diff --git a/sdk/textanalytics/azure-ai-textanalytics/CHANGELOG.md b/sdk/textanalytics/azure-ai-textanalytics/CHANGELOG.md
index f05e021f850a4..f08ca18b2e5a3 100644
--- a/sdk/textanalytics/azure-ai-textanalytics/CHANGELOG.md
+++ b/sdk/textanalytics/azure-ai-textanalytics/CHANGELOG.md
@@ -5,6 +5,9 @@
 - `score` attribute has been renamed to `confidence_score` for the `CategorizedEntity`, `LinkedEntityMatch`, and
 `PiiEntity` models
 
+**Breaking changes**
+- All input parameters `inputs` have been renamed to `documents`
+
 
 ## 1.0.0b3 (2020-03-10)
 
diff --git a/sdk/textanalytics/azure-ai-textanalytics/README.md b/sdk/textanalytics/azure-ai-textanalytics/README.md
index 7072d674ec6dd..d600984f88cc1 100644
--- a/sdk/textanalytics/azure-ai-textanalytics/README.md
+++ b/sdk/textanalytics/azure-ai-textanalytics/README.md
@@ -138,7 +138,7 @@ The input for each operation is passed as a **list** of documents.
 
 Each document can be passed as a string in the list, e.g.
 ```python
-docs = ["I hated the movie. It was so slow!", "The movie made it into my top ten favorites.", "What a great movie!"]
+documents = ["I hated the movie. It was so slow!", "The movie made it into my top ten favorites.", "What a great movie!"]
 ```
 
 or, if you wish to pass in a per-item document `id` or `language`/`country_hint`, they can be passed as a list of
@@ -147,7 +147,7 @@ or, if you wish to pass in a per-item document `id` or `language`/`country_hint`
 or a dict-like representation of the object:
 
 ```python
-inputs = [
+documents = [
     {"id": "1", "language": "en", "text": "I hated the movie. It was so slow!"},
     {"id": "2", "language": "en", "text": "The movie made it into my top ten favorites."},
     {"id": "3", "language": "en", "text": "What a great movie!"}
diff --git a/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_text_analytics_client.py b/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_text_analytics_client.py
index 221d0fbc9b054..bf54aa5c8b754 100644
--- a/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_text_analytics_client.py
+++ b/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/_text_analytics_client.py
@@ -95,7 +95,7 @@ def __init__(self, endpoint, credential, **kwargs):
     @distributed_trace
     def detect_language(  # type: ignore
         self,
-        inputs,  # type: Union[List[str], List[DetectLanguageInput], List[Dict[str, str]]]
+        documents,  # type: Union[List[str], List[DetectLanguageInput], List[Dict[str, str]]]
         **kwargs  # type: Any
     ):
         # type: (...) -> List[Union[DetectLanguageResult, DocumentError]]
@@ -108,12 +108,12 @@ def detect_language(  # type: ignore
         See https://docs.microsoft.com/azure/cognitive-services/text-analytics/overview#data-limits
         for document length limits, maximum batch size, and supported text encoding.
 
-        :param inputs: The set of documents to process as part of this batch.
+        :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 inputs:
+        :type documents:
             list[str] or list[~azure.ai.textanalytics.DetectLanguageInput]
         :keyword str country_hint: A country hint for the entire batch. Accepts two
             letter country codes specified by ISO 3166-1 alpha-2. Per-document
@@ -142,7 +142,7 @@ def detect_language(  # type: ignore
         """
         country_hint_arg = kwargs.pop("country_hint", None)
         country_hint = country_hint_arg if country_hint_arg is not None else self._default_country_hint
-        docs = _validate_batch_input(inputs, "country_hint", country_hint)
+        docs = _validate_batch_input(documents, "country_hint", country_hint)
         model_version = kwargs.pop("model_version", None)
         show_stats = kwargs.pop("show_stats", False)
         try:
@@ -159,7 +159,7 @@ def detect_language(  # type: ignore
     @distributed_trace
     def recognize_entities(  # type: ignore
         self,
-        inputs,  # type: Union[List[str], List[TextDocumentInput], List[Dict[str, str]]]
+        documents,  # type: Union[List[str], List[TextDocumentInput], List[Dict[str, str]]]
         **kwargs  # type: Any
     ):
         # type: (...) -> List[Union[RecognizeEntitiesResult, DocumentError]]
@@ -172,12 +172,12 @@ def recognize_entities(  # type: ignore
         See https://docs.microsoft.com/azure/cognitive-services/text-analytics/overview#data-limits
         for document length limits, maximum batch size, and supported text encoding.
 
-        :param inputs: The set of documents to process as part of this batch.
+        :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 inputs:
+        :type documents:
             list[str] or list[~azure.ai.textanalytics.TextDocumentInput]
         :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.
