Source code for ibm_watson.assistant_v2

# coding: utf-8

# Copyright 2018 IBM All Rights Reserved.
#
# 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.
"""
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.
"""

from __future__ import absolute_import

import json
from .common import get_sdk_headers
from ibm_cloud_sdk_core import BaseService

##############################################################################
# Service
##############################################################################


class AssistantV2(BaseService):
    """The Assistant V2 service."""

    default_url = 'https://gateway.watsonplatform.net/assistant/api'

    def __init__(
            self,
            version,
            url=default_url,
            username=None,
            password=None,
            iam_apikey=None,
            iam_access_token=None,
            iam_url=None,
            iam_client_id=None,
            iam_client_secret=None,
            icp4d_access_token=None,
            icp4d_url=None,
            authentication_type=None,
    ):
        """
        Construct a new client for the Assistant service.

        :param str version: The API version date to use with the service, in
               "YYYY-MM-DD" format. Whenever the API is changed in a backwards
               incompatible way, a new minor version of the API is released.
               The service uses the API version for the date you specify, or
               the most recent version before that date. Note that you should
               not programmatically specify the current date at runtime, in
               case the API has been updated since your application's release.
               Instead, specify a version date that is compatible with your
               application, and don't change it until your application is
               ready for a later version.

        :param str url: The base url to use when contacting the service (e.g.
               "https://gateway.watsonplatform.net/assistant/api/assistant/api").
               The base url may differ between IBM Cloud regions.

        :param str username: The username used to authenticate with the service.
               Username and password credentials are only required to run your
               application locally or outside of IBM Cloud. When running on
               IBM Cloud, the credentials will be automatically loaded from the
               `VCAP_SERVICES` environment variable.

        :param str password: The password used to authenticate with the service.
               Username and password credentials are only required to run your
               application locally or outside of IBM Cloud. When running on
               IBM Cloud, the credentials will be automatically loaded from the
               `VCAP_SERVICES` environment variable.

        :param str iam_apikey: An API key that can be used to request IAM tokens. If
               this API key is provided, the SDK will manage the token and handle the
               refreshing.

        :param str iam_access_token:  An IAM access token is fully managed by the application.
               Responsibility falls on the application to refresh the token, either before
               it expires or reactively upon receiving a 401 from the service as any requests
               made with an expired token will fail.

        :param str iam_url: An optional URL for the IAM service API. Defaults to
               'https://iam.cloud.ibm.com/identity/token'.

        :param str iam_client_id: An optional client_id value to use when interacting with the IAM service.

        :param str iam_client_secret: An optional client_secret value to use when interacting with the IAM service.

        :param str icp4d_access_token:  A ICP4D(IBM Cloud Pak for Data) access token is
               fully managed by the application. Responsibility falls on the application to
               refresh the token, either before it expires or reactively upon receiving a 401
               from the service as any requests made with an expired token will fail.

        :param str icp4d_url: In order to use an SDK-managed token with ICP4D authentication, this
               URL must be passed in.

        :param str authentication_type: Specifies the authentication pattern to use. Values that it
               takes are basic, iam or icp4d.
        """

        BaseService.__init__(
            self,
            vcap_services_name='conversation',
            url=url,
            username=username,
            password=password,
            iam_apikey=iam_apikey,
            iam_access_token=iam_access_token,
            iam_url=iam_url,
            iam_client_id=iam_client_id,
            iam_client_secret=iam_client_secret,
            use_vcap_services=True,
            display_name='Assistant',
            icp4d_access_token=icp4d_access_token,
            icp4d_url=icp4d_url,
            authentication_type=authentication_type)
        self.version = version

    #########################
    # Sessions
    #########################

    def create_session(self, assistant_id, **kwargs):
        """
        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.

        :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/services/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
        """

        if assistant_id is None:
            raise ValueError('assistant_id must be provided')

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('conversation', 'V2', 'create_session')
        headers.update(sdk_headers)

        params = {'version': self.version}

        url = '/v2/assistants/{0}/sessions'.format(
            *self._encode_path_vars(assistant_id))
        response = self.request(
            method='POST',
            url=url,
            headers=headers,
            params=params,
            accept_json=True)
        return response

    def delete_session(self, assistant_id, session_id, **kwargs):
        """
        Delete session.

        Deletes a session explicitly before it times out.

