# 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 v2 API provides runtime methods your client application can use to send user input to an assistant and receive a response. API Version: 2.0 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 AssistantV2(BaseService): """The Assistant V2 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) ######################### # Sessions ######################### def create_session(self, assistant_id: str, **kwargs) -> DetailedResponse: """ Create a session. Create a new session. A session is used to send user input to a skill and receive responses. It also maintains the state of the conversation. A session persists until it is deleted, or until it times out because of inactivity. (For more information, see the [documentation](https://cloud.ibm.com/docs/assistant?topic=assistant-assistant-settings). :param str assistant_id: Unique identifier of the assistant. To find the assistant ID in the Watson Assistant user interface, open the assistant settings and click **API Details**. For information about creating assistants, see the [documentation](https://cloud.ibm.com/docs/assistant?topic=assistant-assistant-add#assistant-add-task). **Note:** Currently, the v2 API does not support creating assistants. :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 `SessionResponse` object """ if assistant_id is None: raise ValueError('assistant_id must be provided') headers = {} sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME, service_version='V2', operation_id='create_session') headers.update(sdk_headers) params = {'version': self.version} data = {} 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 = ['assistant_id'] path_param_values = self.encode_path_vars(assistant_id) path_param_dict = dict(zip(path_param_keys, path_param_values)) url = '/v2/assistants/{assistant_id}/sessions'.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_session(self, assistant_id: str, session_id: str, **kwargs) -> DetailedResponse: """ Delete session. Deletes a session explicitly before it times out. (For more information about the session inactivity timeout, see the [documentation](https://cloud.ibm.com/docs/assistant?topic=assistant-assistant-settings)). :param str assistant_id: Unique identifier of the assistant. To find the assistant ID in the Watson Assistant user interface, open the assistant settings and click **API Details**. For information about creating assistants, see the [documentation](https://cloud.ibm.com/docs/assistant?topic=assistant-assistant-add#assistant-add-task). **Note:** Currently, the v2 API does not support creating assistants. :param str session_id: Unique identifier of the session. :param dict headers: A `dict` containing the request headers :return: A `DetailedResponse` containing the result, headers and HTTP status code. :rtype: DetailedResponse """ if assistant_id is None: raise ValueError('assistant_id must be provided') if session_id is None: raise ValueError('session_id must be provided') headers = {} sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME, service_version='V2', operation_id='delete_session') 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 = ['assistant_id', 'session_id'] path_param_values = self.encode_path_vars(assistant_id, session_id) path_param_dict = dict(zip(path_param_keys, path_param_values)) url = '/v2/assistants/{assistant_id}/sessions/{session_id}'.format( **path_param_dict) request = self.prepare_request(method='DELETE', url=url, headers=headers, params=params) response = self.send(request, **kwargs) return response ######################### # Message ######################### def message(self, assistant_id: str, session_id: str, *, input: 'MessageInput' = None, context: 'MessageContext' = None, user_id: str = None, **kwargs) -> DetailedResponse: """ Send user input to assistant (stateful). Send user input to an assistant and receive a response, with conversation state (including context data) stored by Watson Assistant for the duration of the session. :param str assistant_id: Unique identifier of the assistant. To find the assistant ID in the Watson Assistant user interface, open the assistant settings and click **API Details**. For information about creating assistants, see the [documentation](https://cloud.ibm.com/docs/assistant?topic=assistant-assistant-add#assistant-add-task). **Note:** Currently, the v2 API does not support creating assistants. :param str session_id: Unique identifier of the session. :param MessageInput input: (optional) An input object that includes the input text. :param MessageContext context: (optional) Context data for the conversation. You can use this property to set or modify context variables, which can also be accessed by dialog nodes. The context is stored by the assistant on a per-session basis. **Note:** The total size of the context data stored for a stateful session cannot exceed 100KB. :param str user_id: (optional) A string value that identifies the user who is interacting with the assistant. 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.global.session_id**. **Note:** This property is the same as the **user_id** property in the global system context. If **user_id** is specified in both locations, the value specified at the root is used. :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 assistant_id is None: raise ValueError('assistant_id must be provided') if session_id is None: raise ValueError('session_id must be provided') if input is not None: input = convert_model(input) if context is not None: context = convert_model(context) headers = {} sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME, service_version='V2', operation_id='message') headers.update(sdk_headers) params = {'version': self.version} data = {'input': input, 'context': context, '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 = ['assistant_id', 'session_id'] path_param_values = self.encode_path_vars(assistant_id, session_id) path_param_dict = dict(zip(path_param_keys, path_param_values)) url = '/v2/assistants/{assistant_id}/sessions/{session_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 def message_stateless(self, assistant_id: str, *, input: 'MessageInputStateless' = None, context: 'MessageContextStateless' = None, user_id: str = None, **kwargs) -> DetailedResponse: """ Send user input to assistant (stateless). Send user input to an assistant and receive a response, with conversation state (including context data) managed by your application. :param str assistant_id: Unique identifier of the assistant. To find the assistant ID in the Watson Assistant user interface, open the assistant settings and click **API Details**. For information about creating assistants, see the [documentation](https://cloud.ibm.com/docs/assistant?topic=assistant-assistant-add#assistant-add-task). **Note:** Currently, the v2 API does not support creating assistants. :param MessageInputStateless input: (optional) An input object that includes the input text. :param MessageContextStateless context: (optional) Context data for the conversation. You can use this property to set or modify context variables, which can also be accessed by dialog nodes. The context is not stored by the assistant. To maintain session state, include the context from the previous response. **Note:** The total size of the context data for a stateless session cannot exceed 250KB. :param str user_id: (optional) A string value that identifies the user who is interacting with the assistant. 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.global.session_id**. **Note:** This property is the same as the **user_id** property in the global system context. If **user_id** is specified in both locations in a message request, the value specified at the root is used. :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 `MessageResponseStateless` object """ if assistant_id is None: raise ValueError('assistant_id must be provided') if input is not None: input = convert_model(input) if context is not None: context = convert_model(context) headers = {} sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME, service_version='V2', operation_id='message_stateless') headers.update(sdk_headers) params = {'version': self.version} data = {'input': input, 'context': context, '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 = ['assistant_id'] path_param_values = self.encode_path_vars(assistant_id) path_param_dict = dict(zip(path_param_keys, path_param_values)) url = '/v2/assistants/{assistant_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, skill_id: str, input: List['BulkClassifyUtterance'], **kwargs) -> DetailedResponse: """ Identify intents and entities in multiple user utterances. Send multiple user inputs to a dialog skill 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 skills or skill versions. This method is available only with Enterprise with Data Isolation plans. :param str skill_id: Unique identifier of the skill. To find the skill ID in the Watson Assistant user interface, open the skill settings and click **API Details**. :param List[BulkClassifyUtterance] input: 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 skill_id is None: raise ValueError('skill_id must be provided') if input is None: raise ValueError('input must be provided') input = [convert_model(x) for x in input] headers = {} sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME, service_version='V2', 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 = ['skill_id'] path_param_values = self.encode_path_vars(skill_id) path_param_dict = dict(zip(path_param_keys, path_param_values)) url = '/v2/skills/{skill_id}/workspace/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 ######################### # Logs ######################### def list_logs(self, assistant_id: str, *, sort: str = None, filter: str = None, page_limit: int = None, cursor: str = None, **kwargs) -> DetailedResponse: """ List log events for an assistant. List the events from the log of an assistant. This method requires Manager access, and is available only with Enterprise plans. **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 assistant_id: Unique identifier of the assistant. To find the assistant ID in the Watson Assistant user interface, open the assistant settings and click **API Details**. For information about creating assistants, see the [documentation](https://cloud.ibm.com/docs/assistant?topic=assistant-assistant-add#assistant-add-task). **Note:** Currently, the v2 API does not support creating assistants. :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 assistant_id is None: raise ValueError('assistant_id must be provided') headers = {} sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME, service_version='V2', 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 = ['assistant_id'] path_param_values = self.encode_path_vars(assistant_id) path_param_dict = dict(zip(path_param_keys, path_param_values)) url = '/v2/assistants/{assistant_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 ######################### # 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='V2', 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 = '/v2/user_data' request = self.prepare_request(method='DELETE', url=url, headers=headers, params=params) response = self.send(request, **kwargs) return response ######################### # Environments ######################### def list_environments(self, assistant_id: str, *, page_limit: int = None, include_count: bool = None, sort: str = None, cursor: str = None, include_audit: bool = None, **kwargs) -> DetailedResponse: """ List environments. List the environments associated with an assistant. :param str assistant_id: Unique identifier of the assistant. To find the assistant ID in the Watson Assistant user interface, open the assistant settings and click **API Details**. For information about creating assistants, see the [documentation](https://cloud.ibm.com/docs/assistant?topic=assistant-assistant-add#assistant-add-task). **Note:** Currently, the v2 API does not support creating assistants. :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 environments 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 `EnvironmentCollection` object """ if assistant_id is None: raise ValueError('assistant_id must be provided') headers = {} sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME, service_version='V2', operation_id='list_environments') 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 = ['assistant_id'] path_param_values = self.encode_path_vars(assistant_id) path_param_dict = dict(zip(path_param_keys, path_param_values)) url = '/v2/assistants/{assistant_id}/environments'.format( **path_param_dict) request = self.prepare_request(method='GET', url=url, headers=headers, params=params) response = self.send(request, **kwargs) return response def get_environment(self, assistant_id: str, environment_id: str, *, include_audit: bool = None, **kwargs) -> DetailedResponse: """ Get environment. Get information about an environment. For more information about environments, see [Environments](https://cloud.ibm.com/docs/watson-assistant?topic=watson-assistant-publish-overview#environments). :param str assistant_id: Unique identifier of the assistant. To find the assistant ID in the Watson Assistant user interface, open the assistant settings and click **API Details**. For information about creating assistants, see the [documentation](https://cloud.ibm.com/docs/assistant?topic=assistant-assistant-add#assistant-add-task). **Note:** Currently, the v2 API does not support creating assistants. :param str environment_id: Unique identifier of the environment. To find the environment ID in the Watson Assistant user interface, open the environment settings and click **API Details**. **Note:** Currently, the API does not support creating environments. :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 `Environment` object """ if assistant_id is None: raise ValueError('assistant_id must be provided') if environment_id is None: raise ValueError('environment_id must be provided') headers = {} sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME, service_version='V2', operation_id='get_environment') 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 = ['assistant_id', 'environment_id'] path_param_values = self.encode_path_vars(assistant_id, environment_id) path_param_dict = dict(zip(path_param_keys, path_param_values)) url = '/v2/assistants/{assistant_id}/environments/{environment_id}'.format( **path_param_dict) request = self.prepare_request(method='GET', url=url, headers=headers, params=params) response = self.send(request, **kwargs) return response ######################### # Releases ######################### def list_releases(self, assistant_id: str, *, page_limit: int = None, include_count: bool = None, sort: str = None, cursor: str = None, include_audit: bool = None, **kwargs) -> DetailedResponse: """ List releases. List the releases associated with an assistant. (In the Watson Assistant user interface, a release is called a *version*.). :param str assistant_id: Unique identifier of the assistant. To find the assistant ID in the Watson Assistant user interface, open the assistant settings and click **API Details**. For information about creating assistants, see the [documentation](https://cloud.ibm.com/docs/assistant?topic=assistant-assistant-add#assistant-add-task). **Note:** Currently, the v2 API does not support creating assistants. :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 `ReleaseCollection` object """ if assistant_id is None: raise ValueError('assistant_id must be provided') headers = {} sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME, service_version='V2', operation_id='list_releases') 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 = ['assistant_id'] path_param_values = self.encode_path_vars(assistant_id) path_param_dict = dict(zip(path_param_keys, path_param_values)) url = '/v2/assistants/{assistant_id}/releases'.format(**path_param_dict) request = self.prepare_request(method='GET', url=url, headers=headers, params=params) response = self.send(request, **kwargs) return response def get_release(self, assistant_id: str, release: str, *, include_audit: bool = None, **kwargs) -> DetailedResponse: """ Get release. Get information about a release. Release data is not available until publishing of the release completes. If publishing is still in progress, 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 release data. :param str assistant_id: Unique identifier of the assistant. To find the assistant ID in the Watson Assistant user interface, open the assistant settings and click **API Details**. For information about creating assistants, see the [documentation](https://cloud.ibm.com/docs/assistant?topic=assistant-assistant-add#assistant-add-task). **Note:** Currently, the v2 API does not support creating assistants. :param str release: Unique identifier of the release. :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 `Release` object """ if assistant_id is None: raise ValueError('assistant_id must be provided') if release is None: raise ValueError('release must be provided') headers = {} sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME, service_version='V2', operation_id='get_release') 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 = ['assistant_id', 'release'] path_param_values = self.encode_path_vars(assistant_id, release) path_param_dict = dict(zip(path_param_keys, path_param_values)) url = '/v2/assistants/{assistant_id}/releases/{release}'.format( **path_param_dict) request = self.prepare_request(method='GET', url=url, headers=headers, params=params) response = self.send(request, **kwargs) return response def deploy_release(self, assistant_id: str, release: str, environment_id: str, *, include_audit: bool = None, **kwargs) -> DetailedResponse: """ Deploy release. Update the environment with the content of the release. All snapshots saved as part of the release become active in the environment. :param str assistant_id: Unique identifier of the assistant. To find the assistant ID in the Watson Assistant user interface, open the assistant settings and click **API Details**. For information about creating assistants, see the [documentation](https://cloud.ibm.com/docs/assistant?topic=assistant-assistant-add#assistant-add-task). **Note:** Currently, the v2 API does not support creating assistants. :param str release: Unique identifier of the release. :param str environment_id: The environment ID of the environment where the release is to be deployed. :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 `Environment` object """ if assistant_id is None: raise ValueError('assistant_id must be provided') if release is None: raise ValueError('release must be provided') if environment_id is None: raise ValueError('environment_id must be provided') headers = {} sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME, service_version='V2', operation_id='deploy_release') headers.update(sdk_headers) params = {'version': self.version, 'include_audit': include_audit} data = {'environment_id': environment_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 = ['assistant_id', 'release'] path_param_values = self.encode_path_vars(assistant_id, release) path_param_dict = dict(zip(path_param_keys, path_param_values)) url = '/v2/assistants/{assistant_id}/releases/{release}/deploy'.