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[QnA] Added method overloads #19876

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merged 7 commits into from
Jul 21, 2021
Merged

[QnA] Added method overloads #19876

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2edf2a4
Added overloads
annatisch Jul 13, 2021
afae0cc
Overload tests
annatisch Jul 13, 2021
60d6d69
Regen and updates
annatisch Jul 16, 2021
2a33d1c
Merge remote-tracking branch 'upstream/main' into feature/cognitivese…
annatisch Jul 20, 2021
794fc48
Removed extra docs
annatisch Jul 20, 2021
a81df8b
Fixed docstring
annatisch Jul 20, 2021
e10534a
Bad request builders internal
annatisch Jul 21, 2021
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14 changes: 7 additions & 7 deletions sdk/cognitivelanguage/azure-ai-language-questionanswering/README.md
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Original file line number Diff line number Diff line change
Expand Up @@ -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))
Expand All @@ -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))
Expand All @@ -128,8 +128,8 @@ params = qna.KnowledgeBaseQueryOptions(
)

output = await client.query_knowledgebase(
project_name="FAQ",
knowledge_base_query_options=params
params,
project_name="FAQ"
)
```

Expand All @@ -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))
Expand Down
136 changes: 130 additions & 6 deletions ...ure/ai/language/questionanswering/aio/operations/_question_answering_client_operations.py
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Original file line number Diff line number Diff line change
Expand Up @@ -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 (
Expand All @@ -27,6 +27,7 @@


class QuestionAnsweringClientOperationsMixin:
@overload
async def query_knowledgebase(
self,
knowledge_base_query_options: "_models.KnowledgeBaseQueryOptions",
Expand All @@ -37,24 +38,100 @@ async def query_knowledgebase(
) -> "_models.KnowledgeBaseAnswers":
"""Answers the specified question using your knowledge base.

Answers the specified question using your knowledge base.

:keyword project_name: The name of the project to use.
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:paramtype project_name: str
:param knowledge_base_query_options: Post body of the request.
:type knowledge_base_query_options:
~azure.ai.language.questionanswering.models.KnowledgeBaseQueryOptions
:keyword deployment_name: The name of the specific deployment of the project to use.
:paramtype deployment_name: str
: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
"""
...

@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")

Expand Down Expand Up @@ -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", {}))
Expand Down
118 changes: 113 additions & 5 deletions ...g/azure/ai/language/questionanswering/operations/_question_answering_client_operations.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -6,7 +6,7 @@
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
import functools
from typing import TYPE_CHECKING
from typing import TYPE_CHECKING, overload
import warnings

from azure.core.exceptions import (
Expand All @@ -31,6 +31,7 @@


class QuestionAnsweringClientOperationsMixin(object):
@overload
def query_knowledgebase(
self,
knowledge_base_query_options, # type: "_models.KnowledgeBaseQueryOptions"
Expand All @@ -39,8 +40,6 @@ def query_knowledgebase(
# type: (...) -> "_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
Expand All @@ -53,6 +52,71 @@ def query_knowledgebase(
:rtype: ~azure.ai.language.questionanswering.models.KnowledgeBaseAnswers
:raises: ~azure.core.exceptions.HttpResponseError
"""
pass

@overload
def query_knowledgebase(
self,
**kwargs # type: Any
):
# type: (...) -> "_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 question: User question to query against the knowledge base.
:paramtype question: str
:keyword qna_id: Exact QnA ID to fetch from the knowledge base, this field takes priority over
question.
:paramtype qna_id: int
: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
"""
pass

def query_knowledgebase(
self,
*args, # type: "_models.KnowledgeBaseQueryOptions"
**kwargs # type: Any
):
# type: (...) -> "_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", {}))
Expand Down Expand Up @@ -91,6 +155,7 @@ def query_knowledgebase(

query_knowledgebase.metadata = {"url": "/:query-knowledgebases"} # type: ignore

@overload
def query_text(
self,
text_query_options, # type: "_models.TextQueryOptions"
Expand All @@ -99,15 +164,58 @@ def query_text(
# type: (...) -> "_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
"""
pass

@overload
def query_text(
self,
**kwargs # type: Any
):
# type: (...) -> "_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.TextInput]
: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
"""
pass

def query_text(
self,
*args, # type: "_models.TextQueryOptions"
**kwargs # type: Any
):
# type: (...) -> "_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", {}))
Expand Down
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