@@ -206,7 +206,7 @@ def recognize_entities(  # type: ignore
         """
         language_arg = kwargs.pop("language", None)
         language = language_arg if language_arg is not None else self._default_language
-        docs = _validate_batch_input(inputs, "language", language)
+        docs = _validate_batch_input(documents, "language", language)
         model_version = kwargs.pop("model_version", None)
         show_stats = kwargs.pop("show_stats", False)
         try:
@@ -223,7 +223,7 @@ def recognize_entities(  # type: ignore
     @distributed_trace
     def recognize_pii_entities(  # type: ignore
         self,
-        inputs,  # type: Union[List[str], List[TextDocumentInput], List[Dict[str, str]]]
+        documents,  # type: Union[List[str], List[TextDocumentInput], List[Dict[str, str]]]
         **kwargs  # type: Any
     ):
         # type: (...) -> List[Union[RecognizePiiEntitiesResult, DocumentError]]
@@ -236,12 +236,12 @@ def recognize_pii_entities(  # type: ignore
         See https://docs.microsoft.com/azure/cognitive-services/text-analytics/overview#data-limits
         for document length limits, maximum batch size, and supported text encoding.
 
-        :param inputs: The set of documents to process as part of this batch.
+        :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 inputs:
+        :type documents:
             list[str] or list[~azure.ai.textanalytics.TextDocumentInput]
         :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.
@@ -270,7 +270,7 @@ def recognize_pii_entities(  # type: ignore
         """
         language_arg = kwargs.pop("language", None)
         language = language_arg if language_arg is not None else self._default_language
-        docs = _validate_batch_input(inputs, "language", language)
+        docs = _validate_batch_input(documents, "language", language)
         model_version = kwargs.pop("model_version", None)
         show_stats = kwargs.pop("show_stats", False)
         try:
@@ -287,7 +287,7 @@ def recognize_pii_entities(  # type: ignore
     @distributed_trace
     def recognize_linked_entities(  # type: ignore
         self,
-        inputs,  # type: Union[List[str], List[TextDocumentInput], List[Dict[str, str]]]
+        documents,  # type: Union[List[str], List[TextDocumentInput], List[Dict[str, str]]]
         **kwargs  # type: Any
     ):
         # type: (...) -> List[Union[RecognizeLinkedEntitiesResult, DocumentError]]
@@ -301,12 +301,12 @@ def recognize_linked_entities(  # type: ignore
         See https://docs.microsoft.com/azure/cognitive-services/text-analytics/overview#data-limits
         for document length limits, maximum batch size, and supported text encoding.
 
-        :param inputs: The set of documents to process as part of this batch.
+        :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 inputs:
+        :type documents:
             list[str] or list[~azure.ai.textanalytics.TextDocumentInput]
         :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.
@@ -335,7 +335,7 @@ def recognize_linked_entities(  # type: ignore
         """
         language_arg = kwargs.pop("language", None)
         language = language_arg if language_arg is not None else self._default_language
-        docs = _validate_batch_input(inputs, "language", language)
+        docs = _validate_batch_input(documents, "language", language)
         model_version = kwargs.pop("model_version", None)
         show_stats = kwargs.pop("show_stats", False)
         try:
@@ -352,7 +352,7 @@ def recognize_linked_entities(  # type: ignore
     @distributed_trace
     def extract_key_phrases(  # type: ignore
         self,
-        inputs,  # type: Union[List[str], List[TextDocumentInput], List[Dict[str, str]]]
+        documents,  # type: Union[List[str], List[TextDocumentInput], List[Dict[str, str]]]
         **kwargs  # type: Any
     ):
         # type: (...) -> List[Union[ExtractKeyPhrasesResult, DocumentError]]
@@ -366,12 +366,12 @@ def extract_key_phrases(  # type: ignore
         See https://docs.microsoft.com/azure/cognitive-services/text-analytics/overview#data-limits
         for document length limits, maximum batch size, and supported text encoding.
 
-        :param inputs: The set of documents to process as part of this batch.
+        :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 inputs:
+        :type documents:
             list[str] or list[~azure.ai.textanalytics.TextDocumentInput]
         :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.
@@ -400,7 +400,7 @@ def extract_key_phrases(  # type: ignore
         """
         language_arg = kwargs.pop("language", None)
         language = language_arg if language_arg is not None else self._default_language
-        docs = _validate_batch_input(inputs, "language", language)
+        docs = _validate_batch_input(documents, "language", language)
         model_version = kwargs.pop("model_version", None)
         show_stats = kwargs.pop("show_stats", False)
         try:
@@ -417,7 +417,7 @@ def extract_key_phrases(  # type: ignore
     @distributed_trace
     def analyze_sentiment(  # type: ignore
         self,
-        inputs,  # type: Union[List[str], List[TextDocumentInput], List[Dict[str, str]]]
+        documents,  # type: Union[List[str], List[TextDocumentInput], List[Dict[str, str]]]
         **kwargs  # type: Any
     ):
         # type: (...) -> List[Union[AnalyzeSentimentResult, DocumentError]]
@@ -430,12 +430,12 @@ def analyze_sentiment(  # type: ignore
         See https://docs.microsoft.com/azure/cognitive-services/text-analytics/overview#data-limits
         for document length limits, maximum batch size, and supported text encoding.
