Code Gen for QNA maker

sdk/cognitiveservices/azure-cognitiveservices-knowledge-qnamaker/azure/cognitiveservices/knowledge/qnamaker/authoring/models/__init__.py

@@ -47,6 +47,18 @@
     from .alterations_dto_py3 import AlterationsDTO
     from .word_alterations_dto_py3 import WordAlterationsDTO
     from .endpoint_keys_dto_py3 import EndpointKeysDTO
+    from .query_dto_context_py3 import QueryDTOContext
+    from .query_dto_answer_span_request_py3 import QueryDTOAnswerSpanRequest
+    from .query_dto_py3 import QueryDTO
+    from .query_context_dto_py3 import QueryContextDTO
+    from .qn_asearch_result_context_py3 import QnASearchResultContext
+    from .qn_asearch_result_answer_span_py3 import QnASearchResultAnswerSpan
+    from .qn_asearch_result_py3 import QnASearchResult
+    from .qn_asearch_result_list_py3 import QnASearchResultList
+    from .feedback_record_dto_py3 import FeedbackRecordDTO
+    from .feedback_records_dto_py3 import FeedbackRecordsDTO
+    from .answer_span_request_dto_py3 import AnswerSpanRequestDTO
+    from .answer_span_response_dto_py3 import AnswerSpanResponseDTO
 except (SyntaxError, ImportError):
     from .update_kb_operation_dto_add import UpdateKbOperationDTOAdd
     from .update_kb_operation_dto_delete import UpdateKbOperationDTODelete
@@ -85,9 +97,22 @@
     from .alterations_dto import AlterationsDTO
     from .word_alterations_dto import WordAlterationsDTO
     from .endpoint_keys_dto import EndpointKeysDTO
+    from .query_dto_context import QueryDTOContext
+    from .query_dto_answer_span_request import QueryDTOAnswerSpanRequest
+    from .query_dto import QueryDTO
+    from .query_context_dto import QueryContextDTO
+    from .qn_asearch_result_context import QnASearchResultContext
+    from .qn_asearch_result_answer_span import QnASearchResultAnswerSpan
+    from .qn_asearch_result import QnASearchResult
+    from .qn_asearch_result_list import QnASearchResultList
+    from .feedback_record_dto import FeedbackRecordDTO
+    from .feedback_records_dto import FeedbackRecordsDTO
+    from .answer_span_request_dto import AnswerSpanRequestDTO
+    from .answer_span_response_dto import AnswerSpanResponseDTO
 from .qn_amaker_client_enums import (
     ErrorCodeType,
     OperationStateType,
+    StrictFiltersCompoundOperationType,
     EnvironmentType,
 )
 
@@ -129,7 +154,20 @@
     'AlterationsDTO',
     'WordAlterationsDTO',
     'EndpointKeysDTO',
+    'QueryDTOContext',
+    'QueryDTOAnswerSpanRequest',
+    'QueryDTO',
+    'QueryContextDTO',
+    'QnASearchResultContext',
+    'QnASearchResultAnswerSpan',
+    'QnASearchResult',
+    'QnASearchResultList',
+    'FeedbackRecordDTO',
+    'FeedbackRecordsDTO',
+    'AnswerSpanRequestDTO',
+    'AnswerSpanResponseDTO',
     'ErrorCodeType',
     'OperationStateType',
+    'StrictFiltersCompoundOperationType',
     'EnvironmentType',
 ]

sdk/cognitiveservices/azure-cognitiveservices-knowledge-qnamaker/azure/cognitiveservices/knowledge/qnamaker/authoring/models/answer_span_request_dto.py

