[QnA] Added method overloads (Azure#19876)

* Added overloads

* Overload tests

* Regen and updates

* Removed extra docs

* Fixed docstring

* Bad request builders internal

Author: annatisch

sdk/cognitivelanguage/azure-ai-language-questionanswering/README.md

@@ -80,8 +80,8 @@ params = qna.KnowledgeBaseQueryOptions(
 )
 
 output = client.query_knowledgebase(
+    params,
     project_name="FAQ",
-    knowledge_base_query_options=params
 )
 for candidate in output.answers:
     print("({}) {}".format(candidate.confidence_score, candidate.answer))
@@ -105,8 +105,8 @@ params = qna.models.KnowledgeBaseQueryOptions(
 )
 
 output = client.query_knowledgebase(
-    project_name="FAQ",
-    knowledge_base_query_options=params
+    params,
+    project_name="FAQ"
 )
 for candidate in output.answers:
     print("({}) {}".format(candidate.confidence_score, candidate.answer))
@@ -128,8 +128,8 @@ params = qna.KnowledgeBaseQueryOptions(
 )
 
 output = await client.query_knowledgebase(
-    project_name="FAQ",
-    knowledge_base_query_options=params
+    params,
+    project_name="FAQ"
 )
 ```
 
@@ -149,8 +149,8 @@ from azure.core.exceptions import HttpResponseError
 
 try:
     client.query_knowledgebase(
-        project_name="invalid-knowledge-base",
-        knowledge_base_query_options=params
+        params,
+        project_name="invalid-knowledge-base"
     )
 except HttpResponseError as error:
     print("Query failed: {}".format(error.message))

…guage/questionanswering/rest/__init__.py …uage/questionanswering/_rest/__init__.pysdk/cognitivelanguage/azure-ai-language-questionanswering/azure/ai/language/questionanswering/rest/__init__.py renamed to sdk/cognitivelanguage/azure-ai-language-questionanswering/azure/ai/language/questionanswering/_rest/__init__.py sdk/cognitivelanguage/azure-ai-language-questionanswering/azure/ai/language/questionanswering/rest/__init__.py renamed to sdk/cognitivelanguage/azure-ai-language-questionanswering/azure/ai/language/questionanswering/_rest/__init__.py

@@ -42,17 +42,7 @@ def __init__(self, endpoint: str, credential: AzureKeyCredential, **kwargs: Any)
     def send_request(self, request: HttpRequest, **kwargs: Any) -> Awaitable[AsyncHttpResponse]:
         """Runs the network request through the client's chained policies.
 
-        We have helper methods to create requests specific to this service in `azure.ai.language.questionanswering.rest`.
-        Use these helper methods to create the request you pass to this method. See our example below:
-
-        >>> from azure.ai.language.questionanswering.rest import build_query_knowledgebase_request
-        >>> request = build_query_knowledgebase_request(project_name=project_name, json=json, content=content, deployment_name=deployment_name, **kwargs)
-        <HttpRequest [POST], url: '/:query-knowledgebases'>
-        >>> response = await client.send_request(request)
-        <AsyncHttpResponse: 200 OK>
-
         For more information on this code flow, see https://aka.ms/azsdk/python/protocol/quickstart
-
         For advanced cases, you can also create your own :class:`~azure.core.rest.HttpRequest`
         and pass it in.
 

…stionanswering/rest/_request_builders.py …tionanswering/_rest/_request_builders.pysdk/cognitivelanguage/azure-ai-language-questionanswering/azure/ai/language/questionanswering/rest/_request_builders.py renamed to sdk/cognitivelanguage/azure-ai-language-questionanswering/azure/ai/language/questionanswering/_rest/_request_builders.py sdk/cognitivelanguage/azure-ai-language-questionanswering/azure/ai/language/questionanswering/rest/_request_builders.py renamed to sdk/cognitivelanguage/azure-ai-language-questionanswering/azure/ai/language/questionanswering/_rest/_request_builders.py

@@ -6,7 +6,7 @@
 # Changes may cause incorrect behavior and will be lost if the code is regenerated.
 # --------------------------------------------------------------------------
 import functools
-from typing import Any, Callable, Dict, Generic, Optional, TypeVar
+from typing import Any, Callable, Dict, Generic, Optional, TypeVar, overload, Union, List
 import warnings
 
 from azure.core.exceptions import (
@@ -20,13 +20,14 @@
 from azure.core.pipeline.transport import AsyncHttpResponse
 from azure.core.rest import HttpRequest
 
-from ... import models as _models, rest as rest
+from ... import models as _models, _rest as rest
 
 T = TypeVar("T")
 ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]]
 
 
