[QnA] Review feedback

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

@@ -1,5 +1,14 @@
 # Release History
 
+## 1.0.0b2 (unreleased)
+
+### Breaking changes
+* The method `QuestionAnsweringClient.query_knowledgebase` has been renamed to `query_knowledge_base`.
+
+### Features Added
+* The method `QuestionAnsweringClient.query_text` now supports a list of records as strings, where the ID value will be automatically populated.
+
+
 ## 1.0.0b1 (2021-07-27)
 
 ### Features Added

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

@@ -79,7 +79,7 @@ params = qna.KnowledgeBaseQueryOptions(
     question="How long should my Surface battery last?"
 )
 
-output = client.query_knowledgebase(
+output = client.query_knowledge_base(
     params,
     project_name="FAQ",
 )
@@ -104,7 +104,7 @@ params = qna.models.KnowledgeBaseQueryOptions(
     )
 )
 
-output = client.query_knowledgebase(
+output = client.query_knowledge_base(
     params,
     project_name="FAQ"
 )
@@ -127,7 +127,7 @@ params = qna.KnowledgeBaseQueryOptions(
     question="How long should my Surface battery last?"
 )
 
-output = await client.query_knowledgebase(
+output = await client.query_knowledge_base(
     params,
     project_name="FAQ"
 )
@@ -148,7 +148,7 @@ For example, if you submit a question to a non-existant knowledge base, a `400`
 from azure.core.exceptions import HttpResponseError
 
 try:
-    client.query_knowledgebase(
+    client.query_knowledge_base(
         params,
         project_name="invalid-knowledge-base"
     )

sdk/cognitivelanguage/azure-ai-language-questionanswering/azure/ai/language/questionanswering/_patch.py

@@ -0,0 +1,38 @@
+# 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.
+# --------------------------------------------------------------------------
+
+import six
+
+from .models import TextRecord
+
+
+def _validate_text_records(records):
+    if not records:
+        raise ValueError("Input records can not be empty or None")
+
+    if isinstance(records, six.string_types):
+        raise TypeError("Input records cannot be a string.")
+
+    if isinstance(records, dict):
+        raise TypeError("Input records cannot be a dict")
+
+    if not all(isinstance(x, six.string_types) for x in records):
+        if not all(
+            isinstance(x, (dict, TextRecord))
+            for x in records
+        ):
+            raise TypeError(
+                "Mixing string and dictionary/object record input unsupported."
+            )
+
+    request_batch = []
+    for idx, doc in enumerate(records):
+        if isinstance(doc, six.string_types):
+            record = {"id": str(idx), "text": doc}
+            request_batch.append(record)
+        else:
+            request_batch.append(doc)
+    return request_batch

sdk/cognitivelanguage/azure-ai-language-questionanswering/azure/ai/language/questionanswering/_rest/__init__.py

@@ -7,13 +7,13 @@
 # --------------------------------------------------------------------------
 
 try:
-    from ._request_builders_py3 import build_query_knowledgebase_request
+    from ._request_builders_py3 import build_query_knowledge_base_request
     from ._request_builders_py3 import build_query_text_request
 except (SyntaxError, ImportError):
-    from ._request_builders import build_query_knowledgebase_request  # type: ignore
+    from ._request_builders import build_query_knowledge_base_request  # type: ignore
     from ._request_builders import build_query_text_request  # type: ignore
 
 __all__ = [
-    "build_query_knowledgebase_request",
+    "build_query_knowledge_base_request",
     "build_query_text_request",
 ]

sdk/cognitivelanguage/azure-ai-language-questionanswering/azure/ai/language/questionanswering/_rest/_request_builders.py

@@ -18,7 +18,7 @@
 
 # fmt: off
 
-def build_query_knowledgebase_request(
+def build_query_knowledge_base_request(
     **kwargs  # type: Any
 ):
     # type: (...) -> HttpRequest

sdk/cognitivelanguage/azure-ai-language-questionanswering/azure/ai/language/questionanswering/_rest/_request_builders_py3.py

@@ -13,7 +13,7 @@
 _SERIALIZER = Serializer()
 
 
-def build_query_knowledgebase_request(
+def build_query_knowledge_base_request(
     *, project_name: str, json: Any = None, content: Any = None, deployment_name: Optional[str] = None, **kwargs: Any
 ) -> HttpRequest:
     """Answers the specified question using your knowledge base.

sdk/cognitivelanguage/azure-ai-language-questionanswering/azure/ai/language/questionanswering/aio/operations/_question_answering_client_operations.py

@@ -21,14 +21,15 @@
 from azure.core.rest import HttpRequest
 
 from ... import models as _models, _rest as rest
+from ..._patch import _validate_text_records
 
 T = TypeVar("T")
 ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]]
 
 
 class QuestionAnsweringClientOperationsMixin:
     @overload
-    async def query_knowledgebase(
+    async def query_knowledge_base(
         self,
         knowledge_base_query_options: "_models.KnowledgeBaseQueryOptions",
         *,
@@ -53,7 +54,7 @@ async def query_knowledgebase(
         ...
 
