None: _dict['time'] = self.time if hasattr(self, 'typing') and self.typing is not None: _dict['typing'] = self.typing if hasattr(self, 'channels') and self.channels is not None: _dict['channels'] = [x.to_dict() for x in self.channels] return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this DialogNodeOutputGenericDialogNodeOutputResponseTypePause object.""" return json.dumps(self.to_dict(), indent=2) def __eq__( self, other: 'DialogNodeOutputGenericDialogNodeOutputResponseTypePause' ) -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__( self, other: 'DialogNodeOutputGenericDialogNodeOutputResponseTypePause' ) -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class DialogNodeOutputGenericDialogNodeOutputResponseTypeSearchSkill( DialogNodeOutputGeneric): """ DialogNodeOutputGenericDialogNodeOutputResponseTypeSearchSkill. :attr str response_type: The type of response returned by the dialog node. The specified response type must be supported by the client application or channel. **Note:** The **search_skill** response type is used only by the v2 runtime API. :attr str query: The text of the search query. This can be either a natural-language query or a query that uses the Discovery query language syntax, depending on the value of the **query_type** property. For more information, see the [Discovery service documentation](https://cloud.ibm.com/docs/discovery?topic=discovery-query-operators#query-operators). :attr str query_type: The type of the search query. :attr str filter: (optional) An optional filter that narrows the set of documents to be searched. For more information, see the [Discovery service documentation]([Discovery service documentation](https://cloud.ibm.com/docs/discovery?topic=discovery-query-parameters#filter). :attr str discovery_version: (optional) The version of the Discovery service API to use for the query. :attr List[ResponseGenericChannel] channels: (optional) An array of objects specifying channels for which the response is intended. """ def __init__(self, response_type: str, query: str, query_type: str, *, filter: str = None, discovery_version: str = None, channels: List['ResponseGenericChannel'] = None) -> None: """ Initialize a DialogNodeOutputGenericDialogNodeOutputResponseTypeSearchSkill object. :param str response_type: The type of response returned by the dialog node. The specified response type must be supported by the client application or channel. **Note:** The **search_skill** response type is used only by the v2 runtime API. :param str query: The text of the search query. This can be either a natural-language query or a query that uses the Discovery query language syntax, depending on the value of the **query_type** property. For more information, see the [Discovery service documentation](https://cloud.ibm.com/docs/discovery?topic=discovery-query-operators#query-operators). :param str query_type: The type of the search query. :param str filter: (optional) An optional filter that narrows the set of documents to be searched. For more information, see the [Discovery service documentation]([Discovery service documentation](https://cloud.ibm.com/docs/discovery?topic=discovery-query-parameters#filter). :param str discovery_version: (optional) The version of the Discovery service API to use for the query. :param List[ResponseGenericChannel] channels: (optional) An array of objects specifying channels for which the response is intended. """ # pylint: disable=super-init-not-called self.response_type = response_type self.query = query self.query_type = query_type self.filter = filter self.discovery_version = discovery_version self.channels = channels @classmethod def from_dict( cls, _dict: Dict ) -> 'DialogNodeOutputGenericDialogNodeOutputResponseTypeSearchSkill': """Initialize a DialogNodeOutputGenericDialogNodeOutputResponseTypeSearchSkill object from a json dictionary.""" args = {} if 'response_type' in _dict: args['response_type'] = _dict.get('response_type') else: raise ValueError( 'Required property \'response_type\' not present in DialogNodeOutputGenericDialogNodeOutputResponseTypeSearchSkill JSON' ) if 'query' in _dict: args['query'] = _dict.get('query') else: raise ValueError( 'Required property \'query\' not present in DialogNodeOutputGenericDialogNodeOutputResponseTypeSearchSkill JSON' ) if 'query_type' in _dict: args['query_type'] = _dict.get('query_type') else: raise ValueError( 'Required property \'query_type\' not present in DialogNodeOutputGenericDialogNodeOutputResponseTypeSearchSkill JSON' ) if 'filter' in _dict: args['filter'] = _dict.get('filter') if 'discovery_version' in _dict: args['discovery_version'] = _dict.get('discovery_version') if 'channels' in _dict: args['channels'] = [ ResponseGenericChannel.from_dict(x) for x in _dict.get('channels') ] return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a DialogNodeOutputGenericDialogNodeOutputResponseTypeSearchSkill object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'response_type') and self.response_type is not None: _dict['response_type'] = self.response_type if hasattr(self, 'query') and self.query is not None: _dict['query'] = self.query if hasattr(self, 'query_type') and self.query_type is not None: _dict['query_type'] = self.query_type if hasattr(self, 'filter') and self.filter is not None: _dict['filter'] = self.filter if hasattr(self, 'discovery_version') and self.discovery_version is not None: _dict['discovery_version'] = self.discovery_version if hasattr(self, 'channels') and self.channels is not None: _dict['channels'] = [x.to_dict() for x in self.channels] return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this DialogNodeOutputGenericDialogNodeOutputResponseTypeSearchSkill object.""" return json.dumps(self.to_dict(), indent=2) def __eq__( self, other: 'DialogNodeOutputGenericDialogNodeOutputResponseTypeSearchSkill' ) -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__( self, other: 'DialogNodeOutputGenericDialogNodeOutputResponseTypeSearchSkill' ) -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class QueryTypeEnum(str, Enum): """ The type of the search query. """ NATURAL_LANGUAGE = 'natural_language' DISCOVERY_QUERY_LANGUAGE = 'discovery_query_language' class DialogNodeOutputGenericDialogNodeOutputResponseTypeText( DialogNodeOutputGeneric): """ DialogNodeOutputGenericDialogNodeOutputResponseTypeText. :attr str response_type: The type of response returned by the dialog node. The specified response type must be supported by the client application or channel. :attr List[DialogNodeOutputTextValuesElement] values: A list of one or more objects defining text responses. :attr str selection_policy: (optional) How a response is selected from the list, if more than one response is specified. :attr str delimiter: (optional) The delimiter to use as a separator between responses when `selection_policy`=`multiline`. :attr List[ResponseGenericChannel] channels: (optional) An array of objects specifying channels for which the response is intended. """ def __init__(self, response_type: str, values: List['DialogNodeOutputTextValuesElement'], *, selection_policy: str = None, delimiter: str = None, channels: List['ResponseGenericChannel'] = None) -> None: """ Initialize a DialogNodeOutputGenericDialogNodeOutputResponseTypeText object. :param str response_type: The type of response returned by the dialog node. The specified response type must be supported by the client application or channel. :param List[DialogNodeOutputTextValuesElement] values: A list of one or more objects defining text responses. :param str selection_policy: (optional) How a response is selected from the list, if more than one response is specified. :param str delimiter: (optional) The delimiter to use as a separator between responses when `selection_policy`=`multiline`. :param List[ResponseGenericChannel] channels: (optional) An array of objects specifying channels for which the response is intended. """ # pylint: disable=super-init-not-called self.response_type = response_type self.values = values self.selection_policy = selection_policy self.delimiter = delimiter self.channels = channels @classmethod def from_dict( cls, _dict: Dict ) -> 'DialogNodeOutputGenericDialogNodeOutputResponseTypeText': """Initialize a DialogNodeOutputGenericDialogNodeOutputResponseTypeText object from a json dictionary.""" args = {} if 'response_type' in _dict: args['response_type'] = _dict.get('response_type') else: raise ValueError( 'Required property \'response_type\' not present in DialogNodeOutputGenericDialogNodeOutputResponseTypeText JSON' ) if 'values' in _dict: args['values'] = [ DialogNodeOutputTextValuesElement.from_dict(x) for x in _dict.get('values') ] else: raise ValueError( 'Required property \'values\' not present in DialogNodeOutputGenericDialogNodeOutputResponseTypeText JSON' ) if 'selection_policy' in _dict: args['selection_policy'] = _dict.get('selection_policy') if 'delimiter' in _dict: args['delimiter'] = _dict.get('delimiter') if 'channels' in _dict: args['channels'] = [ ResponseGenericChannel.from_dict(x) for x in _dict.get('channels') ] return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a DialogNodeOutputGenericDialogNodeOutputResponseTypeText object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'response_type') and self.response_type is not None: _dict['response_type'] = self.response_type if hasattr(self, 'values') and self.values is not None: _dict['values'] = [x.to_dict() for x in self.values] if hasattr(self, 'selection_policy') and self.selection_policy is not None: _dict['selection_policy'] = self.selection_policy if hasattr(self, 'delimiter') and self.delimiter is not None: _dict['delimiter'] = self.delimiter if hasattr(self, 'channels') and self.channels is not None: _dict['channels'] = [x.to_dict() for x in self.channels] return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this DialogNodeOutputGenericDialogNodeOutputResponseTypeText object.""" return json.dumps(self.to_dict(), indent=2) def __eq__( self, other: 'DialogNodeOutputGenericDialogNodeOutputResponseTypeText' ) -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__( self, other: 'DialogNodeOutputGenericDialogNodeOutputResponseTypeText' ) -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class SelectionPolicyEnum(str, Enum): """ How a response is selected from the list, if more than one response is specified. """ SEQUENTIAL = 'sequential' RANDOM = 'random' MULTILINE = 'multiline' class DialogNodeOutputGenericDialogNodeOutputResponseTypeUserDefined( DialogNodeOutputGeneric): """ DialogNodeOutputGenericDialogNodeOutputResponseTypeUserDefined. :attr str response_type: The type of response returned by the dialog node. The specified response type must be supported by the client application or channel. :attr dict user_defined: An object containing any properties for the user-defined response type. The total size of this object cannot exceed 5000 bytes. :attr List[ResponseGenericChannel] channels: (optional) An array of objects specifying channels for which the response is intended. """ def __init__(self, response_type: str, user_defined: dict, *, channels: List['ResponseGenericChannel'] = None) -> None: """ Initialize a DialogNodeOutputGenericDialogNodeOutputResponseTypeUserDefined object. :param str response_type: The type of response returned by the dialog node. The specified response type must be supported by the client application or channel. :param dict user_defined: An object containing any properties for the user-defined response type. The total size of this object cannot exceed 5000 bytes. :param List[ResponseGenericChannel] channels: (optional) An array of objects specifying channels for which the response is intended. """ # pylint: disable=super-init-not-called self.response_type = response_type self.user_defined = user_defined self.channels = channels @classmethod def from_dict( cls, _dict: Dict ) -> 'DialogNodeOutputGenericDialogNodeOutputResponseTypeUserDefined': """Initialize a DialogNodeOutputGenericDialogNodeOutputResponseTypeUserDefined object from a json dictionary.""" args = {} if 'response_type' in _dict: args['response_type'] = _dict.get('response_type') else: raise ValueError( 'Required property \'response_type\' not present in DialogNodeOutputGenericDialogNodeOutputResponseTypeUserDefined JSON' ) if 'user_defined' in _dict: args['user_defined'] = _dict.get('user_defined') else: raise ValueError( 'Required property \'user_defined\' not present in DialogNodeOutputGenericDialogNodeOutputResponseTypeUserDefined JSON' ) if 'channels' in _dict: args['channels'] = [ ResponseGenericChannel.from_dict(x) for x in _dict.get('channels') ] return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a DialogNodeOutputGenericDialogNodeOutputResponseTypeUserDefined object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'response_type') and self.response_type is not None: _dict['response_type'] = self.response_type if hasattr(self, 'user_defined') and self.user_defined is not None: _dict['user_defined'] = self.user_defined if hasattr(self, 'channels') and self.channels is not None: _dict['channels'] = [x.to_dict() for x in self.channels] return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this DialogNodeOutputGenericDialogNodeOutputResponseTypeUserDefined object.""" return json.dumps(self.to_dict(), indent=2) def __eq__( self, other: 'DialogNodeOutputGenericDialogNodeOutputResponseTypeUserDefined' ) -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__( self, other: 'DialogNodeOutputGenericDialogNodeOutputResponseTypeUserDefined' ) -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class DialogNodeOutputGenericDialogNodeOutputResponseTypeVideo( DialogNodeOutputGeneric): """ DialogNodeOutputGenericDialogNodeOutputResponseTypeVideo. :attr str response_type: The type of response returned by the dialog node. The specified response type must be supported by the client application or channel. :attr str source: The `https:` URL of the video. :attr str title: (optional) An optional title to show before the response. :attr str description: (optional) An optional description to show with the response. :attr List[ResponseGenericChannel] channels: (optional) An array of objects specifying channels for which the response is intended. If **channels** is present, the response is intended for a built-in integration and should not be handled by an API client. :attr object channel_options: (optional) For internal use only. :attr str alt_text: (optional) Descriptive text that can be used for screen readers or other situations where the video cannot be seen. """ def __init__(self, response_type: str, source: str, *, title: str = None, description: str = None, channels: List['ResponseGenericChannel'] = None, channel_options: object = None, alt_text: str = None) -> None: """ Initialize a DialogNodeOutputGenericDialogNodeOutputResponseTypeVideo object. :param str response_type: The type of response returned by the dialog node. The specified response type must be supported by the client application or channel. :param str source: The `https:` URL of the video. :param str title: (optional) An optional title to show before the response. :param str description: (optional) An optional description to show with the response. :param List[ResponseGenericChannel] channels: (optional) An array of objects specifying channels for which the response is intended. If **channels** is present, the response is intended for a built-in integration and should not be handled by an API client. :param object channel_options: (optional) For internal use only. :param str alt_text: (optional) Descriptive text that can be used for screen readers or other situations where the video cannot be seen. """ # pylint: disable=super-init-not-called self.response_type = response_type self.source = source self.title = title self.description = description self.channels = channels self.channel_options = channel_options self.alt_text = alt_text @classmethod def from_dict( cls, _dict: Dict ) -> 'DialogNodeOutputGenericDialogNodeOutputResponseTypeVideo': """Initialize a