 class QuestionAnsweringClientOperationsMixin:
+    @overload
     async def query_knowledgebase(
         self,
         knowledge_base_query_options: "_models.KnowledgeBaseQueryOptions",
@@ -37,8 +38,6 @@ async def query_knowledgebase(
     ) -> "_models.KnowledgeBaseAnswers":
         """Answers the specified question using your knowledge base.
 
-        Answers the specified question using your knowledge base.
-
         :param knowledge_base_query_options: Post body of the request.
         :type knowledge_base_query_options:
          ~azure.ai.language.questionanswering.models.KnowledgeBaseQueryOptions
@@ -51,10 +50,88 @@ async def query_knowledgebase(
         :rtype: ~azure.ai.language.questionanswering.models.KnowledgeBaseAnswers
         :raises: ~azure.core.exceptions.HttpResponseError
         """
+        ...
+
+    @overload
+    async def query_knowledgebase(
+        self,
+        *,
+        project_name: str,
+        deployment_name: Optional[str] = None,
+        qna_id: Optional[int] = None,
+        question: Optional[str] = None,
+        top: Optional[int] = None,
+        user_id: Optional[str] = None,
+        confidence_score_threshold: Optional[float] = None,
+        context: Optional["_models.KnowledgeBaseAnswerRequestContext"] = None,
+        ranker_type: Optional[Union[str, "_models.RankerType"]] = None,
+        strict_filters: Optional["_models.StrictFilters"] = None,
+        answer_span_request: Optional["_models.AnswerSpanRequest"] = None,
+        include_unstructured_sources: Optional[bool] = None,
+        **kwargs: Any
+    ) -> "_models.KnowledgeBaseAnswers":
+        """Answers the specified question using your knowledge base.
+
+        :keyword project_name: The name of the project to use.
+        :paramtype project_name: str
+        :keyword deployment_name: The name of the specific deployment of the project to use.
+        :paramtype deployment_name: str
+        :keyword qna_id: Exact QnA ID to fetch from the knowledge base, this field takes priority over
+        question.
+        :paramtype qna_id: int
+        :keyword question: User question to query against the knowledge base.
+        :paramtype question: str
+        :keyword top: Max number of answers to be returned for the question.
+        :paramtype top: int
+        :keyword user_id: Unique identifier for the user.
+        :paramtype user_id: str
+        :keyword confidence_score_threshold: Minimum threshold score for answers, value ranges from 0 to
+        1.
+        :paramtype confidence_score_threshold: float
+        :keyword context: Context object with previous QnA's information.
+        :paramtype context: ~azure.ai.language.questionanswering.models.KnowledgeBaseAnswerRequestContext
+        :keyword ranker_type: (Optional) Set to 'QuestionOnly' for using a question only Ranker. Possible
+        values include: "Default", "QuestionOnly".
+        :paramtype ranker_type: str or ~azure.ai.language.questionanswering.models.RankerType
+        :keyword strict_filters: Filter QnAs based on give metadata list and knowledge base source names.
+        :paramtype strict_filters: ~azure.ai.language.questionanswering.models.StrictFilters
+        :keyword answer_span_request: To configure Answer span prediction feature.
+        :paramtype answer_span_request: ~azure.ai.language.questionanswering.models.AnswerSpanRequest
+        :keyword include_unstructured_sources: (Optional) Flag to enable Query over Unstructured Sources.
+        :paramtype include_unstructured_sources: bool
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: KnowledgeBaseAnswers, or the result of cls(response)
+        :rtype: ~azure.ai.language.questionanswering.models.KnowledgeBaseAnswers
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        ...
+
+    async def query_knowledgebase(
+        self,
+        *args,
+        **kwargs: Any
+    ) -> "_models.KnowledgeBaseAnswers":
+        if args:
+            knowledge_base_query_options = args[0]
+        else:
+            knowledge_base_query_options = _models.KnowledgeBaseQueryOptions(
+                qna_id=kwargs.pop("qna_id", None),
+                question=kwargs.pop("question", None),
+                top=kwargs.pop("top", None),
+                user_id=kwargs.pop("user_id", None),
+                confidence_score_threshold=kwargs.pop("confidence_score_threshold", None),
