# coding: utf-8
# (C) Copyright IBM Corp. 2019, 2021.
#
# 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: 99-SNAPSHOT-902c9336-20210507-162723
"""
The IBM Watson™ Assistant service combines machine learning, natural language
understanding, and an integrated dialog editor to create conversation flows between your
apps and your users.
The Assistant v1 API provides authoring methods your application can use to create or
update a workspace.
"""
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
##############################################################################
[docs]class AssistantV1(BaseService):
"""The Assistant V1 service."""
DEFAULT_SERVICE_URL = 'https://api.us-south.assistant.watson.cloud.ibm.com'
DEFAULT_SERVICE_NAME = 'assistant'
def __init__(
self,
version: str,
authenticator: Authenticator = None,
service_name: str = DEFAULT_SERVICE_NAME,
) -> None:
"""
Construct a new client for the Assistant service.
:param str version: Release date of the API version you want to use.
Specify dates in YYYY-MM-DD format. The current version is `2020-04-01`.
:param Authenticator authenticator: The authenticator specifies the authentication mechanism.
Get up to date information from https://github.com/IBM/python-sdk-core/blob/master/README.md
about initializing the authenticator of your choice.
"""
if version is None:
raise ValueError('version must be provided')
if not authenticator:
authenticator = get_authenticator_from_environment(service_name)
BaseService.__init__(self,
service_url=self.DEFAULT_SERVICE_URL,
authenticator=authenticator)
self.version = version
self.configure_service(service_name)
#########################
# Message
#########################
[docs] def message(self,
workspace_id: str,
*,
input: 'MessageInput' = None,
intents: List['RuntimeIntent'] = None,
entities: List['RuntimeEntity'] = None,
alternate_intents: bool = None,
context: 'Context' = None,
output: 'OutputData' = None,
user_id: str = None,
nodes_visited_details: bool = None,
**kwargs) -> DetailedResponse:
"""
Get response to user input.
Send user input to a workspace and receive a response.
**Important:** This method has been superseded by the new v2 runtime API. The v2
API offers significant advantages, including ease of deployment, automatic state
management, versioning, and search capabilities. For more information, see the
[documentation](https://cloud.ibm.com/docs/assistant?topic=assistant-api-overview).
:param str workspace_id: Unique identifier of the workspace.
:param MessageInput input: (optional) An input object that includes the
input text.
:param List[RuntimeIntent] intents: (optional) Intents to use when
evaluating the user input. Include intents from the previous response to
continue using those intents rather than trying to recognize intents in the
new input.
:param List[RuntimeEntity] entities: (optional) Entities to use when
evaluating the message. Include entities from the previous response to
continue using those entities rather than detecting entities in the new
input.
:param bool alternate_intents: (optional) Whether to return more than one
intent. A value of `true` indicates that all matching intents are returned.
:param Context context: (optional) State information for the conversation.
To maintain state, include the context from the previous response.
:param OutputData output: (optional) An output object that includes the
response to the user, the dialog nodes that were triggered, and messages
from the log.
:param str user_id: (optional) A string value that identifies the user who
is interacting with the workspace. The client must provide a unique
identifier for each individual end user who accesses the application. For
user-based plans, this user ID is used to identify unique users for billing
purposes. This string cannot contain carriage return, newline, or tab
characters. If no value is specified in the input, **user_id** is
automatically set to the value of **context.conversation_id**.
**Note:** This property is the same as the **user_id** property in the
context metadata. If **user_id** is specified in both locations in a
message request, the value specified at the root is used.
:param bool nodes_visited_details: (optional) Whether to include additional
diagnostic information about the dialog nodes that were visited during
processing of the message.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `dict` result representing a `MessageResponse` object
"""
if workspace_id is None:
raise ValueError('workspace_id must be provided')
if input is not None:
input = convert_model(input)
if intents is not None:
intents = [convert_model(x) for x in intents]
if entities is not None:
entities = [convert_model(x) for x in entities]
if context is not None:
context = convert_model(context)
if output is not None:
output = convert_model(output)
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='message')
headers.update(sdk_headers)
params = {
'version': self.version,
'nodes_visited_details': nodes_visited_details
}
data = {
'input': input,
'intents': intents,
'entities': entities,
'alternate_intents': alternate_intents,
'context': context,
'output': output,
'user_id': user_id
}
data = {k: v for (k, v) in data.items() if v is not None}
data = json.dumps(data)
headers['content-type'] = 'application/json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
path_param_keys = ['workspace_id']
path_param_values = self.encode_path_vars(workspace_id)
path_param_dict = dict(zip(path_param_keys, path_param_values))
url = '/v1/workspaces/{workspace_id}/message'.format(**path_param_dict)
request = self.prepare_request(method='POST',
url=url,
headers=headers,
params=params,
data=data)
response = self.send(request)
return response
#########################
# Bulk classify
#########################
[docs] def bulk_classify(self,
workspace_id: str,
*,
input: List['BulkClassifyUtterance'] = None,
**kwargs) -> DetailedResponse:
"""
Identify intents and entities in multiple user utterances.
Send multiple user inputs to a workspace in a single request and receive
information about the intents and entities recognized in each input. This method
is useful for testing and comparing the performance of different workspaces.
This method is available only with Enterprise with Data Isolation plans.
:param str workspace_id: Unique identifier of the workspace.
:param List[BulkClassifyUtterance] input: (optional) An array of input
utterances to classify.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `dict` result representing a `BulkClassifyResponse` object
"""
if workspace_id is None:
raise ValueError('workspace_id must be provided')
if input is not None:
input = [convert_model(x) for x in input]
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='bulk_classify')
headers.update(sdk_headers)
params = {'version': self.version}
data = {'input': input}
data = {k: v for (k, v) in data.items() if v is not None}
data = json.dumps(data)
headers['content-type'] = 'application/json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
path_param_keys = ['workspace_id']
path_param_values = self.encode_path_vars(workspace_id)
path_param_dict = dict(zip(path_param_keys, path_param_values))
url = '/v1/workspaces/{workspace_id}/bulk_classify'.format(
**path_param_dict)
request = self.prepare_request(method='POST',
url=url,
headers=headers,
params=params,
data=data)
response = self.send(request)
return response
#########################
# Workspaces
#########################
[docs] def list_workspaces(self,
*,
page_limit: int = None,
include_count: bool = None,
sort: str = None,
cursor: str = None,
include_audit: bool = None,
**kwargs) -> DetailedResponse:
"""
List workspaces.
List the workspaces associated with a Watson Assistant service instance.
:param int page_limit: (optional) The number of records to return in each
page of results.
:param bool include_count: (optional) Whether to include information about
the number of records that satisfy the request, regardless of the page
limit. If this parameter is `true`, the `pagination` object in the response
includes the `total` property.
:param str sort: (optional) The attribute by which returned workspaces will
be sorted. To reverse the sort order, prefix the value with a minus sign
(`-`).
:param str cursor: (optional) A token identifying the page of results to
retrieve.
:param bool include_audit: (optional) Whether to include the audit
properties (`created` and `updated` timestamps) in the response.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `dict` result representing a `WorkspaceCollection` object
"""
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='list_workspaces')
headers.update(sdk_headers)
params = {
'version': self.version,
'page_limit': page_limit,
'include_count': include_count,
'sort': sort,
'cursor': cursor,
'include_audit': include_audit
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v1/workspaces'
request = self.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.send(request)
return response
[docs] def create_workspace(self,
*,
name: str = None,
description: str = None,
language: str = None,
dialog_nodes: List['DialogNode'] = None,
counterexamples: List['Counterexample'] = None,
metadata: dict = None,
learning_opt_out: bool = None,
system_settings: 'WorkspaceSystemSettings' = None,
webhooks: List['Webhook'] = None,
intents: List['CreateIntent'] = None,
entities: List['CreateEntity'] = None,
include_audit: bool = None,
**kwargs) -> DetailedResponse:
"""
Create workspace.
Create a workspace based on component objects. You must provide workspace
components defining the content of the new workspace.
:param str name: (optional) The name of the workspace. This string cannot
contain carriage return, newline, or tab characters.
:param str description: (optional) The description of the workspace. This
string cannot contain carriage return, newline, or tab characters.
:param str language: (optional) The language of the workspace.
:param List[DialogNode] dialog_nodes: (optional) An array of objects
describing the dialog nodes in the workspace.
:param List[Counterexample] counterexamples: (optional) An array of objects
defining input examples that have been marked as irrelevant input.
:param dict metadata: (optional) Any metadata related to the workspace.
:param bool learning_opt_out: (optional) Whether training data from the
workspace (including artifacts such as intents and entities) can be used by
IBM for general service improvements. `true` indicates that workspace
training data is not to be used.
:param WorkspaceSystemSettings system_settings: (optional) Global settings
for the workspace.
:param List[Webhook] webhooks: (optional)
:param List[CreateIntent] intents: (optional) An array of objects defining
the intents for the workspace.
:param List[CreateEntity] entities: (optional) An array of objects
describing the entities for the workspace.
:param bool include_audit: (optional) Whether to include the audit
properties (`created` and `updated` timestamps) in the response.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `dict` result representing a `Workspace` object
"""
if dialog_nodes is not None:
dialog_nodes = [convert_model(x) for x in dialog_nodes]
if counterexamples is not None:
counterexamples = [convert_model(x) for x in counterexamples]
if system_settings is not None:
system_settings = convert_model(system_settings)
if webhooks is not None:
webhooks = [convert_model(x) for x in webhooks]
if intents is not None:
intents = [convert_model(x) for x in intents]
if entities is not None:
entities = [convert_model(x) for x in entities]
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='create_workspace')
headers.update(sdk_headers)
params = {'version': self.version, 'include_audit': include_audit}
data = {
'name': name,
'description': description,
'language': language,
'dialog_nodes': dialog_nodes,
'counterexamples': counterexamples,
'metadata': metadata,
'learning_opt_out': learning_opt_out,
'system_settings': system_settings,
'webhooks': webhooks,
'intents': intents,
'entities': entities
}
data = {k: v for (k, v) in data.items() if v is not None}
data = json.dumps(data)
headers['content-type'] = 'application/json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v1/workspaces'
request = self.prepare_request(method='POST',
url=url,
headers=headers,
params=params,
data=data)
response = self.send(request)
return response
[docs] def get_workspace(self,
workspace_id: str,
*,
export: bool = None,
include_audit: bool = None,
sort: str = None,
**kwargs) -> DetailedResponse:
"""
Get information about a workspace.
Get information about a workspace, optionally including all workspace content.
:param str workspace_id: Unique identifier of the workspace.
:param bool export: (optional) Whether to include all element content in
the returned data. If **export**=`false`, the returned data includes only
information about the element itself. If **export**=`true`, all content,
including subelements, is included.
:param bool include_audit: (optional) Whether to include the audit
properties (`created` and `updated` timestamps) in the response.
:param str sort: (optional) Indicates how the returned workspace data will
be sorted. This parameter is valid only if **export**=`true`. Specify
`sort=stable` to sort all workspace objects by unique identifier, in
ascending alphabetical order.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `dict` result representing a `Workspace` object
"""
if workspace_id is None:
raise ValueError('workspace_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='get_workspace')
headers.update(sdk_headers)
params = {
'version': self.version,
'export': export,
'include_audit': include_audit,
'sort': sort
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
path_param_keys = ['workspace_id']
path_param_values = self.encode_path_vars(workspace_id)
path_param_dict = dict(zip(path_param_keys, path_param_values))
url = '/v1/workspaces/{workspace_id}'.format(**path_param_dict)
request = self.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.send(request)
return response
[docs] def update_workspace(self,
workspace_id: str,
*,
name: str = None,
description: str = None,
language: str = None,
dialog_nodes: List['DialogNode'] = None,
counterexamples: List['Counterexample'] = None,
metadata: dict = None,
learning_opt_out: bool = None,
system_settings: 'WorkspaceSystemSettings' = None,
webhooks: List['Webhook'] = None,
intents: List['CreateIntent'] = None,
entities: List['CreateEntity'] = None,
append: bool = None,
include_audit: bool = None,
**kwargs) -> DetailedResponse:
"""
Update workspace.
Update an existing workspace with new or modified data. You must provide component
objects defining the content of the updated workspace.
:param str workspace_id: Unique identifier of the workspace.
:param str name: (optional) The name of the workspace. This string cannot
contain carriage return, newline, or tab characters.
:param str description: (optional) The description of the workspace. This
string cannot contain carriage return, newline, or tab characters.
:param str language: (optional) The language of the workspace.
:param List[DialogNode] dialog_nodes: (optional) An array of objects
describing the dialog nodes in the workspace.
:param List[Counterexample] counterexamples: (optional) An array of objects
defining input examples that have been marked as irrelevant input.
:param dict metadata: (optional) Any metadata related to the workspace.
:param bool learning_opt_out: (optional) Whether training data from the
workspace (including artifacts such as intents and entities) can be used by
IBM for general service improvements. `true` indicates that workspace
training data is not to be used.
:param WorkspaceSystemSettings system_settings: (optional) Global settings
for the workspace.
:param List[Webhook] webhooks: (optional)
:param List[CreateIntent] intents: (optional) An array of objects defining
the intents for the workspace.
:param List[CreateEntity] entities: (optional) An array of objects
describing the entities for the workspace.
:param bool append: (optional) Whether the new data is to be appended to
the existing data in the object. If **append**=`false`, elements included
in the new data completely replace the corresponding existing elements,
including all subelements. For example, if the new data for a workspace
includes **entities** and **append**=`false`, all existing entities in the
workspace are discarded and replaced with the new entities.
If **append**=`true`, existing elements are preserved, and the new elements
are added. If any elements in the new data collide with existing elements,
the update request fails.
:param bool include_audit: (optional) Whether to include the audit
properties (`created` and `updated` timestamps) in the response.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `dict` result representing a `Workspace` object
"""
if workspace_id is None:
raise ValueError('workspace_id must be provided')
if dialog_nodes is not None:
dialog_nodes = [convert_model(x) for x in dialog_nodes]
if counterexamples is not None:
counterexamples = [convert_model(x) for x in counterexamples]
if system_settings is not None:
system_settings = convert_model(system_settings)
if webhooks is not None:
webhooks = [convert_model(x) for x in webhooks]
if intents is not None:
intents = [convert_model(x) for x in intents]
if entities is not None:
entities = [convert_model(x) for x in entities]
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='update_workspace')
headers.update(sdk_headers)
params = {
'version': self.version,
'append': append,
'include_audit': include_audit
}
data = {
'name': name,
'description': description,
'language': language,
'dialog_nodes': dialog_nodes,
'counterexamples': counterexamples,
'metadata': metadata,
'learning_opt_out': learning_opt_out,
'system_settings': system_settings,
'webhooks': webhooks,
'intents': intents,
'entities': entities
}
data = {k: v for (k, v) in data.items() if v is not None}
data = json.dumps(data)
headers['content-type'] = 'application/json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
path_param_keys = ['workspace_id']
path_param_values = self.encode_path_vars(workspace_id)
path_param_dict = dict(zip(path_param_keys, path_param_values))
url = '/v1/workspaces/{workspace_id}'.format(**path_param_dict)
request = self.prepare_request(method='POST',
url=url,
headers=headers,
params=params,
data=data)
response = self.send(request)
return response
[docs] def delete_workspace(self, workspace_id: str, **kwargs) -> DetailedResponse:
"""
Delete workspace.
Delete a workspace from the service instance.
:param str workspace_id: Unique identifier of the workspace.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse
"""
if workspace_id is None:
raise ValueError('workspace_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='delete_workspace')
headers.update(sdk_headers)
params = {'version': self.version}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
path_param_keys = ['workspace_id']
path_param_values = self.encode_path_vars(workspace_id)
path_param_dict = dict(zip(path_param_keys, path_param_values))
url = '/v1/workspaces/{workspace_id}'.format(**path_param_dict)
request = self.prepare_request(method='DELETE',
url=url,
headers=headers,
params=params)
response = self.send(request)
return response
#########################
# Intents
#########################
[docs] def list_intents(self,
workspace_id: str,
*,
export: bool = None,
page_limit: int = None,
include_count: bool = None,
sort: str = None,
cursor: str = None,
include_audit: bool = None,
**kwargs) -> DetailedResponse:
"""
List intents.
List the intents for a workspace.
:param str workspace_id: Unique identifier of the workspace.
:param bool export: (optional) Whether to include all element content in
the returned data. If **export**=`false`, the returned data includes only
information about the element itself. If **export**=`true`, all content,
including subelements, is included.
:param int page_limit: (optional) The number of records to return in each
page of results.
:param bool include_count: (optional) Whether to include information about
the number of records that satisfy the request, regardless of the page
limit. If this parameter is `true`, the `pagination` object in the response
includes the `total` property.
:param str sort: (optional) The attribute by which returned intents will be
sorted. To reverse the sort order, prefix the value with a minus sign
(`-`).
:param str cursor: (optional) A token identifying the page of results to
retrieve.
:param bool include_audit: (optional) Whether to include the audit
properties (`created` and `updated` timestamps) in the response.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `dict` result representing a `IntentCollection` object
"""
if workspace_id is None:
raise ValueError('workspace_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='list_intents')
headers.update(sdk_headers)
params = {
'version': self.version,
'export': export,
'page_limit': page_limit,
'include_count': include_count,
'sort': sort,
'cursor': cursor,
'include_audit': include_audit
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
path_param_keys = ['workspace_id']
path_param_values = self.encode_path_vars(workspace_id)
path_param_dict = dict(zip(path_param_keys, path_param_values))
url = '/v1/workspaces/{workspace_id}/intents'.format(**path_param_dict)
request = self.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.send(request)
return response
[docs] def create_intent(self,
workspace_id: str,
intent: str,
*,
description: str = None,
examples: List['Example'] = None,
include_audit: bool = None,
**kwargs) -> DetailedResponse:
"""
Create intent.
Create a new intent.
If you want to create multiple intents with a single API call, consider using the
**[Update workspace](#update-workspace)** method instead.
:param str workspace_id: Unique identifier of the workspace.
:param str intent: The name of the intent. This string must conform to the
following restrictions:
- It can contain only Unicode alphanumeric, underscore, hyphen, and dot
characters.
- It cannot begin with the reserved prefix `sys-`.
:param str description: (optional) The description of the intent. This
string cannot contain carriage return, newline, or tab characters.
:param List[Example] examples: (optional) An array of user input examples
for the intent.
:param bool include_audit: (optional) Whether to include the audit
properties (`created` and `updated` timestamps) in the response.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `dict` result representing a `Intent` object
"""
if workspace_id is None:
raise ValueError('workspace_id must be provided')
if intent is None:
raise ValueError('intent must be provided')
if examples is not None:
examples = [convert_model(x) for x in examples]
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='create_intent')
headers.update(sdk_headers)
params = {'version': self.version, 'include_audit': include_audit}
data = {
'intent': intent,
'description': description,
'examples': examples
}
data = {k: v for (k, v) in data.items() if v is not None}
data = json.dumps(data)
headers['content-type'] = 'application/json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
path_param_keys = ['workspace_id']
path_param_values = self.encode_path_vars(workspace_id)
path_param_dict = dict(zip(path_param_keys, path_param_values))
url = '/v1/workspaces/{workspace_id}/intents'.format(**path_param_dict)
request = self.prepare_request(method='POST',
url=url,
headers=headers,
params=params,
data=data)
response = self.send(request)
return response
[docs] def get_intent(self,
workspace_id: str,
intent: str,
*,
export: bool = None,
include_audit: bool = None,
**kwargs) -> DetailedResponse:
"""
Get intent.
Get information about an intent, optionally including all intent content.
:param str workspace_id: Unique identifier of the workspace.
:param str intent: The intent name.
:param bool export: (optional) Whether to include all element content in
the returned data. If **export**=`false`, the returned data includes only
information about the element itself. If **export**=`true`, all content,
including subelements, is included.
:param bool include_audit: (optional) Whether to include the audit
properties (`created` and `updated` timestamps) in the response.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `dict` result representing a `Intent` object
"""
if workspace_id is None:
raise ValueError('workspace_id must be provided')
if intent is None:
raise ValueError('intent must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='get_intent')
headers.update(sdk_headers)
params = {
'version': self.version,
'export': export,
'include_audit': include_audit
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
path_param_keys = ['workspace_id', 'intent']
path_param_values = self.encode_path_vars(workspace_id, intent)
path_param_dict = dict(zip(path_param_keys, path_param_values))
url = '/v1/workspaces/{workspace_id}/intents/{intent}'.format(
**path_param_dict)
request = self.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.send(request)
return response
[docs] def update_intent(self,
workspace_id: str,
intent: str,
*,
new_intent: str = None,
new_description: str = None,
new_examples: List['Example'] = None,
append: bool = None,
include_audit: bool = None,
**kwargs) -> DetailedResponse:
"""
Update intent.
Update an existing intent with new or modified data. You must provide component
objects defining the content of the updated intent.
If you want to update multiple intents with a single API call, consider using the
**[Update workspace](#update-workspace)** method instead.
:param str workspace_id: Unique identifier of the workspace.
:param str intent: The intent name.
:param str new_intent: (optional) The name of the intent. This string must
conform to the following restrictions:
- It can contain only Unicode alphanumeric, underscore, hyphen, and dot
characters.
- It cannot begin with the reserved prefix `sys-`.
:param str new_description: (optional) The description of the intent. This
string cannot contain carriage return, newline, or tab characters.
:param List[Example] new_examples: (optional) An array of user input
examples for the intent.
:param bool append: (optional) Whether the new data is to be appended to
the existing data in the object. If **append**=`false`, elements included
in the new data completely replace the corresponding existing elements,
including all subelements. For example, if the new data for the intent
includes **examples** and **append**=`false`, all existing examples for the
intent are discarded and replaced with the new examples.
If **append**=`true`, existing elements are preserved, and the new elements
are added. If any elements in the new data collide with existing elements,
the update request fails.
:param bool include_audit: (optional) Whether to include the audit
properties (`created` and `updated` timestamps) in the response.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `dict` result representing a `Intent` object
"""
if workspace_id is None:
raise ValueError('workspace_id must be provided')
if intent is None:
raise ValueError('intent must be provided')
if new_examples is not None:
new_examples = [convert_model(x) for x in new_examples]
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='update_intent')
headers.update(sdk_headers)
params = {
'version': self.version,
'append': append,
'include_audit': include_audit
}
data = {
'intent': new_intent,
'description': new_description,
'examples': new_examples
}
data = {k: v for (k, v) in data.items() if v is not None}
data = json.dumps(data)
headers['content-type'] = 'application/json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
path_param_keys = ['workspace_id', 'intent']
path_param_values = self.encode_path_vars(workspace_id, intent)
path_param_dict = dict(zip(path_param_keys, path_param_values))
url = '/v1/workspaces/{workspace_id}/intents/{intent}'.format(
**path_param_dict)
request = self.prepare_request(method='POST',
url=url,
headers=headers,
params=params,
data=data)
response = self.send(request)
return response
[docs] def delete_intent(self, workspace_id: str, intent: str,
**kwargs) -> DetailedResponse:
"""
Delete intent.
Delete an intent from a workspace.
:param str workspace_id: Unique identifier of the workspace.
:param str intent: The intent name.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse
"""
if workspace_id is None:
raise ValueError('workspace_id must be provided')
if intent is None:
raise ValueError('intent must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='delete_intent')
headers.update(sdk_headers)
params = {'version': self.version}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
path_param_keys = ['workspace_id', 'intent']
path_param_values = self.encode_path_vars(workspace_id, intent)
path_param_dict = dict(zip(path_param_keys, path_param_values))
url = '/v1/workspaces/{workspace_id}/intents/{intent}'.format(
**path_param_dict)
request = self.prepare_request(method='DELETE',
url=url,
headers=headers,
params=params)
response = self.send(request)
return response
#########################
# Examples
#########################
[docs] def list_examples(self,
workspace_id: str,
intent: str,
*,
page_limit: int = None,
include_count: bool = None,
sort: str = None,
cursor: str = None,
include_audit: bool = None,
**kwargs) -> DetailedResponse:
"""
List user input examples.
List the user input examples for an intent, optionally including contextual entity
mentions.
:param str workspace_id: Unique identifier of the workspace.
:param str intent: The intent name.
:param int page_limit: (optional) The number of records to return in each
page of results.
:param bool include_count: (optional) Whether to include information about
the number of records that satisfy the request, regardless of the page
limit. If this parameter is `true`, the `pagination` object in the response
includes the `total` property.
:param str sort: (optional) The attribute by which returned examples will
be sorted. To reverse the sort order, prefix the value with a minus sign
(`-`).
:param str cursor: (optional) A token identifying the page of results to
retrieve.
:param bool include_audit: (optional) Whether to include the audit
properties (`created` and `updated` timestamps) in the response.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `dict` result representing a `ExampleCollection` object
"""
if workspace_id is None:
raise ValueError('workspace_id must be provided')
if intent is None:
raise ValueError('intent must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='list_examples')
headers.update(sdk_headers)
params = {
'version': self.version,
'page_limit': page_limit,
'include_count': include_count,
'sort': sort,
'cursor': cursor,
'include_audit': include_audit
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
path_param_keys = ['workspace_id', 'intent']
path_param_values = self.encode_path_vars(workspace_id, intent)
path_param_dict = dict(zip(path_param_keys, path_param_values))
url = '/v1/workspaces/{workspace_id}/intents/{intent}/examples'.format(
**path_param_dict)
request = self.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.send(request)
return response
[docs] def create_example(self,
workspace_id: str,
intent: str,
text: str,
*,
mentions: List['Mention'] = None,
include_audit: bool = None,
**kwargs) -> DetailedResponse:
"""
Create user input example.
Add a new user input example to an intent.
If you want to add multiple examples with a single API call, consider using the
**[Update intent](#update-intent)** method instead.
:param str workspace_id: Unique identifier of the workspace.
:param str intent: The intent name.
:param str text: The text of a user input example. This string must conform
to the following restrictions:
- It cannot contain carriage return, newline, or tab characters.
- It cannot consist of only whitespace characters.
:param List[Mention] mentions: (optional) An array of contextual entity
mentions.
:param bool include_audit: (optional) Whether to include the audit
properties (`created` and `updated` timestamps) in the response.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `dict` result representing a `Example` object
"""
if workspace_id is None:
raise ValueError('workspace_id must be provided')
if intent is None:
raise ValueError('intent must be provided')
if text is None:
raise ValueError('text must be provided')
if mentions is not None:
mentions = [convert_model(x) for x in mentions]
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='create_example')
headers.update(sdk_headers)
params = {'version': self.version, 'include_audit': include_audit}
data = {'text': text, 'mentions': mentions}
data = {k: v for (k, v) in data.items() if v is not None}
data = json.dumps(data)
headers['content-type'] = 'application/json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
path_param_keys = ['workspace_id', 'intent']
path_param_values = self.encode_path_vars(workspace_id, intent)
path_param_dict = dict(zip(path_param_keys, path_param_values))
url = '/v1/workspaces/{workspace_id}/intents/{intent}/examples'.format(
**path_param_dict)
request = self.prepare_request(method='POST',
url=url,
headers=headers,
params=params,
data=data)
response = self.send(request)
return response
[docs] def get_example(self,
workspace_id: str,
intent: str,
text: str,
*,
include_audit: bool = None,
**kwargs) -> DetailedResponse:
"""
Get user input example.
Get information about a user input example.
:param str workspace_id: Unique identifier of the workspace.
:param str intent: The intent name.
:param str text: The text of the user input example.
:param bool include_audit: (optional) Whether to include the audit
properties (`created` and `updated` timestamps) in the response.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `dict` result representing a `Example` object
"""
if workspace_id is None:
raise ValueError('workspace_id must be provided')
if intent is None:
raise ValueError('intent must be provided')
if text is None:
raise ValueError('text must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='get_example')
headers.update(sdk_headers)
params = {'version': self.version, 'include_audit': include_audit}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
path_param_keys = ['workspace_id', 'intent', 'text']
path_param_values = self.encode_path_vars(workspace_id, intent, text)
path_param_dict = dict(zip(path_param_keys, path_param_values))
url = '/v1/workspaces/{workspace_id}/intents/{intent}/examples/{text}'.format(
**path_param_dict)
request = self.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.send(request)
return response
[docs] def update_example(self,
workspace_id: str,
intent: str,
text: str,
*,
new_text: str = None,
new_mentions: List['Mention'] = None,
include_audit: bool = None,
**kwargs) -> DetailedResponse:
"""
Update user input example.
Update the text of a user input example.
If you want to update multiple examples with a single API call, consider using the
**[Update intent](#update-intent)** method instead.
:param str workspace_id: Unique identifier of the workspace.
:param str intent: The intent name.
:param str text: The text of the user input example.
:param str new_text: (optional) The text of the user input example. This
string must conform to the following restrictions:
- It cannot contain carriage return, newline, or tab characters.
- It cannot consist of only whitespace characters.
:param List[Mention] new_mentions: (optional) An array of contextual entity
mentions.
:param bool include_audit: (optional) Whether to include the audit
properties (`created` and `updated` timestamps) in the response.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `dict` result representing a `Example` object
"""
if workspace_id is None:
raise ValueError('workspace_id must be provided')
if intent is None:
raise ValueError('intent must be provided')
if text is None:
raise ValueError('text must be provided')
if new_mentions is not None:
new_mentions = [convert_model(x) for x in new_mentions]
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='update_example')
headers.update(sdk_headers)
params = {'version': self.version, 'include_audit': include_audit}
data = {'text': new_text, 'mentions': new_mentions}
data = {k: v for (k, v) in data.items() if v is not None}
data = json.dumps(data)
headers['content-type'] = 'application/json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
path_param_keys = ['workspace_id', 'intent', 'text']
path_param_values = self.encode_path_vars(workspace_id, intent, text)
path_param_dict = dict(zip(path_param_keys, path_param_values))
url = '/v1/workspaces/{workspace_id}/intents/{intent}/examples/{text}'.format(
**path_param_dict)
request = self.prepare_request(method='POST',
url=url,
headers=headers,
params=params,
data=data)
response = self.send(request)
return response
[docs] def delete_example(self, workspace_id: str, intent: str, text: str,
**kwargs) -> DetailedResponse:
"""
Delete user input example.
Delete a user input example from an intent.
:param str workspace_id: Unique identifier of the workspace.
:param str intent: The intent name.
:param str text: The text of the user input example.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse
"""
if workspace_id is None:
raise ValueError('workspace_id must be provided')
if intent is None:
raise ValueError('intent must be provided')
if text is None:
raise ValueError('text must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='delete_example')
headers.update(sdk_headers)
params = {'version': self.version}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
path_param_keys = ['workspace_id', 'intent', 'text']
path_param_values = self.encode_path_vars(workspace_id, intent, text)
path_param_dict = dict(zip(path_param_keys, path_param_values))
url = '/v1/workspaces/{workspace_id}/intents/{intent}/examples/{text}'.format(
**path_param_dict)
request = self.prepare_request(method='DELETE',
url=url,
headers=headers,
params=params)
response = self.send(request)
return response
#########################
# Counterexamples
#########################
[docs] def list_counterexamples(self,
workspace_id: str,
*,
page_limit: int = None,
include_count: bool = None,
sort: str = None,
cursor: str = None,
include_audit: bool = None,
**kwargs) -> DetailedResponse:
"""
List counterexamples.
List the counterexamples for a workspace. Counterexamples are examples that have
been marked as irrelevant input.
:param str workspace_id: Unique identifier of the workspace.
:param int page_limit: (optional) The number of records to return in each
page of results.
:param bool include_count: (optional) Whether to include information about
the number of records that satisfy the request, regardless of the page
limit. If this parameter is `true`, the `pagination` object in the response
includes the `total` property.
:param str sort: (optional) The attribute by which returned counterexamples
will be sorted. To reverse the sort order, prefix the value with a minus
sign (`-`).
:param str cursor: (optional) A token identifying the page of results to
retrieve.