DialogNodeOutputGenericDialogNodeOutputResponseTypeVideo object from a json dictionary.""" args = {} if 'response_type' in _dict: args['response_type'] = _dict.get('response_type') else: raise ValueError( 'Required property \'response_type\' not present in DialogNodeOutputGenericDialogNodeOutputResponseTypeVideo JSON' ) if 'source' in _dict: args['source'] = _dict.get('source') else: raise ValueError( 'Required property \'source\' not present in DialogNodeOutputGenericDialogNodeOutputResponseTypeVideo JSON' ) if 'title' in _dict: args['title'] = _dict.get('title') if 'description' in _dict: args['description'] = _dict.get('description') if 'channels' in _dict: args['channels'] = [ ResponseGenericChannel.from_dict(x) for x in _dict.get('channels') ] if 'channel_options' in _dict: args['channel_options'] = _dict.get('channel_options') if 'alt_text' in _dict: args['alt_text'] = _dict.get('alt_text') return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a DialogNodeOutputGenericDialogNodeOutputResponseTypeVideo object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'response_type') and self.response_type is not None: _dict['response_type'] = self.response_type if hasattr(self, 'source') and self.source is not None: _dict['source'] = self.source if hasattr(self, 'title') and self.title is not None: _dict['title'] = self.title if hasattr(self, 'description') and self.description is not None: _dict['description'] = self.description if hasattr(self, 'channels') and self.channels is not None: _dict['channels'] = [x.to_dict() for x in self.channels] if hasattr(self, 'channel_options') and self.channel_options is not None: _dict['channel_options'] = self.channel_options if hasattr(self, 'alt_text') and self.alt_text is not None: _dict['alt_text'] = self.alt_text return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this DialogNodeOutputGenericDialogNodeOutputResponseTypeVideo object.""" return json.dumps(self.to_dict(), indent=2) def __eq__( self, other: 'DialogNodeOutputGenericDialogNodeOutputResponseTypeVideo' ) -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__( self, other: 'DialogNodeOutputGenericDialogNodeOutputResponseTypeVideo' ) -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class RuntimeResponseGenericRuntimeResponseTypeAudio(RuntimeResponseGeneric): """ RuntimeResponseGenericRuntimeResponseTypeAudio. :attr str response_type: The type of response returned by the dialog node. The specified response type must be supported by the client application or channel. :attr str source: The `https:` URL of the audio clip. :attr str title: (optional) The title or introductory text to show before the response. :attr str description: (optional) The description to show with the response. :attr List[ResponseGenericChannel] channels: (optional) An array of objects specifying channels for which the response is intended. If **channels** is present, the response is intended for a built-in integration and should not be handled by an API client. :attr object channel_options: (optional) For internal use only. :attr str alt_text: (optional) Descriptive text that can be used for screen readers or other situations where the audio player cannot be seen. """ def __init__(self, response_type: str, source: str, *, title: str = None, description: str = None, channels: List['ResponseGenericChannel'] = None, channel_options: object = None, alt_text: str = None) -> None: """ Initialize a RuntimeResponseGenericRuntimeResponseTypeAudio object. :param str response_type: The type of response returned by the dialog node. The specified response type must be supported by the client application or channel. :param str source: The `https:` URL of the audio clip. :param str title: (optional) The title or introductory text to show before the response. :param str description: (optional) The description to show with the response. :param List[ResponseGenericChannel] channels: (optional) An array of objects specifying channels for which the response is intended. If **channels** is present, the response is intended for a built-in integration and should not be handled by an API client. :param object channel_options: (optional) For internal use only. :param str alt_text: (optional) Descriptive text that can be used for screen readers or other situations where the audio player cannot be seen. """ # pylint: disable=super-init-not-called self.response_type = response_type self.source = source self.title = title self.description = description self.channels = channels self.channel_options = channel_options self.alt_text = alt_text @classmethod def from_dict( cls, _dict: Dict) -> 'RuntimeResponseGenericRuntimeResponseTypeAudio': """Initialize a RuntimeResponseGenericRuntimeResponseTypeAudio object from a json dictionary.""" args = {} if 'response_type' in _dict: args['response_type'] = _dict.get('response_type') else: raise ValueError( 'Required property \'response_type\' not present in RuntimeResponseGenericRuntimeResponseTypeAudio JSON' ) if 'source' in _dict: args['source'] = _dict.get('source') else: raise ValueError( 'Required property \'source\' not present in RuntimeResponseGenericRuntimeResponseTypeAudio JSON' ) if 'title' in _dict: args['title'] = _dict.get('title') if 'description' in _dict: args['description'] = _dict.get('description') if 'channels' in _dict: args['channels'] = [ ResponseGenericChannel.from_dict(x) for x in _dict.get('channels') ] if 'channel_options' in _dict: args['channel_options'] = _dict.get('channel_options') if 'alt_text' in _dict: args['alt_text'] = _dict.get('alt_text') return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a RuntimeResponseGenericRuntimeResponseTypeAudio object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'response_type') and self.response_type is not None: _dict['response_type'] = self.response_type if hasattr(self, 'source') and self.source is not None: _dict['source'] = self.source if hasattr(self, 'title') and self.title is not None: _dict['title'] = self.title if hasattr(self, 'description') and self.description is not None: _dict['description'] = self.description if hasattr(self, 'channels') and self.channels is not None: _dict['channels'] = [x.to_dict() for x in self.channels] if hasattr(self, 'channel_options') and self.channel_options is not None: _dict['channel_options'] = self.channel_options if hasattr(self, 'alt_text') and self.alt_text is not None: _dict['alt_text'] = self.alt_text return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this RuntimeResponseGenericRuntimeResponseTypeAudio object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'RuntimeResponseGenericRuntimeResponseTypeAudio') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'RuntimeResponseGenericRuntimeResponseTypeAudio') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class RuntimeResponseGenericRuntimeResponseTypeChannelTransfer( RuntimeResponseGeneric): """ RuntimeResponseGenericRuntimeResponseTypeChannelTransfer. :attr str response_type: The type of response returned by the dialog node. The specified response type must be supported by the client application or channel. :attr str message_to_user: The message to display to the user when initiating a channel transfer. :attr ChannelTransferInfo transfer_info: Information used by an integration to transfer the conversation to a different channel. :attr List[ResponseGenericChannel] channels: (optional) An array of objects specifying channels for which the response is intended. If **channels** is present, the response is intended only for a built-in integration and should not be handled by an API client. """ def __init__(self, response_type: str, message_to_user: str, transfer_info: 'ChannelTransferInfo', *, channels: List['ResponseGenericChannel'] = None) -> None: """ Initialize a RuntimeResponseGenericRuntimeResponseTypeChannelTransfer object. :param str response_type: The type of response returned by the dialog node. The specified response type must be supported by the client application or channel. :param str message_to_user: The message to display to the user