@@ -0,0 +1,42 @@
+# coding=utf-8
+# --------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for
+# license information.
+#
+# Code generated by Microsoft (R) AutoRest Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is
+# regenerated.
+# --------------------------------------------------------------------------
+
+from msrest.serialization import Model
+
+
+class AnswerSpanRequestDTO(Model):
+    """To configure Answer span prediction feature.
+
+    :param enable: Enable or Disable Answer Span prediction.
+    :type enable: bool
+    :param score_threshold: Minimum threshold score required to include an
+     answer span.
+    :type score_threshold: float
+    :param top_answers_with_span: Number of Top answers to be considered for
+     span prediction.
+    :type top_answers_with_span: int
+    """
+
+    _validation = {
+        'top_answers_with_span': {'maximum': 10, 'minimum': 1},
+    }
+
+    _attribute_map = {
+        'enable': {'key': 'enable', 'type': 'bool'},
+        'score_threshold': {'key': 'scoreThreshold', 'type': 'float'},
+        'top_answers_with_span': {'key': 'topAnswersWithSpan', 'type': 'int'},
+    }
+
+    def __init__(self, **kwargs):
+        super(AnswerSpanRequestDTO, self).__init__(**kwargs)
+        self.enable = kwargs.get('enable', None)
+        self.score_threshold = kwargs.get('score_threshold', None)
+        self.top_answers_with_span = kwargs.get('top_answers_with_span', None)

sdk/cognitiveservices/azure-cognitiveservices-knowledge-qnamaker/azure/cognitiveservices/knowledge/qnamaker/authoring/models/answer_span_request_dto_py3.py

@@ -0,0 +1,42 @@
+# coding=utf-8
+# --------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for
+# license information.
+#
+# Code generated by Microsoft (R) AutoRest Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is
+# regenerated.
+# --------------------------------------------------------------------------
+
+from msrest.serialization import Model
+
+
+class AnswerSpanRequestDTO(Model):
+    """To configure Answer span prediction feature.
+
+    :param enable: Enable or Disable Answer Span prediction.
+    :type enable: bool
+    :param score_threshold: Minimum threshold score required to include an
+     answer span.
+    :type score_threshold: float
+    :param top_answers_with_span: Number of Top answers to be considered for
+     span prediction.
+    :type top_answers_with_span: int
+    """
+
+    _validation = {
+        'top_answers_with_span': {'maximum': 10, 'minimum': 1},
+    }
+
+    _attribute_map = {
+        'enable': {'key': 'enable', 'type': 'bool'},
+        'score_threshold': {'key': 'scoreThreshold', 'type': 'float'},
+        'top_answers_with_span': {'key': 'topAnswersWithSpan', 'type': 'int'},
+    }
+
+    def __init__(self, *, enable: bool=None, score_threshold: float=None, top_answers_with_span: int=None, **kwargs) -> None:
+        super(AnswerSpanRequestDTO, self).__init__(**kwargs)
+        self.enable = enable
+        self.score_threshold = score_threshold
+        self.top_answers_with_span = top_answers_with_span

sdk/cognitiveservices/azure-cognitiveservices-knowledge-qnamaker/azure/cognitiveservices/knowledge/qnamaker/authoring/models/answer_span_response_dto.py

@@ -0,0 +1,40 @@
+# coding=utf-8
+# --------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for
+# license information.
+#
+# Code generated by Microsoft (R) AutoRest Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is
+# regenerated.
+# --------------------------------------------------------------------------
+
+from msrest.serialization import Model
+
+
+class AnswerSpanResponseDTO(Model):
+    """Answer span object of QnA.
+
+    :param text: Predicted text of answer span.
+    :type text: str
+    :param score: Predicted score of answer span.
+    :type score: float
+    :param start_index: Start index of answer span in answer.
+    :type start_index: int
+    :param end_index: End index of answer span in answer.
+    :type end_index: int
+    """
+
+    _attribute_map = {
+        'text': {'key': 'text', 'type': 'str'},
+        'score': {'key': 'score', 'type': 'float'},
+        'start_index': {'key': 'startIndex', 'type': 'int'},
+        'end_index': {'key': 'endIndex', 'type': 'int'},
+    }
+
+    def __init__(self, **kwargs):
+        super(AnswerSpanResponseDTO, self).__init__(**kwargs)
+        self.text = kwargs.get('text', None)
+        self.score = kwargs.get('score', None)
+        self.start_index = kwargs.get('start_index', None)
+        self.end_index = kwargs.get('end_index', None)

sdk/cognitiveservices/azure-cognitiveservices-knowledge-qnamaker/azure/cognitiveservices/knowledge/qnamaker/authoring/models/answer_span_response_dto_py3.py