+                context=kwargs.pop("context", None),
+                ranker_type=kwargs.pop("ranker_type", None),
+                strict_filters=kwargs.pop("strict_filters", None),
+                answer_span_request=kwargs.pop("answer_span_request", None),
+                include_unstructured_sources=kwargs.pop("include_unstructured_sources", None)
+            )
         cls = kwargs.pop("cls", None)  # type: ClsType["_models.KnowledgeBaseAnswers"]
         error_map = {401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError}
         error_map.update(kwargs.pop("error_map", {}))
         content_type = kwargs.pop("content_type", "application/json")  # type: Optional[str]
+        project_name = kwargs.pop("project_name")  # type: str
+        deployment_name = kwargs.pop("deployment_name", None)  # type: Optional[str]
 
         json = self._serialize.body(knowledge_base_query_options, "KnowledgeBaseQueryOptions")
 
@@ -89,18 +166,65 @@ async def query_knowledgebase(
 
     query_knowledgebase.metadata = {"url": "/:query-knowledgebases"}  # type: ignore
 
-    async def query_text(self, text_query_options: "_models.TextQueryOptions", **kwargs: Any) -> "_models.TextAnswers":
+    @overload
+    async def query_text(
+        self, text_query_options: "_models.TextQueryOptions", **kwargs: Any
+    ) -> "_models.TextAnswers":
         """Answers the specified question using the provided text in the body.
 
-        Answers the specified question using the provided text in the body.
-
         :param text_query_options: Post body of the request.
         :type text_query_options: ~azure.ai.language.questionanswering.models.TextQueryOptions
         :keyword callable cls: A custom type or function that will be passed the direct response
         :return: TextAnswers, or the result of cls(response)
         :rtype: ~azure.ai.language.questionanswering.models.TextAnswers
         :raises: ~azure.core.exceptions.HttpResponseError
         """
+        ...
+
+    @overload
+    async def query_text(
+        self,
+        *,
+        question: str,
+        records: List["_models.TextRecord"],
+        language: Optional[str] = None,
+        string_index_type: Optional[Union[str, "_models.StringIndexType"]] = "TextElements_v8",
+        **kwargs: Any
+    ) -> "_models.TextAnswers":
+        """Answers the specified question using the provided text in the body.
+
+        :keyword question: Required. User question to query against the given text records.
+        :paramtype question: str
+        :keyword records: Required. Text records to be searched for given question.
+        :paramtype records: list[~azure.ai.language.questionanswering.models.TextRecord]
+        :keyword language: Language of the text records. This is BCP-47 representation of a language. For
+        example, use "en" for English; "es" for Spanish etc. If not set, use "en" for English as
+        default.
+        :paramtype language: str
+        :keyword string_index_type: Specifies the method used to interpret string offsets.  Defaults to
+        Text Elements (Graphemes) according to Unicode v8.0.0. For additional information see
+        https://aka.ms/text-analytics-offsets. Possible values include: "TextElements_v8",
+        "UnicodeCodePoint", "Utf16CodeUnit". Default value: "TextElements_v8".
+        :paramtype string_index_type: str or ~azure.ai.language.questionanswering.models.StringIndexType
+        :keyword callable cls: A custom type or function that will be passed the direct response
+        :return: TextAnswers, or the result of cls(response)
+        :rtype: ~azure.ai.language.questionanswering.models.TextAnswers
+        :raises: ~azure.core.exceptions.HttpResponseError
+        """
+        ...
+
+    async def query_text(
+        self, *args, **kwargs: Any
+    ) -> "_models.TextAnswers":
+        if args:
+            text_query_options = args[0]
+        else:
+            text_query_options = _models.TextQueryOptions(
+                question=kwargs.pop("question"),
+                records=kwargs.pop("records"),
+                language=kwargs.pop("language", None),
+                string_index_type=kwargs.pop("string_index_type", "TextElements_v8")
+            )
         cls = kwargs.pop("cls", None)  # type: ClsType["_models.TextAnswers"]
         error_map = {401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError}
         error_map.update(kwargs.pop("error_map", {}))