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 class ListEnvironmentsEnums: """ Enums for list_environments parameters. """ class Sort(str, Enum): """ The attribute by which returned environments will be sorted. To reverse the sort order, prefix the value with a minus sign (`-`). """ NAME = 'name' UPDATED = 'updated' class ListReleasesEnums: """ Enums for list_releases 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' ############################################################################## # 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(): """ CaptureGroup. :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 DialogLogMessage(): """ Dialog log message details. :attr str level: The severity of the log message. :attr str message: 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, message: str, code: str, *, source: 'LogMessageSource' = None) -> None: """ Initialize a DialogLogMessage object. :param str level: The severity of the log message. :param str message: 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.message = message self.code = code self.source = source @classmethod def from_dict(cls, _dict: Dict) -> 'DialogLogMessage': """Initialize a DialogLogMessage object from a json dictionary.""" args = {} if 'level' in _dict: args['level'] = _dict.get('level') else: raise ValueError( 'Required property \'level\' not present in DialogLogMessage JSON' ) if 'message' in _dict: args['message'] = _dict.get('message') else: raise ValueError( 'Required property \'message\' not present in DialogLogMessage JSON' ) if 'code' in _dict: args['code'] = _dict.get('code') else: raise ValueError( 'Required property \'code\' not present in DialogLogMessage JSON' ) if 'source' in _dict: args['source'] = LogMessageSource.from_dict(_dict.get('source')) return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a DialogLogMessage 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, 'message') and self.message is not None: _dict['message'] = self.message 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 DialogLogMessage object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'DialogLogMessage') -> 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: 'DialogLogMessage') -> 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 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' WEB_ACTION = 'web-action' CLOUD_FUNCTION = 'cloud-function' 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 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 assistant 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 assistant 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 assistant if the user selects the corresponding option. :attr MessageInput input: (optional) An input object that includes the input text. """ def __init__(self, *, input: 'MessageInput' = None) -> None: """ Initialize a DialogNodeOutputOptionsElementValue object. :param MessageInput input: (optional) An input object that includes the input text. """ self.input = input @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')) 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() 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 DialogNodeVisited(): """ An objects containing detailed diagnostic information about a dialog node that was visited during processing of the input message. :attr str dialog_node: (optional) A dialog node that was visited 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 DialogNodeVisited object. :param str dialog_node: (optional) A dialog node that was visited 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) -> 'DialogNodeVisited': """Initialize a DialogNodeVisited 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 DialogNodeVisited 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 DialogNodeVisited object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'DialogNodeVisited') -> 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: 'DialogNodeVisited') -> 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 suggestion. This label is taken from the **title** or **user_label** property of the corresponding dialog node, depending on the disambiguation options. :attr DialogSuggestionValue value: An object defining the message input to be sent to the assistant 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. """ def __init__(self, label: str, value: 'DialogSuggestionValue', *, output: dict = None) -> None: """ Initialize a DialogSuggestion object. :param str label: The user-facing label for the suggestion. This label is taken from the **title** or **user_label** property of the corresponding dialog node, depending on the disambiguation options. :param DialogSuggestionValue value: An object defining the message input to be sent to the assistant 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. """ self.label = label self.value = value self.output = output @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') 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 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 to be sent to the assistant if the user selects the corresponding disambiguation option. :attr MessageInput input: (optional) An input object that includes the input text. """ def __init__(self, *, input: 'MessageInput' = None) -> None: """ Initialize a DialogSuggestionValue object. :param MessageInput input: (optional) An input object that includes the input text. """ self.input = input @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')) 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() 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 Environment(): """ Environment. :attr str name: (optional) The name of the environment. :attr str description: (optional) The description of the environment. :attr str language: (optional) The language of the environment. An environment is always created with the same language as the assistant it is associated with. :attr str assistant_id: (optional) The assistant ID of the assistant the environment is associated with. :attr str environment_id: (optional) The environment ID of the environment. :attr str environment: (optional) The type of the environment. All environments other than the `draft` and `live` environments have the type `staging`. :attr EnvironmentReleaseReference release_reference: (optional) An object describing the release that is currently deployed in the environment. :attr EnvironmentOrchestration orchestration: (optional) The search skill orchestration settings for the environment. :attr int session_timeout: (optional) The session inactivity timeout setting for the environment. :attr List[IntegrationReference] integration_references: (optional) An array of objects describing the integrations that exist in the environment. :attr List[SkillReference] skill_references: (optional) An array of objects describing the skills (such as actions and dialog) that exist in the environment. :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, *, name: str = None, description: str = None, language: str = None, assistant_id: str = None, environment_id: str = None, environment: str = None, release_reference: 'EnvironmentReleaseReference' = None, orchestration: 'EnvironmentOrchestration' = None, session_timeout: int = None, integration_references: List['IntegrationReference'] = None, skill_references: List['SkillReference'] = None, created: datetime = None, updated: datetime = None) -> None: """ Initialize a Environment object. :param str name: (optional) The name of the environment. :param str description: (optional) The description of the environment. :param str language: (optional) The language of the environment. An environment is always created with the same language as the assistant it is associated with. :param EnvironmentReleaseReference release_reference: (optional) An object describing the release that is currently deployed in the environment. :param EnvironmentOrchestration orchestration: (optional) The search skill orchestration settings for the environment. :param int session_timeout: (optional) The session inactivity timeout setting for the environment. :param List[IntegrationReference] integration_references: (optional) An array of objects describing the integrations that exist in the environment. :param List[SkillReference] skill_references: (optional) An array of objects describing the skills (such as actions and dialog) that exist in the environment. """ self.name = name self.description = description self.language = language self.assistant_id = assistant_id self.environment_id = environment_id self.environment = environment self.release_reference = release_reference self.orchestration = orchestration self.session_timeout = session_timeout self.integration_references = integration_references self.skill_references = skill_references self.created = created self.updated = updated @classmethod def from_dict(cls, _dict: Dict) -> 'Environment': """Initialize a Environment object from a json dictionary.""" args = {} if 'name' in _dict: args['name'] = _dict.get('name') if 'description' in _dict: args['description'] = _dict.get('description') if 'language' in _dict: args['language'] = _dict.get('language') if 'assistant_id' in _dict: args['assistant_id'] = _dict.get('assistant_id') if 'environment_id' in _dict: args['environment_id'] = _dict.get('environment_id') if 'environment' in _dict: args['environment'] = _dict.get('environment') if 'release_reference' in _dict: args['release_reference'] = EnvironmentReleaseReference.from_dict( _dict.get('release_reference')) if 'orchestration' in _dict: args['orchestration'] = EnvironmentOrchestration.from_dict( _dict.get('orchestration')) if 'session_timeout' in _dict: args['session_timeout'] = _dict.get('session_timeout') if 'integration_references' in _dict: args['integration_references'] = [ IntegrationReference.from_dict(x) for x in _dict.get('integration_references') ] if 'skill_references' in _dict: args['skill_references'] = [ SkillReference.from_dict(x) for x in _dict.get('skill_references') ] 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 Environment 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, 'assistant_id') and getattr( self, 'assistant_id') is not None: _dict['assistant_id'] = getattr(self, 'assistant_id') if hasattr(self, 'environment_id') and getattr( self, 'environment_id') is not None: _dict['environment_id'] = getattr(self, 'environment_id') if hasattr(self, 'environment') and getattr(self, 'environment') is not None: _dict['environment'] = getattr(self, 'environment') if hasattr(self, 'release_reference') and self.release_reference is not None: _dict['release_reference'] = self.release_reference.to_dict() if hasattr(self, 'orchestration') and self.orchestration is not None: _dict['orchestration'] = self.orchestration.to_dict() if hasattr(self, 'session_timeout') and self.session_timeout is not None: _dict['session_timeout'] = self.session_timeout if hasattr(self, 'integration_references' ) and self.integration_references is not None: _dict['integration_references'] = [ x.to_dict() for x in self.integration_references ] if hasattr(self, 'skill_references') and self.skill_references is not None: _dict['skill_references'] = [ x.to_dict() for x in self.skill_references ] 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 Environment object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'Environment') -> 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: 'Environment') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class EnvironmentCollection(): """ EnvironmentCollection. :attr List[Environment] environments: An array of objects describing the environments associated with an assistant. :attr Pagination pagination: The pagination data for the returned objects. """ def __init__(self, environments: List['Environment'], pagination: 'Pagination') -> None: """ Initialize a EnvironmentCollection object. :param List[Environment] environments: An array of objects describing the environments associated with an assistant. :param Pagination pagination: The pagination data for the returned objects. """ self.environments = environments self.pagination = pagination @classmethod def from_dict(cls, _dict: Dict) -> 'EnvironmentCollection': """Initialize a EnvironmentCollection object from a json dictionary.""" args = {} if 'environments' in _dict: args['environments'] = [ Environment.from_dict(x) for x in _dict.get('environments') ] else: raise ValueError( 'Required property \'environments\' not present in EnvironmentCollection JSON' ) if 'pagination' in _dict: args['pagination'] = Pagination.from_dict(_dict.get('pagination')) else: raise ValueError( 'Required property \'pagination\' not present in EnvironmentCollection JSON' ) return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a EnvironmentCollection 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, 'environments') and self.environments is not None: _dict['environments'] = [x.to_dict() for x in self.environments] 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 EnvironmentCollection object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'EnvironmentCollection') -> 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: 'EnvironmentCollection') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class EnvironmentOrchestration(): """ The search skill orchestration settings for the environment. :attr bool search_skill_fallback: (optional) Whether assistants deployed to the environment fall back to a search skill when responding to messages that do not match any intent. If no search skill is configured for the assistant, this property is ignored. """ def __init__(self, *, search_skill_fallback: bool = None) -> None: """ Initialize a EnvironmentOrchestration object. :param bool search_skill_fallback: (optional) Whether assistants deployed to the environment fall back to a search skill when responding to messages that do not match any intent. If no search skill is configured for the assistant, this property is ignored. """ self.search_skill_fallback = search_skill_fallback @classmethod def from_dict(cls, _dict: Dict) -> 'EnvironmentOrchestration': """Initialize a EnvironmentOrchestration object from a json dictionary.""" args = {} if 'search_skill_fallback' in _dict: args['search_skill_fallback'] = _dict.get('search_skill_fallback') return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a EnvironmentOrchestration 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, 'search_skill_fallback' ) and self.search_skill_fallback is not None: _dict['search_skill_fallback'] = self.search_skill_fallback 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 EnvironmentOrchestration object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'EnvironmentOrchestration') -> 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: 'EnvironmentOrchestration') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class EnvironmentReference(): """ EnvironmentReference. :attr str name: (optional) The name of the deployed environment. :attr str environment_id: (optional) The environment ID of the deployed environment. :attr str environment: (optional) The type of the deployed environment. All environments other than the draft and live environments have the type `staging`. """ def __init__(self, *, name: str = None, environment_id: str = None, environment: str = None) -> None: """ Initialize a EnvironmentReference object. :param str name: (optional) The name of the deployed environment. """ self.name = name self.environment_id = environment_id self.environment = environment @classmethod def from_dict(cls, _dict: Dict) -> 'EnvironmentReference': """Initialize a EnvironmentReference object from a json dictionary.""" args = {} if 'name' in _dict: args['name'] = _dict.get('name') if 'environment_id' in _dict: args['environment_id'] = _dict.get('environment_id') if 'environment' in _dict: args['environment'] = _dict.get('environment') return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a EnvironmentReference 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, 'environment_id') and getattr( self, 'environment_id') is not None: _dict['environment_id'] = getattr(self, 'environment_id') if hasattr(self, 'environment') and getattr(self, 'environment') is not None: _dict['environment'] = getattr(self, 'environment') 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 EnvironmentReference object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'EnvironmentReference') -> 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: 'EnvironmentReference') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class EnvironmentEnum(str, Enum): """ The type of the deployed environment. All environments other than the draft and live environments have the type `staging`. """ DRAFT = 'draft' LIVE = 'live' STAGING = 'staging' class EnvironmentReleaseReference(): """ An object describing the release that is currently deployed in the environment. :attr str release: (optional) The name of the deployed release. """ def __init__(self, *, release: str = None) -> None: """ Initialize a EnvironmentReleaseReference object. :param str release: (optional) The name of the deployed release. """ self.release = release @classmethod def from_dict(cls, _dict: Dict) -> 'EnvironmentReleaseReference': """Initialize a EnvironmentReleaseReference object from a json dictionary.""" args = {} if 'release' in _dict: args['release'] = _dict.get('release') return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a EnvironmentReleaseReference 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, 'release') and self.release is not None: _dict['release'] = self.release 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 EnvironmentReleaseReference object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'EnvironmentReleaseReference') -> 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: 'EnvironmentReleaseReference') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class IntegrationReference(): """ IntegrationReference. :attr str integration_id: (optional) The integration ID of the integration. :attr str type: (optional) The type of the integration. """ def __init__(self, *, integration_id: str = None, type: str = None) -> None: """ Initialize a IntegrationReference object. :param str integration_id: (optional) The integration ID of the integration. :param str type: (optional) The type of the integration. """ self.integration_id = integration_id self.type = type @classmethod def from_dict(cls, _dict: Dict) -> 'IntegrationReference': """Initialize a IntegrationReference object from a json dictionary.""" args = {} if 'integration_id' in _dict: args['integration_id'] = _dict.get('integration_id') if 'type' in _dict: args['type'] = _dict.get('type') return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a IntegrationReference 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, 'integration_id') and self.integration_id is not None: _dict['integration_id'] = self.integration_id 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 IntegrationReference object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'IntegrationReference') -> 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: 'IntegrationReference') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class Log(): """ Log. :attr str log_id: A unique identifier for the logged event. :attr MessageRequest request: A stateful message request formatted for the Watson Assistant service. :attr MessageResponse response: A response from the Watson Assistant service. :attr str assistant_id: Unique identifier of the assistant. :attr str session_id: The ID of the session the message was part of. :attr str skill_id: The unique identifier of the skill that responded to the message. :attr str snapshot: The name of the snapshot (dialog skill version) that responded to the message (for example, `draft`). :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 language: The language of the assistant to which the message request was made. :attr str customer_id: (optional) The customer ID specified for the message, if any. """ def __init__(self, log_id: str, request: 'MessageRequest', response: 'MessageResponse', assistant_id: str, session_id: str, skill_id: str, snapshot: str, request_timestamp: str, response_timestamp: str, language: str, *, customer_id: str = None) -> None: """ Initialize a Log object. :param str log_id: A unique identifier for the logged event. :param MessageRequest request: A stateful message request formatted for the Watson Assistant service. :param MessageResponse response: A response from the Watson Assistant service. :param str assistant_id: Unique identifier of the assistant. :param str session_id: The ID of the session the message was part of. :param str skill_id: The unique identifier of the skill that responded to the message. :param str snapshot: The name of the snapshot (dialog skill version) that responded to the message (for example, `draft`). :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 language: The language of the assistant to which the message request was made. :param str customer_id: (optional) The customer ID specified for the message, if any. """ self.log_id = log_id self.request = request self.response = response self.assistant_id = assistant_id self.session_id = session_id self.skill_id = skill_id self.snapshot = snapshot self.request_timestamp = request_timestamp self.response_timestamp = response_timestamp self.language = language self.customer_id = customer_id @classmethod def from_dict(cls, _dict: Dict) -> 'Log': """Initialize a Log object from a json dictionary.""" args = {} 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' 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 'assistant_id' in _dict: args['assistant_id'] = _dict.get('assistant_id') else: raise ValueError( 'Required property \'assistant_id\' not present in Log JSON') if 'session_id' in _dict: args['session_id'] = _dict.get('session_id') else: raise ValueError( 'Required property \'session_id\' not present in Log JSON') if 'skill_id' in _dict: args['skill_id'] = _dict.get('skill_id') else: raise ValueError( 'Required property \'skill_id\' not present in Log JSON') if 'snapshot' in _dict: args['snapshot'] = _dict.get('snapshot') else: raise ValueError( 'Required property \'snapshot\' 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 'language' in _dict: args['language'] = _dict.get('language') else: raise ValueError( 'Required property \'language\' not present in Log JSON') if 'customer_id' in _dict: args['customer_id'] = _dict.get('customer_id') 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, 'log_id') and self.log_id is not None: _dict['log_id'] = self.log_id 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, 'assistant_id') and self.assistant_id is not None: _dict['assistant_id'] = self.assistant_id if hasattr(self, 'session_id') and self.session_id is not None: _dict['session_id'] = self.session_id if hasattr(self, 'skill_id') and self.skill_id is not None: _dict['skill_id'] = self.skill_id if hasattr(self, 'snapshot') and self.snapshot is not None: _dict['snapshot'] = self.snapshot 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, 'language') and self.language is not None: _dict['language'] = self.language if hasattr(self, 'customer_id') and self.customer_id is not None: _dict['customer_id'] = self.customer_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 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 LogMessageSource(): """ An object that identifies the dialog element that generated the error message. """ def __init__(self) -> None: """ Initialize a LogMessageSource object. """ msg = "Cannot instantiate base class. Instead, instantiate one of the defined subclasses: {0}".format( ", ".join([ 'LogMessageSourceDialogNode', 'LogMessageSourceAction', 'LogMessageSourceStep', 'LogMessageSourceHandler' ])) raise Exception(msg) @classmethod def from_dict(cls, _dict: Dict) -> 'LogMessageSource': """Initialize a LogMessageSource 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 'LogMessageSource'. " + "The discriminator value should map to a valid subclass: {1}" ).format(", ".join([ 'LogMessageSourceDialogNode', 'LogMessageSourceAction', 'LogMessageSourceStep', 'LogMessageSourceHandler' ])) raise Exception(msg) @classmethod def _from_dict(cls, _dict: Dict): """Initialize a LogMessageSource object from a json dictionary.""" return cls.from_dict(_dict) @classmethod def _get_class_by_discriminator(cls, _dict: Dict) -> object: mapping = {} mapping['dialog_node'] = 'LogMessageSourceDialogNode' mapping['action'] = 'LogMessageSourceAction' mapping['step'] = 'LogMessageSourceStep' mapping['handler'] = 'LogMessageSourceHandler' disc_value = _dict.get('type') if disc_value is None: raise ValueError( 'Discriminator property \'type\' not found in LogMessageSource 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 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 MessageContext(): """ MessageContext. :attr MessageContextGlobal global_: (optional) Session context data that is shared by all skills used by the assistant. :attr dict skills: (optional) Information specific to particular skills used by the assistant. :attr object integrations: (optional) An object containing context