 
-        :param inputs: The set of documents to process as part of this batch.
+        :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 inputs:
+        :type documents:
             list[str] or list[~azure.ai.textanalytics.TextDocumentInput]
         :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.
@@ -464,7 +464,7 @@ def analyze_sentiment(  # type: ignore
         """
         language_arg = kwargs.pop("language", None)
         language = language_arg if language_arg is not None else self._default_language
-        docs = _validate_batch_input(inputs, "language", language)
+        docs = _validate_batch_input(documents, "language", language)
         model_version = kwargs.pop("model_version", None)
         show_stats = kwargs.pop("show_stats", False)
         try:
diff --git a/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/aio/_text_analytics_client_async.py b/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/aio/_text_analytics_client_async.py
index 59fccb1b5a858..adab4ac9a3a34 100644
--- a/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/aio/_text_analytics_client_async.py
+++ b/sdk/textanalytics/azure-ai-textanalytics/azure/ai/textanalytics/aio/_text_analytics_client_async.py
@@ -99,7 +99,7 @@ def __init__(  # type: ignore
     @distributed_trace_async
     async def detect_language(  # type: ignore
         self,
-        inputs: Union[List[str], List[DetectLanguageInput], List[Dict[str, str]]],
+        documents: Union[List[str], List[DetectLanguageInput], List[Dict[str, str]]],
         **kwargs: Any
     ) -> List[Union[DetectLanguageResult, DocumentError]]:
         """Detects Language for a batch of documents.
@@ -111,12 +111,12 @@ async def detect_language(  # type: ignore
         See https://docs.microsoft.com/azure/cognitive-services/text-analytics/overview#data-limits
         for document length limits, maximum batch size, and supported text encoding.
 
-        :param inputs: The set of documents to process as part of this batch.
+        :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 inputs:
+        :type documents:
             list[str] or list[~azure.ai.textanalytics.DetectLanguageInput]
         :keyword str country_hint: A country hint for the entire batch. Accepts two
             letter country codes specified by ISO 3166-1 alpha-2. Per-document
@@ -145,7 +145,7 @@ async def detect_language(  # type: ignore
         """
         country_hint_arg = kwargs.pop("country_hint", None)
         country_hint = country_hint_arg if country_hint_arg is not None else self._default_country_hint
-        docs = _validate_batch_input(inputs, "country_hint", country_hint)
+        docs = _validate_batch_input(documents, "country_hint", country_hint)
         model_version = kwargs.pop("model_version", None)
         show_stats = kwargs.pop("show_stats", False)
         try:
@@ -162,7 +162,7 @@ async def detect_language(  # type: ignore
     @distributed_trace_async
     async def recognize_entities(  # type: ignore
         self,
-        inputs: Union[List[str], List[TextDocumentInput], List[Dict[str, str]]],
+        documents: Union[List[str], List[TextDocumentInput], List[Dict[str, str]]],
         **kwargs: Any
     ) -> List[Union[RecognizeEntitiesResult, DocumentError]]:
         """Entity Recognition for a batch of documents.
@@ -174,12 +174,12 @@ async def recognize_entities(  # type: ignore
         See https://docs.microsoft.com/azure/cognitive-services/text-analytics/overview#data-limits
         for document length limits, maximum batch size, and supported text encoding.
 
-        :param inputs: The set of documents to process as part of this batch.
+        :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 inputs:
+        :type documents:
             list[str] or list[~azure.ai.textanalytics.TextDocumentInput]
         :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.
@@ -208,7 +208,7 @@ async def recognize_entities(  # type: ignore
         """
         language_arg = kwargs.pop("language", None)
         language = language_arg if language_arg is not None else self._default_language
-        docs = _validate_batch_input(inputs, "language", language)
+        docs = _validate_batch_input(documents, "language", language)
         model_version = kwargs.pop("model_version", None)
         show_stats = kwargs.pop("show_stats", False)
         try:
@@ -225,7 +225,7 @@ async def recognize_entities(  # type: ignore
     @distributed_trace_async
     async def recognize_pii_entities(  # type: ignore
         self,
-        inputs: Union[List[str], List[TextDocumentInput], List[Dict[str, str]]],
+        documents: Union[List[str], List[TextDocumentInput], List[Dict[str, str]]],
         **kwargs: Any
     ) -> List[Union[RecognizePiiEntitiesResult, DocumentError]]:
         """Recognize entities containing personal information for a batch of documents.