@@ -0,0 +1,40 @@
+# coding=utf-8
+# --------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for
+# license information.
+#
+# Code generated by Microsoft (R) AutoRest Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is
+# regenerated.
+# --------------------------------------------------------------------------
+
+from msrest.serialization import Model
+
+
+class AnswerSpanResponseDTO(Model):
+    """Answer span object of QnA.
+
+    :param text: Predicted text of answer span.
+    :type text: str
+    :param score: Predicted score of answer span.
+    :type score: float
+    :param start_index: Start index of answer span in answer.
+    :type start_index: int
+    :param end_index: End index of answer span in answer.
+    :type end_index: int
+    """
+
+    _attribute_map = {
+        'text': {'key': 'text', 'type': 'str'},
+        'score': {'key': 'score', 'type': 'float'},
+        'start_index': {'key': 'startIndex', 'type': 'int'},
+        'end_index': {'key': 'endIndex', 'type': 'int'},
+    }
+
+    def __init__(self, *, text: str=None, score: float=None, start_index: int=None, end_index: int=None, **kwargs) -> None:
+        super(AnswerSpanResponseDTO, self).__init__(**kwargs)
+        self.text = text
+        self.score = score
+        self.start_index = start_index
+        self.end_index = end_index

sdk/cognitiveservices/azure-cognitiveservices-knowledge-qnamaker/azure/cognitiveservices/knowledge/qnamaker/authoring/models/create_kb_dto.py

@@ -37,14 +37,24 @@ class CreateKbDTO(Model):
      a hierarchy. Required when EnableHierarchicalExtraction field is set to
      True.
     :type default_answer_used_for_extraction: str
-    :param language: Language of the knowledgebase.
+    :param language: Language of the knowledgebase. Please find the list of
+     supported languages <a
+     href="https://aka.ms/qnamaker-languages#languages-supported"
+     target="_blank">here</a>.
     :type language: str
+    :param enable_multiple_languages: Set to true to enable creating KBs in
+     different languages for the same resource.
+    :type enable_multiple_languages: bool
+    :param default_answer: Default answer sent to user if no good match is
+     found in the KB.
+    :type default_answer: str
     """
 
     _validation = {
         'name': {'required': True, 'max_length': 100, 'min_length': 1},
         'default_answer_used_for_extraction': {'max_length': 300, 'min_length': 1},
         'language': {'max_length': 100, 'min_length': 1},
+        'default_answer': {'max_length': 300, 'min_length': 1},
     }
 
     _attribute_map = {
@@ -55,6 +65,8 @@ class CreateKbDTO(Model):
         'enable_hierarchical_extraction': {'key': 'enableHierarchicalExtraction', 'type': 'bool'},
         'default_answer_used_for_extraction': {'key': 'defaultAnswerUsedForExtraction', 'type': 'str'},
         'language': {'key': 'language', 'type': 'str'},
+        'enable_multiple_languages': {'key': 'enableMultipleLanguages', 'type': 'bool'},
+        'default_answer': {'key': 'defaultAnswer', 'type': 'str'},
     }
 
     def __init__(self, **kwargs):
@@ -66,3 +78,5 @@ def __init__(self, **kwargs):
         self.enable_hierarchical_extraction = kwargs.get('enable_hierarchical_extraction', None)
         self.default_answer_used_for_extraction = kwargs.get('default_answer_used_for_extraction', None)
         self.language = kwargs.get('language', None)
+        self.enable_multiple_languages = kwargs.get('enable_multiple_languages', None)
+        self.default_answer = kwargs.get('default_answer', None)

sdk/cognitiveservices/azure-cognitiveservices-knowledge-qnamaker/azure/cognitiveservices/knowledge/qnamaker/authoring/models/create_kb_dto_py3.py