:param bool include_audit: (optional) Whether to include the audit
properties (`created` and `updated` timestamps) in the response.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `dict` result representing a `CounterexampleCollection` object
"""
if workspace_id is None:
raise ValueError('workspace_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='list_counterexamples')
headers.update(sdk_headers)
params = {
'version': self.version,
'page_limit': page_limit,
'include_count': include_count,
'sort': sort,
'cursor': cursor,
'include_audit': include_audit
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
path_param_keys = ['workspace_id']
path_param_values = self.encode_path_vars(workspace_id)
path_param_dict = dict(zip(path_param_keys, path_param_values))
url = '/v1/workspaces/{workspace_id}/counterexamples'.format(
**path_param_dict)
request = self.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.send(request)
return response
[docs] def create_counterexample(self,
workspace_id: str,
text: str,
*,
include_audit: bool = None,
**kwargs) -> DetailedResponse:
"""
Create counterexample.
Add a new counterexample to a workspace. Counterexamples are examples that have
been marked as irrelevant input.
If you want to add multiple counterexamples with a single API call, consider using
the **[Update workspace](#update-workspace)** method instead.
:param str workspace_id: Unique identifier of the workspace.
:param str text: The text of a user input marked as irrelevant input. This
string must conform to the following restrictions:
- It cannot contain carriage return, newline, or tab characters.
- It cannot consist of only whitespace characters.
:param bool include_audit: (optional) Whether to include the audit
properties (`created` and `updated` timestamps) in the response.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `dict` result representing a `Counterexample` object
"""
if workspace_id is None:
raise ValueError('workspace_id must be provided')
if text is None:
raise ValueError('text must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='create_counterexample')
headers.update(sdk_headers)
params = {'version': self.version, 'include_audit': include_audit}
data = {'text': text}
data = {k: v for (k, v) in data.items() if v is not None}
data = json.dumps(data)
headers['content-type'] = 'application/json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
path_param_keys = ['workspace_id']
path_param_values = self.encode_path_vars(workspace_id)
path_param_dict = dict(zip(path_param_keys, path_param_values))
url = '/v1/workspaces/{workspace_id}/counterexamples'.format(
**path_param_dict)
request = self.prepare_request(method='POST',
url=url,
headers=headers,
params=params,
data=data)
response = self.send(request)
return response
[docs] def get_counterexample(self,
workspace_id: str,
text: str,
*,
include_audit: bool = None,
**kwargs) -> DetailedResponse:
"""
Get counterexample.
Get information about a counterexample. Counterexamples are examples that have
been marked as irrelevant input.
:param str workspace_id: Unique identifier of the workspace.
:param str text: The text of a user input counterexample (for example,
`What are you wearing?`).
:param bool include_audit: (optional) Whether to include the audit
properties (`created` and `updated` timestamps) in the response.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `dict` result representing a `Counterexample` object
"""
if workspace_id is None:
raise ValueError('workspace_id must be provided')
if text is None:
raise ValueError('text must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='get_counterexample')
headers.update(sdk_headers)
params = {'version': self.version, 'include_audit': include_audit}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
path_param_keys = ['workspace_id', 'text']
path_param_values = self.encode_path_vars(workspace_id, text)
path_param_dict = dict(zip(path_param_keys, path_param_values))
url = '/v1/workspaces/{workspace_id}/counterexamples/{text}'.format(
**path_param_dict)
request = self.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.send(request)
return response
[docs] def update_counterexample(self,
workspace_id: str,
text: str,
*,
new_text: str = None,
include_audit: bool = None,
**kwargs) -> DetailedResponse:
"""
Update counterexample.
Update the text of a counterexample. Counterexamples are examples that have been
marked as irrelevant input.
:param str workspace_id: Unique identifier of the workspace.
:param str text: The text of a user input counterexample (for example,
`What are you wearing?`).
:param str new_text: (optional) The text of a user input marked as
irrelevant input. This string must conform to the following restrictions:
- It cannot contain carriage return, newline, or tab characters.
- It cannot consist of only whitespace characters.
:param bool include_audit: (optional) Whether to include the audit
properties (`created` and `updated` timestamps) in the response.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `dict` result representing a `Counterexample` object
"""
if workspace_id is None:
raise ValueError('workspace_id must be provided')
if text is None:
raise ValueError('text must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='update_counterexample')
headers.update(sdk_headers)
params = {'version': self.version, 'include_audit': include_audit}
data = {'text': new_text}
data = {k: v for (k, v) in data.items() if v is not None}
data = json.dumps(data)
headers['content-type'] = 'application/json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
path_param_keys = ['workspace_id', 'text']
path_param_values = self.encode_path_vars(workspace_id, text)
path_param_dict = dict(zip(path_param_keys, path_param_values))
url = '/v1/workspaces/{workspace_id}/counterexamples/{text}'.format(
**path_param_dict)
request = self.prepare_request(method='POST',
url=url,
headers=headers,
params=params,
data=data)
response = self.send(request)
return response
[docs] def delete_counterexample(self, workspace_id: str, text: str,
**kwargs) -> DetailedResponse:
"""
Delete counterexample.
Delete a counterexample from a workspace. Counterexamples are examples that have
been marked as irrelevant input.
:param str workspace_id: Unique identifier of the workspace.
:param str text: The text of a user input counterexample (for example,
`What are you wearing?`).
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse
"""
if workspace_id is None:
raise ValueError('workspace_id must be provided')
if text is None:
raise ValueError('text must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='delete_counterexample')
headers.update(sdk_headers)
params = {'version': self.version}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
path_param_keys = ['workspace_id', 'text']
path_param_values = self.encode_path_vars(workspace_id, text)
path_param_dict = dict(zip(path_param_keys, path_param_values))
url = '/v1/workspaces/{workspace_id}/counterexamples/{text}'.format(
**path_param_dict)
request = self.prepare_request(method='DELETE',
url=url,
headers=headers,
params=params)
response = self.send(request)
return response
#########################
# Entities
#########################
[docs] def list_entities(self,
workspace_id: str,
*,
export: bool = None,
page_limit: int = None,
include_count: bool = None,
sort: str = None,
cursor: str = None,
include_audit: bool = None,
**kwargs) -> DetailedResponse:
"""
List entities.
List the entities for a workspace.
:param str workspace_id: Unique identifier of the workspace.
:param bool export: (optional) Whether to include all element content in
the returned data. If **export**=`false`, the returned data includes only
information about the element itself. If **export**=`true`, all content,
including subelements, is included.
:param int page_limit: (optional) The number of records to return in each
page of results.
:param bool include_count: (optional) Whether to include information about
the number of records that satisfy the request, regardless of the page
limit. If this parameter is `true`, the `pagination` object in the response
includes the `total` property.
:param str sort: (optional) The attribute by which returned entities will
be sorted. To reverse the sort order, prefix the value with a minus sign
(`-`).
:param str cursor: (optional) A token identifying the page of results to
retrieve.
:param bool include_audit: (optional) Whether to include the audit
properties (`created` and `updated` timestamps) in the response.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `dict` result representing a `EntityCollection` object
"""
if workspace_id is None:
raise ValueError('workspace_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='list_entities')
headers.update(sdk_headers)
params = {
'version': self.version,
'export': export,
'page_limit': page_limit,
'include_count': include_count,
'sort': sort,
'cursor': cursor,
'include_audit': include_audit
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
path_param_keys = ['workspace_id']
path_param_values = self.encode_path_vars(workspace_id)
path_param_dict = dict(zip(path_param_keys, path_param_values))
url = '/v1/workspaces/{workspace_id}/entities'.format(**path_param_dict)
request = self.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.send(request)
return response
[docs] def create_entity(self,
workspace_id: str,
entity: str,
*,
description: str = None,
metadata: dict = None,
fuzzy_match: bool = None,
values: List['CreateValue'] = None,
include_audit: bool = None,
**kwargs) -> DetailedResponse:
"""
Create entity.
Create a new entity, or enable a system entity.
If you want to create multiple entities with a single API call, consider using the
**[Update workspace](#update-workspace)** method instead.
:param str workspace_id: Unique identifier of the workspace.
:param str entity: The name of the entity. This string must conform to the
following restrictions:
- It can contain only Unicode alphanumeric, underscore, and hyphen
characters.
- If you specify an entity name beginning with the reserved prefix `sys-`,
it must be the name of a system entity that you want to enable. (Any entity
content specified with the request is ignored.).
:param str description: (optional) The description of the entity. This
string cannot contain carriage return, newline, or tab characters.
:param dict metadata: (optional) Any metadata related to the entity.
:param bool fuzzy_match: (optional) Whether to use fuzzy matching for the
entity.
:param List[CreateValue] values: (optional) An array of objects describing
the entity values.
:param bool include_audit: (optional) Whether to include the audit
properties (`created` and `updated` timestamps) in the response.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `dict` result representing a `Entity` object
"""
if workspace_id is None:
raise ValueError('workspace_id must be provided')
if entity is None:
raise ValueError('entity must be provided')
if values is not None:
values = [convert_model(x) for x in values]
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='create_entity')
headers.update(sdk_headers)
params = {'version': self.version, 'include_audit': include_audit}
data = {
'entity': entity,
'description': description,
'metadata': metadata,
'fuzzy_match': fuzzy_match,
'values': values
}
data = {k: v for (k, v) in data.items() if v is not None}
data = json.dumps(data)
headers['content-type'] = 'application/json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
path_param_keys = ['workspace_id']
path_param_values = self.encode_path_vars(workspace_id)
path_param_dict = dict(zip(path_param_keys, path_param_values))
url = '/v1/workspaces/{workspace_id}/entities'.format(**path_param_dict)
request = self.prepare_request(method='POST',
url=url,
headers=headers,
params=params,
data=data)
response = self.send(request)
return response
[docs] def get_entity(self,
workspace_id: str,
entity: str,
*,
export: bool = None,
include_audit: bool = None,
**kwargs) -> DetailedResponse:
"""
Get entity.
Get information about an entity, optionally including all entity content.
:param str workspace_id: Unique identifier of the workspace.
:param str entity: The name of the entity.
:param bool export: (optional) Whether to include all element content in
the returned data. If **export**=`false`, the returned data includes only
information about the element itself. If **export**=`true`, all content,
including subelements, is included.
:param bool include_audit: (optional) Whether to include the audit
properties (`created` and `updated` timestamps) in the response.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `dict` result representing a `Entity` object
"""
if workspace_id is None:
raise ValueError('workspace_id must be provided')
if entity is None:
raise ValueError('entity must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='get_entity')
headers.update(sdk_headers)
params = {
'version': self.version,
'export': export,
'include_audit': include_audit
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
path_param_keys = ['workspace_id', 'entity']
path_param_values = self.encode_path_vars(workspace_id, entity)
path_param_dict = dict(zip(path_param_keys, path_param_values))
url = '/v1/workspaces/{workspace_id}/entities/{entity}'.format(
**path_param_dict)
request = self.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.send(request)
return response
[docs] def update_entity(self,
workspace_id: str,
entity: str,
*,
new_entity: str = None,
new_description: str = None,
new_metadata: dict = None,
new_fuzzy_match: bool = None,
new_values: List['CreateValue'] = None,
append: bool = None,
include_audit: bool = None,
**kwargs) -> DetailedResponse:
"""
Update entity.
Update an existing entity with new or modified data. You must provide component
objects defining the content of the updated entity.
If you want to update multiple entities with a single API call, consider using the
**[Update workspace](#update-workspace)** method instead.
:param str workspace_id: Unique identifier of the workspace.
:param str entity: The name of the entity.
:param str new_entity: (optional) The name of the entity. This string must
conform to the following restrictions:
- It can contain only Unicode alphanumeric, underscore, and hyphen
characters.
- It cannot begin with the reserved prefix `sys-`.
:param str new_description: (optional) The description of the entity. This
string cannot contain carriage return, newline, or tab characters.
:param dict new_metadata: (optional) Any metadata related to the entity.
:param bool new_fuzzy_match: (optional) Whether to use fuzzy matching for
the entity.
:param List[CreateValue] new_values: (optional) An array of objects
describing the entity values.
:param bool append: (optional) Whether the new data is to be appended to
the existing data in the entity. If **append**=`false`, elements included
in the new data completely replace the corresponding existing elements,
including all subelements. For example, if the new data for the entity
includes **values** and **append**=`false`, all existing values for the
entity are discarded and replaced with the new values.
If **append**=`true`, existing elements are preserved, and the new elements
are added. If any elements in the new data collide with existing elements,
the update request fails.
:param bool include_audit: (optional) Whether to include the audit
properties (`created` and `updated` timestamps) in the response.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `dict` result representing a `Entity` object
"""
if workspace_id is None:
raise ValueError('workspace_id must be provided')
if entity is None:
raise ValueError('entity must be provided')
if new_values is not None:
new_values = [convert_model(x) for x in new_values]
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='update_entity')
headers.update(sdk_headers)
params = {
'version': self.version,
'append': append,
'include_audit': include_audit
}
data = {
'entity': new_entity,
'description': new_description,
'metadata': new_metadata,
'fuzzy_match': new_fuzzy_match,
'values': new_values
}
data = {k: v for (k, v) in data.items() if v is not None}
data = json.dumps(data)
headers['content-type'] = 'application/json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
path_param_keys = ['workspace_id', 'entity']
path_param_values = self.encode_path_vars(workspace_id, entity)
path_param_dict = dict(zip(path_param_keys, path_param_values))
url = '/v1/workspaces/{workspace_id}/entities/{entity}'.format(
**path_param_dict)
request = self.prepare_request(method='POST',
url=url,
headers=headers,
params=params,
data=data)
response = self.send(request)
return response
[docs] def delete_entity(self, workspace_id: str, entity: str,
**kwargs) -> DetailedResponse:
"""
Delete entity.
Delete an entity from a workspace, or disable a system entity.
:param str workspace_id: Unique identifier of the workspace.
:param str entity: The name of the entity.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse
"""
if workspace_id is None:
raise ValueError('workspace_id must be provided')
if entity is None:
raise ValueError('entity must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='delete_entity')
headers.update(sdk_headers)
params = {'version': self.version}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
path_param_keys = ['workspace_id', 'entity']
path_param_values = self.encode_path_vars(workspace_id, entity)
path_param_dict = dict(zip(path_param_keys, path_param_values))
url = '/v1/workspaces/{workspace_id}/entities/{entity}'.format(
**path_param_dict)
request = self.prepare_request(method='DELETE',
url=url,
headers=headers,
params=params)
response = self.send(request)
return response
#########################
# Mentions
#########################
[docs] def list_mentions(self,
workspace_id: str,
entity: str,
*,
export: bool = None,
include_audit: bool = None,
**kwargs) -> DetailedResponse:
"""
List entity mentions.
List mentions for a contextual entity. An entity mention is an occurrence of a
contextual entity in the context of an intent user input example.
:param str workspace_id: Unique identifier of the workspace.
:param str entity: The name of the entity.
:param bool export: (optional) Whether to include all element content in
the returned data. If **export**=`false`, the returned data includes only
information about the element itself. If **export**=`true`, all content,
including subelements, is included.
:param bool include_audit: (optional) Whether to include the audit
properties (`created` and `updated` timestamps) in the response.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `dict` result representing a `EntityMentionCollection` object
"""
if workspace_id is None:
raise ValueError('workspace_id must be provided')
if entity is None:
raise ValueError('entity must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='list_mentions')
headers.update(sdk_headers)
params = {
'version': self.version,
'export': export,
'include_audit': include_audit
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
path_param_keys = ['workspace_id', 'entity']
path_param_values = self.encode_path_vars(workspace_id, entity)
path_param_dict = dict(zip(path_param_keys, path_param_values))
url = '/v1/workspaces/{workspace_id}/entities/{entity}/mentions'.format(
**path_param_dict)
request = self.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.send(request)
return response
#########################
# Values
#########################
[docs] def list_values(self,
workspace_id: str,
entity: str,
*,
export: bool = None,
page_limit: int = None,
include_count: bool = None,
sort: str = None,
cursor: str = None,
include_audit: bool = None,
**kwargs) -> DetailedResponse:
"""
List entity values.
List the values for an entity.
:param str workspace_id: Unique identifier of the workspace.
:param str entity: The name of the entity.
:param bool export: (optional) Whether to include all element content in
the returned data. If **export**=`false`, the returned data includes only
information about the element itself. If **export**=`true`, all content,
including subelements, is included.
:param int page_limit: (optional) The number of records to return in each
page of results.
:param bool include_count: (optional) Whether to include information about
the number of records that satisfy the request, regardless of the page
limit. If this parameter is `true`, the `pagination` object in the response
includes the `total` property.
:param str sort: (optional) The attribute by which returned entity values
will be sorted. To reverse the sort order, prefix the value with a minus
sign (`-`).
:param str cursor: (optional) A token identifying the page of results to
retrieve.
:param bool include_audit: (optional) Whether to include the audit
properties (`created` and `updated` timestamps) in the response.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `dict` result representing a `ValueCollection` object
"""
if workspace_id is None:
raise ValueError('workspace_id must be provided')
if entity is None:
raise ValueError('entity must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='list_values')
headers.update(sdk_headers)
params = {
'version': self.version,
'export': export,
'page_limit': page_limit,
'include_count': include_count,
'sort': sort,
'cursor': cursor,
'include_audit': include_audit
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
path_param_keys = ['workspace_id', 'entity']
path_param_values = self.encode_path_vars(workspace_id, entity)
path_param_dict = dict(zip(path_param_keys, path_param_values))
url = '/v1/workspaces/{workspace_id}/entities/{entity}/values'.format(
**path_param_dict)
request = self.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.send(request)
return response
[docs] def create_value(self,
workspace_id: str,
entity: str,
value: str,
*,
metadata: dict = None,
type: str = None,
synonyms: List[str] = None,
patterns: List[str] = None,
include_audit: bool = None,
**kwargs) -> DetailedResponse:
"""
Create entity value.
Create a new value for an entity.
If you want to create multiple entity values with a single API call, consider
using the **[Update entity](#update-entity)** method instead.
:param str workspace_id: Unique identifier of the workspace.
:param str entity: The name of the entity.
:param str value: The text of the entity value. This string must conform to
the following restrictions:
- It cannot contain carriage return, newline, or tab characters.
- It cannot consist of only whitespace characters.
:param dict metadata: (optional) Any metadata related to the entity value.
:param str type: (optional) Specifies the type of entity value.
:param List[str] synonyms: (optional) An array of synonyms for the entity
value. A value can specify either synonyms or patterns (depending on the
value type), but not both. A synonym must conform to the following
resrictions:
- It cannot contain carriage return, newline, or tab characters.
- It cannot consist of only whitespace characters.
:param List[str] patterns: (optional) An array of patterns for the entity
value. A value can specify either synonyms or patterns (depending on the
value type), but not both. A pattern is a regular expression; for more
information about how to specify a pattern, see the
[documentation](https://cloud.ibm.com/docs/assistant?topic=assistant-entities#entities-create-dictionary-based).
:param bool include_audit: (optional) Whether to include the audit
properties (`created` and `updated` timestamps) in the response.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `dict` result representing a `Value` object
"""
if workspace_id is None:
raise ValueError('workspace_id must be provided')
if entity is None:
raise ValueError('entity must be provided')
if value is None:
raise ValueError('value must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='create_value')
headers.update(sdk_headers)
params = {'version': self.version, 'include_audit': include_audit}
data = {
'value': value,
'metadata': metadata,
'type': type,
'synonyms': synonyms,
'patterns': patterns
}
data = {k: v for (k, v) in data.items() if v is not None}
data = json.dumps(data)
headers['content-type'] = 'application/json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
path_param_keys = ['workspace_id', 'entity']
path_param_values = self.encode_path_vars(workspace_id, entity)
path_param_dict = dict(zip(path_param_keys, path_param_values))
url = '/v1/workspaces/{workspace_id}/entities/{entity}/values'.format(
**path_param_dict)
request = self.prepare_request(method='POST',
url=url,
headers=headers,
params=params,
data=data)
response = self.send(request)
return response
[docs] def get_value(self,
workspace_id: str,
entity: str,
value: str,
*,
export: bool = None,
include_audit: bool = None,
**kwargs) -> DetailedResponse:
"""
Get entity value.
Get information about an entity value.
:param str workspace_id: Unique identifier of the workspace.
:param str entity: The name of the entity.
:param str value: The text of the entity value.
:param bool export: (optional) Whether to include all element content in
the returned data. If **export**=`false`, the returned data includes only
information about the element itself. If **export**=`true`, all content,
including subelements, is included.
:param bool include_audit: (optional) Whether to include the audit
properties (`created` and `updated` timestamps) in the response.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `dict` result representing a `Value` object
"""
if workspace_id is None:
raise ValueError('workspace_id must be provided')
if entity is None:
raise ValueError('entity must be provided')
if value is None:
raise ValueError('value must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='get_value')
headers.update(sdk_headers)
params = {
'version': self.version,
'export': export,
'include_audit': include_audit
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
path_param_keys = ['workspace_id', 'entity', 'value']
path_param_values = self.encode_path_vars(workspace_id, entity, value)
path_param_dict = dict(zip(path_param_keys, path_param_values))
url = '/v1/workspaces/{workspace_id}/entities/{entity}/values/{value}'.format(
**path_param_dict)
request = self.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.send(request)
return response
[docs] def update_value(self,
workspace_id: str,
entity: str,
value: str,
*,
new_value: str = None,
new_metadata: dict = None,
new_type: str = None,
new_synonyms: List[str] = None,
new_patterns: List[str] = None,
append: bool = None,
include_audit: bool = None,
**kwargs) -> DetailedResponse:
"""
Update entity value.
Update an existing entity value with new or modified data. You must provide
component objects defining the content of the updated entity value.
If you want to update multiple entity values with a single API call, consider
using the **[Update entity](#update-entity)** method instead.
:param str workspace_id: Unique identifier of the workspace.
:param str entity: The name of the entity.
:param str value: The text of the entity value.
:param str new_value: (optional) The text of the entity value. This string
must conform to the following restrictions:
- It cannot contain carriage return, newline, or tab characters.
- It cannot consist of only whitespace characters.
:param dict new_metadata: (optional) Any metadata related to the entity
value.
:param str new_type: (optional) Specifies the type of entity value.
:param List[str] new_synonyms: (optional) An array of synonyms for the
entity value. A value can specify either synonyms or patterns (depending on
the value type), but not both. A synonym must conform to the following
resrictions:
- It cannot contain carriage return, newline, or tab characters.
- It cannot consist of only whitespace characters.
:param List[str] new_patterns: (optional) An array of patterns for the
entity value. A value can specify either synonyms or patterns (depending on
the value type), but not both. A pattern is a regular expression; for more
information about how to specify a pattern, see the
[documentation](https://cloud.ibm.com/docs/assistant?topic=assistant-entities#entities-create-dictionary-based).
:param bool append: (optional) Whether the new data is to be appended to
the existing data in the entity value. If **append**=`false`, elements
included in the new data completely replace the corresponding existing
elements, including all subelements. For example, if the new data for the
entity value includes **synonyms** and **append**=`false`, all existing
synonyms for the entity value are discarded and replaced with the new
synonyms.
If **append**=`true`, existing elements are preserved, and the new elements
are added. If any elements in the new data collide with existing elements,
the update request fails.
:param bool include_audit: (optional) Whether to include the audit
properties (`created` and `updated` timestamps) in the response.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `dict` result representing a `Value` object
"""
if workspace_id is None:
raise ValueError('workspace_id must be provided')
if entity is None:
raise ValueError('entity must be provided')
if value is None:
raise ValueError('value must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='update_value')
headers.update(sdk_headers)
params = {
'version': self.version,
'append': append,
'include_audit': include_audit
}
data = {
'value': new_value,
'metadata': new_metadata,
'type': new_type,
'synonyms': new_synonyms,
'patterns': new_patterns
}
data = {k: v for (k, v) in data.items() if v is not None}
data = json.dumps(data)
headers['content-type'] = 'application/json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
path_param_keys = ['workspace_id', 'entity', 'value']
path_param_values = self.encode_path_vars(workspace_id, entity, value)
path_param_dict = dict(zip(path_param_keys, path_param_values))
url = '/v1/workspaces/{workspace_id}/entities/{entity}/values/{value}'.format(
**path_param_dict)
request = self.prepare_request(method='POST',
url=url,
headers=headers,
params=params,
data=data)
response = self.send(request)
return response
[docs] def delete_value(self, workspace_id: str, entity: str, value: str,
**kwargs) -> DetailedResponse:
"""
Delete entity value.
Delete a value from an entity.
:param str workspace_id: Unique identifier of the workspace.
:param str entity: The name of the entity.
:param str value: The text of the entity value.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse
"""
if workspace_id is None:
raise ValueError('workspace_id must be provided')
if entity is None:
raise ValueError('entity must be provided')
if value is None:
raise ValueError('value must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='delete_value')
headers.update(sdk_headers)
params = {'version': self.version}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
path_param_keys = ['workspace_id', 'entity', 'value']
path_param_values = self.encode_path_vars(workspace_id, entity, value)
path_param_dict = dict(zip(path_param_keys, path_param_values))
url = '/v1/workspaces/{workspace_id}/entities/{entity}/values/{value}'.format(
**path_param_dict)
request = self.prepare_request(method='DELETE',
url=url,
headers=headers,
params=params)
response = self.send(request)
return response
#########################
# Synonyms
#########################
[docs] def list_synonyms(self,
workspace_id: str,
entity: str,
value: str,
*,
page_limit: int = None,
include_count: bool = None,
sort: str = None,
cursor: str = None,
include_audit: bool = None,
**kwargs) -> DetailedResponse:
"""
List entity value synonyms.
List the synonyms for an entity value.
:param str workspace_id: Unique identifier of the workspace.
:param str entity: The name of the entity.
:param str value: The text of the entity value.
:param int page_limit: (optional) The number of records to return in each
page of results.
:param bool include_count: (optional) Whether to include information about
the number of records that satisfy the request, regardless of the page
limit. If this parameter is `true`, the `pagination` object in the response
includes the `total` property.
:param str sort: (optional) The attribute by which returned entity value
synonyms will be sorted. To reverse the sort order, prefix the value with a
minus sign (`-`).
:param str cursor: (optional) A token identifying the page of results to
retrieve.
:param bool include_audit: (optional) Whether to include the audit
properties (`created` and `updated` timestamps) in the response.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `dict` result representing a `SynonymCollection` object
"""
if workspace_id is None:
raise ValueError('workspace_id must be provided')
if entity is None:
raise ValueError('entity must be provided')
if value is None:
raise ValueError('value must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='list_synonyms')
headers.update(sdk_headers)
params = {
'version': self.version,
'page_limit': page_limit,
'include_count': include_count,
'sort': sort,
'cursor': cursor,
'include_audit': include_audit
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
path_param_keys = ['workspace_id', 'entity', 'value']
path_param_values = self.encode_path_vars(workspace_id, entity, value)
path_param_dict = dict(zip(path_param_keys, path_param_values))
url = '/v1/workspaces/{workspace_id}/entities/{entity}/values/{value}/synonyms'.format(
**path_param_dict)
request = self.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.send(request)
return response
[docs] def create_synonym(self,
workspace_id: str,
entity: str,
value: str,
synonym: str,
*,
include_audit: bool = None,
**kwargs) -> DetailedResponse:
"""
Create entity value synonym.
Add a new synonym to an entity value.
If you want to create multiple synonyms with a single API call, consider using the
**[Update entity](#update-entity)** or **[Update entity
value](#update-entity-value)** method instead.
:param str workspace_id: Unique identifier of the workspace.
:param str entity: The name of the entity.
:param str value: The text of the entity value.
:param str synonym: The text of the synonym. This string must conform to
the following restrictions:
- It cannot contain carriage return, newline, or tab characters.
- It cannot consist of only whitespace characters.
:param bool include_audit: (optional) Whether to include the audit
properties (`created` and `updated` timestamps) in the response.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `dict` result representing a `Synonym` object
"""
if workspace_id is None:
raise ValueError('workspace_id must be provided')
if entity is None:
raise ValueError('entity must be provided')
if value is None:
raise ValueError('value must be provided')
if synonym is None:
raise ValueError('synonym must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='create_synonym')
headers.update(sdk_headers)
params = {'version': self.version, 'include_audit': include_audit}
data = {'synonym': synonym}
data = {k: v for (k, v) in data.items() if v is not None}
data = json.dumps(data)
headers['content-type'] = 'application/json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
path_param_keys = ['workspace_id', 'entity', 'value']
path_param_values = self.encode_path_vars(workspace_id, entity, value)
path_param_dict = dict(zip(path_param_keys, path_param_values))
url = '/v1/workspaces/{workspace_id}/entities/{entity}/values/{value}/synonyms'.format(
**path_param_dict)
request = self.prepare_request(method='POST',
url=url,
headers=headers,
params=params,
data=data)
response = self.send(request)
return response
[docs] def get_synonym(self,
workspace_id: str,
entity: str,
value: str,
synonym: str,
*,
include_audit: bool = None,
**kwargs) -> DetailedResponse:
"""
Get entity value synonym.
Get information about a synonym of an entity value.
:param str workspace_id: Unique identifier of the workspace.
:param str entity: The name of the entity.
:param str value: The text of the entity value.
:param str synonym: The text of the synonym.
:param bool include_audit: (optional) Whether to include the audit
properties (`created` and `updated` timestamps) in the response.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `dict` result representing a `Synonym` object
"""
if workspace_id is None:
raise ValueError('workspace_id must be provided')
if entity is None:
raise ValueError('entity must be provided')
if value is None:
raise ValueError('value must be provided')
if synonym is None:
raise ValueError('synonym must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='get_synonym')
headers.update(sdk_headers)
params = {'version': self.version, 'include_audit': include_audit}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
path_param_keys = ['workspace_id', 'entity', 'value', 'synonym']
path_param_values = self.encode_path_vars(workspace_id, entity, value,
synonym)
path_param_dict = dict(zip(path_param_keys, path_param_values))
url = '/v1/workspaces/{workspace_id}/entities/{entity}/values/{value}/synonyms/{synonym}'.format(
**path_param_dict)
request = self.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.send(request)
return response
[docs] def update_synonym(self,
workspace_id: str,
entity: str,
value: str,
synonym: str,
*,
new_synonym: str = None,
include_audit: bool = None,
**kwargs) -> DetailedResponse:
"""
Update entity value synonym.
Update an existing entity value synonym with new text.
If you want to update multiple synonyms with a single API call, consider using the
**[Update entity](#update-entity)** or **[Update entity
value](#update-entity-value)** method instead.
:param str workspace_id: Unique identifier of the workspace.
:param str entity: The name of the entity.
:param str value: The text of the entity value.
:param str synonym: The text of the synonym.
:param str new_synonym: (optional) The text of the synonym. This string
must conform to the following restrictions:
- It cannot contain carriage return, newline, or tab characters.
- It cannot consist of only whitespace characters.
:param bool include_audit: (optional) Whether to include the audit
properties (`created` and `updated` timestamps) in the response.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `dict` result representing a `Synonym` object
"""
if workspace_id is None:
raise ValueError('workspace_id must be provided')
if entity is None:
raise ValueError('entity must be provided')
if value is None:
raise ValueError('value must be provided')
if synonym is None:
raise ValueError('synonym must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='update_synonym')
headers.update(sdk_headers)
params = {'version': self.version, 'include_audit': include_audit}
data = {'synonym': new_synonym}
data = {k: v for (k, v) in data.items() if v is not None}
data = json.dumps(data)
headers['content-type'] = 'application/json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
path_param_keys = ['workspace_id', 'entity', 'value', 'synonym']
path_param_values = self.encode_path_vars(workspace_id, entity, value,
synonym)
path_param_dict = dict(zip(path_param_keys, path_param_values))
url = '/v1/workspaces/{workspace_id}/entities/{entity}/values/{value}/synonyms/{synonym}'.format(
**path_param_dict)
request = self.prepare_request(method='POST',
url=url,
headers=headers,
params=params,
data=data)
response = self.send(request)
return response
[docs] def delete_synonym(self, workspace_id: str, entity: str, value: str,
synonym: str, **kwargs) -> DetailedResponse:
"""
Delete entity value synonym.
Delete a synonym from an entity value.