@@ -237,12 +237,12 @@ async def recognize_pii_entities(  # type: ignore
         See https://docs.microsoft.com/azure/cognitive-services/text-analytics/overview#data-limits
         for document length limits, maximum batch size, and supported text encoding.
 
-        :param inputs: The set of documents to process as part of this batch.
+        :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 inputs:
+        :type documents:
             list[str] or list[~azure.ai.textanalytics.TextDocumentInput]
         :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.
@@ -271,7 +271,7 @@ async def recognize_pii_entities(  # type: ignore
         """
         language_arg = kwargs.pop("language", None)
         language = language_arg if language_arg is not None else self._default_language
-        docs = _validate_batch_input(inputs, "language", language)
+        docs = _validate_batch_input(documents, "language", language)
         model_version = kwargs.pop("model_version", None)
         show_stats = kwargs.pop("show_stats", False)
         try:
@@ -288,7 +288,7 @@ async def recognize_pii_entities(  # type: ignore
     @distributed_trace_async
     async def recognize_linked_entities(  # type: ignore
         self,
-        inputs: Union[List[str], List[TextDocumentInput], List[Dict[str, str]]],
+        documents: Union[List[str], List[TextDocumentInput], List[Dict[str, str]]],
         **kwargs: Any
     ) -> List[Union[RecognizeLinkedEntitiesResult, DocumentError]]:
         """Recognize linked entities from a well-known knowledge base for a batch of documents.
@@ -301,12 +301,12 @@ async def recognize_linked_entities(  # type: ignore
         See https://docs.microsoft.com/azure/cognitive-services/text-analytics/overview#data-limits
         for document length limits, maximum batch size, and supported text encoding.
 
-        :param inputs: The set of documents to process as part of this batch.
+        :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 inputs:
+        :type documents:
             list[str] or list[~azure.ai.textanalytics.TextDocumentInput]
         :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.
@@ -335,7 +335,7 @@ async def recognize_linked_entities(  # type: ignore
         """
         language_arg = kwargs.pop("language", None)
         language = language_arg if language_arg is not None else self._default_language
-        docs = _validate_batch_input(inputs, "language", language)
+        docs = _validate_batch_input(documents, "language", language)
         model_version = kwargs.pop("model_version", None)
         show_stats = kwargs.pop("show_stats", False)
         try:
@@ -352,7 +352,7 @@ async def recognize_linked_entities(  # type: ignore
     @distributed_trace_async
     async def extract_key_phrases(  # type: ignore
         self,
-        inputs: Union[List[str], List[TextDocumentInput], List[Dict[str, str]]],
+        documents: Union[List[str], List[TextDocumentInput], List[Dict[str, str]]],
         **kwargs: Any
     ) -> List[Union[ExtractKeyPhrasesResult, DocumentError]]:
         """Extract Key Phrases from a batch of documents.
@@ -365,12 +365,12 @@ async def extract_key_phrases(  # type: ignore
         See https://docs.microsoft.com/azure/cognitive-services/text-analytics/overview#data-limits
         for document length limits, maximum batch size, and supported text encoding.
 
-        :param inputs: The set of documents to process as part of this batch.
+        :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 inputs:
+        :type documents:
             list[str] or list[~azure.ai.textanalytics.TextDocumentInput]
         :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.
@@ -399,7 +399,7 @@ async def extract_key_phrases(  # type: ignore
         """
         language_arg = kwargs.pop("language", None)
         language = language_arg if language_arg is not None else self._default_language
-        docs = _validate_batch_input(inputs, "language", language)
+        docs = _validate_batch_input(documents, "language", language)
         model_version = kwargs.pop("model_version", None)
         show_stats = kwargs.pop("show_stats", False)
         try:
@@ -416,7 +416,7 @@ async def extract_key_phrases(  # type: ignore
     @distributed_trace_async
     async def analyze_sentiment(  # type: ignore
         self,
-        inputs: Union[List[str], List[TextDocumentInput], List[Dict[str, str]]],
+        documents: Union[List[str], List[TextDocumentInput], List[Dict[str, str]]],
         **kwargs: Any
     ) -> List[Union[AnalyzeSentimentResult, DocumentError]]:
         """Analyze sentiment for a batch of documents.
@@ -428,12 +428,12 @@ async def analyze_sentiment(  # type: ignore
         See https://docs.microsoft.com/azure/cognitive-services/text-analytics/overview#data-limits
         for document length limits, maximum batch size, and supported text encoding.
 
-        :param inputs: The set of documents to process as part of this batch.
+        :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 inputs:
+        :type documents:
             list[str] or list[~azure.ai.textanalytics.TextDocumentInput]
         :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.