when initiating a channel transfer. :param ChannelTransferInfo transfer_info: Information used by an integration to transfer the conversation to a different channel. :param List[ResponseGenericChannel] channels: (optional) An array of objects specifying channels for which the response is intended. If **channels** is present, the response is intended only for a built-in integration and should not be handled by an API client. """ # pylint: disable=super-init-not-called self.response_type = response_type self.message_to_user = message_to_user self.transfer_info = transfer_info self.channels = channels @classmethod def from_dict( cls, _dict: Dict ) -> 'RuntimeResponseGenericRuntimeResponseTypeChannelTransfer': """Initialize a RuntimeResponseGenericRuntimeResponseTypeChannelTransfer object from a json dictionary.""" args = {} if 'response_type' in _dict: args['response_type'] = _dict.get('response_type') else: raise ValueError( 'Required property \'response_type\' not present in RuntimeResponseGenericRuntimeResponseTypeChannelTransfer JSON' ) if 'message_to_user' in _dict: args['message_to_user'] = _dict.get('message_to_user') else: raise ValueError( 'Required property \'message_to_user\' not present in RuntimeResponseGenericRuntimeResponseTypeChannelTransfer JSON' ) if 'transfer_info' in _dict: args['transfer_info'] = ChannelTransferInfo.from_dict( _dict.get('transfer_info')) else: raise ValueError( 'Required property \'transfer_info\' not present in RuntimeResponseGenericRuntimeResponseTypeChannelTransfer JSON' ) if 'channels' in _dict: args['channels'] = [ ResponseGenericChannel.from_dict(x) for x in _dict.get('channels') ] return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a RuntimeResponseGenericRuntimeResponseTypeChannelTransfer object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'response_type') and self.response_type is not None: _dict['response_type'] = self.response_type if hasattr(self, 'message_to_user') and self.message_to_user is not None: _dict['message_to_user'] = self.message_to_user if hasattr(self, 'transfer_info') and self.transfer_info is not None: _dict['transfer_info'] = self.transfer_info.to_dict() if hasattr(self, 'channels') and self.channels is not None: _dict['channels'] = [x.to_dict() for x in self.channels] return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this RuntimeResponseGenericRuntimeResponseTypeChannelTransfer object.""" return json.dumps(self.to_dict(), indent=2) def __eq__( self, other: 'RuntimeResponseGenericRuntimeResponseTypeChannelTransfer' ) -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__( self, other: 'RuntimeResponseGenericRuntimeResponseTypeChannelTransfer' ) -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class RuntimeResponseGenericRuntimeResponseTypeConnectToAgent( RuntimeResponseGeneric): """ RuntimeResponseGenericRuntimeResponseTypeConnectToAgent. :attr str response_type: The type of response returned by the dialog node. The specified response type must be supported by the client application or channel. :attr str message_to_human_agent: (optional) A message to be sent to the human agent who will be taking over the conversation. :attr AgentAvailabilityMessage agent_available: (optional) An optional message to be displayed to the user to indicate that the conversation will be transferred to the next available agent. :attr AgentAvailabilityMessage agent_unavailable: (optional) An optional message to be displayed to the user to indicate that no online agent is available to take over the conversation. :attr DialogNodeOutputConnectToAgentTransferInfo transfer_info: (optional) Routing or other contextual information to be used by target service desk systems. :attr str topic: (optional) A label identifying the topic of the conversation, derived from the **title** property of the relevant node or the **topic** property of the dialog node response. :attr str dialog_node: (optional) The unique ID of the dialog node that the **topic** property is taken from. The **topic** property is populated using the value of the dialog node's **title** property. :attr List[ResponseGenericChannel] channels: (optional) An array of objects specifying channels for which the response is intended. If **channels** is present, the response is intended for a built-in integration and should not be handled by an API client. """ def __init__( self, response_type: str, *, message_to_human_agent: str = None, agent_available: 'AgentAvailabilityMessage' = None, agent_unavailable: 'AgentAvailabilityMessage' = None, transfer_info: 'DialogNodeOutputConnectToAgentTransferInfo' = None, topic: str = None, dialog_node: str = None, channels: List['ResponseGenericChannel'] = None) -> None: """ Initialize a RuntimeResponseGenericRuntimeResponseTypeConnectToAgent object. :param str response_type: The type of response returned by the dialog node. The specified response type must be supported by the client application or channel. :param str message_to_human_agent: (optional) A message to be sent to the human agent who will be taking over the conversation. :param AgentAvailabilityMessage agent_available: (optional) An optional message to be displayed to the user to indicate that the conversation will be transferred to the next available agent. :param AgentAvailabilityMessage agent_unavailable: (optional) An optional message to be displayed to the user to indicate that no online agent is available to take over the conversation. :param DialogNodeOutputConnectToAgentTransferInfo transfer_info: (optional) Routing or other contextual information to be used by target service desk systems. :param str topic: (optional) A label identifying the topic of the conversation, derived from the **title** property of the relevant node or the **topic** property of the dialog node response. :param str dialog_node: (optional) The unique ID of the dialog node that the **topic** property is taken from. The **topic** property is populated using the value of the dialog node's **title** property. :param List[ResponseGenericChannel] channels: (optional) An array of objects specifying channels for which the response is intended. If **channels** is present, the response is intended for a built-in integration and should not be handled by an API client. """ # pylint: disable=super-init-not-called self.response_type = response_type self.message_to_human_agent = message_to_human_agent self.agent_available = agent_available self.agent_unavailable = agent_unavailable self.transfer_info = transfer_info self.topic = topic self.dialog_node = dialog_node self.channels = channels @classmethod def from_dict( cls, _dict: Dict ) -> 'RuntimeResponseGenericRuntimeResponseTypeConnectToAgent': """Initialize a RuntimeResponseGenericRuntimeResponseTypeConnectToAgent object from a json dictionary.""" args = {} if 'response_type' in _dict: args['response_type'] = _dict.get('response_type') else: raise ValueError( 'Required property \'response_type\' not present in RuntimeResponseGenericRuntimeResponseTypeConnectToAgent JSON' ) if 'message_to_human_agent' in _dict: args['message_to_human_agent'] = _dict.get('message_to_human_agent') if 'agent_available' in _dict: args['agent_available'] = AgentAvailabilityMessage.from_dict( _dict.get('agent_available')) if 'agent_unavailable' in _dict: args['agent_unavailable'] = AgentAvailabilityMessage.from_dict( _dict.get('agent_unavailable')) if 'transfer_info' in _dict: args[ 'transfer_info'] = DialogNodeOutputConnectToAgentTransferInfo.from_dict( _dict.get('transfer_info')) if 'topic' in _dict: args['topic'] = _dict.get('topic') if 'dialog_node' in _dict: args['dialog_node'] = _dict.get('dialog_node') if 'channels' in _dict: args['channels'] = [ ResponseGenericChannel.from_dict(x) for x in _dict.get('channels') ] return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a RuntimeResponseGenericRuntimeResponseTypeConnectToAgent object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'response_type') and self.response_type is not None: _dict['response_type'] = self.response_type if hasattr(self, 