data that is specific to particular integrations. For more information, see the [documentation](https://cloud.ibm.com/docs/assistant?topic=assistant-dialog-integrations). """ def __init__(self, *, global_: 'MessageContextGlobal' = None, skills: dict = None, integrations: object = None) -> None: """ Initialize a MessageContext object. :param MessageContextGlobal global_: (optional) Session context data that is shared by all skills used by the assistant. :param dict skills: (optional) Information specific to particular skills used by the assistant. :param object integrations: (optional) An object containing context data that is specific to particular integrations. For more information, see the [documentation](https://cloud.ibm.com/docs/assistant?topic=assistant-dialog-integrations). """ self.global_ = global_ self.skills = skills self.integrations = integrations @classmethod def from_dict(cls, _dict: Dict) -> 'MessageContext': """Initialize a MessageContext object from a json dictionary.""" args = {} if 'global' in _dict: args['global_'] = MessageContextGlobal.from_dict( _dict.get('global')) if 'skills' in _dict: args['skills'] = { k: MessageContextSkill.from_dict(v) for k, v in _dict.get('skills').items() } if 'integrations' in _dict: args['integrations'] = _dict.get('integrations') return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a MessageContext 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, 'global_') and self.global_ is not None: _dict['global'] = self.global_.to_dict() if hasattr(self, 'skills') and self.skills is not None: _dict['skills'] = {k: v.to_dict() for k, v in self.skills.items()} if hasattr(self, 'integrations') and self.integrations is not None: _dict['integrations'] = self.integrations 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 MessageContext object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'MessageContext') -> 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: 'MessageContext') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class MessageContextGlobal(): """ Session context data that is shared by all skills used by the assistant. :attr MessageContextGlobalSystem system: (optional) Built-in system properties that apply to all skills used by the assistant. :attr str session_id: (optional) The session ID. """ def __init__(self, *, system: 'MessageContextGlobalSystem' = None, session_id: str = None) -> None: """ Initialize a MessageContextGlobal object. :param MessageContextGlobalSystem system: (optional) Built-in system properties that apply to all skills used by the assistant. """ self.system = system self.session_id = session_id @classmethod def from_dict(cls, _dict: Dict) -> 'MessageContextGlobal': """Initialize a MessageContextGlobal object from a json dictionary.""" args = {} if 'system' in _dict: args['system'] = MessageContextGlobalSystem.from_dict( _dict.get('system')) if 'session_id' in _dict: args['session_id'] = _dict.get('session_id') return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a MessageContextGlobal 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, 'system') and self.system is not None: _dict['system'] = self.system.to_dict() if hasattr(self, 'session_id') and getattr(self, 'session_id') is not None: _dict['session_id'] = getattr(self, 'session_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 MessageContextGlobal object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'MessageContextGlobal') -> 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: 'MessageContextGlobal') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class MessageContextGlobalStateless(): """ Session context data that is shared by all skills used by the assistant. :attr MessageContextGlobalSystem system: (optional) Built-in system properties that apply to all skills used by the assistant. :attr str session_id: (optional) The unique identifier of the session. """ def __init__(self, *, system: 'MessageContextGlobalSystem' = None, session_id: str = None) -> None: """ Initialize a MessageContextGlobalStateless object. :param MessageContextGlobalSystem system: (optional) Built-in system properties that apply to all skills used by the assistant. :param str session_id: (optional) The unique identifier of the session. """ self.system = system self.session_id = session_id @classmethod def from_dict(cls, _dict: Dict) -> 'MessageContextGlobalStateless': """Initialize a MessageContextGlobalStateless object from a json dictionary.""" args = {} if 'system' in _dict: args['system'] = MessageContextGlobalSystem.from_dict( _dict.get('system')) if 'session_id' in _dict: args['session_id'] = _dict.get('session_id') return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a MessageContextGlobalStateless 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, 'system') and self.system is not None: _dict['system'] = self.system.to_dict() if hasattr(self, 'session_id') and self.session_id is not None: _dict['session_id'] = self.session_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 MessageContextGlobalStateless object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'MessageContextGlobalStateless') -> 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: 'MessageContextGlobalStateless') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class MessageContextGlobalSystem(): """ Built-in system properties that apply to all skills used by the assistant. :attr str timezone: (optional) The user time zone. The assistant uses the time zone to correctly resolve relative time references. :attr str user_id: (optional) A string value that identifies the user who is interacting with the assistant. 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.global.session_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. :attr int turn_count: (optional) A counter that is automatically incremented with each turn of the conversation. A value of 1 indicates that this is the the first turn of a new conversation, which can affect the behavior of some skills (for example, triggering the start node of a dialog). :attr str locale: (optional) The language code for localization in the user input. The specified locale overrides the default for the assistant, and is used for interpreting entity values in user input such as date values. For example, `04/03/2018` might be interpreted either as April 3 or March 4, depending on the locale. This property is included only if the new system entities are enabled for the skill. :attr str reference_time: (optional) The base time for interpreting any relative time mentions in the user input. The specified time overrides the current server time, and is used to calculate times mentioned in relative terms such as `now` or `tomorrow`. This can be useful for simulating past or future times for testing purposes, or when analyzing documents such as news articles. This value must be a UTC time value formatted according to ISO 8601 (for example, `2021-06-26T12:00:00Z` for noon UTC on 26 June 2021). This property is included only if the new system entities are enabled for the skill. :attr str session_start_time: (optional) The time at which the session started. With the stateful `message` method, the start time is always present, and is set by the service based on the time the session was created. With the stateless `message` method, the start time is set by the service in the response to the first message, and should be returned as part of the context with each subsequent message in the session. This value is a UTC time value formatted according to ISO 8601 (for example, `2021-06-26T12:00:00Z` for noon UTC on 26 June 2021). :attr str state: (optional) An encoded string that represents the configuration state of the assistant at the beginning of the conversation. If you are using the stateless `message` method, save this value and then send it in the context of the subsequent message request to avoid disruptions if there are configuration changes during the conversation (such as a change to a skill the assistant uses). :attr bool skip_user_input: (optional) For internal use only. """ def __init__(self, *, timezone: str = None, user_id: str = None, turn_count: int = None, locale: str = None, reference_time: str = None, session_start_time: str = None, state: str = None, skip_user_input: bool = None) -> None: """ Initialize a MessageContextGlobalSystem object. :param str timezone: (optional) The user time zone. The assistant uses the time zone to correctly resolve relative time references. :param str user_id: (optional) A string value that identifies the user who is interacting with the assistant. 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.global.session_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. :param int turn_count: (optional) A counter that is automatically incremented with each turn of the conversation. A value of 1 indicates that this is the the first turn of a new conversation, which can affect the behavior of some skills (for example, triggering the start node of a dialog). :param str locale: (optional) The language code for localization in the user input. The specified locale overrides the default for the assistant, and is used for interpreting entity values in user input such as date values. For example, `04/03/2018` might be interpreted either as April 3 or March 4, depending on the locale. This property is included only if the new system entities are enabled for the skill. :param str reference_time: (optional) The base time for interpreting any relative time mentions in the user input. The specified time overrides the current server time, and is used to calculate times mentioned in relative terms such as `now` or `tomorrow`. This can be useful for simulating past or future times for testing purposes, or when analyzing documents such as news articles. This value must be a UTC time value formatted according to ISO 8601 (for example, `2021-06-26T12:00:00Z` for noon UTC on 26 June 2021). This property is included only if the new system entities are enabled for the skill. :param str session_start_time: (optional) The time at which the session started. With the stateful `message` method, the start time is always present, and is set by the service based on the time the session was created. With the stateless `message` method, the start time is set by the service in the response to the first message, and should be returned as part of the context with each subsequent message in the session. This value is a UTC time value formatted according to ISO 8601 (for example, `2021-06-26T12:00:00Z` for noon UTC on 26 June 2021). :param str state: (optional) An encoded string that represents the configuration state of the assistant at the beginning of the conversation. If you are using the stateless `message` method, save this value and then send it in the context of the subsequent message request to avoid disruptions if there are configuration changes during the conversation (such as a change to a skill the assistant uses). :param bool skip_user_input: (optional) For internal use only. """ self.timezone = timezone self.user_id = user_id self.turn_count = turn_count self.locale = locale self.reference_time = reference_time self.session_start_time = session_start_time self.state = state self.skip_user_input = skip_user_input @classmethod def from_dict(cls, _dict: Dict) -> 'MessageContextGlobalSystem': """Initialize a MessageContextGlobalSystem object from a json dictionary.""" args = {} if 'timezone' in _dict: args['timezone'] = _dict.get('timezone') if 'user_id' in _dict: args['user_id'] = _dict.get('user_id') if 'turn_count' in _dict: args['turn_count'] = _dict.get('turn_count') if 'locale' in _dict: args['locale'] = _dict.get('locale') if 'reference_time' in _dict: args['reference_time'] = _dict.get('reference_time') if 'session_start_time' in _dict: args['session_start_time'] = _dict.get('session_start_time') if 'state' in _dict: args['state'] = _dict.get('state') if 'skip_user_input' in _dict: args['skip_user_input'] = _dict.get('skip_user_input') return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a MessageContextGlobalSystem 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, 'timezone') and self.timezone is not None: _dict['timezone'] = self.timezone if hasattr(self, 'user_id') and self.user_id is not None: _dict['user_id'] = self.user_id if hasattr(self, 'turn_count') and self.turn_count is not None: _dict['turn_count'] = self.turn_count if hasattr(self, 'locale') and self.locale is not None: _dict['locale'] = self.locale if hasattr(self, 'reference_time') and self.reference_time is not None: _dict['reference_time'] = self.reference_time if hasattr( self, 'session_start_time') and self.session_start_time is not None: _dict['session_start_time'] = self.session_start_time if hasattr(self, 'state') and self.state is not None: _dict['state'] = self.state if hasattr(self, 'skip_user_input') and self.skip_user_input is not None: _dict['skip_user_input'] = self.skip_user_input 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 MessageContextGlobalSystem object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'MessageContextGlobalSystem') -> 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: 'MessageContextGlobalSystem') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class LocaleEnum(str, Enum): """ The language code for localization in the user input. The specified locale overrides the default for the assistant, and is used for interpreting entity values in user input such as date values. For example, `04/03/2018` might be interpreted either as April 3 or March 4, depending on the locale. This property is included only if the new system entities are enabled for the skill. """ EN_US = 'en-us' EN_CA = 'en-ca' EN_GB = 'en-gb' AR_AR = 'ar-ar' CS_CZ = 'cs-cz' DE_DE = 'de-de' ES_ES = 'es-es' FR_FR = 'fr-fr' IT_IT = 'it-it' JA_JP = 'ja-jp' KO_KR = 'ko-kr' NL_NL = 'nl-nl' PT_BR = 'pt-br' ZH_CN = 'zh-cn' ZH_TW = 'zh-tw' class MessageContextSkill(): """ Contains information specific to a particular skill used by the assistant. The property name must be the same as the name of the skill. **Note:** The default skill names are `main skill` for the dialog skill (if enabled), and `actions skill` for the actions skill. :attr dict user_defined: (optional) Arbitrary variables that can be read and written by a particular skill. :attr MessageContextSkillSystem system: (optional) System context data used by the skill. """ def __init__(self, *, user_defined: dict = None, system: 'MessageContextSkillSystem' = None) -> None: """ Initialize a MessageContextSkill object. :param dict user_defined: (optional) Arbitrary variables that can be read and written by a particular skill. :param MessageContextSkillSystem system: (optional) System context data used by the skill. """ self.user_defined = user_defined self.system = system @classmethod def from_dict(cls, _dict: Dict) -> 'MessageContextSkill': """Initialize a MessageContextSkill object from a json dictionary.""" args = {} if 'user_defined' in _dict: args['user_defined'] = _dict.get('user_defined') if 'system' in _dict: args['system'] = MessageContextSkillSystem.from_dict( _dict.get('system')) return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a MessageContextSkill 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, 'user_defined') and self.user_defined is not None: _dict['user_defined'] = self.user_defined if hasattr(self, 'system') and self.system is not None: _dict['system'] = self.system.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 MessageContextSkill object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'MessageContextSkill') -> 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: 'MessageContextSkill') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class MessageContextSkillSystem(): """ System context data used by the skill. :attr str state: (optional) An encoded string that represents the current conversation state. By saving this value and then sending it in the context of a subsequent message request, you can return to an earlier point in the conversation. If you are using stateful sessions, you can also use a stored state value to restore a paused conversation whose session is expired. """ # The set of defined properties for the class _properties = frozenset(['state']) def __init__(self, *, state: str = None, **kwargs) -> None: """ Initialize a MessageContextSkillSystem object. :param str state: (optional) An encoded string that represents the current conversation state. By saving this value and then sending it in the context of a subsequent message request, you can return to an earlier point in the conversation. If you are using stateful sessions, you can also use a stored state value to restore a paused conversation whose session is expired. :param **kwargs: (optional) Any additional properties. """ self.state = state for _key, _value in kwargs.items(): setattr(self, _key, _value) @classmethod def from_dict(cls, _dict: Dict) -> 'MessageContextSkillSystem': """Initialize a MessageContextSkillSystem object from a json dictionary.""" args = {} if 'state' in _dict: args['state'] = _dict.get('state') 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 MessageContextSkillSystem 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, 'state') and self.state is not None: _dict['state'] = self.state for _key in [ k for k in vars(self).keys() if k not in MessageContextSkillSystem._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 MessageContextSkillSystem""" _dict = {} for _key in [ k for k in vars(self).keys() if k not in MessageContextSkillSystem._properties ]: _dict[_key] = getattr(self, _key) return _dict def set_properties(self, _dict: dict): """Set a dictionary of arbitrary properties to this instance of MessageContextSkillSystem""" for _key in [ k for k in vars(self).keys() if k not in MessageContextSkillSystem._properties ]: delattr(self, _key) for _key, _value in _dict.items(): if _key not in MessageContextSkillSystem._properties: setattr(self, _key, _value) def __str__(self) -> str: """Return a `str` version of this MessageContextSkillSystem object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'MessageContextSkillSystem') -> 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: 'MessageContextSkillSystem') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class MessageContextStateless(): """ MessageContextStateless. :attr MessageContextGlobalStateless global_: (optional) Session context data that is shared by all skills used by the assistant. :attr dict skills: (optional) Information specific to particular skills used by the assistant. :attr object integrations: (optional) An object containing context data that is specific to particular integrations. For more information, see the [documentation](https://cloud.ibm.com/docs/assistant?topic=assistant-dialog-integrations). """ def __init__(self, *, global_: 'MessageContextGlobalStateless' = None, skills: dict = None, integrations: object = None) -> None: """ Initialize a MessageContextStateless object. :param MessageContextGlobalStateless global_: (optional) Session context data that is shared by all skills used by the assistant. :param dict skills: (optional) Information specific to particular skills used by the assistant. :param object integrations: (optional) An object containing context data that is specific to particular integrations. For more information, see the [documentation](https://cloud.ibm.com/docs/assistant?topic=assistant-dialog-integrations). """ self.global_ = global_ self.skills = skills self.integrations = integrations @classmethod def from_dict(cls, _dict: Dict) -> 'MessageContextStateless': """Initialize a MessageContextStateless object from a json dictionary.""" args = {} if 'global' in _dict: args['global_'] = MessageContextGlobalStateless.from_dict( _dict.get('global')) if 'skills' in _dict: args['skills'] = { k: MessageContextSkill.from_dict(v) for k, v in _dict.get('skills').items() } if 'integrations' in _dict: args['integrations'] = _dict.get('integrations') return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a MessageContextStateless 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, 'global_') and self.global_ is not None: _dict['global'] = self.global_.to_dict() if hasattr(self, 'skills') and self.skills is not None: _dict['skills'] = {k: v.to_dict() for k, v in self.skills.items()} if hasattr(self, 'integrations') and self.integrations is not None: _dict['integrations'] = self.integrations 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 MessageContextStateless object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'MessageContextStateless') -> 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: 'MessageContextStateless') -> 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 message_type: (optional) The type of the message: - `text`: The user input is processed normally by the assistant. - `search`: Only search results are returned. (Any dialog or actions skill is bypassed.) **Note:** A `search` message results in an error if no search skill is configured for the assistant. :attr str text: (optional) The text of the user input. This string cannot contain carriage return, newline, or tab characters. :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 str suggestion_id: (optional) For internal use only. :attr List[MessageInputAttachment] attachments: (optional) An array of multimedia attachments to be sent with the message. **Note:** Attachments are not processed by the assistant itself, but can be sent to external services by webhooks. :attr MessageInputOptions options: (optional) Optional properties that control how the assistant responds. """ def __init__(self, *, message_type: str = None, text: str = None, intents: List['RuntimeIntent'] = None, entities: List['RuntimeEntity'] = None, suggestion_id: str = None, attachments: List['MessageInputAttachment'] = None, options: 'MessageInputOptions' = None) -> None: """ Initialize a MessageInput object. :param str message_type: (optional) The type of the message: - `text`: The user input is processed normally by the assistant. - `search`: Only search results are returned. (Any dialog or actions skill is bypassed.) **Note:** A `search` message results in an error if no search skill is configured for the assistant. :param str text: (optional) The text of the user input. This string cannot contain carriage return, newline, or tab characters. :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 str suggestion_id: (optional) For internal use only. :param List[MessageInputAttachment] attachments: (optional) An array of multimedia attachments to be sent with the message. **Note:** Attachments are not processed by the assistant itself, but can be sent to external services by webhooks. :param MessageInputOptions options: (optional) Optional properties that control how the assistant responds. """ self.message_type = message_type self.text = text self.intents = intents self.entities = entities self.suggestion_id = suggestion_id self.attachments = attachments self.options = options @classmethod def from_dict(cls, _dict: Dict) -> 'MessageInput': """Initialize a MessageInput object from a json dictionary.""" args = {} if 'message_type' in _dict: args['message_type'] = _dict.get('message_type') if 'text' in _dict: args['text'] = _dict.get('text') 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 'suggestion_id' in _dict: args['suggestion_id'] = _dict.get('suggestion_id') if 'attachments' in _dict: args['attachments'] = [ MessageInputAttachment.from_dict(x) for x in _dict.get('attachments') ] if 'options' in _dict: args['options'] = MessageInputOptions.from_dict( _dict.get('options')) 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, 'message_type') and self.message_type is not None: _dict['message_type'] = self.message_type if hasattr(self, 'text') and self.text is not None: _dict['text'] = self.text 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, 'suggestion_id') and self.suggestion_id is not None: _dict['suggestion_id'] = self.suggestion_id if hasattr(self, 'attachments') and self.attachments is not None: _dict['attachments'] = [x.to_dict() for x in self.attachments] if hasattr(self, 'options') and self.options is not None: _dict['options'] = self.options.