        :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/services/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 = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('conversation', 'V2', 'delete_session')
        headers.update(sdk_headers)

        params = {'version': self.version}

        url = '/v2/assistants/{0}/sessions/{1}'.format(
            *self._encode_path_vars(assistant_id, session_id))
        response = self.request(
            method='DELETE',
            url=url,
            headers=headers,
            params=params,
            accept_json=True)
        return response

    #########################
    # Message
    #########################

    def message(self,
                assistant_id,
                session_id,
                input=None,
                context=None,
                **kwargs):
        """
        Send user input to assistant.

        Send user input to an assistant and receive a response.
        There is no rate limit for this operation.

        :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/services/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: An input object that includes the input text.
        :param MessageContext context: State information for the conversation. The context
        is stored by the assistant on a per-session basis. You can use this property to
        set or modify context variables, which can also be accessed by dialog nodes.
        :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')
        if input is not None:
            input = self._convert_model(input, MessageInput)
        if context is not None:
            context = self._convert_model(context, MessageContext)

        headers = {}
        if 'headers' in kwargs:
            headers.update(kwargs.get('headers'))
        sdk_headers = get_sdk_headers('conversation', 'V2', 'message')
        headers.update(sdk_headers)

        params = {'version': self.version}

        data = {'input': input, 'context': context}

        url = '/v2/assistants/{0}/sessions/{1}/message'.format(
            *self._encode_path_vars(assistant_id, session_id))
        response = self.request(
            method='POST',
            url=url,
            headers=headers,
            params=params,
            json=data,
            accept_json=True)
        return response


##############################################################################
# Models
##############################################################################


class CaptureGroup(object):
    """
    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, location=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):
        """Initialize a CaptureGroup object from a json dictionary."""
        args = {}
        validKeys = ['group', 'location']
        badKeys = set(_dict.keys()) - set(validKeys)
        if badKeys:
            raise ValueError(
                'Unrecognized keys detected in dictionary for class CaptureGroup: '
                + ', '.join(badKeys))
        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)

    def _to_dict(self):
        """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 __str__(self):
        """Return a `str` version of this CaptureGroup object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """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):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class DialogLogMessage(object):
    """
    Dialog log message details.

    :attr str level: The severity of the log message.
    :attr str message: The text of the log message.
    """

    def __init__(self, level, message):
        """
        Initialize a DialogLogMessage object.

        :param str level: The severity of the log message.
        :param str message: The text of the log message.
        """
        self.level = level
        self.message = message

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a DialogLogMessage object from a json dictionary."""
        args = {}
        validKeys = ['level', 'message']
        badKeys = set(_dict.keys()) - set(validKeys)
        if badKeys:
            raise ValueError(
                'Unrecognized keys detected in dictionary for class DialogLogMessage: '
                + ', '.join(badKeys))
        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'
            )
        return cls(**args)

    def _to_dict(self):
        """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
        return _dict

    def __str__(self):
        """Return a `str` version of this DialogLogMessage object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """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):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class DialogNodeAction(object):
    """
    DialogNodeAction.

    :attr str name: The name of the action.
    :attr str action_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,
                 result_variable,
                 action_type=None,
                 parameters=None,
                 credentials=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 action_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.action_type = action_type
        self.parameters = parameters
        self.result_variable = result_variable
        self.credentials = credentials

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a DialogNodeAction object from a json dictionary."""
        args = {}
        validKeys = [
            'name', 'action_type', 'type', 'parameters', 'result_variable',
            'credentials'
        ]
        badKeys = set(_dict.keys()) - set(validKeys)
        if badKeys:
            raise ValueError(
                'Unrecognized keys detected in dictionary for class DialogNodeAction: '
                + ', '.join(badKeys))
        if 'name' in _dict:
            args['name'] = _dict.get('name')
        else:
            raise ValueError(
                'Required property \'name\' not present in DialogNodeAction JSON'
            )
        if 'type' in _dict or 'action_type' in _dict:
            args['action_type'] = _dict.get('type') or _dict.get('action_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)

    def _to_dict(self):
        """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, 'action_type') and self.action_type is not None:
            _dict['type'] = self.action_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 __str__(self):
        """Return a `str` version of this DialogNodeAction object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """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):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class DialogNodeOutputOptionsElement(object):
    """
    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, value):
        """
        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):
        """Initialize a DialogNodeOutputOptionsElement object from a json dictionary."""
        args = {}
        validKeys = ['label', 'value']
        badKeys = set(_dict.keys()) - set(validKeys)
        if badKeys:
            raise ValueError(
                'Unrecognized keys detected in dictionary for class DialogNodeOutputOptionsElement: '
                + ', '.join(badKeys))
        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)

