8000 QnA Parity: Adding Active Learning Feature (#264) · sherlock666/botbuilder-python@1f541e4 · GitHub
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QnA Parity: Adding Active Learning Feature (microsoft#264)
* Initial active learning commit w/FeedbackRecord model * port FeedbackRecords & added param types to FeedbackRecord * added all qna models * begin porting HttpRequestUtils * ported GenerateAnswerUtils * used black to auto format qna library * ported TrainUtils * TrainUtil now calls Train API in call_train() * black to format all libraries * ported ActiveLearningUtils class * Ported all QnAMaker methods; reorganized folder structure according to dotnet QnA update * resolved conflicts AND SAVED CHANGES this time * merge conflicts 3 * conflicts 4 * fixed linting errors * black to format * made QnA classes serializable using msrest * changed class name to GenerateAnswerRequestBody to be consistent with TrainRequestBody * updated GenerateAnswerRequestBody's to document params correctly * added call train api test case * completed tests for low score variation * removed context; changed matched kb ans to check id; removed legacy support * removed legacy tests * removed TODO comment from qna __init__ file
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‎libraries/botbuilder-ai/botbuilder/ai/qna/__init__.py

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# Copyright (c) Microsoft Corporation. All rights reserved.
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# Licensed under the MIT License.
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from .metadata import Metadata
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from .query_result import QueryResult
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from .qnamaker import QnAMaker
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from .qnamaker_endpoint import QnAMakerEndpoint
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from .qnamaker_options import QnAMakerOptions
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from .qnamaker_telemetry_client import QnAMakerTelemetryClient
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from .qna_telemetry_constants import QnATelemetryConstants
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from .qnamaker_trace_info import QnAMakerTraceInfo
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from .utils import (
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ActiveLearningUtils,
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GenerateAnswerUtils,
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HttpRequestUtils,
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QnATelemetryConstants,
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)
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from .models import (
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FeedbackRecord,
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FeedbackRecords,
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Metadata,
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QnAMakerTraceInfo,
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QueryResult,
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QueryResults,
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)
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__all__ = [
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"ActiveLearningUtils",
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"FeedbackRecord",
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"FeedbackRecords",
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"GenerateAnswerUtils",
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"HttpRequestUtils",
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"Metadata",
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"QueryResult",
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"QueryResults",
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"QnAMaker",
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"QnAMakerEndpoint",
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"QnAMakerOptions",

‎libraries/botbuilder-ai/botbuilder/ai/qna/metadata.py

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This file was deleted.

‎libraries/botbuilder-ai/botbuilder/ai/qna/models/__init__.py

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# coding=utf-8
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# --------------------------------------------------------------------------
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# Copyright (c) Microsoft Corporation. All rights reserved.
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# Licensed under the MIT License. See License.txt in the project root for
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# license information.
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# --------------------------------------------------------------------------
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from .feedback_record import FeedbackRecord
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from .feedback_records import FeedbackRecords
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from .generate_answer_request_body import GenerateAnswerRequestBody
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from .metadata import Metadata
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from .qnamaker_trace_info import QnAMakerTraceInfo
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from .query_result import QueryResult
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from .query_results import QueryResults
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from .train_request_body import TrainRequestBody
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__all__ = [
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"FeedbackRecord",
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"FeedbackRecords",
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"GenerateAnswerRequestBody",
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"Metadata",
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"QnAMakerTraceInfo",
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"QueryResult",
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"QueryResults",
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"TrainRequestBody",
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]

‎libraries/botbuilder-ai/botbuilder/ai/qna/models/feedback_record.py

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# Copyright (c) Microsoft Corporation. All rights reserved.
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# Licensed under the MIT License.
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from msrest.serialization import Model
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class FeedbackRecord(Model):
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""" Active learning feedback record. """
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_attribute_map = {
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"user_id": {"key": "userId", "type": "str"},
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"user_question": {"key": "userQuestion", "type": "str"},
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"qna_id": {"key": "qnaId", "type": "int"},
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}
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def __init__(self, user_id: str, user_question: str, qna_id: int, **kwargs):
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"""
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Parameters:
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-----------
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user_id: ID of the user.
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user_question: User question.
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qna_id: QnA ID.
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"""
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super().__init__(**kwargs)
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self.user_id = user_id
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self.user_question = user_question
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self.qna_id = qna_id

‎libraries/botbuilder-ai/botbuilder/ai/qna/models/feedback_records.py

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# Copyright (c) Microsoft Corporation. All rights reserved.
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# Licensed under the MIT License.
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from typing import List
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from msrest.serialization import Model
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from .feedback_record import FeedbackRecord
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class FeedbackRecords(Model):
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""" Active learning feedback records. """
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_attribute_map = {"records": {"key": "records", "type": "[FeedbackRecord]"}}
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def __init__(self, records: List[FeedbackRecord], **kwargs):
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"""
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Parameter(s):
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-------------
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records: List of feedback records.
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"""
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super().__init__(**kwargs)
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self.records = records

‎libraries/botbuilder-ai/botbuilder/ai/qna/models/generate_answer_request_body.py