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 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 MessageTypeEnum(str, Enum): """ The type of the message: - `text`: The user input is processed normally by the assistant. - `search`: Only search results are returned. (Any dialog or actions skill is bypassed.) **Note:** A `search` message results in an error if no search skill is configured for the assistant. """ TEXT = 'text' SEARCH = 'search' class MessageInputAttachment(): """ A reference to a media file to be sent as an attachment with the message. :attr str url: The URL of the media file. :attr str media_type: (optional) The media content type (such as a MIME type) of the attachment. """ def __init__(self, url: str, *, media_type: str = None) -> None: """ Initialize a MessageInputAttachment object. :param str url: The URL of the media file. :param str media_type: (optional) The media content type (such as a MIME type) of the attachment. """ self.url = url self.media_type = media_type @classmethod def from_dict(cls, _dict: Dict) -> 'MessageInputAttachment': """Initialize a MessageInputAttachment object from a json dictionary.""" args = {} if 'url' in _dict: args['url'] = _dict.get('url') else: raise ValueError( 'Required property \'url\' not present in MessageInputAttachment JSON' ) if 'media_type' in _dict: args['media_type'] = _dict.get('media_type') return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a MessageInputAttachment 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, 'media_type') and self.media_type is not None: _dict['media_type'] = self.media_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 MessageInputAttachment object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'MessageInputAttachment') -> 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: 'MessageInputAttachment') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class MessageInputOptions(): """ Optional properties that control how the assistant responds. :attr bool restart: (optional) Whether to restart dialog processing at the root of the dialog, regardless of any previously visited nodes. **Note:** This does not affect `turn_count` or any other context variables. :attr bool alternate_intents: (optional) Whether to return more than one intent. Set to `true` to return all matching intents. :attr MessageInputOptionsSpelling spelling: (optional) Spelling correction options for the message. Any options specified on an individual message override the settings configured for the skill. :attr bool debug: (optional) Whether to return additional diagnostic information. Set to `true` to return additional information in the `output.debug` property. If you also specify **return_context**=`true`, the returned skill context includes the `system.state` property. :attr bool return_context: (optional) Whether to return session context with the response. If you specify `true`, the response includes the `context` property. If you also specify **debug**=`true`, the returned skill context includes the `system.state` property. :attr bool export: (optional) Whether to return session context, including full conversation state. If you specify `true`, the response includes the `context` property, and the skill context includes the `system.state` property. **Note:** If **export**=`true`, the context is returned regardless of the value of **return_context**. """ def __init__(self, *, restart: bool = None, alternate_intents: bool = None, spelling: 'MessageInputOptionsSpelling' = None, debug: bool = None, return_context: bool = None, export: bool = None) -> None: """ Initialize a MessageInputOptions object. :param bool restart: (optional) Whether to restart dialog processing at the root of the dialog, regardless of any previously visited nodes. **Note:** This does not affect `turn_count` or any other context variables. :param bool alternate_intents: (optional) Whether to return more than one intent. Set to `true` to return all matching intents. :param MessageInputOptionsSpelling spelling: (optional) Spelling correction options for the message. Any options specified on an individual message override the settings configured for the skill. :param bool debug: (optional) Whether to return additional diagnostic information. Set to `true` to return additional information in the `output.debug` property. If you also specify **return_context**=`true`, the returned skill context includes the `system.state` property. :param bool return_context: (optional) Whether to return session context with the response. If you specify `true`, the response includes the `context` property. If you also specify **debug**=`true`, the returned skill context includes the `system.state` property. :param bool export: (optional) Whether to return session context, including full conversation state. If you specify `true`, the response includes the `context` property, and the skill context includes the `system.state` property. **Note:** If **export**=`true`, the context is returned regardless of the value of **return_context**. """ self.restart = restart self.alternate_intents = alternate_intents self.spelling = spelling self.debug = debug self.return_context = return_context self.export = export @classmethod def from_dict(cls, _dict: Dict) -> 'MessageInputOptions': """Initialize a MessageInputOptions object from a json dictionary.""" args = {} if 'restart' in _dict: args['restart'] = _dict.get('restart') if 'alternate_intents' in _dict: args['alternate_intents'] = _dict.get('alternate_intents') if 'spelling' in _dict: args['spelling'] = MessageInputOptionsSpelling.from_dict( _dict.get('spelling')) if 'debug' in _dict: args['debug'] = _dict.get('debug') if 'return_context' in _dict: args['return_context'] = _dict.get('return_context') if 'export' in _dict: args['export'] = _dict.get('export') return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a MessageInputOptions 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, 'restart') and self.restart is not None: _dict['restart'] = self.restart if hasattr(self, 'alternate_intents') and self.alternate_intents is not None: _dict['alternate_intents'] = self.alternate_intents if hasattr(self, 'spelling') and self.spelling is not None: _dict['spelling'] = self.spelling.to_dict() if hasattr(self, 'debug') and self.debug is not None: _dict['debug'] = self.debug if hasattr(self, 'return_context') and self.return_context is not None: _dict['return_context'] = self.return_context if hasattr(self, 'export') and self.export is not None: _dict['export'] = self.export 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 MessageInputOptions object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'MessageInputOptions') -> 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: 'MessageInputOptions') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class MessageInputOptionsSpelling(): """ Spelling correction options for the message. Any options specified on an individual message override the settings configured for the skill. :attr bool suggestions: (optional) Whether to use spelling correction when processing the input. If spelling correction is used and **auto_correct** is `true`, any spelling corrections are automatically applied to the user input. If **auto_correct** is `false`, any suggested corrections are returned in the **output.spelling** property. This property overrides the value of the **spelling_suggestions** property in the workspace settings for the skill. :attr bool auto_correct: (optional) Whether to use autocorrection when processing the input. If this property is `true`, any corrections are automatically applied to the user input, and the original text is returned in the **output.spelling** property of the message response. This property overrides the value of the **spelling_auto_correct** property in the workspace settings for the skill. """ def __init__(self, *, suggestions: bool = None, auto_correct: bool = None) -> None: """ Initialize a MessageInputOptionsSpelling object. :param bool suggestions: (optional) Whether to use spelling correction when processing the input. If spelling correction is used and **auto_correct** is `true`, any spelling corrections are automatically applied to the user input. If **auto_correct** is `false`, any suggested corrections are returned in the **output.spelling** property. This property overrides the value of the **spelling_suggestions** property in the workspace settings for the skill. :param bool auto_correct: (optional) Whether to use autocorrection when processing the input. If this property is `true`, any corrections are automatically applied to the user input, and the original text is returned in the **output.spelling** property of the message response. This property overrides the value of the **spelling_auto_correct** property in the workspace settings for the skill. """ self.suggestions = suggestions self.auto_correct = auto_correct @classmethod def from_dict(cls, _dict: Dict) -> 'MessageInputOptionsSpelling': """Initialize a MessageInputOptionsSpelling object from a json dictionary.""" args = {} if 'suggestions' in _dict: args['suggestions'] = _dict.get('suggestions') if 'auto_correct' in _dict: args['auto_correct'] = _dict.get('auto_correct') return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a MessageInputOptionsSpelling 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, 'suggestions') and self.suggestions is not None: _dict['suggestions'] = self.suggestions if hasattr(self, 'auto_correct') and self.auto_correct is not None: _dict['auto_correct'] = self.auto_correct 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 MessageInputOptionsSpelling object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'MessageInputOptionsSpelling') -> 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: 'MessageInputOptionsSpelling') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class MessageInputOptionsStateless(): """ Optional properties that control how the assistant responds. :attr bool restart: (optional) Whether to restart dialog processing at the root of the dialog, regardless of any previously visited nodes. **Note:** This does not affect `turn_count` or any other context variables. :attr bool alternate_intents: (optional) Whether to return more than one intent. Set to `true` to return all matching intents. :attr MessageInputOptionsSpelling spelling: (optional) Spelling correction options for the message. Any options specified on an individual message override the settings configured for the skill. :attr bool debug: (optional) Whether to return additional diagnostic information. Set to `true` to return additional information in the `output.debug` property. """ def __init__(self, *, restart: bool = None, alternate_intents: bool = None, spelling: 'MessageInputOptionsSpelling' = None, debug: bool = None) -> None: """ Initialize a MessageInputOptionsStateless object. :param bool restart: (optional) Whether to restart dialog processing at the root of the dialog, regardless of any previously visited nodes. **Note:** This does not affect `turn_count` or any other context variables. :param bool alternate_intents: (optional) Whether to return more than one intent. Set to `true` to return all matching intents. :param MessageInputOptionsSpelling spelling: (optional) Spelling correction options for the message. Any options specified on an individual message override the settings configured for the skill. :param bool debug: (optional) Whether to return additional diagnostic information. Set to `true` to return additional information in the `output.debug` property. """ self.restart = restart self.alternate_intents = alternate_intents self.spelling = spelling self.debug = debug @classmethod def from_dict(cls, _dict: Dict) -> 'MessageInputOptionsStateless': """Initialize a MessageInputOptionsStateless object from a json dictionary.""" args = {} if 'restart' in _dict: args['restart'] = _dict.get('restart') if 'alternate_intents' in _dict: args['alternate_intents'] = _dict.get('alternate_intents') if 'spelling' in _dict: args['spelling'] = MessageInputOptionsSpelling.from_dict( _dict.get('spelling')) if 'debug' in _dict: args['debug'] = _dict.get('debug') return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a MessageInputOptionsStateless 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, 'restart') and self.restart is not None: _dict['restart'] = self.restart if hasattr(self, 'alternate_intents') and self.alternate_intents is not None: _dict['alternate_intents'] = self.alternate_intents if hasattr(self, 'spelling') and self.spelling is not None: _dict['spelling'] = self.spelling.to_dict() if hasattr(self, 'debug') and self.debug is not None: _dict['debug'] = self.debug 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 MessageInputOptionsStateless object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'MessageInputOptionsStateless') -> 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: 'MessageInputOptionsStateless') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class MessageInputStateless(): """ An input object that includes the input text. :attr str message_type: (optional) The type of the message: - `text`: The user input is processed normally by the assistant. - `search`: Only search results are returned. (Any dialog or actions skill is bypassed.) **Note:** A `search` message results in an error if no search skill is configured for the assistant. :attr str text: (optional) The text of the user input. This string cannot contain carriage return, newline, or tab characters. :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 str suggestion_id: (optional) For internal use only. :attr List[MessageInputAttachment] attachments: (optional) An array of multimedia attachments to be sent with the message. **Note:** Attachments are not processed by the assistant itself, but can be sent to external services by webhooks. :attr MessageInputOptionsStateless options: (optional) Optional properties that control how the assistant responds. """ def __init__(self, *, message_type: str = None, text: str = None, intents: List['RuntimeIntent'] = None, entities: List['RuntimeEntity'] = None, suggestion_id: str = None, attachments: List['MessageInputAttachment'] = None, options: 'MessageInputOptionsStateless' = None) -> None: """ Initialize a MessageInputStateless object. :param str message_type: (optional) The type of the message: - `text`: The user input is processed normally by the assistant. - `search`: Only search results are returned. (Any dialog or actions skill is bypassed.) **Note:** A `search` message results in an error if no search skill is configured for the assistant. :param str text: (optional) The text of the user input. This string cannot contain carriage return, newline, or tab characters. :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 str suggestion_id: (optional) For internal use only. :param List[MessageInputAttachment] attachments: (optional) An array of multimedia attachments to be sent with the message. **Note:** Attachments are not processed by the assistant itself, but can be sent to external services by webhooks. :param MessageInputOptionsStateless options: (optional) Optional properties that control how the assistant responds. """ self.message_type = message_type self.text = text self.intents = intents self.entities = entities self.suggestion_id = suggestion_id self.attachments = attachments self.options = options @classmethod def from_dict(cls, _dict: Dict) -> 'MessageInputStateless': """Initialize a MessageInputStateless object from a json dictionary.""" args = {} if 'message_type' in _dict: args['message_type'] = _dict.get('message_type') if 'text' in _dict: args['text'] = _dict.get('text') 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 'suggestion_id' in _dict: args['suggestion_id'] = _dict.get('suggestion_id') if 'attachments' in _dict: args['attachments'] = [ MessageInputAttachment.from_dict(x) for x in _dict.get('attachments') ] if 'options' in _dict: args['options'] = MessageInputOptionsStateless.from_dict( _dict.get('options')) return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a MessageInputStateless 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_type') and self.message_type is not None: _dict['message_type'] = self.message_type if hasattr(self, 'text') and self.text is not None: _dict['text'] = self.text 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, 'suggestion_id') and self.suggestion_id is not None: _dict['suggestion_id'] = self.suggestion_id if hasattr(self, 'attachments') and self.attachments is not None: _dict['attachments'] = [x.to_dict() for x in self.attachments] if hasattr(self, 'options') and self.options is not None: _dict['options'] = self.options.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 MessageInputStateless object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'MessageInputStateless') -> 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: 'MessageInputStateless') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class MessageTypeEnum(str, Enum): """ The type of the message: - `text`: The user input is processed normally by the assistant. - `search`: Only search results are returned. (Any dialog or actions skill is bypassed.) **Note:** A `search` message results in an error if no search skill is configured for the assistant. """ TEXT = 'text' SEARCH = 'search' class MessageOutput(): """ Assistant output to be rendered or processed by the client. :attr List[RuntimeResponseGeneric] generic: (optional) Output intended for any channel. It is the responsibility of the client application to implement the supported response types. :attr List[RuntimeIntent] intents: (optional) An array of intents recognized in the user input, sorted in descending order of confidence. :attr List[RuntimeEntity] entities: (optional) An array of entities identified in the user input. :attr List[DialogNodeAction] actions: (optional) An array of objects describing any actions requested by the dialog node. :attr MessageOutputDebug debug: (optional) Additional detailed information about a message response and how it was generated. :attr dict user_defined: (optional) An object containing any custom properties included in the response. This object includes any arbitrary properties defined in the dialog JSON editor as part of the dialog node output. :attr MessageOutputSpelling spelling: (optional) Properties describing any spelling corrections in the user input that was received. """ def __init__(self, *, generic: List['RuntimeResponseGeneric'] = None, intents: List['RuntimeIntent'] = None, entities: List['RuntimeEntity'] = None, actions: List['DialogNodeAction'] = None, debug: 'MessageOutputDebug' = None, user_defined: dict = None, spelling: 'MessageOutputSpelling' = None) -> None: """ Initialize a MessageOutput object. :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 List[RuntimeIntent] intents: (optional) An array of intents recognized in the user input, sorted in descending order of confidence. :param List[RuntimeEntity] entities: (optional) An array of entities identified in the user input. :param List[DialogNodeAction] actions: (optional) An array of objects describing any actions requested by the dialog node. :param MessageOutputDebug debug: (optional) Additional detailed information about a message response and how it was generated. :param dict user_defined: (optional) An object containing any custom properties included in the response. This object includes any arbitrary properties defined in the dialog JSON editor as part of the dialog node output. :param MessageOutputSpelling spelling: (optional) Properties describing any spelling corrections in the user input that was received. """ self.generic = generic self.intents = intents self.entities = entities self.actions = actions self.debug = debug self.user_defined = user_defined self.spelling = spelling @classmethod def from_dict(cls, _dict: Dict) -> 'MessageOutput': """Initialize a MessageOutput object from a json dictionary.""" args = {} if 'generic' in _dict: args['generic'] = [ RuntimeResponseGeneric.from_dict(x) for x in _dict.get('generic') ] 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 'actions' in _dict: args['actions'] = [ DialogNodeAction.from_dict(x) for x in _dict.get('actions') ] if 'debug' in _dict: args['debug'] = MessageOutputDebug.from_dict(_dict.get('debug')) if 'user_defined' in _dict: args['user_defined'] = _dict.get('user_defined') if 'spelling' in _dict: args['spelling'] = MessageOutputSpelling.from_dict( _dict.get('spelling')) return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a MessageOutput 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, '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, 'actions') and self.actions is not None: _dict['actions'] = [x.to_dict() for x in self.actions] if hasattr(self, 'debug') and self.debug is not None: _dict['debug'] = self.debug.to_dict() if hasattr(self, 'user_defined') and self.user_defined is not None: _dict['user_defined'] = self.user_defined if hasattr(self, 'spelling') and self.spelling is not None: _dict['spelling'] = self.spelling.