:param str workspace_id: Unique identifier of the workspace.
:param str entity: The name of the entity.
:param str value: The text of the entity value.
:param str synonym: The text of the synonym.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse
"""
if workspace_id is None:
raise ValueError('workspace_id must be provided')
if entity is None:
raise ValueError('entity must be provided')
if value is None:
raise ValueError('value must be provided')
if synonym is None:
raise ValueError('synonym must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='delete_synonym')
headers.update(sdk_headers)
params = {'version': self.version}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
path_param_keys = ['workspace_id', 'entity', 'value', 'synonym']
path_param_values = self.encode_path_vars(workspace_id, entity, value,
synonym)
path_param_dict = dict(zip(path_param_keys, path_param_values))
url = '/v1/workspaces/{workspace_id}/entities/{entity}/values/{value}/synonyms/{synonym}'.format(
**path_param_dict)
request = self.prepare_request(method='DELETE',
url=url,
headers=headers,
params=params)
response = self.send(request)
return response
#########################
# Dialog nodes
#########################
[docs] def list_dialog_nodes(self,
workspace_id: str,
*,
page_limit: int = None,
include_count: bool = None,
sort: str = None,
cursor: str = None,
include_audit: bool = None,
**kwargs) -> DetailedResponse:
"""
List dialog nodes.
List the dialog nodes for a workspace.
:param str workspace_id: Unique identifier of the workspace.
:param int page_limit: (optional) The number of records to return in each
page of results.
:param bool include_count: (optional) Whether to include information about
the number of records that satisfy the request, regardless of the page
limit. If this parameter is `true`, the `pagination` object in the response
includes the `total` property.
:param str sort: (optional) The attribute by which returned dialog nodes
will be sorted. To reverse the sort order, prefix the value with a minus
sign (`-`).
:param str cursor: (optional) A token identifying the page of results to
retrieve.
:param bool include_audit: (optional) Whether to include the audit
properties (`created` and `updated` timestamps) in the response.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `dict` result representing a `DialogNodeCollection` object
"""
if workspace_id is None:
raise ValueError('workspace_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='list_dialog_nodes')
headers.update(sdk_headers)
params = {
'version': self.version,
'page_limit': page_limit,
'include_count': include_count,
'sort': sort,
'cursor': cursor,
'include_audit': include_audit
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
path_param_keys = ['workspace_id']
path_param_values = self.encode_path_vars(workspace_id)
path_param_dict = dict(zip(path_param_keys, path_param_values))
url = '/v1/workspaces/{workspace_id}/dialog_nodes'.format(
**path_param_dict)
request = self.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.send(request)
return response
[docs] def create_dialog_node(self,
workspace_id: str,
dialog_node: str,
*,
description: str = None,
conditions: str = None,
parent: str = None,
previous_sibling: str = None,
output: 'DialogNodeOutput' = None,
context: 'DialogNodeContext' = None,
metadata: dict = None,
next_step: 'DialogNodeNextStep' = None,
title: str = None,
type: str = None,
event_name: str = None,
variable: str = None,
actions: List['DialogNodeAction'] = None,
digress_in: str = None,
digress_out: str = None,
digress_out_slots: str = None,
user_label: str = None,
disambiguation_opt_out: bool = None,
include_audit: bool = None,
**kwargs) -> DetailedResponse:
"""
Create dialog node.
Create a new dialog node.
If you want to create multiple dialog nodes with a single API call, consider using
the **[Update workspace](#update-workspace)** method instead.
:param str workspace_id: Unique identifier of the workspace.
:param str dialog_node: The unique ID of the dialog node. This is an
internal identifier used to refer to the dialog node from other dialog
nodes and in the diagnostic information included with message responses.
This string can contain only Unicode alphanumeric, space, underscore,
hyphen, and dot characters.
:param str description: (optional) The description of the dialog node. This
string cannot contain carriage return, newline, or tab characters.
:param str conditions: (optional) The condition that will trigger the
dialog node. This string cannot contain carriage return, newline, or tab
characters.
:param str parent: (optional) The unique ID of the parent dialog node. This
property is omitted if the dialog node has no parent.
:param str previous_sibling: (optional) The unique ID of the previous
sibling dialog node. This property is omitted if the dialog node has no
previous sibling.
:param DialogNodeOutput output: (optional) The output of the dialog node.
For more information about how to specify dialog node output, see the
[documentation](https://cloud.ibm.com/docs/assistant?topic=assistant-dialog-overview#dialog-overview-responses).
:param DialogNodeContext context: (optional) The context for the dialog
node.
:param dict metadata: (optional) The metadata for the dialog node.
:param DialogNodeNextStep next_step: (optional) The next step to execute
following this dialog node.
:param str title: (optional) A human-readable name for the dialog node. If
the node is included in disambiguation, this title is used to populate the
**label** property of the corresponding suggestion in the `suggestion`
response type (unless it is overridden by the **user_label** property). The
title is also used to populate the **topic** property in the
`connect_to_agent` response type.
This string can contain only Unicode alphanumeric, space, underscore,
hyphen, and dot characters.
:param str type: (optional) How the dialog node is processed.
:param str event_name: (optional) How an `event_handler` node is processed.
:param str variable: (optional) The location in the dialog context where
output is stored.
:param List[DialogNodeAction] actions: (optional) An array of objects
describing any actions to be invoked by the dialog node.
:param str digress_in: (optional) Whether this top-level dialog node can be
digressed into.
:param str digress_out: (optional) Whether this dialog node can be returned
to after a digression.
:param str digress_out_slots: (optional) Whether the user can digress to
top-level nodes while filling out slots.
:param str user_label: (optional) A label that can be displayed externally
to describe the purpose of the node to users. If set, this label is used to
identify the node in disambiguation responses (overriding the value of the
**title** property).
:param bool disambiguation_opt_out: (optional) Whether the dialog node
should be excluded from disambiguation suggestions. Valid only when
**type**=`standard` or `frame`.
:param bool include_audit: (optional) Whether to include the audit
properties (`created` and `updated` timestamps) in the response.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `dict` result representing a `DialogNode` object
"""
if workspace_id is None:
raise ValueError('workspace_id must be provided')
if dialog_node is None:
raise ValueError('dialog_node must be provided')
if output is not None:
output = convert_model(output)
if context is not None:
context = convert_model(context)
if next_step is not None:
next_step = convert_model(next_step)
if actions is not None:
actions = [convert_model(x) for x in actions]
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='create_dialog_node')
headers.update(sdk_headers)
params = {'version': self.version, 'include_audit': include_audit}
data = {
'dialog_node': dialog_node,
'description': description,
'conditions': conditions,
'parent': parent,
'previous_sibling': previous_sibling,
'output': output,
'context': context,
'metadata': metadata,
'next_step': next_step,
'title': title,
'type': type,
'event_name': event_name,
'variable': variable,
'actions': actions,
'digress_in': digress_in,
'digress_out': digress_out,
'digress_out_slots': digress_out_slots,
'user_label': user_label,
'disambiguation_opt_out': disambiguation_opt_out
}
data = {k: v for (k, v) in data.items() if v is not None}
data = json.dumps(data)
headers['content-type'] = 'application/json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
path_param_keys = ['workspace_id']
path_param_values = self.encode_path_vars(workspace_id)
path_param_dict = dict(zip(path_param_keys, path_param_values))
url = '/v1/workspaces/{workspace_id}/dialog_nodes'.format(
**path_param_dict)
request = self.prepare_request(method='POST',
url=url,
headers=headers,
params=params,
data=data)
response = self.send(request)
return response
[docs] def get_dialog_node(self,
workspace_id: str,
dialog_node: str,
*,
include_audit: bool = None,
**kwargs) -> DetailedResponse:
"""
Get dialog node.
Get information about a dialog node.
:param str workspace_id: Unique identifier of the workspace.
:param str dialog_node: The dialog node ID (for example,
`node_1_1479323581900`).
:param bool include_audit: (optional) Whether to include the audit
properties (`created` and `updated` timestamps) in the response.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `dict` result representing a `DialogNode` object
"""
if workspace_id is None:
raise ValueError('workspace_id must be provided')
if dialog_node is None:
raise ValueError('dialog_node must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='get_dialog_node')
headers.update(sdk_headers)
params = {'version': self.version, 'include_audit': include_audit}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
path_param_keys = ['workspace_id', 'dialog_node']
path_param_values = self.encode_path_vars(workspace_id, dialog_node)
path_param_dict = dict(zip(path_param_keys, path_param_values))
url = '/v1/workspaces/{workspace_id}/dialog_nodes/{dialog_node}'.format(
**path_param_dict)
request = self.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.send(request)
return response
[docs] def update_dialog_node(self,
workspace_id: str,
dialog_node: str,
*,
new_dialog_node: str = None,
new_description: str = None,
new_conditions: str = None,
new_parent: str = None,
new_previous_sibling: str = None,
new_output: 'DialogNodeOutput' = None,
new_context: 'DialogNodeContext' = None,
new_metadata: dict = None,
new_next_step: 'DialogNodeNextStep' = None,
new_title: str = None,
new_type: str = None,
new_event_name: str = None,
new_variable: str = None,
new_actions: List['DialogNodeAction'] = None,
new_digress_in: str = None,
new_digress_out: str = None,
new_digress_out_slots: str = None,
new_user_label: str = None,
new_disambiguation_opt_out: bool = None,
include_audit: bool = None,
**kwargs) -> DetailedResponse:
"""
Update dialog node.
Update an existing dialog node with new or modified data.
If you want to update multiple dialog nodes with a single API call, consider using
the **[Update workspace](#update-workspace)** method instead.
:param str workspace_id: Unique identifier of the workspace.
:param str dialog_node: The dialog node ID (for example,
`node_1_1479323581900`).
:param str new_dialog_node: (optional) The unique ID of the dialog node.
This is an internal identifier used to refer to the dialog node from other
dialog nodes and in the diagnostic information included with message
responses.
This string can contain only Unicode alphanumeric, space, underscore,
hyphen, and dot characters.
:param str new_description: (optional) The description of the dialog node.
This string cannot contain carriage return, newline, or tab characters.
:param str new_conditions: (optional) The condition that will trigger the
dialog node. This string cannot contain carriage return, newline, or tab
characters.
:param str new_parent: (optional) The unique ID of the parent dialog node.
This property is omitted if the dialog node has no parent.
:param str new_previous_sibling: (optional) The unique ID of the previous
sibling dialog node. This property is omitted if the dialog node has no
previous sibling.
:param DialogNodeOutput new_output: (optional) The output of the dialog
node. For more information about how to specify dialog node output, see the
[documentation](https://cloud.ibm.com/docs/assistant?topic=assistant-dialog-overview#dialog-overview-responses).
:param DialogNodeContext new_context: (optional) The context for the dialog
node.
:param dict new_metadata: (optional) The metadata for the dialog node.
:param DialogNodeNextStep new_next_step: (optional) The next step to
execute following this dialog node.
:param str new_title: (optional) A human-readable name for the dialog node.
If the node is included in disambiguation, this title is used to populate
the **label** property of the corresponding suggestion in the `suggestion`
response type (unless it is overridden by the **user_label** property). The
title is also used to populate the **topic** property in the
`connect_to_agent` response type.
This string can contain only Unicode alphanumeric, space, underscore,
hyphen, and dot characters.
:param str new_type: (optional) How the dialog node is processed.
:param str new_event_name: (optional) How an `event_handler` node is
processed.
:param str new_variable: (optional) The location in the dialog context
where output is stored.
:param List[DialogNodeAction] new_actions: (optional) An array of objects
describing any actions to be invoked by the dialog node.
:param str new_digress_in: (optional) Whether this top-level dialog node
can be digressed into.
:param str new_digress_out: (optional) Whether this dialog node can be
returned to after a digression.
:param str new_digress_out_slots: (optional) Whether the user can digress
to top-level nodes while filling out slots.
:param str new_user_label: (optional) A label that can be displayed
externally to describe the purpose of the node to users. If set, this label
is used to identify the node in disambiguation responses (overriding the
value of the **title** property).
:param bool new_disambiguation_opt_out: (optional) Whether the dialog node
should be excluded from disambiguation suggestions. Valid only when
**type**=`standard` or `frame`.
:param bool include_audit: (optional) Whether to include the audit
properties (`created` and `updated` timestamps) in the response.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `dict` result representing a `DialogNode` object
"""
if workspace_id is None:
raise ValueError('workspace_id must be provided')
if dialog_node is None:
raise ValueError('dialog_node must be provided')
if new_output is not None:
new_output = convert_model(new_output)
if new_context is not None:
new_context = convert_model(new_context)
if new_next_step is not None:
new_next_step = convert_model(new_next_step)
if new_actions is not None:
new_actions = [convert_model(x) for x in new_actions]
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='update_dialog_node')
headers.update(sdk_headers)
params = {'version': self.version, 'include_audit': include_audit}
data = {
'dialog_node': new_dialog_node,
'description': new_description,
'conditions': new_conditions,
'parent': new_parent,
'previous_sibling': new_previous_sibling,
'output': new_output,
'context': new_context,
'metadata': new_metadata,
'next_step': new_next_step,
'title': new_title,
'type': new_type,
'event_name': new_event_name,
'variable': new_variable,
'actions': new_actions,
'digress_in': new_digress_in,
'digress_out': new_digress_out,
'digress_out_slots': new_digress_out_slots,
'user_label': new_user_label,
'disambiguation_opt_out': new_disambiguation_opt_out
}
data = {k: v for (k, v) in data.items() if v is not None}
data = json.dumps(data)
headers['content-type'] = 'application/json'
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
path_param_keys = ['workspace_id', 'dialog_node']
path_param_values = self.encode_path_vars(workspace_id, dialog_node)
path_param_dict = dict(zip(path_param_keys, path_param_values))
url = '/v1/workspaces/{workspace_id}/dialog_nodes/{dialog_node}'.format(
**path_param_dict)
request = self.prepare_request(method='POST',
url=url,
headers=headers,
params=params,
data=data)
response = self.send(request)
return response
[docs] def delete_dialog_node(self, workspace_id: str, dialog_node: str,
**kwargs) -> DetailedResponse:
"""
Delete dialog node.
Delete a dialog node from a workspace.
:param str workspace_id: Unique identifier of the workspace.
:param str dialog_node: The dialog node ID (for example,
`node_1_1479323581900`).
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse
"""
if workspace_id is None:
raise ValueError('workspace_id must be provided')
if dialog_node is None:
raise ValueError('dialog_node must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='delete_dialog_node')
headers.update(sdk_headers)
params = {'version': self.version}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
path_param_keys = ['workspace_id', 'dialog_node']
path_param_values = self.encode_path_vars(workspace_id, dialog_node)
path_param_dict = dict(zip(path_param_keys, path_param_values))
url = '/v1/workspaces/{workspace_id}/dialog_nodes/{dialog_node}'.format(
**path_param_dict)
request = self.prepare_request(method='DELETE',
url=url,
headers=headers,
params=params)
response = self.send(request)
return response
#########################
# Logs
#########################
[docs] def list_logs(self,
workspace_id: str,
*,
sort: str = None,
filter: str = None,
page_limit: int = None,
cursor: str = None,
**kwargs) -> DetailedResponse:
"""
List log events in a workspace.
List the events from the log of a specific workspace.
This method requires Manager access.
:param str workspace_id: Unique identifier of the workspace.
:param str sort: (optional) How to sort the returned log events. You can
sort by **request_timestamp**. To reverse the sort order, prefix the
parameter value with a minus sign (`-`).
:param str filter: (optional) A cacheable parameter that limits the results
to those matching the specified filter. For more information, see the
[documentation](https://cloud.ibm.com/docs/assistant?topic=assistant-filter-reference#filter-reference).
:param int page_limit: (optional) The number of records to return in each
page of results.
:param str cursor: (optional) A token identifying the page of results to
retrieve.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `dict` result representing a `LogCollection` object
"""
if workspace_id is None:
raise ValueError('workspace_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='list_logs')
headers.update(sdk_headers)
params = {
'version': self.version,
'sort': sort,
'filter': filter,
'page_limit': page_limit,
'cursor': cursor
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
path_param_keys = ['workspace_id']
path_param_values = self.encode_path_vars(workspace_id)
path_param_dict = dict(zip(path_param_keys, path_param_values))
url = '/v1/workspaces/{workspace_id}/logs'.format(**path_param_dict)
request = self.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.send(request)
return response
[docs] def list_all_logs(self,
filter: str,
*,
sort: str = None,
page_limit: int = None,
cursor: str = None,
**kwargs) -> DetailedResponse:
"""
List log events in all workspaces.
List the events from the logs of all workspaces in the service instance.
:param str filter: A cacheable parameter that limits the results to those
matching the specified filter. You must specify a filter query that
includes a value for `language`, as well as a value for
`request.context.system.assistant_id`, `workspace_id`, or
`request.context.metadata.deployment`. For more information, see the
[documentation](https://cloud.ibm.com/docs/assistant?topic=assistant-filter-reference#filter-reference).
:param str sort: (optional) How to sort the returned log events. You can
sort by **request_timestamp**. To reverse the sort order, prefix the
parameter value with a minus sign (`-`).
:param int page_limit: (optional) The number of records to return in each
page of results.
:param str cursor: (optional) A token identifying the page of results to
retrieve.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse with `dict` result representing a `LogCollection` object
"""
if filter is None:
raise ValueError('filter must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='list_all_logs')
headers.update(sdk_headers)
params = {
'version': self.version,
'filter': filter,
'sort': sort,
'page_limit': page_limit,
'cursor': cursor
}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v1/logs'
request = self.prepare_request(method='GET',
url=url,
headers=headers,
params=params)
response = self.send(request)
return response
#########################
# User data
#########################
[docs] def delete_user_data(self, customer_id: str, **kwargs) -> DetailedResponse:
"""
Delete labeled data.
Deletes all data associated with a specified customer ID. The method has no effect
if no data is associated with the customer ID.
You associate a customer ID with data by passing the `X-Watson-Metadata` header
with a request that passes data. For more information about personal data and
customer IDs, see [Information
security](https://cloud.ibm.com/docs/assistant?topic=assistant-information-security#information-security).
**Note:** This operation is intended only for deleting data associated with a
single specific customer, not for deleting data associated with multiple customers
or for any other purpose. For more information, see [Labeling and deleting data in
Watson
Assistant](https://cloud.ibm.com/docs/assistant?topic=assistant-information-security#information-security-gdpr-wa).
:param str customer_id: The customer ID for which all data is to be
deleted.
:param dict headers: A `dict` containing the request headers
:return: A `DetailedResponse` containing the result, headers and HTTP status code.
:rtype: DetailedResponse
"""
if customer_id is None:
raise ValueError('customer_id must be provided')
headers = {}
sdk_headers = get_sdk_headers(service_name=self.DEFAULT_SERVICE_NAME,
service_version='V1',
operation_id='delete_user_data')
headers.update(sdk_headers)
params = {'version': self.version, 'customer_id': customer_id}
if 'headers' in kwargs:
headers.update(kwargs.get('headers'))
headers['Accept'] = 'application/json'
url = '/v1/user_data'
request = self.prepare_request(method='DELETE',
url=url,
headers=headers,
params=params)
response = self.send(request)
return response
[docs]class ListWorkspacesEnums:
"""
Enums for list_workspaces parameters.
"""
[docs] 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'
[docs]class GetWorkspaceEnums:
"""
Enums for get_workspace parameters.
"""
[docs] class Sort(str, Enum):
"""
Indicates how the returned workspace data will be sorted. This parameter is valid
only if **export**=`true`. Specify `sort=stable` to sort all workspace objects by
unique identifier, in ascending alphabetical order.
"""
STABLE = 'stable'
[docs]class ListIntentsEnums:
"""
Enums for list_intents parameters.
"""
[docs] class Sort(str, Enum):
"""
The attribute by which returned intents will be sorted. To reverse the sort order,
prefix the value with a minus sign (`-`).
"""
INTENT = 'intent'
UPDATED = 'updated'
[docs]class ListExamplesEnums:
"""
Enums for list_examples parameters.
"""
[docs] class Sort(str, Enum):
"""
The attribute by which returned examples will be sorted. To reverse the sort
order, prefix the value with a minus sign (`-`).
"""
TEXT = 'text'
UPDATED = 'updated'
[docs]class ListCounterexamplesEnums:
"""
Enums for list_counterexamples parameters.
"""
[docs] class Sort(str, Enum):
"""
The attribute by which returned counterexamples will be sorted. To reverse the
sort order, prefix the value with a minus sign (`-`).
"""
TEXT = 'text'
UPDATED = 'updated'
[docs]class ListEntitiesEnums:
"""
Enums for list_entities parameters.
"""
[docs] class Sort(str, Enum):
"""
The attribute by which returned entities will be sorted. To reverse the sort
order, prefix the value with a minus sign (`-`).
"""
ENTITY = 'entity'
UPDATED = 'updated'
[docs]class ListValuesEnums:
"""
Enums for list_values parameters.
"""
[docs] class Sort(str, Enum):
"""
The attribute by which returned entity values will be sorted. To reverse the sort
order, prefix the value with a minus sign (`-`).
"""
VALUE = 'value'
UPDATED = 'updated'
[docs]class ListSynonymsEnums:
"""
Enums for list_synonyms parameters.
"""
[docs] class Sort(str, Enum):
"""
The attribute by which returned entity value synonyms will be sorted. To reverse
the sort order, prefix the value with a minus sign (`-`).
"""
SYNONYM = 'synonym'
UPDATED = 'updated'
[docs]class ListDialogNodesEnums:
"""
Enums for list_dialog_nodes parameters.
"""
[docs] class Sort(str, Enum):
"""
The attribute by which returned dialog nodes will be sorted. To reverse the sort
order, prefix the value with a minus sign (`-`).
"""
DIALOG_NODE = 'dialog_node'
UPDATED = 'updated'
##############################################################################
# Models
##############################################################################
[docs]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
[docs] @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)
[docs] 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
[docs]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
[docs] @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)
[docs] 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
[docs]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
[docs] @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)
[docs] 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
[docs]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
[docs] @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)
[docs] 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
[docs]class CaptureGroup():
"""
A recognized capture group for a pattern-based entity.
:attr str group: A recognized capture group for the entity.
:attr List[int] location: (optional) Zero-based character offsets that indicate
where the entity value begins and ends in the input text.
"""
def __init__(self, group: str, *, location: List[int] = None) -> None:
"""
Initialize a CaptureGroup object.
:param str group: A recognized capture group for the entity.
:param List[int] location: (optional) Zero-based character offsets that
indicate where the entity value begins and ends in the input text.
"""
self.group = group
self.location = location
[docs] @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)
[docs] 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
[docs]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
[docs] @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)
[docs] 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
[docs]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
[docs] @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)
[docs] 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
[docs]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
[docs] @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)
[docs] 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
[docs]class Context():
"""
State information for the conversation. To maintain state, include the context from
the previous response.
:attr str conversation_id: (optional) The unique identifier of the conversation.
:attr dict system: (optional) For internal use only.
:attr MessageContextMetadata metadata: (optional) Metadata related to the
message.
"""
# The set of defined properties for the class
_properties = frozenset(['conversation_id', 'system', 'metadata'])
def __init__(self,
*,
conversation_id: str = None,
system: dict = None,
metadata: 'MessageContextMetadata' = None,
**kwargs) -> None:
"""
Initialize a Context object.
:param str conversation_id: (optional) The unique identifier of the
conversation.
:param dict system: (optional) For internal use only.
:param MessageContextMetadata metadata: (optional) Metadata related to the
message.
:param **kwargs: (optional) Any additional properties.
"""
self.conversation_id = conversation_id
self.system = system
self.metadata = metadata
for _key, _value in kwargs.items():
setattr(self, _key, _value)
[docs] @classmethod
def from_dict(cls, _dict: Dict) -> 'Context':
"""Initialize a Context object from a json dictionary."""
args = {}
if 'conversation_id' in _dict:
args['conversation_id'] = _dict.get('conversation_id')
if 'system' in _dict:
args['system'] = _dict.get('system')
if 'metadata' in _dict:
args['metadata'] = MessageContextMetadata.from_dict(
_dict.get('metadata'))
args.update(
{k: v for (k, v) in _dict.items() if k not in cls._properties})
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a Context object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self,
'conversation_id') and self.conversation_id is not None:
_dict['conversation_id'] = self.conversation_id
if hasattr(self, 'system') and self.system is not None:
_dict['system'] = self.system
if hasattr(self, 'metadata') and self.metadata is not None:
_dict['metadata'] = self.metadata.to_dict()
for _key in [
k for k in vars(self).keys() if k not in Context._properties
]:
if getattr(self, _key, None) is not None:
_dict[_key] = getattr(self, _key)
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this Context object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'Context') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'Context') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]class Counterexample():
"""
Counterexample.
:attr str text: The text of a user input marked as irrelevant input. This string
must conform to the following restrictions:
- It cannot contain carriage return, newline, or tab characters.
- It cannot consist of only whitespace characters.
:attr datetime created: (optional) The timestamp for creation of the object.
:attr datetime updated: (optional) The timestamp for the most recent update to
the object.
"""
def __init__(self,
text: str,
*,
created: datetime = None,
updated: datetime = None) -> None:
"""
Initialize a Counterexample object.
:param str text: The text of a user input marked as irrelevant input. This
string must conform to the following restrictions:
- It cannot contain carriage return, newline, or tab characters.
- It cannot consist of only whitespace characters.
"""
self.text = text
self.created = created
self.updated = updated
[docs] @classmethod
def from_dict(cls, _dict: Dict) -> 'Counterexample':
"""Initialize a Counterexample object from a json dictionary."""
args = {}
if 'text' in _dict:
args['text'] = _dict.get('text')
else:
raise ValueError(
'Required property \'text\' not present in Counterexample JSON')
if 'created' in _dict:
args['created'] = string_to_datetime(_dict.get('created'))
if 'updated' in _dict:
args['updated'] = string_to_datetime(_dict.get('updated'))
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a Counterexample object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'text') and self.text is not None:
_dict['text'] = self.text
if hasattr(self, 'created') and getattr(self, 'created') is not None:
_dict['created'] = datetime_to_string(getattr(self, 'created'))
if hasattr(self, 'updated') and getattr(self, 'updated') is not None:
_dict['updated'] = datetime_to_string(getattr(self, 'updated'))
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this Counterexample object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'Counterexample') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'Counterexample') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]class CounterexampleCollection():
"""
CounterexampleCollection.
:attr List[Counterexample] counterexamples: An array of objects describing the
examples marked as irrelevant input.
:attr Pagination pagination: The pagination data for the returned objects.
"""
def __init__(self, counterexamples: List['Counterexample'],
pagination: 'Pagination') -> None:
"""
Initialize a CounterexampleCollection object.
:param List[Counterexample] counterexamples: An array of objects describing
the examples marked as irrelevant input.
:param Pagination pagination: The pagination data for the returned objects.
"""
self.counterexamples = counterexamples
self.pagination = pagination
[docs] @classmethod
def from_dict(cls, _dict: Dict) -> 'CounterexampleCollection':
"""Initialize a CounterexampleCollection object from a json dictionary."""
args = {}
if 'counterexamples' in _dict:
args['counterexamples'] = [
Counterexample.from_dict(x)
for x in _dict.get('counterexamples')
]
else:
raise ValueError(
'Required property \'counterexamples\' not present in CounterexampleCollection JSON'
)
if 'pagination' in _dict:
args['pagination'] = Pagination.from_dict(_dict.get('pagination'))
else:
raise ValueError(
'Required property \'pagination\' not present in CounterexampleCollection JSON'
)
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a CounterexampleCollection object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self,
'counterexamples') and self.counterexamples is not None:
_dict['counterexamples'] = [
x.to_dict() for x in self.counterexamples
]
if hasattr(self, 'pagination') and self.pagination is not None:
_dict['pagination'] = self.pagination.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this CounterexampleCollection object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'CounterexampleCollection') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'CounterexampleCollection') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]class CreateEntity():
"""
CreateEntity.
:attr str entity: The name of the entity. This string must conform to the
following restrictions:
- It can contain only Unicode alphanumeric, underscore, and hyphen characters.
- If you specify an entity name beginning with the reserved prefix `sys-`, it
must be the name of a system entity that you want to enable. (Any entity content
specified with the request is ignored.).
:attr str description: (optional) The description of the entity. This string
cannot contain carriage return, newline, or tab characters.
:attr dict metadata: (optional) Any metadata related to the entity.
:attr bool fuzzy_match: (optional) Whether to use fuzzy matching for the entity.
:attr datetime created: (optional) The timestamp for creation of the object.
:attr datetime updated: (optional) The timestamp for the most recent update to
the object.
:attr List[CreateValue] values: (optional) An array of objects describing the
entity values.
"""
def __init__(self,
entity: str,
*,
description: str = None,
metadata: dict = None,
fuzzy_match: bool = None,
created: datetime = None,
updated: datetime = None,
values: List['CreateValue'] = None) -> None:
"""
Initialize a CreateEntity object.
:param str entity: The name of the entity. This string must conform to the
following restrictions:
- It can contain only Unicode alphanumeric, underscore, and hyphen
characters.
- If you specify an entity name beginning with the reserved prefix `sys-`,
it must be the name of a system entity that you want to enable. (Any entity
content specified with the request is ignored.).
:param str description: (optional) The description of the entity. This
string cannot contain carriage return, newline, or tab characters.
:param dict metadata: (optional) Any metadata related to the entity.
:param bool fuzzy_match: (optional) Whether to use fuzzy matching for the
entity.
:param List[CreateValue] values: (optional) An array of objects describing
the entity values.
"""
self.entity = entity
self.description = description
self.metadata = metadata
self.fuzzy_match = fuzzy_match
self.created = created
self.updated = updated
self.values = values
[docs] @classmethod
def from_dict(cls, _dict: Dict) -> 'CreateEntity':
"""Initialize a CreateEntity object from a json dictionary."""
args = {}
if 'entity' in _dict:
args['entity'] = _dict.get('entity')
else:
raise ValueError(
'Required property \'entity\' not present in CreateEntity JSON')
if 'description' in _dict:
args['description'] = _dict.get('description')
if 'metadata' in _dict:
args['metadata'] = _dict.get('metadata')
if 'fuzzy_match' in _dict:
args['fuzzy_match'] = _dict.get('fuzzy_match')
if 'created' in _dict:
args['created'] = string_to_datetime(_dict.get('created'))
if 'updated' in _dict:
args['updated'] = string_to_datetime(_dict.get('updated'))
if 'values' in _dict:
args['values'] = [
CreateValue.from_dict(x) for x in _dict.get('values')
]
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a CreateEntity object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'entity') and self.entity is not None:
_dict['entity'] = self.entity
if hasattr(self, 'description') and self.description is not None:
_dict['description'] = self.description
if hasattr(self, 'metadata') and self.metadata is not None:
_dict['metadata'] = self.metadata
if hasattr(self, 'fuzzy_match') and self.fuzzy_match is not None:
_dict['fuzzy_match'] = self.fuzzy_match
if hasattr(self, 'created') and getattr(self, 'created') is not None:
_dict['created'] = datetime_to_string(getattr(self, 'created'))
if hasattr(self, 'updated') and getattr(self, 'updated') is not None:
_dict['updated'] = datetime_to_string(getattr(self, 'updated'))
if hasattr(self, 'values') and self.values is not None:
_dict['values'] = [x.to_dict() for x in self.values]
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this CreateEntity object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'CreateEntity') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'CreateEntity') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]class CreateIntent():
"""
CreateIntent.
:attr str intent: The name of the intent. This string must conform to the
following restrictions:
- It can contain only Unicode alphanumeric, underscore, hyphen, and dot
characters.
- It cannot begin with the reserved prefix `sys-`.
:attr str description: (optional) The description of the intent. This string
cannot contain carriage return, newline, or tab characters.
:attr datetime created: (optional) The timestamp for creation of the object.
:attr datetime updated: (optional) The timestamp for the most recent update to
the object.
:attr List[Example] examples: (optional) An array of user input examples for the
intent.