@@ -462,7 +462,7 @@ async def analyze_sentiment(  # type: ignore
         """
         language_arg = kwargs.pop("language", None)
         language = language_arg if language_arg is not None else self._default_language
-        docs = _validate_batch_input(inputs, "language", language)
+        docs = _validate_batch_input(documents, "language", language)
         model_version = kwargs.pop("model_version", None)
         show_stats = kwargs.pop("show_stats", False)
         try:
diff --git a/sdk/textanalytics/azure-ai-textanalytics/tests/test_analyze_sentiment.py b/sdk/textanalytics/azure-ai-textanalytics/tests/test_analyze_sentiment.py
index 21f524ff68a01..bdf22054907ae 100644
--- a/sdk/textanalytics/azure-ai-textanalytics/tests/test_analyze_sentiment.py
+++ b/sdk/textanalytics/azure-ai-textanalytics/tests/test_analyze_sentiment.py
@@ -127,7 +127,7 @@ def test_bad_model_version(self, resource_group, location, text_analytics_accoun
         text_analytics = TextAnalyticsClient(text_analytics_account, TextAnalyticsApiKeyCredential(text_analytics_account_key))
         with self.assertRaises(HttpResponseError):
             response = text_analytics.analyze_sentiment(
-                inputs=["Microsoft was founded by Bill Gates."],
+                documents=["Microsoft was founded by Bill Gates."],
                 model_version="old"
             )
 
@@ -496,7 +496,7 @@ def callback(response):
             self.assertIsNotNone(response.statistics)
 
         res = text_analytics.analyze_sentiment(
-            inputs=["Bill Gates is the CEO of Microsoft."],
+            documents=["Bill Gates is the CEO of Microsoft."],
             model_version="latest",
             show_stats=True,
             language="es",
diff --git a/sdk/textanalytics/azure-ai-textanalytics/tests/test_analyze_sentiment_async.py b/sdk/textanalytics/azure-ai-textanalytics/tests/test_analyze_sentiment_async.py
index f2f16bf524766..ce54631f723e2 100644
--- a/sdk/textanalytics/azure-ai-textanalytics/tests/test_analyze_sentiment_async.py
+++ b/sdk/textanalytics/azure-ai-textanalytics/tests/test_analyze_sentiment_async.py
@@ -151,7 +151,7 @@ async def test_bad_model_version(self, resource_group, location, text_analytics_
         text_analytics = TextAnalyticsClient(text_analytics_account, TextAnalyticsApiKeyCredential(text_analytics_account_key))
         with self.assertRaises(HttpResponseError):
             response = await text_analytics.analyze_sentiment(
-                inputs=["Microsoft was founded by Bill Gates."],
+                documents=["Microsoft was founded by Bill Gates."],
                 model_version="old"
             )
 
@@ -544,7 +544,7 @@ def callback(response):
             self.assertIsNotNone(response.statistics)
 
         res = await text_analytics.analyze_sentiment(
-            inputs=["Bill Gates is the CEO of Microsoft."],
+            documents=["Bill Gates is the CEO of Microsoft."],
             model_version="latest",
             show_stats=True,
             language="es",
diff --git a/sdk/textanalytics/azure-ai-textanalytics/tests/test_detect_language.py b/sdk/textanalytics/azure-ai-textanalytics/tests/test_detect_language.py
index 6c5f4d24ef548..1799d02dc5d47 100644
--- a/sdk/textanalytics/azure-ai-textanalytics/tests/test_detect_language.py
+++ b/sdk/textanalytics/azure-ai-textanalytics/tests/test_detect_language.py
@@ -149,7 +149,7 @@ def test_bad_model_version(self, resource_group, location, text_analytics_accoun
         text_analytics = TextAnalyticsClient(text_analytics_account, TextAnalyticsApiKeyCredential(text_analytics_account_key))
         with self.assertRaises(HttpResponseError):
             response = text_analytics.detect_language(
-                inputs=["Microsoft was founded by Bill Gates."],
+                documents=["Microsoft was founded by Bill Gates."],
                 model_version="old"
             )
 
@@ -533,10 +533,10 @@ def callback(response):
         # test DetectLanguageInput
         result2 = text_analytics.detect_language(documents2, raw_response_hook=callback)
         # test per-operation
-        result3 = text_analytics.detect_language(inputs=["this is written in english"], country_hint="none", raw_response_hook=callback)
+        result3 = text_analytics.detect_language(documents=["this is written in english"], country_hint="none", raw_response_hook=callback)
         # test client default
         new_client = TextAnalyticsClient(text_analytics_account, TextAnalyticsApiKeyCredential(text_analytics_account_key), default_country_hint="none")
-        result4 = new_client.detect_language(inputs=["this is written in english"], raw_response_hook=callback)
+        result4 = new_client.detect_language(documents=["this is written in english"], raw_response_hook=callback)
 
     @GlobalTextAnalyticsAccountPreparer()