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 MessageOutput object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'MessageOutput') -> 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: 'MessageOutput') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class MessageOutputDebug(): """ Additional detailed information about a message response and how it was generated. :attr List[DialogNodeVisited] nodes_visited: (optional) An array of objects containing detailed diagnostic information about dialog nodes that were visited during processing of the input message. :attr List[DialogLogMessage] log_messages: (optional) An array of up to 50 messages logged with the request. :attr bool branch_exited: (optional) Assistant sets this to true when this message response concludes or interrupts a dialog. :attr str branch_exited_reason: (optional) When `branch_exited` is set to `true` by the assistant, the `branch_exited_reason` specifies whether the dialog completed by itself or got interrupted. :attr List[MessageOutputDebugTurnEvent] turn_events: (optional) An array of objects containing detailed diagnostic information about dialog nodes and actions that were visited during processing of the input message. This property is present only if the assistant has an actions skill. """ def __init__( self, *, nodes_visited: List['DialogNodeVisited'] = None, log_messages: List['DialogLogMessage'] = None, branch_exited: bool = None, branch_exited_reason: str = None, turn_events: List['MessageOutputDebugTurnEvent'] = None) -> None: """ Initialize a MessageOutputDebug object. :param List[DialogNodeVisited] nodes_visited: (optional) An array of objects containing detailed diagnostic information about dialog nodes that were visited during processing of the input message. :param List[DialogLogMessage] log_messages: (optional) An array of up to 50 messages logged with the request. :param bool branch_exited: (optional) Assistant sets this to true when this message response concludes or interrupts a dialog. :param str branch_exited_reason: (optional) When `branch_exited` is set to `true` by the assistant, the `branch_exited_reason` specifies whether the dialog completed by itself or got interrupted. :param List[MessageOutputDebugTurnEvent] turn_events: (optional) An array of objects containing detailed diagnostic information about dialog nodes and actions that were visited during processing of the input message. This property is present only if the assistant has an actions skill. """ self.nodes_visited = nodes_visited self.log_messages = log_messages self.branch_exited = branch_exited self.branch_exited_reason = branch_exited_reason self.turn_events = turn_events @classmethod def from_dict(cls, _dict: Dict) -> 'MessageOutputDebug': """Initialize a MessageOutputDebug object from a json dictionary.""" args = {} if 'nodes_visited' in _dict: args['nodes_visited'] = [ DialogNodeVisited.from_dict(x) for x in _dict.get('nodes_visited') ] if 'log_messages' in _dict: args['log_messages'] = [ DialogLogMessage.from_dict(x) for x in _dict.get('log_messages') ] if 'branch_exited' in _dict: args['branch_exited'] = _dict.get('branch_exited') if 'branch_exited_reason' in _dict: args['branch_exited_reason'] = _dict.get('branch_exited_reason') if 'turn_events' in _dict: args['turn_events'] = [ MessageOutputDebugTurnEvent.from_dict(x) for x in _dict.get('turn_events') ] return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a MessageOutputDebug 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'] = [x.to_dict() for x in self.nodes_visited] 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, 'branch_exited') and self.branch_exited is not None: _dict['branch_exited'] = self.branch_exited if hasattr(self, 'branch_exited_reason' ) and self.branch_exited_reason is not None: _dict['branch_exited_reason'] = self.branch_exited_reason if hasattr(self, 'turn_events') and self.turn_events is not None: _dict['turn_events'] = [x.to_dict() for x in self.turn_events] 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 MessageOutputDebug object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'MessageOutputDebug') -> 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: 'MessageOutputDebug') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class BranchExitedReasonEnum(str, Enum): """ When `branch_exited` is set to `true` by the assistant, the `branch_exited_reason` specifies whether the dialog completed by itself or got interrupted. """ COMPLETED = 'completed' FALLBACK = 'fallback' class MessageOutputDebugTurnEvent(): """ MessageOutputDebugTurnEvent. """ def __init__(self) -> None: """ Initialize a MessageOutputDebugTurnEvent object. """ msg = "Cannot instantiate base class. Instead, instantiate one of the defined subclasses: {0}".format( ", ".join([ 'MessageOutputDebugTurnEventTurnEventActionVisited', 'MessageOutputDebugTurnEventTurnEventActionFinished', 'MessageOutputDebugTurnEventTurnEventStepVisited', 'MessageOutputDebugTurnEventTurnEventStepAnswered', 'MessageOutputDebugTurnEventTurnEventHandlerVisited', 'MessageOutputDebugTurnEventTurnEventCallout', 'MessageOutputDebugTurnEventTurnEventSearch', 'MessageOutputDebugTurnEventTurnEventNodeVisited' ])) raise Exception(msg) @classmethod def from_dict(cls, _dict: Dict) -> 'MessageOutputDebugTurnEvent': """Initialize a MessageOutputDebugTurnEvent 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 'MessageOutputDebugTurnEvent'. " + "The discriminator value should map to a valid subclass: {1}" ).format(", ".join([ 'MessageOutputDebugTurnEventTurnEventActionVisited', 'MessageOutputDebugTurnEventTurnEventActionFinished', 'MessageOutputDebugTurnEventTurnEventStepVisited', 'MessageOutputDebugTurnEventTurnEventStepAnswered', 'MessageOutputDebugTurnEventTurnEventHandlerVisited', 'MessageOutputDebugTurnEventTurnEventCallout', 'MessageOutputDebugTurnEventTurnEventSearch', 'MessageOutputDebugTurnEventTurnEventNodeVisited' ])) raise Exception(msg) @classmethod def _from_dict(cls, _dict: Dict): """Initialize a MessageOutputDebugTurnEvent object from a json dictionary.""" return cls.from_dict(_dict) @classmethod def _get_class_by_discriminator(cls, _dict: Dict) -> object: mapping = {} mapping[ 'action_visited'] = 'MessageOutputDebugTurnEventTurnEventActionVisited' mapping[ 'action_finished'] = 'MessageOutputDebugTurnEventTurnEventActionFinished' mapping[ 'step_visited'] = 'MessageOutputDebugTurnEventTurnEventStepVisited' mapping[ 'step_answered'] = 'MessageOutputDebugTurnEventTurnEventStepAnswered' mapping[ 'handler_visited'] = 'MessageOutputDebugTurnEventTurnEventHandlerVisited' mapping['callout'] = 'MessageOutputDebugTurnEventTurnEventCallout' mapping['search'] = 'MessageOutputDebugTurnEventTurnEventSearch' mapping[ 'node_visited'] = 'MessageOutputDebugTurnEventTurnEventNodeVisited' disc_value = _dict.get('event') if disc_value is None: raise ValueError( 'Discriminator property \'event\' not found in MessageOutputDebugTurnEvent 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 MessageOutputSpelling(): """ Properties describing any spelling corrections in the user input that was received. :attr str text: (optional) The user input text that was used to generate the response. If spelling autocorrection is enabled, this text reflects any spelling corrections that were applied. :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. :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. """ def __init__(self, *, text: str = None, original_text: str = None, suggested_text: str = None) -> None: """ Initialize a MessageOutputSpelling object. :param str text: (optional) The user input text that was used to generate the response. If spelling autocorrection is enabled, this text reflects any spelling corrections that were applied. :param str original_text: (optional) The original user input text. This property is returned only if autocorrection is enabled and the user input was corrected. :param 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. """ self.text = text self.original_text = original_text self.suggested_text = suggested_text @classmethod def from_dict(cls, _dict: Dict) -> 'MessageOutputSpelling': """Initialize a MessageOutputSpelling object from a json dictionary.""" args = {} if 'text' in _dict: args['text'] = _dict.get('text') if 'original_text' in _dict: args['original_text'] = _dict.get('original_text') if 'suggested_text' in _dict: args['suggested_text'] = _dict.get('suggested_text') return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a MessageOutputSpelling 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, 'original_text') and self.original_text is not None: _dict['original_text'] = self.original_text if hasattr(self, 'suggested_text') and self.suggested_text is not None: _dict['suggested_text'] = self.suggested_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 MessageOutputSpelling object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'MessageOutputSpelling') -> 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: 'MessageOutputSpelling') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class MessageRequest(): """ A stateful message request formatted for the Watson Assistant service. :attr MessageInput input: (optional) An input object that includes the input text. :attr MessageContext context: (optional) Context data for the conversation. You can use this property to set or modify context variables, which can also be accessed by dialog nodes. The context is stored by the assistant on a per-session basis. **Note:** The total size of the context data stored for a stateful session cannot exceed 100KB. :attr str user_id: (optional) A string value that identifies the user who is interacting with the assistant. 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.global.session_id**. **Note:** This property is the same as the **user_id** property in the global system context. If **user_id** is specified in both locations, the value specified at the root is used. """ def __init__(self, *, input: 'MessageInput' = None, context: 'MessageContext' = None, user_id: str = None) -> None: """ Initialize a MessageRequest object. :param MessageInput input: (optional) An input object that includes the input text. :param MessageContext context: (optional) Context data for the conversation. You can use this property to set or modify context variables, which can also be accessed by dialog nodes. The context is stored by the assistant on a per-session basis. **Note:** The total size of the context data stored for a stateful session cannot exceed 100KB. :param str user_id: (optional) A string value that identifies the user who is interacting with the assistant. 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.global.session_id**. **Note:** This property is the same as the **user_id** property in the global system context. If **user_id** is specified in both locations, the value specified at the root is used. """ self.input = input self.context = context 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 'context' in _dict: args['context'] = MessageContext.from_dict(_dict.get('context')) 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, 'context') and self.context is not None: _dict['context'] = self.context.to_dict() 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(): """ A response from the Watson Assistant service. :attr MessageOutput output: Assistant output to be rendered or processed by the client. :attr MessageContext context: (optional) Context data for the conversation. You can use this property to access context variables. The context is stored by the assistant on a per-session basis. **Note:** The context is included in message responses only if **return_context**=`true` in the message request. Full context is always included in logs. :attr str user_id: A string value that identifies the user who is interacting with the assistant. 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.global.session_id**. **Note:** This property is the same as the **user_id** property in the global system context. """ def __init__(self, output: 'MessageOutput', user_id: str, *, context: 'MessageContext' = None) -> None: """ Initialize a MessageResponse object. :param MessageOutput output: Assistant output to be rendered or processed by the client. :param str user_id: A string value that identifies the user who is interacting with the assistant. 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.global.session_id**. **Note:** This property is the same as the **user_id** property in the global system context. :param MessageContext context: (optional) Context data for the conversation. You can use this property to access context variables. The context is stored by the assistant on a per-session basis. **Note:** The context is included in message responses only if **return_context**=`true` in the message request. Full context is always included in logs. """ self.output = output self.context = context self.user_id = user_id @classmethod def from_dict(cls, _dict: Dict) -> 'MessageResponse': """Initialize a MessageResponse object from a json dictionary.""" args = {} if 'output' in _dict: args['output'] = MessageOutput.from_dict(_dict.get('output')) else: raise ValueError( 'Required property \'output\' not present in MessageResponse JSON' ) if 'context' in _dict: args['context'] = MessageContext.from_dict(_dict.get('context')) 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, '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, '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 MessageResponseStateless(): """ A stateless response from the Watson Assistant service. :attr MessageOutput output: Assistant output to be rendered or processed by the client. :attr MessageContextStateless context: Context data for the conversation. You can use this property to access context variables. The context is not stored by the assistant; to maintain session state, include the context from the response in the next message. :attr str user_id: (optional) A string value that identifies the user who is interacting with the assistant. 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.global.session_id**. **Note:** This property is the same as the **user_id** property in the global system context. """ def __init__(self, output: 'MessageOutput', context: 'MessageContextStateless', *, user_id: str = None) -> None: """ Initialize a MessageResponseStateless object. :param MessageOutput output: Assistant output to be rendered or processed by the client. :param MessageContextStateless context: Context data for the conversation. You can use this property to access context variables. The context is not stored by the assistant; to maintain session state, include the context from the response in the next message. :param str user_id: (optional) A string value that identifies the user who is interacting with the assistant. 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.global.session_id**. **Note:** This property is the same as the **user_id** property in the global system context. """ self.output = output self.context = context self.user_id = user_id @classmethod def from_dict(cls, _dict: Dict) -> 'MessageResponseStateless': """Initialize a MessageResponseStateless object from a json dictionary.""" args = {} if 'output' in _dict: args['output'] = MessageOutput.from_dict(_dict.get('output')) else: raise ValueError( 'Required property \'output\' not present in MessageResponseStateless JSON' ) if 'context' in _dict: args['context'] = MessageContextStateless.from_dict( _dict.get('context')) else: raise ValueError( 'Required property \'context\' not present in MessageResponseStateless JSON' ) if 'user_id' in _dict: args['user_id'] = _dict.get('user_id') return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a MessageResponseStateless 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'] = self.output.to_dict() if hasattr(self, 'context') and self.context is not None: _dict['context'] = self.context.to_dict() 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 MessageResponseStateless object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'MessageResponseStateless') -> 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: 'MessageResponseStateless') -> 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 Release(): """ Release. :attr str release: (optional) The name of the release. The name is the version number (an integer), returned as a string. :attr str description: (optional) The description of the release. :attr List[EnvironmentReference] environment_references: (optional) An array of objects describing the environments where this release has been deployed. :attr ReleaseContent content: (optional) An object describing the versionable content objects (such as skill snapshots) that are included in the release. :attr str status: (optional) The current status of the release: - **Available**: The release is available for deployment. - **Failed**: An asynchronous publish operation has failed. - **Processing**: An asynchronous publish operation has not yet completed. :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, *, release: str = None, description: str = None, environment_references: List['EnvironmentReference'] = None, content: 'ReleaseContent' = None, status: str = None, created: datetime = None, updated: datetime = None) -> None: """ Initialize a Release object. :param str release: (optional) The name of the release. The name is the version number (an integer), returned as a string. :param str description: (optional) The description of the release. :param ReleaseContent content: (optional) An object describing the versionable content objects (such as skill snapshots) that are included in the release. :param str status: (optional) The current status of the release: - **Available**: The release is available for deployment. - **Failed**: An asynchronous publish operation has failed. - **Processing**: An asynchronous publish operation has not yet completed. """ self.release = release self.description = description self.environment_references = environment_references self.content = content self.status = status self.created = created self.updated = updated @classmethod def from_dict(cls, _dict: Dict) -> 'Release': """Initialize a Release object from a json dictionary.""" args = {} if 'release' in _dict: args['release'] = _dict.get('release') if 'description' in _dict: args['description'] = _dict.get('description') if 'environment_references' in _dict: args['environment_references'] = [ EnvironmentReference.from_dict(x) for x in _dict.get('environment_references') ] if 'content' in _dict: args['content'] = ReleaseContent.from_dict(_dict.get('content')) if 'status' in _dict: args['status'] = _dict.get('status') 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 Release 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, 'release') and self.release is not None: _dict['release'] = self.release if hasattr(self, 'description') and self.description is not None: _dict['description'] = self.description if hasattr(self, 'environment_references') and getattr( self, 'environment_references') is not None: _dict['environment_references'] = [ x.to_dict() for x in getattr(self, 'environment_references') ] if hasattr(self, 'content') and self.content is not None: _dict['content'] = self.content.to_dict() if hasattr(self, 'status') and self.status is not None: _dict['status'] = self.status 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 Release object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'Release') -> 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: 'Release') -> 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 release: - **Available**: The release is available for deployment. - **Failed**: An asynchronous publish operation has failed. - **Processing**: An asynchronous publish operation has not yet completed. """ AVAILABLE = 'Available' FAILED = 'Failed' PROCESSING = 'Processing' class ReleaseCollection(): """ ReleaseCollection. :attr List[Release] releases: An array of objects describing the releases associated with an assistant. :attr Pagination pagination: The pagination data for the returned objects. """ def __init__(self, releases: List['Release'], pagination: 'Pagination') -> None: """ Initialize a ReleaseCollection object. :param List[Release] releases: An array of objects describing the releases associated with an assistant. :param Pagination pagination: The pagination data for the returned objects. """ self.releases = releases self.pagination = pagination @classmethod def from_dict(cls, _dict: Dict) -> 'ReleaseCollection': """Initialize a ReleaseCollection object from a json dictionary.""" args = {} if 'releases' in _dict: args['releases'] = [ Release.from_dict(x) for x in _dict.get('releases') ] else: raise ValueError( 'Required property \'releases\' not present in ReleaseCollection JSON' ) if 'pagination' in _dict: args['pagination'] = Pagination.from_dict(_dict.get('pagination')) else: raise ValueError( 'Required property \'pagination\' not present in ReleaseCollection JSON' ) return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a ReleaseCollection 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, 'releases') and self.releases is not None: _dict['releases'] = [x.to_dict() for x in self.releases] 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 ReleaseCollection object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'ReleaseCollection') -> 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: 'ReleaseCollection') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class