[textanalytics] release prep + fixing docstrings and links (Azure#23315)

* release prep + fixing docstrings and links

* revert change from previous PR where we created a type alias for the input types

Author: kristapratico

sdk/textanalytics/azure-ai-textanalytics/CHANGELOG.md

@@ -1,10 +1,6 @@
 # Release History
 
-## 5.2.0b3 (Unreleased)
-
-### Features Added
-
-### Breaking Changes
+## 5.2.0b3 (2022-03-08)
 
 ### Bugs Fixed
 - `string_index_type` now correctly defaults to the Python default `UnicodeCodePoint` for `AnalyzeSentimentAction` and `RecognizeCustomEntitiesAction`.

sdk/textanalytics/azure-ai-textanalytics/README.md

@@ -692,7 +692,7 @@ This project has adopted the [Microsoft Open Source Code of Conduct][code_of_con
 [cognitive_authentication_aad]: https://docs.microsoft.com/azure/cognitive-services/authentication#authenticate-with-azure-active-directory
 [azure_identity_credentials]: https://github.com/Azure/azure-sdk-for-python/tree/main/sdk/identity/azure-identity#credentials
 [default_azure_credential]: https://github.com/Azure/azure-sdk-for-python/tree/main/sdk/identity/azure-identity#defaultazurecredential
-[service_limits]: https://docs.microsoft.com/azure/cognitive-services/text-analytics/concepts/data-limits?tabs=version-3
+[service_limits]: https://aka.ms/azsdk/textanalytics/data-limits
 [azure-key-credential]: https://aka.ms/azsdk-python-core-azurekeycredential
 [document_error]: https://aka.ms/azsdk-python-textanalytics-documenterror
 [detect_language_result]: https://aka.ms/azsdk-python-textanalytics-detectlanguageresult
@@ -712,15 +712,15 @@ This project has adopted the [Microsoft Open Source Code of Conduct][code_of_con
 [recognize_linked_entities]: https://aka.ms/azsdk-python-textanalytics-recognizelinkedentities
 [extract_key_phrases]: https://aka.ms/azsdk-python-textanalytics-extractkeyphrases
 [detect_language]: https://aka.ms/azsdk-python-textanalytics-detectlanguage
-[language_detection]: https://docs.microsoft.com/azure/cognitive-services/Text-Analytics/how-tos/text-analytics-how-to-language-detection
-[language_and_regional_support]: https://docs.microsoft.com/azure/cognitive-services/text-analytics/language-support?tabs=language-detection
-[sentiment_analysis]: https://docs.microsoft.com/azure/cognitive-services/text-analytics/how-tos/text-analytics-how-to-sentiment-analysis
-[key_phrase_extraction]: https://docs.microsoft.com/azure/cognitive-services/text-analytics/how-tos/text-analytics-how-to-keyword-extraction
-[linked_entities_categories]: https://docs.microsoft.com/azure/cognitive-services/text-analytics/named-entity-types?tabs=general
-[linked_entity_recognition]: https://docs.microsoft.com/azure/cognitive-services/text-analytics/how-tos/text-analytics-how-to-entity-linking
-[pii_entity_categories]: https://docs.microsoft.com/azure/cognitive-services/text-analytics/named-entity-types?tabs=personal
-[named_entity_recognition]: https://docs.microsoft.com/azure/cognitive-services/text-analytics/how-tos/text-analytics-how-to-entity-linking
-[named_entity_categories]: https://docs.microsoft.com/azure/cognitive-services/text-analytics/named-entity-types?tabs=general
+[language_detection]: https://docs.microsoft.com/azure/cognitive-services/language-service/language-detection/overview
+[language_and_regional_support]: https://docs.microsoft.com/azure/cognitive-services/language-service/language-detection/language-support
+[sentiment_analysis]: https://docs.microsoft.com/azure/cognitive-services/language-service/sentiment-opinion-mining/overview
+[key_phrase_extraction]: https://docs.microsoft.com/azure/cognitive-services/language-service/key-phrase-extraction/overview
+[linked_entities_categories]: https://aka.ms/taner
+[linked_entity_recognition]: https://docs.microsoft.com/azure/cognitive-services/language-service/entity-linking/overview
+[pii_entity_categories]: https://aka.ms/tanerpii
+[named_entity_recognition]: https://docs.microsoft.com/azure/cognitive-services/language-service/named-entity-recognition/overview
+[named_entity_categories]: https://aka.ms/taner
 [azure_core_ref_docs]: https://aka.ms/azsdk-python-core-policies
 [azure_core]: https://github.com/Azure/azure-sdk-for-python/blob/main/sdk/core/azure-core/README.md
 [azure_identity]: https://github.com/Azure/azure-sdk-for-python/tree/main/sdk/identity/azure-identity

sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_text_analytics_client.py

@@ -69,35 +69,6 @@
     MultiCategoryClassifyResult,
 )
 