    def _to_dict(self):
        """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 __str__(self):
        """Return a `str` version of this DialogNodeOutputOptionsElement object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """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):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class DialogNodeOutputOptionsElementValue(object):
    """
    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=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):
        """Initialize a DialogNodeOutputOptionsElementValue object from a json dictionary."""
        args = {}
        validKeys = ['input']
        badKeys = set(_dict.keys()) - set(validKeys)
        if badKeys:
            raise ValueError(
                'Unrecognized keys detected in dictionary for class DialogNodeOutputOptionsElementValue: '
                + ', '.join(badKeys))
        if 'input' in _dict:
            args['input'] = MessageInput._from_dict(_dict.get('input'))
        return cls(**args)

    def _to_dict(self):
        """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 __str__(self):
        """Return a `str` version of this DialogNodeOutputOptionsElementValue object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """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):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class DialogNodesVisited(object):
    """
    DialogNodesVisited.

    :attr str dialog_node: (optional) A dialog node that was triggered during processing
    of the input message.
    :attr str title: (optional) The title of the dialog node.
    :attr str conditions: (optional) The conditions that trigger the dialog node.
    """

    def __init__(self, dialog_node=None, title=None, conditions=None):
        """
        Initialize a DialogNodesVisited object.

        :param str dialog_node: (optional) A dialog node that was triggered during
        processing of the input message.
        :param str title: (optional) The title of the dialog node.
        :param str conditions: (optional) The conditions that trigger the dialog node.
        """
        self.dialog_node = dialog_node
        self.title = title
        self.conditions = conditions

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a DialogNodesVisited object from a json dictionary."""
        args = {}
        validKeys = ['dialog_node', 'title', 'conditions']
        badKeys = set(_dict.keys()) - set(validKeys)
        if badKeys:
            raise ValueError(
                'Unrecognized keys detected in dictionary for class DialogNodesVisited: '
                + ', '.join(badKeys))
        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)

    def _to_dict(self):
        """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 __str__(self):
        """Return a `str` version of this DialogNodesVisited object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """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):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class DialogRuntimeResponseGeneric(object):
    """
    DialogRuntimeResponseGeneric.

    :attr str response_type: The type of response returned by the dialog node. The
    specified response type must be supported by the client application or channel.
    **Note:** The **suggestion** response type is part of the disambiguation feature,
    which is only available for Premium users.
    :attr str text: (optional) The text of the response.
    :attr int time: (optional) How long to pause, in milliseconds.
    :attr bool typing: (optional) Whether to send a "user is typing" event during the
    pause.
    :attr str source: (optional) The URL of the image.
    :attr str title: (optional) The title or introductory text to show before the
    response.
    :attr str description: (optional) The description to show with the the response.
    :attr str preference: (optional) The preferred type of control to display.
    :attr list[DialogNodeOutputOptionsElement] options: (optional) An array of objects
    describing the options from which the user can choose.
    :attr str message_to_human_agent: (optional) A message to be sent to the human agent
    who will be taking over the conversation.
    :attr str topic: (optional) A label identifying the topic of the conversation, derived
    from the **user_label** property of the relevant node.
    :attr list[DialogSuggestion] suggestions: (optional) An array of objects describing
    the possible matching dialog nodes from which the user can choose.
    **Note:** The **suggestions** property is part of the disambiguation feature, which is
    only available for Premium users.
    """

    def __init__(self,
                 response_type,
                 text=None,
                 time=None,
                 typing=None,
                 source=None,
                 title=None,
                 description=None,
                 preference=None,
                 options=None,
                 message_to_human_agent=None,
                 topic=None,
                 suggestions=None):
        """
        Initialize a DialogRuntimeResponseGeneric object.

        :param str response_type: The type of response returned by the dialog node. The
        specified response type must be supported by the client application or channel.
        **Note:** The **suggestion** response type is part of the disambiguation feature,
        which is only available for Premium users.
        :param str text: (optional) The text of the response.
        :param int time: (optional) How long to pause, in milliseconds.
        :param bool typing: (optional) Whether to send a "user is typing" event during the
        pause.
        :param str source: (optional) The URL of the image.
        :param str title: (optional) The title or introductory text to show before the
        response.
        :param str description: (optional) The description to show with the the response.
        :param str preference: (optional) The preferred type of control to display.
        :param list[DialogNodeOutputOptionsElement] options: (optional) An array of
        objects describing the options from which the user can choose.
        :param str message_to_human_agent: (optional) A message to be sent to the human
        agent who will be taking over the conversation.
        :param str topic: (optional) A label identifying the topic of the conversation,
        derived from the **user_label** property of the relevant node.
        :param list[DialogSuggestion] suggestions: (optional) An array of objects
        describing the possible matching dialog nodes from which the user can choose.
        **Note:** The **suggestions** property is part of the disambiguation feature,
        which is only available for Premium users.
        """
        self.response_type = response_type
        self.text = text
        self.time = time
        self.typing = typing
        self.source = source
        self.title = title
        self.description = description
        self.preference = preference
        self.options = options
        self.message_to_human_agent = message_to_human_agent
        self.topic = topic
        self.suggestions = suggestions