'message_to_human_agent' ) and self.message_to_human_agent is not None: _dict['message_to_human_agent'] = self.message_to_human_agent if hasattr(self, 'agent_available') and self.agent_available is not None: _dict['agent_available'] = self.agent_available.to_dict() if hasattr(self, 'agent_unavailable') and self.agent_unavailable is not None: _dict['agent_unavailable'] = self.agent_unavailable.to_dict() if hasattr(self, 'transfer_info') and self.transfer_info is not None: _dict['transfer_info'] = self.transfer_info.to_dict() if hasattr(self, 'topic') and self.topic is not None: _dict['topic'] = self.topic if hasattr(self, 'dialog_node') and self.dialog_node is not None: _dict['dialog_node'] = self.dialog_node if hasattr(self, 'channels') and self.channels is not None: _dict['channels'] = [x.to_dict() for x in self.channels] return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this RuntimeResponseGenericRuntimeResponseTypeConnectToAgent object.""" return json.dumps(self.to_dict(), indent=2) def __eq__( self, other: 'RuntimeResponseGenericRuntimeResponseTypeConnectToAgent' ) -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__( self, other: 'RuntimeResponseGenericRuntimeResponseTypeConnectToAgent' ) -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class RuntimeResponseGenericRuntimeResponseTypeIframe(RuntimeResponseGeneric): """ RuntimeResponseGenericRuntimeResponseTypeIframe. :attr str response_type: The type of response returned by the dialog node. The specified response type must be supported by the client application or channel. :attr str source: The `https:` URL of the embeddable content. :attr str title: (optional) The title or introductory text to show before the response. :attr str description: (optional) The description to show with the response. :attr str image_url: (optional) The URL of an image that shows a preview of the embedded content. :attr List[ResponseGenericChannel] channels: (optional) An array of objects specifying channels for which the response is intended. If **channels** is present, the response is intended for a built-in integration and should not be handled by an API client. """ def __init__(self, response_type: str, source: str, *, title: str = None, description: str = None, image_url: str = None, channels: List['ResponseGenericChannel'] = None) -> None: """ Initialize a RuntimeResponseGenericRuntimeResponseTypeIframe object. :param str response_type: The type of response returned by the dialog node. The specified response type must be supported by the client application or channel. :param str source: The `https:` URL of the embeddable content. :param str title: (optional) The title or introductory text to show before the response. :param str description: (optional) The description to show with the response. :param str image_url: (optional) The URL of an image that shows a preview of the embedded content. :param List[ResponseGenericChannel] channels: (optional) An array of objects specifying channels for which the response is intended. If **channels** is present, the response is intended for a built-in integration and should not be handled by an API client. """ # pylint: disable=super-init-not-called self.response_type = response_type self.source = source self.title = title self.description = description self.image_url = image_url self.channels = channels @classmethod def from_dict( cls, _dict: Dict) -> 'RuntimeResponseGenericRuntimeResponseTypeIframe': """Initialize a RuntimeResponseGenericRuntimeResponseTypeIframe object from a json dictionary.""" args = {} if 'response_type' in _dict: args['response_type'] = _dict.get('response_type') else: raise ValueError( 'Required property \'response_type\' not present in RuntimeResponseGenericRuntimeResponseTypeIframe JSON' ) if 'source' in _dict: args['source'] = _dict.get('source') else: raise ValueError( 'Required property \'source\' not present in RuntimeResponseGenericRuntimeResponseTypeIframe JSON' ) if 'title' in _dict: args['title'] = _dict.get('title') if 'description' in _dict: args['description'] = _dict.get('description') if 'image_url' in _dict: args['image_url'] = _dict.get('image_url') if 'channels' in _dict: args['channels'] = [ ResponseGenericChannel.from_dict(x) for x in _dict.get('channels') ] return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a RuntimeResponseGenericRuntimeResponseTypeIframe object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'response_type') and self.response_type is not None: _dict['response_type'] = self.response_type if hasattr(self, 'source') and self.source is not None: _dict['source'] = self.source if hasattr(self, 'title') and self.title is not None: _dict['title'] = self.title if hasattr(self, 'description') and self.description is not None: _dict['description'] = self.description if hasattr(self, 'image_url') and self.image_url is not None: _dict['image_url'] = self.image_url if hasattr(self, 'channels') and self.channels is not None: _dict['channels'] = [x.to_dict() for x in self.channels] return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this RuntimeResponseGenericRuntimeResponseTypeIframe object.""" return json.dumps(self.to_dict(), indent=2) def __eq__( self, other: 'RuntimeResponseGenericRuntimeResponseTypeIframe') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__( self, other: 'RuntimeResponseGenericRuntimeResponseTypeIframe') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class RuntimeResponseGenericRuntimeResponseTypeImage(RuntimeResponseGeneric): """ RuntimeResponseGenericRuntimeResponseTypeImage. :attr str response_type: The type of response returned by the dialog node. The specified response type must be supported by the client application or channel. :attr str source: The `https:` URL of the image. :attr str title: (optional) The title or introductory text to show before the response. :attr str description: (optional) The description to show with the response. :attr List[ResponseGenericChannel] channels: (optional) An array of objects specifying channels for which the response is intended. If **channels** is present, the response is intended for a built-in integration and should not be handled by an API client. :attr str alt_text: (optional) Descriptive text that can be used for screen readers or other situations where the image cannot be seen. """ def __init__(self, response_type: str, source: str, *, title: str = None, description: str = None, channels: List['ResponseGenericChannel'] = None, alt_text: str = None) -> None: """ Initialize a RuntimeResponseGenericRuntimeResponseTypeImage object. :param str response_type: The type of response returned by the dialog node. The specified response type must be supported by the client application or channel. :param str source: The `https:` URL of the image. :param str title: (optional) The title or introductory text to show before the response. :param str description: (optional) The description to show with the response. :param List[ResponseGenericChannel] channels: (optional) An array of objects specifying channels for which the response is intended. If **channels** is present, the response is intended for a built-in integration and should not be handled by an API client. :param str alt_text: (optional) Descriptive text that can be used for screen readers or other situations where the image cannot be seen. """ # pylint: disable=super-init-not-called self.response_type = response_type self.source = source self.title = title self.description = description self.channels = channels self.alt_text = alt_text @classmethod def from_dict( cls, _dict: Dict) -> 'RuntimeResponseGenericRuntimeResponseTypeImage': """Initialize a RuntimeResponseGenericRuntimeResponseTypeImage object from a json dictionary.""" args = {} if 'response_type' in _dict: args['response_type'] = _dict.get('response_type') else: raise ValueError( 'Required property \'response_type\' not present in RuntimeResponseGenericRuntimeResponseTypeImage JSON' ) if 'source' in _dict: args['source'] = _dict.get('source') else: raise ValueError( 'Required property \'source\' not present in RuntimeResponseGenericRuntimeResponseTypeImage JSON' ) if 'title' in _dict: args['title'] = _dict.get('title') if 'description' in _dict: args['description'] = _dict.get('description') if 'channels' in _dict: args['channels'] = [ ResponseGenericChannel.from_dict(x) for x in _dict.get('channels') ] if 'alt_text' in _dict: args['alt_text'] = _dict.get('alt_text') return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a RuntimeResponseGenericRuntimeResponseTypeImage object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'response_type') and self.response_type is not None: _dict['response_type'] = self.response_type if hasattr(self, 'source') and self.source is not None: _dict['source'] = self.source if hasattr(self, 'title') and self.title is not None: _dict['title'] = self.title if hasattr(self, 'description') and self.description is not None: _dict['description'] = self.description if hasattr(self, 'channels') and self.channels is not None: _dict['channels'] = [x.to_dict() for x in self.channels] if hasattr(self, 'alt_text') and self.alt_text is not None: _dict['alt_text'] = self.alt_text return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this RuntimeResponseGenericRuntimeResponseTypeImage object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'RuntimeResponseGenericRuntimeResponseTypeImage') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'RuntimeResponseGenericRuntimeResponseTypeImage') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class RuntimeResponseGenericRuntimeResponseTypeOption(RuntimeResponseGeneric): """ RuntimeResponseGenericRuntimeResponseTypeOption. :attr str response_type: The type of response returned by the dialog node. The specified response type must be supported by the client application or channel. :attr str title: The title or introductory text to show before the response. :attr str description: (optional) The description to show with the response. :attr str preference: (optional) The preferred type of control to display. :attr List[DialogNodeOutputOptionsElement] options: An array of objects describing the options from which the user can choose. :attr List[ResponseGenericChannel] channels: (optional) An array of objects specifying channels for which the response is intended. If **channels** is present, the response is intended for a built-in integration and should not be handled by an API client. """ def __init__(self, response_type: str, title: str, options: List['DialogNodeOutputOptionsElement'], *, description: str = None, preference: str = None, channels: List['ResponseGenericChannel'] = None) -> None: """ Initialize a RuntimeResponseGenericRuntimeResponseTypeOption object. :param str response_type: The type of response returned by the dialog node. The specified response type must be supported by the client application or channel. :param str title: The title or introductory text to show before the response. :param List[DialogNodeOutputOptionsElement] options: An array of objects describing the options from which the user can choose. :param str description: (optional) The description to show with the response. :param str preference: (optional) The preferred type of control to display. :param List[ResponseGenericChannel] channels: (optional) An array of objects specifying channels for which the response is intended. If **channels** is present, the response is intended for a built-in integration and should not be handled by an API client. """ # pylint: disable=super-init-not-called self.response_type = response_type self.title = title self.description = description self.preference = preference self.options = options self.channels = channels @classmethod def from_dict( cls, _dict: Dict) -> 'RuntimeResponseGenericRuntimeResponseTypeOption': """Initialize a RuntimeResponseGenericRuntimeResponseTypeOption object from a json dictionary.""" args = {} if 'response_type' in _dict: args['response_type'] = _dict.get('response_type') else: raise ValueError( 'Required property \'response_type\' not present in RuntimeResponseGenericRuntimeResponseTypeOption JSON' ) if 'title' in _dict: args['title'] = _dict.get('title') else: raise ValueError( 'Required property \'title\' not present in RuntimeResponseGenericRuntimeResponseTypeOption JSON' ) if 'description' in _dict: args['description'] = _dict.get('description') if 'preference' in _dict: args['preference'] = _dict.get('preference') if 'options' in _dict: args['options'] = [ DialogNodeOutputOptionsElement.from_dict(x) for x in _dict.get('options') ] else: raise ValueError( 'Required property \'options\' not present in RuntimeResponseGenericRuntimeResponseTypeOption JSON' ) if 'channels' in _dict: args['channels'] = [ ResponseGenericChannel.from_dict(x) for x in _dict.get('channels') ] return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a RuntimeResponseGenericRuntimeResponseTypeOption object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'response_type') and self.response_type is not None: _dict['response_type'] = self.response_type if hasattr(self, 'title') and self.title is not None: _dict['title'] = self.title if hasattr(self, 'description') and self.description is not None: _dict['description'] = self.description if hasattr(self, 'preference') and self.preference is not None: _dict['preference'] = self.preference if hasattr(self, 'options') and self.options is not None: _dict['options'] = [x.to_dict() for x in self.options] if hasattr(self, 'channels') and self.channels is not None: _dict['channels'] = [x.to_dict() for x in self.channels] return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this RuntimeResponseGenericRuntimeResponseTypeOption object.""" return json.dumps(self.to_dict(), indent=2) def __eq__( self, other: 'RuntimeResponseGenericRuntimeResponseTypeOption') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__( self, other: 'RuntimeResponseGenericRuntimeResponseTypeOption') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class PreferenceEnum(str, Enum): """ The preferred type of control to display. """ DROPDOWN = 'dropdown' BUTTON = 'button' class RuntimeResponseGenericRuntimeResponseTypePause(RuntimeResponseGeneric): """ RuntimeResponseGenericRuntimeResponseTypePause. :attr str response_type: The type of response returned by the dialog node. The specified response type must be supported by the client application or channel. :attr int time: How long to pause, in milliseconds. :attr bool typing: (optional) Whether to send a "user is typing" event during the pause. :attr List[ResponseGenericChannel] channels: (optional) An array of objects specifying channels for which the response is intended. If **channels** is present, the response is intended for a built-in integration and should not be handled by an API client. """ def __init__(self, response_type: str, time: int, *, typing: bool = None, channels: List['ResponseGenericChannel'] = None) -> None: """ Initialize a RuntimeResponseGenericRuntimeResponseTypePause object. :param str response_type: The type of response returned by the dialog node. The specified response type must be supported by the client application or channel. :param int time: How long to pause, in milliseconds. :param bool typing: (optional) Whether to send a "user is typing" event during the pause. :param List[ResponseGenericChannel] channels: (optional) An array of objects specifying channels for which the response is intended. If **channels** is present, the response is intended for a built-in integration and should not be handled by an API client. """ # pylint: disable=super-init-not-called self.response_type = response_type self.time = time self.typing = typing self.channels = channels @classmethod def from_dict( cls, _dict: Dict) -> 'RuntimeResponseGenericRuntimeResponseTypePause': """Initialize a RuntimeResponseGenericRuntimeResponseTypePause object from a json dictionary.""" args = {} if 'response_type' in _dict: args['response_type'] = _dict.get('response_type') else: raise ValueError( 'Required property \'response_type\' not present in