     def test_country_hint_kwarg(self, resource_group, location, text_analytics_account, text_analytics_account_key):
@@ -549,7 +549,7 @@ def callback(response):
             self.assertIsNotNone(response.statistics)
 
         res = text_analytics.detect_language(
-            inputs=["this is written in english"],
+            documents=["this is written in english"],
             model_version="latest",
             show_stats=True,
             country_hint="ES",
diff --git a/sdk/textanalytics/azure-ai-textanalytics/tests/test_detect_language_async.py b/sdk/textanalytics/azure-ai-textanalytics/tests/test_detect_language_async.py
index aa36ff5a1ae8a..e7c3c96bf2e3f 100644
--- a/sdk/textanalytics/azure-ai-textanalytics/tests/test_detect_language_async.py
+++ b/sdk/textanalytics/azure-ai-textanalytics/tests/test_detect_language_async.py
@@ -172,7 +172,7 @@ async def test_bad_model_version(self, resource_group, location, text_analytics_
         text_analytics = TextAnalyticsClient(text_analytics_account, TextAnalyticsApiKeyCredential(text_analytics_account_key))
         with self.assertRaises(HttpResponseError):
             response = await text_analytics.detect_language(
-                inputs=["Microsoft was founded by Bill Gates."],
+                documents=["Microsoft was founded by Bill Gates."],
                 model_version="old"
             )
 
@@ -193,7 +193,7 @@ async def test_mixing_inputs(self, resource_group, location, text_analytics_acco
         docs = [
             {"id": "1", "text": "Microsoft was founded by Bill Gates and Paul Allen."},
             TextDocumentInput(id="2", text="I did not like the hotel we stayed at. It was too expensive."),
-            u"You cannot mix string input with the above inputs"
+            u"You cannot mix string input with the above documents"
         ]
         with self.assertRaises(TypeError):
             response = await text_analytics.detect_language(docs)
@@ -579,10 +579,10 @@ def callback(response):
         # test DetectLanguageInput
         result2 = await text_analytics.detect_language(documents2, raw_response_hook=callback)
         # test per-operation
-        result3 = await text_analytics.detect_language(inputs=["this is written in english"], country_hint="none", raw_response_hook=callback)
+        result3 = await text_analytics.detect_language(documents=["this is written in english"], country_hint="none", raw_response_hook=callback)
         # test client default
         new_client = TextAnalyticsClient(text_analytics_account, TextAnalyticsApiKeyCredential(text_analytics_account_key), default_country_hint="none")
-        result4 = await new_client.detect_language(inputs=["this is written in english"], raw_response_hook=callback)
+        result4 = await new_client.detect_language(documents=["this is written in english"], raw_response_hook=callback)
 
     @GlobalTextAnalyticsAccountPreparer()
     @AsyncTextAnalyticsTest.await_prepared_test
@@ -596,7 +596,7 @@ def callback(response):
             self.assertIsNotNone(response.statistics)
 
         res = await text_analytics.detect_language(
-            inputs=["this is written in english"],
+            documents=["this is written in english"],
             model_version="latest",
             show_stats=True,
             country_hint="ES",
diff --git a/sdk/textanalytics/azure-ai-textanalytics/tests/test_extract_key_phrases.py b/sdk/textanalytics/azure-ai-textanalytics/tests/test_extract_key_phrases.py
index 558ff271edd28..4d1df8d562199 100644
--- a/sdk/textanalytics/azure-ai-textanalytics/tests/test_extract_key_phrases.py
+++ b/sdk/textanalytics/azure-ai-textanalytics/tests/test_extract_key_phrases.py
@@ -112,7 +112,7 @@ def test_bad_model_version(self, resource_group, location, text_analytics_accoun
         text_analytics = TextAnalyticsClient(text_analytics_account, TextAnalyticsApiKeyCredential(text_analytics_account_key))
         with self.assertRaises(HttpResponseError):
             response = text_analytics.extract_key_phrases(
-                inputs=["Microsoft was founded by Bill Gates."],
+                documents=["Microsoft was founded by Bill Gates."],
                 model_version="old"
             )
 
@@ -465,7 +465,7 @@ def callback(response):
             self.assertIsNotNone(response.statistics)
 
         res = text_analytics.extract_key_phrases(
-            inputs=["Bill Gates is the CEO of Microsoft."],
+            documents=["Bill Gates is the CEO of Microsoft."],
             model_version="latest",
             show_stats=True,
             language="es",
diff --git a/sdk/textanalytics/azure-ai-textanalytics/tests/test_extract_key_phrases_async.py b/sdk/textanalytics/azure-ai-textanalytics/tests/test_extract_key_phrases_async.py
index e05ea66b0c74a..a8813e8619cca 100644