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a DialogRuntimeResponseGeneric object from a json dictionary."""
        args = {}
        validKeys = [
            'response_type', 'text', 'time', 'typing', 'source', 'title',
            'description', 'preference', 'options', 'message_to_human_agent',
            'topic', 'suggestions'
        ]
        badKeys = set(_dict.keys()) - set(validKeys)
        if badKeys:
            raise ValueError(
                'Unrecognized keys detected in dictionary for class DialogRuntimeResponseGeneric: '
                + ', '.join(badKeys))
        if 'response_type' in _dict:
            args['response_type'] = _dict.get('response_type')
        else:
            raise ValueError(
                'Required property \'response_type\' not present in DialogRuntimeResponseGeneric JSON'
            )
        if 'text' in _dict:
            args['text'] = _dict.get('text')
        if 'time' in _dict:
            args['time'] = _dict.get('time')
        if 'typing' in _dict:
            args['typing'] = _dict.get('typing')
        if 'source' in _dict:
            args['source'] = _dict.get('source')
        if 'title' in _dict:
            args['title'] = _dict.get('title')
        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'))
            ]
        if 'message_to_human_agent' in _dict:
            args['message_to_human_agent'] = _dict.get('message_to_human_agent')
        if 'topic' in _dict:
            args['topic'] = _dict.get('topic')
        if 'suggestions' in _dict:
            args['suggestions'] = [
                DialogSuggestion._from_dict(x)
                for x in (_dict.get('suggestions'))
            ]
        return cls(**args)

    def _to_dict(self):
        """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, '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, '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, '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, '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, 'topic') and self.topic is not None:
            _dict['topic'] = self.topic
        if hasattr(self, 'suggestions') and self.suggestions is not None:
            _dict['suggestions'] = [x._to_dict() for x in self.suggestions]
        return _dict

    def __str__(self):
        """Return a `str` version of this DialogRuntimeResponseGeneric object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """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):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class DialogSuggestion(object):
    """
    DialogSuggestion.

    :attr str label: The user-facing label for the disambiguation option. This label is
    taken from the **user_label** property of the corresponding dialog node.
    :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, value, output=None):
        """
        Initialize a DialogSuggestion object.

        :param str label: The user-facing label for the disambiguation option. This label
        is taken from the **user_label** property of the corresponding dialog node.
        :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):
        """Initialize a DialogSuggestion object from a json dictionary."""
        args = {}
        validKeys = ['label', 'value', 'output']
        badKeys = set(_dict.keys()) - set(validKeys)
        if badKeys:
            raise ValueError(
                'Unrecognized keys detected in dictionary for class DialogSuggestion: '
                + ', '.join(badKeys))
        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)

    def _to_dict(self):
        """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 __str__(self):
        """Return a `str` version of this DialogSuggestion object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """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):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class DialogSuggestionValue(object):
    """
    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=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):
        """Initialize a DialogSuggestionValue object from a json dictionary."""
        args = {}
        validKeys = ['input']
        badKeys = set(_dict.keys()) - set(validKeys)
        if badKeys:
            raise ValueError(
                'Unrecognized keys detected in dictionary for class DialogSuggestionValue: '
                + ', '.join(badKeys))
        if 'input' in _dict:
            args['input'] = MessageInput._from_dict(_dict.get('input'))
        return cls(**args)

    def _to_dict(self):
        """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 __str__(self):
        """Return a `str` version of this DialogSuggestionValue object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """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):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class MessageContext(object):
    """
    MessageContext.

    :attr MessageContextGlobal global_: (optional) Information that is shared by all
    skills used by the Assistant.
    :attr MessageContextSkills skills: (optional) Information specific to particular
    skills used by the Assistant.
    **Note:** Currently, only a single property named `main skill` is supported. This
    object contains variables that apply to the dialog skill used by the assistant.
    """

    def __init__(self, global_=None, skills=None):
        """
        Initialize a MessageContext object.