"""
def __init__(self,
intent: str,
*,
description: str = None,
created: datetime = None,
updated: datetime = None,
examples: List['Example'] = None) -> None:
"""
Initialize a CreateIntent object.
:param str intent: The name of the intent. This string must conform to the
following restrictions:
- It can contain only Unicode alphanumeric, underscore, hyphen, and dot
characters.
- It cannot begin with the reserved prefix `sys-`.
:param str description: (optional) The description of the intent. This
string cannot contain carriage return, newline, or tab characters.
:param List[Example] examples: (optional) An array of user input examples
for the intent.
"""
self.intent = intent
self.description = description
self.created = created
self.updated = updated
self.examples = examples
[docs] @classmethod
def from_dict(cls, _dict: Dict) -> 'CreateIntent':
"""Initialize a CreateIntent object from a json dictionary."""
args = {}
if 'intent' in _dict:
args['intent'] = _dict.get('intent')
else:
raise ValueError(
'Required property \'intent\' not present in CreateIntent JSON')
if 'description' in _dict:
args['description'] = _dict.get('description')
if 'created' in _dict:
args['created'] = string_to_datetime(_dict.get('created'))
if 'updated' in _dict:
args['updated'] = string_to_datetime(_dict.get('updated'))
if 'examples' in _dict:
args['examples'] = [
Example.from_dict(x) for x in _dict.get('examples')
]
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a CreateIntent object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'intent') and self.intent is not None:
_dict['intent'] = self.intent
if hasattr(self, 'description') and self.description is not None:
_dict['description'] = self.description
if hasattr(self, 'created') and getattr(self, 'created') is not None:
_dict['created'] = datetime_to_string(getattr(self, 'created'))
if hasattr(self, 'updated') and getattr(self, 'updated') is not None:
_dict['updated'] = datetime_to_string(getattr(self, 'updated'))
if hasattr(self, 'examples') and self.examples is not None:
_dict['examples'] = [x.to_dict() for x in self.examples]
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this CreateIntent object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'CreateIntent') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'CreateIntent') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]class CreateValue():
"""
CreateValue.
:attr str value: The text of the entity value. This string must conform to the
following restrictions:
- It cannot contain carriage return, newline, or tab characters.
- It cannot consist of only whitespace characters.
:attr dict metadata: (optional) Any metadata related to the entity value.
:attr str type: (optional) Specifies the type of entity value.
:attr List[str] synonyms: (optional) An array of synonyms for the entity value.
A value can specify either synonyms or patterns (depending on the value type),
but not both. A synonym must conform to the following resrictions:
- It cannot contain carriage return, newline, or tab characters.
- It cannot consist of only whitespace characters.
:attr List[str] patterns: (optional) An array of patterns for the entity value.
A value can specify either synonyms or patterns (depending on the value type),
but not both. A pattern is a regular expression; for more information about how
to specify a pattern, see the
[documentation](https://cloud.ibm.com/docs/assistant?topic=assistant-entities#entities-create-dictionary-based).
:attr datetime created: (optional) The timestamp for creation of the object.
:attr datetime updated: (optional) The timestamp for the most recent update to
the object.
"""
def __init__(self,
value: str,
*,
metadata: dict = None,
type: str = None,
synonyms: List[str] = None,
patterns: List[str] = None,
created: datetime = None,
updated: datetime = None) -> None:
"""
Initialize a CreateValue object.
:param str value: The text of the entity value. This string must conform to
the following restrictions:
- It cannot contain carriage return, newline, or tab characters.
- It cannot consist of only whitespace characters.
:param dict metadata: (optional) Any metadata related to the entity value.
:param str type: (optional) Specifies the type of entity value.
:param List[str] synonyms: (optional) An array of synonyms for the entity
value. A value can specify either synonyms or patterns (depending on the
value type), but not both. A synonym must conform to the following
resrictions:
- It cannot contain carriage return, newline, or tab characters.
- It cannot consist of only whitespace characters.
:param List[str] patterns: (optional) An array of patterns for the entity
value. A value can specify either synonyms or patterns (depending on the
value type), but not both. A pattern is a regular expression; for more
information about how to specify a pattern, see the
[documentation](https://cloud.ibm.com/docs/assistant?topic=assistant-entities#entities-create-dictionary-based).
"""
self.value = value
self.metadata = metadata
self.type = type
self.synonyms = synonyms
self.patterns = patterns
self.created = created
self.updated = updated
[docs] @classmethod
def from_dict(cls, _dict: Dict) -> 'CreateValue':
"""Initialize a CreateValue object from a json dictionary."""
args = {}
if 'value' in _dict:
args['value'] = _dict.get('value')
else:
raise ValueError(
'Required property \'value\' not present in CreateValue JSON')
if 'metadata' in _dict:
args['metadata'] = _dict.get('metadata')
if 'type' in _dict:
args['type'] = _dict.get('type')
if 'synonyms' in _dict:
args['synonyms'] = _dict.get('synonyms')
if 'patterns' in _dict:
args['patterns'] = _dict.get('patterns')
if 'created' in _dict:
args['created'] = string_to_datetime(_dict.get('created'))
if 'updated' in _dict:
args['updated'] = string_to_datetime(_dict.get('updated'))
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a CreateValue object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'value') and self.value is not None:
_dict['value'] = self.value
if hasattr(self, 'metadata') and self.metadata is not None:
_dict['metadata'] = self.metadata
if hasattr(self, 'type') and self.type is not None:
_dict['type'] = self.type
if hasattr(self, 'synonyms') and self.synonyms is not None:
_dict['synonyms'] = self.synonyms
if hasattr(self, 'patterns') and self.patterns is not None:
_dict['patterns'] = self.patterns
if hasattr(self, 'created') and getattr(self, 'created') is not None:
_dict['created'] = datetime_to_string(getattr(self, 'created'))
if hasattr(self, 'updated') and getattr(self, 'updated') is not None:
_dict['updated'] = datetime_to_string(getattr(self, 'updated'))
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this CreateValue object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'CreateValue') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'CreateValue') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs] class TypeEnum(str, Enum):
"""
Specifies the type of entity value.
"""
SYNONYMS = 'synonyms'
PATTERNS = 'patterns'
[docs]class DialogNode():
"""
DialogNode.
:attr str dialog_node: The unique ID of the dialog node. This is an internal
identifier used to refer to the dialog node from other dialog nodes and in the
diagnostic information included with message responses.
This string can contain only Unicode alphanumeric, space, underscore, hyphen,
and dot characters.
:attr str description: (optional) The description of the dialog node. This
string cannot contain carriage return, newline, or tab characters.
:attr str conditions: (optional) The condition that will trigger the dialog
node. This string cannot contain carriage return, newline, or tab characters.
:attr str parent: (optional) The unique ID of the parent dialog node. This
property is omitted if the dialog node has no parent.
:attr str previous_sibling: (optional) The unique ID of the previous sibling
dialog node. This property is omitted if the dialog node has no previous
sibling.
:attr DialogNodeOutput output: (optional) The output of the dialog node. For
more information about how to specify dialog node output, see the
[documentation](https://cloud.ibm.com/docs/assistant?topic=assistant-dialog-overview#dialog-overview-responses).
:attr DialogNodeContext context: (optional) The context for the dialog node.
:attr dict metadata: (optional) The metadata for the dialog node.
:attr DialogNodeNextStep next_step: (optional) The next step to execute
following this dialog node.
:attr str title: (optional) A human-readable name for the dialog node. If the
node is included in disambiguation, this title is used to populate the **label**
property of the corresponding suggestion in the `suggestion` response type
(unless it is overridden by the **user_label** property). The title is also used
to populate the **topic** property in the `connect_to_agent` response type.
This string can contain only Unicode alphanumeric, space, underscore, hyphen,
and dot characters.
:attr str type: (optional) How the dialog node is processed.
:attr str event_name: (optional) How an `event_handler` node is processed.
:attr str variable: (optional) The location in the dialog context where output
is stored.
:attr List[DialogNodeAction] actions: (optional) An array of objects describing
any actions to be invoked by the dialog node.
:attr str digress_in: (optional) Whether this top-level dialog node can be
digressed into.
:attr str digress_out: (optional) Whether this dialog node can be returned to
after a digression.
:attr str digress_out_slots: (optional) Whether the user can digress to
top-level nodes while filling out slots.
:attr str user_label: (optional) A label that can be displayed externally to
describe the purpose of the node to users. If set, this label is used to
identify the node in disambiguation responses (overriding the value of the
**title** property).
:attr bool disambiguation_opt_out: (optional) Whether the dialog node should be
excluded from disambiguation suggestions. Valid only when **type**=`standard` or
`frame`.
:attr bool disabled: (optional) For internal use only.
:attr datetime created: (optional) The timestamp for creation of the object.
:attr datetime updated: (optional) The timestamp for the most recent update to
the object.
"""
def __init__(self,
dialog_node: str,
*,
description: str = None,
conditions: str = None,
parent: str = None,
previous_sibling: str = None,
output: 'DialogNodeOutput' = None,
context: 'DialogNodeContext' = None,
metadata: dict = None,
next_step: 'DialogNodeNextStep' = None,
title: str = None,
type: str = None,
event_name: str = None,
variable: str = None,
actions: List['DialogNodeAction'] = None,
digress_in: str = None,
digress_out: str = None,
digress_out_slots: str = None,
user_label: str = None,
disambiguation_opt_out: bool = None,
disabled: bool = None,
created: datetime = None,
updated: datetime = None) -> None:
"""
Initialize a DialogNode object.
:param str dialog_node: The unique ID of the dialog node. This is an
internal identifier used to refer to the dialog node from other dialog
nodes and in the diagnostic information included with message responses.
This string can contain only Unicode alphanumeric, space, underscore,
hyphen, and dot characters.
:param str description: (optional) The description of the dialog node. This
string cannot contain carriage return, newline, or tab characters.
:param str conditions: (optional) The condition that will trigger the
dialog node. This string cannot contain carriage return, newline, or tab
characters.
:param str parent: (optional) The unique ID of the parent dialog node. This
property is omitted if the dialog node has no parent.
:param str previous_sibling: (optional) The unique ID of the previous
sibling dialog node. This property is omitted if the dialog node has no
previous sibling.
:param DialogNodeOutput output: (optional) The output of the dialog node.
For more information about how to specify dialog node output, see the
[documentation](https://cloud.ibm.com/docs/assistant?topic=assistant-dialog-overview#dialog-overview-responses).
:param DialogNodeContext context: (optional) The context for the dialog
node.
:param dict metadata: (optional) The metadata for the dialog node.
:param DialogNodeNextStep next_step: (optional) The next step to execute
following this dialog node.
:param str title: (optional) A human-readable name for the dialog node. If
the node is included in disambiguation, this title is used to populate the
**label** property of the corresponding suggestion in the `suggestion`
response type (unless it is overridden by the **user_label** property). The
title is also used to populate the **topic** property in the
`connect_to_agent` response type.
This string can contain only Unicode alphanumeric, space, underscore,
hyphen, and dot characters.
:param str type: (optional) How the dialog node is processed.
:param str event_name: (optional) How an `event_handler` node is processed.
:param str variable: (optional) The location in the dialog context where
output is stored.
:param List[DialogNodeAction] actions: (optional) An array of objects
describing any actions to be invoked by the dialog node.
:param str digress_in: (optional) Whether this top-level dialog node can be
digressed into.
:param str digress_out: (optional) Whether this dialog node can be returned
to after a digression.
:param str digress_out_slots: (optional) Whether the user can digress to
top-level nodes while filling out slots.
:param str user_label: (optional) A label that can be displayed externally
to describe the purpose of the node to users. If set, this label is used to
identify the node in disambiguation responses (overriding the value of the
**title** property).
:param bool disambiguation_opt_out: (optional) Whether the dialog node
should be excluded from disambiguation suggestions. Valid only when
**type**=`standard` or `frame`.
"""
self.dialog_node = dialog_node
self.description = description
self.conditions = conditions
self.parent = parent
self.previous_sibling = previous_sibling
self.output = output
self.context = context
self.metadata = metadata
self.next_step = next_step
self.title = title
self.type = type
self.event_name = event_name
self.variable = variable
self.actions = actions
self.digress_in = digress_in
self.digress_out = digress_out
self.digress_out_slots = digress_out_slots
self.user_label = user_label
self.disambiguation_opt_out = disambiguation_opt_out
self.disabled = disabled
self.created = created
self.updated = updated
[docs] @classmethod
def from_dict(cls, _dict: Dict) -> 'DialogNode':
"""Initialize a DialogNode object from a json dictionary."""
args = {}
if 'dialog_node' in _dict:
args['dialog_node'] = _dict.get('dialog_node')
else:
raise ValueError(
'Required property \'dialog_node\' not present in DialogNode JSON'
)
if 'description' in _dict:
args['description'] = _dict.get('description')
if 'conditions' in _dict:
args['conditions'] = _dict.get('conditions')
if 'parent' in _dict:
args['parent'] = _dict.get('parent')
if 'previous_sibling' in _dict:
args['previous_sibling'] = _dict.get('previous_sibling')
if 'output' in _dict:
args['output'] = DialogNodeOutput.from_dict(_dict.get('output'))
if 'context' in _dict:
args['context'] = DialogNodeContext.from_dict(_dict.get('context'))
if 'metadata' in _dict:
args['metadata'] = _dict.get('metadata')
if 'next_step' in _dict:
args['next_step'] = DialogNodeNextStep.from_dict(
_dict.get('next_step'))
if 'title' in _dict:
args['title'] = _dict.get('title')
if 'type' in _dict:
args['type'] = _dict.get('type')
if 'event_name' in _dict:
args['event_name'] = _dict.get('event_name')
if 'variable' in _dict:
args['variable'] = _dict.get('variable')
if 'actions' in _dict:
args['actions'] = [
DialogNodeAction.from_dict(x) for x in _dict.get('actions')
]
if 'digress_in' in _dict:
args['digress_in'] = _dict.get('digress_in')
if 'digress_out' in _dict:
args['digress_out'] = _dict.get('digress_out')
if 'digress_out_slots' in _dict:
args['digress_out_slots'] = _dict.get('digress_out_slots')
if 'user_label' in _dict:
args['user_label'] = _dict.get('user_label')
if 'disambiguation_opt_out' in _dict:
args['disambiguation_opt_out'] = _dict.get('disambiguation_opt_out')
if 'disabled' in _dict:
args['disabled'] = _dict.get('disabled')
if 'created' in _dict:
args['created'] = string_to_datetime(_dict.get('created'))
if 'updated' in _dict:
args['updated'] = string_to_datetime(_dict.get('updated'))
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DialogNode object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'dialog_node') and self.dialog_node is not None:
_dict['dialog_node'] = self.dialog_node
if hasattr(self, 'description') and self.description is not None:
_dict['description'] = self.description
if hasattr(self, 'conditions') and self.conditions is not None:
_dict['conditions'] = self.conditions
if hasattr(self, 'parent') and self.parent is not None:
_dict['parent'] = self.parent
if hasattr(self,
'previous_sibling') and self.previous_sibling is not None:
_dict['previous_sibling'] = self.previous_sibling
if hasattr(self, 'output') and self.output is not None:
_dict['output'] = self.output.to_dict()
if hasattr(self, 'context') and self.context is not None:
_dict['context'] = self.context.to_dict()
if hasattr(self, 'metadata') and self.metadata is not None:
_dict['metadata'] = self.metadata
if hasattr(self, 'next_step') and self.next_step is not None:
_dict['next_step'] = self.next_step.to_dict()
if hasattr(self, 'title') and self.title is not None:
_dict['title'] = self.title
if hasattr(self, 'type') and self.type is not None:
_dict['type'] = self.type
if hasattr(self, 'event_name') and self.event_name is not None:
_dict['event_name'] = self.event_name
if hasattr(self, 'variable') and self.variable is not None:
_dict['variable'] = self.variable
if hasattr(self, 'actions') and self.actions is not None:
_dict['actions'] = [x.to_dict() for x in self.actions]
if hasattr(self, 'digress_in') and self.digress_in is not None:
_dict['digress_in'] = self.digress_in
if hasattr(self, 'digress_out') and self.digress_out is not None:
_dict['digress_out'] = self.digress_out
if hasattr(self,
'digress_out_slots') and self.digress_out_slots is not None:
_dict['digress_out_slots'] = self.digress_out_slots
if hasattr(self, 'user_label') and self.user_label is not None:
_dict['user_label'] = self.user_label
if hasattr(self, 'disambiguation_opt_out'
) and self.disambiguation_opt_out is not None:
_dict['disambiguation_opt_out'] = self.disambiguation_opt_out
if hasattr(self, 'disabled') and getattr(self, 'disabled') is not None:
_dict['disabled'] = getattr(self, 'disabled')
if hasattr(self, 'created') and getattr(self, 'created') is not None:
_dict['created'] = datetime_to_string(getattr(self, 'created'))
if hasattr(self, 'updated') and getattr(self, 'updated') is not None:
_dict['updated'] = datetime_to_string(getattr(self, 'updated'))
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DialogNode object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'DialogNode') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'DialogNode') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs] class TypeEnum(str, Enum):
"""
How the dialog node is processed.
"""
STANDARD = 'standard'
EVENT_HANDLER = 'event_handler'
FRAME = 'frame'
SLOT = 'slot'
RESPONSE_CONDITION = 'response_condition'
FOLDER = 'folder'
[docs] class EventNameEnum(str, Enum):
"""
How an `event_handler` node is processed.
"""
FOCUS = 'focus'
INPUT = 'input'
FILLED = 'filled'
VALIDATE = 'validate'
FILLED_MULTIPLE = 'filled_multiple'
GENERIC = 'generic'
NOMATCH = 'nomatch'
NOMATCH_RESPONSES_DEPLETED = 'nomatch_responses_depleted'
DIGRESSION_RETURN_PROMPT = 'digression_return_prompt'
[docs] class DigressInEnum(str, Enum):
"""
Whether this top-level dialog node can be digressed into.
"""
NOT_AVAILABLE = 'not_available'
RETURNS = 'returns'
DOES_NOT_RETURN = 'does_not_return'
[docs] class DigressOutEnum(str, Enum):
"""
Whether this dialog node can be returned to after a digression.
"""
ALLOW_RETURNING = 'allow_returning'
ALLOW_ALL = 'allow_all'
ALLOW_ALL_NEVER_RETURN = 'allow_all_never_return'
[docs] class DigressOutSlotsEnum(str, Enum):
"""
Whether the user can digress to top-level nodes while filling out slots.
"""
NOT_ALLOWED = 'not_allowed'
ALLOW_RETURNING = 'allow_returning'
ALLOW_ALL = 'allow_all'
[docs]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
[docs] @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)
[docs] 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
[docs] class TypeEnum(str, Enum):
"""
The type of action to invoke.
"""
CLIENT = 'client'
SERVER = 'server'
CLOUD_FUNCTION = 'cloud_function'
WEB_ACTION = 'web_action'
WEBHOOK = 'webhook'
[docs]class DialogNodeCollection():
"""
An array of dialog nodes.
:attr List[DialogNode] dialog_nodes: An array of objects describing the dialog
nodes defined for the workspace.
:attr Pagination pagination: The pagination data for the returned objects.
"""
def __init__(self, dialog_nodes: List['DialogNode'],
pagination: 'Pagination') -> None:
"""
Initialize a DialogNodeCollection object.
:param List[DialogNode] dialog_nodes: An array of objects describing the
dialog nodes defined for the workspace.
:param Pagination pagination: The pagination data for the returned objects.
"""
self.dialog_nodes = dialog_nodes
self.pagination = pagination
[docs] @classmethod
def from_dict(cls, _dict: Dict) -> 'DialogNodeCollection':
"""Initialize a DialogNodeCollection object from a json dictionary."""
args = {}
if 'dialog_nodes' in _dict:
args['dialog_nodes'] = [
DialogNode.from_dict(x) for x in _dict.get('dialog_nodes')
]
else:
raise ValueError(
'Required property \'dialog_nodes\' not present in DialogNodeCollection JSON'
)
if 'pagination' in _dict:
args['pagination'] = Pagination.from_dict(_dict.get('pagination'))
else:
raise ValueError(
'Required property \'pagination\' not present in DialogNodeCollection JSON'
)
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DialogNodeCollection object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'dialog_nodes') and self.dialog_nodes is not None:
_dict['dialog_nodes'] = [x.to_dict() for x in self.dialog_nodes]
if hasattr(self, 'pagination') and self.pagination is not None:
_dict['pagination'] = self.pagination.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DialogNodeCollection object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'DialogNodeCollection') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'DialogNodeCollection') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]class DialogNodeContext():
"""
The context for the dialog node.
:attr dict integrations: (optional) Context data intended for specific
integrations.
"""
# The set of defined properties for the class
_properties = frozenset(['integrations'])
def __init__(self, *, integrations: dict = None, **kwargs) -> None:
"""
Initialize a DialogNodeContext object.
:param dict integrations: (optional) Context data intended for specific
integrations.
:param **kwargs: (optional) Any additional properties.
"""
self.integrations = integrations
for _key, _value in kwargs.items():
setattr(self, _key, _value)
[docs] @classmethod
def from_dict(cls, _dict: Dict) -> 'DialogNodeContext':
"""Initialize a DialogNodeContext object from a json dictionary."""
args = {}
if 'integrations' in _dict:
args['integrations'] = _dict.get('integrations')
args.update(
{k: v for (k, v) in _dict.items() if k not in cls._properties})
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DialogNodeContext object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'integrations') and self.integrations is not None:
_dict['integrations'] = self.integrations
for _key in [
k for k in vars(self).keys()
if k not in DialogNodeContext._properties
]:
if getattr(self, _key, None) is not None:
_dict[_key] = getattr(self, _key)
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DialogNodeContext object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'DialogNodeContext') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'DialogNodeContext') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]class DialogNodeNextStep():
"""
The next step to execute following this dialog node.
:attr str behavior: What happens after the dialog node completes. The valid
values depend on the node type:
- The following values are valid for any node:
- `get_user_input`
- `skip_user_input`
- `jump_to`
- If the node is of type `event_handler` and its parent node is of type `slot`
or `frame`, additional values are also valid:
- if **event_name**=`filled` and the type of the parent node is `slot`:
- `reprompt`
- `skip_all_slots`
- if **event_name**=`nomatch` and the type of the parent node is `slot`:
- `reprompt`
- `skip_slot`
- `skip_all_slots`
- if **event_name**=`generic` and the type of the parent node is `frame`:
- `reprompt`
- `skip_slot`
- `skip_all_slots`
If you specify `jump_to`, then you must also specify a value for the
`dialog_node` property.
:attr str dialog_node: (optional) The unique ID of the dialog node to process
next. This parameter is required if **behavior**=`jump_to`.
:attr str selector: (optional) Which part of the dialog node to process next.
"""
def __init__(self,
behavior: str,
*,
dialog_node: str = None,
selector: str = None) -> None:
"""
Initialize a DialogNodeNextStep object.
:param str behavior: What happens after the dialog node completes. The
valid values depend on the node type:
- The following values are valid for any node:
- `get_user_input`
- `skip_user_input`
- `jump_to`
- If the node is of type `event_handler` and its parent node is of type
`slot` or `frame`, additional values are also valid:
- if **event_name**=`filled` and the type of the parent node is `slot`:
- `reprompt`
- `skip_all_slots`
- if **event_name**=`nomatch` and the type of the parent node is `slot`:
- `reprompt`
- `skip_slot`
- `skip_all_slots`
- if **event_name**=`generic` and the type of the parent node is `frame`:
- `reprompt`
- `skip_slot`
- `skip_all_slots`
If you specify `jump_to`, then you must also specify a value for the
`dialog_node` property.
:param str dialog_node: (optional) The unique ID of the dialog node to
process next. This parameter is required if **behavior**=`jump_to`.
:param str selector: (optional) Which part of the dialog node to process
next.
"""
self.behavior = behavior
self.dialog_node = dialog_node
self.selector = selector
[docs] @classmethod
def from_dict(cls, _dict: Dict) -> 'DialogNodeNextStep':
"""Initialize a DialogNodeNextStep object from a json dictionary."""
args = {}
if 'behavior' in _dict:
args['behavior'] = _dict.get('behavior')
else:
raise ValueError(
'Required property \'behavior\' not present in DialogNodeNextStep JSON'
)
if 'dialog_node' in _dict:
args['dialog_node'] = _dict.get('dialog_node')
if 'selector' in _dict:
args['selector'] = _dict.get('selector')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DialogNodeNextStep object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'behavior') and self.behavior is not None:
_dict['behavior'] = self.behavior
if hasattr(self, 'dialog_node') and self.dialog_node is not None:
_dict['dialog_node'] = self.dialog_node
if hasattr(self, 'selector') and self.selector is not None:
_dict['selector'] = self.selector
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DialogNodeNextStep object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'DialogNodeNextStep') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'DialogNodeNextStep') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs] class BehaviorEnum(str, Enum):
"""
What happens after the dialog node completes. The valid values depend on the node
type:
- The following values are valid for any node:
- `get_user_input`
- `skip_user_input`
- `jump_to`
- If the node is of type `event_handler` and its parent node is of type `slot` or
`frame`, additional values are also valid:
- if **event_name**=`filled` and the type of the parent node is `slot`:
- `reprompt`
- `skip_all_slots`
- if **event_name**=`nomatch` and the type of the parent node is `slot`:
- `reprompt`
- `skip_slot`
- `skip_all_slots`
- if **event_name**=`generic` and the type of the parent node is `frame`:
- `reprompt`
- `skip_slot`
- `skip_all_slots`
If you specify `jump_to`, then you must also specify a value for the
`dialog_node` property.
"""
GET_USER_INPUT = 'get_user_input'
SKIP_USER_INPUT = 'skip_user_input'
JUMP_TO = 'jump_to'
REPROMPT = 'reprompt'
SKIP_SLOT = 'skip_slot'
SKIP_ALL_SLOTS = 'skip_all_slots'
[docs] class SelectorEnum(str, Enum):
"""
Which part of the dialog node to process next.
"""
CONDITION = 'condition'
CLIENT = 'client'
USER_INPUT = 'user_input'
BODY = 'body'
[docs]class DialogNodeOutput():
"""
The output of the dialog node. For more information about how to specify dialog node
output, see the
[documentation](https://cloud.ibm.com/docs/assistant?topic=assistant-dialog-overview#dialog-overview-responses).
:attr List[DialogNodeOutputGeneric] generic: (optional) An array of objects
describing the output defined for the dialog node.
:attr dict integrations: (optional) Output intended for specific integrations.
For more information, see the
[documentation](https://cloud.ibm.com/docs/assistant?topic=assistant-dialog-responses-json).
:attr DialogNodeOutputModifiers modifiers: (optional) Options that modify how
specified output is handled.
"""
# The set of defined properties for the class
_properties = frozenset(['generic', 'integrations', 'modifiers'])
def __init__(self,
*,
generic: List['DialogNodeOutputGeneric'] = None,
integrations: dict = None,
modifiers: 'DialogNodeOutputModifiers' = None,
**kwargs) -> None:
"""
Initialize a DialogNodeOutput object.
:param List[DialogNodeOutputGeneric] generic: (optional) An array of
objects describing the output defined for the dialog node.
:param dict integrations: (optional) Output intended for specific
integrations. For more information, see the
[documentation](https://cloud.ibm.com/docs/assistant?topic=assistant-dialog-responses-json).
:param DialogNodeOutputModifiers modifiers: (optional) Options that modify
how specified output is handled.
:param **kwargs: (optional) Any additional properties.
"""
self.generic = generic
self.integrations = integrations
self.modifiers = modifiers
for _key, _value in kwargs.items():
setattr(self, _key, _value)
[docs] @classmethod
def from_dict(cls, _dict: Dict) -> 'DialogNodeOutput':
"""Initialize a DialogNodeOutput object from a json dictionary."""
args = {}
if 'generic' in _dict:
args['generic'] = [
DialogNodeOutputGeneric.from_dict(x)
for x in _dict.get('generic')
]
if 'integrations' in _dict:
args['integrations'] = _dict.get('integrations')
if 'modifiers' in _dict:
args['modifiers'] = DialogNodeOutputModifiers.from_dict(
_dict.get('modifiers'))
args.update(
{k: v for (k, v) in _dict.items() if k not in cls._properties})
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DialogNodeOutput object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'generic') and self.generic is not None:
_dict['generic'] = [x.to_dict() for x in self.generic]
if hasattr(self, 'integrations') and self.integrations is not None:
_dict['integrations'] = self.integrations
if hasattr(self, 'modifiers') and self.modifiers is not None:
_dict['modifiers'] = self.modifiers.to_dict()
for _key in [
k for k in vars(self).keys()
if k not in DialogNodeOutput._properties
]:
if getattr(self, _key, None) is not None:
_dict[_key] = getattr(self, _key)
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DialogNodeOutput object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'DialogNodeOutput') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'DialogNodeOutput') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]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
[docs] @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)
[docs] 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
[docs]class DialogNodeOutputGeneric():
"""
DialogNodeOutputGeneric.
"""
def __init__(self) -> None:
"""
Initialize a DialogNodeOutputGeneric object.
"""
msg = "Cannot instantiate base class. Instead, instantiate one of the defined subclasses: {0}".format(
", ".join([
'DialogNodeOutputGenericDialogNodeOutputResponseTypeText',
'DialogNodeOutputGenericDialogNodeOutputResponseTypePause',
'DialogNodeOutputGenericDialogNodeOutputResponseTypeImage',
'DialogNodeOutputGenericDialogNodeOutputResponseTypeOption',
'DialogNodeOutputGenericDialogNodeOutputResponseTypeConnectToAgent',
'DialogNodeOutputGenericDialogNodeOutputResponseTypeSearchSkill',
'DialogNodeOutputGenericDialogNodeOutputResponseTypeChannelTransfer',
'DialogNodeOutputGenericDialogNodeOutputResponseTypeUserDefined'
]))
raise Exception(msg)
[docs] @classmethod
def from_dict(cls, _dict: Dict) -> 'DialogNodeOutputGeneric':
"""Initialize a DialogNodeOutputGeneric object from a json dictionary."""
disc_class = cls._get_class_by_discriminator(_dict)
if disc_class != cls:
return disc_class.from_dict(_dict)
msg = (
"Cannot convert dictionary into an instance of base class 'DialogNodeOutputGeneric'. "
+ "The discriminator value should map to a valid subclass: {1}"
).format(", ".join([
'DialogNodeOutputGenericDialogNodeOutputResponseTypeText',
'DialogNodeOutputGenericDialogNodeOutputResponseTypePause',
'DialogNodeOutputGenericDialogNodeOutputResponseTypeImage',
'DialogNodeOutputGenericDialogNodeOutputResponseTypeOption',
'DialogNodeOutputGenericDialogNodeOutputResponseTypeConnectToAgent',
'DialogNodeOutputGenericDialogNodeOutputResponseTypeSearchSkill',
'DialogNodeOutputGenericDialogNodeOutputResponseTypeChannelTransfer',
'DialogNodeOutputGenericDialogNodeOutputResponseTypeUserDefined'
]))
raise Exception(msg)
@classmethod
def _from_dict(cls, _dict: Dict):
"""Initialize a DialogNodeOutputGeneric object from a json dictionary."""
return cls.from_dict(_dict)
@classmethod
def _get_class_by_discriminator(cls, _dict: Dict) -> object:
mapping = {}
mapping[
'channel_transfer'] = 'DialogNodeOutputGenericDialogNodeOutputResponseTypeChannelTransfer'
mapping[
'connect_to_agent'] = 'DialogNodeOutputGenericDialogNodeOutputResponseTypeConnectToAgent'
mapping[
'image'] = 'DialogNodeOutputGenericDialogNodeOutputResponseTypeImage'
mapping[
'option'] = 'DialogNodeOutputGenericDialogNodeOutputResponseTypeOption'
mapping[
'pause'] = 'DialogNodeOutputGenericDialogNodeOutputResponseTypePause'
mapping[
'search_skill'] = 'DialogNodeOutputGenericDialogNodeOutputResponseTypeSearchSkill'
mapping[
'text'] = 'DialogNodeOutputGenericDialogNodeOutputResponseTypeText'
mapping[
'user_defined'] = 'DialogNodeOutputGenericDialogNodeOutputResponseTypeUserDefined'
disc_value = _dict.get('response_type')
if disc_value is None:
raise ValueError(
'Discriminator property \'response_type\' not found in DialogNodeOutputGeneric JSON'
)
class_name = mapping.get(disc_value, disc_value)
try:
disc_class = getattr(sys.modules[__name__], class_name)
except AttributeError:
disc_class = cls
if isinstance(disc_class, object):
return disc_class
raise TypeError('%s is not a discriminator class' % class_name)
[docs]class DialogNodeOutputModifiers():
"""
Options that modify how specified output is handled.