--- a/sdk/textanalytics/azure-ai-textanalytics/tests/test_extract_key_phrases_async.py
+++ b/sdk/textanalytics/azure-ai-textanalytics/tests/test_extract_key_phrases_async.py
@@ -136,7 +136,7 @@ async def test_bad_model_version(self, resource_group, location, text_analytics_
         text_analytics = TextAnalyticsClient(text_analytics_account, TextAnalyticsApiKeyCredential(text_analytics_account_key))
         with self.assertRaises(HttpResponseError):
             response = await text_analytics.extract_key_phrases(
-                inputs=["Microsoft was founded by Bill Gates."],
+                documents=["Microsoft was founded by Bill Gates."],
                 model_version="old"
             )
 
@@ -513,7 +513,7 @@ def callback(response):
             self.assertIsNotNone(response.statistics)
 
         res = await text_analytics.extract_key_phrases(
-            inputs=["Bill Gates is the CEO of Microsoft."],
+            documents=["Bill Gates is the CEO of Microsoft."],
             model_version="latest",
             show_stats=True,
             language="es",
diff --git a/sdk/textanalytics/azure-ai-textanalytics/tests/test_recognize_entities.py b/sdk/textanalytics/azure-ai-textanalytics/tests/test_recognize_entities.py
index 878b564bbdf66..07745bd47a1fb 100644
--- a/sdk/textanalytics/azure-ai-textanalytics/tests/test_recognize_entities.py
+++ b/sdk/textanalytics/azure-ai-textanalytics/tests/test_recognize_entities.py
@@ -127,7 +127,7 @@ def test_bad_model_version(self, resource_group, location, text_analytics_accoun
         text_analytics = TextAnalyticsClient(text_analytics_account, TextAnalyticsApiKeyCredential(text_analytics_account_key))
         with self.assertRaises(HttpResponseError):
             response = text_analytics.recognize_entities(
-                inputs=["Microsoft was founded by Bill Gates."],
+                documents=["Microsoft was founded by Bill Gates."],
                 model_version="old"
             )
 
@@ -480,7 +480,7 @@ def callback(response):
             self.assertIsNotNone(response.statistics)
 
         res = text_analytics.recognize_entities(
-            inputs=["Bill Gates is the CEO of Microsoft."],
+            documents=["Bill Gates is the CEO of Microsoft."],
             model_version="latest",
             show_stats=True,
             language="es",
diff --git a/sdk/textanalytics/azure-ai-textanalytics/tests/test_recognize_entities_async.py b/sdk/textanalytics/azure-ai-textanalytics/tests/test_recognize_entities_async.py
index 3eebafdd3b265..6754a26ee43c0 100644
--- a/sdk/textanalytics/azure-ai-textanalytics/tests/test_recognize_entities_async.py
+++ b/sdk/textanalytics/azure-ai-textanalytics/tests/test_recognize_entities_async.py
@@ -151,7 +151,7 @@ async def test_bad_model_version(self, resource_group, location, text_analytics_
         text_analytics = TextAnalyticsClient(text_analytics_account, TextAnalyticsApiKeyCredential(text_analytics_account_key))
         with self.assertRaises(HttpResponseError):
             response = await text_analytics.recognize_entities(
-                inputs=["Microsoft was founded by Bill Gates."],
+                documents=["Microsoft was founded by Bill Gates."],
                 model_version="old"
             )
 
@@ -525,7 +525,7 @@ def callback(response):
             self.assertIsNotNone(response.statistics)
 
         res = await text_analytics.recognize_entities(
-            inputs=["Bill Gates is the CEO of Microsoft."],
+            documents=["Bill Gates is the CEO of Microsoft."],
             model_version="latest",
             show_stats=True,
             language="es",
diff --git a/sdk/textanalytics/azure-ai-textanalytics/tests/test_recognize_linked_entities.py b/sdk/textanalytics/azure-ai-textanalytics/tests/test_recognize_linked_entities.py
index 61826105d5936..68f79f8dfbd4f 100644
--- a/sdk/textanalytics/azure-ai-textanalytics/tests/test_recognize_linked_entities.py
+++ b/sdk/textanalytics/azure-ai-textanalytics/tests/test_recognize_linked_entities.py
@@ -123,7 +123,7 @@ def test_bad_model_version(self, resource_group, location, text_analytics_accoun
         text_analytics = TextAnalyticsClient(text_analytics_account, TextAnalyticsApiKeyCredential(text_analytics_account_key))
         with self.assertRaises(HttpResponseError):
             response = text_analytics.recognize_linked_entities(
-                inputs=["Microsoft was founded by Bill Gates."],
+                documents=["Microsoft was founded by Bill Gates."],
                 model_version="old"
             )
 
@@ -475,7 +475,7 @@ def callback(response):
             self.assertIsNotNone(response.statistics)
 
         res = text_analytics.recognize_linked_entities(
-            inputs=["Bill Gates is the CEO of Microsoft."],
+            documents=["Bill Gates is the CEO of Microsoft."],
             model_version="latest",