        :param MessageContextGlobal global_: (optional) Information that is shared by all
        skills used by the Assistant.
        :param MessageContextSkills skills: (optional) Information specific to particular
        skills used by the Assistant.
        **Note:** Currently, only a single property named `main skill` is supported. This
        object contains variables that apply to the dialog skill used by the assistant.
        """
        self.global_ = global_
        self.skills = skills

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a MessageContext object from a json dictionary."""
        args = {}
        validKeys = ['global_', 'global', 'skills']
        badKeys = set(_dict.keys()) - set(validKeys)
        if badKeys:
            raise ValueError(
                'Unrecognized keys detected in dictionary for class MessageContext: '
                + ', '.join(badKeys))
        if 'global' in _dict:
            args['global_'] = MessageContextGlobal._from_dict(
                _dict.get('global'))
        if 'skills' in _dict:
            args['skills'] = MessageContextSkills._from_dict(
                _dict.get('skills'))
        return cls(**args)

    def _to_dict(self):
        """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'] = self.skills._to_dict()
        return _dict

    def __str__(self):
        """Return a `str` version of this MessageContext object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """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):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class MessageContextGlobal(object):
    """
    Information 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.
    """

    def __init__(self, system=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

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a MessageContextGlobal object from a json dictionary."""
        args = {}
        validKeys = ['system']
        badKeys = set(_dict.keys()) - set(validKeys)
        if badKeys:
            raise ValueError(
                'Unrecognized keys detected in dictionary for class MessageContextGlobal: '
                + ', '.join(badKeys))
        if 'system' in _dict:
            args['system'] = MessageContextGlobalSystem._from_dict(
                _dict.get('system'))
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'system') and self.system is not None:
            _dict['system'] = self.system._to_dict()
        return _dict

    def __str__(self):
        """Return a `str` version of this MessageContextGlobal object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """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):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class MessageContextGlobalSystem(object):
    """
    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 Plus and Premium plans, this
    user ID is used to identify unique users for billing purposes. This string cannot
    contain carriage return, newline, or tab characters.
    :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).
    """

    def __init__(self, timezone=None, user_id=None, turn_count=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 Plus and Premium plans,
        this user ID is used to identify unique users for billing purposes. This string
        cannot contain carriage return, newline, or tab characters.
        :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).
        """
        self.timezone = timezone
        self.user_id = user_id
        self.turn_count = turn_count

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a MessageContextGlobalSystem object from a json dictionary."""
        args = {}
        validKeys = ['timezone', 'user_id', 'turn_count']
        badKeys = set(_dict.keys()) - set(validKeys)
        if badKeys:
            raise ValueError(
                'Unrecognized keys detected in dictionary for class MessageContextGlobalSystem: '
                + ', '.join(badKeys))
        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')
        return cls(**args)

    def _to_dict(self):
        """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
        return _dict

    def __str__(self):
        """Return a `str` version of this MessageContextGlobalSystem object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """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):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class MessageContextSkill(object):
    """
    Contains information specific to a particular skill used by the Assistant.

    :attr dict user_defined: (optional) Arbitrary variables that can be read and written
    by a particular skill.
    """

    def __init__(self, user_defined=None):
        """
        Initialize a MessageContextSkill object.

        :param dict user_defined: (optional) Arbitrary variables that can be read and
        written by a particular skill.
        """
        self.user_defined = user_defined

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a MessageContextSkill object from a json dictionary."""
        args = {}
        validKeys = ['user_defined']
        badKeys = set(_dict.keys()) - set(validKeys)
        if badKeys:
            raise ValueError(
                'Unrecognized keys detected in dictionary for class MessageContextSkill: '
                + ', '.join(badKeys))
        if 'user_defined' in _dict:
            args['user_defined'] = _dict.get('user_defined')
        return cls(**args)

    def _to_dict(self):
        """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
        return _dict

    def __str__(self):
        """Return a `str` version of this MessageContextSkill object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """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):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class MessageContextSkills(object):
    """
    Information specific to particular skills used by the Assistant.
    **Note:** Currently, only a single property named `main skill` is supported. This
    object contains variables that apply to the dialog skill used by the assistant.

    """

    def __init__(self, **kwargs):
        """
        Initialize a MessageContextSkills object.