-ActionInputTypes = List[
-    Union[
-        RecognizeEntitiesAction,
-        RecognizeLinkedEntitiesAction,
-        RecognizePiiEntitiesAction,
-        ExtractKeyPhrasesAction,
-        AnalyzeSentimentAction,
-        ExtractSummaryAction,
-        RecognizeCustomEntitiesAction,
-        SingleCategoryClassifyAction,
-        MultiCategoryClassifyAction,
-    ]
-]
-
-ActionResultTypes = List[
-    Union[
-        RecognizeEntitiesResult,
-        RecognizeLinkedEntitiesResult,
-        RecognizePiiEntitiesResult,
-        ExtractKeyPhrasesResult,
-        AnalyzeSentimentResult,
-        ExtractSummaryResult,
-        RecognizeCustomEntitiesResult,
-        SingleCategoryClassifyResult,
-        MultiCategoryClassifyResult,
-        DocumentError,
-    ]
-]
-
 if TYPE_CHECKING:
     from azure.core.credentials import TokenCredential
 
@@ -106,20 +77,19 @@ class TextAnalyticsClient(TextAnalyticsClientBase):
     """The Text Analytics API is a suite of text analytics web services built with best-in-class
     Microsoft machine learning algorithms. The API can be used to analyze unstructured text for
     tasks such as sentiment analysis, key phrase extraction, entities recognition,
-    and language detection. No training data is needed to use this API - just bring your text data.
+    and language detection, and more. No training data is needed to use this API - just bring your text data.
     This API uses advanced natural language processing techniques to deliver best in class predictions.
 
     Further documentation can be found in
-    https://docs.microsoft.com/azure/cognitive-services/text-analytics/overview
+    https://docs.microsoft.com/azure/cognitive-services/language-service/overview
 
     :param str endpoint: Supported Cognitive Services or Text Analytics resource
-        endpoints (protocol and hostname, for example: https://westus2.api.cognitive.microsoft.com).
+        endpoints (protocol and hostname, for example: 'https://<resource-name>.cognitiveservices.azure.com').
     :param credential: Credentials needed for the client to connect to Azure.
         This can be the an instance of AzureKeyCredential if using a
         cognitive services/text analytics API key or a token credential
         from :mod:`azure.identity`.
-    :type credential: :class:`~azure.core.credentials.AzureKeyCredential` or
-        :class:`~azure.core.credentials.TokenCredential`
+    :type credential: ~azure.core.credentials.AzureKeyCredential or ~azure.core.credentials.TokenCredential
     :keyword str default_country_hint: Sets the default country_hint to use for all operations.
         Defaults to "US". If you don't want to use a country hint, pass the string "none".
     :keyword str default_language: Sets the default language to use for all operations.
@@ -173,17 +143,15 @@ def detect_language(
         one. Scores close to one indicate 100% certainty that the identified
         language is true. See https://aka.ms/talangs for the list of enabled languages.
 
-        See https://docs.microsoft.com/azure/cognitive-services/text-analytics/concepts/data-limits?tabs=version-3
-        for document length limits, maximum batch size, and supported text encoding.
+        See https://aka.ms/azsdk/textanalytics/data-limits for service data limits.
 
         :param documents: The set of documents to process as part of this batch.
             If you wish to specify the ID and country_hint on a per-item basis you must
             use as input a list[:class:`~azure.ai.textanalytics.DetectLanguageInput`] or a list of
             dict representations of :class:`~azure.ai.textanalytics.DetectLanguageInput`, like
             `{"id": "1", "country_hint": "us", "text": "hello world"}`.
         :type documents:
-            list[str] or list[~azure.ai.textanalytics.DetectLanguageInput] or
-            list[dict[str, str]]
+            list[str] or list[~azure.ai.textanalytics.DetectLanguageInput] or list[dict[str, str]]
         :keyword str country_hint: Country of origin hint for the entire batch. Accepts two
             letter country codes specified by ISO 3166-1 alpha-2. Per-document
             country hints will take precedence over whole batch hints. Defaults to
@@ -255,17 +223,15 @@ def recognize_entities(
         organizations, date/time, quantities, percentages, currencies, and more.
         For the list of supported entity types, check: https://aka.ms/taner
 
-        See https://docs.microsoft.com/azure/cognitive-services/text-analytics/concepts/data-limits?tabs=version-3
-        for document length limits, maximum batch size, and supported text encoding.
+        See https://aka.ms/azsdk/textanalytics/data-limits for service data limits.
 