             show_stats=True,
             language="es",
diff --git a/sdk/textanalytics/azure-ai-textanalytics/tests/test_recognize_linked_entities_async.py b/sdk/textanalytics/azure-ai-textanalytics/tests/test_recognize_linked_entities_async.py
index 0a7b39ae52c68..904f3080a2ace 100644
--- a/sdk/textanalytics/azure-ai-textanalytics/tests/test_recognize_linked_entities_async.py
+++ b/sdk/textanalytics/azure-ai-textanalytics/tests/test_recognize_linked_entities_async.py
@@ -147,7 +147,7 @@ async def test_bad_model_version(self, resource_group, location, text_analytics_
         text_analytics = TextAnalyticsClient(text_analytics_account, TextAnalyticsApiKeyCredential(text_analytics_account_key))
         with self.assertRaises(HttpResponseError):
             response = await text_analytics.recognize_linked_entities(
-                inputs=["Microsoft was founded by Bill Gates."],
+                documents=["Microsoft was founded by Bill Gates."],
                 model_version="old"
             )
 
@@ -521,7 +521,7 @@ def callback(response):
             self.assertIsNotNone(response.statistics)
 
         res = await text_analytics.recognize_linked_entities(
-            inputs=["Bill Gates is the CEO of Microsoft."],
+            documents=["Bill Gates is the CEO of Microsoft."],
             model_version="latest",
             show_stats=True,
             language="es",
diff --git a/sdk/textanalytics/azure-ai-textanalytics/tests/test_recognize_pii_entities.py b/sdk/textanalytics/azure-ai-textanalytics/tests/test_recognize_pii_entities.py
index 97e5e7a987a75..7a2119e9c0eeb 100644
--- a/sdk/textanalytics/azure-ai-textanalytics/tests/test_recognize_pii_entities.py
+++ b/sdk/textanalytics/azure-ai-textanalytics/tests/test_recognize_pii_entities.py
@@ -150,7 +150,7 @@ def test_bad_model_version(self, resource_group, location, text_analytics_accoun
         text_analytics = TextAnalyticsClient(text_analytics_account, TextAnalyticsApiKeyCredential(text_analytics_account_key))
         with self.assertRaises(HttpResponseError):
             response = text_analytics.recognize_pii_entities(
-                inputs=["Microsoft was founded by Bill Gates."],
+                documents=["Microsoft was founded by Bill Gates."],
                 model_version="old"
             )
 
@@ -503,7 +503,7 @@ def callback(response):
             self.assertIsNotNone(response.statistics)
 
         res = text_analytics.recognize_pii_entities(
-            inputs=["Bill Gates is the CEO of Microsoft."],
+            documents=["Bill Gates is the CEO of Microsoft."],
             model_version="latest",
             show_stats=True,
             language="en",
diff --git a/sdk/textanalytics/azure-ai-textanalytics/tests/test_recognize_pii_entities_async.py b/sdk/textanalytics/azure-ai-textanalytics/tests/test_recognize_pii_entities_async.py
index 4255e895c722c..661ffefa2e33f 100644
--- a/sdk/textanalytics/azure-ai-textanalytics/tests/test_recognize_pii_entities_async.py
+++ b/sdk/textanalytics/azure-ai-textanalytics/tests/test_recognize_pii_entities_async.py
@@ -175,7 +175,7 @@ async def test_bad_model_version(self, resource_group, location, text_analytics_
         text_analytics = TextAnalyticsClient(text_analytics_account, TextAnalyticsApiKeyCredential(text_analytics_account_key))
         with self.assertRaises(HttpResponseError):
             response = await text_analytics.recognize_pii_entities(
-                inputs=["Microsoft was founded by Bill Gates."],
+                documents=["Microsoft was founded by Bill Gates."],
                 model_version="old"
             )
 
@@ -549,7 +549,7 @@ def callback(response):
             self.assertIsNotNone(response.statistics)
 
         res = await text_analytics.recognize_pii_entities(
-            inputs=["Bill Gates is the CEO of Microsoft."],
+            documents=["Bill Gates is the CEO of Microsoft."],
             model_version="latest",
             show_stats=True,
             language="en",
diff --git a/sdk/textanalytics/azure-ai-textanalytics/tests/test_text_analytics.py b/sdk/textanalytics/azure-ai-textanalytics/tests/test_text_analytics.py
index 0b229ecabcd47..0f30aca4c998a 100644
--- a/sdk/textanalytics/azure-ai-textanalytics/tests/test_text_analytics.py
+++ b/sdk/textanalytics/azure-ai-textanalytics/tests/test_text_analytics.py
@@ -18,7 +18,7 @@ def test_detect_language(self, resource_group, location, text_analytics_account,
         text_analytics = TextAnalyticsClient(text_analytics_account, TextAnalyticsApiKeyCredential(text_analytics_account_key))
 
         response = text_analytics.detect_language(
-            inputs=[{
+            documents=[{
                 'id': 1,
                 'text': 'I had a wonderful experience! The rooms were wonderful and the staff was helpful.'
             }]