ReleaseContent(): """ An object describing the versionable content objects (such as skill snapshots) that are included in the release. :attr List[ReleaseSkillReference] skills: (optional) The skill snapshots that are included in the release. """ def __init__(self, *, skills: List['ReleaseSkillReference'] = None) -> None: """ Initialize a ReleaseContent object. """ self.skills = skills @classmethod def from_dict(cls, _dict: Dict) -> 'ReleaseContent': """Initialize a ReleaseContent object from a json dictionary.""" args = {} if 'skills' in _dict: args['skills'] = [ ReleaseSkillReference.from_dict(x) for x in _dict.get('skills') ] return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a ReleaseContent 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, 'skills') and getattr(self, 'skills') is not None: _dict['skills'] = [x.to_dict() for x in getattr(self, 'skills')] 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 ReleaseContent object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'ReleaseContent') -> 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: 'ReleaseContent') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class ReleaseSkillReference(): """ ReleaseSkillReference. :attr str skill_id: (optional) The skill ID of the skill. :attr str type: (optional) The type of the skill. :attr str snapshot: (optional) The name of the snapshot (skill version) that is saved as part of the release (for example, `draft` or `1`). """ def __init__(self, *, skill_id: str = None, type: str = None, snapshot: str = None) -> None: """ Initialize a ReleaseSkillReference object. :param str skill_id: (optional) The skill ID of the skill. :param str type: (optional) The type of the skill. :param str snapshot: (optional) The name of the snapshot (skill version) that is saved as part of the release (for example, `draft` or `1`). """ self.skill_id = skill_id self.type = type self.snapshot = snapshot @classmethod def from_dict(cls, _dict: Dict) -> 'ReleaseSkillReference': """Initialize a ReleaseSkillReference object from a json dictionary.""" args = {} if 'skill_id' in _dict: args['skill_id'] = _dict.get('skill_id') if 'type' in _dict: args['type'] = _dict.get('type') if 'snapshot' in _dict: args['snapshot'] = _dict.get('snapshot') return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a ReleaseSkillReference 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, 'skill_id') and self.skill_id is not None: _dict['skill_id'] = self.skill_id if hasattr(self, 'type') and self.type is not None: _dict['type'] = self.type if hasattr(self, 'snapshot') and self.snapshot is not None: _dict['snapshot'] = self.snapshot 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 ReleaseSkillReference object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'ReleaseSkillReference') -> 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: 'ReleaseSkillReference') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class TypeEnum(str, Enum): """ The type of the skill. """ DIALOG = 'dialog' ACTION = 'action' SEARCH = 'search' 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 RuntimeEntity(): """ The entity value that was recognized in the user input. :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 term in the input text that was recognized as an entity value. :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. This property is included only if the new system entities are enabled for the skill. For more information about how the new system entities are interpreted, see the [documentation](https://cloud.ibm.com/docs/assistant?topic=assistant-beta-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 skill. :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 skill. :attr str skill: (optional) The skill that recognized the entity value. Currently, the only possible values are `main skill` for the dialog skill (if enabled) and `actions skill` for the actions skill. This property is present only if the assistant has both a dialog skill and an actions skill. """ 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, skill: str = None) -> None: """ Initialize a RuntimeEntity object. :param str entity: An entity detected in the input. :param str value: The term in the input text that was recognized as an entity value. :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. This property is included only if the new system entities are enabled for the skill. For more information about how the new system entities are interpreted, see the [documentation](https://cloud.ibm.com/docs/assistant?topic=assistant-beta-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 skill. :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 skill. :param str skill: (optional) The skill that recognized the entity value. Currently, the only possible values are `main skill` for the dialog skill (if enabled) and `actions skill` for the actions skill. This property is present only if the assistant has both a dialog skill and an actions skill. """ self.entity = entity self.location = location self.value = value self.confidence = confidence self.groups = groups self.interpretation = interpretation self.alternatives = alternatives self.role = role self.skill = skill @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')) if 'skill' in _dict: args['skill'] = _dict.get('skill') 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() if hasattr(self, 'skill') and self.skill is not None: _dict['skill'] = self.skill 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 skill. :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`. :attr str skill: (optional) The skill that identified the intent. Currently, the only possible values are `main skill` for the dialog skill (if enabled) and `actions skill` for the actions skill. This property is present only if the assistant has both a dialog skill and an actions skill. """ def __init__(self, intent: str, *, confidence: float = None, skill: str = 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`. :param str skill: (optional) The skill that identified the intent. Currently, the only possible values are `main skill` for the dialog skill (if enabled) and `actions skill` for the actions skill. This property is present only if the assistant has both a dialog skill and an actions skill. """ self.intent = intent self.confidence = confidence self.skill = skill @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') if 'skill' in _dict: args['skill'] = _dict.get('skill') 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 if hasattr(self, 'skill') and self.skill is not None: _dict['skill'] = self.skill 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', 'RuntimeResponseGenericRuntimeResponseTypeSearch', 'RuntimeResponseGenericRuntimeResponseTypeUserDefined', 'RuntimeResponseGenericRuntimeResponseTypeVideo', 'RuntimeResponseGenericRuntimeResponseTypeAudio', 'RuntimeResponseGenericRuntimeResponseTypeIframe', 'RuntimeResponseGenericRuntimeResponseTypeDate' ])) 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', 'RuntimeResponseGenericRuntimeResponseTypeSearch', 'RuntimeResponseGenericRuntimeResponseTypeUserDefined', 'RuntimeResponseGenericRuntimeResponseTypeVideo', 'RuntimeResponseGenericRuntimeResponseTypeAudio', 'RuntimeResponseGenericRuntimeResponseTypeIframe', 'RuntimeResponseGenericRuntimeResponseTypeDate' ])) 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['date'] = 'RuntimeResponseGenericRuntimeResponseTypeDate' mapping['iframe'] = 'RuntimeResponseGenericRuntimeResponseTypeIframe' mapping['image'] = 'RuntimeResponseGenericRuntimeResponseTypeImage' mapping['option'] = 'RuntimeResponseGenericRuntimeResponseTypeOption' mapping[ 'suggestion'] = 'RuntimeResponseGenericRuntimeResponseTypeSuggestion' mapping['pause'] = 'RuntimeResponseGenericRuntimeResponseTypePause' mapping['search'] = 'RuntimeResponseGenericRuntimeResponseTypeSearch' 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 SearchResult(): """ SearchResult. :attr str id: The unique identifier of the document in the Discovery service collection. This property is included in responses from search skills, which are available only to Plus or Enterprise plan users. :attr SearchResultMetadata result_metadata: An object containing search result metadata from the Discovery service. :attr str body: (optional) A description of the search result. This is taken from an abstract, summary, or highlight field in the Discovery service response, as specified in the search skill configuration. :attr str title: (optional) The title of the search result. This is taken from a title or name field in the Discovery service response, as specified in the search skill configuration. :attr str url: (optional) The URL of the original data object in its native data source. :attr SearchResultHighlight highlight: (optional) An object containing segments of text from search results with query-matching text highlighted using HTML `` tags. :attr List[SearchResultAnswer] answers: (optional) An array specifying segments of text within the result that were identified as direct answers to the search query. Currently, only the single answer with the highest confidence (if any) is returned. **Note:** This property uses the answer finding beta feature, and is available only if the search skill is connected to a Discovery v2 service instance. """ def __init__(self, id: str, result_metadata: 'SearchResultMetadata', *, body: str = None, title: str = None, url: str = None, highlight: 'SearchResultHighlight' = None, answers: List['SearchResultAnswer'] = None) -> None: """ Initialize a SearchResult object. :param str id: The unique identifier of the document in the Discovery service collection. This property is included in responses from search skills, which are available only to Plus or Enterprise plan users. :param SearchResultMetadata result_metadata: An object containing search result metadata from the Discovery service. :param str body: (optional) A description of the search result. This is taken from an abstract, summary, or highlight field in the Discovery service response, as specified in the search skill configuration. :param str title: (optional) The title of the search result. This is taken from a title or name field in the Discovery service response, as specified in the search skill configuration. :param str url: (optional) The URL of the original data object in its native data source. :param SearchResultHighlight highlight: (optional) An object containing segments of text from search results with query-matching text highlighted using HTML `` tags. :param List[SearchResultAnswer] answers: (optional) An array specifying segments of text within the result that were identified as direct answers to the search query. Currently, only the single answer with the highest confidence (if any) is returned. **Note:** This property uses the answer finding beta feature, and is available only if the search skill is connected to a Discovery v2 service instance. """ self.id = id self.result_metadata = result_metadata self.body = body self.title = title self.url = url self.highlight = highlight self.answers = answers @classmethod def from_dict(cls, _dict: Dict) -> 'SearchResult': """Initialize a SearchResult object from a json dictionary.""" args = {} if 'id' in _dict: args['id'] = _dict.get('id') else: raise ValueError( 'Required property \'id\' not present in SearchResult JSON') if 'result_metadata' in _dict: args['result_metadata'] = SearchResultMetadata.from_dict( _dict.get('result_metadata')) else: raise ValueError( 'Required property \'result_metadata\' not present in SearchResult JSON' ) if 'body' in _dict: args['body'] = _dict.get('body') if 'title' in _dict: args['title'] = _dict.get('title') if 'url' in _dict: args['url'] = _dict.get('url') if 'highlight' in _dict: args['highlight'] = SearchResultHighlight.from_dict( _dict.get('highlight')) if 'answers' in _dict: args['answers'] = [ SearchResultAnswer.from_dict(x) for x in _dict.get('answers') ] return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a SearchResult 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, 'id') and self.id is not None: _dict['id'] = self.id if hasattr(self, 'result_metadata') and self.result_metadata is not None: _dict['result_metadata'] = self.result_metadata.to_dict() if hasattr(self, 'body') and self.body is not None: _dict['body'] = self.body if hasattr(self, 'title') and self.title is not None: _dict['title'] = self.title if hasattr(self, 'url') and self.url is not None: _dict['url'] = self.url if hasattr(self, 'highlight') and self.highlight is not None: _dict['highlight'] = self.highlight.to_dict() if hasattr(self, 'answers') and self.answers is not None: _dict['answers'] = [x.to_dict() for x in self.answers] 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 SearchResult object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'SearchResult') -> 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: 'SearchResult') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class SearchResultAnswer(): """ An object specifing a segment of text that was identified as a direct answer to the search query. :attr str text: The text of the answer. :attr float confidence: The confidence score for the answer, as returned by the Discovery service. """ def __init__(self, text: str, confidence: float) -> None: """ Initialize a SearchResultAnswer object. :param str text: The text of the answer. :param float confidence: The confidence score for the answer, as returned by the Discovery service. """ self.text = text self.confidence = confidence @classmethod def from_dict(cls, _dict: Dict) -> 'SearchResultAnswer': """Initialize a SearchResultAnswer object from a json dictionary.""" args = {} if 'text' in _dict: args['text'] = _dict.get('text') else: raise ValueError( 'Required property \'text\' not present in SearchResultAnswer JSON' ) if 'confidence' in _dict: args['confidence'] = _dict.get('confidence') else: raise ValueError( 'Required property \'confidence\' not present in SearchResultAnswer JSON' ) return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a SearchResultAnswer 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, '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 SearchResultAnswer object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'SearchResultAnswer') -> 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: 'SearchResultAnswer') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class SearchResultHighlight(): """ An object containing segments of text from search results with query-matching text highlighted using HTML `` tags. :attr List[str] body: (optional) An array of strings containing segments taken from body text in the search results, with query-matching substrings highlighted. :attr List[str] title: (optional) An array of strings containing segments taken from title text in the search results, with query-matching substrings highlighted. :attr List[str] url: (optional) An array of strings containing segments taken from URLs in the search results, with query-matching substrings highlighted. """ # The set of defined properties for the class _properties = frozenset(['body', 'title', 'url']) def __init__(self, *, body: List[str] = None, title: List[str] = None, url: List[str] = None, **kwargs) -> None: """ Initialize a SearchResultHighlight object. :param List[str] body: (optional) An array of strings containing segments taken from body text in the search results, with query-matching substrings highlighted. :param List[str] title: (optional) An array of strings containing segments taken from title text in the search results, with query-matching substrings highlighted. :param List[str] url: (optional) An array of strings containing segments taken from URLs in the search results, with query-matching substrings highlighted. :param **kwargs: (optional) Any additional properties. """ self.body = body self.title = title self.url = url for _key, _value in kwargs.items(): setattr(self, _key, _value) @classmethod def from_dict(cls, _dict: Dict) -> 'SearchResultHighlight': """Initialize a SearchResultHighlight object from a json dictionary.""" args = {} if 'body' in _dict: args['body'] = _dict.get('body') if 'title' in _dict: args['title'] = _dict.get('title') if 'url' in _dict: args['url'] = _dict.get('url') 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 SearchResultHighlight 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, 'body') and self.body is not None: _dict['body'] = self.body if hasattr(self, 'title') and self.title is not None: _dict['title'] = self.title if hasattr(self, 'url') and self.url is not None: _dict['url'] = self.url for _key in [ k for k in vars(self).keys() if k not in SearchResultHighlight._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 SearchResultHighlight""" _dict = {} for _key in [ k for k in vars(self).keys() if k not in SearchResultHighlight._properties ]: _dict[_key] = getattr(self, _key) return _dict def set_properties(self, _dict: dict): """Set a dictionary of arbitrary properties to this instance of SearchResultHighlight""" for _key in [ k for k in vars(self).keys() if k not in SearchResultHighlight._properties ]: delattr(self, _key) for _key, _value in _dict.items(): if _key not in SearchResultHighlight._properties: setattr(self, _key, _value) def __str__(self) -> str: """Return a `str` version of this SearchResultHighlight object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'SearchResultHighlight') -> 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: 'SearchResultHighlight') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class SearchResultMetadata(): """ An object containing search result metadata from the Discovery service. :attr float confidence: (optional) The confidence score for the given result, as returned by the Discovery service. :attr float score: (optional) An unbounded measure of the relevance of a particular result, dependent on the query and matching document. A higher score indicates a greater match to the query parameters. """ def __init__(self, *, confidence: float = None, score: float = None) -> None: """ Initialize a SearchResultMetadata object. :param float confidence: (optional) The confidence score for the given result, as returned by the Discovery service. :param float score: (optional) An unbounded measure of the relevance of a particular result, dependent on the query and matching document. A higher score indicates a greater match to the query parameters. """ self.confidence = confidence self.score = score @classmethod def from_dict(cls, _dict: Dict) -> 'SearchResultMetadata': """Initialize a SearchResultMetadata object from a json dictionary.""" args = {} if 'confidence' in _dict: args['confidence'] = _dict.get('confidence') if 'score' in _dict: args['score'] = _dict.get('score') return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a SearchResultMetadata 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, 'confidence') and self.confidence is not None: _dict['confidence'] = self.confidence if hasattr(self, 'score') and self.score is not None: _dict['score'] = self.score 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 SearchResultMetadata object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'SearchResultMetadata') -> 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: 'SearchResultMetadata') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class SessionResponse(): """ SessionResponse. :attr str session_id: The session ID. """ def __init__(self, session_id: str) -> None: """ Initialize a SessionResponse object. :param str session_id: The session ID. """ self.session_id = session_id @classmethod def from_dict(cls, _dict: Dict) -> 'SessionResponse': """Initialize a SessionResponse object from a json dictionary.""" args = {} if 'session_id' in _dict: args['session_id'] = _dict.get('session_id') else: raise ValueError( 'Required property \'session_id\' not present in SessionResponse JSON' ) return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a SessionResponse 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, 'session_id') and self.session_id is not None: _dict['session_id'] = self.session_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 SessionResponse object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'SessionResponse') -> 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: 'SessionResponse') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class SkillReference(): """ SkillReference. :attr str skill_id: (optional) The skill ID of the skill. :attr str type: (optional) The type of the skill. :attr bool disabled: (optional) Whether the skill is disabled. A disabled skill in the draft environment does not handle any messages at run time, and it is not included in saved releases. :attr str snapshot: (optional) The name of the snapshot (skill version) that is saved as part of the release (for example, `draft` or `1`). :attr str skill_reference: (optional) The type of skill identified by the skill reference. The possible values are `main skill` (for a dialog skill), `actions skill`, and `search skill`. """ def __init__(self, *, skill_id: str = None, type: str = None, disabled: bool = None, snapshot: str = None, skill_reference: str = None) -> None: """ Initialize a SkillReference object. :param str skill_id: (optional) The skill ID of the skill. :param str type: (optional) The type of the skill. :param bool disabled: (optional) Whether the skill is disabled. A disabled skill in the draft environment does not handle any messages at run time, and it is not included in saved releases. :param str snapshot: (optional) The name of the snapshot (skill version) that is saved as part of the release (for example, `draft` or `1`). :param str skill_reference: (optional) The type of skill identified by the skill reference. The possible values are `main skill` (for a dialog skill), `actions skill`, and `search skill`. """ self.skill_id = skill_id self.type = type self.disabled = disabled self.snapshot = snapshot self.skill_reference = skill_reference @classmethod def from_dict(cls, _dict: Dict) -> 'SkillReference': """Initialize a SkillReference object from a json dictionary.""" args = {} if 'skill_id' in _dict: args['skill_id'] = _dict.get('skill_id') if 'type' in _dict: args['type'] = _dict.get('type') if 'disabled' in _dict: args['disabled'] = _dict.get('disabled') if 'snapshot' in _dict: args['snapshot'] = _dict.get('snapshot') if 'skill_reference' in _dict: args['skill_reference'] = _dict.get('skill_reference') return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a SkillReference 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, 'skill_id') and self.skill_id is not None: _dict['skill_id'] = self.skill_id if hasattr(self, 'type') and self.type is not None: _dict['type'] = self.type if hasattr(self, 'disabled') and self.disabled is not None: _dict['disabled'] = self.disabled if hasattr(self, 'snapshot') and self.snapshot is not None: _dict['snapshot'] = self.snapshot if hasattr(self, 'skill_reference') and self.skill_reference is not None: _dict['skill_reference'] = self.skill_reference 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 SkillReference object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'SkillReference') -> 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: 'SkillReference') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class TypeEnum(str, Enum): """ The type of the skill. """ DIALOG = 'dialog' ACTION = 'action' SEARCH = 'search' class TurnEventActionSource(): """ TurnEventActionSource. :attr str type: (optional) The type of turn event. :attr str action: (optional) An action that was visited during processing of the message. :attr str action_title: (optional) The title of the action. :attr str condition: (optional) The condition that triggered the dialog node. """ def __init__(self, *, type: str = None, action: str = None, action_title: str = None, condition: str = None) -> None: """ Initialize a TurnEventActionSource object. :param str type: (optional) The type of turn event. :param str action: (optional) An action that was visited during processing of the message. :param str action_title: (optional) The title of the action. :param str condition: (optional) The condition that triggered the dialog node. """ self.type = type self.action = action self.action_title = action_title self.condition = condition @classmethod def from_dict(cls, _dict: Dict) -> 'TurnEventActionSource': """Initialize a TurnEventActionSource object from a json dictionary.""" args = {} if 'type' in _dict: args['type'] = _dict.get('type') if 'action' in _dict: args['action'] = _dict.get('action') if 'action_title' in _dict: args['action_title'] = _dict.get('action_title') if 'condition' in _dict: args['condition'] = _dict.get('condition') return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a TurnEventActionSource 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, 'action') and self.action is not None: _dict['action'] = self.action if hasattr(self, 'action_title') and self.action_title is not None: _dict['action_title'] = self.action_title if hasattr(self, 'condition') and self.condition is not None: _dict['condition'] = self.condition 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 TurnEventActionSource object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'TurnEventActionSource') -> 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: 'TurnEventActionSource') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class TypeEnum(str, Enum): """ The type of turn event. """ ACTION = 'action' class TurnEventCalloutCallout(): """ TurnEventCalloutCallout. :attr str type: (optional) callout type. :attr dict internal: (optional) For internal use only. """ def __init__(self, *, type: str = None, internal: dict = None) -> None: """ Initialize a TurnEventCalloutCallout object. :param str type: (optional) callout type. :param dict internal: (optional) For internal use only. """ self.type = type self.internal = internal @classmethod def from_dict(cls, _dict: Dict) -> 'TurnEventCalloutCallout': """Initialize a TurnEventCalloutCallout object from a json dictionary.""" args = {} if 'type' in _dict: args['type'] = _dict.get('type') if 'internal' in _dict: args['internal'] = _dict.get('internal') return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a TurnEventCalloutCallout 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, 'internal') and self.internal is not None: _dict['internal'] = self.internal 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 TurnEventCalloutCallout object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'TurnEventCalloutCallout') -> 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: 'TurnEventCalloutCallout') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class TypeEnum(str, Enum): """ callout type. """ INTEGRATION_INTERACTION = 'integration_interaction' class TurnEventCalloutError(): """ TurnEventCalloutError. :attr str message: (optional) Any error message returned by a failed call to an external service. """ def __init__(self, *, message: str = None) -> None: """ Initialize a TurnEventCalloutError object. :param str message: (optional) Any error message returned by a failed call to an external service. """ self.message = message @classmethod def from_dict(cls, _dict: Dict) -> 'TurnEventCalloutError': """Initialize a TurnEventCalloutError 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 TurnEventCalloutError 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 TurnEventCalloutError object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'TurnEventCalloutError') -> 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: 'TurnEventCalloutError') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class TurnEventNodeSource(): """ TurnEventNodeSource. :attr str type: (optional) The type of turn event. :attr str dialog_node: (optional) A dialog node that was visited during processing of the input message. :attr str title: (optional) The title of the dialog node. :attr str condition: (optional) The condition that triggered the dialog node. """ def __init__(self, *, type: str = None, dialog_node: str = None, title: str = None, condition: str = None) -> None: """ Initialize a TurnEventNodeSource object. :param str type: (optional) The type of turn event. :param str dialog_node: (optional) A dialog node that was visited during processing of the input message. :param str title: (optional) The title of the dialog node. :param str condition: (optional) The condition that triggered the dialog node. """ self.type = type self.dialog_node = dialog_node self.title = title self.condition = condition @classmethod def from_dict(cls, _dict: Dict) -> 'TurnEventNodeSource': """Initialize a TurnEventNodeSource 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') if 'title' in _dict: args['title'] = _dict.get('title') if 'condition' in _dict: args['condition'] = _dict.get('condition') return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a TurnEventNodeSource 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 if hasattr(self, 'title') and self.title is not None: _dict['title'] = self.title if hasattr(self, 'condition') and self.condition is not None: _dict['condition'] = self.condition 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 TurnEventNodeSource object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'TurnEventNodeSource') -> 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: 'TurnEventNodeSource') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class TypeEnum(str, Enum): """ The type of turn event. """ DIALOG_NODE = 'dialog_node' class TurnEventSearchError(): """ TurnEventSearchError. :attr str message: (optional) Any error message returned by a failed call to a search skill. """ def __init__(self, *, message: str = None) -> None: """ Initialize a TurnEventSearchError object. :param str message: (optional) Any error message returned by a failed call to a search skill. """ self.message = message @classmethod def from_dict(cls, _dict: Dict) -> 'TurnEventSearchError': """Initialize a TurnEventSearchError 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 TurnEventSearchError 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 TurnEventSearchError object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'TurnEventSearchError') -> 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: 'TurnEventSearchError') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class LogMessageSourceAction(LogMessageSource): """ An object that identifies the dialog element that generated the error message. :attr str type: A string that indicates the type of dialog element that generated the error message. :attr str action: The unique identifier of the action that generated the error message. """ def __init__(self, type: str, action: str) -> None: """ Initialize a LogMessageSourceAction object. :param str type: A string that indicates the type of dialog element that generated the error message. :param str action: The unique identifier of the action that generated the error message. """ # pylint: disable=super-init-not-called self.type = type self.action = action @classmethod def from_dict(cls, _dict: Dict) -> 'LogMessageSourceAction': """Initialize a LogMessageSourceAction object from a json dictionary.""" args = {} if 'type' in _dict: args['type'] = _dict.get('type') else: raise ValueError( 'Required property \'type\' not present in LogMessageSourceAction JSON' ) if 'action' in _dict: args['action'] = _dict.get('action') else: raise ValueError( 'Required property \'action\' not present in LogMessageSourceAction JSON' ) return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a LogMessageSourceAction 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, 'action') and self.action is not None: _dict['action'] = self.action 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 LogMessageSourceAction object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'LogMessageSourceAction') -> 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: 'LogMessageSourceAction') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class LogMessageSourceDialogNode(LogMessageSource): """ An object that identifies the dialog element that generated the error message. :attr str type: A string that indicates the type of dialog element that generated the error message. :attr str dialog_node: The unique identifier of the dialog node that generated the error message. """ def __init__(self, type: str, dialog_node: str) -> None: """ Initialize a LogMessageSourceDialogNode object. :param str type: A string that indicates the type of dialog element that generated the error message. :param str dialog_node: The unique identifier of the dialog node that generated the error message. """ # pylint: disable=super-init-not-called self.type = type self.dialog_node = dialog_node @classmethod def from_dict(cls, _dict: Dict) -> 'LogMessageSourceDialogNode': """Initialize a LogMessageSourceDialogNode object from a json dictionary.""" args = {} if 'type' in _dict: args['type'] = _dict.get('type') else: raise ValueError( 'Required property \'type\' not present in LogMessageSourceDialogNode JSON' ) if 'dialog_node' in _dict: args['dialog_node'] = _dict.get('dialog_node') else: raise ValueError( 'Required property \'dialog_node\' not present in LogMessageSourceDialogNode JSON' ) return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a LogMessageSourceDialogNode 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 LogMessageSourceDialogNode object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'LogMessageSourceDialogNode') -> 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: 'LogMessageSourceDialogNode') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class LogMessageSourceHandler(LogMessageSource): """ An object that identifies the dialog element that generated the error message. :attr str type: A string that indicates the type of dialog element that generated the error message. :attr str action: The unique identifier of the action that generated the error message. :attr str step: (optional) The unique identifier of the step that generated the error message. :attr str handler: The unique identifier of the handler that generated the error message. """ def __init__(self, type: str, action: str, handler: str, *, step: str = None) -> None: """ Initialize a LogMessageSourceHandler object. :param str type: A string that indicates the type of dialog element that generated the error message. :param str action: The unique identifier of the action that generated the error message. :param str handler: The unique identifier of the handler that generated the error message. :param str step: (optional) The unique identifier of the step that generated the error message. """ # pylint: disable=super-init-not-called self.type = type self.action = action self.step = step self.handler = handler @classmethod def from_dict(cls, _dict: Dict) -> 'LogMessageSourceHandler': """Initialize a LogMessageSourceHandler object from a json dictionary.""" args = {} if 'type' in _dict: args['type'] = _dict.get('type') else: raise ValueError( 'Required property \'type\' not present in LogMessageSourceHandler JSON' ) if 'action' in _dict: args['action'] = _dict.get('action') else: raise ValueError( 'Required property \'action\' not present in LogMessageSourceHandler JSON' ) if 'step' in _dict: args['step'] = _dict.get('step') if 'handler' in _dict: args['handler'] = _dict.get('handler') else: raise ValueError( 'Required property \'handler\' not present in LogMessageSourceHandler JSON' ) return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a LogMessageSourceHandler 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, 'action') and self.action is not None: _dict['action'] = self.action if hasattr(self, 'step') and self.step is not None: _dict['step'] = self.step if hasattr(self, 'handler') and self.handler is not None: _dict['handler'] = self.handler 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 LogMessageSourceHandler object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'LogMessageSourceHandler') -> 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: 'LogMessageSourceHandler') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class LogMessageSourceStep(LogMessageSource): """ An object that identifies the dialog element that generated the error message. :attr str type: A string that indicates the type of dialog element that generated the error message. :attr str action: The unique identifier of the action that generated the error message. :attr str step: The unique identifier of the step that generated the error message. """ def __init__(self, type: str, action: str, step: str) -> None: """ Initialize a LogMessageSourceStep object. :param str type: A string that indicates the type of dialog element that generated the error message. :param str action: The unique identifier of the action that generated the error message. :param str step: The unique identifier of the step that generated the error message. """ # pylint: disable=super-init-not-called self.type = type self.action = action self.step = step @classmethod def from_dict(cls, _dict: Dict) -> 'LogMessageSourceStep': """Initialize a LogMessageSourceStep object from a json dictionary.""" args = {} if 'type' in _dict: args['type'] = _dict.get('type') else: raise ValueError( 'Required property \'type\' not present in LogMessageSourceStep JSON' ) if 'action' in _dict: args['action'] = _dict.get('action') else: raise ValueError( 'Required property \'action\' not present in LogMessageSourceStep JSON' ) if 'step' in _dict: args['step'] = _dict.get('step') else: raise ValueError( 'Required property \'step\' not present in LogMessageSourceStep JSON' ) return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a LogMessageSourceStep 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, 'action') and self.action is not None: _dict['action'] = self.action if hasattr(self, 'step') and self.step is not None: _dict['step'] = self.step 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 LogMessageSourceStep object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'LogMessageSourceStep') -> 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: 'LogMessageSourceStep') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class MessageOutputDebugTurnEventTurnEventActionFinished( MessageOutputDebugTurnEvent): """ MessageOutputDebugTurnEventTurnEventActionFinished. :attr str event: (optional) The type of turn event. :attr TurnEventActionSource source: (optional) :attr str action_start_time: (optional) The time when the action started processing the message. :attr str condition_type: (optional) The type of condition (if any) that is defined for the action. :attr str reason: (optional) The reason the action finished processing. :attr dict action_variables: (optional) The state of all action variables at the time the action finished. """ def __init__(self, *, event: str = None, source: 'TurnEventActionSource' = None, action_start_time: str = None, condition_type: str = None, reason: str = None, action_variables: dict = None) -> None: """ Initialize a MessageOutputDebugTurnEventTurnEventActionFinished object. :param str event: (optional) The type of turn event. :param TurnEventActionSource source: (optional) :param str action_start_time: (optional) The time when the action started processing the message. :param str condition_type: (optional) The type of condition (if any) that is defined for the action. :param str reason: (optional) The reason the action finished processing. :param dict action_variables: (optional) The state of all action variables at the time the action finished. """ # pylint: disable=super-init-not-called self.event = event self.source = source self.action_start_time = action_start_time self.condition_type = condition_type self.reason = reason self.action_variables = action_variables @classmethod def from_dict( cls, _dict: Dict ) -> 'MessageOutputDebugTurnEventTurnEventActionFinished': """Initialize a MessageOutputDebugTurnEventTurnEventActionFinished object from a json dictionary.""" args = {} if 'event' in _dict: args['event'] = _dict.get('event') if 'source' in _dict: args['source'] = TurnEventActionSource.from_dict( _dict.get('source')) if 'action_start_time' in _dict: args['action_start_time'] = _dict.get('action_start_time') if 'condition_type' in _dict: args['condition_type'] = _dict.get('condition_type') if 'reason' in _dict: args['reason'] = _dict.get('reason') if 'action_variables' in _dict: args['action_variables'] = _dict.get('action_variables') return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a MessageOutputDebugTurnEventTurnEventActionFinished 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, 'event') and self.event is not None: _dict['event'] = self.event if hasattr(self, 'source') and self.source is not None: _dict['source'] = self.source.to_dict() if hasattr(self, 'action_start_time') and self.action_start_time is not None: _dict['action_start_time'] = self.action_start_time if hasattr(self, 'condition_type') and self.condition_type is not None: _dict['condition_type'] = self.condition_type if hasattr(self, 'reason') and self.reason is not None: _dict['reason'] = self.reason if hasattr(self, 'action_variables') and self.action_variables is not None: _dict['action_variables'] = self.action_variables 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 MessageOutputDebugTurnEventTurnEventActionFinished object.""" return json.dumps(self.to_dict(), indent=2) def __eq__( self, other: 'MessageOutputDebugTurnEventTurnEventActionFinished' ) -> 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: 'MessageOutputDebugTurnEventTurnEventActionFinished' ) -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class ConditionTypeEnum(str, Enum): """ The type of condition (if any) that is defined for the action. """ USER_DEFINED = 'user_defined' WELCOME = 'welcome' ANYTHING_ELSE = 'anything_else' class ReasonEnum(str, Enum): """ The reason the action finished processing. """ ALL_STEPS_DONE = 'all_steps_done' NO_STEPS_VISITED = 'no_steps_visited' ENDED_BY_STEP = 'ended_by_step' CONNECT_TO_AGENT = 'connect_to_agent' MAX_RETRIES_REACHED = 'max_retries_reached' FALLBACK = 'fallback' class MessageOutputDebugTurnEventTurnEventActionVisited( MessageOutputDebugTurnEvent): """ MessageOutputDebugTurnEventTurnEventActionVisited. :attr str event: (optional) The type of turn event. :attr TurnEventActionSource source: (optional) :attr str action_start_time: (optional) The time when the action started processing the message. :attr str condition_type: (optional) The type of condition (if any) that is defined for the action. :attr str reason: (optional) The reason the action was visited. """ def __init__(self, *, event: str = None, source: 'TurnEventActionSource' = None, action_start_time: str = None, condition_type: str = None, reason: str = None) -> None: """ Initialize a MessageOutputDebugTurnEventTurnEventActionVisited object. :param str event: (optional) The type of turn event. :param TurnEventActionSource source: (optional) :param str action_start_time: (optional) The time when the action started processing the message. :param str condition_type: (optional) The type of condition (if any) that is defined for the action. :param str reason: (optional) The reason the action was visited. """ # pylint: disable=super-init-not-called self.event = event self.source = source self.action_start_time = action_start_time self.condition_type = condition_type self.reason = reason @classmethod def from_dict( cls, _dict: Dict) -> 'MessageOutputDebugTurnEventTurnEventActionVisited': """Initialize a MessageOutputDebugTurnEventTurnEventActionVisited object from a json dictionary.""" args = {} if 'event' in _dict: args['event'] = _dict.get('event') if 'source' in _dict: args['source'] = TurnEventActionSource.from_dict( _dict.get('source')) if 'action_start_time' in _dict: args['action_start_time'] = _dict.get('action_start_time') if 'condition_type' in _dict: args['condition_type'] = _dict.get('condition_type') if 'reason' in _dict: args['reason'] = _dict.get('reason') return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a MessageOutputDebugTurnEventTurnEventActionVisited 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, 'event') and self.event is not None: _dict['event'] = self.event if hasattr(self, 'source') and self.source is not None: _dict['source'] = self.source.to_dict() if hasattr(self, 'action_start_time') and self.action_start_time is not None: _dict['action_start_time'] = self.action_start_time if hasattr(self, 'condition_type') and self.condition_type is not None: _dict['condition_type'] = self.condition_type if hasattr(self, 'reason') and self.reason is not None: _dict['reason'] = self.reason 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 MessageOutputDebugTurnEventTurnEventActionVisited object.""" return json.dumps(self.to_dict(), indent=2) def __eq__( self, other: 'MessageOutputDebugTurnEventTurnEventActionVisited') -> 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: 'MessageOutputDebugTurnEventTurnEventActionVisited') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class ConditionTypeEnum(str, Enum): """ The type of condition (if any) that is defined for the action. """ USER_DEFINED = 'user_defined' WELCOME = 'welcome' ANYTHING_ELSE = 'anything_else' class ReasonEnum(str, Enum): """ The reason the action was visited. """ INTENT = 'intent' INVOKE_SUBACTION = 'invoke_subaction' SUBACTION_RETURN = 'subaction_return' INVOKE_EXTERNAL = 'invoke_external' TOPIC_SWITCH = 'topic_switch' TOPIC_RETURN = 'topic_return' AGENT_REQUESTED = 'agent_requested' STEP_VALIDATION_FAILED = 'step_validation_failed' NO_ACTION_MATCHES = 'no_action_matches' class MessageOutputDebugTurnEventTurnEventCallout(MessageOutputDebugTurnEvent): """ MessageOutputDebugTurnEventTurnEventCallout. :attr str event: (optional) The type of turn event. :attr TurnEventActionSource source: (optional) :attr TurnEventCalloutCallout callout: (optional) :attr TurnEventCalloutError error: (optional) """ def __init__(self, *, event: str = None, source: 'TurnEventActionSource' = None, callout: 'TurnEventCalloutCallout' = None, error: 'TurnEventCalloutError' = None) -> None: """ Initialize a MessageOutputDebugTurnEventTurnEventCallout object. :param str event: (optional) The type of turn event. :param TurnEventActionSource source: (optional) :param TurnEventCalloutCallout callout: (optional) :param TurnEventCalloutError error: (optional) """ # pylint: disable=super-init-not-called self.event = event self.source = source self.callout = callout self.error = error @classmethod def from_dict(cls, _dict: Dict) -> 'MessageOutputDebugTurnEventTurnEventCallout': """Initialize a MessageOutputDebugTurnEventTurnEventCallout object from a json dictionary.""" args = {} if 'event' in _dict: args['event'] = _dict.get('event') if 'source' in _dict: args['source'] = TurnEventActionSource.from_dict( _dict.get('source')) if 'callout' in _dict: args['callout'] = TurnEventCalloutCallout.from_dict( _dict.get('callout')) if 'error' in _dict: args['error'] = TurnEventCalloutError.from_dict(_dict.get('error')) return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a MessageOutputDebugTurnEventTurnEventCallout 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, 'event') and self.event is not None: _dict['event'] = self.event if hasattr(self, 'source') and self.source is not None: _dict['source'] = self.source.to_dict() if hasattr(self, 'callout') and self.callout is not None: _dict['callout'] = self.callout.to_dict() if hasattr(self, 'error') and self.error is not None: _dict['error'] = self.error.