RuntimeResponseGenericRuntimeResponseTypePause JSON' ) if 'time' in _dict: args['time'] = _dict.get('time') else: raise ValueError( 'Required property \'time\' not present in RuntimeResponseGenericRuntimeResponseTypePause JSON' ) if 'typing' in _dict: args['typing'] = _dict.get('typing') if 'channels' in _dict: args['channels'] = [ ResponseGenericChannel.from_dict(x) for x in _dict.get('channels') ] return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a RuntimeResponseGenericRuntimeResponseTypePause object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'response_type') and self.response_type is not None: _dict['response_type'] = self.response_type if hasattr(self, 'time') and self.time is not None: _dict['time'] = self.time if hasattr(self, 'typing') and self.typing is not None: _dict['typing'] = self.typing if hasattr(self, 'channels') and self.channels is not None: _dict['channels'] = [x.to_dict() for x in self.channels] return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this RuntimeResponseGenericRuntimeResponseTypePause object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'RuntimeResponseGenericRuntimeResponseTypePause') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'RuntimeResponseGenericRuntimeResponseTypePause') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class RuntimeResponseGenericRuntimeResponseTypeSuggestion( RuntimeResponseGeneric): """ RuntimeResponseGenericRuntimeResponseTypeSuggestion. :attr str response_type: The type of response returned by the dialog node. The specified response type must be supported by the client application or channel. :attr str title: The title or introductory text to show before the response. :attr List[DialogSuggestion] suggestions: An array of objects describing the possible matching dialog nodes from which the user can choose. :attr List[ResponseGenericChannel] channels: (optional) An array of objects specifying channels for which the response is intended. If **channels** is present, the response is intended for a built-in integration and should not be handled by an API client. """ def __init__(self, response_type: str, title: str, suggestions: List['DialogSuggestion'], *, channels: List['ResponseGenericChannel'] = None) -> None: """ Initialize a RuntimeResponseGenericRuntimeResponseTypeSuggestion object. :param str response_type: The type of response returned by the dialog node. The specified response type must be supported by the client application or channel. :param str title: The title or introductory text to show before the response. :param List[DialogSuggestion] suggestions: An array of objects describing the possible matching dialog nodes from which the user can choose. :param List[ResponseGenericChannel] channels: (optional) An array of objects specifying channels for which the response is intended. If **channels** is present, the response is intended for a built-in integration and should not be handled by an API client. """ # pylint: disable=super-init-not-called self.response_type = response_type self.title = title self.suggestions = suggestions self.channels = channels @classmethod def from_dict( cls, _dict: Dict ) -> 'RuntimeResponseGenericRuntimeResponseTypeSuggestion': """Initialize a RuntimeResponseGenericRuntimeResponseTypeSuggestion object from a json dictionary.""" args = {} if 'response_type' in _dict: args['response_type'] = _dict.get('response_type') else: raise ValueError( 'Required property \'response_type\' not present in RuntimeResponseGenericRuntimeResponseTypeSuggestion JSON' ) if 'title' in _dict: args['title'] = _dict.get('title') else: raise ValueError( 'Required property \'title\' not present in RuntimeResponseGenericRuntimeResponseTypeSuggestion JSON' ) if 'suggestions' in _dict: args['suggestions'] = [ DialogSuggestion.from_dict(x) for x in _dict.get('suggestions') ] else: raise ValueError( 'Required property \'suggestions\' not present in RuntimeResponseGenericRuntimeResponseTypeSuggestion JSON' ) if 'channels' in _dict: args['channels'] = [ ResponseGenericChannel.from_dict(x) for x in _dict.get('channels') ] return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a RuntimeResponseGenericRuntimeResponseTypeSuggestion object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'response_type') and self.response_type is not None: _dict['response_type'] = self.response_type if hasattr(self, 'title') and self.title is not None: _dict['title'] = self.title if hasattr(self, 'suggestions') and self.suggestions is not None: _dict['suggestions'] = [x.to_dict() for x in self.suggestions] if hasattr(self, 'channels') and self.channels is not None: _dict['channels'] = [x.to_dict() for x in self.channels] return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this RuntimeResponseGenericRuntimeResponseTypeSuggestion object.""" return json.dumps(self.to_dict(), indent=2) def __eq__( self, other: 'RuntimeResponseGenericRuntimeResponseTypeSuggestion' ) -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__( self, other: 'RuntimeResponseGenericRuntimeResponseTypeSuggestion' ) -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class RuntimeResponseGenericRuntimeResponseTypeText(RuntimeResponseGeneric): """ RuntimeResponseGenericRuntimeResponseTypeText. :attr str response_type: The type of response returned by the dialog node. The specified response type must be supported by the client application or channel. :attr str text: The text of the response. :attr List[ResponseGenericChannel] channels: (optional) An array of objects specifying channels for which the response is intended. If **channels** is present, the response is intended for a built-in integration and should not be handled by an API client. """ def __init__(self, response_type: str, text: str, *, channels: List['ResponseGenericChannel'] = None) -> None: """ Initialize a RuntimeResponseGenericRuntimeResponseTypeText object. :param str response_type: The type of response returned by the dialog node. The specified response type must be supported by the client application or channel. :param str text: The text of the response. :param List[ResponseGenericChannel] channels: (optional) An array of objects specifying channels for which the response is intended. If **channels** is present, the response is intended for a built-in integration and should not be handled by an API client. """ # pylint: disable=super-init-not-called self.response_type = response_type self.text = text self.channels = channels @classmethod def from_dict( cls, _dict: Dict) -> 'RuntimeResponseGenericRuntimeResponseTypeText': """Initialize a RuntimeResponseGenericRuntimeResponseTypeText object from a json dictionary.""" args = {} if 'response_type' in _dict: args['response_type'] = _dict.get('response_type') else: raise ValueError( 'Required property \'response_type\' not present in RuntimeResponseGenericRuntimeResponseTypeText JSON' ) if 'text' in _dict: args['text'] = _dict.get('text') else: raise ValueError( 'Required property \'text\' not present in RuntimeResponseGenericRuntimeResponseTypeText JSON' ) if 'channels' in _dict: args['channels'] = [ ResponseGenericChannel.from_dict(x) for x in _dict.get('channels') ] return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a RuntimeResponseGenericRuntimeResponseTypeText object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'response_type') and self.response_type is not None: _dict['response_type'] = self.response_type if hasattr(self, 'text') and self.text is not None: _dict['text'] = self.text if hasattr(self, 'channels') and self.channels is not None: _dict['channels'] = [x.to_dict() for x in self.channels] return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this RuntimeResponseGenericRuntimeResponseTypeText object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'RuntimeResponseGenericRuntimeResponseTypeText') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'RuntimeResponseGenericRuntimeResponseTypeText') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class RuntimeResponseGenericRuntimeResponseTypeUserDefined( RuntimeResponseGeneric): """ RuntimeResponseGenericRuntimeResponseTypeUserDefined. :attr str response_type: The type of response returned by the dialog node. The specified response type must be supported by the client application or channel. :attr dict user_defined: An object containing any properties for the user-defined response type. :attr List[ResponseGenericChannel] channels: (optional) An array of objects specifying channels for which the response is intended. If **channels** is present, the response is intended for a built-in integration and should not be handled by an API client. """ def __init__(self, response_type: str, user_defined: dict, *, channels: List['ResponseGenericChannel'] = None) -> None: """ Initialize a RuntimeResponseGenericRuntimeResponseTypeUserDefined object. :param str response_type: The type of response returned by the dialog node. The specified response type must be supported by the client application or channel. :param dict user_defined: An object containing any properties for the user-defined response type. :param List[ResponseGenericChannel] channels: (optional) An array of objects specifying channels for which the response is intended. If **channels** is present, the response is intended for a built-in integration and should not be handled by an API client. """ # pylint: disable=super-init-not-called self.response_type = response_type self.user_defined = user_defined self.channels = channels @classmethod def from_dict( cls, _dict: Dict ) -> 'RuntimeResponseGenericRuntimeResponseTypeUserDefined': """Initialize a RuntimeResponseGenericRuntimeResponseTypeUserDefined object from a json dictionary.""" args = {} if 'response_type' in _dict: args['response_type'] = _dict.get('response_type') else: raise ValueError( 'Required property \'response_type\' not present in RuntimeResponseGenericRuntimeResponseTypeUserDefined JSON' ) if 'user_defined' in _dict: args['user_defined'] = _dict.get('user_defined') else: raise ValueError( 'Required property \'user_defined\' not present in RuntimeResponseGenericRuntimeResponseTypeUserDefined JSON' ) if 'channels' in _dict: args['channels'] = [ ResponseGenericChannel.from_dict(x) for x in _dict.get('channels') ] return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a RuntimeResponseGenericRuntimeResponseTypeUserDefined object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'response_type') and self.response_type is not None: _dict['response_type'] = self.response_type if hasattr(self, 'user_defined') and self.user_defined is not None: _dict['user_defined'] = self.user_defined if hasattr(self, 'channels') and self.channels is not None: _dict['channels'] = [x.to_dict() for x in self.channels] return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this RuntimeResponseGenericRuntimeResponseTypeUserDefined object.""" return json.dumps(self.to_dict(), indent=2) def __eq__( self, other: 'RuntimeResponseGenericRuntimeResponseTypeUserDefined' ) -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__( self, other: 'RuntimeResponseGenericRuntimeResponseTypeUserDefined' ) -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class RuntimeResponseGenericRuntimeResponseTypeVideo(RuntimeResponseGeneric): """ RuntimeResponseGenericRuntimeResponseTypeVideo. :attr str response_type: The type of response returned by the dialog node. The specified response type must be supported by the client application or channel. :attr str source: The `https:` URL of the video. :attr str title: (optional) The title or introductory text to show before the response. :attr str description: (optional) The description to show with the response. :attr List[ResponseGenericChannel] channels: (optional) An array of objects specifying channels for which the response is intended. If **channels** is present, the response is intended for a built-in integration and should not be handled by an API client. :attr object channel_options: (optional) For internal use only. :attr str alt_text: (optional) Descriptive text that can be used for screen readers or other situations where the video cannot be seen. """ def __init__(self, response_type: str, source: str, *, title: str = None, description: str = None, channels: List['ResponseGenericChannel'] = None, channel_options: object = None, alt_text: str = None) -> None: """ Initialize a RuntimeResponseGenericRuntimeResponseTypeVideo object. :param str response_type: The type of response returned by the dialog node. The specified response type must be supported by the client application or channel. :param str source: The `https:` URL of the video. :param str title: (optional) The title or introductory text to show before the response. :param str description: (optional) The description to show with the response. :param List[ResponseGenericChannel] channels: (optional) An array of objects specifying channels for which the response is intended. If **channels** is present, the response is intended for a built-in integration and should not be handled by an API client. :param object channel_options: (optional) For internal use only. :param str alt_text: (optional) Descriptive text that can be used for screen readers or other situations where the video cannot be seen. """ # pylint: disable=super-init-not-called self.response_type = response_type self.source = source self.title = title self.description = description self.channels = channels self.channel_options = channel_options self.alt_text = alt_text @classmethod def from_dict( cls, _dict: Dict) -> 'RuntimeResponseGenericRuntimeResponseTypeVideo': """Initialize a RuntimeResponseGenericRuntimeResponseTypeVideo object from a json dictionary.""" args = {} if 'response_type' in _dict: args['response_type'] = _dict.get('response_type') else: raise ValueError( 'Required property \'response_type\' not present in RuntimeResponseGenericRuntimeResponseTypeVideo JSON' ) if 'source' in _dict: args['source'] = _dict.get('source') else: raise ValueError( 'Required property \'source\' not present in RuntimeResponseGenericRuntimeResponseTypeVideo JSON' ) if 'title' in _dict: args['title'] = _dict.get('title') if 'description' in _dict: args['description'] = _dict.get('description') if 'channels' in _dict: args['channels'] = [ ResponseGenericChannel.from_dict(x) for x in _dict.get('channels') ] if 'channel_options' in _dict: args['channel_options'] = _dict.get('channel_options') if 'alt_text' in _dict: args['alt_text'] = _dict.get('alt_text') return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a RuntimeResponseGenericRuntimeResponseTypeVideo object from a json dictionary.""" return cls.from_dict(_dict) def to_dict(self) -> Dict: """Return a json dictionary representing this model.""" _dict = {} if hasattr(self, 'response_type') and self.response_type is not None: _dict['response_type'] = self.response_type if hasattr(self, 'source') and self.source is not None: _dict['source'] = self.source if hasattr(self, 'title') and self.title is not None: _dict['title'] = self.title if hasattr(self, 'description') and self.description is not None: _dict['description'] = self.description if hasattr(self, 'channels') and self.channels is not None: _dict['channels'] = [x.to_dict() for x in self.channels] if hasattr(self, 'channel_options') and self.channel_options is not None: _dict['channel_options'] = self.channel_options if hasattr(self, 'alt_text') and self.alt_text is not None: _dict['alt_text'] = self.alt_text return _dict def _to_dict(self): """Return a json dictionary representing this model.""" return self.to_dict() def __str__(self) -> str: """Return a `str` version of this RuntimeResponseGenericRuntimeResponseTypeVideo object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'RuntimeResponseGenericRuntimeResponseTypeVideo') -> bool: """Return `true` when self and other are equal, false otherwise.""" if not isinstance(other, self.__class__): return False return self.__dict__ == other.__dict__ def __ne__(self, other: 'RuntimeResponseGenericRuntimeResponseTypeVideo') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other