     @overload
-    async def query_knowledgebase(
+    async def query_knowledge_base(
         self,
         *,
         project_name: str,
@@ -106,7 +107,7 @@ async def query_knowledgebase(
         """
         ...
 
-    async def query_knowledgebase(
+    async def query_knowledge_base(
         self,
         *args,
         **kwargs: Any
@@ -172,12 +173,12 @@ async def query_knowledgebase(
 
         json = self._serialize.body(knowledge_base_query_options, "KnowledgeBaseQueryOptions")
 
-        request = rest.build_query_knowledgebase_request(
+        request = rest.build_query_knowledge_base_request(
             content_type=content_type,
             project_name=project_name,
             deployment_name=deployment_name,
             json=json,
-            template_url=self.query_knowledgebase.metadata["url"],
+            template_url=self.query_knowledge_base.metadata["url"],
         )._to_pipeline_transport_request()
         path_format_arguments = {
             "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str", skip_quote=True),
@@ -201,7 +202,7 @@ async def query_knowledgebase(
 
         return deserialized
 
-    query_knowledgebase.metadata = {"url": "/:query-knowledgebases"}  # type: ignore
+    query_knowledge_base.metadata = {"url": "/:query-knowledgebases"}  # type: ignore
 
     @overload
     async def query_text(
@@ -286,6 +287,11 @@ async def query_text(
                 language=kwargs.pop("language", None),
                 string_index_type=kwargs.pop("string_index_type", "TextElements_v8")
             )
+        try:
+            text_query_options['records'] = _validate_text_records(text_query_options['records'])
+        except TypeError:
+            text_query_options.records = _validate_text_records(text_query_options.records)
+
         cls = kwargs.pop("cls", None)  # type: ClsType["_models.TextAnswers"]
         error_map = {401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError}
         error_map.update(kwargs.pop("error_map", {}))

sdk/cognitivelanguage/azure-ai-language-questionanswering/azure/ai/language/questionanswering/operations/_question_answering_client_operations.py

@@ -21,6 +21,7 @@
 from azure.core.rest import HttpRequest
 
 from .. import models as _models, _rest as rest
+from .._patch import _validate_text_records
 
 if TYPE_CHECKING:
     # pylint: disable=unused-import,ungrouped-imports
@@ -32,7 +33,7 @@
 
 class QuestionAnsweringClientOperationsMixin(object):
     @overload
-    def query_knowledgebase(
+    def query_knowledge_base(
         self,
         knowledge_base_query_options,  # type: "_models.KnowledgeBaseQueryOptions"
         **kwargs  # type: Any
@@ -55,7 +56,7 @@ def query_knowledgebase(
         pass
 
     @overload
-    def query_knowledgebase(
+    def query_knowledge_base(
         self,
         **kwargs  # type: Any
     ):
@@ -96,7 +97,7 @@ def query_knowledgebase(
         """
         pass
 
-    def query_knowledgebase(
+    def query_knowledge_base(
         self,
         *args,  # type: "_models.KnowledgeBaseQueryOptions"
         **kwargs  # type: Any
@@ -163,12 +164,12 @@ def query_knowledgebase(
 
         json = self._serialize.body(knowledge_base_query_options, "KnowledgeBaseQueryOptions")
 
-        request = rest.build_query_knowledgebase_request(
+        request = rest.build_query_knowledge_base_request(
             content_type=content_type,
             project_name=project_name,
             deployment_name=deployment_name,
             json=json,
-            template_url=self.query_knowledgebase.metadata["url"],
+            template_url=self.query_knowledge_base.metadata["url"],
         )._to_pipeline_transport_request()
         path_format_arguments = {
             "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str", skip_quote=True),
@@ -190,7 +191,7 @@ def query_knowledgebase(
 
         return deserialized
 
-    query_knowledgebase.metadata = {"url": "/:query-knowledgebases"}  # type: ignore
+    query_knowledge_base.metadata = {"url": "/:query-knowledgebases"}  # type: ignore
 
     @overload
     def query_text(
@@ -221,7 +222,7 @@ def query_text(
         :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.TextInput]
+        :paramtype records: list[str or ~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.
@@ -254,7 +255,7 @@ def query_text(
         :paramtype question: str
         :keyword records: Text records to be searched for given question. Provide either `text_query_options`, OR
          individual keyword arguments. If both are provided, only the options object will be used.
-        :paramtype records: list[~azure.ai.language.questionanswering.models.TextInput]
+        :paramtype records: list[str or ~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
@@ -277,6 +278,11 @@ def query_text(
                 language=kwargs.pop("language", None),
                 string_index_type=kwargs.pop("string_index_type", "TextElements_v8")
             )
+        try:
+            text_query_options['records'] = _validate_text_records(text_query_options['records'])
+        except TypeError:
+            text_query_options.records = _validate_text_records(text_query_options.records)
+
         cls = kwargs.pop("cls", None)  # type: ClsType["_models.TextAnswers"]
         error_map = {401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError}
         error_map.update(kwargs.pop("error_map", {}))

sdk/cognitivelanguage/azure-ai-language-questionanswering/samples/async_samples/sample_chat_async.py