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# Copyright (c) Microsoft Corporation. All rights reserved.
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# Licensed under the MIT License.
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from typing import List
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from msrest.serialization import Model
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from .metadata import Metadata
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class GenerateAnswerRequestBody(Model):
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""" Question used as the payload body for QnA Maker's Generate Answer API. """
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_attribute_map = {
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"question": {"key": "question", "type": "str"},
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"top": {"key": "top", "type": "int"},
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"score_threshold": {"key": "scoreThreshold", "type": "float"},
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"strict_filters": {"key": "strictFilters", "type": "[Metadata]"},
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}
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def __init__(
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self,
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question: str,
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top: int,
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score_threshold: float,
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strict_filters: List[Metadata],
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**kwargs
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):
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"""
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Parameters:
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-----------
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question: The user question to query against the knowledge base.
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top: Max number of answers to be returned for the question.
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score_threshold: Threshold for answers returned based on score.
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strict_filters: Find only answers that contain these metadata.
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"""
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super().__init__(**kwargs)
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self.question = question
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self.top = top
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self.score_threshold = score_threshold
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self.strict_filters = strict_filters

‎libraries/botbuilder-ai/botbuilder/ai/qna/models/metadata.py

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# Copyright (c) Microsoft Corporation. All rights reserved.
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# Licensed under the MIT License.
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from msrest.serialization import Model
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class Metadata(Model):
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""" Metadata associated with the answer. """
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_attribute_map = {
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"name": {"key": "name", "type": "str"},
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"value": {"key": "value", "type": "str"},
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}
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def __init__(self, name: str, value: str, **kwargs):
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"""
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Parameters:
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-----------
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name: Metadata name. Max length: 100.
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value: Metadata value. Max length: 100.
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"""
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super().__init__(**kwargs)
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self.name = name
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self.value = value

‎libraries/botbuilder-ai/botbuilder/ai/qna/models/qnamaker_trace_info.py

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# Copyright (c) Microsoft Corporation. All rights reserved.
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# Licensed under the MIT License.
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from typing import List
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from botbuilder.schema import Activity
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from .metadata import Metadata
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from .query_result import QueryResult
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class QnAMakerTraceInfo:
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""" Represents all the trice info that we collect from the QnAMaker Middleware. """
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def __init__(
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self,
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message: Activity,
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query_results: List[QueryResult],
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knowledge_base_id: str,
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score_threshold: float,
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top: int,
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strict_filters: List[Metadata],
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):
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"""
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Parameters:
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-----------
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message: Message which instigated the query to QnA Maker.
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query_results: Results that QnA Maker returned.
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knowledge_base_id: ID of the knowledge base that is being queried.
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score_threshold: The minimum score threshold, used to filter returned results.
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top: Number of ranked results that are asked to be returned.
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strict_filters: Filters used on query.
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"""
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self.message = message
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self.query_results = query_results
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self.knowledge_base_id = knowledge_base_id
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self.score_threshold = score_threshold
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self.top = top
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self.strict_filters = strict_filters

‎libraries/botbuilder-ai/botbuilder/ai/qna/models/query_result.py

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# Copyright (c) Microsoft Corporation. All rights reserved.
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# Licensed under the MIT License.
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from typing import List
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from .metadata import Metadata
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class QueryResult:
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""" Represents an individual result from a knowledge base query. """
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def __init__(
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self,
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questions: List[str],
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answer: str,
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score: float,
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metadata: object = None,
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source: str = None,
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id: int = None, # pylint: disable=invalid-name
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):
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"""
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Parameters:
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-----------
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questions: The list of questions indexed in the QnA Service for the given answer (if any).
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answer: Answer from the knowledge base.
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score: Confidence on a scale from 0.0 to 1.0 that the answer matches the user's intent.
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metadata: Metadata associated with the answer (if any).
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source: The source from which the QnA was extracted (if any).
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id: The index of the answer in the knowledge base. V3 uses 'qnaId', V4 uses 'id' (if any).
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"""
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self.questions = questions
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self.answer = answer
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self.score = score
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self.metadata = list(map(lambda meta: Metadata(**meta), metadata))
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self.source = source
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self.id = id # pylint: disable=invalid-name

‎libraries/botbuilder-ai/botbuilder/ai/qna/models/query_results.py

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# Copyright (c) Microsoft Corporation. All rights reserved.
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# Licensed under the MIT License.
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from typing import List
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from .query_result import QueryResult
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class QueryResults:
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""" Contains answers for a user query. """
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def __init__(self, answers: List[QueryResult]):
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"""
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Parameters:
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-----------
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answers: The answers for a user query.
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"""
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self.answers = answers

‎libraries/botbuilder-ai/botbuilder/ai/qna/models/train_request_body.py

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# Copyright (c) Microsoft Corporation. All rights reserved.
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# Licensed under the MIT License.
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from typing import List
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from msrest.serialization import Model
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from .feedback_record import FeedbackRecord
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class TrainRequestBody(Model):
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""" Class the models the request body that is sent as feedback to the Train API. """
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_attribute_map = {
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"feedback_records": {"key": "feedbackRecords", "type": "[FeedbackRecord]"}
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}
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def __init__(self, feedback_records: List[FeedbackRecord], **kwargs):
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"""
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Parameters:
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-----------
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feedback_records: List of feedback records.
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"""
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super().__init__(**kwargs)
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self.feedback_records = feedback_records

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