@@ -37,14 +37,24 @@ class CreateKbDTO(Model):
      a hierarchy. Required when EnableHierarchicalExtraction field is set to
      True.
     :type default_answer_used_for_extraction: str
-    :param language: Language of the knowledgebase.
+    :param language: Language of the knowledgebase. Please find the list of
+     supported languages <a
+     href="https://aka.ms/qnamaker-languages#languages-supported"
+     target="_blank">here</a>.
     :type language: str
+    :param enable_multiple_languages: Set to true to enable creating KBs in
+     different languages for the same resource.
+    :type enable_multiple_languages: bool
+    :param default_answer: Default answer sent to user if no good match is
+     found in the KB.
+    :type default_answer: str
     """
 
     _validation = {
         'name': {'required': True, 'max_length': 100, 'min_length': 1},
         'default_answer_used_for_extraction': {'max_length': 300, 'min_length': 1},
         'language': {'max_length': 100, 'min_length': 1},
+        'default_answer': {'max_length': 300, 'min_length': 1},
     }
 
     _attribute_map = {
@@ -55,9 +65,11 @@ class CreateKbDTO(Model):
         'enable_hierarchical_extraction': {'key': 'enableHierarchicalExtraction', 'type': 'bool'},
         'default_answer_used_for_extraction': {'key': 'defaultAnswerUsedForExtraction', 'type': 'str'},
         'language': {'key': 'language', 'type': 'str'},
+        'enable_multiple_languages': {'key': 'enableMultipleLanguages', 'type': 'bool'},
+        'default_answer': {'key': 'defaultAnswer', 'type': 'str'},
     }
 
-    def __init__(self, *, name: str, qna_list=None, urls=None, files=None, enable_hierarchical_extraction: bool=None, default_answer_used_for_extraction: str=None, language: str=None, **kwargs) -> None:
+    def __init__(self, *, name: str, qna_list=None, urls=None, files=None, enable_hierarchical_extraction: bool=None, default_answer_used_for_extraction: str=None, language: str=None, enable_multiple_languages: bool=None, default_answer: str=None, **kwargs) -> None:
         super(CreateKbDTO, self).__init__(**kwargs)
         self.name = name
         self.qna_list = qna_list
@@ -66,3 +78,5 @@ def __init__(self, *, name: str, qna_list=None, urls=None, files=None, enable_hi
         self.enable_hierarchical_extraction = enable_hierarchical_extraction
         self.default_answer_used_for_extraction = default_answer_used_for_extraction
         self.language = language
+        self.enable_multiple_languages = enable_multiple_languages
+        self.default_answer = default_answer

sdk/cognitiveservices/azure-cognitiveservices-knowledge-qnamaker/azure/cognitiveservices/knowledge/qnamaker/authoring/models/feedback_record_dto.py

@@ -0,0 +1,41 @@
+# coding=utf-8
+# --------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for
+# license information.
+#
+# Code generated by Microsoft (R) AutoRest Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is
+# regenerated.
+# --------------------------------------------------------------------------
+
+from msrest.serialization import Model
+
+
+class FeedbackRecordDTO(Model):
+    """Active learning feedback record.
+
+    :param user_id: Unique identifier for the user.
+    :type user_id: str
+    :param user_question: The suggested question being provided as feedback.
+    :type user_question: str
+    :param qna_id: The qnaId for which the suggested question is provided as
+     feedback.
+    :type qna_id: int
+    """
+
+    _validation = {
+        'user_question': {'max_length': 1000},
+    }
+
+    _attribute_map = {
+        'user_id': {'key': 'userId', 'type': 'str'},
+        'user_question': {'key': 'userQuestion', 'type': 'str'},
+        'qna_id': {'key': 'qnaId', 'type': 'int'},
+    }
+
+    def __init__(self, **kwargs):
+        super(FeedbackRecordDTO, self).__init__(**kwargs)
+        self.user_id = kwargs.get('user_id', None)
+        self.user_question = kwargs.get('user_question', None)
+        self.qna_id = kwargs.get('qna_id', None)