@@ -31,7 +31,7 @@ async def sample_chit_chat():
 
     endpoint = os.environ["AZURE_QUESTIONANSWERING_ENDPOINT"]
     key = os.environ["AZURE_QUESTIONANSWERING_KEY"]
-    knowledgebase_project = os.environ["AZURE_QUESTIONANSWERING_PROJECT"]
+    knowledge_base_project = os.environ["AZURE_QUESTIONANSWERING_PROJECT"]
 
     client = QuestionAnsweringClient(endpoint, AzureKeyCredential(key))
     async with client:
@@ -47,9 +47,9 @@ async def sample_chit_chat():
             ),
         )
 
-        output = await client.query_knowledgebase(
+        output = await client.query_knowledge_base(
             first_question,
-            project_name=knowledgebase_project,
+            project_name=knowledge_base_project,
             deployment_name="test"
         )
         best_candidate = [a for a in output.answers if a.confidence_score > 0.9][0]
@@ -72,9 +72,9 @@ async def sample_chit_chat():
             include_unstructured_sources=True
         )
 
-        output = await client.query_knowledgebase(
+        output = await client.query_knowledge_base(
             followup_question,
-            project_name=knowledgebase_project,
+            project_name=knowledge_base_project,
             deployment_name="test"
         )
         print("Q: {}".format(followup_question.question))

sdk/cognitivelanguage/azure-ai-language-questionanswering/samples/async_samples/sample_query_knowledgebase_async.py

@@ -31,7 +31,7 @@ async def sample_query_knowledgebase():
 
     endpoint = os.environ["AZURE_QUESTIONANSWERING_ENDPOINT"]
     key = os.environ["AZURE_QUESTIONANSWERING_KEY"]
-    knowledgebase_project = os.environ["AZURE_QUESTIONANSWERING_PROJECT"]
+    knowledge_base_project = os.environ["AZURE_QUESTIONANSWERING_PROJECT"]
 
     client = QuestionAnsweringClient(endpoint, AzureKeyCredential(key))
     async with client:
@@ -47,9 +47,9 @@ async def sample_query_knowledgebase():
             ),
         )
 
-        output = await client.query_knowledgebase(
+        output = await client.query_knowledge_base(
             input,
-            project_name=knowledgebase_project,
+            project_name=knowledge_base_project,
             deployment_name="test"
         )
         best_candidate = [a for a in output.answers if a.confidence_score > 0.9][0]

sdk/cognitivelanguage/azure-ai-language-questionanswering/samples/sample_chat.py

@@ -29,7 +29,7 @@ def sample_chit_chat():
 
     endpoint = os.environ["AZURE_QUESTIONANSWERING_ENDPOINT"]
     key = os.environ["AZURE_QUESTIONANSWERING_KEY"]
-    knowledgebase_project = os.environ["AZURE_QUESTIONANSWERING_PROJECT"]
+    knowledge_base_project = os.environ["AZURE_QUESTIONANSWERING_PROJECT"]
 
     client = QuestionAnsweringClient(endpoint, AzureKeyCredential(key))
     with client:
@@ -45,9 +45,9 @@ def sample_chit_chat():
             ),
         )
 
-        output = client.query_knowledgebase(
+        output = client.query_knowledge_base(
             first_question,
-            project_name=knowledgebase_project,
+            project_name=knowledge_base_project,
             deployment_name="test"
         )
         best_candidate = [a for a in output.answers if a.confidence_score > 0.9][0]
@@ -70,9 +70,9 @@ def sample_chit_chat():
             include_unstructured_sources=True
         )
 
-        output = client.query_knowledgebase(
+        output = client.query_knowledge_base(
             followup_question,
-            project_name=knowledgebase_project,
+            project_name=knowledge_base_project,
             deployment_name="test"
         )
         print("Q: {}".format(followup_question.question))

sdk/cognitivelanguage/azure-ai-language-questionanswering/samples/sample_query_knowledgebase.py

@@ -29,7 +29,7 @@ def sample_query_knowledgebase():
 
     endpoint = os.environ["AZURE_QUESTIONANSWERING_ENDPOINT"]
     key = os.environ["AZURE_QUESTIONANSWERING_KEY"]
-    knowledgebase_project = os.environ["AZURE_QUESTIONANSWERING_PROJECT"]
+    knowledge_base_project = os.environ["AZURE_QUESTIONANSWERING_PROJECT"]
 
     client = QuestionAnsweringClient(endpoint, AzureKeyCredential(key))
     with client:
@@ -45,9 +45,9 @@ def sample_query_knowledgebase():
             ),
         )
 
-        output = client.query_knowledgebase(
+        output = client.query_knowledge_base(
             input,
-            project_name=knowledgebase_project,
+            project_name=knowledge_base_project,
             deployment_name="test"
         )
         best_candidate = [a for a in output.answers if a.confidence_score > 0.9][0]