:attr bool overwrite: (optional) Whether values in the output will overwrite
output values in an array specified by previously executed dialog nodes. If this
option is set to `false`, new values will be appended to previously specified
values.
"""
def __init__(self, *, overwrite: bool = None) -> None:
"""
Initialize a DialogNodeOutputModifiers object.
:param bool overwrite: (optional) Whether values in the output will
overwrite output values in an array specified by previously executed dialog
nodes. If this option is set to `false`, new values will be appended to
previously specified values.
"""
self.overwrite = overwrite
[docs] @classmethod
def from_dict(cls, _dict: Dict) -> 'DialogNodeOutputModifiers':
"""Initialize a DialogNodeOutputModifiers object from a json dictionary."""
args = {}
if 'overwrite' in _dict:
args['overwrite'] = _dict.get('overwrite')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DialogNodeOutputModifiers object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'overwrite') and self.overwrite is not None:
_dict['overwrite'] = self.overwrite
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DialogNodeOutputModifiers object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'DialogNodeOutputModifiers') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'DialogNodeOutputModifiers') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]class DialogNodeOutputOptionsElement():
"""
DialogNodeOutputOptionsElement.
:attr str label: The user-facing label for the option.
:attr DialogNodeOutputOptionsElementValue value: An object defining the message
input to be sent to the Watson Assistant service if the user selects the
corresponding option.
"""
def __init__(self, label: str,
value: 'DialogNodeOutputOptionsElementValue') -> None:
"""
Initialize a DialogNodeOutputOptionsElement object.
:param str label: The user-facing label for the option.
:param DialogNodeOutputOptionsElementValue value: An object defining the
message input to be sent to the Watson Assistant service if the user
selects the corresponding option.
"""
self.label = label
self.value = value
[docs] @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)
[docs] 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
[docs]class DialogNodeOutputOptionsElementValue():
"""
An object defining the message input to be sent to the Watson Assistant service if the
user selects the corresponding option.
:attr MessageInput input: (optional) An input object that includes the input
text.
:attr List[RuntimeIntent] intents: (optional) An array of intents to be used
while processing the input.
**Note:** This property is supported for backward compatibility with
applications that use the v1 **Get response to user input** method.
:attr List[RuntimeEntity] entities: (optional) An array of entities to be used
while processing the user input.
**Note:** This property is supported for backward compatibility with
applications that use the v1 **Get response to user input** method.
"""
def __init__(self,
*,
input: 'MessageInput' = None,
intents: List['RuntimeIntent'] = None,
entities: List['RuntimeEntity'] = None) -> None:
"""
Initialize a DialogNodeOutputOptionsElementValue object.
:param MessageInput input: (optional) An input object that includes the
input text.
:param List[RuntimeIntent] intents: (optional) An array of intents to be
used while processing the input.
**Note:** This property is supported for backward compatibility with
applications that use the v1 **Get response to user input** method.
:param List[RuntimeEntity] entities: (optional) An array of entities to be
used while processing the user input.
**Note:** This property is supported for backward compatibility with
applications that use the v1 **Get response to user input** method.
"""
self.input = input
self.intents = intents
self.entities = entities
[docs] @classmethod
def from_dict(cls, _dict: Dict) -> 'DialogNodeOutputOptionsElementValue':
"""Initialize a DialogNodeOutputOptionsElementValue object from a json dictionary."""
args = {}
if 'input' in _dict:
args['input'] = MessageInput.from_dict(_dict.get('input'))
if 'intents' in _dict:
args['intents'] = [
RuntimeIntent.from_dict(x) for x in _dict.get('intents')
]
if 'entities' in _dict:
args['entities'] = [
RuntimeEntity.from_dict(x) for x in _dict.get('entities')
]
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DialogNodeOutputOptionsElementValue object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'input') and self.input is not None:
_dict['input'] = self.input.to_dict()
if hasattr(self, 'intents') and self.intents is not None:
_dict['intents'] = [x.to_dict() for x in self.intents]
if hasattr(self, 'entities') and self.entities is not None:
_dict['entities'] = [x.to_dict() for x in self.entities]
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DialogNodeOutputOptionsElementValue object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'DialogNodeOutputOptionsElementValue') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'DialogNodeOutputOptionsElementValue') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]class DialogNodeOutputTextValuesElement():
"""
DialogNodeOutputTextValuesElement.
:attr str text: (optional) The text of a response. This string can include
newline characters (`\n`), Markdown tagging, or other special characters, if
supported by the channel.
"""
def __init__(self, *, text: str = None) -> None:
"""
Initialize a DialogNodeOutputTextValuesElement object.
:param str text: (optional) The text of a response. This string can include
newline characters (`\n`), Markdown tagging, or other special characters,
if supported by the channel.
"""
self.text = text
[docs] @classmethod
def from_dict(cls, _dict: Dict) -> 'DialogNodeOutputTextValuesElement':
"""Initialize a DialogNodeOutputTextValuesElement object from a json dictionary."""
args = {}
if 'text' in _dict:
args['text'] = _dict.get('text')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DialogNodeOutputTextValuesElement object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'text') and self.text is not None:
_dict['text'] = self.text
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DialogNodeOutputTextValuesElement object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'DialogNodeOutputTextValuesElement') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'DialogNodeOutputTextValuesElement') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]class DialogNodeVisitedDetails():
"""
DialogNodeVisitedDetails.
:attr str dialog_node: (optional) The unique ID of a dialog node that was
triggered during processing of the input message.
:attr str title: (optional) The title of the dialog node.
:attr str conditions: (optional) The conditions that trigger the dialog node.
"""
def __init__(self,
*,
dialog_node: str = None,
title: str = None,
conditions: str = None) -> None:
"""
Initialize a DialogNodeVisitedDetails object.
:param str dialog_node: (optional) The unique ID of a dialog node that was
triggered during processing of the input message.
:param str title: (optional) The title of the dialog node.
:param str conditions: (optional) The conditions that trigger the dialog
node.
"""
self.dialog_node = dialog_node
self.title = title
self.conditions = conditions
[docs] @classmethod
def from_dict(cls, _dict: Dict) -> 'DialogNodeVisitedDetails':
"""Initialize a DialogNodeVisitedDetails object from a json dictionary."""
args = {}
if 'dialog_node' in _dict:
args['dialog_node'] = _dict.get('dialog_node')
if 'title' in _dict:
args['title'] = _dict.get('title')
if 'conditions' in _dict:
args['conditions'] = _dict.get('conditions')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DialogNodeVisitedDetails object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'dialog_node') and self.dialog_node is not None:
_dict['dialog_node'] = self.dialog_node
if hasattr(self, 'title') and self.title is not None:
_dict['title'] = self.title
if hasattr(self, 'conditions') and self.conditions is not None:
_dict['conditions'] = self.conditions
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DialogNodeVisitedDetails object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'DialogNodeVisitedDetails') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'DialogNodeVisitedDetails') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]class DialogSuggestion():
"""
DialogSuggestion.
:attr str label: The user-facing label for the disambiguation option. This label
is taken from the **title** or **user_label** property of the corresponding
dialog node.
:attr DialogSuggestionValue value: An object defining the message input,
intents, and entities to be sent to the Watson Assistant service if the user
selects the corresponding disambiguation option.
:attr dict output: (optional) The dialog output that will be returned from the
Watson Assistant service if the user selects the corresponding option.
:attr str dialog_node: (optional) The unique ID of the dialog node that the
**label** property is taken from. The **label** property is populated using the
value of the dialog node's **title** or **user_label** property.
"""
def __init__(self,
label: str,
value: 'DialogSuggestionValue',
*,
output: dict = None,
dialog_node: str = None) -> None:
"""
Initialize a DialogSuggestion object.
:param str label: The user-facing label for the disambiguation option. This
label is taken from the **title** or **user_label** property of the
corresponding dialog node.
:param DialogSuggestionValue value: An object defining the message input,
intents, and entities to be sent to the Watson Assistant service if the
user selects the corresponding disambiguation option.
:param dict output: (optional) The dialog output that will be returned from
the Watson Assistant service if the user selects the corresponding option.
:param str dialog_node: (optional) The unique ID of the dialog node that
the **label** property is taken from. The **label** property is populated
using the value of the dialog node's **title** or **user_label** property.
"""
self.label = label
self.value = value
self.output = output
self.dialog_node = dialog_node
[docs] @classmethod
def from_dict(cls, _dict: Dict) -> 'DialogSuggestion':
"""Initialize a DialogSuggestion object from a json dictionary."""
args = {}
if 'label' in _dict:
args['label'] = _dict.get('label')
else:
raise ValueError(
'Required property \'label\' not present in DialogSuggestion JSON'
)
if 'value' in _dict:
args['value'] = DialogSuggestionValue.from_dict(_dict.get('value'))
else:
raise ValueError(
'Required property \'value\' not present in DialogSuggestion JSON'
)
if 'output' in _dict:
args['output'] = _dict.get('output')
if 'dialog_node' in _dict:
args['dialog_node'] = _dict.get('dialog_node')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DialogSuggestion object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'label') and self.label is not None:
_dict['label'] = self.label
if hasattr(self, 'value') and self.value is not None:
_dict['value'] = self.value.to_dict()
if hasattr(self, 'output') and self.output is not None:
_dict['output'] = self.output
if hasattr(self, 'dialog_node') and self.dialog_node is not None:
_dict['dialog_node'] = self.dialog_node
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DialogSuggestion object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'DialogSuggestion') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'DialogSuggestion') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]class DialogSuggestionValue():
"""
An object defining the message input, intents, and entities to be sent to the Watson
Assistant service if the user selects the corresponding disambiguation option.
:attr MessageInput input: (optional) An input object that includes the input
text.
:attr List[RuntimeIntent] intents: (optional) An array of intents to be sent
along with the user input.
:attr List[RuntimeEntity] entities: (optional) An array of entities to be sent
along with the user input.
"""
def __init__(self,
*,
input: 'MessageInput' = None,
intents: List['RuntimeIntent'] = None,
entities: List['RuntimeEntity'] = None) -> None:
"""
Initialize a DialogSuggestionValue object.
:param MessageInput input: (optional) An input object that includes the
input text.
:param List[RuntimeIntent] intents: (optional) An array of intents to be
sent along with the user input.
:param List[RuntimeEntity] entities: (optional) An array of entities to be
sent along with the user input.
"""
self.input = input
self.intents = intents
self.entities = entities
[docs] @classmethod
def from_dict(cls, _dict: Dict) -> 'DialogSuggestionValue':
"""Initialize a DialogSuggestionValue object from a json dictionary."""
args = {}
if 'input' in _dict:
args['input'] = MessageInput.from_dict(_dict.get('input'))
if 'intents' in _dict:
args['intents'] = [
RuntimeIntent.from_dict(x) for x in _dict.get('intents')
]
if 'entities' in _dict:
args['entities'] = [
RuntimeEntity.from_dict(x) for x in _dict.get('entities')
]
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DialogSuggestionValue object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'input') and self.input is not None:
_dict['input'] = self.input.to_dict()
if hasattr(self, 'intents') and self.intents is not None:
_dict['intents'] = [x.to_dict() for x in self.intents]
if hasattr(self, 'entities') and self.entities is not None:
_dict['entities'] = [x.to_dict() for x in self.entities]
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DialogSuggestionValue object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'DialogSuggestionValue') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'DialogSuggestionValue') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]class Entity():
"""
Entity.
:attr str entity: The name of the entity. This string must conform to the
following restrictions:
- It can contain only Unicode alphanumeric, underscore, and hyphen characters.
- If you specify an entity name beginning with the reserved prefix `sys-`, it
must be the name of a system entity that you want to enable. (Any entity content
specified with the request is ignored.).
:attr str description: (optional) The description of the entity. This string
cannot contain carriage return, newline, or tab characters.
:attr dict metadata: (optional) Any metadata related to the entity.
:attr bool fuzzy_match: (optional) Whether to use fuzzy matching for the entity.
:attr datetime created: (optional) The timestamp for creation of the object.
:attr datetime updated: (optional) The timestamp for the most recent update to
the object.
:attr List[Value] values: (optional) An array of objects describing the entity
values.
"""
def __init__(self,
entity: str,
*,
description: str = None,
metadata: dict = None,
fuzzy_match: bool = None,
created: datetime = None,
updated: datetime = None,
values: List['Value'] = None) -> None:
"""
Initialize a Entity object.
:param str entity: The name of the entity. This string must conform to the
following restrictions:
- It can contain only Unicode alphanumeric, underscore, and hyphen
characters.
- If you specify an entity name beginning with the reserved prefix `sys-`,
it must be the name of a system entity that you want to enable. (Any entity
content specified with the request is ignored.).
:param str description: (optional) The description of the entity. This
string cannot contain carriage return, newline, or tab characters.
:param dict metadata: (optional) Any metadata related to the entity.
:param bool fuzzy_match: (optional) Whether to use fuzzy matching for the
entity.
:param List[Value] values: (optional) An array of objects describing the
entity values.
"""
self.entity = entity
self.description = description
self.metadata = metadata
self.fuzzy_match = fuzzy_match
self.created = created
self.updated = updated
self.values = values
[docs] @classmethod
def from_dict(cls, _dict: Dict) -> 'Entity':
"""Initialize a Entity object from a json dictionary."""
args = {}
if 'entity' in _dict:
args['entity'] = _dict.get('entity')
else:
raise ValueError(
'Required property \'entity\' not present in Entity JSON')
if 'description' in _dict:
args['description'] = _dict.get('description')
if 'metadata' in _dict:
args['metadata'] = _dict.get('metadata')
if 'fuzzy_match' in _dict:
args['fuzzy_match'] = _dict.get('fuzzy_match')
if 'created' in _dict:
args['created'] = string_to_datetime(_dict.get('created'))
if 'updated' in _dict:
args['updated'] = string_to_datetime(_dict.get('updated'))
if 'values' in _dict:
args['values'] = [Value.from_dict(x) for x in _dict.get('values')]
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a Entity object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'entity') and self.entity is not None:
_dict['entity'] = self.entity
if hasattr(self, 'description') and self.description is not None:
_dict['description'] = self.description
if hasattr(self, 'metadata') and self.metadata is not None:
_dict['metadata'] = self.metadata
if hasattr(self, 'fuzzy_match') and self.fuzzy_match is not None:
_dict['fuzzy_match'] = self.fuzzy_match
if hasattr(self, 'created') and getattr(self, 'created') is not None:
_dict['created'] = datetime_to_string(getattr(self, 'created'))
if hasattr(self, 'updated') and getattr(self, 'updated') is not None:
_dict['updated'] = datetime_to_string(getattr(self, 'updated'))
if hasattr(self, 'values') and self.values is not None:
_dict['values'] = [x.to_dict() for x in self.values]
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this Entity object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'Entity') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'Entity') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]class EntityCollection():
"""
An array of objects describing the entities for the workspace.
:attr List[Entity] entities: An array of objects describing the entities defined
for the workspace.
:attr Pagination pagination: The pagination data for the returned objects.
"""
def __init__(self, entities: List['Entity'],
pagination: 'Pagination') -> None:
"""
Initialize a EntityCollection object.
:param List[Entity] entities: An array of objects describing the entities
defined for the workspace.
:param Pagination pagination: The pagination data for the returned objects.
"""
self.entities = entities
self.pagination = pagination
[docs] @classmethod
def from_dict(cls, _dict: Dict) -> 'EntityCollection':
"""Initialize a EntityCollection object from a json dictionary."""
args = {}
if 'entities' in _dict:
args['entities'] = [
Entity.from_dict(x) for x in _dict.get('entities')
]
else:
raise ValueError(
'Required property \'entities\' not present in EntityCollection JSON'
)
if 'pagination' in _dict:
args['pagination'] = Pagination.from_dict(_dict.get('pagination'))
else:
raise ValueError(
'Required property \'pagination\' not present in EntityCollection JSON'
)
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a EntityCollection object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'entities') and self.entities is not None:
_dict['entities'] = [x.to_dict() for x in self.entities]
if hasattr(self, 'pagination') and self.pagination is not None:
_dict['pagination'] = self.pagination.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this EntityCollection object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'EntityCollection') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'EntityCollection') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]class EntityMention():
"""
An object describing a contextual entity mention.
:attr str text: The text of the user input example.
:attr str intent: The name of the intent.
:attr List[int] location: An array of zero-based character offsets that indicate
where the entity mentions begin and end in the input text.
"""
def __init__(self, text: str, intent: str, location: List[int]) -> None:
"""
Initialize a EntityMention object.
:param str text: The text of the user input example.
:param str intent: The name of the intent.
:param List[int] location: An array of zero-based character offsets that
indicate where the entity mentions begin and end in the input text.
"""
self.text = text
self.intent = intent
self.location = location
[docs] @classmethod
def from_dict(cls, _dict: Dict) -> 'EntityMention':
"""Initialize a EntityMention object from a json dictionary."""
args = {}
if 'text' in _dict:
args['text'] = _dict.get('text')
else:
raise ValueError(
'Required property \'text\' not present in EntityMention JSON')
if 'intent' in _dict:
args['intent'] = _dict.get('intent')
else:
raise ValueError(
'Required property \'intent\' not present in EntityMention JSON'
)
if 'location' in _dict:
args['location'] = _dict.get('location')
else:
raise ValueError(
'Required property \'location\' not present in EntityMention JSON'
)
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a EntityMention object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'text') and self.text is not None:
_dict['text'] = self.text
if hasattr(self, 'intent') and self.intent is not None:
_dict['intent'] = self.intent
if hasattr(self, 'location') and self.location is not None:
_dict['location'] = self.location
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this EntityMention object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'EntityMention') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'EntityMention') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]class EntityMentionCollection():
"""
EntityMentionCollection.
:attr List[EntityMention] examples: An array of objects describing the entity
mentions defined for an entity.
:attr Pagination pagination: The pagination data for the returned objects.
"""
def __init__(self, examples: List['EntityMention'],
pagination: 'Pagination') -> None:
"""
Initialize a EntityMentionCollection object.
:param List[EntityMention] examples: An array of objects describing the
entity mentions defined for an entity.
:param Pagination pagination: The pagination data for the returned objects.
"""
self.examples = examples
self.pagination = pagination
[docs] @classmethod
def from_dict(cls, _dict: Dict) -> 'EntityMentionCollection':
"""Initialize a EntityMentionCollection object from a json dictionary."""
args = {}
if 'examples' in _dict:
args['examples'] = [
EntityMention.from_dict(x) for x in _dict.get('examples')
]
else:
raise ValueError(
'Required property \'examples\' not present in EntityMentionCollection JSON'
)
if 'pagination' in _dict:
args['pagination'] = Pagination.from_dict(_dict.get('pagination'))
else:
raise ValueError(
'Required property \'pagination\' not present in EntityMentionCollection JSON'
)
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a EntityMentionCollection object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'examples') and self.examples is not None:
_dict['examples'] = [x.to_dict() for x in self.examples]
if hasattr(self, 'pagination') and self.pagination is not None:
_dict['pagination'] = self.pagination.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this EntityMentionCollection object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'EntityMentionCollection') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'EntityMentionCollection') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]class Example():
"""
Example.
:attr str text: The text of a user input example. This string must conform to
the following restrictions:
- It cannot contain carriage return, newline, or tab characters.
- It cannot consist of only whitespace characters.
:attr List[Mention] mentions: (optional) An array of contextual entity mentions.
:attr datetime created: (optional) The timestamp for creation of the object.
:attr datetime updated: (optional) The timestamp for the most recent update to
the object.
"""
def __init__(self,
text: str,
*,
mentions: List['Mention'] = None,
created: datetime = None,
updated: datetime = None) -> None:
"""
Initialize a Example object.
:param str text: The text of a user input example. This string must conform
to the following restrictions:
- It cannot contain carriage return, newline, or tab characters.
- It cannot consist of only whitespace characters.
:param List[Mention] mentions: (optional) An array of contextual entity
mentions.
"""
self.text = text
self.mentions = mentions
self.created = created
self.updated = updated
[docs] @classmethod
def from_dict(cls, _dict: Dict) -> 'Example':
"""Initialize a Example object from a json dictionary."""
args = {}
if 'text' in _dict:
args['text'] = _dict.get('text')
else:
raise ValueError(
'Required property \'text\' not present in Example JSON')
if 'mentions' in _dict:
args['mentions'] = [
Mention.from_dict(x) for x in _dict.get('mentions')
]
if 'created' in _dict:
args['created'] = string_to_datetime(_dict.get('created'))
if 'updated' in _dict:
args['updated'] = string_to_datetime(_dict.get('updated'))
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a Example object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'text') and self.text is not None:
_dict['text'] = self.text
if hasattr(self, 'mentions') and self.mentions is not None:
_dict['mentions'] = [x.to_dict() for x in self.mentions]
if hasattr(self, 'created') and getattr(self, 'created') is not None:
_dict['created'] = datetime_to_string(getattr(self, 'created'))
if hasattr(self, 'updated') and getattr(self, 'updated') is not None:
_dict['updated'] = datetime_to_string(getattr(self, 'updated'))
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this Example object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'Example') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'Example') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]class ExampleCollection():
"""
ExampleCollection.
:attr List[Example] examples: An array of objects describing the examples
defined for the intent.
:attr Pagination pagination: The pagination data for the returned objects.
"""
def __init__(self, examples: List['Example'],
pagination: 'Pagination') -> None:
"""
Initialize a ExampleCollection object.
:param List[Example] examples: An array of objects describing the examples
defined for the intent.
:param Pagination pagination: The pagination data for the returned objects.
"""
self.examples = examples
self.pagination = pagination
[docs] @classmethod
def from_dict(cls, _dict: Dict) -> 'ExampleCollection':
"""Initialize a ExampleCollection object from a json dictionary."""
args = {}
if 'examples' in _dict:
args['examples'] = [
Example.from_dict(x) for x in _dict.get('examples')
]
else:
raise ValueError(
'Required property \'examples\' not present in ExampleCollection JSON'
)
if 'pagination' in _dict:
args['pagination'] = Pagination.from_dict(_dict.get('pagination'))
else:
raise ValueError(
'Required property \'pagination\' not present in ExampleCollection JSON'
)
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a ExampleCollection object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'examples') and self.examples is not None:
_dict['examples'] = [x.to_dict() for x in self.examples]
if hasattr(self, 'pagination') and self.pagination is not None:
_dict['pagination'] = self.pagination.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this ExampleCollection object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'ExampleCollection') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'ExampleCollection') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]class Intent():
"""
Intent.
:attr str intent: The name of the intent. This string must conform to the
following restrictions:
- It can contain only Unicode alphanumeric, underscore, hyphen, and dot
characters.
- It cannot begin with the reserved prefix `sys-`.
:attr str description: (optional) The description of the intent. This string
cannot contain carriage return, newline, or tab characters.
:attr datetime created: (optional) The timestamp for creation of the object.
:attr datetime updated: (optional) The timestamp for the most recent update to
the object.
:attr List[Example] examples: (optional) An array of user input examples for the
intent.
"""
def __init__(self,
intent: str,
*,
description: str = None,
created: datetime = None,
updated: datetime = None,
examples: List['Example'] = None) -> None:
"""
Initialize a Intent object.
:param str intent: The name of the intent. This string must conform to the
following restrictions:
- It can contain only Unicode alphanumeric, underscore, hyphen, and dot
characters.
- It cannot begin with the reserved prefix `sys-`.
:param str description: (optional) The description of the intent. This
string cannot contain carriage return, newline, or tab characters.
:param List[Example] examples: (optional) An array of user input examples
for the intent.
"""
self.intent = intent
self.description = description
self.created = created
self.updated = updated
self.examples = examples
[docs] @classmethod
def from_dict(cls, _dict: Dict) -> 'Intent':
"""Initialize a Intent object from a json dictionary."""
args = {}
if 'intent' in _dict:
args['intent'] = _dict.get('intent')
else:
raise ValueError(
'Required property \'intent\' not present in Intent JSON')
if 'description' in _dict:
args['description'] = _dict.get('description')
if 'created' in _dict:
args['created'] = string_to_datetime(_dict.get('created'))
if 'updated' in _dict:
args['updated'] = string_to_datetime(_dict.get('updated'))
if 'examples' in _dict:
args['examples'] = [
Example.from_dict(x) for x in _dict.get('examples')
]
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a Intent object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'intent') and self.intent is not None:
_dict['intent'] = self.intent
if hasattr(self, 'description') and self.description is not None:
_dict['description'] = self.description
if hasattr(self, 'created') and getattr(self, 'created') is not None:
_dict['created'] = datetime_to_string(getattr(self, 'created'))
if hasattr(self, 'updated') and getattr(self, 'updated') is not None:
_dict['updated'] = datetime_to_string(getattr(self, 'updated'))
if hasattr(self, 'examples') and self.examples is not None:
_dict['examples'] = [x.to_dict() for x in self.examples]
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this Intent object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'Intent') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'Intent') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]class IntentCollection():
"""
IntentCollection.
:attr List[Intent] intents: An array of objects describing the intents defined
for the workspace.
:attr Pagination pagination: The pagination data for the returned objects.
"""
def __init__(self, intents: List['Intent'],
pagination: 'Pagination') -> None:
"""
Initialize a IntentCollection object.
:param List[Intent] intents: An array of objects describing the intents
defined for the workspace.
:param Pagination pagination: The pagination data for the returned objects.
"""
self.intents = intents
self.pagination = pagination
[docs] @classmethod
def from_dict(cls, _dict: Dict) -> 'IntentCollection':
"""Initialize a IntentCollection object from a json dictionary."""
args = {}
if 'intents' in _dict:
args['intents'] = [
Intent.from_dict(x) for x in _dict.get('intents')
]
else:
raise ValueError(
'Required property \'intents\' not present in IntentCollection JSON'
)
if 'pagination' in _dict:
args['pagination'] = Pagination.from_dict(_dict.get('pagination'))
else:
raise ValueError(
'Required property \'pagination\' not present in IntentCollection JSON'
)
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a IntentCollection object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'intents') and self.intents is not None:
_dict['intents'] = [x.to_dict() for x in self.intents]
if hasattr(self, 'pagination') and self.pagination is not None:
_dict['pagination'] = self.pagination.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this IntentCollection object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'IntentCollection') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'IntentCollection') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]class Log():
"""
Log.
:attr MessageRequest request: A request sent to the workspace, including the
user input and context.
:attr MessageResponse response: The response sent by the workspace, including
the output text, detected intents and entities, and context.
:attr str log_id: A unique identifier for the logged event.
:attr str request_timestamp: The timestamp for receipt of the message.
:attr str response_timestamp: The timestamp for the system response to the
message.
:attr str workspace_id: The unique identifier of the workspace where the request
was made.
:attr str language: The language of the workspace where the message request was
made.
"""
def __init__(self, request: 'MessageRequest', response: 'MessageResponse',
log_id: str, request_timestamp: str, response_timestamp: str,
workspace_id: str, language: str) -> None:
"""
Initialize a Log object.
:param MessageRequest request: A request sent to the workspace, including
the user input and context.
:param MessageResponse response: The response sent by the workspace,
including the output text, detected intents and entities, and context.
:param str log_id: A unique identifier for the logged event.
:param str request_timestamp: The timestamp for receipt of the message.
:param str response_timestamp: The timestamp for the system response to the
message.
:param str workspace_id: The unique identifier of the workspace where the
request was made.
:param str language: The language of the workspace where the message
request was made.
"""
self.request = request
self.response = response
self.log_id = log_id
self.request_timestamp = request_timestamp
self.response_timestamp = response_timestamp
self.workspace_id = workspace_id
self.language = language
[docs] @classmethod
def from_dict(cls, _dict: Dict) -> 'Log':
"""Initialize a Log object from a json dictionary."""
args = {}
if 'request' in _dict:
args['request'] = MessageRequest.from_dict(_dict.get('request'))
else:
raise ValueError(
'Required property \'request\' not present in Log JSON')
if 'response' in _dict:
args['response'] = MessageResponse.from_dict(_dict.get('response'))
else:
raise ValueError(
'Required property \'response\' not present in Log JSON')
if 'log_id' in _dict:
args['log_id'] = _dict.get('log_id')
else:
raise ValueError(
'Required property \'log_id\' not present in Log JSON')
if 'request_timestamp' in _dict:
args['request_timestamp'] = _dict.get('request_timestamp')
else:
raise ValueError(
'Required property \'request_timestamp\' not present in Log JSON'
)
if 'response_timestamp' in _dict:
args['response_timestamp'] = _dict.get('response_timestamp')
else:
raise ValueError(
'Required property \'response_timestamp\' not present in Log JSON'
)
if 'workspace_id' in _dict:
args['workspace_id'] = _dict.get('workspace_id')
else:
raise ValueError(
'Required property \'workspace_id\' not present in Log JSON')
if 'language' in _dict:
args['language'] = _dict.get('language')
else:
raise ValueError(
'Required property \'language\' not present in Log JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a Log object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'request') and self.request is not None:
_dict['request'] = self.request.to_dict()
if hasattr(self, 'response') and self.response is not None:
_dict['response'] = self.response.to_dict()
if hasattr(self, 'log_id') and self.log_id is not None:
_dict['log_id'] = self.log_id
if hasattr(self,
'request_timestamp') and self.request_timestamp is not None:
_dict['request_timestamp'] = self.request_timestamp
if hasattr(
self,
'response_timestamp') and self.response_timestamp is not None:
_dict['response_timestamp'] = self.response_timestamp
if hasattr(self, 'workspace_id') and self.workspace_id is not None:
_dict['workspace_id'] = self.workspace_id
if hasattr(self, 'language') and self.language is not None:
_dict['language'] = self.language
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this Log object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'Log') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'Log') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]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
[docs] @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)
[docs] 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
[docs]class LogMessage():
"""
Log message details.
:attr str level: The severity of the log message.
:attr str msg: The text of the log message.
:attr str code: A code that indicates the category to which the error message
belongs.
:attr LogMessageSource source: (optional) An object that identifies the dialog
element that generated the error message.
"""
def __init__(self,
level: str,
msg: str,
code: str,
*,
source: 'LogMessageSource' = None) -> None:
"""
Initialize a LogMessage object.
:param str level: The severity of the log message.
:param str msg: The text of the log message.
:param str code: A code that indicates the category to which the error
message belongs.
:param LogMessageSource source: (optional) An object that identifies the
dialog element that generated the error message.
"""
self.level = level
self.msg = msg
self.code = code
self.source = source
[docs] @classmethod
def from_dict(cls, _dict: Dict) -> 'LogMessage':
"""Initialize a LogMessage object from a json dictionary."""
args = {}
if 'level' in _dict:
args['level'] = _dict.get('level')
else:
raise ValueError(
'Required property \'level\' not present in LogMessage JSON')
if 'msg' in _dict:
args['msg'] = _dict.get('msg')
else:
raise ValueError(
'Required property \'msg\' not present in LogMessage JSON')
if 'code' in _dict:
args['code'] = _dict.get('code')
else:
raise ValueError(
'Required property \'code\' not present in LogMessage JSON')
if 'source' in _dict:
args['source'] = LogMessageSource.from_dict(_dict.get('source'))
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a LogMessage object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'level') and self.level is not None:
_dict['level'] = self.level
if hasattr(self, 'msg') and self.msg is not None:
_dict['msg'] = self.msg
if hasattr(self, 'code') and self.code is not None:
_dict['code'] = self.code
if hasattr(self, 'source') and self.source is not None:
_dict['source'] = self.source.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this LogMessage object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'LogMessage') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'LogMessage') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs] class LevelEnum(str, Enum):
"""
The severity of the log message.