        :param **kwargs: (optional) Any additional properties.
        """
        for _key, _value in kwargs.items():
            setattr(self, _key, _value)

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a MessageContextSkills object from a json dictionary."""
        args = {}
        xtra = _dict.copy()
        args.update(xtra)
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, '_additionalProperties'):
            for _key in self._additionalProperties:
                _value = getattr(self, _key, None)
                if _value is not None:
                    _dict[_key] = _value
        return _dict

    def __setattr__(self, name, value):
        properties = {}
        if not hasattr(self, '_additionalProperties'):
            super(MessageContextSkills, self).__setattr__(
                '_additionalProperties', set())
        if name not in properties:
            self._additionalProperties.add(name)
        super(MessageContextSkills, self).__setattr__(name, value)

    def __str__(self):
        """Return a `str` version of this MessageContextSkills object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """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):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class MessageInput(object):
    """
    An input object that includes the input text.

    :attr str message_type: (optional) The type of user input. Currently, only text input
    is supported.
    :attr str text: (optional) The text of the user input. This string cannot contain
    carriage return, newline, or tab characters.
    :attr MessageInputOptions options: (optional) Optional properties that control how the
    assistant responds.
    :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.
    """

    def __init__(self,
                 message_type=None,
                 text=None,
                 options=None,
                 intents=None,
                 entities=None,
                 suggestion_id=None):
        """
        Initialize a MessageInput object.

        :param str message_type: (optional) The type of user input. Currently, only text
        input is supported.
        :param str text: (optional) The text of the user input. This string cannot contain
        carriage return, newline, or tab characters.
        :param MessageInputOptions options: (optional) Optional properties that control
        how the assistant responds.
        :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.
        """
        self.message_type = message_type
        self.text = text
        self.options = options
        self.intents = intents
        self.entities = entities
        self.suggestion_id = suggestion_id

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a MessageInput object from a json dictionary."""
        args = {}
        validKeys = [
            'message_type', 'text', 'options', 'intents', 'entities',
            'suggestion_id'
        ]
        badKeys = set(_dict.keys()) - set(validKeys)
        if badKeys:
            raise ValueError(
                'Unrecognized keys detected in dictionary for class MessageInput: '
                + ', '.join(badKeys))
        if 'message_type' in _dict:
            args['message_type'] = _dict.get('message_type')
        if 'text' in _dict:
            args['text'] = _dict.get('text')
        if 'options' in _dict:
            args['options'] = MessageInputOptions._from_dict(
                _dict.get('options'))
        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')
        return cls(**args)

    def _to_dict(self):
        """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, 'options') and self.options is not None:
            _dict['options'] = self.options._to_dict()
        if hasattr(self, 'intents') and self.intents is not None:
            _dict['intents'] = [x._to_dict() for x in self.intents]
        if hasattr(self, 'entities') and self.entities is not None:
            _dict['entities'] = [x._to_dict() for x in self.entities]
        if hasattr(self, 'suggestion_id') and self.suggestion_id is not None:
            _dict['suggestion_id'] = self.suggestion_id
        return _dict

    def __str__(self):
        """Return a `str` version of this MessageInput object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """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):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class MessageInputOptions(object):
    """
    Optional properties that control how the assistant responds.

    :attr bool debug: (optional) Whether to return additional diagnostic information. Set
    to `true` to return additional information under the `output.debug` key.
    :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 bool return_context: (optional) Whether to return session context with the
    response. If you specify `true`, the response will include the `context` property.
    """

    def __init__(self,
                 debug=None,
                 restart=None,
                 alternate_intents=None,
                 return_context=None):
        """
        Initialize a MessageInputOptions object.

        :param bool debug: (optional) Whether to return additional diagnostic information.
        Set to `true` to return additional information under the `output.debug` key.
        :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 bool return_context: (optional) Whether to return session context with the
        response. If you specify `true`, the response will include the `context` property.
        """
        self.debug = debug
        self.restart = restart
        self.alternate_intents = alternate_intents
        self.return_context = return_context

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a MessageInputOptions object from a json dictionary."""
        args = {}
        validKeys = ['debug', 'restart', 'alternate_intents', 'return_context']
        badKeys = set(_dict.keys()) - set(validKeys)
        if badKeys:
            raise ValueError(
                'Unrecognized keys detected in dictionary for class MessageInputOptions: '
                + ', '.join(badKeys))
        if 'debug' in _dict:
            args['debug'] = _dict.get('debug')
        if 'restart' in _dict:
            args['restart'] = _dict.get('restart')
        if 'alternate_intents' in _dict:
            args['alternate_intents'] = _dict.get('alternate_intents')
        if 'return_context' in _dict:
            args['return_context'] = _dict.get('return_context')
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'debug') and self.debug is not None:
            _dict['debug'] = self.debug
        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, 'return_context') and self.return_context is not None:
            _dict['return_context'] = self.return_context
        return _dict

    def __str__(self):
        """Return a `str` version of this MessageInputOptions object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """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):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class MessageOutput(object):
    """
    Assistant output to be rendered or processed by the client.