         :param documents: The set of documents to process as part of this batch.
             If you wish to specify the ID and language on a per-item basis you must
             use as input a list[:class:`~azure.ai.textanalytics.TextDocumentInput`] or a list
             of dict representations of :class:`~azure.ai.textanalytics.TextDocumentInput`,
             like `{"id": "1", "language": "en", "text": "hello world"}`.
         :type documents:
-            list[str] or list[~azure.ai.textanalytics.TextDocumentInput] or
-            list[dict[str, str]]
+            list[str] or list[~azure.ai.textanalytics.TextDocumentInput] or list[dict[str, str]]
         :keyword str language: The 2 letter ISO 639-1 representation of language for the
             entire batch. For example, use "en" for English; "es" for Spanish etc.
             If not set, uses "en" for English as default. Per-document language will
@@ -346,17 +312,15 @@ def recognize_pii_entities(
         "Bank Account", etc) in the document.  For the list of supported entity types,
         check https://aka.ms/tanerpii
 
-        See https://docs.microsoft.com/azure/cognitive-services/text-analytics/concepts/data-limits?tabs=version-3
-        for document length limits, maximum batch size, and supported text encoding.
+        See https://aka.ms/azsdk/textanalytics/data-limits for service data limits.
 
         :param documents: The set of documents to process as part of this batch.
             If you wish to specify the ID and language on a per-item basis you must
             use as input a list[:class:`~azure.ai.textanalytics.TextDocumentInput`] or a list of
             dict representations of :class:`~azure.ai.textanalytics.TextDocumentInput`, like
             `{"id": "1", "language": "en", "text": "hello world"}`.
         :type documents:
-            list[str] or list[~azure.ai.textanalytics.TextDocumentInput] or
-            list[dict[str, str]]
+            list[str] or list[~azure.ai.textanalytics.TextDocumentInput] or list[dict[str, str]]
         :keyword str language: The 2 letter ISO 639-1 representation of language for the
             entire batch. For example, use "en" for English; "es" for Spanish etc.
             If not set, uses "en" for English as default. Per-document language will
@@ -460,17 +424,15 @@ def recognize_linked_entities(
         Roman god of war). Recognized entities are associated with URLs to a well-known
         knowledge base, like Wikipedia.
 
-        See https://docs.microsoft.com/azure/cognitive-services/text-analytics/concepts/data-limits?tabs=version-3
-        for document length limits, maximum batch size, and supported text encoding.
+        See https://aka.ms/azsdk/textanalytics/data-limits for service data limits.
 
         :param documents: The set of documents to process as part of this batch.
             If you wish to specify the ID and language on a per-item basis you must
             use as input a list[:class:`~azure.ai.textanalytics.TextDocumentInput`] or a list of
             dict representations of :class:`~azure.ai.textanalytics.TextDocumentInput`, like
             `{"id": "1", "language": "en", "text": "hello world"}`.
         :type documents:
-            list[str] or list[~azure.ai.textanalytics.TextDocumentInput] or
-            list[dict[str, str]]
+            list[str] or list[~azure.ai.textanalytics.TextDocumentInput] or list[dict[str, str]]
         :keyword str language: The 2 letter ISO 639-1 representation of language for the
             entire batch. For example, use "en" for English; "es" for Spanish etc.
             If not set, uses "en" for English as default. Per-document language will
@@ -575,8 +537,7 @@ def begin_analyze_healthcare_entities(
             dict representations of :class:`~azure.ai.textanalytics.TextDocumentInput`, like
             `{"id": "1", "language": "en", "text": "hello world"}`.
         :type documents:
-            list[str] or list[~azure.ai.textanalytics.TextDocumentInput] or
-            list[dict[str, str]]
+            list[str] or list[~azure.ai.textanalytics.TextDocumentInput] or list[dict[str, str]]
         :keyword str model_version: This value indicates which model will
             be used for scoring, e.g. "latest", "2019-10-01". If a model-version
             is not specified, the API will default to the latest, non-preview version.
@@ -711,17 +672,15 @@ def extract_key_phrases(
         were wonderful staff", the API returns the main talking points: "food"
         and "wonderful staff"
 
-        See https://docs.microsoft.com/azure/cognitive-services/text-analytics/concepts/data-limits?tabs=version-3
-        for document length limits, maximum batch size, and supported text encoding.
+        See https://aka.ms/azsdk/textanalytics/data-limits for service data limits.
 