"""
INFO = 'info'
ERROR = 'error'
WARN = 'warn'
[docs]class LogMessageSource():
"""
An object that identifies the dialog element that generated the error message.
:attr str type: (optional) A string that indicates the type of dialog element
that generated the error message.
:attr str dialog_node: (optional) The unique identifier of the dialog node that
generated the error message.
"""
def __init__(self, *, type: str = None, dialog_node: str = None) -> None:
"""
Initialize a LogMessageSource object.
:param str type: (optional) A string that indicates the type of dialog
element that generated the error message.
:param str dialog_node: (optional) The unique identifier of the dialog node
that generated the error message.
"""
self.type = type
self.dialog_node = dialog_node
[docs] @classmethod
def from_dict(cls, _dict: Dict) -> 'LogMessageSource':
"""Initialize a LogMessageSource object from a json dictionary."""
args = {}
if 'type' in _dict:
args['type'] = _dict.get('type')
if 'dialog_node' in _dict:
args['dialog_node'] = _dict.get('dialog_node')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a LogMessageSource object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'type') and self.type is not None:
_dict['type'] = self.type
if hasattr(self, 'dialog_node') and self.dialog_node is not None:
_dict['dialog_node'] = self.dialog_node
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this LogMessageSource object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'LogMessageSource') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'LogMessageSource') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs] class TypeEnum(str, Enum):
"""
A string that indicates the type of dialog element that generated the error
message.
"""
DIALOG_NODE = 'dialog_node'
[docs]class Mention():
"""
A mention of a contextual entity.
:attr str entity: The name of the entity.
:attr List[int] location: An array of zero-based character offsets that indicate
where the entity mentions begin and end in the input text.
"""
def __init__(self, entity: str, location: List[int]) -> None:
"""
Initialize a Mention object.
:param str entity: The name of the entity.
:param List[int] location: An array of zero-based character offsets that
indicate where the entity mentions begin and end in the input text.
"""
self.entity = entity
self.location = location
[docs] @classmethod
def from_dict(cls, _dict: Dict) -> 'Mention':
"""Initialize a Mention object from a json dictionary."""
args = {}
if 'entity' in _dict:
args['entity'] = _dict.get('entity')
else:
raise ValueError(
'Required property \'entity\' not present in Mention JSON')
if 'location' in _dict:
args['location'] = _dict.get('location')
else:
raise ValueError(
'Required property \'location\' not present in Mention JSON')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a Mention object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'entity') and self.entity is not None:
_dict['entity'] = self.entity
if hasattr(self, 'location') and self.location is not None:
_dict['location'] = self.location
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this Mention object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'Mention') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'Mention') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]class MessageContextMetadata():
"""
Metadata related to the message.
:attr str deployment: (optional) A label identifying the deployment environment,
used for filtering log data. This string cannot contain carriage return,
newline, or tab characters.
:attr str user_id: (optional) A string value that identifies the user who is
interacting with the workspace. The client must provide a unique identifier for
each individual end user who accesses the application. For user-based plans,
this user ID is used to identify unique users for billing purposes. This string
cannot contain carriage return, newline, or tab characters. If no value is
specified in the input, **user_id** is automatically set to the value of
**context.conversation_id**.
**Note:** This property is the same as the **user_id** property at the root of
the message body. If **user_id** is specified in both locations in a message
request, the value specified at the root is used.
"""
def __init__(self, *, deployment: str = None, user_id: str = None) -> None:
"""
Initialize a MessageContextMetadata object.
:param str deployment: (optional) A label identifying the deployment
environment, used for filtering log data. This string cannot contain
carriage return, newline, or tab characters.
:param str user_id: (optional) A string value that identifies the user who
is interacting with the workspace. The client must provide a unique
identifier for each individual end user who accesses the application. For
user-based plans, this user ID is used to identify unique users for billing
purposes. This string cannot contain carriage return, newline, or tab
characters. If no value is specified in the input, **user_id** is
automatically set to the value of **context.conversation_id**.
**Note:** This property is the same as the **user_id** property at the root
of the message body. If **user_id** is specified in both locations in a
message request, the value specified at the root is used.
"""
self.deployment = deployment
self.user_id = user_id
[docs] @classmethod
def from_dict(cls, _dict: Dict) -> 'MessageContextMetadata':
"""Initialize a MessageContextMetadata object from a json dictionary."""
args = {}
if 'deployment' in _dict:
args['deployment'] = _dict.get('deployment')
if 'user_id' in _dict:
args['user_id'] = _dict.get('user_id')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a MessageContextMetadata object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'deployment') and self.deployment is not None:
_dict['deployment'] = self.deployment
if hasattr(self, 'user_id') and self.user_id is not None:
_dict['user_id'] = self.user_id
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this MessageContextMetadata object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'MessageContextMetadata') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'MessageContextMetadata') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]class MessageRequest():
"""
A request sent to the workspace, including the user input and context.
:attr MessageInput input: (optional) An input object that includes the input
text.
:attr List[RuntimeIntent] intents: (optional) Intents to use when evaluating the
user input. Include intents from the previous response to continue using those
intents rather than trying to recognize intents in the new input.
:attr List[RuntimeEntity] entities: (optional) Entities to use when evaluating
the message. Include entities from the previous response to continue using those
entities rather than detecting entities in the new input.
:attr bool alternate_intents: (optional) Whether to return more than one intent.
A value of `true` indicates that all matching intents are returned.
:attr Context context: (optional) State information for the conversation. To
maintain state, include the context from the previous response.
:attr OutputData output: (optional) An output object that includes the response
to the user, the dialog nodes that were triggered, and messages from the log.
:attr List[DialogNodeAction] actions: (optional) An array of objects describing
any actions requested by the dialog node.
:attr str user_id: (optional) A string value that identifies the user who is
interacting with the workspace. The client must provide a unique identifier for
each individual end user who accesses the application. For user-based plans,
this user ID is used to identify unique users for billing purposes. This string
cannot contain carriage return, newline, or tab characters. If no value is
specified in the input, **user_id** is automatically set to the value of
**context.conversation_id**.
**Note:** This property is the same as the **user_id** property in the context
metadata. If **user_id** is specified in both locations in a message request,
the value specified at the root is used.
"""
def __init__(self,
*,
input: 'MessageInput' = None,
intents: List['RuntimeIntent'] = None,
entities: List['RuntimeEntity'] = None,
alternate_intents: bool = None,
context: 'Context' = None,
output: 'OutputData' = None,
actions: List['DialogNodeAction'] = None,
user_id: str = None) -> None:
"""
Initialize a MessageRequest object.
:param MessageInput input: (optional) An input object that includes the
input text.
:param List[RuntimeIntent] intents: (optional) Intents to use when
evaluating the user input. Include intents from the previous response to
continue using those intents rather than trying to recognize intents in the
new input.
:param List[RuntimeEntity] entities: (optional) Entities to use when
evaluating the message. Include entities from the previous response to
continue using those entities rather than detecting entities in the new
input.
:param bool alternate_intents: (optional) Whether to return more than one
intent. A value of `true` indicates that all matching intents are returned.
:param Context context: (optional) State information for the conversation.
To maintain state, include the context from the previous response.
:param OutputData output: (optional) An output object that includes the
response to the user, the dialog nodes that were triggered, and messages
from the log.
:param str user_id: (optional) A string value that identifies the user who
is interacting with the workspace. The client must provide a unique
identifier for each individual end user who accesses the application. For
user-based plans, this user ID is used to identify unique users for billing
purposes. This string cannot contain carriage return, newline, or tab
characters. If no value is specified in the input, **user_id** is
automatically set to the value of **context.conversation_id**.
**Note:** This property is the same as the **user_id** property in the
context metadata. If **user_id** is specified in both locations in a
message request, the value specified at the root is used.
"""
self.input = input
self.intents = intents
self.entities = entities
self.alternate_intents = alternate_intents
self.context = context
self.output = output
self.actions = actions
self.user_id = user_id
[docs] @classmethod
def from_dict(cls, _dict: Dict) -> 'MessageRequest':
"""Initialize a MessageRequest object from a json dictionary."""
args = {}
if 'input' in _dict:
args['input'] = MessageInput.from_dict(_dict.get('input'))
if 'intents' in _dict:
args['intents'] = [
RuntimeIntent.from_dict(x) for x in _dict.get('intents')
]
if 'entities' in _dict:
args['entities'] = [
RuntimeEntity.from_dict(x) for x in _dict.get('entities')
]
if 'alternate_intents' in _dict:
args['alternate_intents'] = _dict.get('alternate_intents')
if 'context' in _dict:
args['context'] = Context.from_dict(_dict.get('context'))
if 'output' in _dict:
args['output'] = OutputData.from_dict(_dict.get('output'))
if 'actions' in _dict:
args['actions'] = [
DialogNodeAction.from_dict(x) for x in _dict.get('actions')
]
if 'user_id' in _dict:
args['user_id'] = _dict.get('user_id')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a MessageRequest object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'input') and self.input is not None:
_dict['input'] = self.input.to_dict()
if hasattr(self, 'intents') and self.intents is not None:
_dict['intents'] = [x.to_dict() for x in self.intents]
if hasattr(self, 'entities') and self.entities is not None:
_dict['entities'] = [x.to_dict() for x in self.entities]
if hasattr(self,
'alternate_intents') and self.alternate_intents is not None:
_dict['alternate_intents'] = self.alternate_intents
if hasattr(self, 'context') and self.context is not None:
_dict['context'] = self.context.to_dict()
if hasattr(self, 'output') and self.output is not None:
_dict['output'] = self.output.to_dict()
if hasattr(self, 'actions') and getattr(self, 'actions') is not None:
_dict['actions'] = [x.to_dict() for x in getattr(self, 'actions')]
if hasattr(self, 'user_id') and self.user_id is not None:
_dict['user_id'] = self.user_id
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this MessageRequest object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'MessageRequest') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'MessageRequest') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]class MessageResponse():
"""
The response sent by the workspace, including the output text, detected intents and
entities, and context.
:attr MessageInput input: An input object that includes the input text.
:attr List[RuntimeIntent] intents: An array of intents recognized in the user
input, sorted in descending order of confidence.
:attr List[RuntimeEntity] entities: An array of entities identified in the user
input.
:attr bool alternate_intents: (optional) Whether to return more than one intent.
A value of `true` indicates that all matching intents are returned.
:attr Context context: State information for the conversation. To maintain
state, include the context from the previous response.
:attr OutputData output: An output object that includes the response to the
user, the dialog nodes that were triggered, and messages from the log.
:attr List[DialogNodeAction] actions: (optional) An array of objects describing
any actions requested by the dialog node.
:attr str user_id: A string value that identifies the user who is interacting
with the workspace. The client must provide a unique identifier for each
individual end user who accesses the application. For user-based plans, this
user ID is used to identify unique users for billing purposes. This string
cannot contain carriage return, newline, or tab characters. If no value is
specified in the input, **user_id** is automatically set to the value of
**context.conversation_id**.
**Note:** This property is the same as the **user_id** property in the context
metadata. If **user_id** is specified in both locations in a message request,
the value specified at the root is used.
"""
def __init__(self,
input: 'MessageInput',
intents: List['RuntimeIntent'],
entities: List['RuntimeEntity'],
context: 'Context',
output: 'OutputData',
user_id: str,
*,
alternate_intents: bool = None,
actions: List['DialogNodeAction'] = None) -> None:
"""
Initialize a MessageResponse object.
:param MessageInput input: An input object that includes the input text.
:param List[RuntimeIntent] intents: An array of intents recognized in the
user input, sorted in descending order of confidence.
:param List[RuntimeEntity] entities: An array of entities identified in the
user input.
:param Context context: State information for the conversation. To maintain
state, include the context from the previous response.
:param OutputData output: An output object that includes the response to
the user, the dialog nodes that were triggered, and messages from the log.
:param str user_id: A string value that identifies the user who is
interacting with the workspace. The client must provide a unique identifier
for each individual end user who accesses the application. For user-based
plans, this user ID is used to identify unique users for billing purposes.
This string cannot contain carriage return, newline, or tab characters. If
no value is specified in the input, **user_id** is automatically set to the
value of **context.conversation_id**.
**Note:** This property is the same as the **user_id** property in the
context metadata. If **user_id** is specified in both locations in a
message request, the value specified at the root is used.
:param bool alternate_intents: (optional) Whether to return more than one
intent. A value of `true` indicates that all matching intents are returned.
"""
self.input = input
self.intents = intents
self.entities = entities
self.alternate_intents = alternate_intents
self.context = context
self.output = output
self.actions = actions
self.user_id = user_id
[docs] @classmethod
def from_dict(cls, _dict: Dict) -> 'MessageResponse':
"""Initialize a MessageResponse object from a json dictionary."""
args = {}
if 'input' in _dict:
args['input'] = MessageInput.from_dict(_dict.get('input'))
else:
raise ValueError(
'Required property \'input\' not present in MessageResponse JSON'
)
if 'intents' in _dict:
args['intents'] = [
RuntimeIntent.from_dict(x) for x in _dict.get('intents')
]
else:
raise ValueError(
'Required property \'intents\' not present in MessageResponse JSON'
)
if 'entities' in _dict:
args['entities'] = [
RuntimeEntity.from_dict(x) for x in _dict.get('entities')
]
else:
raise ValueError(
'Required property \'entities\' not present in MessageResponse JSON'
)
if 'alternate_intents' in _dict:
args['alternate_intents'] = _dict.get('alternate_intents')
if 'context' in _dict:
args['context'] = Context.from_dict(_dict.get('context'))
else:
raise ValueError(
'Required property \'context\' not present in MessageResponse JSON'
)
if 'output' in _dict:
args['output'] = OutputData.from_dict(_dict.get('output'))
else:
raise ValueError(
'Required property \'output\' not present in MessageResponse JSON'
)
if 'actions' in _dict:
args['actions'] = [
DialogNodeAction.from_dict(x) for x in _dict.get('actions')
]
if 'user_id' in _dict:
args['user_id'] = _dict.get('user_id')
else:
raise ValueError(
'Required property \'user_id\' not present in MessageResponse JSON'
)
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a MessageResponse object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'input') and self.input is not None:
_dict['input'] = self.input.to_dict()
if hasattr(self, 'intents') and self.intents is not None:
_dict['intents'] = [x.to_dict() for x in self.intents]
if hasattr(self, 'entities') and self.entities is not None:
_dict['entities'] = [x.to_dict() for x in self.entities]
if hasattr(self,
'alternate_intents') and self.alternate_intents is not None:
_dict['alternate_intents'] = self.alternate_intents
if hasattr(self, 'context') and self.context is not None:
_dict['context'] = self.context.to_dict()
if hasattr(self, 'output') and self.output is not None:
_dict['output'] = self.output.to_dict()
if hasattr(self, 'actions') and getattr(self, 'actions') is not None:
_dict['actions'] = [x.to_dict() for x in getattr(self, 'actions')]
if hasattr(self, 'user_id') and self.user_id is not None:
_dict['user_id'] = self.user_id
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this MessageResponse object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'MessageResponse') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'MessageResponse') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]class OutputData():
"""
An output object that includes the response to the user, the dialog nodes that were
triggered, and messages from the log.
:attr List[str] nodes_visited: (optional) An array of the nodes that were
triggered to create the response, in the order in which they were visited. This
information is useful for debugging and for tracing the path taken through the
node tree.
:attr List[DialogNodeVisitedDetails] nodes_visited_details: (optional) An array
of objects containing detailed diagnostic information about the nodes that were
triggered during processing of the input message. Included only if
**nodes_visited_details** is set to `true` in the message request.
:attr List[LogMessage] log_messages: An array of up to 50 messages logged with
the request.
:attr List[str] text: An array of responses to the user.
:attr List[RuntimeResponseGeneric] generic: (optional) Output intended for any
channel. It is the responsibility of the client application to implement the
supported response types.
"""
# The set of defined properties for the class
_properties = frozenset([
'nodes_visited', 'nodes_visited_details', 'log_messages', 'text',
'generic'
])
def __init__(self,
log_messages: List['LogMessage'],
text: List[str],
*,
nodes_visited: List[str] = None,
nodes_visited_details: List['DialogNodeVisitedDetails'] = None,
generic: List['RuntimeResponseGeneric'] = None,
**kwargs) -> None:
"""
Initialize a OutputData object.
:param List[LogMessage] log_messages: An array of up to 50 messages logged
with the request.
:param List[str] text: An array of responses to the user.
:param List[str] nodes_visited: (optional) An array of the nodes that were
triggered to create the response, in the order in which they were visited.
This information is useful for debugging and for tracing the path taken
through the node tree.
:param List[DialogNodeVisitedDetails] nodes_visited_details: (optional) An
array of objects containing detailed diagnostic information about the nodes
that were triggered during processing of the input message. Included only
if **nodes_visited_details** is set to `true` in the message request.
:param List[RuntimeResponseGeneric] generic: (optional) Output intended for
any channel. It is the responsibility of the client application to
implement the supported response types.
:param **kwargs: (optional) Any additional properties.
"""
self.nodes_visited = nodes_visited
self.nodes_visited_details = nodes_visited_details
self.log_messages = log_messages
self.text = text
self.generic = generic
for _key, _value in kwargs.items():
setattr(self, _key, _value)
[docs] @classmethod
def from_dict(cls, _dict: Dict) -> 'OutputData':
"""Initialize a OutputData object from a json dictionary."""
args = {}
if 'nodes_visited' in _dict:
args['nodes_visited'] = _dict.get('nodes_visited')
if 'nodes_visited_details' in _dict:
args['nodes_visited_details'] = [
DialogNodeVisitedDetails.from_dict(x)
for x in _dict.get('nodes_visited_details')
]
if 'log_messages' in _dict:
args['log_messages'] = [
LogMessage.from_dict(x) for x in _dict.get('log_messages')
]
else:
raise ValueError(
'Required property \'log_messages\' not present in OutputData JSON'
)
if 'text' in _dict:
args['text'] = _dict.get('text')
else:
raise ValueError(
'Required property \'text\' not present in OutputData JSON')
if 'generic' in _dict:
args['generic'] = [
RuntimeResponseGeneric.from_dict(x)
for x in _dict.get('generic')
]
args.update(
{k: v for (k, v) in _dict.items() if k not in cls._properties})
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a OutputData object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'nodes_visited') and self.nodes_visited is not None:
_dict['nodes_visited'] = self.nodes_visited
if hasattr(self, 'nodes_visited_details'
) and self.nodes_visited_details is not None:
_dict['nodes_visited_details'] = [
x.to_dict() for x in self.nodes_visited_details
]
if hasattr(self, 'log_messages') and self.log_messages is not None:
_dict['log_messages'] = [x.to_dict() for x in self.log_messages]
if hasattr(self, 'text') and self.text is not None:
_dict['text'] = self.text
if hasattr(self, 'generic') and self.generic is not None:
_dict['generic'] = [x.to_dict() for x in self.generic]
for _key in [
k for k in vars(self).keys() if k not in OutputData._properties
]:
if getattr(self, _key, None) is not None:
_dict[_key] = getattr(self, _key)
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this OutputData object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'OutputData') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'OutputData') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]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
[docs] @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)
[docs] 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
[docs] class ChannelEnum(str, Enum):
"""
A channel for which the response is intended.
"""
CHAT = 'chat'
FACEBOOK = 'facebook'
INTERCOM = 'intercom'
SLACK = 'slack'
TEXT_MESSAGING = 'text_messaging'
VOICE_TELEPHONY = 'voice_telephony'
WHATSAPP = 'whatsapp'
[docs]class RuntimeEntity():
"""
A term from the request that was identified as an entity.
:attr str entity: An entity detected in the input.
:attr List[int] location: An array of zero-based character offsets that indicate
where the detected entity values begin and end in the input text.
:attr str value: The entity value that was recognized in the user input.
:attr float confidence: (optional) A decimal percentage that represents Watson's
confidence in the recognized entity.
:attr 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.
:attr RuntimeEntityInterpretation interpretation: (optional) An object
containing detailed information about the entity recognized in the user input.
For more information about how system entities are interpreted, see the
[documentation](https://cloud.ibm.com/docs/assistant?topic=assistant-system-entities).
:attr List[RuntimeEntityAlternative] alternatives: (optional) An array of
possible alternative values that the user might have intended instead of the
value returned in the **value** property. This property is returned only for
`@sys-time` and `@sys-date` entities when the user's input is ambiguous.
This property is included only if the new system entities are enabled for the
workspace.
:attr RuntimeEntityRole role: (optional) An object describing the role played by
a system entity that is specifies the beginning or end of a range recognized in
the user input. This property is included only if the new system entities are
enabled for the workspace.
"""
def __init__(self,
entity: str,
location: List[int],
value: str,
*,
confidence: float = None,
metadata: dict = None,
groups: List['CaptureGroup'] = None,
interpretation: 'RuntimeEntityInterpretation' = None,
alternatives: List['RuntimeEntityAlternative'] = None,
role: 'RuntimeEntityRole' = None) -> None:
"""
Initialize a RuntimeEntity object.
:param str entity: An entity detected in the input.
:param 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 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.
: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.
:param RuntimeEntityInterpretation interpretation: (optional) An object
containing detailed information about the entity recognized in the user
input.
For more information about how system entities are interpreted, see the
[documentation](https://cloud.ibm.com/docs/assistant?topic=assistant-system-entities).
:param List[RuntimeEntityAlternative] alternatives: (optional) An array of
possible alternative values that the user might have intended instead of
the value returned in the **value** property. This property is returned
only for `@sys-time` and `@sys-date` entities when the user's input is
ambiguous.
This property is included only if the new system entities are enabled for
the workspace.
:param RuntimeEntityRole role: (optional) An object describing the role
played by a system entity that is specifies the beginning or end of a range
recognized in the user input. This property is included only if the new
system entities are enabled for the workspace.
"""
self.entity = entity
self.location = location
self.value = value
self.confidence = confidence
self.metadata = metadata
self.groups = groups
self.interpretation = interpretation
self.alternatives = alternatives
self.role = role
[docs] @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')
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')
]
if 'interpretation' in _dict:
args['interpretation'] = RuntimeEntityInterpretation.from_dict(
_dict.get('interpretation'))
if 'alternatives' in _dict:
args['alternatives'] = [
RuntimeEntityAlternative.from_dict(x)
for x in _dict.get('alternatives')
]
if 'role' in _dict:
args['role'] = RuntimeEntityRole.from_dict(_dict.get('role'))
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a RuntimeEntity object from a json dictionary."""
return cls.from_dict(_dict)
[docs] 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, '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]
if hasattr(self, 'interpretation') and self.interpretation is not None:
_dict['interpretation'] = self.interpretation.to_dict()
if hasattr(self, 'alternatives') and self.alternatives is not None:
_dict['alternatives'] = [x.to_dict() for x in self.alternatives]
if hasattr(self, 'role') and self.role is not None:
_dict['role'] = self.role.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this RuntimeEntity object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'RuntimeEntity') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'RuntimeEntity') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]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
[docs] @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)
[docs] 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
[docs]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
[docs] @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)
[docs] 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
[docs] 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'
[docs]class RuntimeEntityRole():
"""
An object describing the role played by a system entity that is specifies the
beginning or end of a range recognized in the user input. This property is included
only if the new system entities are enabled for the workspace.
:attr str type: (optional) The relationship of the entity to the range.
"""
def __init__(self, *, type: str = None) -> None:
"""
Initialize a RuntimeEntityRole object.
:param str type: (optional) The relationship of the entity to the range.
"""
self.type = type
[docs] @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)
[docs] 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
[docs] 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'
[docs]class RuntimeIntent():
"""
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: str, confidence: float) -> None:
"""
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
[docs] @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')
else:
raise ValueError(
'Required property \'confidence\' not present in RuntimeIntent JSON'
)
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a RuntimeIntent object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'intent') and self.intent is not None:
_dict['intent'] = self.intent
if hasattr(self, 'confidence') and self.confidence is not None:
_dict['confidence'] = self.confidence
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this RuntimeIntent object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'RuntimeIntent') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'RuntimeIntent') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]class RuntimeResponseGeneric():
"""
RuntimeResponseGeneric.
"""
def __init__(self) -> None:
"""
Initialize a RuntimeResponseGeneric object.
"""
msg = "Cannot instantiate base class. Instead, instantiate one of the defined subclasses: {0}".format(
", ".join([
'RuntimeResponseGenericRuntimeResponseTypeText',
'RuntimeResponseGenericRuntimeResponseTypePause',
'RuntimeResponseGenericRuntimeResponseTypeImage',
'RuntimeResponseGenericRuntimeResponseTypeOption',
'RuntimeResponseGenericRuntimeResponseTypeConnectToAgent',
'RuntimeResponseGenericRuntimeResponseTypeSuggestion',
'RuntimeResponseGenericRuntimeResponseTypeChannelTransfer',
'RuntimeResponseGenericRuntimeResponseTypeUserDefined'
]))
raise Exception(msg)
[docs] @classmethod
def from_dict(cls, _dict: Dict) -> 'RuntimeResponseGeneric':
"""Initialize a RuntimeResponseGeneric object from a json dictionary."""
disc_class = cls._get_class_by_discriminator(_dict)
if disc_class != cls:
return disc_class.from_dict(_dict)
msg = (
"Cannot convert dictionary into an instance of base class 'RuntimeResponseGeneric'. "
+ "The discriminator value should map to a valid subclass: {1}"
).format(", ".join([
'RuntimeResponseGenericRuntimeResponseTypeText',
'RuntimeResponseGenericRuntimeResponseTypePause',
'RuntimeResponseGenericRuntimeResponseTypeImage',
'RuntimeResponseGenericRuntimeResponseTypeOption',
'RuntimeResponseGenericRuntimeResponseTypeConnectToAgent',
'RuntimeResponseGenericRuntimeResponseTypeSuggestion',
'RuntimeResponseGenericRuntimeResponseTypeChannelTransfer',
'RuntimeResponseGenericRuntimeResponseTypeUserDefined'
]))
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[
'channel_transfer'] = 'RuntimeResponseGenericRuntimeResponseTypeChannelTransfer'
mapping[
'connect_to_agent'] = 'RuntimeResponseGenericRuntimeResponseTypeConnectToAgent'
mapping['image'] = 'RuntimeResponseGenericRuntimeResponseTypeImage'
mapping['option'] = 'RuntimeResponseGenericRuntimeResponseTypeOption'
mapping[
'suggestion'] = 'RuntimeResponseGenericRuntimeResponseTypeSuggestion'
mapping['pause'] = 'RuntimeResponseGenericRuntimeResponseTypePause'
mapping['text'] = 'RuntimeResponseGenericRuntimeResponseTypeText'
mapping[
'user_defined'] = 'RuntimeResponseGenericRuntimeResponseTypeUserDefined'
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)
[docs]class Synonym():
"""
Synonym.
:attr str synonym: The text of the synonym. This string must conform to the
following restrictions:
- It cannot contain carriage return, newline, or tab characters.
- It cannot consist of only whitespace characters.
:attr datetime created: (optional) The timestamp for creation of the object.
:attr datetime updated: (optional) The timestamp for the most recent update to
the object.
"""
def __init__(self,
synonym: str,
*,
created: datetime = None,
updated: datetime = None) -> None:
"""
Initialize a Synonym object.
:param str synonym: The text of the synonym. This string must conform to
the following restrictions:
- It cannot contain carriage return, newline, or tab characters.
- It cannot consist of only whitespace characters.
"""
self.synonym = synonym
self.created = created
self.updated = updated
[docs] @classmethod
def from_dict(cls, _dict: Dict) -> 'Synonym':
"""Initialize a Synonym object from a json dictionary."""
args = {}
if 'synonym' in _dict:
args['synonym'] = _dict.get('synonym')
else:
raise ValueError(
'Required property \'synonym\' not present in Synonym JSON')
if 'created' in _dict:
args['created'] = string_to_datetime(_dict.get('created'))
if 'updated' in _dict:
args['updated'] = string_to_datetime(_dict.get('updated'))
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a Synonym object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'synonym') and self.synonym is not None:
_dict['synonym'] = self.synonym
if hasattr(self, 'created') and getattr(self, 'created') is not None:
_dict['created'] = datetime_to_string(getattr(self, 'created'))
if hasattr(self, 'updated') and getattr(self, 'updated') is not None:
_dict['updated'] = datetime_to_string(getattr(self, 'updated'))
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this Synonym object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'Synonym') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'Synonym') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]class SynonymCollection():
"""
SynonymCollection.
:attr List[Synonym] synonyms: An array of synonyms.
:attr Pagination pagination: The pagination data for the returned objects.
"""
def __init__(self, synonyms: List['Synonym'],
pagination: 'Pagination') -> None:
"""
Initialize a SynonymCollection object.
:param List[Synonym] synonyms: An array of synonyms.
:param Pagination pagination: The pagination data for the returned objects.
"""
self.synonyms = synonyms
self.pagination = pagination
[docs] @classmethod
def from_dict(cls, _dict: Dict) -> 'SynonymCollection':
"""Initialize a SynonymCollection object from a json dictionary."""
args = {}
if 'synonyms' in _dict:
args['synonyms'] = [
Synonym.from_dict(x) for x in _dict.get('synonyms')
]
else:
raise ValueError(
'Required property \'synonyms\' not present in SynonymCollection JSON'
)
if 'pagination' in _dict:
args['pagination'] = Pagination.from_dict(_dict.get('pagination'))
else:
raise ValueError(
'Required property \'pagination\' not present in SynonymCollection JSON'
)
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a SynonymCollection object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'synonyms') and self.synonyms is not None:
_dict['synonyms'] = [x.to_dict() for x in self.synonyms]
if hasattr(self, 'pagination') and self.pagination is not None:
_dict['pagination'] = self.pagination.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this SynonymCollection object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'SynonymCollection') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'SynonymCollection') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]class Value():
"""
Value.
:attr str value: The text of the entity value. This string must conform to the
following restrictions:
- It cannot contain carriage return, newline, or tab characters.
- It cannot consist of only whitespace characters.
:attr dict metadata: (optional) Any metadata related to the entity value.
:attr str type: Specifies the type of entity value.
:attr List[str] synonyms: (optional) An array of synonyms for the entity value.
A value can specify either synonyms or patterns (depending on the value type),
but not both. A synonym must conform to the following resrictions:
- It cannot contain carriage return, newline, or tab characters.
- It cannot consist of only whitespace characters.
:attr List[str] patterns: (optional) An array of patterns for the entity value.
A value can specify either synonyms or patterns (depending on the value type),
but not both. A pattern is a regular expression; for more information about how
to specify a pattern, see the
[documentation](https://cloud.ibm.com/docs/assistant?topic=assistant-entities#entities-create-dictionary-based).
:attr datetime created: (optional) The timestamp for creation of the object.
:attr datetime updated: (optional) The timestamp for the most recent update to
the object.
"""
def __init__(self,
value: str,
type: str,
*,
metadata: dict = None,
synonyms: List[str] = None,
patterns: List[str] = None,
created: datetime = None,
updated: datetime = None) -> None:
"""
Initialize a Value object.
:param str value: The text of the entity value. This string must conform to
the following restrictions:
- It cannot contain carriage return, newline, or tab characters.
- It cannot consist of only whitespace characters.
:param str type: Specifies the type of entity value.
:param dict metadata: (optional) Any metadata related to the entity value.
:param List[str] synonyms: (optional) An array of synonyms for the entity
value. A value can specify either synonyms or patterns (depending on the
value type), but not both. A synonym must conform to the following
resrictions:
- It cannot contain carriage return, newline, or tab characters.
- It cannot consist of only whitespace characters.
:param List[str] patterns: (optional) An array of patterns for the entity
value. A value can specify either synonyms or patterns (depending on the
value type), but not both. A pattern is a regular expression; for more
information about how to specify a pattern, see the
[documentation](https://cloud.ibm.com/docs/assistant?topic=assistant-entities#entities-create-dictionary-based).
"""
self.value = value
self.metadata = metadata
self.type = type
self.synonyms = synonyms
self.patterns = patterns
self.created = created
self.updated = updated
[docs] @classmethod
def from_dict(cls, _dict: Dict) -> 'Value':
"""Initialize a Value object from a json dictionary."""
args = {}
if 'value' in _dict:
args['value'] = _dict.get('value')
else:
raise ValueError(
'Required property \'value\' not present in Value JSON')
if 'metadata' in _dict:
args['metadata'] = _dict.get('metadata')
if 'type' in _dict:
args['type'] = _dict.get('type')
else:
raise ValueError(
'Required property \'type\' not present in Value JSON')
if 'synonyms' in _dict:
args['synonyms'] = _dict.get('synonyms')
if 'patterns' in _dict:
args['patterns'] = _dict.get('patterns')
if 'created' in _dict:
args['created'] = string_to_datetime(_dict.get('created'))
if 'updated' in _dict:
args['updated'] = string_to_datetime(_dict.get('updated'))
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a Value object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'value') and self.value is not None:
_dict['value'] = self.value
if hasattr(self, 'metadata') and self.metadata is not None:
_dict['metadata'] = self.metadata
if hasattr(self, 'type') and self.type is not None:
_dict['type'] = self.type
if hasattr(self, 'synonyms') and self.synonyms is not None:
_dict['synonyms'] = self.synonyms
if hasattr(self, 'patterns') and self.patterns is not None:
_dict['patterns'] = self.patterns
if hasattr(self, 'created') and getattr(self, 'created') is not None:
_dict['created'] = datetime_to_string(getattr(self, 'created'))
if hasattr(self, 'updated') and getattr(self, 'updated') is not None:
_dict['updated'] = datetime_to_string(getattr(self, 'updated'))
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this Value object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'Value') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'Value') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs] class TypeEnum(str, Enum):
"""
Specifies the type of entity value.
"""
SYNONYMS = 'synonyms'
PATTERNS = 'patterns'
[docs]class ValueCollection():
"""
ValueCollection.
:attr List[Value] values: An array of entity values.
:attr Pagination pagination: The pagination data for the returned objects.
"""
def __init__(self, values: List['Value'], pagination: 'Pagination') -> None:
"""
Initialize a ValueCollection object.
:param List[Value] values: An array of entity values.
:param Pagination pagination: The pagination data for the returned objects.
"""
self.values = values
self.pagination = pagination
[docs] @classmethod
def from_dict(cls, _dict: Dict) -> 'ValueCollection':
"""Initialize a ValueCollection object from a json dictionary."""
args = {}
if 'values' in _dict:
args['values'] = [Value.from_dict(x) for x in _dict.get('values')]
else:
raise ValueError(
'Required property \'values\' not present in ValueCollection JSON'
)
if 'pagination' in _dict:
args['pagination'] = Pagination.from_dict(_dict.get('pagination'))
else:
raise ValueError(
'Required property \'pagination\' not present in ValueCollection JSON'
)
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a ValueCollection object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'values') and self.values is not None:
_dict['values'] = [x.to_dict() for x in self.values]
if hasattr(self, 'pagination') and self.pagination is not None:
_dict['pagination'] = self.pagination.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this ValueCollection object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'ValueCollection') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'ValueCollection') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]class Webhook():
"""
A webhook that can be used by dialog nodes to make programmatic calls to an external
function.
**Note:** Currently, only a single webhook named `main_webhook` is supported.
:attr str url: The URL for the external service or application to which you want
to send HTTP POST requests.
:attr str name: The name of the webhook. Currently, `main_webhook` is the only
supported value.
:attr List[WebhookHeader] headers_: (optional) An optional array of HTTP headers
to pass with the HTTP request.
"""
def __init__(self,
url: str,
name: str,
*,
headers_: List['WebhookHeader'] = None) -> None:
"""
Initialize a Webhook object.
:param str url: The URL for the external service or application to which
you want to send HTTP POST requests.
:param str name: The name of the webhook. Currently, `main_webhook` is the
only supported value.
:param List[WebhookHeader] headers_: (optional) An optional array of HTTP
headers to pass with the HTTP request.
"""
self.url = url
self.name = name
self.headers_ = headers_
[docs] @classmethod
def from_dict(cls, _dict: Dict) -> 'Webhook':
"""Initialize a Webhook object from a json dictionary."""
args = {}
if 'url' in _dict:
args['url'] = _dict.get('url')
else:
raise ValueError(
'Required property \'url\' not present in Webhook JSON')
if 'name' in _dict:
args['name'] = _dict.get('name')
else:
raise ValueError(
'Required property \'name\' not present in Webhook JSON')
if 'headers' in _dict:
args['headers_'] = [
WebhookHeader.from_dict(x) for x in _dict.get('headers')
]
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a Webhook object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'url') and self.url is not None:
_dict['url'] = self.url
if hasattr(self, 'name') and self.name is not None:
_dict['name'] = self.name
if hasattr(self, 'headers_') and self.headers_ is not None:
_dict['headers'] = [x.to_dict() for x in self.headers_]
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this Webhook object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'Webhook') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'Webhook') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]class Workspace():
"""
Workspace.
:attr str name: The name of the workspace. This string cannot contain carriage
return, newline, or tab characters.
:attr str description: (optional) The description of the workspace. This string
cannot contain carriage return, newline, or tab characters.
:attr str language: The language of the workspace.
:attr str workspace_id: The workspace ID of the workspace.
:attr List[DialogNode] dialog_nodes: (optional) An array of objects describing
the dialog nodes in the workspace.
:attr List[Counterexample] counterexamples: (optional) An array of objects
defining input examples that have been marked as irrelevant input.
:attr datetime created: (optional) The timestamp for creation of the object.
:attr datetime updated: (optional) The timestamp for the most recent update to
the object.
:attr dict metadata: (optional) Any metadata related to the workspace.
:attr bool learning_opt_out: Whether training data from the workspace (including
artifacts such as intents and entities) can be used by IBM for general service
improvements. `true` indicates that workspace training data is not to be used.
:attr WorkspaceSystemSettings system_settings: (optional) Global settings for
the workspace.
:attr str status: (optional) The current status of the workspace.
:attr List[Webhook] webhooks: (optional)
:attr List[Intent] intents: (optional) An array of intents.
:attr List[Entity] entities: (optional) An array of objects describing the
entities for the workspace.
"""
def __init__(self,
name: str,
language: str,
workspace_id: str,
learning_opt_out: bool,
*,
description: str = None,
dialog_nodes: List['DialogNode'] = None,
counterexamples: List['Counterexample'] = None,
created: datetime = None,
updated: datetime = None,
metadata: dict = None,
system_settings: 'WorkspaceSystemSettings' = None,
status: str = None,
webhooks: List['Webhook'] = None,
intents: List['Intent'] = None,
entities: List['Entity'] = None) -> None:
"""
Initialize a Workspace object.
:param str name: The name of the workspace. This string cannot contain
carriage return, newline, or tab characters.
:param str language: The language of the workspace.
:param str workspace_id: The workspace ID of the workspace.
:param bool learning_opt_out: Whether training data from the workspace
(including artifacts such as intents and entities) can be used by IBM for
general service improvements. `true` indicates that workspace training data
is not to be used.
:param str description: (optional) The description of the workspace. This
string cannot contain carriage return, newline, or tab characters.
:param List[DialogNode] dialog_nodes: (optional) An array of objects
describing the dialog nodes in the workspace.
:param List[Counterexample] counterexamples: (optional) An array of objects
defining input examples that have been marked as irrelevant input.
:param dict metadata: (optional) Any metadata related to the workspace.
:param WorkspaceSystemSettings system_settings: (optional) Global settings
for the workspace.
:param List[Webhook] webhooks: (optional)
:param List[Intent] intents: (optional) An array of intents.
:param List[Entity] entities: (optional) An array of objects describing the
entities for the workspace.
"""
self.name = name
self.description = description
self.language = language
self.workspace_id = workspace_id
self.dialog_nodes = dialog_nodes
self.counterexamples = counterexamples
self.created = created
self.updated = updated
self.metadata = metadata
self.learning_opt_out = learning_opt_out
self.system_settings = system_settings
self.status = status
self.webhooks = webhooks
self.intents = intents
self.entities = entities
[docs] @classmethod
def from_dict(cls, _dict: Dict) -> 'Workspace':
"""Initialize a Workspace object from a json dictionary."""
args = {}
if 'name' in _dict:
args['name'] = _dict.get('name')
else:
raise ValueError(
'Required property \'name\' not present in Workspace JSON')
if 'description' in _dict:
args['description'] = _dict.get('description')
if 'language' in _dict:
args['language'] = _dict.get('language')
else:
raise ValueError(
'Required property \'language\' not present in Workspace JSON')
if 'workspace_id' in _dict:
args['workspace_id'] = _dict.get('workspace_id')
else:
raise ValueError(
'Required property \'workspace_id\' not present in Workspace JSON'
)
if 'dialog_nodes' in _dict:
args['dialog_nodes'] = [
DialogNode.from_dict(x) for x in _dict.get('dialog_nodes')
]
if 'counterexamples' in _dict:
args['counterexamples'] = [
Counterexample.from_dict(x)
for x in _dict.get('counterexamples')
]
if 'created' in _dict:
args['created'] = string_to_datetime(_dict.get('created'))
if 'updated' in _dict:
args['updated'] = string_to_datetime(_dict.get('updated'))
if 'metadata' in _dict:
args['metadata'] = _dict.get('metadata')
if 'learning_opt_out' in _dict:
args['learning_opt_out'] = _dict.get('learning_opt_out')
else:
raise ValueError(
'Required property \'learning_opt_out\' not present in Workspace JSON'
)
if 'system_settings' in _dict:
args['system_settings'] = WorkspaceSystemSettings.from_dict(
_dict.get('system_settings'))
if 'status' in _dict:
args['status'] = _dict.get('status')
if 'webhooks' in _dict:
args['webhooks'] = [
Webhook.from_dict(x) for x in _dict.get('webhooks')
]
if 'intents' in _dict:
args['intents'] = [
Intent.from_dict(x) for x in _dict.get('intents')
]
if 'entities' in _dict:
args['entities'] = [
Entity.from_dict(x) for x in _dict.get('entities')
]
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a Workspace object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'name') and self.name is not None:
_dict['name'] = self.name
if hasattr(self, 'description') and self.description is not None:
_dict['description'] = self.description
if hasattr(self, 'language') and self.language is not None:
_dict['language'] = self.language
if hasattr(self, 'workspace_id') and getattr(
self, 'workspace_id') is not None:
_dict['workspace_id'] = getattr(self, 'workspace_id')
if hasattr(self, 'dialog_nodes') and self.dialog_nodes is not None:
_dict['dialog_nodes'] = [x.to_dict() for x in self.dialog_nodes]
if hasattr(self,
'counterexamples') and self.counterexamples is not None:
_dict['counterexamples'] = [
x.to_dict() for x in self.counterexamples
]
if hasattr(self, 'created') and getattr(self, 'created') is not None:
_dict['created'] = datetime_to_string(getattr(self, 'created'))
if hasattr(self, 'updated') and getattr(self, 'updated') is not None:
_dict['updated'] = datetime_to_string(getattr(self, 'updated'))
if hasattr(self, 'metadata') and self.metadata is not None:
_dict['metadata'] = self.metadata
if hasattr(self,
'learning_opt_out') and self.learning_opt_out is not None:
_dict['learning_opt_out'] = self.learning_opt_out
if hasattr(self,
'system_settings') and self.system_settings is not None:
_dict['system_settings'] = self.system_settings.to_dict()
if hasattr(self, 'status') and getattr(self, 'status') is not None:
_dict['status'] = getattr(self, 'status')
if hasattr(self, 'webhooks') and self.webhooks is not None:
_dict['webhooks'] = [x.to_dict() for x in self.webhooks]
if hasattr(self, 'intents') and self.intents is not None:
_dict['intents'] = [x.to_dict() for x in self.intents]
if hasattr(self, 'entities') and self.entities is not None:
_dict['entities'] = [x.to_dict() for x in self.entities]
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this Workspace object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'Workspace') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'Workspace') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs] class StatusEnum(str, Enum):
"""
The current status of the workspace.
"""
NON_EXISTENT = 'Non Existent'
TRAINING = 'Training'
FAILED = 'Failed'
AVAILABLE = 'Available'
UNAVAILABLE = 'Unavailable'
[docs]class WorkspaceCollection():
"""
WorkspaceCollection.
:attr List[Workspace] workspaces: An array of objects describing the workspaces
associated with the service instance.
:attr Pagination pagination: The pagination data for the returned objects.
"""
def __init__(self, workspaces: List['Workspace'],
pagination: 'Pagination') -> None:
"""
Initialize a WorkspaceCollection object.
:param List[Workspace] workspaces: An array of objects describing the
workspaces associated with the service instance.
:param Pagination pagination: The pagination data for the returned objects.
"""
self.workspaces = workspaces
self.pagination = pagination
[docs] @classmethod
def from_dict(cls, _dict: Dict) -> 'WorkspaceCollection':
"""Initialize a WorkspaceCollection object from a json dictionary."""
args = {}
if 'workspaces' in _dict:
args['workspaces'] = [
Workspace.from_dict(x) for x in _dict.get('workspaces')
]
else:
raise ValueError(
'Required property \'workspaces\' not present in WorkspaceCollection JSON'
)
if 'pagination' in _dict:
args['pagination'] = Pagination.from_dict(_dict.get('pagination'))
else:
raise ValueError(
'Required property \'pagination\' not present in WorkspaceCollection JSON'
)
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a WorkspaceCollection object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'workspaces') and self.workspaces is not None:
_dict['workspaces'] = [x.to_dict() for x in self.workspaces]
if hasattr(self, 'pagination') and self.pagination is not None:
_dict['pagination'] = self.pagination.to_dict()
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this WorkspaceCollection object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'WorkspaceCollection') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'WorkspaceCollection') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]class WorkspaceSystemSettings():
"""
Global settings for the workspace.
:attr WorkspaceSystemSettingsTooling tooling: (optional) Workspace settings
related to the Watson Assistant user interface.
:attr WorkspaceSystemSettingsDisambiguation disambiguation: (optional) Workspace
settings related to the disambiguation feature.
:attr dict human_agent_assist: (optional) For internal use only.
:attr bool spelling_suggestions: (optional) Whether spelling correction is
enabled for the workspace.
:attr bool spelling_auto_correct: (optional) Whether autocorrection is enabled
for the workspace. If spelling correction is enabled and this property is
`false`, any suggested corrections are returned in the **suggested_text**
property of the message response. If this property is `true`, any corrections
are automatically applied to the user input, and the original text is returned
in the **original_text** property of the message response.
:attr WorkspaceSystemSettingsSystemEntities system_entities: (optional)
Workspace settings related to the behavior of system entities.
:attr WorkspaceSystemSettingsOffTopic off_topic: (optional) Workspace settings
related to detection of irrelevant input.
"""
def __init__(
self,
*,
tooling: 'WorkspaceSystemSettingsTooling' = None,
disambiguation: 'WorkspaceSystemSettingsDisambiguation' = None,
human_agent_assist: dict = None,
spelling_suggestions: bool = None,
spelling_auto_correct: bool = None,
system_entities: 'WorkspaceSystemSettingsSystemEntities' = None,
off_topic: 'WorkspaceSystemSettingsOffTopic' = None) -> None:
"""
Initialize a WorkspaceSystemSettings object.
:param WorkspaceSystemSettingsTooling tooling: (optional) Workspace
settings related to the Watson Assistant user interface.
:param WorkspaceSystemSettingsDisambiguation disambiguation: (optional)
Workspace settings related to the disambiguation feature.
:param dict human_agent_assist: (optional) For internal use only.
:param bool spelling_suggestions: (optional) Whether spelling correction is
enabled for the workspace.
:param bool spelling_auto_correct: (optional) Whether autocorrection is
enabled for the workspace. If spelling correction is enabled and this
property is `false`, any suggested corrections are returned in the
**suggested_text** property of the message response. If this property is
`true`, any corrections are automatically applied to the user input, and
the original text is returned in the **original_text** property of the
message response.
:param WorkspaceSystemSettingsSystemEntities system_entities: (optional)
Workspace settings related to the behavior of system entities.
:param WorkspaceSystemSettingsOffTopic off_topic: (optional) Workspace
settings related to detection of irrelevant input.
"""
self.tooling = tooling
self.disambiguation = disambiguation
self.human_agent_assist = human_agent_assist
self.spelling_suggestions = spelling_suggestions
self.spelling_auto_correct = spelling_auto_correct
self.system_entities = system_entities
self.off_topic = off_topic
[docs] @classmethod
def from_dict(cls, _dict: Dict) -> 'WorkspaceSystemSettings':
"""Initialize a WorkspaceSystemSettings object from a json dictionary."""
args = {}
if 'tooling' in _dict:
args['tooling'] = WorkspaceSystemSettingsTooling.from_dict(
_dict.get('tooling'))
if 'disambiguation' in _dict:
args[
'disambiguation'] = WorkspaceSystemSettingsDisambiguation.from_dict(
_dict.get('disambiguation'))
if 'human_agent_assist' in _dict:
args['human_agent_assist'] = _dict.get('human_agent_assist')
if 'spelling_suggestions' in _dict:
args['spelling_suggestions'] = _dict.get('spelling_suggestions')
if 'spelling_auto_correct' in _dict:
args['spelling_auto_correct'] = _dict.get('spelling_auto_correct')
if 'system_entities' in _dict:
args[
'system_entities'] = WorkspaceSystemSettingsSystemEntities.from_dict(
_dict.get('system_entities'))
if 'off_topic' in _dict:
args['off_topic'] = WorkspaceSystemSettingsOffTopic.from_dict(
_dict.get('off_topic'))
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a WorkspaceSystemSettings object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'tooling') and self.tooling is not None:
_dict['tooling'] = self.tooling.to_dict()
if hasattr(self, 'disambiguation') and self.disambiguation is not None:
_dict['disambiguation'] = self.disambiguation.to_dict()
if hasattr(
self,
'human_agent_assist') and self.human_agent_assist is not None:
_dict['human_agent_assist'] = self.human_agent_assist
if hasattr(self, 'spelling_suggestions'
) and self.spelling_suggestions is not None:
_dict['spelling_suggestions'] = self.spelling_suggestions
if hasattr(self, 'spelling_auto_correct'
) and self.spelling_auto_correct is not None:
_dict['spelling_auto_correct'] = self.spelling_auto_correct
if hasattr(self,
'system_entities') and self.system_entities is not None:
_dict['system_entities'] = self.system_entities.to_dict()
if hasattr(self, 'off_topic') and self.off_topic is not None:
_dict['off_topic'] = self.off_topic.to_dict()
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 WorkspaceSystemSettings object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'WorkspaceSystemSettings') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'WorkspaceSystemSettings') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]class WorkspaceSystemSettingsDisambiguation():
"""
Workspace settings related to the disambiguation feature.
:attr str prompt: (optional) The text of the introductory prompt that
accompanies disambiguation options presented to the user.
:attr str none_of_the_above_prompt: (optional) The user-facing label for the
option users can select if none of the suggested options is correct. If no value
is specified for this property, this option does not appear.
:attr bool enabled: (optional) Whether the disambiguation feature is enabled for
the workspace.
:attr str sensitivity: (optional) The sensitivity of the disambiguation feature
to intent detection conflicts. Set to **high** if you want the disambiguation
feature to be triggered more often. This can be useful for testing or
demonstration purposes.
:attr bool randomize: (optional) Whether the order in which disambiguation
suggestions are presented should be randomized (but still influenced by relative
confidence).
:attr int max_suggestions: (optional) The maximum number of disambigation
suggestions that can be included in a `suggestion` response.
:attr str suggestion_text_policy: (optional) For internal use only.
"""
def __init__(self,
*,
prompt: str = None,
none_of_the_above_prompt: str = None,
enabled: bool = None,
sensitivity: str = None,
randomize: bool = None,
max_suggestions: int = None,
suggestion_text_policy: str = None) -> None:
"""
Initialize a WorkspaceSystemSettingsDisambiguation object.
:param str prompt: (optional) The text of the introductory prompt that
accompanies disambiguation options presented to the user.
:param str none_of_the_above_prompt: (optional) The user-facing label for
the option users can select if none of the suggested options is correct. If
no value is specified for this property, this option does not appear.
:param bool enabled: (optional) Whether the disambiguation feature is
enabled for the workspace.
:param str sensitivity: (optional) The sensitivity of the disambiguation
feature to intent detection conflicts. Set to **high** if you want the
disambiguation feature to be triggered more often. This can be useful for
testing or demonstration purposes.
:param bool randomize: (optional) Whether the order in which disambiguation
suggestions are presented should be randomized (but still influenced by
relative confidence).
:param int max_suggestions: (optional) The maximum number of disambigation
suggestions that can be included in a `suggestion` response.
:param str suggestion_text_policy: (optional) For internal use only.
"""
self.prompt = prompt
self.none_of_the_above_prompt = none_of_the_above_prompt
self.enabled = enabled
self.sensitivity = sensitivity
self.randomize = randomize
self.max_suggestions = max_suggestions
self.suggestion_text_policy = suggestion_text_policy
[docs] @classmethod
def from_dict(cls, _dict: Dict) -> 'WorkspaceSystemSettingsDisambiguation':
"""Initialize a WorkspaceSystemSettingsDisambiguation object from a json dictionary."""
args = {}
if 'prompt' in _dict:
args['prompt'] = _dict.get('prompt')
if 'none_of_the_above_prompt' in _dict:
args['none_of_the_above_prompt'] = _dict.get(
'none_of_the_above_prompt')
if 'enabled' in _dict:
args['enabled'] = _dict.get('enabled')
if 'sensitivity' in _dict:
args['sensitivity'] = _dict.get('sensitivity')
if 'randomize' in _dict:
args['randomize'] = _dict.get('randomize')
if 'max_suggestions' in _dict:
args['max_suggestions'] = _dict.get('max_suggestions')
if 'suggestion_text_policy' in _dict:
args['suggestion_text_policy'] = _dict.get('suggestion_text_policy')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a WorkspaceSystemSettingsDisambiguation object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'prompt') and self.prompt is not None:
_dict['prompt'] = self.prompt
if hasattr(self, 'none_of_the_above_prompt'
) and self.none_of_the_above_prompt is not None:
_dict['none_of_the_above_prompt'] = self.none_of_the_above_prompt
if hasattr(self, 'enabled') and self.enabled is not None:
_dict['enabled'] = self.enabled
if hasattr(self, 'sensitivity') and self.sensitivity is not None:
_dict['sensitivity'] = self.sensitivity
if hasattr(self, 'randomize') and self.randomize is not None:
_dict['randomize'] = self.randomize
if hasattr(self,
'max_suggestions') and self.max_suggestions is not None:
_dict['max_suggestions'] = self.max_suggestions
if hasattr(self, 'suggestion_text_policy'
) and self.suggestion_text_policy is not None:
_dict['suggestion_text_policy'] = self.suggestion_text_policy
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this WorkspaceSystemSettingsDisambiguation object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'WorkspaceSystemSettingsDisambiguation') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'WorkspaceSystemSettingsDisambiguation') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs] class SensitivityEnum(str, Enum):
"""
The sensitivity of the disambiguation feature to intent detection conflicts. Set
to **high** if you want the disambiguation feature to be triggered more often.
This can be useful for testing or demonstration purposes.
"""
AUTO = 'auto'
HIGH = 'high'
[docs]class WorkspaceSystemSettingsOffTopic():
"""
Workspace settings related to detection of irrelevant input.
:attr bool enabled: (optional) Whether enhanced irrelevance detection is enabled
for the workspace.
"""
def __init__(self, *, enabled: bool = None) -> None:
"""
Initialize a WorkspaceSystemSettingsOffTopic object.
:param bool enabled: (optional) Whether enhanced irrelevance detection is
enabled for the workspace.
"""
self.enabled = enabled
[docs] @classmethod
def from_dict(cls, _dict: Dict) -> 'WorkspaceSystemSettingsOffTopic':
"""Initialize a WorkspaceSystemSettingsOffTopic object from a json dictionary."""
args = {}
if 'enabled' in _dict:
args['enabled'] = _dict.get('enabled')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a WorkspaceSystemSettingsOffTopic object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'enabled') and self.enabled is not None:
_dict['enabled'] = self.enabled
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this WorkspaceSystemSettingsOffTopic object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'WorkspaceSystemSettingsOffTopic') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'WorkspaceSystemSettingsOffTopic') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]class WorkspaceSystemSettingsSystemEntities():
"""
Workspace settings related to the behavior of system entities.
:attr bool enabled: (optional) Whether the new system entities are enabled for
the workspace.
"""
def __init__(self, *, enabled: bool = None) -> None:
"""
Initialize a WorkspaceSystemSettingsSystemEntities object.
:param bool enabled: (optional) Whether the new system entities are enabled
for the workspace.
"""
self.enabled = enabled
[docs] @classmethod
def from_dict(cls, _dict: Dict) -> 'WorkspaceSystemSettingsSystemEntities':
"""Initialize a WorkspaceSystemSettingsSystemEntities object from a json dictionary."""
args = {}
if 'enabled' in _dict:
args['enabled'] = _dict.get('enabled')
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a WorkspaceSystemSettingsSystemEntities object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'enabled') and self.enabled is not None:
_dict['enabled'] = self.enabled
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this WorkspaceSystemSettingsSystemEntities object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(self, other: 'WorkspaceSystemSettingsSystemEntities') -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(self, other: 'WorkspaceSystemSettingsSystemEntities') -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]class DialogNodeOutputGenericDialogNodeOutputResponseTypeChannelTransfer(
DialogNodeOutputGeneric):
"""
DialogNodeOutputGenericDialogNodeOutputResponseTypeChannelTransfer.
:attr str response_type: The type of response returned by the dialog node. The
specified response type must be supported by the client application or channel.
:attr str message_to_user: The message to display to the user when initiating a
channel transfer.
:attr ChannelTransferInfo transfer_info: Information used by an integration to
transfer the conversation to a different channel.
:attr List[ResponseGenericChannel] channels: (optional) An array of objects
specifying channels for which the response is intended.
"""
def __init__(self,
response_type: str,
message_to_user: str,
transfer_info: 'ChannelTransferInfo',
*,
channels: List['ResponseGenericChannel'] = None) -> None:
"""
Initialize a DialogNodeOutputGenericDialogNodeOutputResponseTypeChannelTransfer object.
:param str response_type: The type of response returned by the dialog node.
The specified response type must be supported by the client application or
channel.
:param str message_to_user: The message to display to the user when
initiating a channel transfer.
:param ChannelTransferInfo transfer_info: Information used by an
integration to transfer the conversation to a different channel.
:param List[ResponseGenericChannel] channels: (optional) An array of
objects specifying channels for which the response is intended.
"""
# pylint: disable=super-init-not-called
self.response_type = response_type
self.message_to_user = message_to_user
self.transfer_info = transfer_info
self.channels = channels
[docs] @classmethod
def from_dict(
cls, _dict: Dict
) -> 'DialogNodeOutputGenericDialogNodeOutputResponseTypeChannelTransfer':
"""Initialize a DialogNodeOutputGenericDialogNodeOutputResponseTypeChannelTransfer object from a json dictionary."""
args = {}
if 'response_type' in _dict:
args['response_type'] = _dict.get('response_type')
else:
raise ValueError(
'Required property \'response_type\' not present in DialogNodeOutputGenericDialogNodeOutputResponseTypeChannelTransfer JSON'
)
if 'message_to_user' in _dict:
args['message_to_user'] = _dict.get('message_to_user')
else:
raise ValueError(
'Required property \'message_to_user\' not present in DialogNodeOutputGenericDialogNodeOutputResponseTypeChannelTransfer JSON'
)
if 'transfer_info' in _dict:
args['transfer_info'] = ChannelTransferInfo.from_dict(
_dict.get('transfer_info'))
else:
raise ValueError(
'Required property \'transfer_info\' not present in DialogNodeOutputGenericDialogNodeOutputResponseTypeChannelTransfer JSON'
)
if 'channels' in _dict:
args['channels'] = [
ResponseGenericChannel.from_dict(x)
for x in _dict.get('channels')
]
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DialogNodeOutputGenericDialogNodeOutputResponseTypeChannelTransfer object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'response_type') and self.response_type is not None:
_dict['response_type'] = self.response_type
if hasattr(self,
'message_to_user') and self.message_to_user is not None:
_dict['message_to_user'] = self.message_to_user
if hasattr(self, 'transfer_info') and self.transfer_info is not None:
_dict['transfer_info'] = self.transfer_info.to_dict()
if hasattr(self, 'channels') and self.channels is not None:
_dict['channels'] = [x.to_dict() for x in self.channels]
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DialogNodeOutputGenericDialogNodeOutputResponseTypeChannelTransfer object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(
self, other:
'DialogNodeOutputGenericDialogNodeOutputResponseTypeChannelTransfer'
) -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(
self, other:
'DialogNodeOutputGenericDialogNodeOutputResponseTypeChannelTransfer'
) -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]class DialogNodeOutputGenericDialogNodeOutputResponseTypeConnectToAgent(
DialogNodeOutputGeneric):
"""
DialogNodeOutputGenericDialogNodeOutputResponseTypeConnectToAgent.
:attr str response_type: The type of response returned by the dialog node. The
specified response type must be supported by the client application or channel.
:attr str message_to_human_agent: (optional) An optional message to be sent to
the human agent who will be taking over the conversation.
:attr AgentAvailabilityMessage agent_available: (optional) An optional message
to be displayed to the user to indicate that the conversation will be
transferred to the next available agent.
:attr AgentAvailabilityMessage agent_unavailable: (optional) An optional message
to be displayed to the user to indicate that no online agent is available to
take over the conversation.
:attr DialogNodeOutputConnectToAgentTransferInfo transfer_info: (optional)
Routing or other contextual information to be used by target service desk
systems.
:attr List[ResponseGenericChannel] channels: (optional) An array of objects
specifying channels for which the response is intended.
"""
def __init__(
self,
response_type: str,
*,
message_to_human_agent: str = None,
agent_available: 'AgentAvailabilityMessage' = None,
agent_unavailable: 'AgentAvailabilityMessage' = None,
transfer_info: 'DialogNodeOutputConnectToAgentTransferInfo' = None,
channels: List['ResponseGenericChannel'] = None) -> None:
"""
Initialize a DialogNodeOutputGenericDialogNodeOutputResponseTypeConnectToAgent object.
:param str response_type: The type of response returned by the dialog node.
The specified response type must be supported by the client application or
channel.
:param str message_to_human_agent: (optional) An optional message to be
sent to the human agent who will be taking over the conversation.
:param AgentAvailabilityMessage agent_available: (optional) An optional
message to be displayed to the user to indicate that the conversation will
be transferred to the next available agent.
:param AgentAvailabilityMessage agent_unavailable: (optional) An optional
message to be displayed to the user to indicate that no online agent is
available to take over the conversation.
:param DialogNodeOutputConnectToAgentTransferInfo transfer_info: (optional)
Routing or other contextual information to be used by target service desk
systems.
:param List[ResponseGenericChannel] channels: (optional) An array of
objects specifying channels for which the response is intended.