    :attr list[DialogRuntimeResponseGeneric] 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.
    """

    def __init__(self,
                 generic=None,
                 intents=None,
                 entities=None,
                 actions=None,
                 debug=None,
                 user_defined=None):
        """
        Initialize a MessageOutput object.

        :param list[DialogRuntimeResponseGeneric] 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.
        """
        self.generic = generic
        self.intents = intents
        self.entities = entities
        self.actions = actions
        self.debug = debug
        self.user_defined = user_defined

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a MessageOutput object from a json dictionary."""
        args = {}
        validKeys = [
            'generic', 'intents', 'entities', 'actions', 'debug', 'user_defined'
        ]
        badKeys = set(_dict.keys()) - set(validKeys)
        if badKeys:
            raise ValueError(
                'Unrecognized keys detected in dictionary for class MessageOutput: '
                + ', '.join(badKeys))
        if 'generic' in _dict:
            args['generic'] = [
                DialogRuntimeResponseGeneric._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')
        return cls(**args)

    def _to_dict(self):
        """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
        return _dict

    def __str__(self):
        """Return a `str` version of this MessageOutput object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """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):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class MessageOutputDebug(object):
    """
    Additional detailed information about a message response and how it was generated.

    :attr list[DialogNodesVisited] nodes_visited: (optional) An array of objects
    containing detailed diagnostic information about the nodes that were triggered 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.
    """

    def __init__(self,
                 nodes_visited=None,
                 log_messages=None,
                 branch_exited=None,
                 branch_exited_reason=None):
        """
        Initialize a MessageOutputDebug object.

        :param list[DialogNodesVisited] nodes_visited: (optional) An array of objects
        containing detailed diagnostic information about the nodes that were triggered
        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.
        """
        self.nodes_visited = nodes_visited
        self.log_messages = log_messages
        self.branch_exited = branch_exited
        self.branch_exited_reason = branch_exited_reason

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a MessageOutputDebug object from a json dictionary."""
        args = {}
        validKeys = [
            'nodes_visited', 'log_messages', 'branch_exited',
            'branch_exited_reason'
        ]
        badKeys = set(_dict.keys()) - set(validKeys)
        if badKeys:
            raise ValueError(
                'Unrecognized keys detected in dictionary for class MessageOutputDebug: '
                + ', '.join(badKeys))
        if 'nodes_visited' in _dict:
            args['nodes_visited'] = [
                DialogNodesVisited._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')
        return cls(**args)

    def _to_dict(self):
        """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
        return _dict

    def __str__(self):
        """Return a `str` version of this MessageOutputDebug object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """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):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class MessageResponse(object):
    """
    A response from the Watson Assistant service.

    :attr MessageOutput output: Assistant output to be rendered or processed by the
    client.
    :attr MessageContext context: (optional) State information for the conversation. The
    context is stored by the assistant on a per-session basis. You can use this property
    to access context variables.
    **Note:** The context is included in message responses only if
    **return_context**=`true` in the message request.
    """

    def __init__(self, output, context=None):
        """
        Initialize a MessageResponse object.

        :param MessageOutput output: Assistant output to be rendered or processed by the
        client.
        :param MessageContext context: (optional) State information for the conversation.
        The context is stored by the assistant on a per-session basis. You can use this
        property to access context variables.
        **Note:** The context is included in message responses only if
        **return_context**=`true` in the message request.
        """
        self.output = output
        self.context = context

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a MessageResponse object from a json dictionary."""
        args = {}
        validKeys = ['output', 'context']
        badKeys = set(_dict.keys()) - set(validKeys)
        if badKeys:
            raise ValueError(
                'Unrecognized keys detected in dictionary for class MessageResponse: '
                + ', '.join(badKeys))
        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'))
        return cls(**args)

    def _to_dict(self):
        """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()
        return _dict

    def __str__(self):
        """Return a `str` version of this MessageResponse object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """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):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class RuntimeEntity(object):
    """
    A term from the request that was identified as an entity.

