QnA Parity: Adding Active Learning Feature (#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

Author: Zerryth

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

@@ -1,18 +1,35 @@
 # Copyright (c) Microsoft Corporation. All rights reserved.
 # Licensed under the MIT License.
 
-from .metadata import Metadata
-from .query_result import QueryResult
 from .qnamaker import QnAMaker
 from .qnamaker_endpoint import QnAMakerEndpoint
 from .qnamaker_options import QnAMakerOptions
 from .qnamaker_telemetry_client import QnAMakerTelemetryClient
-from .qna_telemetry_constants import QnATelemetryConstants
-from .qnamaker_trace_info import QnAMakerTraceInfo
+from .utils import (
+    ActiveLearningUtils,
+    GenerateAnswerUtils,
+    HttpRequestUtils,
+    QnATelemetryConstants,
+)
+
+from .models import (
+    FeedbackRecord,
+    FeedbackRecords,
+    Metadata,
+    QnAMakerTraceInfo,
+    QueryResult,
+    QueryResults,
+)
 
 __all__ = [
+    "ActiveLearningUtils",
+    "FeedbackRecord",
+    "FeedbackRecords",
+    "GenerateAnswerUtils",
+    "HttpRequestUtils",
     "Metadata",
     "QueryResult",
+    "QueryResults",
     "QnAMaker",
     "QnAMakerEndpoint",
     "QnAMakerOptions",

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

@@ -0,0 +1,26 @@
+# 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.
+# --------------------------------------------------------------------------
+
+from .feedback_record import FeedbackRecord
+from .feedback_records import FeedbackRecords
+from .generate_answer_request_body import GenerateAnswerRequestBody
+from .metadata import Metadata
+from .qnamaker_trace_info import QnAMakerTraceInfo
+from .query_result import QueryResult
+from .query_results import QueryResults
+from .train_request_body import TrainRequestBody
+
+__all__ = [
+    "FeedbackRecord",
+    "FeedbackRecords",
+    "GenerateAnswerRequestBody",
+    "Metadata",
+    "QnAMakerTraceInfo",
+    "QueryResult",
+    "QueryResults",
+    "TrainRequestBody",
+]

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

@@ -0,0 +1,32 @@
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License.
+
+from msrest.serialization import Model
+
+
+class FeedbackRecord(Model):
+    """ Active learning feedback record. """
+
+    _attribute_map = {
+        "user_id": {"key": "userId", "type": "str"},
+        "user_question": {"key": "userQuestion", "type": "str"},
+        "qna_id": {"key": "qnaId", "type": "int"},
+    }
+
+    def __init__(self, user_id: str, user_question: str, qna_id: int, **kwargs):
+        """
+        Parameters:
+        -----------
+
+        user_id: ID of the user.
+
+        user_question: User question.
+
+        qna_id: QnA ID.
+        """
+
+        super().__init__(**kwargs)
+
+        self.user_id = user_id
+        self.user_question = user_question
+        self.qna_id = qna_id

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

@@ -0,0 +1,26 @@
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License.
+
+from typing import List
+
+from msrest.serialization import Model
+
+from .feedback_record import FeedbackRecord
+
+
+class FeedbackRecords(Model):
+    """ Active learning feedback records. """
+
+    _attribute_map = {"records": {"key": "records", "type": "[FeedbackRecord]"}}
+
+    def __init__(self, records: List[FeedbackRecord], **kwargs):
+        """
+        Parameter(s):
+        -------------
+
+        records: List of feedback records.
+        """
+
+        super().__init__(**kwargs)
+
+        self.records = records