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 MessageOutputDebugTurnEventTurnEventCallout object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'MessageOutputDebugTurnEventTurnEventCallout') -> 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: 'MessageOutputDebugTurnEventTurnEventCallout') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class MessageOutputDebugTurnEventTurnEventHandlerVisited( MessageOutputDebugTurnEvent): """ MessageOutputDebugTurnEventTurnEventHandlerVisited. :attr str event: (optional) The type of turn event. :attr TurnEventActionSource source: (optional) :attr str action_start_time: (optional) The time when the action started processing the message. """ def __init__(self, *, event: str = None, source: 'TurnEventActionSource' = None, action_start_time: str = None) -> None: """ Initialize a MessageOutputDebugTurnEventTurnEventHandlerVisited object. :param str event: (optional) The type of turn event. :param TurnEventActionSource source: (optional) :param str action_start_time: (optional) The time when the action started processing the message. """ # pylint: disable=super-init-not-called self.event = event self.source = source self.action_start_time = action_start_time @classmethod def from_dict( cls, _dict: Dict ) -> 'MessageOutputDebugTurnEventTurnEventHandlerVisited': """Initialize a MessageOutputDebugTurnEventTurnEventHandlerVisited object from a json dictionary.""" args = {} if 'event' in _dict: args['event'] = _dict.get('event') if 'source' in _dict: args['source'] = TurnEventActionSource.from_dict( _dict.get('source')) if 'action_start_time' in _dict: args['action_start_time'] = _dict.get('action_start_time') return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a MessageOutputDebugTurnEventTurnEventHandlerVisited 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, 'event') and self.event is not None: _dict['event'] = self.event if hasattr(self, 'source') and self.source is not None: _dict['source'] = self.source.to_dict() if hasattr(self, 'action_start_time') and self.action_start_time is not None: _dict['action_start_time'] = self.action_start_time 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 MessageOutputDebugTurnEventTurnEventHandlerVisited object.""" return json.dumps(self.to_dict(), indent=2) def __eq__( self, other: 'MessageOutputDebugTurnEventTurnEventHandlerVisited' ) -> 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: 'MessageOutputDebugTurnEventTurnEventHandlerVisited' ) -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class MessageOutputDebugTurnEventTurnEventNodeVisited( MessageOutputDebugTurnEvent): """ MessageOutputDebugTurnEventTurnEventNodeVisited. :attr str event: (optional) The type of turn event. :attr TurnEventNodeSource source: (optional) :attr str reason: (optional) The reason the dialog node was visited. """ def __init__(self, *, event: str = None, source: 'TurnEventNodeSource' = None, reason: str = None) -> None: """ Initialize a MessageOutputDebugTurnEventTurnEventNodeVisited object. :param str event: (optional) The type of turn event. :param TurnEventNodeSource source: (optional) :param str reason: (optional) The reason the dialog node was visited. """ # pylint: disable=super-init-not-called self.event = event self.source = source self.reason = reason @classmethod def from_dict( cls, _dict: Dict) -> 'MessageOutputDebugTurnEventTurnEventNodeVisited': """Initialize a MessageOutputDebugTurnEventTurnEventNodeVisited object from a json dictionary.""" args = {} if 'event' in _dict: args['event'] = _dict.get('event') if 'source' in _dict: args['source'] = TurnEventNodeSource.from_dict(_dict.get('source')) if 'reason' in _dict: args['reason'] = _dict.get('reason') return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a MessageOutputDebugTurnEventTurnEventNodeVisited 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, 'event') and self.event is not None: _dict['event'] = self.event if hasattr(self, 'source') and self.source is not None: _dict['source'] = self.source.to_dict() if hasattr(self, 'reason') and self.reason is not None: _dict['reason'] = self.reason 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 MessageOutputDebugTurnEventTurnEventNodeVisited object.""" return json.dumps(self.to_dict(), indent=2) def __eq__( self, other: 'MessageOutputDebugTurnEventTurnEventNodeVisited') -> 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: 'MessageOutputDebugTurnEventTurnEventNodeVisited') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class ReasonEnum(str, Enum): """ The reason the dialog node was visited. """ WELCOME = 'welcome' BRANCH_START = 'branch_start' TOPIC_SWITCH = 'topic_switch' TOPIC_RETURN = 'topic_return' TOPIC_SWITCH_WITHOUT_RETURN = 'topic_switch_without_return' JUMP = 'jump' class MessageOutputDebugTurnEventTurnEventSearch(MessageOutputDebugTurnEvent): """ MessageOutputDebugTurnEventTurnEventSearch. :attr str event: (optional) The type of turn event. :attr TurnEventActionSource source: (optional) :attr TurnEventSearchError error: (optional) """ def __init__(self, *, event: str = None, source: 'TurnEventActionSource' = None, error: 'TurnEventSearchError' = None) -> None: """ Initialize a MessageOutputDebugTurnEventTurnEventSearch object. :param str event: (optional) The type of turn event. :param TurnEventActionSource source: (optional) :param TurnEventSearchError error: (optional) """ # pylint: disable=super-init-not-called self.event = event self.source = source self.error = error @classmethod def from_dict(cls, _dict: Dict) -> 'MessageOutputDebugTurnEventTurnEventSearch': """Initialize a MessageOutputDebugTurnEventTurnEventSearch object from a json dictionary.""" args = {} if 'event' in _dict: args['event'] = _dict.get('event') if 'source' in _dict: args['source'] = TurnEventActionSource.from_dict( _dict.get('source')) if 'error' in _dict: args['error'] = TurnEventSearchError.from_dict(_dict.get('error')) return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a MessageOutputDebugTurnEventTurnEventSearch 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, 'event') and self.event is not None: _dict['event'] = self.event if hasattr(self, 'source') and self.source is not None: _dict['source'] = self.source.to_dict() if hasattr(self, 'error') and self.error is not None: _dict['error'] = self.error.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 MessageOutputDebugTurnEventTurnEventSearch object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'MessageOutputDebugTurnEventTurnEventSearch') -> 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: 'MessageOutputDebugTurnEventTurnEventSearch') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class MessageOutputDebugTurnEventTurnEventStepAnswered( MessageOutputDebugTurnEvent): """ MessageOutputDebugTurnEventTurnEventStepAnswered. :attr str event: (optional) The type of turn event. :attr TurnEventActionSource source: (optional) :attr str condition_type: (optional) The type of condition (if any) that is defined for the action. :attr str action_start_time: (optional) The time when the action started processing the message. :attr bool prompted: (optional) Whether the step was answered in response to a prompt from the assistant. If this property is `false`, the user provided the answer without visiting the step. """ def __init__(self, *, event: str = None, source: 'TurnEventActionSource' = None, condition_type: str = None, action_start_time: str = None, prompted: bool = None) -> None: """ Initialize a MessageOutputDebugTurnEventTurnEventStepAnswered object. :param str event: (optional) The type of turn event. :param TurnEventActionSource source: (optional) :param str condition_type: (optional) The type of condition (if any) that is defined for the action. :param str action_start_time: (optional) The time when the action started processing the message. :param bool prompted: (optional) Whether the step was answered in response to a prompt from the assistant. If this property is `false`, the user provided the answer without visiting the step. """ # pylint: disable=super-init-not-called self.event = event self.source = source self.condition_type = condition_type self.action_start_time = action_start_time self.prompted = prompted @classmethod def from_dict( cls, _dict: Dict) -> 'MessageOutputDebugTurnEventTurnEventStepAnswered': """Initialize a MessageOutputDebugTurnEventTurnEventStepAnswered object from a json dictionary.""" args = {} if 'event' in _dict: args['event'] = _dict.get('event') if 'source' in _dict: args['source'] = TurnEventActionSource.from_dict( _dict.get('source')) if 'condition_type' in _dict: args['condition_type'] = _dict.get('condition_type') if 'action_start_time' in _dict: args['action_start_time'] = _dict.get('action_start_time') if 'prompted' in _dict: args['prompted'] = _dict.get('prompted') return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a MessageOutputDebugTurnEventTurnEventStepAnswered 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, 'event') and self.event is not None: _dict['event'] = self.event if hasattr(self, 'source') and self.source is not None: _dict['source'] = self.source.to_dict() if hasattr(self, 'condition_type') and self.condition_type is not None: _dict['condition_type'] = self.condition_type if hasattr(self, 'action_start_time') and self.action_start_time is not None: _dict['action_start_time'] = self.action_start_time if hasattr(self, 'prompted') and self.prompted is not None: _dict['prompted'] = self.prompted 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 MessageOutputDebugTurnEventTurnEventStepAnswered object.""" return json.dumps(self.to_dict(), indent=2) def __eq__( self, other: 'MessageOutputDebugTurnEventTurnEventStepAnswered') -> 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: 'MessageOutputDebugTurnEventTurnEventStepAnswered') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class ConditionTypeEnum(str, Enum): """ The type of condition (if any) that is defined for the action. """ USER_DEFINED = 'user_defined' WELCOME = 'welcome' ANYTHING_ELSE = 'anything_else' class MessageOutputDebugTurnEventTurnEventStepVisited( MessageOutputDebugTurnEvent): """ MessageOutputDebugTurnEventTurnEventStepVisited. :attr str event: (optional) The type of turn event. :attr TurnEventActionSource source: (optional) :attr str condition_type: (optional) The type of condition (if any) that is defined for the action. :attr str action_start_time: (optional) The time when the action started processing the message. :attr bool has_question: (optional) Whether the step collects a customer response. """ def __init__(self, *, event: str = None, source: 'TurnEventActionSource' = None, condition_type: str = None, action_start_time: str = None, has_question: bool = None) -> None: """ Initialize a MessageOutputDebugTurnEventTurnEventStepVisited object. :param str event: (optional) The type of turn event. :param TurnEventActionSource source: (optional) :param str condition_type: (optional) The type of condition (if any) that is defined for the action. :param str action_start_time: (optional) The time when the action started processing the message. :param bool has_question: (optional) Whether the step collects a customer response. """ # pylint: disable=super-init-not-called self.event = event self.source = source self.condition_type = condition_type self.action_start_time = action_start_time self.has_question = has_question @classmethod def from_dict( cls, _dict: Dict) -> 'MessageOutputDebugTurnEventTurnEventStepVisited': """Initialize a MessageOutputDebugTurnEventTurnEventStepVisited object from a json dictionary.""" args = {} if 'event' in _dict: args['event'] = _dict.get('event') if 'source' in _dict: args['source'] = TurnEventActionSource.from_dict( _dict.get('source')) if 'condition_type' in _dict: args['condition_type'] = _dict.get('condition_type') if 'action_start_time' in _dict: args['action_start_time'] = _dict.get('action_start_time') if 'has_question' in _dict: args['has_question'] = _dict.get('has_question') return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a MessageOutputDebugTurnEventTurnEventStepVisited 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, 'event') and self.event is not None: _dict['event'] = self.event if hasattr(self, 'source') and self.source is not None: _dict['source'] = self.source.to_dict() if hasattr(self, 'condition_type') and self.condition_type is not None: _dict['condition_type'] = self.condition_type if hasattr(self, 'action_start_time') and self.action_start_time is not None: _dict['action_start_time'] = self.action_start_time if hasattr(self, 'has_question') and self.has_question is not None: _dict['has_question'] = self.has_question 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 MessageOutputDebugTurnEventTurnEventStepVisited object.""" return json.dumps(self.to_dict(), indent=2) def __eq__( self, other: 'MessageOutputDebugTurnEventTurnEventStepVisited') -> 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: 'MessageOutputDebugTurnEventTurnEventStepVisited') -> bool: """Return `true` when self and other are not equal, false otherwise.""" return not self == other class ConditionTypeEnum(str, Enum): """ The type of condition (if any) that is defined for the action. """ USER_DEFINED = 'user_defined' WELCOME = 'welcome' ANYTHING_ELSE = 'anything_else' 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 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 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 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 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 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, 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 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.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 '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, '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 RuntimeResponseGenericRuntimeResponseTypeDate(RuntimeResponseGeneric): """ RuntimeResponseGenericRuntimeResponseTypeDate. :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. """ def __init__(self, response_type: str) -> None: """ Initialize a RuntimeResponseGenericRuntimeResponseTypeDate 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. """ # pylint: disable=super-init-not-called self.response_type = response_type @classmethod def from_dict( cls, _dict: Dict) -> 'RuntimeResponseGenericRuntimeResponseTypeDate': """Initialize a RuntimeResponseGenericRuntimeResponseTypeDate 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 RuntimeResponseGenericRuntimeResponseTypeDate JSON' ) return cls(**args) @classmethod def _from_dict(cls, _dict): """Initialize a RuntimeResponseGenericRuntimeResponseTypeDate 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 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 RuntimeResponseGenericRuntimeResponseTypeDate object.""" return json.dumps(self.to_dict(), indent=2) def __eq__(self, other: 'RuntimeResponseGenericRuntimeResponseTypeDate') -> 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: 'RuntimeResponseGenericRuntimeResponseTypeDate') -> 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 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 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 to show before the response. :attr str description: (optional) The description to show with the 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 to show before the response. :param str description: (optional) The description to show with the 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 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 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 RuntimeResponseGenericRuntimeResponseTypeSearch(RuntimeResponseGeneric): """ RuntimeResponseGenericRuntimeResponseTypeSearch. :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 header: The title or introductory text to show before the response. This text is defined in the search skill configuration. :attr List[SearchResult] primary_results: An array of objects that contains the search results to be displayed in the initial response to the user. :attr List[SearchResult] additional_results: An array of objects that contains additional search results that can be displayed to the user upon request. :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, header: str, primary_results: List['SearchResult'], additional_results: List['SearchResult'], *, channels: List['ResponseGenericChannel'] = None) -> None: """ Initialize a RuntimeResponseGenericRuntimeResponseTypeSearch 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 header: The title or introductory text to show before the response. This text is defined in the search skill configuration. :param List[SearchResult] primary_results: An array of objects that contains the search results to be displayed in the initial response to the user. :param List[SearchResult] additional_results: An array of objects that contains additional search results that can be displayed to the user upon request. :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.header = header self.primary_results = primary_results self.additional_results = additional_results self.channels = channels @classmethod def from_dict( cls, _dict: Dict) -> 'RuntimeResponseGenericRuntimeResponseTypeSearch': """Initialize a RuntimeResponseGenericRuntimeResponseTypeSearch 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 RuntimeResponseGenericRuntimeResponseTypeSearch JSON' ) if 'header' in _dict: args['header'] = _dict.get('header') else: raise ValueError( 'Required property \'header\' not present in RuntimeResponseGenericRuntimeResponseTypeSearch JSON' ) if 'primary_results' in _dict: args['primary_results'] = [ SearchResult.from_dict(x) for x in _dict.get('primary_results') ] else: raise ValueError( 'Required property \'primary_results\' not present in RuntimeResponseGenericRuntimeResponseTypeSearch JSON' ) if 'additional_results' in _dict: args['additional_results'] = [ SearchResult.from_dict(x) for x in _dict.get('additional_results') ] else: raise ValueError( 'Required property \'additional_results\' not present in RuntimeResponseGenericRuntimeResponseTypeSearch 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 RuntimeResponseGenericRuntimeResponseTypeSearch 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, 'header') and self.header is not None: _dict['header'] = self.header if hasattr(self, 'primary_results') and self.primary_results is not None: _dict['primary_results'] = [ x.to_dict() for x in self.primary_results ] if hasattr( self, 'additional_results') and self.additional_results is not None: _dict['additional_results'] = [ x.to_dict() for x in self.additional_results ] 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 RuntimeResponseGenericRuntimeResponseTypeSearch object.""" return json.dumps(self.to_dict(), indent=2) def __eq__( self, other: 'RuntimeResponseGenericRuntimeResponseTypeSearch') -> 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: 'RuntimeResponseGenericRuntimeResponseTypeSearch') -> 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 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 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