    :attr str entity: An entity detected in the input.
    :attr list[int] location: 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 entity.
    :attr dict metadata: (optional) Any metadata for the entity.
    :attr list[CaptureGroup] groups: (optional) The recognized capture groups for the
    entity, as defined by the entity pattern.
    """

    def __init__(self,
                 entity,
                 location,
                 value,
                 confidence=None,
                 metadata=None,
                 groups=None):
        """
        Initialize a RuntimeEntity object.

        :param str entity: An entity detected in the input.
        :param list[int] location: An array of zero-based character offsets that indicate
        where the detected entity values begin and end in the input text.
        :param str value: The term in the input text that was recognized as an entity
        value.
        :param float confidence: (optional) A decimal percentage that represents Watson's
        confidence in the entity.
        :param dict metadata: (optional) Any metadata for the entity.
        :param list[CaptureGroup] groups: (optional) The recognized capture groups for the
        entity, as defined by the entity pattern.
        """
        self.entity = entity
        self.location = location
        self.value = value
        self.confidence = confidence
        self.metadata = metadata
        self.groups = groups

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a RuntimeEntity object from a json dictionary."""
        args = {}
        validKeys = [
            'entity', 'location', 'value', 'confidence', 'metadata', 'groups'
        ]
        badKeys = set(_dict.keys()) - set(validKeys)
        if badKeys:
            raise ValueError(
                'Unrecognized keys detected in dictionary for class RuntimeEntity: '
                + ', '.join(badKeys))
        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')
        else:
            raise ValueError(
                'Required property \'location\' not present in RuntimeEntity JSON'
            )
        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 'metadata' in _dict:
            args['metadata'] = _dict.get('metadata')
        if 'groups' in _dict:
            args['groups'] = [
                CaptureGroup._from_dict(x) for x in (_dict.get('groups'))
            ]
        return cls(**args)

    def _to_dict(self):
        """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, 'metadata') and self.metadata is not None:
            _dict['metadata'] = self.metadata
        if hasattr(self, 'groups') and self.groups is not None:
            _dict['groups'] = [x._to_dict() for x in self.groups]
        return _dict

    def __str__(self):
        """Return a `str` version of this RuntimeEntity object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """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):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class RuntimeIntent(object):
    """
    An intent identified in the user input.

    :attr str intent: The name of the recognized intent.
    :attr float confidence: A decimal percentage that represents Watson's confidence in
    the intent.
    """

    def __init__(self, intent, confidence):
        """
        Initialize a RuntimeIntent object.

        :param str intent: The name of the recognized intent.
        :param float confidence: A decimal percentage that represents Watson's confidence
        in the intent.
        """
        self.intent = intent
        self.confidence = confidence

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a RuntimeIntent object from a json dictionary."""
        args = {}
        validKeys = ['intent', 'confidence']
        badKeys = set(_dict.keys()) - set(validKeys)
        if badKeys:
            raise ValueError(
                'Unrecognized keys detected in dictionary for class RuntimeIntent: '
                + ', '.join(badKeys))
        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')
        else:
            raise ValueError(
                'Required property \'confidence\' not present in RuntimeIntent JSON'
            )
        return cls(**args)

    def _to_dict(self):
        """Return a json dictionary representing this model."""
        _dict = {}
        if hasattr(self, 'intent') and self.intent is not None:
            _dict['intent'] = self.intent
        if hasattr(self, 'confidence') and self.confidence is not None:
            _dict['confidence'] = self.confidence
        return _dict

    def __str__(self):
        """Return a `str` version of this RuntimeIntent object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """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):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other


class SessionResponse(object):
    """
    SessionResponse.

    :attr str session_id: The session ID.
    """

    def __init__(self, session_id):
        """
        Initialize a SessionResponse object.

        :param str session_id: The session ID.
        """
        self.session_id = session_id

    @classmethod
    def _from_dict(cls, _dict):
        """Initialize a SessionResponse object from a json dictionary."""
        args = {}
        validKeys = ['session_id']
        badKeys = set(_dict.keys()) - set(validKeys)
        if badKeys:
            raise ValueError(
                'Unrecognized keys detected in dictionary for class SessionResponse: '
                + ', '.join(badKeys))
        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)

    def _to_dict(self):
        """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 __str__(self):
        """Return a `str` version of this SessionResponse object."""
        return json.dumps(self._to_dict(), indent=2)

    def __eq__(self, other):
        """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):
        """Return `true` when self and other are not equal, false otherwise."""
        return not self == other