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

@@ -0,0 +1,47 @@
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License.
+
+from typing import List
+
+from msrest.serialization import Model
+
+from .metadata import Metadata
+
+
+class GenerateAnswerRequestBody(Model):
+    """ Question used as the payload body for QnA Maker's Generate Answer API. """
+
+    _attribute_map = {
+        "question": {"key": "question", "type": "str"},
+        "top": {"key": "top", "type": "int"},
+        "score_threshold": {"key": "scoreThreshold", "type": "float"},
+        "strict_filters": {"key": "strictFilters", "type": "[Metadata]"},
+    }
+
+    def __init__(
+        self,
+        question: str,
+        top: int,
+        score_threshold: float,
+        strict_filters: List[Metadata],
+        **kwargs
+    ):
+        """
+        Parameters:
+        -----------
+
+        question: The user question to query against the knowledge base.
+
+        top: Max number of answers to be returned for the question.
+
+        score_threshold: Threshold for answers returned based on score.
+
+        strict_filters: Find only answers that contain these metadata.
+        """
+
+        super().__init__(**kwargs)
+
+        self.question = question
+        self.top = top
+        self.score_threshold = score_threshold
+        self.strict_filters = strict_filters

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

@@ -0,0 +1,28 @@
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License.
+
+from msrest.serialization import Model
+
+
+class Metadata(Model):
+    """ Metadata associated with the answer. """
+
+    _attribute_map = {
+        "name": {"key": "name", "type": "str"},
+        "value": {"key": "value", "type": "str"},
+    }
+
+    def __init__(self, name: str, value: str, **kwargs):
+        """
+        Parameters:
+        -----------
+
+        name: Metadata name. Max length: 100.
+
+        value: Metadata value. Max length: 100.
+        """
+
+        super().__init__(**kwargs)
+
+        self.name = name
+        self.value = value

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

@@ -0,0 +1,44 @@
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License.
+
+from typing import List
+
+from botbuilder.schema import Activity
+from .metadata import Metadata
+from .query_result import QueryResult
+
+
+class QnAMakerTraceInfo:
+    """ Represents all the trice info that we collect from the QnAMaker Middleware. """
+
+    def __init__(
+        self,
+        message: Activity,
+        query_results: List[QueryResult],
+        knowledge_base_id: str,
+        score_threshold: float,
+        top: int,
+        strict_filters: List[Metadata],
+    ):
+        """
+        Parameters:
+        -----------
+
+        message: Message which instigated the query to QnA Maker.
+
+        query_results: Results that QnA Maker returned.
+
+        knowledge_base_id: ID of the knowledge base that is being queried.
+
+        score_threshold: The minimum score threshold, used to filter returned results.
+
+        top: Number of ranked results that are asked to be returned.
+
+        strict_filters: Filters used on query.
+        """
+        self.message = message
+        self.query_results = query_results
+        self.knowledge_base_id = knowledge_base_id
+        self.score_threshold = score_threshold
+        self.top = top
+        self.strict_filters = strict_filters

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

@@ -0,0 +1,42 @@
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License.
+
+from typing import List
+
+from .metadata import Metadata
+
+
+class QueryResult:
+    """ Represents an individual result from a knowledge base query. """
+
+    def __init__(
+        self,
+        questions: List[str],
+        answer: str,
+        score: float,
+        metadata: object = None,
+        source: str = None,
+        id: int = None,  # pylint: disable=invalid-name
+    ):
+        """
+        Parameters:
+        -----------
+
+        questions: The list of questions indexed in the QnA Service for the given answer (if any).
+
+        answer: Answer from the knowledge base.
+
+        score: Confidence on a scale from 0.0 to 1.0 that the answer matches the user's intent.
+
+        metadata: Metadata associated with the answer (if any).
+
+        source: The source from which the QnA was extracted (if any).
+
+        id: The index of the answer in the knowledge base. V3 uses 'qnaId', V4 uses 'id' (if any).
+        """
+        self.questions = questions
+        self.answer = answer
+        self.score = score
+        self.metadata = list(map(lambda meta: Metadata(**meta), metadata))
+        self.source = source
+        self.id = id  # pylint: disable=invalid-name

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

@@ -0,0 +1,19 @@
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License.
+
+from typing import List
+
+from .query_result import QueryResult
+
+
+class QueryResults:
+    """ Contains answers for a user query. """
+
+    def __init__(self, answers: List[QueryResult]):
+        """
+        Parameters:
+        -----------
+
+        answers: The answers for a user query.
+        """
+        self.answers = answers