"""
# pylint: disable=super-init-not-called
self.response_type = response_type
self.message_to_human_agent = message_to_human_agent
self.agent_available = agent_available
self.agent_unavailable = agent_unavailable
self.transfer_info = transfer_info
self.channels = channels
[docs] @classmethod
def from_dict(
cls, _dict: Dict
) -> 'DialogNodeOutputGenericDialogNodeOutputResponseTypeConnectToAgent':
"""Initialize a DialogNodeOutputGenericDialogNodeOutputResponseTypeConnectToAgent object from a json dictionary."""
args = {}
if 'response_type' in _dict:
args['response_type'] = _dict.get('response_type')
else:
raise ValueError(
'Required property \'response_type\' not present in DialogNodeOutputGenericDialogNodeOutputResponseTypeConnectToAgent JSON'
)
if 'message_to_human_agent' in _dict:
args['message_to_human_agent'] = _dict.get('message_to_human_agent')
if 'agent_available' in _dict:
args['agent_available'] = AgentAvailabilityMessage.from_dict(
_dict.get('agent_available'))
if 'agent_unavailable' in _dict:
args['agent_unavailable'] = AgentAvailabilityMessage.from_dict(
_dict.get('agent_unavailable'))
if 'transfer_info' in _dict:
args[
'transfer_info'] = DialogNodeOutputConnectToAgentTransferInfo.from_dict(
_dict.get('transfer_info'))
if 'channels' in _dict:
args['channels'] = [
ResponseGenericChannel.from_dict(x)
for x in _dict.get('channels')
]
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DialogNodeOutputGenericDialogNodeOutputResponseTypeConnectToAgent object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'response_type') and self.response_type is not None:
_dict['response_type'] = self.response_type
if hasattr(self, 'message_to_human_agent'
) and self.message_to_human_agent is not None:
_dict['message_to_human_agent'] = self.message_to_human_agent
if hasattr(self,
'agent_available') and self.agent_available is not None:
_dict['agent_available'] = self.agent_available.to_dict()
if hasattr(self,
'agent_unavailable') and self.agent_unavailable is not None:
_dict['agent_unavailable'] = self.agent_unavailable.to_dict()
if hasattr(self, 'transfer_info') and self.transfer_info is not None:
_dict['transfer_info'] = self.transfer_info.to_dict()
if hasattr(self, 'channels') and self.channels is not None:
_dict['channels'] = [x.to_dict() for x in self.channels]
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DialogNodeOutputGenericDialogNodeOutputResponseTypeConnectToAgent object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(
self,
other: 'DialogNodeOutputGenericDialogNodeOutputResponseTypeConnectToAgent'
) -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(
self,
other: 'DialogNodeOutputGenericDialogNodeOutputResponseTypeConnectToAgent'
) -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]class DialogNodeOutputGenericDialogNodeOutputResponseTypeImage(
DialogNodeOutputGeneric):
"""
DialogNodeOutputGenericDialogNodeOutputResponseTypeImage.
:attr str response_type: The type of response returned by the dialog node. The
specified response type must be supported by the client application or channel.
:attr str source: The URL of the image.
:attr str title: (optional) An optional title to show before the response.
:attr str description: (optional) An optional description to show with the
response.
:attr List[ResponseGenericChannel] channels: (optional) An array of objects
specifying channels for which the response is intended.
"""
def __init__(self,
response_type: str,
source: str,
*,
title: str = None,
description: str = None,
channels: List['ResponseGenericChannel'] = None) -> None:
"""
Initialize a DialogNodeOutputGenericDialogNodeOutputResponseTypeImage object.
:param str response_type: The type of response returned by the dialog node.
The specified response type must be supported by the client application or
channel.
:param str source: The URL of the image.
:param str title: (optional) An optional title to show before the response.
:param str description: (optional) An optional description to show with the
response.
:param List[ResponseGenericChannel] channels: (optional) An array of
objects specifying channels for which the response is intended.
"""
# pylint: disable=super-init-not-called
self.response_type = response_type
self.source = source
self.title = title
self.description = description
self.channels = channels
[docs] @classmethod
def from_dict(
cls, _dict: Dict
) -> 'DialogNodeOutputGenericDialogNodeOutputResponseTypeImage':
"""Initialize a DialogNodeOutputGenericDialogNodeOutputResponseTypeImage object from a json dictionary."""
args = {}
if 'response_type' in _dict:
args['response_type'] = _dict.get('response_type')
else:
raise ValueError(
'Required property \'response_type\' not present in DialogNodeOutputGenericDialogNodeOutputResponseTypeImage JSON'
)
if 'source' in _dict:
args['source'] = _dict.get('source')
else:
raise ValueError(
'Required property \'source\' not present in DialogNodeOutputGenericDialogNodeOutputResponseTypeImage JSON'
)
if 'title' in _dict:
args['title'] = _dict.get('title')
if 'description' in _dict:
args['description'] = _dict.get('description')
if 'channels' in _dict:
args['channels'] = [
ResponseGenericChannel.from_dict(x)
for x in _dict.get('channels')
]
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DialogNodeOutputGenericDialogNodeOutputResponseTypeImage object from a json dictionary."""
return cls.from_dict(_dict)
[docs] 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]
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DialogNodeOutputGenericDialogNodeOutputResponseTypeImage object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(
self, other: 'DialogNodeOutputGenericDialogNodeOutputResponseTypeImage'
) -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(
self, other: 'DialogNodeOutputGenericDialogNodeOutputResponseTypeImage'
) -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]class DialogNodeOutputGenericDialogNodeOutputResponseTypeOption(
DialogNodeOutputGeneric):
"""
DialogNodeOutputGenericDialogNodeOutputResponseTypeOption.
:attr str response_type: The type of response returned by the dialog node. The
specified response type must be supported by the client application or channel.
:attr str title: An optional title to show before the response.
:attr str description: (optional) An optional description to show with the
response.
:attr str preference: (optional) The preferred type of control to display, if
supported by the channel.
:attr List[DialogNodeOutputOptionsElement] options: An array of objects
describing the options from which the user can choose. You can include up to 20
options.
:attr List[ResponseGenericChannel] channels: (optional) An array of objects
specifying channels for which the response is intended.
"""
def __init__(self,
response_type: str,
title: str,
options: List['DialogNodeOutputOptionsElement'],
*,
description: str = None,
preference: str = None,
channels: List['ResponseGenericChannel'] = None) -> None:
"""
Initialize a DialogNodeOutputGenericDialogNodeOutputResponseTypeOption object.
:param str response_type: The type of response returned by the dialog node.
The specified response type must be supported by the client application or
channel.
:param str title: An optional title to show before the response.
:param List[DialogNodeOutputOptionsElement] options: An array of objects
describing the options from which the user can choose. You can include up
to 20 options.
:param str description: (optional) An optional description to show with the
response.
:param str preference: (optional) The preferred type of control to display,
if supported by the channel.
:param List[ResponseGenericChannel] channels: (optional) An array of
objects specifying channels for which the response is intended.
"""
# pylint: disable=super-init-not-called
self.response_type = response_type
self.title = title
self.description = description
self.preference = preference
self.options = options
self.channels = channels
[docs] @classmethod
def from_dict(
cls, _dict: Dict
) -> 'DialogNodeOutputGenericDialogNodeOutputResponseTypeOption':
"""Initialize a DialogNodeOutputGenericDialogNodeOutputResponseTypeOption object from a json dictionary."""
args = {}
if 'response_type' in _dict:
args['response_type'] = _dict.get('response_type')
else:
raise ValueError(
'Required property \'response_type\' not present in DialogNodeOutputGenericDialogNodeOutputResponseTypeOption JSON'
)
if 'title' in _dict:
args['title'] = _dict.get('title')
else:
raise ValueError(
'Required property \'title\' not present in DialogNodeOutputGenericDialogNodeOutputResponseTypeOption JSON'
)
if 'description' in _dict:
args['description'] = _dict.get('description')
if 'preference' in _dict:
args['preference'] = _dict.get('preference')
if 'options' in _dict:
args['options'] = [
DialogNodeOutputOptionsElement.from_dict(x)
for x in _dict.get('options')
]
else:
raise ValueError(
'Required property \'options\' not present in DialogNodeOutputGenericDialogNodeOutputResponseTypeOption JSON'
)
if 'channels' in _dict:
args['channels'] = [
ResponseGenericChannel.from_dict(x)
for x in _dict.get('channels')
]
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DialogNodeOutputGenericDialogNodeOutputResponseTypeOption object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'response_type') and self.response_type is not None:
_dict['response_type'] = self.response_type
if hasattr(self, 'title') and self.title is not None:
_dict['title'] = self.title
if hasattr(self, 'description') and self.description is not None:
_dict['description'] = self.description
if hasattr(self, 'preference') and self.preference is not None:
_dict['preference'] = self.preference
if hasattr(self, 'options') and self.options is not None:
_dict['options'] = [x.to_dict() for x in self.options]
if hasattr(self, 'channels') and self.channels is not None:
_dict['channels'] = [x.to_dict() for x in self.channels]
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DialogNodeOutputGenericDialogNodeOutputResponseTypeOption object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(
self, other: 'DialogNodeOutputGenericDialogNodeOutputResponseTypeOption'
) -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(
self, other: 'DialogNodeOutputGenericDialogNodeOutputResponseTypeOption'
) -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs] class PreferenceEnum(str, Enum):
"""
The preferred type of control to display, if supported by the channel.
"""
DROPDOWN = 'dropdown'
BUTTON = 'button'
[docs]class DialogNodeOutputGenericDialogNodeOutputResponseTypePause(
DialogNodeOutputGeneric):
"""
DialogNodeOutputGenericDialogNodeOutputResponseTypePause.
:attr str response_type: The type of response returned by the dialog node. The
specified response type must be supported by the client application or channel.
:attr int time: How long to pause, in milliseconds. The valid values are from 0
to 10000.
:attr bool typing: (optional) Whether to send a "user is typing" event during
the pause. Ignored if the channel does not support this event.
:attr List[ResponseGenericChannel] channels: (optional) An array of objects
specifying channels for which the response is intended.
"""
def __init__(self,
response_type: str,
time: int,
*,
typing: bool = None,
channels: List['ResponseGenericChannel'] = None) -> None:
"""
Initialize a DialogNodeOutputGenericDialogNodeOutputResponseTypePause object.
:param str response_type: The type of response returned by the dialog node.
The specified response type must be supported by the client application or
channel.
:param int time: How long to pause, in milliseconds. The valid values are
from 0 to 10000.
:param bool typing: (optional) Whether to send a "user is typing" event
during the pause. Ignored if the channel does not support this event.
:param List[ResponseGenericChannel] channels: (optional) An array of
objects specifying channels for which the response is intended.
"""
# pylint: disable=super-init-not-called
self.response_type = response_type
self.time = time
self.typing = typing
self.channels = channels
[docs] @classmethod
def from_dict(
cls, _dict: Dict
) -> 'DialogNodeOutputGenericDialogNodeOutputResponseTypePause':
"""Initialize a DialogNodeOutputGenericDialogNodeOutputResponseTypePause object from a json dictionary."""
args = {}
if 'response_type' in _dict:
args['response_type'] = _dict.get('response_type')
else:
raise ValueError(
'Required property \'response_type\' not present in DialogNodeOutputGenericDialogNodeOutputResponseTypePause JSON'
)
if 'time' in _dict:
args['time'] = _dict.get('time')
else:
raise ValueError(
'Required property \'time\' not present in DialogNodeOutputGenericDialogNodeOutputResponseTypePause JSON'
)
if 'typing' in _dict:
args['typing'] = _dict.get('typing')
if 'channels' in _dict:
args['channels'] = [
ResponseGenericChannel.from_dict(x)
for x in _dict.get('channels')
]
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DialogNodeOutputGenericDialogNodeOutputResponseTypePause object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'response_type') and self.response_type is not None:
_dict['response_type'] = self.response_type
if hasattr(self, 'time') and self.time is not None:
_dict['time'] = self.time
if hasattr(self, 'typing') and self.typing is not None:
_dict['typing'] = self.typing
if hasattr(self, 'channels') and self.channels is not None:
_dict['channels'] = [x.to_dict() for x in self.channels]
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DialogNodeOutputGenericDialogNodeOutputResponseTypePause object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(
self, other: 'DialogNodeOutputGenericDialogNodeOutputResponseTypePause'
) -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(
self, other: 'DialogNodeOutputGenericDialogNodeOutputResponseTypePause'
) -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]class DialogNodeOutputGenericDialogNodeOutputResponseTypeSearchSkill(
DialogNodeOutputGeneric):
"""
DialogNodeOutputGenericDialogNodeOutputResponseTypeSearchSkill.
:attr str response_type: The type of response returned by the dialog node. The
specified response type must be supported by the client application or channel.
**Note:** The **search_skill** response type is used only by the v2 runtime API.
:attr str query: The text of the search query. This can be either a
natural-language query or a query that uses the Discovery query language syntax,
depending on the value of the **query_type** property. For more information, see
the [Discovery service
documentation](https://cloud.ibm.com/docs/discovery?topic=discovery-query-operators#query-operators).
:attr str query_type: The type of the search query.
:attr str filter: (optional) An optional filter that narrows the set of
documents to be searched. For more information, see the [Discovery service
documentation]([Discovery service
documentation](https://cloud.ibm.com/docs/discovery?topic=discovery-query-parameters#filter).
:attr str discovery_version: (optional) The version of the Discovery service API
to use for the query.
:attr List[ResponseGenericChannel] channels: (optional) An array of objects
specifying channels for which the response is intended.
"""
def __init__(self,
response_type: str,
query: str,
query_type: str,
*,
filter: str = None,
discovery_version: str = None,
channels: List['ResponseGenericChannel'] = None) -> None:
"""
Initialize a DialogNodeOutputGenericDialogNodeOutputResponseTypeSearchSkill object.
:param str response_type: The type of response returned by the dialog node.
The specified response type must be supported by the client application or
channel.
**Note:** The **search_skill** response type is used only by the v2 runtime
API.
:param str query: The text of the search query. This can be either a
natural-language query or a query that uses the Discovery query language
syntax, depending on the value of the **query_type** property. For more
information, see the [Discovery service
documentation](https://cloud.ibm.com/docs/discovery?topic=discovery-query-operators#query-operators).
:param str query_type: The type of the search query.
:param str filter: (optional) An optional filter that narrows the set of
documents to be searched. For more information, see the [Discovery service
documentation]([Discovery service
documentation](https://cloud.ibm.com/docs/discovery?topic=discovery-query-parameters#filter).
:param str discovery_version: (optional) The version of the Discovery
service API to use for the query.
:param List[ResponseGenericChannel] channels: (optional) An array of
objects specifying channels for which the response is intended.
"""
# pylint: disable=super-init-not-called
self.response_type = response_type
self.query = query
self.query_type = query_type
self.filter = filter
self.discovery_version = discovery_version
self.channels = channels
[docs] @classmethod
def from_dict(
cls, _dict: Dict
) -> 'DialogNodeOutputGenericDialogNodeOutputResponseTypeSearchSkill':
"""Initialize a DialogNodeOutputGenericDialogNodeOutputResponseTypeSearchSkill object from a json dictionary."""
args = {}
if 'response_type' in _dict:
args['response_type'] = _dict.get('response_type')
else:
raise ValueError(
'Required property \'response_type\' not present in DialogNodeOutputGenericDialogNodeOutputResponseTypeSearchSkill JSON'
)
if 'query' in _dict:
args['query'] = _dict.get('query')
else:
raise ValueError(
'Required property \'query\' not present in DialogNodeOutputGenericDialogNodeOutputResponseTypeSearchSkill JSON'
)
if 'query_type' in _dict:
args['query_type'] = _dict.get('query_type')
else:
raise ValueError(
'Required property \'query_type\' not present in DialogNodeOutputGenericDialogNodeOutputResponseTypeSearchSkill JSON'
)
if 'filter' in _dict:
args['filter'] = _dict.get('filter')
if 'discovery_version' in _dict:
args['discovery_version'] = _dict.get('discovery_version')
if 'channels' in _dict:
args['channels'] = [
ResponseGenericChannel.from_dict(x)
for x in _dict.get('channels')
]
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DialogNodeOutputGenericDialogNodeOutputResponseTypeSearchSkill object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'response_type') and self.response_type is not None:
_dict['response_type'] = self.response_type
if hasattr(self, 'query') and self.query is not None:
_dict['query'] = self.query
if hasattr(self, 'query_type') and self.query_type is not None:
_dict['query_type'] = self.query_type
if hasattr(self, 'filter') and self.filter is not None:
_dict['filter'] = self.filter
if hasattr(self,
'discovery_version') and self.discovery_version is not None:
_dict['discovery_version'] = self.discovery_version
if hasattr(self, 'channels') and self.channels is not None:
_dict['channels'] = [x.to_dict() for x in self.channels]
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DialogNodeOutputGenericDialogNodeOutputResponseTypeSearchSkill object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(
self,
other: 'DialogNodeOutputGenericDialogNodeOutputResponseTypeSearchSkill'
) -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(
self,
other: 'DialogNodeOutputGenericDialogNodeOutputResponseTypeSearchSkill'
) -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs] class QueryTypeEnum(str, Enum):
"""
The type of the search query.
"""
NATURAL_LANGUAGE = 'natural_language'
DISCOVERY_QUERY_LANGUAGE = 'discovery_query_language'
[docs]class DialogNodeOutputGenericDialogNodeOutputResponseTypeText(
DialogNodeOutputGeneric):
"""
DialogNodeOutputGenericDialogNodeOutputResponseTypeText.
:attr str response_type: The type of response returned by the dialog node. The
specified response type must be supported by the client application or channel.
:attr List[DialogNodeOutputTextValuesElement] values: A list of one or more
objects defining text responses.
:attr str selection_policy: (optional) How a response is selected from the list,
if more than one response is specified.
:attr str delimiter: (optional) The delimiter to use as a separator between
responses when `selection_policy`=`multiline`.
:attr List[ResponseGenericChannel] channels: (optional) An array of objects
specifying channels for which the response is intended.
"""
def __init__(self,
response_type: str,
values: List['DialogNodeOutputTextValuesElement'],
*,
selection_policy: str = None,
delimiter: str = None,
channels: List['ResponseGenericChannel'] = None) -> None:
"""
Initialize a DialogNodeOutputGenericDialogNodeOutputResponseTypeText object.
:param str response_type: The type of response returned by the dialog node.
The specified response type must be supported by the client application or
channel.
:param List[DialogNodeOutputTextValuesElement] values: A list of one or
more objects defining text responses.
:param str selection_policy: (optional) How a response is selected from the
list, if more than one response is specified.
:param str delimiter: (optional) The delimiter to use as a separator
between responses when `selection_policy`=`multiline`.
:param List[ResponseGenericChannel] channels: (optional) An array of
objects specifying channels for which the response is intended.
"""
# pylint: disable=super-init-not-called
self.response_type = response_type
self.values = values
self.selection_policy = selection_policy
self.delimiter = delimiter
self.channels = channels
[docs] @classmethod
def from_dict(
cls, _dict: Dict
) -> 'DialogNodeOutputGenericDialogNodeOutputResponseTypeText':
"""Initialize a DialogNodeOutputGenericDialogNodeOutputResponseTypeText object from a json dictionary."""
args = {}
if 'response_type' in _dict:
args['response_type'] = _dict.get('response_type')
else:
raise ValueError(
'Required property \'response_type\' not present in DialogNodeOutputGenericDialogNodeOutputResponseTypeText JSON'
)
if 'values' in _dict:
args['values'] = [
DialogNodeOutputTextValuesElement.from_dict(x)
for x in _dict.get('values')
]
else:
raise ValueError(
'Required property \'values\' not present in DialogNodeOutputGenericDialogNodeOutputResponseTypeText JSON'
)
if 'selection_policy' in _dict:
args['selection_policy'] = _dict.get('selection_policy')
if 'delimiter' in _dict:
args['delimiter'] = _dict.get('delimiter')
if 'channels' in _dict:
args['channels'] = [
ResponseGenericChannel.from_dict(x)
for x in _dict.get('channels')
]
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DialogNodeOutputGenericDialogNodeOutputResponseTypeText object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'response_type') and self.response_type is not None:
_dict['response_type'] = self.response_type
if hasattr(self, 'values') and self.values is not None:
_dict['values'] = [x.to_dict() for x in self.values]
if hasattr(self,
'selection_policy') and self.selection_policy is not None:
_dict['selection_policy'] = self.selection_policy
if hasattr(self, 'delimiter') and self.delimiter is not None:
_dict['delimiter'] = self.delimiter
if hasattr(self, 'channels') and self.channels is not None:
_dict['channels'] = [x.to_dict() for x in self.channels]
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DialogNodeOutputGenericDialogNodeOutputResponseTypeText object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(
self, other: 'DialogNodeOutputGenericDialogNodeOutputResponseTypeText'
) -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(
self, other: 'DialogNodeOutputGenericDialogNodeOutputResponseTypeText'
) -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs] class SelectionPolicyEnum(str, Enum):
"""
How a response is selected from the list, if more than one response is specified.
"""
SEQUENTIAL = 'sequential'
RANDOM = 'random'
MULTILINE = 'multiline'
[docs]class DialogNodeOutputGenericDialogNodeOutputResponseTypeUserDefined(
DialogNodeOutputGeneric):
"""
DialogNodeOutputGenericDialogNodeOutputResponseTypeUserDefined.
:attr str response_type: The type of response returned by the dialog node. The
specified response type must be supported by the client application or channel.
:attr dict user_defined: An object containing any properties for the
user-defined response type. The total size of this object cannot exceed 5000
bytes.
:attr List[ResponseGenericChannel] channels: (optional) An array of objects
specifying channels for which the response is intended.
"""
def __init__(self,
response_type: str,
user_defined: dict,
*,
channels: List['ResponseGenericChannel'] = None) -> None:
"""
Initialize a DialogNodeOutputGenericDialogNodeOutputResponseTypeUserDefined object.
:param str response_type: The type of response returned by the dialog node.
The specified response type must be supported by the client application or
channel.
:param dict user_defined: An object containing any properties for the
user-defined response type. The total size of this object cannot exceed
5000 bytes.
:param List[ResponseGenericChannel] channels: (optional) An array of
objects specifying channels for which the response is intended.
"""
# pylint: disable=super-init-not-called
self.response_type = response_type
self.user_defined = user_defined
self.channels = channels
[docs] @classmethod
def from_dict(
cls, _dict: Dict
) -> 'DialogNodeOutputGenericDialogNodeOutputResponseTypeUserDefined':
"""Initialize a DialogNodeOutputGenericDialogNodeOutputResponseTypeUserDefined object from a json dictionary."""
args = {}
if 'response_type' in _dict:
args['response_type'] = _dict.get('response_type')
else:
raise ValueError(
'Required property \'response_type\' not present in DialogNodeOutputGenericDialogNodeOutputResponseTypeUserDefined JSON'
)
if 'user_defined' in _dict:
args['user_defined'] = _dict.get('user_defined')
else:
raise ValueError(
'Required property \'user_defined\' not present in DialogNodeOutputGenericDialogNodeOutputResponseTypeUserDefined JSON'
)
if 'channels' in _dict:
args['channels'] = [
ResponseGenericChannel.from_dict(x)
for x in _dict.get('channels')
]
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a DialogNodeOutputGenericDialogNodeOutputResponseTypeUserDefined object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'response_type') and self.response_type is not None:
_dict['response_type'] = self.response_type
if hasattr(self, 'user_defined') and self.user_defined is not None:
_dict['user_defined'] = self.user_defined
if hasattr(self, 'channels') and self.channels is not None:
_dict['channels'] = [x.to_dict() for x in self.channels]
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this DialogNodeOutputGenericDialogNodeOutputResponseTypeUserDefined object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(
self,
other: 'DialogNodeOutputGenericDialogNodeOutputResponseTypeUserDefined'
) -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(
self,
other: 'DialogNodeOutputGenericDialogNodeOutputResponseTypeUserDefined'
) -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]class RuntimeResponseGenericRuntimeResponseTypeChannelTransfer(
RuntimeResponseGeneric):
"""
RuntimeResponseGenericRuntimeResponseTypeChannelTransfer.
:attr str response_type: The type of response returned by the dialog node. The
specified response type must be supported by the client application or channel.
:attr str message_to_user: The message to display to the user when initiating a
channel transfer.
:attr ChannelTransferInfo transfer_info: Information used by an integration to
transfer the conversation to a different channel.
:attr List[ResponseGenericChannel] channels: (optional) An array of objects
specifying channels for which the response is intended. If **channels** is
present, the response is intended only for a built-in integration and should not
be handled by an API client.
"""
def __init__(self,
response_type: str,
message_to_user: str,
transfer_info: 'ChannelTransferInfo',
*,
channels: List['ResponseGenericChannel'] = None) -> None:
"""
Initialize a RuntimeResponseGenericRuntimeResponseTypeChannelTransfer object.
:param str response_type: The type of response returned by the dialog node.
The specified response type must be supported by the client application or
channel.
:param str message_to_user: The message to display to the user when
initiating a channel transfer.
:param ChannelTransferInfo transfer_info: Information used by an
integration to transfer the conversation to a different channel.
:param List[ResponseGenericChannel] channels: (optional) An array of
objects specifying channels for which the response is intended. If
**channels** is present, the response is intended only for a built-in
integration and should not be handled by an API client.
"""
# pylint: disable=super-init-not-called
self.response_type = response_type
self.message_to_user = message_to_user
self.transfer_info = transfer_info
self.channels = channels
[docs] @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)
[docs] 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
[docs]class RuntimeResponseGenericRuntimeResponseTypeConnectToAgent(
RuntimeResponseGeneric):
"""
RuntimeResponseGenericRuntimeResponseTypeConnectToAgent.
:attr str response_type: The type of response returned by the dialog node. The
specified response type must be supported by the client application or channel.
:attr str message_to_human_agent: (optional) A message to be sent to the human
agent who will be taking over the conversation.
:attr AgentAvailabilityMessage agent_available: (optional) An optional message
to be displayed to the user to indicate that the conversation will be
transferred to the next available agent.
:attr AgentAvailabilityMessage agent_unavailable: (optional) An optional message
to be displayed to the user to indicate that no online agent is available to
take over the conversation.
:attr DialogNodeOutputConnectToAgentTransferInfo transfer_info: (optional)
Routing or other contextual information to be used by target service desk
systems.
:attr str topic: (optional) A label identifying the topic of the conversation,
derived from the **title** property of the relevant node or the **topic**
property of the dialog node response.
:attr str dialog_node: (optional) The unique ID of the dialog node that the
**topic** property is taken from. The **topic** property is populated using the
value of the dialog node's **title** property.
:attr List[ResponseGenericChannel] channels: (optional) An array of objects
specifying channels for which the response is intended. If **channels** is
present, the response is intended for a built-in integration and should not be
handled by an API client.
"""
def __init__(
self,
response_type: str,
*,
message_to_human_agent: str = None,
agent_available: 'AgentAvailabilityMessage' = None,
agent_unavailable: 'AgentAvailabilityMessage' = None,
transfer_info: 'DialogNodeOutputConnectToAgentTransferInfo' = None,
topic: str = None,
dialog_node: str = None,
channels: List['ResponseGenericChannel'] = None) -> None:
"""
Initialize a RuntimeResponseGenericRuntimeResponseTypeConnectToAgent object.
:param str response_type: The type of response returned by the dialog node.
The specified response type must be supported by the client application or
channel.
:param str message_to_human_agent: (optional) A message to be sent to the
human agent who will be taking over the conversation.
:param AgentAvailabilityMessage agent_available: (optional) An optional
message to be displayed to the user to indicate that the conversation will
be transferred to the next available agent.
:param AgentAvailabilityMessage agent_unavailable: (optional) An optional
message to be displayed to the user to indicate that no online agent is
available to take over the conversation.
:param DialogNodeOutputConnectToAgentTransferInfo transfer_info: (optional)
Routing or other contextual information to be used by target service desk
systems.
:param str topic: (optional) A label identifying the topic of the
conversation, derived from the **title** property of the relevant node or
the **topic** property of the dialog node response.
:param str dialog_node: (optional) The unique ID of the dialog node that
the **topic** property is taken from. The **topic** property is populated
using the value of the dialog node's **title** property.
:param List[ResponseGenericChannel] channels: (optional) An array of
objects specifying channels for which the response is intended. If
**channels** is present, the response is intended for a built-in
integration and should not be handled by an API client.
"""
# pylint: disable=super-init-not-called
self.response_type = response_type
self.message_to_human_agent = message_to_human_agent
self.agent_available = agent_available
self.agent_unavailable = agent_unavailable
self.transfer_info = transfer_info
self.topic = topic
self.dialog_node = dialog_node
self.channels = channels
[docs] @classmethod
def from_dict(
cls, _dict: Dict
) -> 'RuntimeResponseGenericRuntimeResponseTypeConnectToAgent':
"""Initialize a RuntimeResponseGenericRuntimeResponseTypeConnectToAgent object from a json dictionary."""
args = {}
if 'response_type' in _dict:
args['response_type'] = _dict.get('response_type')
else:
raise ValueError(
'Required property \'response_type\' not present in RuntimeResponseGenericRuntimeResponseTypeConnectToAgent JSON'
)
if 'message_to_human_agent' in _dict:
args['message_to_human_agent'] = _dict.get('message_to_human_agent')
if 'agent_available' in _dict:
args['agent_available'] = AgentAvailabilityMessage.from_dict(
_dict.get('agent_available'))
if 'agent_unavailable' in _dict:
args['agent_unavailable'] = AgentAvailabilityMessage.from_dict(
_dict.get('agent_unavailable'))
if 'transfer_info' in _dict:
args[
'transfer_info'] = DialogNodeOutputConnectToAgentTransferInfo.from_dict(
_dict.get('transfer_info'))
if 'topic' in _dict:
args['topic'] = _dict.get('topic')
if 'dialog_node' in _dict:
args['dialog_node'] = _dict.get('dialog_node')
if 'channels' in _dict:
args['channels'] = [
ResponseGenericChannel.from_dict(x)
for x in _dict.get('channels')
]
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a RuntimeResponseGenericRuntimeResponseTypeConnectToAgent object from a json dictionary."""
return cls.from_dict(_dict)
[docs] def to_dict(self) -> Dict:
"""Return a json dictionary representing this model."""
_dict = {}
if hasattr(self, 'response_type') and self.response_type is not None:
_dict['response_type'] = self.response_type
if hasattr(self, 'message_to_human_agent'
) and self.message_to_human_agent is not None:
_dict['message_to_human_agent'] = self.message_to_human_agent
if hasattr(self,
'agent_available') and self.agent_available is not None:
_dict['agent_available'] = self.agent_available.to_dict()
if hasattr(self,
'agent_unavailable') and self.agent_unavailable is not None:
_dict['agent_unavailable'] = self.agent_unavailable.to_dict()
if hasattr(self, 'transfer_info') and self.transfer_info is not None:
_dict['transfer_info'] = self.transfer_info.to_dict()
if hasattr(self, 'topic') and self.topic is not None:
_dict['topic'] = self.topic
if hasattr(self, 'dialog_node') and self.dialog_node is not None:
_dict['dialog_node'] = self.dialog_node
if hasattr(self, 'channels') and self.channels is not None:
_dict['channels'] = [x.to_dict() for x in self.channels]
return _dict
def _to_dict(self):
"""Return a json dictionary representing this model."""
return self.to_dict()
def __str__(self) -> str:
"""Return a `str` version of this RuntimeResponseGenericRuntimeResponseTypeConnectToAgent object."""
return json.dumps(self.to_dict(), indent=2)
def __eq__(
self, other: 'RuntimeResponseGenericRuntimeResponseTypeConnectToAgent'
) -> bool:
"""Return `true` when self and other are equal, false otherwise."""
if not isinstance(other, self.__class__):
return False
return self.__dict__ == other.__dict__
def __ne__(
self, other: 'RuntimeResponseGenericRuntimeResponseTypeConnectToAgent'
) -> bool:
"""Return `true` when self and other are not equal, false otherwise."""
return not self == other
[docs]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 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 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,
channels: List['ResponseGenericChannel'] = 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 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 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.channels = channels
[docs] @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')
]
return cls(**args)
@classmethod
def _from_dict(cls, _dict):
"""Initialize a RuntimeResponseGenericRuntimeResponseTypeImage object from a json dictionary."""
return cls.from_dict(_dict)
[docs] 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]
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
[docs]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
[docs] @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)
[docs] 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
[docs] class PreferenceEnum(str, Enum):
"""
The preferred type of control to display.
"""
DROPDOWN = 'dropdown'
BUTTON = 'button'
[docs]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
[docs] @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)
[docs] 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
[docs]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
[docs] @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)
[docs] 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
[docs]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
[docs] @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)
[docs] 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
[docs]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
[docs] @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)
[docs] 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