         :param documents: The set of documents to process as part of this batch.
             If you wish to specify the ID and language on a per-item basis you must
             use as input a list[:class:`~azure.ai.textanalytics.TextDocumentInput`] or a list of
             dict representations of :class:`~azure.ai.textanalytics.TextDocumentInput`, like
             `{"id": "1", "language": "en", "text": "hello world"}`.
         :type documents:
-            list[str] or list[~azure.ai.textanalytics.TextDocumentInput] or
-            list[dict[str, str]]
+            list[str] or list[~azure.ai.textanalytics.TextDocumentInput] or list[dict[str, str]]
         :keyword str language: The 2 letter ISO 639-1 representation of language for the
             entire batch. For example, use "en" for English; "es" for Spanish etc.
             If not set, uses "en" for English as default. Per-document language will
@@ -791,17 +750,15 @@ def analyze_sentiment(
         each sentiment class (Positive, Negative, and Neutral) for the document
         and each sentence within it.
 
-        See https://docs.microsoft.com/azure/cognitive-services/text-analytics/concepts/data-limits?tabs=version-3
-        for document length limits, maximum batch size, and supported text encoding.
+        See https://aka.ms/azsdk/textanalytics/data-limits for service data limits.
 
         :param documents: The set of documents to process as part of this batch.
             If you wish to specify the ID and language on a per-item basis you must
             use as input a list[:class:`~azure.ai.textanalytics.TextDocumentInput`] or a list of
             dict representations of  :class:`~azure.ai.textanalytics.TextDocumentInput`, like
             `{"id": "1", "language": "en", "text": "hello world"}`.
         :type documents:
-            list[str] or list[~azure.ai.textanalytics.TextDocumentInput] or
-            list[dict[str, str]]
+            list[str] or list[~azure.ai.textanalytics.TextDocumentInput] or list[dict[str, str]]
         :keyword bool show_opinion_mining: Whether to mine the opinions of a sentence and conduct more
             granular analysis around the aspects of a product or service (also known as
             aspect-based sentiment analysis). If set to true, the returned
@@ -908,10 +865,37 @@ def _analyze_result_callback(
     def begin_analyze_actions(
         self,
         documents: Union[List[str], List[TextDocumentInput], List[Dict[str, str]]],
-        actions: ActionInputTypes,
+        actions: List[
+            Union[
+                RecognizeEntitiesAction,
+                RecognizeLinkedEntitiesAction,
+                RecognizePiiEntitiesAction,
+                ExtractKeyPhrasesAction,
+                AnalyzeSentimentAction,
+                ExtractSummaryAction,
+                RecognizeCustomEntitiesAction,
+                SingleCategoryClassifyAction,
+                MultiCategoryClassifyAction,
+            ]
+        ],
         **kwargs: Any,
     ) -> AnalyzeActionsLROPoller[
-        ItemPaged[ActionResultTypes]
+        ItemPaged[
+            List[
+                Union[
+                    RecognizeEntitiesResult,
+                    RecognizeLinkedEntitiesResult,
+                    RecognizePiiEntitiesResult,
+                    ExtractKeyPhrasesResult,
+                    AnalyzeSentimentResult,
+                    ExtractSummaryResult,
+                    RecognizeCustomEntitiesResult,
+                    SingleCategoryClassifyResult,
+                    MultiCategoryClassifyResult,
+                    DocumentError,
+                ]
+            ]
+        ]
     ]:
         """Start a long-running operation to perform a variety of text analysis actions over a batch of documents.
 
@@ -928,8 +912,7 @@ def begin_analyze_actions(
             dict representations of :class:`~azure.ai.textanalytics.TextDocumentInput`, like
             `{"id": "1", "language": "en", "text": "hello world"}`.
         :type documents:
-            list[str] or list[~azure.ai.textanalytics.TextDocumentInput] or
-            list[dict[str, str]]
+            list[str] or list[~azure.ai.textanalytics.TextDocumentInput] or list[dict[str, str]]
         :param actions: A heterogeneous list of actions to perform on the input documents.
             Each action object encapsulates the parameters used for the particular action type.
             The action results will be in the same order of the input actions.
@@ -963,7 +946,7 @@ def begin_analyze_actions(
             :class:`~azure.ai.textanalytics.AnalyzeSentimentResult` of "world".
         :rtype:
             ~azure.ai.textanalytics.AnalyzeActionsLROPoller[~azure.core.paging.ItemPaged[
-            list[RecognizeEntitiesResult or RecognizeLinkedEntitiesResult or RecognizePiiEntitiesResult,
+            list[RecognizeEntitiesResult or RecognizeLinkedEntitiesResult or RecognizePiiEntitiesResult or
             ExtractKeyPhrasesResult or AnalyzeSentimentResult or ExtractSummaryAction or RecognizeCustomEntitiesResult
             or SingleCategoryClassifyResult or MultiCategoryClassifyResult or DocumentError]]]
         :raises ~azure.core.exceptions.HttpResponseError or TypeError or ValueError or NotImplementedError: