diff --git a/sdk/documentintelligence/azure-ai-documentintelligence/_meta.json b/sdk/documentintelligence/azure-ai-documentintelligence/_meta.json
new file mode 100644
index 0000000000000..1c6d16b51ff53
--- /dev/null
+++ b/sdk/documentintelligence/azure-ai-documentintelligence/_meta.json
@@ -0,0 +1,6 @@
+{
+  "commit": "dd0459d5a8d99b8a15dcbc33fd5b7befe5494897",
+  "repository_url": "https://github.com/Azure/azure-rest-api-specs",
+  "typespec_src": "specification/ai/DocumentIntelligence",
+  "@azure-tools/typespec-python": "0.37.0"
+}
\ No newline at end of file
diff --git a/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/__init__.py b/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/__init__.py
index 5d62b4bb7381e..c474f6a4267ef 100644
--- a/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/__init__.py
+++ b/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/__init__.py
@@ -5,21 +5,30 @@
 # Code generated by Microsoft (R) Python Code Generator.
 # Changes may cause incorrect behavior and will be lost if the code is regenerated.
 # --------------------------------------------------------------------------
+# pylint: disable=wrong-import-position
 
-from ._patch import DocumentIntelligenceClient
-from ._patch import DocumentIntelligenceAdministrationClient
+from typing import TYPE_CHECKING
+
+if TYPE_CHECKING:
+    from ._patch import *  # pylint: disable=unused-wildcard-import
+
+from ._client import DocumentIntelligenceClient  # type: ignore
+from ._client import DocumentIntelligenceAdministrationClient  # type: ignore
 from ._version import VERSION
 
 __version__ = VERSION
 
-
-from ._patch import AnalyzeDocumentLROPoller
+try:
+    from ._patch import __all__ as _patch_all
+    from ._patch import *
+except ImportError:
+    _patch_all = []
 from ._patch import patch_sdk as _patch_sdk
 
 __all__ = [
-    "AnalyzeDocumentLROPoller",
     "DocumentIntelligenceClient",
     "DocumentIntelligenceAdministrationClient",
 ]
+__all__.extend([p for p in _patch_all if p not in __all__])  # pyright: ignore
 
 _patch_sdk()
diff --git a/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/_client.py b/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/_client.py
index a90c19d86ac25..a0fc5dce5b250 100644
--- a/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/_client.py
+++ b/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/_client.py
@@ -38,9 +38,8 @@ class DocumentIntelligenceClient(DocumentIntelligenceClientOperationsMixin):
      AzureKeyCredential type or a TokenCredential type. Required.
     :type credential: ~azure.core.credentials.AzureKeyCredential or
      ~azure.core.credentials.TokenCredential
-    :keyword api_version: The API version to use for this operation. Default value is
-     "2024-07-31-preview". Note that overriding this default value may result in unsupported
-     behavior.
+    :keyword api_version: The API version to use for this operation. Default value is "2024-11-30".
+     Note that overriding this default value may result in unsupported behavior.
     :paramtype api_version: str
     :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
      Retry-After header is present.
@@ -118,9 +117,8 @@ class DocumentIntelligenceAdministrationClient(DocumentIntelligenceAdministratio
      AzureKeyCredential type or a TokenCredential type. Required.
     :type credential: ~azure.core.credentials.AzureKeyCredential or
      ~azure.core.credentials.TokenCredential
-    :keyword api_version: The API version to use for this operation. Default value is
-     "2024-07-31-preview". Note that overriding this default value may result in unsupported
-     behavior.
+    :keyword api_version: The API version to use for this operation. Default value is "2024-11-30".
+     Note that overriding this default value may result in unsupported behavior.
     :paramtype api_version: str
     :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
      Retry-After header is present.
diff --git a/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/_configuration.py b/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/_configuration.py
index 2a0cd7b020894..791799f9cf288 100644
--- a/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/_configuration.py
+++ b/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/_configuration.py
@@ -29,14 +29,13 @@ class DocumentIntelligenceClientConfiguration:  # pylint: disable=too-many-insta
      AzureKeyCredential type or a TokenCredential type. Required.
     :type credential: ~azure.core.credentials.AzureKeyCredential or
      ~azure.core.credentials.TokenCredential
-    :keyword api_version: The API version to use for this operation. Default value is
-     "2024-07-31-preview". Note that overriding this default value may result in unsupported
-     behavior.
+    :keyword api_version: The API version to use for this operation. Default value is "2024-11-30".
+     Note that overriding this default value may result in unsupported behavior.
     :paramtype api_version: str
     """
 
     def __init__(self, endpoint: str, credential: Union[AzureKeyCredential, "TokenCredential"], **kwargs: Any) -> None:
-        api_version: str = kwargs.pop("api_version", "2024-07-31-preview")
+        api_version: str = kwargs.pop("api_version", "2024-11-30")
 
         if endpoint is None:
             raise ValueError("Parameter 'endpoint' must not be None.")
@@ -84,14 +83,13 @@ class DocumentIntelligenceAdministrationClientConfiguration:  # pylint: disable=
      AzureKeyCredential type or a TokenCredential type. Required.
     :type credential: ~azure.core.credentials.AzureKeyCredential or
      ~azure.core.credentials.TokenCredential
-    :keyword api_version: The API version to use for this operation. Default value is
-     "2024-07-31-preview". Note that overriding this default value may result in unsupported
-     behavior.
+    :keyword api_version: The API version to use for this operation. Default value is "2024-11-30".
+     Note that overriding this default value may result in unsupported behavior.
     :paramtype api_version: str
     """
 
     def __init__(self, endpoint: str, credential: Union[AzureKeyCredential, "TokenCredential"], **kwargs: Any) -> None:
-        api_version: str = kwargs.pop("api_version", "2024-07-31-preview")
+        api_version: str = kwargs.pop("api_version", "2024-11-30")
 
         if endpoint is None:
             raise ValueError("Parameter 'endpoint' must not be None.")
diff --git a/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/_model_base.py b/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/_model_base.py
index 9d401b0cf0120..7f73b97b23efa 100644
--- a/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/_model_base.py
+++ b/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/_model_base.py
@@ -5,7 +5,7 @@
 # Licensed under the MIT License. See License.txt in the project root for
 # license information.
 # --------------------------------------------------------------------------
-# pylint: disable=protected-access, arguments-differ, signature-differs, broad-except, too-many-lines
+# pylint: disable=protected-access, broad-except
 
 import copy
 import calendar
@@ -574,7 +574,7 @@ def __init__(self, *args: typing.Any, **kwargs: typing.Any) -> None:
     def copy(self) -> "Model":
         return Model(self.__dict__)
 
-    def __new__(cls, *args: typing.Any, **kwargs: typing.Any) -> Self:  # pylint: disable=unused-argument
+    def __new__(cls, *args: typing.Any, **kwargs: typing.Any) -> Self:
         if f"{cls.__module__}.{cls.__qualname__}" not in cls._calculated:
             # we know the last nine classes in mro are going to be 'Model', '_MyMutableMapping', 'MutableMapping',
             # 'Mapping', 'Collection', 'Sized', 'Iterable', 'Container' and 'object'
@@ -585,8 +585,8 @@ def __new__(cls, *args: typing.Any, **kwargs: typing.Any) -> Self:  # pylint: di
             annotations = {
                 k: v
                 for mro_class in mros
-                if hasattr(mro_class, "__annotations__")  # pylint: disable=no-member
-                for k, v in mro_class.__annotations__.items()  # pylint: disable=no-member
+                if hasattr(mro_class, "__annotations__")
+                for k, v in mro_class.__annotations__.items()
             }
             for attr, rf in attr_to_rest_field.items():
                 rf._module = cls.__module__
@@ -601,8 +601,8 @@ def __new__(cls, *args: typing.Any, **kwargs: typing.Any) -> Self:  # pylint: di
 
     def __init_subclass__(cls, discriminator: typing.Optional[str] = None) -> None:
         for base in cls.__bases__:
-            if hasattr(base, "__mapping__"):  # pylint: disable=no-member
-                base.__mapping__[discriminator or cls.__name__] = cls  # type: ignore  # pylint: disable=no-member
+            if hasattr(base, "__mapping__"):
+                base.__mapping__[discriminator or cls.__name__] = cls  # type: ignore
 
     @classmethod
     def _get_discriminator(cls, exist_discriminators) -> typing.Optional["_RestField"]:
@@ -613,7 +613,7 @@ def _get_discriminator(cls, exist_discriminators) -> typing.Optional["_RestField
 
     @classmethod
     def _deserialize(cls, data, exist_discriminators):
-        if not hasattr(cls, "__mapping__"):  # pylint: disable=no-member
+        if not hasattr(cls, "__mapping__"):
             return cls(data)
         discriminator = cls._get_discriminator(exist_discriminators)
         if discriminator is None:
@@ -633,7 +633,7 @@ def _deserialize(cls, data, exist_discriminators):
                 discriminator_value = data.find(xml_name).text  # pyright: ignore
         else:
             discriminator_value = data.get(discriminator._rest_name)
-        mapped_cls = cls.__mapping__.get(discriminator_value, cls)  # pyright: ignore # pylint: disable=no-member
+        mapped_cls = cls.__mapping__.get(discriminator_value, cls)  # pyright: ignore
         return mapped_cls._deserialize(data, exist_discriminators)
 
     def as_dict(self, *, exclude_readonly: bool = False) -> typing.Dict[str, typing.Any]:
@@ -754,7 +754,7 @@ def _get_deserialize_callable_from_annotation(  # pylint: disable=too-many-retur
         except AttributeError:
             model_name = annotation
         if module is not None:
-            annotation = _get_model(module, model_name)
+            annotation = _get_model(module, model_name)  # type: ignore
 
     try:
         if module and _is_model(annotation):
@@ -894,6 +894,22 @@ def _deserialize(
     return _deserialize_with_callable(deserializer, value)
 
 
+def _failsafe_deserialize(
+    deserializer: typing.Any,
+    value: typing.Any,
+    module: typing.Optional[str] = None,
+    rf: typing.Optional["_RestField"] = None,
+    format: typing.Optional[str] = None,
+) -> typing.Any:
+    try:
+        return _deserialize(deserializer, value, module, rf, format)
+    except DeserializationError:
+        _LOGGER.warning(
+            "Ran into a deserialization error. Ignoring since this is failsafe deserialization", exc_info=True
+        )
+        return None
+
+
 class _RestField:
     def __init__(
         self,
diff --git a/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/_operations/__init__.py b/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/_operations/__init__.py
index 98b551bb5d272..63b6bbb81ed80 100644
--- a/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/_operations/__init__.py
+++ b/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/_operations/__init__.py
@@ -5,15 +5,23 @@
 # Code generated by Microsoft (R) Python Code Generator.
 # Changes may cause incorrect behavior and will be lost if the code is regenerated.
 # --------------------------------------------------------------------------
+# pylint: disable=wrong-import-position
 
-from ._patch import DocumentIntelligenceClientOperationsMixin
-from ._patch import DocumentIntelligenceAdministrationClientOperationsMixin
+from typing import TYPE_CHECKING
 
+if TYPE_CHECKING:
+    from ._patch import *  # pylint: disable=unused-wildcard-import
 
+from ._operations import DocumentIntelligenceClientOperationsMixin  # type: ignore
+from ._operations import DocumentIntelligenceAdministrationClientOperationsMixin  # type: ignore
+
+from ._patch import __all__ as _patch_all
+from ._patch import *
 from ._patch import patch_sdk as _patch_sdk
 
 __all__ = [
     "DocumentIntelligenceClientOperationsMixin",
     "DocumentIntelligenceAdministrationClientOperationsMixin",
 ]
+__all__.extend([p for p in _patch_all if p not in __all__])  # pyright: ignore
 _patch_sdk()
diff --git a/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/_operations/_operations.py b/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/_operations/_operations.py
index 4e00f61ddfd27..fa4b890381eb6 100644
--- a/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/_operations/_operations.py
+++ b/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/_operations/_operations.py
@@ -31,7 +31,7 @@
 from azure.core.utils import case_insensitive_dict
 
 from .. import models as _models
-from .._model_base import SdkJSONEncoder, _deserialize
+from .._model_base import SdkJSONEncoder, _deserialize, _failsafe_deserialize
 from .._serialization import Serializer
 from .._vendor import DocumentIntelligenceAdministrationClientMixinABC, DocumentIntelligenceClientMixinABC
 
@@ -55,7 +55,7 @@ def build_document_intelligence_analyze_document_request(  # pylint: disable=nam
     string_index_type: Optional[Union[str, _models.StringIndexType]] = None,
     features: Optional[List[Union[str, _models.DocumentAnalysisFeature]]] = None,
     query_fields: Optional[List[str]] = None,
-    output_content_format: Optional[Union[str, _models.ContentFormat]] = None,
+    output_content_format: Optional[Union[str, _models.DocumentContentFormat]] = None,
     output: Optional[List[Union[str, _models.AnalyzeOutputOption]]] = None,
     **kwargs: Any,
 ) -> HttpRequest:
@@ -63,7 +63,7 @@ def build_document_intelligence_analyze_document_request(  # pylint: disable=nam
     _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
 
     content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("content-type", None))
-    api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2024-07-31-preview"))
+    api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2024-11-30"))
     accept = _headers.pop("Accept", "application/json")
 
     # Construct URL
@@ -99,6 +99,88 @@ def build_document_intelligence_analyze_document_request(  # pylint: disable=nam
     return HttpRequest(method="POST", url=_url, params=_params, headers=_headers, **kwargs)
 
 
+def build_document_intelligence_get_analyze_result_pdf_request(  # pylint: disable=name-too-long
+    model_id: str, result_id: str, **kwargs: Any
+) -> HttpRequest:
+    _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+    _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+    api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2024-11-30"))
+    accept = _headers.pop("Accept", "application/pdf")
+
+    # Construct URL
+    _url = "/documentModels/{modelId}/analyzeResults/{resultId}/pdf"
+    path_format_arguments = {
+        "modelId": _SERIALIZER.url("model_id", model_id, "str"),
+        "resultId": _SERIALIZER.url("result_id", result_id, "str"),
+    }
+
+    _url: str = _url.format(**path_format_arguments)  # type: ignore
+
+    # Construct parameters
+    _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+
+    # Construct headers
+    _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+    return HttpRequest(method="GET", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_document_intelligence_get_analyze_result_figure_request(  # pylint: disable=name-too-long
+    model_id: str, result_id: str, figure_id: str, **kwargs: Any
+) -> HttpRequest:
+    _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+    _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+    api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2024-11-30"))
+    accept = _headers.pop("Accept", "image/png")
+
+    # Construct URL
+    _url = "/documentModels/{modelId}/analyzeResults/{resultId}/figures/{figureId}"
+    path_format_arguments = {
+        "modelId": _SERIALIZER.url("model_id", model_id, "str"),
+        "resultId": _SERIALIZER.url("result_id", result_id, "str"),
+        "figureId": _SERIALIZER.url("figure_id", figure_id, "str"),
+    }
+
+    _url: str = _url.format(**path_format_arguments)  # type: ignore
+
+    # Construct parameters
+    _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+
+    # Construct headers
+    _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+    return HttpRequest(method="GET", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_document_intelligence_delete_analyze_result_request(  # pylint: disable=name-too-long
+    model_id: str, result_id: str, **kwargs: Any
+) -> HttpRequest:
+    _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+    _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+    api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2024-11-30"))
+    accept = _headers.pop("Accept", "application/json")
+
+    # Construct URL
+    _url = "/documentModels/{modelId}/analyzeResults/{resultId}"
+    path_format_arguments = {
+        "modelId": _SERIALIZER.url("model_id", model_id, "str"),
+        "resultId": _SERIALIZER.url("result_id", result_id, "str"),
+    }
+
+    _url: str = _url.format(**path_format_arguments)  # type: ignore
+
+    # Construct parameters
+    _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+
+    # Construct headers
+    _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+    return HttpRequest(method="DELETE", url=_url, params=_params, headers=_headers, **kwargs)
+
+
 def build_document_intelligence_analyze_batch_documents_request(  # pylint: disable=name-too-long
     model_id: str,
     *,
@@ -107,7 +189,7 @@ def build_document_intelligence_analyze_batch_documents_request(  # pylint: disa
     string_index_type: Optional[Union[str, _models.StringIndexType]] = None,
     features: Optional[List[Union[str, _models.DocumentAnalysisFeature]]] = None,
     query_fields: Optional[List[str]] = None,
-    output_content_format: Optional[Union[str, _models.ContentFormat]] = None,
+    output_content_format: Optional[Union[str, _models.DocumentContentFormat]] = None,
     output: Optional[List[Union[str, _models.AnalyzeOutputOption]]] = None,
     **kwargs: Any,
 ) -> HttpRequest:
@@ -115,7 +197,7 @@ def build_document_intelligence_analyze_batch_documents_request(  # pylint: disa
     _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
 
     content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("content-type", None))
-    api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2024-07-31-preview"))
+    api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2024-11-30"))
     accept = _headers.pop("Accept", "application/json")
 
     # Construct URL
@@ -151,17 +233,43 @@ def build_document_intelligence_analyze_batch_documents_request(  # pylint: disa
     return HttpRequest(method="POST", url=_url, params=_params, headers=_headers, **kwargs)
 
 
-def build_document_intelligence_get_analyze_result_pdf_request(  # pylint: disable=name-too-long
+def build_document_intelligence_list_analyze_batch_results_request(  # pylint: disable=name-too-long
+    model_id: str, **kwargs: Any
+) -> HttpRequest:
+    _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+    _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
+
+    api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2024-11-30"))
+    accept = _headers.pop("Accept", "application/json")
+
+    # Construct URL
+    _url = "/documentModels/{modelId}/analyzeBatchResults"
+    path_format_arguments = {
+        "modelId": _SERIALIZER.url("model_id", model_id, "str"),
+    }
+
+    _url: str = _url.format(**path_format_arguments)  # type: ignore
+
+    # Construct parameters
+    _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+
+    # Construct headers
+    _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+    return HttpRequest(method="GET", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_document_intelligence_delete_analyze_batch_result_request(  # pylint: disable=name-too-long
     model_id: str, result_id: str, **kwargs: Any
 ) -> HttpRequest:
     _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
     _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
 
-    api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2024-07-31-preview"))
-    accept = _headers.pop("Accept", "application/pdf")
+    api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2024-11-30"))
+    accept = _headers.pop("Accept", "application/json")
 
     # Construct URL
-    _url = "/documentModels/{modelId}/analyzeResults/{resultId}/pdf"
+    _url = "/documentModels/{modelId}/analyzeBatchResults/{resultId}"
     path_format_arguments = {
         "modelId": _SERIALIZER.url("model_id", model_id, "str"),
         "resultId": _SERIALIZER.url("result_id", result_id, "str"),
@@ -175,24 +283,23 @@ def build_document_intelligence_get_analyze_result_pdf_request(  # pylint: disab
     # Construct headers
     _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
 
-    return HttpRequest(method="GET", url=_url, params=_params, headers=_headers, **kwargs)
+    return HttpRequest(method="DELETE", url=_url, params=_params, headers=_headers, **kwargs)
 
 
-def build_document_intelligence_get_analyze_result_figure_request(  # pylint: disable=name-too-long
-    model_id: str, result_id: str, figure_id: str, **kwargs: Any
+def build_document_intelligence_get_analyze_batch_result_request(  # pylint: disable=name-too-long
+    model_id: str, result_id: str, **kwargs: Any
 ) -> HttpRequest:
     _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
     _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
 
-    api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2024-07-31-preview"))
-    accept = _headers.pop("Accept", "image/png")
+    api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2024-11-30"))
+    accept = _headers.pop("Accept", "application/json")
 
     # Construct URL
-    _url = "/documentModels/{modelId}/analyzeResults/{resultId}/figures/{figureId}"
+    _url = "/documentModels/{modelId}/analyzeBatchResults/{resultId}"
     path_format_arguments = {
         "modelId": _SERIALIZER.url("model_id", model_id, "str"),
         "resultId": _SERIALIZER.url("result_id", result_id, "str"),
-        "figureId": _SERIALIZER.url("figure_id", figure_id, "str"),
     }
 
     _url: str = _url.format(**path_format_arguments)  # type: ignore
@@ -218,7 +325,7 @@ def build_document_intelligence_classify_document_request(  # pylint: disable=na
     _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
 
     content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("content-type", None))
-    api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2024-07-31-preview"))
+    api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2024-11-30"))
     accept = _headers.pop("Accept", "application/json")
 
     # Construct URL
@@ -253,7 +360,7 @@ def build_document_intelligence_administration_build_document_model_request(  #
     _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
 
     content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
-    api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2024-07-31-preview"))
+    api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2024-11-30"))
     accept = _headers.pop("Accept", "application/json")
 
     # Construct URL
@@ -277,7 +384,7 @@ def build_document_intelligence_administration_compose_model_request(  # pylint:
     _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
 
     content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
-    api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2024-07-31-preview"))
+    api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2024-11-30"))
     accept = _headers.pop("Accept", "application/json")
 
     # Construct URL
@@ -301,7 +408,7 @@ def build_document_intelligence_administration_authorize_model_copy_request(  #
     _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
 
     content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
-    api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2024-07-31-preview"))
+    api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2024-11-30"))
     accept = _headers.pop("Accept", "application/json")
 
     # Construct URL
@@ -325,7 +432,7 @@ def build_document_intelligence_administration_copy_model_to_request(  # pylint:
     _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
 
     content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
-    api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2024-07-31-preview"))
+    api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2024-11-30"))
     accept = _headers.pop("Accept", "application/json")
 
     # Construct URL
@@ -353,7 +460,7 @@ def build_document_intelligence_administration_get_model_request(  # pylint: dis
     _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
     _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
 
-    api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2024-07-31-preview"))
+    api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2024-11-30"))
     accept = _headers.pop("Accept", "application/json")
 
     # Construct URL
@@ -379,7 +486,7 @@ def build_document_intelligence_administration_list_models_request(  # pylint: d
     _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
     _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
 
-    api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2024-07-31-preview"))
+    api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2024-11-30"))
     accept = _headers.pop("Accept", "application/json")
 
     # Construct URL
@@ -400,7 +507,7 @@ def build_document_intelligence_administration_delete_model_request(  # pylint:
     _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
     _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
 
-    api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2024-07-31-preview"))
+    api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2024-11-30"))
     accept = _headers.pop("Accept", "application/json")
 
     # Construct URL
@@ -420,13 +527,13 @@ def build_document_intelligence_administration_delete_model_request(  # pylint:
     return HttpRequest(method="DELETE", url=_url, params=_params, headers=_headers, **kwargs)
 
 
-def build_document_intelligence_administration_get_resource_info_request(  # pylint: disable=name-too-long
+def build_document_intelligence_administration_get_resource_details_request(  # pylint: disable=name-too-long
     **kwargs: Any,
 ) -> HttpRequest:
     _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
     _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
 
-    api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2024-07-31-preview"))
+    api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2024-11-30"))
     accept = _headers.pop("Accept", "application/json")
 
     # Construct URL
@@ -447,7 +554,7 @@ def build_document_intelligence_administration_get_operation_request(  # pylint:
     _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
     _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
 
-    api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2024-07-31-preview"))
+    api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2024-11-30"))
     accept = _headers.pop("Accept", "application/json")
 
     # Construct URL
@@ -473,7 +580,7 @@ def build_document_intelligence_administration_list_operations_request(  # pylin
     _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
     _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
 
-    api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2024-07-31-preview"))
+    api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2024-11-30"))
     accept = _headers.pop("Accept", "application/json")
 
     # Construct URL
@@ -495,7 +602,7 @@ def build_document_intelligence_administration_build_classifier_request(  # pyli
     _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
 
     content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
-    api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2024-07-31-preview"))
+    api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2024-11-30"))
     accept = _headers.pop("Accept", "application/json")
 
     # Construct URL
@@ -519,7 +626,7 @@ def build_document_intelligence_administration_authorize_classifier_copy_request
     _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
 
     content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
-    api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2024-07-31-preview"))
+    api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2024-11-30"))
     accept = _headers.pop("Accept", "application/json")
 
     # Construct URL
@@ -543,7 +650,7 @@ def build_document_intelligence_administration_copy_classifier_to_request(  # py
     _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
 
     content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
-    api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2024-07-31-preview"))
+    api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2024-11-30"))
     accept = _headers.pop("Accept", "application/json")
 
     # Construct URL
@@ -571,7 +678,7 @@ def build_document_intelligence_administration_get_classifier_request(  # pylint
     _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
     _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
 
-    api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2024-07-31-preview"))
+    api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2024-11-30"))
     accept = _headers.pop("Accept", "application/json")
 
     # Construct URL
@@ -597,7 +704,7 @@ def build_document_intelligence_administration_list_classifiers_request(  # pyli
     _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
     _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
 
-    api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2024-07-31-preview"))
+    api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2024-11-30"))
     accept = _headers.pop("Accept", "application/json")
 
     # Construct URL
@@ -618,7 +725,7 @@ def build_document_intelligence_administration_delete_classifier_request(  # pyl
     _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
     _params = case_insensitive_dict(kwargs.pop("params", {}) or {})
 
-    api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2024-07-31-preview"))
+    api_version: str = kwargs.pop("api_version", _params.pop("api-version", "2024-11-30"))
     accept = _headers.pop("Accept", "application/json")
 
     # Construct URL
@@ -643,14 +750,14 @@ class DocumentIntelligenceClientOperationsMixin(DocumentIntelligenceClientMixinA
     def _analyze_document_initial(
         self,
         model_id: str,
-        analyze_request: Optional[Union[_models.AnalyzeDocumentRequest, JSON, IO[bytes]]] = None,
+        body: Union[_models.AnalyzeDocumentRequest, JSON, IO[bytes]],
         *,
         pages: Optional[str] = None,
         locale: Optional[str] = None,
         string_index_type: Optional[Union[str, _models.StringIndexType]] = None,
         features: Optional[List[Union[str, _models.DocumentAnalysisFeature]]] = None,
         query_fields: Optional[List[str]] = None,
-        output_content_format: Optional[Union[str, _models.ContentFormat]] = None,
+        output_content_format: Optional[Union[str, _models.DocumentContentFormat]] = None,
         output: Optional[List[Union[str, _models.AnalyzeOutputOption]]] = None,
         **kwargs: Any,
     ) -> Iterator[bytes]:
@@ -670,13 +777,10 @@ def _analyze_document_initial(
 
         content_type = content_type or "application/json"
         _content = None
-        if isinstance(analyze_request, (IOBase, bytes)):
-            _content = analyze_request
+        if isinstance(body, (IOBase, bytes)):
+            _content = body
         else:
-            if analyze_request is not None:
-                _content = json.dumps(analyze_request, cls=SdkJSONEncoder, exclude_readonly=True)  # type: ignore
-            else:
-                _content = None
+            _content = json.dumps(body, cls=SdkJSONEncoder, exclude_readonly=True)  # type: ignore
 
         _request = build_document_intelligence_analyze_document_request(
             model_id=model_id,
@@ -711,7 +815,7 @@ def _analyze_document_initial(
             except (StreamConsumedError, StreamClosedError):
                 pass
             map_error(status_code=response.status_code, response=response, error_map=error_map)
-            error = _deserialize(_models.ErrorResponse, response.json())
+            error = _failsafe_deserialize(_models.DocumentIntelligenceErrorResponse, response.json())
             raise HttpResponseError(response=response, model=error)
 
         response_headers = {}
@@ -729,14 +833,14 @@ def _analyze_document_initial(
     def begin_analyze_document(
         self,
         model_id: str,
-        analyze_request: Optional[_models.AnalyzeDocumentRequest] = None,
+        body: _models.AnalyzeDocumentRequest,
         *,
         pages: Optional[str] = None,
         locale: Optional[str] = None,
         string_index_type: Optional[Union[str, _models.StringIndexType]] = None,
         features: Optional[List[Union[str, _models.DocumentAnalysisFeature]]] = None,
         query_fields: Optional[List[str]] = None,
-        output_content_format: Optional[Union[str, _models.ContentFormat]] = None,
+        output_content_format: Optional[Union[str, _models.DocumentContentFormat]] = None,
         output: Optional[List[Union[str, _models.AnalyzeOutputOption]]] = None,
         content_type: str = "application/json",
         **kwargs: Any,
@@ -745,10 +849,9 @@ def begin_analyze_document(
 
         :param model_id: Unique document model name. Required.
         :type model_id: str
-        :param analyze_request: Analyze request parameters. Default value is None.
-        :type analyze_request: ~azure.ai.documentintelligence.models.AnalyzeDocumentRequest
-        :keyword pages: Range of 1-based page numbers to analyze.  Ex. "1-3,5,7-9". Default value is
-         None.
+        :param body: Analyze request parameters. Required.
+        :type body: ~azure.ai.documentintelligence.models.AnalyzeDocumentRequest
+        :keyword pages: 1-based page numbers to analyze.  Ex. "1-3,5,7-9". Default value is None.
         :paramtype pages: str
         :keyword locale: Locale hint for text recognition and document analysis.  Value may contain
          only
@@ -765,7 +868,8 @@ def begin_analyze_document(
         :paramtype query_fields: list[str]
         :keyword output_content_format: Format of the analyze result top-level content. Known values
          are: "text" and "markdown". Default value is None.
-        :paramtype output_content_format: str or ~azure.ai.documentintelligence.models.ContentFormat
+        :paramtype output_content_format: str or
+         ~azure.ai.documentintelligence.models.DocumentContentFormat
         :keyword output: Additional outputs to generate during analysis. Default value is None.
         :paramtype output: list[str or ~azure.ai.documentintelligence.models.AnalyzeOutputOption]
         :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
@@ -781,14 +885,14 @@ def begin_analyze_document(
     def begin_analyze_document(
         self,
         model_id: str,
-        analyze_request: Optional[JSON] = None,
+        body: JSON,
         *,
         pages: Optional[str] = None,
         locale: Optional[str] = None,
         string_index_type: Optional[Union[str, _models.StringIndexType]] = None,
         features: Optional[List[Union[str, _models.DocumentAnalysisFeature]]] = None,
         query_fields: Optional[List[str]] = None,
-        output_content_format: Optional[Union[str, _models.ContentFormat]] = None,
+        output_content_format: Optional[Union[str, _models.DocumentContentFormat]] = None,
         output: Optional[List[Union[str, _models.AnalyzeOutputOption]]] = None,
         content_type: str = "application/json",
         **kwargs: Any,
@@ -797,10 +901,9 @@ def begin_analyze_document(
 
         :param model_id: Unique document model name. Required.
         :type model_id: str
-        :param analyze_request: Analyze request parameters. Default value is None.
-        :type analyze_request: JSON
-        :keyword pages: Range of 1-based page numbers to analyze.  Ex. "1-3,5,7-9". Default value is
-         None.
+        :param body: Analyze request parameters. Required.
+        :type body: JSON
+        :keyword pages: 1-based page numbers to analyze.  Ex. "1-3,5,7-9". Default value is None.
         :paramtype pages: str
         :keyword locale: Locale hint for text recognition and document analysis.  Value may contain
          only
@@ -817,7 +920,8 @@ def begin_analyze_document(
         :paramtype query_fields: list[str]
         :keyword output_content_format: Format of the analyze result top-level content. Known values
          are: "text" and "markdown". Default value is None.
-        :paramtype output_content_format: str or ~azure.ai.documentintelligence.models.ContentFormat
+        :paramtype output_content_format: str or
+         ~azure.ai.documentintelligence.models.DocumentContentFormat
         :keyword output: Additional outputs to generate during analysis. Default value is None.
         :paramtype output: list[str or ~azure.ai.documentintelligence.models.AnalyzeOutputOption]
         :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
@@ -833,14 +937,14 @@ def begin_analyze_document(
     def begin_analyze_document(
         self,
         model_id: str,
-        analyze_request: Optional[IO[bytes]] = None,
+        body: IO[bytes],
         *,
         pages: Optional[str] = None,
         locale: Optional[str] = None,
         string_index_type: Optional[Union[str, _models.StringIndexType]] = None,
         features: Optional[List[Union[str, _models.DocumentAnalysisFeature]]] = None,
         query_fields: Optional[List[str]] = None,
-        output_content_format: Optional[Union[str, _models.ContentFormat]] = None,
+        output_content_format: Optional[Union[str, _models.DocumentContentFormat]] = None,
         output: Optional[List[Union[str, _models.AnalyzeOutputOption]]] = None,
         content_type: str = "application/json",
         **kwargs: Any,
@@ -849,10 +953,9 @@ def begin_analyze_document(
 
         :param model_id: Unique document model name. Required.
         :type model_id: str
-        :param analyze_request: Analyze request parameters. Default value is None.
-        :type analyze_request: IO[bytes]
-        :keyword pages: Range of 1-based page numbers to analyze.  Ex. "1-3,5,7-9". Default value is
-         None.
+        :param body: Analyze request parameters. Required.
+        :type body: IO[bytes]
+        :keyword pages: 1-based page numbers to analyze.  Ex. "1-3,5,7-9". Default value is None.
         :paramtype pages: str
         :keyword locale: Locale hint for text recognition and document analysis.  Value may contain
          only
@@ -869,7 +972,8 @@ def begin_analyze_document(
         :paramtype query_fields: list[str]
         :keyword output_content_format: Format of the analyze result top-level content. Known values
          are: "text" and "markdown". Default value is None.
-        :paramtype output_content_format: str or ~azure.ai.documentintelligence.models.ContentFormat
+        :paramtype output_content_format: str or
+         ~azure.ai.documentintelligence.models.DocumentContentFormat
         :keyword output: Additional outputs to generate during analysis. Default value is None.
         :paramtype output: list[str or ~azure.ai.documentintelligence.models.AnalyzeOutputOption]
         :keyword content_type: Body Parameter content-type. Content type parameter for binary body.
@@ -885,14 +989,14 @@ def begin_analyze_document(
     def begin_analyze_document(
         self,
         model_id: str,
-        analyze_request: Optional[Union[_models.AnalyzeDocumentRequest, JSON, IO[bytes]]] = None,
+        body: Union[_models.AnalyzeDocumentRequest, JSON, IO[bytes]],
         *,
         pages: Optional[str] = None,
         locale: Optional[str] = None,
         string_index_type: Optional[Union[str, _models.StringIndexType]] = None,
         features: Optional[List[Union[str, _models.DocumentAnalysisFeature]]] = None,
         query_fields: Optional[List[str]] = None,
-        output_content_format: Optional[Union[str, _models.ContentFormat]] = None,
+        output_content_format: Optional[Union[str, _models.DocumentContentFormat]] = None,
         output: Optional[List[Union[str, _models.AnalyzeOutputOption]]] = None,
         **kwargs: Any,
     ) -> LROPoller[_models.AnalyzeResult]:
@@ -900,12 +1004,10 @@ def begin_analyze_document(
 
         :param model_id: Unique document model name. Required.
         :type model_id: str
-        :param analyze_request: Analyze request parameters. Is one of the following types:
-         AnalyzeDocumentRequest, JSON, IO[bytes] Default value is None.
-        :type analyze_request: ~azure.ai.documentintelligence.models.AnalyzeDocumentRequest or JSON or
-         IO[bytes]
-        :keyword pages: Range of 1-based page numbers to analyze.  Ex. "1-3,5,7-9". Default value is
-         None.
+        :param body: Analyze request parameters. Is one of the following types: AnalyzeDocumentRequest,
+         JSON, IO[bytes] Required.
+        :type body: ~azure.ai.documentintelligence.models.AnalyzeDocumentRequest or JSON or IO[bytes]
+        :keyword pages: 1-based page numbers to analyze.  Ex. "1-3,5,7-9". Default value is None.
         :paramtype pages: str
         :keyword locale: Locale hint for text recognition and document analysis.  Value may contain
          only
@@ -922,7 +1024,8 @@ def begin_analyze_document(
         :paramtype query_fields: list[str]
         :keyword output_content_format: Format of the analyze result top-level content. Known values
          are: "text" and "markdown". Default value is None.
-        :paramtype output_content_format: str or ~azure.ai.documentintelligence.models.ContentFormat
+        :paramtype output_content_format: str or
+         ~azure.ai.documentintelligence.models.DocumentContentFormat
         :keyword output: Additional outputs to generate during analysis. Default value is None.
         :paramtype output: list[str or ~azure.ai.documentintelligence.models.AnalyzeOutputOption]
         :return: An instance of LROPoller that returns AnalyzeResult. The AnalyzeResult is compatible
@@ -941,7 +1044,7 @@ def begin_analyze_document(
         if cont_token is None:
             raw_result = self._analyze_document_initial(
                 model_id=model_id,
-                analyze_request=analyze_request,
+                body=body,
                 pages=pages,
                 locale=locale,
                 string_index_type=string_index_type,
@@ -994,17 +1097,204 @@ def get_long_running_output(pipeline_response):
             self._client, raw_result, get_long_running_output, polling_method  # type: ignore
         )
 
+    @distributed_trace
+    def get_analyze_result_pdf(self, model_id: str, result_id: str, **kwargs: Any) -> Iterator[bytes]:
+        """Gets the generated searchable PDF output from document analysis.
+
+        :param model_id: Unique document model name. Required.
+        :type model_id: str
+        :param result_id: Analyze operation result ID. Required.
+        :type result_id: str
+        :return: Iterator[bytes]
+        :rtype: Iterator[bytes]
+        :raises ~azure.core.exceptions.HttpResponseError:
+        """
+        error_map: MutableMapping = {
+            401: ClientAuthenticationError,
+            404: ResourceNotFoundError,
+            409: ResourceExistsError,
+            304: ResourceNotModifiedError,
+        }
+        error_map.update(kwargs.pop("error_map", {}) or {})
+
+        _headers = kwargs.pop("headers", {}) or {}
+        _params = kwargs.pop("params", {}) or {}
+
+        cls: ClsType[Iterator[bytes]] = kwargs.pop("cls", None)
+
+        _request = build_document_intelligence_get_analyze_result_pdf_request(
+            model_id=model_id,
+            result_id=result_id,
+            api_version=self._config.api_version,
+            headers=_headers,
+            params=_params,
+        )
+        path_format_arguments = {
+            "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str", skip_quote=True),
+        }
+        _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+        _stream = kwargs.pop("stream", True)
+        pipeline_response: PipelineResponse = self._client._pipeline.run(  # pylint: disable=protected-access
+            _request, stream=_stream, **kwargs
+        )
+
+        response = pipeline_response.http_response
+
+        if response.status_code not in [200]:
+            if _stream:
+                try:
+                    response.read()  # Load the body in memory and close the socket
+                except (StreamConsumedError, StreamClosedError):
+                    pass
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            error = _failsafe_deserialize(_models.DocumentIntelligenceErrorResponse, response.json())
+            raise HttpResponseError(response=response, model=error)
+
+        response_headers = {}
+        response_headers["content-type"] = self._deserialize("str", response.headers.get("content-type"))
+
+        deserialized = response.iter_bytes()
+
+        if cls:
+            return cls(pipeline_response, deserialized, response_headers)  # type: ignore
+
+        return deserialized  # type: ignore
+
+    @distributed_trace
+    def get_analyze_result_figure(
+        self, model_id: str, result_id: str, figure_id: str, **kwargs: Any
+    ) -> Iterator[bytes]:
+        """Gets the generated cropped image of specified figure from document analysis.
+
+        :param model_id: Unique document model name. Required.
+        :type model_id: str
+        :param result_id: Analyze operation result ID. Required.
+        :type result_id: str
+        :param figure_id: Figure ID. Required.
+        :type figure_id: str
+        :return: Iterator[bytes]
+        :rtype: Iterator[bytes]
+        :raises ~azure.core.exceptions.HttpResponseError:
+        """
+        error_map: MutableMapping = {
+            401: ClientAuthenticationError,
+            404: ResourceNotFoundError,
+            409: ResourceExistsError,
+            304: ResourceNotModifiedError,
+        }
+        error_map.update(kwargs.pop("error_map", {}) or {})
+
+        _headers = kwargs.pop("headers", {}) or {}
+        _params = kwargs.pop("params", {}) or {}
+
+        cls: ClsType[Iterator[bytes]] = kwargs.pop("cls", None)
+
+        _request = build_document_intelligence_get_analyze_result_figure_request(
+            model_id=model_id,
+            result_id=result_id,
+            figure_id=figure_id,
+            api_version=self._config.api_version,
+            headers=_headers,
+            params=_params,
+        )
+        path_format_arguments = {
+            "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str", skip_quote=True),
+        }
+        _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+        _stream = kwargs.pop("stream", True)
+        pipeline_response: PipelineResponse = self._client._pipeline.run(  # pylint: disable=protected-access
+            _request, stream=_stream, **kwargs
+        )
+
+        response = pipeline_response.http_response
+
+        if response.status_code not in [200]:
+            if _stream:
+                try:
+                    response.read()  # Load the body in memory and close the socket
+                except (StreamConsumedError, StreamClosedError):
+                    pass
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            error = _failsafe_deserialize(_models.DocumentIntelligenceErrorResponse, response.json())
+            raise HttpResponseError(response=response, model=error)
+
+        response_headers = {}
+        response_headers["content-type"] = self._deserialize("str", response.headers.get("content-type"))
+
+        deserialized = response.iter_bytes()
+
+        if cls:
+            return cls(pipeline_response, deserialized, response_headers)  # type: ignore
+
+        return deserialized  # type: ignore
+
+    @distributed_trace
+    def delete_analyze_result(  # pylint: disable=inconsistent-return-statements
+        self, model_id: str, result_id: str, **kwargs: Any
+    ) -> None:
+        """Mark the result of document analysis for deletion.
+
+        :param model_id: Unique document model name. Required.
+        :type model_id: str
+        :param result_id: Analyze operation result ID. Required.
+        :type result_id: str
+        :return: None
+        :rtype: None
+        :raises ~azure.core.exceptions.HttpResponseError:
+        """
+        error_map: MutableMapping = {
+            401: ClientAuthenticationError,
+            404: ResourceNotFoundError,
+            409: ResourceExistsError,
+            304: ResourceNotModifiedError,
+        }
+        error_map.update(kwargs.pop("error_map", {}) or {})
+
+        _headers = kwargs.pop("headers", {}) or {}
+        _params = kwargs.pop("params", {}) or {}
+
+        cls: ClsType[None] = kwargs.pop("cls", None)
+
+        _request = build_document_intelligence_delete_analyze_result_request(
+            model_id=model_id,
+            result_id=result_id,
+            api_version=self._config.api_version,
+            headers=_headers,
+            params=_params,
+        )
+        path_format_arguments = {
+            "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str", skip_quote=True),
+        }
+        _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+        _stream = False
+        pipeline_response: PipelineResponse = self._client._pipeline.run(  # pylint: disable=protected-access
+            _request, stream=_stream, **kwargs
+        )
+
+        response = pipeline_response.http_response
+
+        if response.status_code not in [204]:
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            error = _failsafe_deserialize(_models.DocumentIntelligenceErrorResponse, response.json())
+            raise HttpResponseError(response=response, model=error)
+
+        if cls:
+            return cls(pipeline_response, None, {})  # type: ignore
+
     def _analyze_batch_documents_initial(
         self,
         model_id: str,
-        analyze_batch_request: Optional[Union[_models.AnalyzeBatchDocumentsRequest, JSON, IO[bytes]]] = None,
+        body: Union[_models.AnalyzeBatchDocumentsRequest, JSON, IO[bytes]],
         *,
         pages: Optional[str] = None,
         locale: Optional[str] = None,
         string_index_type: Optional[Union[str, _models.StringIndexType]] = None,
         features: Optional[List[Union[str, _models.DocumentAnalysisFeature]]] = None,
         query_fields: Optional[List[str]] = None,
-        output_content_format: Optional[Union[str, _models.ContentFormat]] = None,
+        output_content_format: Optional[Union[str, _models.DocumentContentFormat]] = None,
         output: Optional[List[Union[str, _models.AnalyzeOutputOption]]] = None,
         **kwargs: Any,
     ) -> Iterator[bytes]:
@@ -1024,13 +1314,10 @@ def _analyze_batch_documents_initial(
 
         content_type = content_type or "application/json"
         _content = None
-        if isinstance(analyze_batch_request, (IOBase, bytes)):
-            _content = analyze_batch_request
+        if isinstance(body, (IOBase, bytes)):
+            _content = body
         else:
-            if analyze_batch_request is not None:
-                _content = json.dumps(analyze_batch_request, cls=SdkJSONEncoder, exclude_readonly=True)  # type: ignore
-            else:
-                _content = None
+            _content = json.dumps(body, cls=SdkJSONEncoder, exclude_readonly=True)  # type: ignore
 
         _request = build_document_intelligence_analyze_batch_documents_request(
             model_id=model_id,
@@ -1065,7 +1352,7 @@ def _analyze_batch_documents_initial(
             except (StreamConsumedError, StreamClosedError):
                 pass
             map_error(status_code=response.status_code, response=response, error_map=error_map)
-            error = _deserialize(_models.ErrorResponse, response.json())
+            error = _failsafe_deserialize(_models.DocumentIntelligenceErrorResponse, response.json())
             raise HttpResponseError(response=response, model=error)
 
         response_headers = {}
@@ -1083,14 +1370,14 @@ def _analyze_batch_documents_initial(
     def begin_analyze_batch_documents(
         self,
         model_id: str,
-        analyze_batch_request: Optional[_models.AnalyzeBatchDocumentsRequest] = None,
+        body: _models.AnalyzeBatchDocumentsRequest,
         *,
         pages: Optional[str] = None,
         locale: Optional[str] = None,
         string_index_type: Optional[Union[str, _models.StringIndexType]] = None,
         features: Optional[List[Union[str, _models.DocumentAnalysisFeature]]] = None,
         query_fields: Optional[List[str]] = None,
-        output_content_format: Optional[Union[str, _models.ContentFormat]] = None,
+        output_content_format: Optional[Union[str, _models.DocumentContentFormat]] = None,
         output: Optional[List[Union[str, _models.AnalyzeOutputOption]]] = None,
         content_type: str = "application/json",
         **kwargs: Any,
@@ -1099,10 +1386,9 @@ def begin_analyze_batch_documents(
 
         :param model_id: Unique document model name. Required.
         :type model_id: str
-        :param analyze_batch_request: Analyze batch request parameters. Default value is None.
-        :type analyze_batch_request: ~azure.ai.documentintelligence.models.AnalyzeBatchDocumentsRequest
-        :keyword pages: Range of 1-based page numbers to analyze.  Ex. "1-3,5,7-9". Default value is
-         None.
+        :param body: Analyze batch request parameters. Required.
+        :type body: ~azure.ai.documentintelligence.models.AnalyzeBatchDocumentsRequest
+        :keyword pages: 1-based page numbers to analyze.  Ex. "1-3,5,7-9". Default value is None.
         :paramtype pages: str
         :keyword locale: Locale hint for text recognition and document analysis.  Value may contain
          only
@@ -1119,7 +1405,8 @@ def begin_analyze_batch_documents(
         :paramtype query_fields: list[str]
         :keyword output_content_format: Format of the analyze result top-level content. Known values
          are: "text" and "markdown". Default value is None.
-        :paramtype output_content_format: str or ~azure.ai.documentintelligence.models.ContentFormat
+        :paramtype output_content_format: str or
+         ~azure.ai.documentintelligence.models.DocumentContentFormat
         :keyword output: Additional outputs to generate during analysis. Default value is None.
         :paramtype output: list[str or ~azure.ai.documentintelligence.models.AnalyzeOutputOption]
         :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
@@ -1135,14 +1422,14 @@ def begin_analyze_batch_documents(
     def begin_analyze_batch_documents(
         self,
         model_id: str,
-        analyze_batch_request: Optional[JSON] = None,
+        body: JSON,
         *,
         pages: Optional[str] = None,
         locale: Optional[str] = None,
         string_index_type: Optional[Union[str, _models.StringIndexType]] = None,
         features: Optional[List[Union[str, _models.DocumentAnalysisFeature]]] = None,
         query_fields: Optional[List[str]] = None,
-        output_content_format: Optional[Union[str, _models.ContentFormat]] = None,
+        output_content_format: Optional[Union[str, _models.DocumentContentFormat]] = None,
         output: Optional[List[Union[str, _models.AnalyzeOutputOption]]] = None,
         content_type: str = "application/json",
         **kwargs: Any,
@@ -1151,10 +1438,9 @@ def begin_analyze_batch_documents(
 
         :param model_id: Unique document model name. Required.
         :type model_id: str
-        :param analyze_batch_request: Analyze batch request parameters. Default value is None.
-        :type analyze_batch_request: JSON
-        :keyword pages: Range of 1-based page numbers to analyze.  Ex. "1-3,5,7-9". Default value is
-         None.
+        :param body: Analyze batch request parameters. Required.
+        :type body: JSON
+        :keyword pages: 1-based page numbers to analyze.  Ex. "1-3,5,7-9". Default value is None.
         :paramtype pages: str
         :keyword locale: Locale hint for text recognition and document analysis.  Value may contain
          only
@@ -1171,7 +1457,8 @@ def begin_analyze_batch_documents(
         :paramtype query_fields: list[str]
         :keyword output_content_format: Format of the analyze result top-level content. Known values
          are: "text" and "markdown". Default value is None.
-        :paramtype output_content_format: str or ~azure.ai.documentintelligence.models.ContentFormat
+        :paramtype output_content_format: str or
+         ~azure.ai.documentintelligence.models.DocumentContentFormat
         :keyword output: Additional outputs to generate during analysis. Default value is None.
         :paramtype output: list[str or ~azure.ai.documentintelligence.models.AnalyzeOutputOption]
         :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
@@ -1187,14 +1474,14 @@ def begin_analyze_batch_documents(
     def begin_analyze_batch_documents(
         self,
         model_id: str,
-        analyze_batch_request: Optional[IO[bytes]] = None,
+        body: IO[bytes],
         *,
         pages: Optional[str] = None,
         locale: Optional[str] = None,
         string_index_type: Optional[Union[str, _models.StringIndexType]] = None,
         features: Optional[List[Union[str, _models.DocumentAnalysisFeature]]] = None,
         query_fields: Optional[List[str]] = None,
-        output_content_format: Optional[Union[str, _models.ContentFormat]] = None,
+        output_content_format: Optional[Union[str, _models.DocumentContentFormat]] = None,
         output: Optional[List[Union[str, _models.AnalyzeOutputOption]]] = None,
         content_type: str = "application/json",
         **kwargs: Any,
@@ -1203,10 +1490,9 @@ def begin_analyze_batch_documents(
 
         :param model_id: Unique document model name. Required.
         :type model_id: str
-        :param analyze_batch_request: Analyze batch request parameters. Default value is None.
-        :type analyze_batch_request: IO[bytes]
-        :keyword pages: Range of 1-based page numbers to analyze.  Ex. "1-3,5,7-9". Default value is
-         None.
+        :param body: Analyze batch request parameters. Required.
+        :type body: IO[bytes]
+        :keyword pages: 1-based page numbers to analyze.  Ex. "1-3,5,7-9". Default value is None.
         :paramtype pages: str
         :keyword locale: Locale hint for text recognition and document analysis.  Value may contain
          only
@@ -1223,7 +1509,8 @@ def begin_analyze_batch_documents(
         :paramtype query_fields: list[str]
         :keyword output_content_format: Format of the analyze result top-level content. Known values
          are: "text" and "markdown". Default value is None.
-        :paramtype output_content_format: str or ~azure.ai.documentintelligence.models.ContentFormat
+        :paramtype output_content_format: str or
+         ~azure.ai.documentintelligence.models.DocumentContentFormat
         :keyword output: Additional outputs to generate during analysis. Default value is None.
         :paramtype output: list[str or ~azure.ai.documentintelligence.models.AnalyzeOutputOption]
         :keyword content_type: Body Parameter content-type. Content type parameter for binary body.
@@ -1239,14 +1526,14 @@ def begin_analyze_batch_documents(
     def begin_analyze_batch_documents(
         self,
         model_id: str,
-        analyze_batch_request: Optional[Union[_models.AnalyzeBatchDocumentsRequest, JSON, IO[bytes]]] = None,
+        body: Union[_models.AnalyzeBatchDocumentsRequest, JSON, IO[bytes]],
         *,
         pages: Optional[str] = None,
         locale: Optional[str] = None,
         string_index_type: Optional[Union[str, _models.StringIndexType]] = None,
         features: Optional[List[Union[str, _models.DocumentAnalysisFeature]]] = None,
         query_fields: Optional[List[str]] = None,
-        output_content_format: Optional[Union[str, _models.ContentFormat]] = None,
+        output_content_format: Optional[Union[str, _models.DocumentContentFormat]] = None,
         output: Optional[List[Union[str, _models.AnalyzeOutputOption]]] = None,
         **kwargs: Any,
     ) -> LROPoller[_models.AnalyzeBatchResult]:
@@ -1254,12 +1541,11 @@ def begin_analyze_batch_documents(
 
         :param model_id: Unique document model name. Required.
         :type model_id: str
-        :param analyze_batch_request: Analyze batch request parameters. Is one of the following types:
-         AnalyzeBatchDocumentsRequest, JSON, IO[bytes] Default value is None.
-        :type analyze_batch_request: ~azure.ai.documentintelligence.models.AnalyzeBatchDocumentsRequest
-         or JSON or IO[bytes]
-        :keyword pages: Range of 1-based page numbers to analyze.  Ex. "1-3,5,7-9". Default value is
-         None.
+        :param body: Analyze batch request parameters. Is one of the following types:
+         AnalyzeBatchDocumentsRequest, JSON, IO[bytes] Required.
+        :type body: ~azure.ai.documentintelligence.models.AnalyzeBatchDocumentsRequest or JSON or
+         IO[bytes]
+        :keyword pages: 1-based page numbers to analyze.  Ex. "1-3,5,7-9". Default value is None.
         :paramtype pages: str
         :keyword locale: Locale hint for text recognition and document analysis.  Value may contain
          only
@@ -1276,7 +1562,8 @@ def begin_analyze_batch_documents(
         :paramtype query_fields: list[str]
         :keyword output_content_format: Format of the analyze result top-level content. Known values
          are: "text" and "markdown". Default value is None.
-        :paramtype output_content_format: str or ~azure.ai.documentintelligence.models.ContentFormat
+        :paramtype output_content_format: str or
+         ~azure.ai.documentintelligence.models.DocumentContentFormat
         :keyword output: Additional outputs to generate during analysis. Default value is None.
         :paramtype output: list[str or ~azure.ai.documentintelligence.models.AnalyzeOutputOption]
         :return: An instance of LROPoller that returns AnalyzeBatchResult. The AnalyzeBatchResult is
@@ -1295,7 +1582,7 @@ def begin_analyze_batch_documents(
         if cont_token is None:
             raw_result = self._analyze_batch_documents_initial(
                 model_id=model_id,
-                analyze_batch_request=analyze_batch_request,
+                body=body,
                 pages=pages,
                 locale=locale,
                 string_index_type=string_index_type,
@@ -1349,15 +1636,104 @@ def get_long_running_output(pipeline_response):
         )
 
     @distributed_trace
-    def get_analyze_result_pdf(self, model_id: str, result_id: str, **kwargs: Any) -> Iterator[bytes]:
-        """Gets the generated searchable PDF output from document analysis.
+    def list_analyze_batch_results(self, model_id: str, **kwargs: Any) -> Iterable["_models.AnalyzeBatchOperation"]:
+        """List batch document analysis results.
 
         :param model_id: Unique document model name. Required.
         :type model_id: str
-        :param result_id: Analyze operation result ID. Required.
+        :return: An iterator like instance of AnalyzeBatchOperation
+        :rtype:
+         ~azure.core.paging.ItemPaged[~azure.ai.documentintelligence.models.AnalyzeBatchOperation]
+        :raises ~azure.core.exceptions.HttpResponseError:
+        """
+        _headers = kwargs.pop("headers", {}) or {}
+        _params = kwargs.pop("params", {}) or {}
+
+        cls: ClsType[List[_models.AnalyzeBatchOperation]] = kwargs.pop("cls", None)
+
+        error_map: MutableMapping = {
+            401: ClientAuthenticationError,
+            404: ResourceNotFoundError,
+            409: ResourceExistsError,
+            304: ResourceNotModifiedError,
+        }
+        error_map.update(kwargs.pop("error_map", {}) or {})
+
+        def prepare_request(next_link=None):
+            if not next_link:
+
+                _request = build_document_intelligence_list_analyze_batch_results_request(
+                    model_id=model_id,
+                    api_version=self._config.api_version,
+                    headers=_headers,
+                    params=_params,
+                )
+                path_format_arguments = {
+                    "endpoint": self._serialize.url(
+                        "self._config.endpoint", self._config.endpoint, "str", skip_quote=True
+                    ),
+                }
+                _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+            else:
+                # make call to next link with the client's api-version
+                _parsed_next_link = urllib.parse.urlparse(next_link)
+                _next_request_params = case_insensitive_dict(
+                    {
+                        key: [urllib.parse.quote(v) for v in value]
+                        for key, value in urllib.parse.parse_qs(_parsed_next_link.query).items()
+                    }
+                )
+                _next_request_params["api-version"] = self._config.api_version
+                _request = HttpRequest(
+                    "GET", urllib.parse.urljoin(next_link, _parsed_next_link.path), params=_next_request_params
+                )
+                path_format_arguments = {
+                    "endpoint": self._serialize.url(
+                        "self._config.endpoint", self._config.endpoint, "str", skip_quote=True
+                    ),
+                }
+                _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+            return _request
+
+        def extract_data(pipeline_response):
+            deserialized = pipeline_response.http_response.json()
+            list_of_elem = _deserialize(List[_models.AnalyzeBatchOperation], deserialized["value"])
+            if cls:
+                list_of_elem = cls(list_of_elem)  # type: ignore
+            return deserialized.get("nextLink") or None, iter(list_of_elem)
+
+        def get_next(next_link=None):
+            _request = prepare_request(next_link)
+
+            _stream = False
+            pipeline_response: PipelineResponse = self._client._pipeline.run(  # pylint: disable=protected-access
+                _request, stream=_stream, **kwargs
+            )
+            response = pipeline_response.http_response
+
+            if response.status_code not in [200]:
+                map_error(status_code=response.status_code, response=response, error_map=error_map)
+                error = _failsafe_deserialize(_models.DocumentIntelligenceErrorResponse, response.json())
+                raise HttpResponseError(response=response, model=error)
+
+            return pipeline_response
+
+        return ItemPaged(get_next, extract_data)
+
+    @distributed_trace
+    def delete_analyze_batch_result(  # pylint: disable=inconsistent-return-statements
+        self, model_id: str, result_id: str, **kwargs: Any
+    ) -> None:
+        """Mark the batch document analysis result for deletion.
+
+        :param model_id: Unique document model name. Required.
+        :type model_id: str
+        :param result_id: Analyze batch operation result ID. Required.
         :type result_id: str
-        :return: Iterator[bytes]
-        :rtype: Iterator[bytes]
+        :return: None
+        :rtype: None
         :raises ~azure.core.exceptions.HttpResponseError:
         """
         error_map: MutableMapping = {
@@ -1371,9 +1747,9 @@ def get_analyze_result_pdf(self, model_id: str, result_id: str, **kwargs: Any) -
         _headers = kwargs.pop("headers", {}) or {}
         _params = kwargs.pop("params", {}) or {}
 
-        cls: ClsType[Iterator[bytes]] = kwargs.pop("cls", None)
+        cls: ClsType[None] = kwargs.pop("cls", None)
 
-        _request = build_document_intelligence_get_analyze_result_pdf_request(
+        _request = build_document_intelligence_delete_analyze_batch_result_request(
             model_id=model_id,
             result_id=result_id,
             api_version=self._config.api_version,
@@ -1385,47 +1761,31 @@ def get_analyze_result_pdf(self, model_id: str, result_id: str, **kwargs: Any) -
         }
         _request.url = self._client.format_url(_request.url, **path_format_arguments)
 
-        _stream = kwargs.pop("stream", True)
+        _stream = False
         pipeline_response: PipelineResponse = self._client._pipeline.run(  # pylint: disable=protected-access
             _request, stream=_stream, **kwargs
         )
 
         response = pipeline_response.http_response
 
-        if response.status_code not in [200]:
-            if _stream:
-                try:
-                    response.read()  # Load the body in memory and close the socket
-                except (StreamConsumedError, StreamClosedError):
-                    pass
+        if response.status_code not in [204]:
             map_error(status_code=response.status_code, response=response, error_map=error_map)
-            error = _deserialize(_models.ErrorResponse, response.json())
+            error = _failsafe_deserialize(_models.DocumentIntelligenceErrorResponse, response.json())
             raise HttpResponseError(response=response, model=error)
 
-        response_headers = {}
-        response_headers["content-type"] = self._deserialize("str", response.headers.get("content-type"))
-
-        deserialized = response.iter_bytes()
-
         if cls:
-            return cls(pipeline_response, deserialized, response_headers)  # type: ignore
-
-        return deserialized  # type: ignore
+            return cls(pipeline_response, None, {})  # type: ignore
 
     @distributed_trace
-    def get_analyze_result_figure(
-        self, model_id: str, result_id: str, figure_id: str, **kwargs: Any
-    ) -> Iterator[bytes]:
-        """Gets the generated cropped image of specified figure from document analysis.
+    def get_analyze_batch_result(self, model_id: str, result_id: str, **kwargs: Any) -> _models.AnalyzeBatchOperation:
+        """Gets the result of batch document analysis.
 
         :param model_id: Unique document model name. Required.
         :type model_id: str
-        :param result_id: Analyze operation result ID. Required.
+        :param result_id: Analyze batch operation result ID. Required.
         :type result_id: str
-        :param figure_id: Figure ID. Required.
-        :type figure_id: str
-        :return: Iterator[bytes]
-        :rtype: Iterator[bytes]
+        :return: AnalyzeBatchOperation. The AnalyzeBatchOperation is compatible with MutableMapping
+        :rtype: ~azure.ai.documentintelligence.models.AnalyzeBatchOperation
         :raises ~azure.core.exceptions.HttpResponseError:
         """
         error_map: MutableMapping = {
@@ -1439,12 +1799,11 @@ def get_analyze_result_figure(
         _headers = kwargs.pop("headers", {}) or {}
         _params = kwargs.pop("params", {}) or {}
 
-        cls: ClsType[Iterator[bytes]] = kwargs.pop("cls", None)
+        cls: ClsType[_models.AnalyzeBatchOperation] = kwargs.pop("cls", None)
 
-        _request = build_document_intelligence_get_analyze_result_figure_request(
+        _request = build_document_intelligence_get_analyze_batch_result_request(
             model_id=model_id,
             result_id=result_id,
-            figure_id=figure_id,
             api_version=self._config.api_version,
             headers=_headers,
             params=_params,
@@ -1454,7 +1813,7 @@ def get_analyze_result_figure(
         }
         _request.url = self._client.format_url(_request.url, **path_format_arguments)
 
-        _stream = kwargs.pop("stream", True)
+        _stream = kwargs.pop("stream", False)
         pipeline_response: PipelineResponse = self._client._pipeline.run(  # pylint: disable=protected-access
             _request, stream=_stream, **kwargs
         )
@@ -1468,23 +1827,23 @@ def get_analyze_result_figure(
                 except (StreamConsumedError, StreamClosedError):
                     pass
             map_error(status_code=response.status_code, response=response, error_map=error_map)
-            error = _deserialize(_models.ErrorResponse, response.json())
+            error = _failsafe_deserialize(_models.DocumentIntelligenceErrorResponse, response.json())
             raise HttpResponseError(response=response, model=error)
 
-        response_headers = {}
-        response_headers["content-type"] = self._deserialize("str", response.headers.get("content-type"))
-
-        deserialized = response.iter_bytes()
+        if _stream:
+            deserialized = response.iter_bytes()
+        else:
+            deserialized = _deserialize(_models.AnalyzeBatchOperation, response.json())
 
         if cls:
-            return cls(pipeline_response, deserialized, response_headers)  # type: ignore
+            return cls(pipeline_response, deserialized, {})  # type: ignore
 
         return deserialized  # type: ignore
 
     def _classify_document_initial(
         self,
         classifier_id: str,
-        classify_request: Union[_models.ClassifyDocumentRequest, JSON, IO[bytes]],
+        body: Union[_models.ClassifyDocumentRequest, JSON, IO[bytes]],
         *,
         string_index_type: Optional[Union[str, _models.StringIndexType]] = None,
         split: Optional[Union[str, _models.SplitMode]] = None,
@@ -1507,10 +1866,10 @@ def _classify_document_initial(
 
         content_type = content_type or "application/json"
         _content = None
-        if isinstance(classify_request, (IOBase, bytes)):
-            _content = classify_request
+        if isinstance(body, (IOBase, bytes)):
+            _content = body
         else:
-            _content = json.dumps(classify_request, cls=SdkJSONEncoder, exclude_readonly=True)  # type: ignore
+            _content = json.dumps(body, cls=SdkJSONEncoder, exclude_readonly=True)  # type: ignore
 
         _request = build_document_intelligence_classify_document_request(
             classifier_id=classifier_id,
@@ -1541,7 +1900,7 @@ def _classify_document_initial(
             except (StreamConsumedError, StreamClosedError):
                 pass
             map_error(status_code=response.status_code, response=response, error_map=error_map)
-            error = _deserialize(_models.ErrorResponse, response.json())
+            error = _failsafe_deserialize(_models.DocumentIntelligenceErrorResponse, response.json())
             raise HttpResponseError(response=response, model=error)
 
         response_headers = {}
@@ -1559,7 +1918,7 @@ def _classify_document_initial(
     def begin_classify_document(
         self,
         classifier_id: str,
-        classify_request: _models.ClassifyDocumentRequest,
+        body: _models.ClassifyDocumentRequest,
         *,
         string_index_type: Optional[Union[str, _models.StringIndexType]] = None,
         split: Optional[Union[str, _models.SplitMode]] = None,
@@ -1571,16 +1930,15 @@ def begin_classify_document(
 
         :param classifier_id: Unique document classifier name. Required.
         :type classifier_id: str
-        :param classify_request: Classify request parameters. Required.
-        :type classify_request: ~azure.ai.documentintelligence.models.ClassifyDocumentRequest
+        :param body: Classify request parameters. Required.
+        :type body: ~azure.ai.documentintelligence.models.ClassifyDocumentRequest
         :keyword string_index_type: Method used to compute string offset and length. Known values are:
          "textElements", "unicodeCodePoint", and "utf16CodeUnit". Default value is None.
         :paramtype string_index_type: str or ~azure.ai.documentintelligence.models.StringIndexType
         :keyword split: Document splitting mode. Known values are: "auto", "none", and "perPage".
          Default value is None.
         :paramtype split: str or ~azure.ai.documentintelligence.models.SplitMode
-        :keyword pages: Range of 1-based page numbers to analyze.  Ex. "1-3,5,7-9". Default value is
-         None.
+        :keyword pages: 1-based page numbers to analyze.  Ex. "1-3,5,7-9". Default value is None.
         :paramtype pages: str
         :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
          Default value is "application/json".
@@ -1595,7 +1953,7 @@ def begin_classify_document(
     def begin_classify_document(
         self,
         classifier_id: str,
-        classify_request: JSON,
+        body: JSON,
         *,
         string_index_type: Optional[Union[str, _models.StringIndexType]] = None,
         split: Optional[Union[str, _models.SplitMode]] = None,
@@ -1607,16 +1965,15 @@ def begin_classify_document(
 
         :param classifier_id: Unique document classifier name. Required.
         :type classifier_id: str
-        :param classify_request: Classify request parameters. Required.
-        :type classify_request: JSON
+        :param body: Classify request parameters. Required.
+        :type body: JSON
         :keyword string_index_type: Method used to compute string offset and length. Known values are:
          "textElements", "unicodeCodePoint", and "utf16CodeUnit". Default value is None.
         :paramtype string_index_type: str or ~azure.ai.documentintelligence.models.StringIndexType
         :keyword split: Document splitting mode. Known values are: "auto", "none", and "perPage".
          Default value is None.
         :paramtype split: str or ~azure.ai.documentintelligence.models.SplitMode
-        :keyword pages: Range of 1-based page numbers to analyze.  Ex. "1-3,5,7-9". Default value is
-         None.
+        :keyword pages: 1-based page numbers to analyze.  Ex. "1-3,5,7-9". Default value is None.
         :paramtype pages: str
         :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
          Default value is "application/json".
@@ -1631,7 +1988,7 @@ def begin_classify_document(
     def begin_classify_document(
         self,
         classifier_id: str,
-        classify_request: IO[bytes],
+        body: IO[bytes],
         *,
         string_index_type: Optional[Union[str, _models.StringIndexType]] = None,
         split: Optional[Union[str, _models.SplitMode]] = None,
@@ -1643,16 +2000,15 @@ def begin_classify_document(
 
         :param classifier_id: Unique document classifier name. Required.
         :type classifier_id: str
-        :param classify_request: Classify request parameters. Required.
-        :type classify_request: IO[bytes]
+        :param body: Classify request parameters. Required.
+        :type body: IO[bytes]
         :keyword string_index_type: Method used to compute string offset and length. Known values are:
          "textElements", "unicodeCodePoint", and "utf16CodeUnit". Default value is None.
         :paramtype string_index_type: str or ~azure.ai.documentintelligence.models.StringIndexType
         :keyword split: Document splitting mode. Known values are: "auto", "none", and "perPage".
          Default value is None.
         :paramtype split: str or ~azure.ai.documentintelligence.models.SplitMode
-        :keyword pages: Range of 1-based page numbers to analyze.  Ex. "1-3,5,7-9". Default value is
-         None.
+        :keyword pages: 1-based page numbers to analyze.  Ex. "1-3,5,7-9". Default value is None.
         :paramtype pages: str
         :keyword content_type: Body Parameter content-type. Content type parameter for binary body.
          Default value is "application/json".
@@ -1667,7 +2023,7 @@ def begin_classify_document(
     def begin_classify_document(
         self,
         classifier_id: str,
-        classify_request: Union[_models.ClassifyDocumentRequest, JSON, IO[bytes]],
+        body: Union[_models.ClassifyDocumentRequest, JSON, IO[bytes]],
         *,
         string_index_type: Optional[Union[str, _models.StringIndexType]] = None,
         split: Optional[Union[str, _models.SplitMode]] = None,
@@ -1678,18 +2034,16 @@ def begin_classify_document(
 
         :param classifier_id: Unique document classifier name. Required.
         :type classifier_id: str
-        :param classify_request: Classify request parameters. Is one of the following types:
+        :param body: Classify request parameters. Is one of the following types:
          ClassifyDocumentRequest, JSON, IO[bytes] Required.
-        :type classify_request: ~azure.ai.documentintelligence.models.ClassifyDocumentRequest or JSON
-         or IO[bytes]
+        :type body: ~azure.ai.documentintelligence.models.ClassifyDocumentRequest or JSON or IO[bytes]
         :keyword string_index_type: Method used to compute string offset and length. Known values are:
          "textElements", "unicodeCodePoint", and "utf16CodeUnit". Default value is None.
         :paramtype string_index_type: str or ~azure.ai.documentintelligence.models.StringIndexType
         :keyword split: Document splitting mode. Known values are: "auto", "none", and "perPage".
          Default value is None.
         :paramtype split: str or ~azure.ai.documentintelligence.models.SplitMode
-        :keyword pages: Range of 1-based page numbers to analyze.  Ex. "1-3,5,7-9". Default value is
-         None.
+        :keyword pages: 1-based page numbers to analyze.  Ex. "1-3,5,7-9". Default value is None.
         :paramtype pages: str
         :return: An instance of LROPoller that returns AnalyzeResult. The AnalyzeResult is compatible
          with MutableMapping
@@ -1707,7 +2061,7 @@ def begin_classify_document(
         if cont_token is None:
             raw_result = self._classify_document_initial(
                 classifier_id=classifier_id,
-                classify_request=classify_request,
+                body=body,
                 string_index_type=string_index_type,
                 split=split,
                 pages=pages,
@@ -1762,7 +2116,7 @@ class DocumentIntelligenceAdministrationClientOperationsMixin(  # pylint: disabl
 ):
 
     def _build_document_model_initial(
-        self, build_request: Union[_models.BuildDocumentModelRequest, JSON, IO[bytes]], **kwargs: Any
+        self, body: Union[_models.BuildDocumentModelRequest, JSON, IO[bytes]], **kwargs: Any
     ) -> Iterator[bytes]:
         error_map: MutableMapping = {
             401: ClientAuthenticationError,
@@ -1780,10 +2134,10 @@ def _build_document_model_initial(
 
         content_type = content_type or "application/json"
         _content = None
-        if isinstance(build_request, (IOBase, bytes)):
-            _content = build_request
+        if isinstance(body, (IOBase, bytes)):
+            _content = body
         else:
-            _content = json.dumps(build_request, cls=SdkJSONEncoder, exclude_readonly=True)  # type: ignore
+            _content = json.dumps(body, cls=SdkJSONEncoder, exclude_readonly=True)  # type: ignore
 
         _request = build_document_intelligence_administration_build_document_model_request(
             content_type=content_type,
@@ -1810,7 +2164,7 @@ def _build_document_model_initial(
             except (StreamConsumedError, StreamClosedError):
                 pass
             map_error(status_code=response.status_code, response=response, error_map=error_map)
-            error = _deserialize(_models.ErrorResponse, response.json())
+            error = _failsafe_deserialize(_models.DocumentIntelligenceErrorResponse, response.json())
             raise HttpResponseError(response=response, model=error)
 
         response_headers = {}
@@ -1826,12 +2180,12 @@ def _build_document_model_initial(
 
     @overload
     def begin_build_document_model(
-        self, build_request: _models.BuildDocumentModelRequest, *, content_type: str = "application/json", **kwargs: Any
+        self, body: _models.BuildDocumentModelRequest, *, content_type: str = "application/json", **kwargs: Any
     ) -> LROPoller[_models.DocumentModelDetails]:
         """Builds a custom document analysis model.
 
-        :param build_request: Build request parameters. Required.
-        :type build_request: ~azure.ai.documentintelligence.models.BuildDocumentModelRequest
+        :param body: Build request parameters. Required.
+        :type body: ~azure.ai.documentintelligence.models.BuildDocumentModelRequest
         :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
          Default value is "application/json".
         :paramtype content_type: str
@@ -1844,12 +2198,12 @@ def begin_build_document_model(
 
     @overload
     def begin_build_document_model(
-        self, build_request: JSON, *, content_type: str = "application/json", **kwargs: Any
+        self, body: JSON, *, content_type: str = "application/json", **kwargs: Any
     ) -> LROPoller[_models.DocumentModelDetails]:
         """Builds a custom document analysis model.
 
-        :param build_request: Build request parameters. Required.
-        :type build_request: JSON
+        :param body: Build request parameters. Required.
+        :type body: JSON
         :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
          Default value is "application/json".
         :paramtype content_type: str
@@ -1862,12 +2216,12 @@ def begin_build_document_model(
 
     @overload
     def begin_build_document_model(
-        self, build_request: IO[bytes], *, content_type: str = "application/json", **kwargs: Any
+        self, body: IO[bytes], *, content_type: str = "application/json", **kwargs: Any
     ) -> LROPoller[_models.DocumentModelDetails]:
         """Builds a custom document analysis model.
 
-        :param build_request: Build request parameters. Required.
-        :type build_request: IO[bytes]
+        :param body: Build request parameters. Required.
+        :type body: IO[bytes]
         :keyword content_type: Body Parameter content-type. Content type parameter for binary body.
          Default value is "application/json".
         :paramtype content_type: str
@@ -1880,13 +2234,13 @@ def begin_build_document_model(
 
     @distributed_trace
     def begin_build_document_model(
-        self, build_request: Union[_models.BuildDocumentModelRequest, JSON, IO[bytes]], **kwargs: Any
+        self, body: Union[_models.BuildDocumentModelRequest, JSON, IO[bytes]], **kwargs: Any
     ) -> LROPoller[_models.DocumentModelDetails]:
         """Builds a custom document analysis model.
 
-        :param build_request: Build request parameters. Is one of the following types:
+        :param body: Build request parameters. Is one of the following types:
          BuildDocumentModelRequest, JSON, IO[bytes] Required.
-        :type build_request: ~azure.ai.documentintelligence.models.BuildDocumentModelRequest or JSON or
+        :type body: ~azure.ai.documentintelligence.models.BuildDocumentModelRequest or JSON or
          IO[bytes]
         :return: An instance of LROPoller that returns DocumentModelDetails. The DocumentModelDetails
          is compatible with MutableMapping
@@ -1904,12 +2258,7 @@ def begin_build_document_model(
         cont_token: Optional[str] = kwargs.pop("continuation_token", None)
         if cont_token is None:
             raw_result = self._build_document_model_initial(
-                build_request=build_request,
-                content_type=content_type,
-                cls=lambda x, y, z: x,
-                headers=_headers,
-                params=_params,
-                **kwargs,
+                body=body, content_type=content_type, cls=lambda x, y, z: x, headers=_headers, params=_params, **kwargs
             )
             raw_result.http_response.read()  # type: ignore
         kwargs.pop("error_map", None)
@@ -1951,7 +2300,7 @@ def get_long_running_output(pipeline_response):
         )
 
     def _compose_model_initial(
-        self, compose_request: Union[_models.ComposeDocumentModelRequest, JSON, IO[bytes]], **kwargs: Any
+        self, body: Union[_models.ComposeDocumentModelRequest, JSON, IO[bytes]], **kwargs: Any
     ) -> Iterator[bytes]:
         error_map: MutableMapping = {
             401: ClientAuthenticationError,
@@ -1969,10 +2318,10 @@ def _compose_model_initial(
 
         content_type = content_type or "application/json"
         _content = None
-        if isinstance(compose_request, (IOBase, bytes)):
-            _content = compose_request
+        if isinstance(body, (IOBase, bytes)):
+            _content = body
         else:
-            _content = json.dumps(compose_request, cls=SdkJSONEncoder, exclude_readonly=True)  # type: ignore
+            _content = json.dumps(body, cls=SdkJSONEncoder, exclude_readonly=True)  # type: ignore
 
         _request = build_document_intelligence_administration_compose_model_request(
             content_type=content_type,
@@ -1999,7 +2348,7 @@ def _compose_model_initial(
             except (StreamConsumedError, StreamClosedError):
                 pass
             map_error(status_code=response.status_code, response=response, error_map=error_map)
-            error = _deserialize(_models.ErrorResponse, response.json())
+            error = _failsafe_deserialize(_models.DocumentIntelligenceErrorResponse, response.json())
             raise HttpResponseError(response=response, model=error)
 
         response_headers = {}
@@ -2015,16 +2364,12 @@ def _compose_model_initial(
 
     @overload
     def begin_compose_model(
-        self,
-        compose_request: _models.ComposeDocumentModelRequest,
-        *,
-        content_type: str = "application/json",
-        **kwargs: Any,
+        self, body: _models.ComposeDocumentModelRequest, *, content_type: str = "application/json", **kwargs: Any
     ) -> LROPoller[_models.DocumentModelDetails]:
         """Creates a new document model from document types of existing document models.
 
-        :param compose_request: Compose request parameters. Required.
-        :type compose_request: ~azure.ai.documentintelligence.models.ComposeDocumentModelRequest
+        :param body: Compose request parameters. Required.
+        :type body: ~azure.ai.documentintelligence.models.ComposeDocumentModelRequest
         :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
          Default value is "application/json".
         :paramtype content_type: str
@@ -2037,12 +2382,12 @@ def begin_compose_model(
 
     @overload
     def begin_compose_model(
-        self, compose_request: JSON, *, content_type: str = "application/json", **kwargs: Any
+        self, body: JSON, *, content_type: str = "application/json", **kwargs: Any
     ) -> LROPoller[_models.DocumentModelDetails]:
         """Creates a new document model from document types of existing document models.
 
-        :param compose_request: Compose request parameters. Required.
-        :type compose_request: JSON
+        :param body: Compose request parameters. Required.
+        :type body: JSON
         :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
          Default value is "application/json".
         :paramtype content_type: str
@@ -2055,12 +2400,12 @@ def begin_compose_model(
 
     @overload
     def begin_compose_model(
-        self, compose_request: IO[bytes], *, content_type: str = "application/json", **kwargs: Any
+        self, body: IO[bytes], *, content_type: str = "application/json", **kwargs: Any
     ) -> LROPoller[_models.DocumentModelDetails]:
         """Creates a new document model from document types of existing document models.
 
-        :param compose_request: Compose request parameters. Required.
-        :type compose_request: IO[bytes]
+        :param body: Compose request parameters. Required.
+        :type body: IO[bytes]
         :keyword content_type: Body Parameter content-type. Content type parameter for binary body.
          Default value is "application/json".
         :paramtype content_type: str
@@ -2073,14 +2418,14 @@ def begin_compose_model(
 
     @distributed_trace
     def begin_compose_model(
-        self, compose_request: Union[_models.ComposeDocumentModelRequest, JSON, IO[bytes]], **kwargs: Any
+        self, body: Union[_models.ComposeDocumentModelRequest, JSON, IO[bytes]], **kwargs: Any
     ) -> LROPoller[_models.DocumentModelDetails]:
         """Creates a new document model from document types of existing document models.
 
-        :param compose_request: Compose request parameters. Is one of the following types:
+        :param body: Compose request parameters. Is one of the following types:
          ComposeDocumentModelRequest, JSON, IO[bytes] Required.
-        :type compose_request: ~azure.ai.documentintelligence.models.ComposeDocumentModelRequest or
-         JSON or IO[bytes]
+        :type body: ~azure.ai.documentintelligence.models.ComposeDocumentModelRequest or JSON or
+         IO[bytes]
         :return: An instance of LROPoller that returns DocumentModelDetails. The DocumentModelDetails
          is compatible with MutableMapping
         :rtype:
@@ -2097,12 +2442,7 @@ def begin_compose_model(
         cont_token: Optional[str] = kwargs.pop("continuation_token", None)
         if cont_token is None:
             raw_result = self._compose_model_initial(
-                compose_request=compose_request,
-                content_type=content_type,
-                cls=lambda x, y, z: x,
-                headers=_headers,
-                params=_params,
-                **kwargs,
+                body=body, content_type=content_type, cls=lambda x, y, z: x, headers=_headers, params=_params, **kwargs
             )
             raw_result.http_response.read()  # type: ignore
         kwargs.pop("error_map", None)
@@ -2145,72 +2485,67 @@ def get_long_running_output(pipeline_response):
 
     @overload
     def authorize_model_copy(
-        self,
-        authorize_copy_request: _models.AuthorizeCopyRequest,
-        *,
-        content_type: str = "application/json",
-        **kwargs: Any,
-    ) -> _models.CopyAuthorization:
+        self, body: _models.AuthorizeCopyRequest, *, content_type: str = "application/json", **kwargs: Any
+    ) -> _models.ModelCopyAuthorization:
         """Generates authorization to copy a document model to this location with
         specified modelId and optional description.
 
-        :param authorize_copy_request: Authorize copy request parameters. Required.
-        :type authorize_copy_request: ~azure.ai.documentintelligence.models.AuthorizeCopyRequest
+        :param body: Authorize copy request parameters. Required.
+        :type body: ~azure.ai.documentintelligence.models.AuthorizeCopyRequest
         :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
          Default value is "application/json".
         :paramtype content_type: str
-        :return: CopyAuthorization. The CopyAuthorization is compatible with MutableMapping
-        :rtype: ~azure.ai.documentintelligence.models.CopyAuthorization
+        :return: ModelCopyAuthorization. The ModelCopyAuthorization is compatible with MutableMapping
+        :rtype: ~azure.ai.documentintelligence.models.ModelCopyAuthorization
         :raises ~azure.core.exceptions.HttpResponseError:
         """
 
     @overload
     def authorize_model_copy(
-        self, authorize_copy_request: JSON, *, content_type: str = "application/json", **kwargs: Any
-    ) -> _models.CopyAuthorization:
+        self, body: JSON, *, content_type: str = "application/json", **kwargs: Any
+    ) -> _models.ModelCopyAuthorization:
         """Generates authorization to copy a document model to this location with
         specified modelId and optional description.
 
-        :param authorize_copy_request: Authorize copy request parameters. Required.
-        :type authorize_copy_request: JSON
+        :param body: Authorize copy request parameters. Required.
+        :type body: JSON
         :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
          Default value is "application/json".
         :paramtype content_type: str
-        :return: CopyAuthorization. The CopyAuthorization is compatible with MutableMapping
-        :rtype: ~azure.ai.documentintelligence.models.CopyAuthorization
+        :return: ModelCopyAuthorization. The ModelCopyAuthorization is compatible with MutableMapping
+        :rtype: ~azure.ai.documentintelligence.models.ModelCopyAuthorization
         :raises ~azure.core.exceptions.HttpResponseError:
         """
 
     @overload
     def authorize_model_copy(
-        self, authorize_copy_request: IO[bytes], *, content_type: str = "application/json", **kwargs: Any
-    ) -> _models.CopyAuthorization:
+        self, body: IO[bytes], *, content_type: str = "application/json", **kwargs: Any
+    ) -> _models.ModelCopyAuthorization:
         """Generates authorization to copy a document model to this location with
         specified modelId and optional description.
 
-        :param authorize_copy_request: Authorize copy request parameters. Required.
-        :type authorize_copy_request: IO[bytes]
+        :param body: Authorize copy request parameters. Required.
+        :type body: IO[bytes]
         :keyword content_type: Body Parameter content-type. Content type parameter for binary body.
          Default value is "application/json".
         :paramtype content_type: str
-        :return: CopyAuthorization. The CopyAuthorization is compatible with MutableMapping
-        :rtype: ~azure.ai.documentintelligence.models.CopyAuthorization
+        :return: ModelCopyAuthorization. The ModelCopyAuthorization is compatible with MutableMapping
+        :rtype: ~azure.ai.documentintelligence.models.ModelCopyAuthorization
         :raises ~azure.core.exceptions.HttpResponseError:
         """
 
     @distributed_trace
     def authorize_model_copy(
-        self, authorize_copy_request: Union[_models.AuthorizeCopyRequest, JSON, IO[bytes]], **kwargs: Any
-    ) -> _models.CopyAuthorization:
+        self, body: Union[_models.AuthorizeCopyRequest, JSON, IO[bytes]], **kwargs: Any
+    ) -> _models.ModelCopyAuthorization:
         """Generates authorization to copy a document model to this location with
         specified modelId and optional description.
 
-        :param authorize_copy_request: Authorize copy request parameters. Is one of the following
-         types: AuthorizeCopyRequest, JSON, IO[bytes] Required.
-        :type authorize_copy_request: ~azure.ai.documentintelligence.models.AuthorizeCopyRequest or
-         JSON or IO[bytes]
-        :return: CopyAuthorization. The CopyAuthorization is compatible with MutableMapping
-        :rtype: ~azure.ai.documentintelligence.models.CopyAuthorization
+        :param body: Authorize copy request parameters. Is one of the following types:
+         AuthorizeCopyRequest, JSON, IO[bytes] Required.
+        :type body: ~azure.ai.documentintelligence.models.AuthorizeCopyRequest or JSON or IO[bytes]
+        :return: ModelCopyAuthorization. The ModelCopyAuthorization is compatible with MutableMapping
+        :rtype: ~azure.ai.documentintelligence.models.ModelCopyAuthorization
         :raises ~azure.core.exceptions.HttpResponseError:
         """
         error_map: MutableMapping = {
@@ -2225,14 +2560,14 @@ def authorize_model_copy(
         _params = kwargs.pop("params", {}) or {}
 
         content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
-        cls: ClsType[_models.CopyAuthorization] = kwargs.pop("cls", None)
+        cls: ClsType[_models.ModelCopyAuthorization] = kwargs.pop("cls", None)
 
         content_type = content_type or "application/json"
         _content = None
-        if isinstance(authorize_copy_request, (IOBase, bytes)):
-            _content = authorize_copy_request
+        if isinstance(body, (IOBase, bytes)):
+            _content = body
         else:
-            _content = json.dumps(authorize_copy_request, cls=SdkJSONEncoder, exclude_readonly=True)  # type: ignore
+            _content = json.dumps(body, cls=SdkJSONEncoder, exclude_readonly=True)  # type: ignore
 
         _request = build_document_intelligence_administration_authorize_model_copy_request(
             content_type=content_type,
@@ -2260,13 +2595,13 @@ def authorize_model_copy(
                 except (StreamConsumedError, StreamClosedError):
                     pass
             map_error(status_code=response.status_code, response=response, error_map=error_map)
-            error = _deserialize(_models.ErrorResponse, response.json())
+            error = _failsafe_deserialize(_models.DocumentIntelligenceErrorResponse, response.json())
             raise HttpResponseError(response=response, model=error)
 
         if _stream:
             deserialized = response.iter_bytes()
         else:
-            deserialized = _deserialize(_models.CopyAuthorization, response.json())
+            deserialized = _deserialize(_models.ModelCopyAuthorization, response.json())
 
         if cls:
             return cls(pipeline_response, deserialized, {})  # type: ignore
@@ -2274,7 +2609,7 @@ def authorize_model_copy(
         return deserialized  # type: ignore
 
     def _copy_model_to_initial(
-        self, model_id: str, copy_to_request: Union[_models.CopyAuthorization, JSON, IO[bytes]], **kwargs: Any
+        self, model_id: str, body: Union[_models.ModelCopyAuthorization, JSON, IO[bytes]], **kwargs: Any
     ) -> Iterator[bytes]:
         error_map: MutableMapping = {
             401: ClientAuthenticationError,
@@ -2292,10 +2627,10 @@ def _copy_model_to_initial(
 
         content_type = content_type or "application/json"
         _content = None
-        if isinstance(copy_to_request, (IOBase, bytes)):
-            _content = copy_to_request
+        if isinstance(body, (IOBase, bytes)):
+            _content = body
         else:
-            _content = json.dumps(copy_to_request, cls=SdkJSONEncoder, exclude_readonly=True)  # type: ignore
+            _content = json.dumps(body, cls=SdkJSONEncoder, exclude_readonly=True)  # type: ignore
 
         _request = build_document_intelligence_administration_copy_model_to_request(
             model_id=model_id,
@@ -2323,7 +2658,7 @@ def _copy_model_to_initial(
             except (StreamConsumedError, StreamClosedError):
                 pass
             map_error(status_code=response.status_code, response=response, error_map=error_map)
-            error = _deserialize(_models.ErrorResponse, response.json())
+            error = _failsafe_deserialize(_models.DocumentIntelligenceErrorResponse, response.json())
             raise HttpResponseError(response=response, model=error)
 
         response_headers = {}
@@ -2341,7 +2676,7 @@ def _copy_model_to_initial(
     def begin_copy_model_to(
         self,
         model_id: str,
-        copy_to_request: _models.CopyAuthorization,
+        body: _models.ModelCopyAuthorization,
         *,
         content_type: str = "application/json",
         **kwargs: Any,
@@ -2350,8 +2685,8 @@ def begin_copy_model_to(
 
         :param model_id: Unique document model name. Required.
         :type model_id: str
-        :param copy_to_request: Copy to request parameters. Required.
-        :type copy_to_request: ~azure.ai.documentintelligence.models.CopyAuthorization
+        :param body: Copy to request parameters. Required.
+        :type body: ~azure.ai.documentintelligence.models.ModelCopyAuthorization
         :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
          Default value is "application/json".
         :paramtype content_type: str
@@ -2364,14 +2699,14 @@ def begin_copy_model_to(
 
     @overload
     def begin_copy_model_to(
-        self, model_id: str, copy_to_request: JSON, *, content_type: str = "application/json", **kwargs: Any
+        self, model_id: str, body: JSON, *, content_type: str = "application/json", **kwargs: Any
     ) -> LROPoller[_models.DocumentModelDetails]:
         """Copies document model to the target resource, region, and modelId.
 
         :param model_id: Unique document model name. Required.
         :type model_id: str
-        :param copy_to_request: Copy to request parameters. Required.
-        :type copy_to_request: JSON
+        :param body: Copy to request parameters. Required.
+        :type body: JSON
         :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
          Default value is "application/json".
         :paramtype content_type: str
@@ -2384,14 +2719,14 @@ def begin_copy_model_to(
 
     @overload
     def begin_copy_model_to(
-        self, model_id: str, copy_to_request: IO[bytes], *, content_type: str = "application/json", **kwargs: Any
+        self, model_id: str, body: IO[bytes], *, content_type: str = "application/json", **kwargs: Any
     ) -> LROPoller[_models.DocumentModelDetails]:
         """Copies document model to the target resource, region, and modelId.
 
         :param model_id: Unique document model name. Required.
         :type model_id: str
-        :param copy_to_request: Copy to request parameters. Required.
-        :type copy_to_request: IO[bytes]
+        :param body: Copy to request parameters. Required.
+        :type body: IO[bytes]
         :keyword content_type: Body Parameter content-type. Content type parameter for binary body.
          Default value is "application/json".
         :paramtype content_type: str
@@ -2404,16 +2739,15 @@ def begin_copy_model_to(
 
     @distributed_trace
     def begin_copy_model_to(
-        self, model_id: str, copy_to_request: Union[_models.CopyAuthorization, JSON, IO[bytes]], **kwargs: Any
+        self, model_id: str, body: Union[_models.ModelCopyAuthorization, JSON, IO[bytes]], **kwargs: Any
     ) -> LROPoller[_models.DocumentModelDetails]:
         """Copies document model to the target resource, region, and modelId.
 
         :param model_id: Unique document model name. Required.
         :type model_id: str
-        :param copy_to_request: Copy to request parameters. Is one of the following types:
-         CopyAuthorization, JSON, IO[bytes] Required.
-        :type copy_to_request: ~azure.ai.documentintelligence.models.CopyAuthorization or JSON or
-         IO[bytes]
+        :param body: Copy to request parameters. Is one of the following types: ModelCopyAuthorization,
+         JSON, IO[bytes] Required.
+        :type body: ~azure.ai.documentintelligence.models.ModelCopyAuthorization or JSON or IO[bytes]
         :return: An instance of LROPoller that returns DocumentModelDetails. The DocumentModelDetails
          is compatible with MutableMapping
         :rtype:
@@ -2431,7 +2765,7 @@ def begin_copy_model_to(
         if cont_token is None:
             raw_result = self._copy_model_to_initial(
                 model_id=model_id,
-                copy_to_request=copy_to_request,
+                body=body,
                 content_type=content_type,
                 cls=lambda x, y, z: x,
                 headers=_headers,
@@ -2525,7 +2859,7 @@ def get_model(self, model_id: str, **kwargs: Any) -> _models.DocumentModelDetail
                 except (StreamConsumedError, StreamClosedError):
                     pass
             map_error(status_code=response.status_code, response=response, error_map=error_map)
-            error = _deserialize(_models.ErrorResponse, response.json())
+            error = _failsafe_deserialize(_models.DocumentIntelligenceErrorResponse, response.json())
             raise HttpResponseError(response=response, model=error)
 
         response_headers = {}
@@ -2620,7 +2954,7 @@ def get_next(next_link=None):
 
             if response.status_code not in [200]:
                 map_error(status_code=response.status_code, response=response, error_map=error_map)
-                error = _deserialize(_models.ErrorResponse, response.json())
+                error = _failsafe_deserialize(_models.DocumentIntelligenceErrorResponse, response.json())
                 raise HttpResponseError(response=response, model=error)
 
             return pipeline_response
@@ -2670,7 +3004,7 @@ def delete_model(self, model_id: str, **kwargs: Any) -> None:  # pylint: disable
 
         if response.status_code not in [204]:
             map_error(status_code=response.status_code, response=response, error_map=error_map)
-            error = _deserialize(_models.ErrorResponse, response.json())
+            error = _failsafe_deserialize(_models.DocumentIntelligenceErrorResponse, response.json())
             raise HttpResponseError(response=response, model=error)
 
         response_headers = {}
@@ -2682,11 +3016,12 @@ def delete_model(self, model_id: str, **kwargs: Any) -> None:  # pylint: disable
             return cls(pipeline_response, None, response_headers)  # type: ignore
 
     @distributed_trace
-    def get_resource_info(self, **kwargs: Any) -> _models.ResourceDetails:
+    def get_resource_details(self, **kwargs: Any) -> _models.DocumentIntelligenceResourceDetails:
         """Return information about the current resource.
 
-        :return: ResourceDetails. The ResourceDetails is compatible with MutableMapping
-        :rtype: ~azure.ai.documentintelligence.models.ResourceDetails
+        :return: DocumentIntelligenceResourceDetails. The DocumentIntelligenceResourceDetails is
+         compatible with MutableMapping
+        :rtype: ~azure.ai.documentintelligence.models.DocumentIntelligenceResourceDetails
         :raises ~azure.core.exceptions.HttpResponseError:
         """
         error_map: MutableMapping = {
@@ -2700,9 +3035,9 @@ def get_resource_info(self, **kwargs: Any) -> _models.ResourceDetails:
         _headers = kwargs.pop("headers", {}) or {}
         _params = kwargs.pop("params", {}) or {}
 
-        cls: ClsType[_models.ResourceDetails] = kwargs.pop("cls", None)
+        cls: ClsType[_models.DocumentIntelligenceResourceDetails] = kwargs.pop("cls", None)
 
-        _request = build_document_intelligence_administration_get_resource_info_request(
+        _request = build_document_intelligence_administration_get_resource_details_request(
             api_version=self._config.api_version,
             headers=_headers,
             params=_params,
@@ -2726,13 +3061,13 @@ def get_resource_info(self, **kwargs: Any) -> _models.ResourceDetails:
                 except (StreamConsumedError, StreamClosedError):
                     pass
             map_error(status_code=response.status_code, response=response, error_map=error_map)
-            error = _deserialize(_models.ErrorResponse, response.json())
+            error = _failsafe_deserialize(_models.DocumentIntelligenceErrorResponse, response.json())
             raise HttpResponseError(response=response, model=error)
 
         if _stream:
             deserialized = response.iter_bytes()
         else:
-            deserialized = _deserialize(_models.ResourceDetails, response.json())
+            deserialized = _deserialize(_models.DocumentIntelligenceResourceDetails, response.json())
 
         if cls:
             return cls(pipeline_response, deserialized, {})  # type: ignore
@@ -2740,13 +3075,14 @@ def get_resource_info(self, **kwargs: Any) -> _models.ResourceDetails:
         return deserialized  # type: ignore
 
     @distributed_trace
-    def get_operation(self, operation_id: str, **kwargs: Any) -> _models.OperationDetails:
+    def get_operation(self, operation_id: str, **kwargs: Any) -> _models.DocumentIntelligenceOperationDetails:
         """Gets operation info.
 
         :param operation_id: Operation ID. Required.
         :type operation_id: str
-        :return: OperationDetails. The OperationDetails is compatible with MutableMapping
-        :rtype: ~azure.ai.documentintelligence.models.OperationDetails
+        :return: DocumentIntelligenceOperationDetails. The DocumentIntelligenceOperationDetails is
+         compatible with MutableMapping
+        :rtype: ~azure.ai.documentintelligence.models.DocumentIntelligenceOperationDetails
         :raises ~azure.core.exceptions.HttpResponseError:
         """
         error_map: MutableMapping = {
@@ -2760,7 +3096,7 @@ def get_operation(self, operation_id: str, **kwargs: Any) -> _models.OperationDe
         _headers = kwargs.pop("headers", {}) or {}
         _params = kwargs.pop("params", {}) or {}
 
-        cls: ClsType[_models.OperationDetails] = kwargs.pop("cls", None)
+        cls: ClsType[_models.DocumentIntelligenceOperationDetails] = kwargs.pop("cls", None)
 
         _request = build_document_intelligence_administration_get_operation_request(
             operation_id=operation_id,
@@ -2787,7 +3123,7 @@ def get_operation(self, operation_id: str, **kwargs: Any) -> _models.OperationDe
                 except (StreamConsumedError, StreamClosedError):
                     pass
             map_error(status_code=response.status_code, response=response, error_map=error_map)
-            error = _deserialize(_models.ErrorResponse, response.json())
+            error = _failsafe_deserialize(_models.DocumentIntelligenceErrorResponse, response.json())
             raise HttpResponseError(response=response, model=error)
 
         response_headers = {}
@@ -2798,7 +3134,7 @@ def get_operation(self, operation_id: str, **kwargs: Any) -> _models.OperationDe
         if _stream:
             deserialized = response.iter_bytes()
         else:
-            deserialized = _deserialize(_models.OperationDetails, response.json())
+            deserialized = _deserialize(_models.DocumentIntelligenceOperationDetails, response.json())
 
         if cls:
             return cls(pipeline_response, deserialized, response_headers)  # type: ignore
@@ -2806,17 +3142,18 @@ def get_operation(self, operation_id: str, **kwargs: Any) -> _models.OperationDe
         return deserialized  # type: ignore
 
     @distributed_trace
-    def list_operations(self, **kwargs: Any) -> Iterable["_models.OperationDetails"]:
+    def list_operations(self, **kwargs: Any) -> Iterable["_models.DocumentIntelligenceOperationDetails"]:
         """Lists all operations.
 
-        :return: An iterator like instance of OperationDetails
-        :rtype: ~azure.core.paging.ItemPaged[~azure.ai.documentintelligence.models.OperationDetails]
+        :return: An iterator like instance of DocumentIntelligenceOperationDetails
+        :rtype:
+         ~azure.core.paging.ItemPaged[~azure.ai.documentintelligence.models.DocumentIntelligenceOperationDetails]
         :raises ~azure.core.exceptions.HttpResponseError:
         """
         _headers = kwargs.pop("headers", {}) or {}
         _params = kwargs.pop("params", {}) or {}
 
-        cls: ClsType[List[_models.OperationDetails]] = kwargs.pop("cls", None)
+        cls: ClsType[List[_models.DocumentIntelligenceOperationDetails]] = kwargs.pop("cls", None)
 
         error_map: MutableMapping = {
             401: ClientAuthenticationError,
@@ -2865,7 +3202,7 @@ def prepare_request(next_link=None):
 
         def extract_data(pipeline_response):
             deserialized = pipeline_response.http_response.json()
-            list_of_elem = _deserialize(List[_models.OperationDetails], deserialized["value"])
+            list_of_elem = _deserialize(List[_models.DocumentIntelligenceOperationDetails], deserialized["value"])
             if cls:
                 list_of_elem = cls(list_of_elem)  # type: ignore
             return deserialized.get("nextLink") or None, iter(list_of_elem)
@@ -2881,7 +3218,7 @@ def get_next(next_link=None):
 
             if response.status_code not in [200]:
                 map_error(status_code=response.status_code, response=response, error_map=error_map)
-                error = _deserialize(_models.ErrorResponse, response.json())
+                error = _failsafe_deserialize(_models.DocumentIntelligenceErrorResponse, response.json())
                 raise HttpResponseError(response=response, model=error)
 
             return pipeline_response
@@ -2889,7 +3226,7 @@ def get_next(next_link=None):
         return ItemPaged(get_next, extract_data)
 
     def _build_classifier_initial(
-        self, build_request: Union[_models.BuildDocumentClassifierRequest, JSON, IO[bytes]], **kwargs: Any
+        self, body: Union[_models.BuildDocumentClassifierRequest, JSON, IO[bytes]], **kwargs: Any
     ) -> Iterator[bytes]:
         error_map: MutableMapping = {
             401: ClientAuthenticationError,
@@ -2907,10 +3244,10 @@ def _build_classifier_initial(
 
         content_type = content_type or "application/json"
         _content = None
-        if isinstance(build_request, (IOBase, bytes)):
-            _content = build_request
+        if isinstance(body, (IOBase, bytes)):
+            _content = body
         else:
-            _content = json.dumps(build_request, cls=SdkJSONEncoder, exclude_readonly=True)  # type: ignore
+            _content = json.dumps(body, cls=SdkJSONEncoder, exclude_readonly=True)  # type: ignore
 
         _request = build_document_intelligence_administration_build_classifier_request(
             content_type=content_type,
@@ -2937,7 +3274,7 @@ def _build_classifier_initial(
             except (StreamConsumedError, StreamClosedError):
                 pass
             map_error(status_code=response.status_code, response=response, error_map=error_map)
-            error = _deserialize(_models.ErrorResponse, response.json())
+            error = _failsafe_deserialize(_models.DocumentIntelligenceErrorResponse, response.json())
             raise HttpResponseError(response=response, model=error)
 
         response_headers = {}
@@ -2953,16 +3290,12 @@ def _build_classifier_initial(
 
     @overload
     def begin_build_classifier(
-        self,
-        build_request: _models.BuildDocumentClassifierRequest,
-        *,
-        content_type: str = "application/json",
-        **kwargs: Any,
+        self, body: _models.BuildDocumentClassifierRequest, *, content_type: str = "application/json", **kwargs: Any
     ) -> LROPoller[_models.DocumentClassifierDetails]:
         """Builds a custom document classifier.
 
-        :param build_request: Build request parameters. Required.
-        :type build_request: ~azure.ai.documentintelligence.models.BuildDocumentClassifierRequest
+        :param body: Build request parameters. Required.
+        :type body: ~azure.ai.documentintelligence.models.BuildDocumentClassifierRequest
         :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
          Default value is "application/json".
         :paramtype content_type: str
@@ -2975,12 +3308,12 @@ def begin_build_classifier(
 
     @overload
     def begin_build_classifier(
-        self, build_request: JSON, *, content_type: str = "application/json", **kwargs: Any
+        self, body: JSON, *, content_type: str = "application/json", **kwargs: Any
     ) -> LROPoller[_models.DocumentClassifierDetails]:
         """Builds a custom document classifier.
 
-        :param build_request: Build request parameters. Required.
-        :type build_request: JSON
+        :param body: Build request parameters. Required.
+        :type body: JSON
         :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
          Default value is "application/json".
         :paramtype content_type: str
@@ -2993,12 +3326,12 @@ def begin_build_classifier(
 
     @overload
     def begin_build_classifier(
-        self, build_request: IO[bytes], *, content_type: str = "application/json", **kwargs: Any
+        self, body: IO[bytes], *, content_type: str = "application/json", **kwargs: Any
     ) -> LROPoller[_models.DocumentClassifierDetails]:
         """Builds a custom document classifier.
 
-        :param build_request: Build request parameters. Required.
-        :type build_request: IO[bytes]
+        :param body: Build request parameters. Required.
+        :type body: IO[bytes]
         :keyword content_type: Body Parameter content-type. Content type parameter for binary body.
          Default value is "application/json".
         :paramtype content_type: str
@@ -3011,14 +3344,14 @@ def begin_build_classifier(
 
     @distributed_trace
     def begin_build_classifier(
-        self, build_request: Union[_models.BuildDocumentClassifierRequest, JSON, IO[bytes]], **kwargs: Any
+        self, body: Union[_models.BuildDocumentClassifierRequest, JSON, IO[bytes]], **kwargs: Any
     ) -> LROPoller[_models.DocumentClassifierDetails]:
         """Builds a custom document classifier.
 
-        :param build_request: Build request parameters. Is one of the following types:
+        :param body: Build request parameters. Is one of the following types:
          BuildDocumentClassifierRequest, JSON, IO[bytes] Required.
-        :type build_request: ~azure.ai.documentintelligence.models.BuildDocumentClassifierRequest or
-         JSON or IO[bytes]
+        :type body: ~azure.ai.documentintelligence.models.BuildDocumentClassifierRequest or JSON or
+         IO[bytes]
         :return: An instance of LROPoller that returns DocumentClassifierDetails. The
          DocumentClassifierDetails is compatible with MutableMapping
         :rtype:
@@ -3035,12 +3368,7 @@ def begin_build_classifier(
         cont_token: Optional[str] = kwargs.pop("continuation_token", None)
         if cont_token is None:
             raw_result = self._build_classifier_initial(
-                build_request=build_request,
-                content_type=content_type,
-                cls=lambda x, y, z: x,
-                headers=_headers,
-                params=_params,
-                **kwargs,
+                body=body, content_type=content_type, cls=lambda x, y, z: x, headers=_headers, params=_params, **kwargs
             )
             raw_result.http_response.read()  # type: ignore
         kwargs.pop("error_map", None)
@@ -3083,18 +3411,13 @@ def get_long_running_output(pipeline_response):
 
     @overload
     def authorize_classifier_copy(
-        self,
-        authorize_copy_request: _models.AuthorizeClassifierCopyRequest,
-        *,
-        content_type: str = "application/json",
-        **kwargs: Any,
+        self, body: _models.AuthorizeClassifierCopyRequest, *, content_type: str = "application/json", **kwargs: Any
     ) -> _models.ClassifierCopyAuthorization:
         """Generates authorization to copy a document classifier to this location with
         specified classifierId and optional description.
 
-        :param authorize_copy_request: Authorize copy request parameters. Required.
-        :type authorize_copy_request:
-         ~azure.ai.documentintelligence.models.AuthorizeClassifierCopyRequest
+        :param body: Authorize copy request parameters. Required.
+        :type body: ~azure.ai.documentintelligence.models.AuthorizeClassifierCopyRequest
         :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
          Default value is "application/json".
         :paramtype content_type: str
@@ -3106,13 +3429,13 @@ def authorize_classifier_copy(
 
     @overload
     def authorize_classifier_copy(
-        self, authorize_copy_request: JSON, *, content_type: str = "application/json", **kwargs: Any
+        self, body: JSON, *, content_type: str = "application/json", **kwargs: Any
     ) -> _models.ClassifierCopyAuthorization:
         """Generates authorization to copy a document classifier to this location with
         specified classifierId and optional description.
 
-        :param authorize_copy_request: Authorize copy request parameters. Required.
-        :type authorize_copy_request: JSON
+        :param body: Authorize copy request parameters. Required.
+        :type body: JSON
         :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
          Default value is "application/json".
         :paramtype content_type: str
@@ -3124,13 +3447,13 @@ def authorize_classifier_copy(
 
     @overload
     def authorize_classifier_copy(
-        self, authorize_copy_request: IO[bytes], *, content_type: str = "application/json", **kwargs: Any
+        self, body: IO[bytes], *, content_type: str = "application/json", **kwargs: Any
     ) -> _models.ClassifierCopyAuthorization:
         """Generates authorization to copy a document classifier to this location with
         specified classifierId and optional description.
 
-        :param authorize_copy_request: Authorize copy request parameters. Required.
-        :type authorize_copy_request: IO[bytes]
+        :param body: Authorize copy request parameters. Required.
+        :type body: IO[bytes]
         :keyword content_type: Body Parameter content-type. Content type parameter for binary body.
          Default value is "application/json".
         :paramtype content_type: str
@@ -3142,15 +3465,15 @@ def authorize_classifier_copy(
 
     @distributed_trace
     def authorize_classifier_copy(
-        self, authorize_copy_request: Union[_models.AuthorizeClassifierCopyRequest, JSON, IO[bytes]], **kwargs: Any
+        self, body: Union[_models.AuthorizeClassifierCopyRequest, JSON, IO[bytes]], **kwargs: Any
     ) -> _models.ClassifierCopyAuthorization:
         """Generates authorization to copy a document classifier to this location with
         specified classifierId and optional description.
 
-        :param authorize_copy_request: Authorize copy request parameters. Is one of the following
-         types: AuthorizeClassifierCopyRequest, JSON, IO[bytes] Required.
-        :type authorize_copy_request:
-         ~azure.ai.documentintelligence.models.AuthorizeClassifierCopyRequest or JSON or IO[bytes]
+        :param body: Authorize copy request parameters. Is one of the following types:
+         AuthorizeClassifierCopyRequest, JSON, IO[bytes] Required.
+        :type body: ~azure.ai.documentintelligence.models.AuthorizeClassifierCopyRequest or JSON or
+         IO[bytes]
         :return: ClassifierCopyAuthorization. The ClassifierCopyAuthorization is compatible with
          MutableMapping
         :rtype: ~azure.ai.documentintelligence.models.ClassifierCopyAuthorization
@@ -3172,10 +3495,10 @@ def authorize_classifier_copy(
 
         content_type = content_type or "application/json"
         _content = None
-        if isinstance(authorize_copy_request, (IOBase, bytes)):
-            _content = authorize_copy_request
+        if isinstance(body, (IOBase, bytes)):
+            _content = body
         else:
-            _content = json.dumps(authorize_copy_request, cls=SdkJSONEncoder, exclude_readonly=True)  # type: ignore
+            _content = json.dumps(body, cls=SdkJSONEncoder, exclude_readonly=True)  # type: ignore
 
         _request = build_document_intelligence_administration_authorize_classifier_copy_request(
             content_type=content_type,
@@ -3203,7 +3526,7 @@ def authorize_classifier_copy(
                 except (StreamConsumedError, StreamClosedError):
                     pass
             map_error(status_code=response.status_code, response=response, error_map=error_map)
-            error = _deserialize(_models.ErrorResponse, response.json())
+            error = _failsafe_deserialize(_models.DocumentIntelligenceErrorResponse, response.json())
             raise HttpResponseError(response=response, model=error)
 
         if _stream:
@@ -3217,10 +3540,7 @@ def authorize_classifier_copy(
         return deserialized  # type: ignore
 
     def _copy_classifier_to_initial(
-        self,
-        classifier_id: str,
-        copy_to_request: Union[_models.ClassifierCopyAuthorization, JSON, IO[bytes]],
-        **kwargs: Any,
+        self, classifier_id: str, body: Union[_models.ClassifierCopyAuthorization, JSON, IO[bytes]], **kwargs: Any
     ) -> Iterator[bytes]:
         error_map: MutableMapping = {
             401: ClientAuthenticationError,
@@ -3238,10 +3558,10 @@ def _copy_classifier_to_initial(
 
         content_type = content_type or "application/json"
         _content = None
-        if isinstance(copy_to_request, (IOBase, bytes)):
-            _content = copy_to_request
+        if isinstance(body, (IOBase, bytes)):
+            _content = body
         else:
-            _content = json.dumps(copy_to_request, cls=SdkJSONEncoder, exclude_readonly=True)  # type: ignore
+            _content = json.dumps(body, cls=SdkJSONEncoder, exclude_readonly=True)  # type: ignore
 
         _request = build_document_intelligence_administration_copy_classifier_to_request(
             classifier_id=classifier_id,
@@ -3269,7 +3589,7 @@ def _copy_classifier_to_initial(
             except (StreamConsumedError, StreamClosedError):
                 pass
             map_error(status_code=response.status_code, response=response, error_map=error_map)
-            error = _deserialize(_models.ErrorResponse, response.json())
+            error = _failsafe_deserialize(_models.DocumentIntelligenceErrorResponse, response.json())
             raise HttpResponseError(response=response, model=error)
 
         response_headers = {}
@@ -3287,7 +3607,7 @@ def _copy_classifier_to_initial(
     def begin_copy_classifier_to(
         self,
         classifier_id: str,
-        copy_to_request: _models.ClassifierCopyAuthorization,
+        body: _models.ClassifierCopyAuthorization,
         *,
         content_type: str = "application/json",
         **kwargs: Any,
@@ -3296,8 +3616,8 @@ def begin_copy_classifier_to(
 
         :param classifier_id: Unique document classifier name. Required.
         :type classifier_id: str
-        :param copy_to_request: Copy to request parameters. Required.
-        :type copy_to_request: ~azure.ai.documentintelligence.models.ClassifierCopyAuthorization
+        :param body: Copy to request parameters. Required.
+        :type body: ~azure.ai.documentintelligence.models.ClassifierCopyAuthorization
         :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
          Default value is "application/json".
         :paramtype content_type: str
@@ -3310,14 +3630,14 @@ def begin_copy_classifier_to(
 
     @overload
     def begin_copy_classifier_to(
-        self, classifier_id: str, copy_to_request: JSON, *, content_type: str = "application/json", **kwargs: Any
+        self, classifier_id: str, body: JSON, *, content_type: str = "application/json", **kwargs: Any
     ) -> LROPoller[_models.DocumentClassifierDetails]:
         """Copies document classifier to the target resource, region, and classifierId.
 
         :param classifier_id: Unique document classifier name. Required.
         :type classifier_id: str
-        :param copy_to_request: Copy to request parameters. Required.
-        :type copy_to_request: JSON
+        :param body: Copy to request parameters. Required.
+        :type body: JSON
         :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
          Default value is "application/json".
         :paramtype content_type: str
@@ -3330,14 +3650,14 @@ def begin_copy_classifier_to(
 
     @overload
     def begin_copy_classifier_to(
-        self, classifier_id: str, copy_to_request: IO[bytes], *, content_type: str = "application/json", **kwargs: Any
+        self, classifier_id: str, body: IO[bytes], *, content_type: str = "application/json", **kwargs: Any
     ) -> LROPoller[_models.DocumentClassifierDetails]:
         """Copies document classifier to the target resource, region, and classifierId.
 
         :param classifier_id: Unique document classifier name. Required.
         :type classifier_id: str
-        :param copy_to_request: Copy to request parameters. Required.
-        :type copy_to_request: IO[bytes]
+        :param body: Copy to request parameters. Required.
+        :type body: IO[bytes]
         :keyword content_type: Body Parameter content-type. Content type parameter for binary body.
          Default value is "application/json".
         :paramtype content_type: str
@@ -3350,19 +3670,16 @@ def begin_copy_classifier_to(
 
     @distributed_trace
     def begin_copy_classifier_to(
-        self,
-        classifier_id: str,
-        copy_to_request: Union[_models.ClassifierCopyAuthorization, JSON, IO[bytes]],
-        **kwargs: Any,
+        self, classifier_id: str, body: Union[_models.ClassifierCopyAuthorization, JSON, IO[bytes]], **kwargs: Any
     ) -> LROPoller[_models.DocumentClassifierDetails]:
         """Copies document classifier to the target resource, region, and classifierId.
 
         :param classifier_id: Unique document classifier name. Required.
         :type classifier_id: str
-        :param copy_to_request: Copy to request parameters. Is one of the following types:
+        :param body: Copy to request parameters. Is one of the following types:
          ClassifierCopyAuthorization, JSON, IO[bytes] Required.
-        :type copy_to_request: ~azure.ai.documentintelligence.models.ClassifierCopyAuthorization or
-         JSON or IO[bytes]
+        :type body: ~azure.ai.documentintelligence.models.ClassifierCopyAuthorization or JSON or
+         IO[bytes]
         :return: An instance of LROPoller that returns DocumentClassifierDetails. The
          DocumentClassifierDetails is compatible with MutableMapping
         :rtype:
@@ -3380,7 +3697,7 @@ def begin_copy_classifier_to(
         if cont_token is None:
             raw_result = self._copy_classifier_to_initial(
                 classifier_id=classifier_id,
-                copy_to_request=copy_to_request,
+                body=body,
                 content_type=content_type,
                 cls=lambda x, y, z: x,
                 headers=_headers,
@@ -3475,7 +3792,7 @@ def get_classifier(self, classifier_id: str, **kwargs: Any) -> _models.DocumentC
                 except (StreamConsumedError, StreamClosedError):
                     pass
             map_error(status_code=response.status_code, response=response, error_map=error_map)
-            error = _deserialize(_models.ErrorResponse, response.json())
+            error = _failsafe_deserialize(_models.DocumentIntelligenceErrorResponse, response.json())
             raise HttpResponseError(response=response, model=error)
 
         response_headers = {}
@@ -3570,7 +3887,7 @@ def get_next(next_link=None):
 
             if response.status_code not in [200]:
                 map_error(status_code=response.status_code, response=response, error_map=error_map)
-                error = _deserialize(_models.ErrorResponse, response.json())
+                error = _failsafe_deserialize(_models.DocumentIntelligenceErrorResponse, response.json())
                 raise HttpResponseError(response=response, model=error)
 
             return pipeline_response
@@ -3622,7 +3939,7 @@ def delete_classifier(  # pylint: disable=inconsistent-return-statements
 
         if response.status_code not in [204]:
             map_error(status_code=response.status_code, response=response, error_map=error_map)
-            error = _deserialize(_models.ErrorResponse, response.json())
+            error = _failsafe_deserialize(_models.DocumentIntelligenceErrorResponse, response.json())
             raise HttpResponseError(response=response, model=error)
 
         response_headers = {}
diff --git a/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/_operations/_patch.py b/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/_operations/_patch.py
index 1d019820174ec..f7dd32510333d 100644
--- a/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/_operations/_patch.py
+++ b/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/_operations/_patch.py
@@ -6,697 +6,9 @@
 
 Follow our quickstart for examples: https://aka.ms/azsdk/python/dpcodegen/python/customize
 """
-import sys
-import re
-from typing import Any, Callable, Dict, IO, List, Optional, TypeVar, Union, Mapping, cast, overload
+from typing import List
 
-from azure.core.pipeline import PipelineResponse
-from azure.core.polling import LROPoller, NoPolling, PollingMethod
-from azure.core.polling.base_polling import LROBasePolling
-from azure.core.rest import HttpRequest, HttpResponse
-from azure.core.tracing.decorator import distributed_trace
-from azure.core.utils import case_insensitive_dict
-
-from ._operations import (
-    DocumentIntelligenceClientOperationsMixin as GeneratedDIClientOps,
-    DocumentIntelligenceAdministrationClientOperationsMixin as GeneratedDIAdminClientOps,
-)
-from .. import models as _models
-from .._model_base import _deserialize
-
-if sys.version_info >= (3, 9):
-    from collections.abc import MutableMapping
-else:
-    from typing import MutableMapping  # type: ignore
-JSON = MutableMapping[str, Any]  # pylint: disable=unsubscriptable-object
-T = TypeVar("T")
-ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]]
-PollingReturnType_co = TypeVar("PollingReturnType_co", covariant=True)
-_FINISHED = frozenset(["succeeded", "canceled", "failed", "completed"])
-
-
-def _parse_operation_id(operation_location_header):
-    regex = "[^:]+://[^/]+/documentintelligence/.+/([^?/]+)"
-    return re.match(regex, operation_location_header).group(1)
-
-
-def _finished(status) -> bool:
-    if hasattr(status, "value"):
-        status = status.value
-    return str(status).lower() in _FINISHED
-
-
-class AnalyzeDocumentLROPoller(LROPoller[PollingReturnType_co]):
-    @property
-    def details(self) -> Mapping[str, Any]:
-        """Returns metadata associated with the long-running operation.
-
-        :return: Returns metadata associated with the long-running operation.
-        :rtype: Mapping[str, Any]
-        """
-        return {
-            "operation_id": _parse_operation_id(
-                self.polling_method()._initial_response.http_response.headers["Operation-Location"]  # type: ignore # pylint: disable=protected-access
-            ),
-        }
-
-    @classmethod
-    def from_continuation_token(
-        cls, polling_method: PollingMethod[PollingReturnType_co], continuation_token: str, **kwargs: Any
-    ) -> "AnalyzeDocumentLROPoller":
-        (
-            client,
-            initial_response,
-            deserialization_callback,
-        ) = polling_method.from_continuation_token(continuation_token, **kwargs)
-
-        return cls(client, initial_response, deserialization_callback, polling_method)
-
-
-class AnalyzeBatchDocumentsLROPollingMethod(LROBasePolling):
-    def finished(self) -> bool:
-        """Is this polling finished?
-
-        :return: Whether polling is finished or not.
-        :rtype: bool
-        """
-        return _finished(self.status())
-
-
-class DocumentIntelligenceAdministrationClientOperationsMixin(
-    GeneratedDIAdminClientOps
-):  # pylint: disable=name-too-long
-    @distributed_trace
-    def begin_build_classifier(
-        self, build_request: Union[_models.BuildDocumentClassifierRequest, JSON, IO[bytes]], **kwargs: Any
-    ) -> LROPoller[_models.DocumentClassifierDetails]:
-        _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
-        _params = kwargs.pop("params", {}) or {}
-
-        content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
-        cls: ClsType[_models.DocumentClassifierDetails] = kwargs.pop("cls", None)
-        polling: Union[bool, PollingMethod] = kwargs.pop("polling", True)
-        lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
-        cont_token: Optional[str] = kwargs.pop("continuation_token", None)
-        if cont_token is None:
-            raw_result = self._build_classifier_initial(
-                build_request=build_request,
-                content_type=content_type,
-                cls=lambda x, y, z: x,
-                headers=_headers,
-                params=_params,
-                **kwargs,
-            )
-            raw_result.http_response.read()  # type: ignore
-        kwargs.pop("error_map", None)
-
-        def get_long_running_output(pipeline_response):
-            response_headers = {}
-            response = pipeline_response.http_response
-            response_headers["Retry-After"] = self._deserialize("int", response.headers.get("Retry-After"))
-            response_headers["Operation-Location"] = self._deserialize(
-                "str", response.headers.get("Operation-Location")
-            )
-
-            deserialized = _deserialize(_models.DocumentClassifierDetails, response.json())
-            if cls:
-                return cls(pipeline_response, deserialized, response_headers)  # type: ignore
-            return deserialized
-
-        path_format_arguments = {
-            "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str", skip_quote=True),
-        }
-
-        if polling is True:
-            polling_method: PollingMethod = cast(
-                PollingMethod, LROBasePolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs)
-            )
-        elif polling is False:
-            polling_method = cast(PollingMethod, NoPolling())
-        else:
-            polling_method = polling
-        if cont_token:
-            return LROPoller[_models.DocumentClassifierDetails].from_continuation_token(
-                polling_method=polling_method,
-                continuation_token=cont_token,
-                client=self._client,
-                deserialization_callback=get_long_running_output,
-            )
-        return LROPoller[_models.DocumentClassifierDetails](
-            self._client, raw_result, get_long_running_output, polling_method  # type: ignore
-        )
-
-    @distributed_trace
-    def begin_build_document_model(
-        self, build_request: Union[_models.BuildDocumentModelRequest, JSON, IO[bytes]], **kwargs: Any
-    ) -> LROPoller[_models.DocumentModelDetails]:
-        _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
-        _params = kwargs.pop("params", {}) or {}
-
-        content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
-        cls: ClsType[_models.DocumentModelDetails] = kwargs.pop("cls", None)
-        polling: Union[bool, PollingMethod] = kwargs.pop("polling", True)
-        lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
-        cont_token: Optional[str] = kwargs.pop("continuation_token", None)
-        if cont_token is None:
-            raw_result = self._build_document_model_initial(
-                build_request=build_request,
-                content_type=content_type,
-                cls=lambda x, y, z: x,
-                headers=_headers,
-                params=_params,
-                **kwargs,
-            )
-            raw_result.http_response.read()  # type: ignore
-        kwargs.pop("error_map", None)
-
-        def get_long_running_output(pipeline_response):
-            response_headers = {}
-            response = pipeline_response.http_response
-            response_headers["Retry-After"] = self._deserialize("int", response.headers.get("Retry-After"))
-            response_headers["Operation-Location"] = self._deserialize(
-                "str", response.headers.get("Operation-Location")
-            )
-
-            deserialized = _deserialize(_models.DocumentModelDetails, response.json())
-            if cls:
-                return cls(pipeline_response, deserialized, response_headers)  # type: ignore
-            return deserialized
-
-        path_format_arguments = {
-            "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str", skip_quote=True),
-        }
-
-        if polling is True:
-            polling_method: PollingMethod = cast(
-                PollingMethod, LROBasePolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs)
-            )
-        elif polling is False:
-            polling_method = cast(PollingMethod, NoPolling())
-        else:
-            polling_method = polling
-        if cont_token:
-            return LROPoller[_models.DocumentModelDetails].from_continuation_token(
-                polling_method=polling_method,
-                continuation_token=cont_token,
-                client=self._client,
-                deserialization_callback=get_long_running_output,
-            )
-        return LROPoller[_models.DocumentModelDetails](
-            self._client, raw_result, get_long_running_output, polling_method  # type: ignore
-        )
-
-    @distributed_trace
-    def begin_compose_model(
-        self, compose_request: Union[_models.ComposeDocumentModelRequest, JSON, IO[bytes]], **kwargs: Any
-    ) -> LROPoller[_models.DocumentModelDetails]:
-        _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
-        _params = kwargs.pop("params", {}) or {}
-
-        content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
-        cls: ClsType[_models.DocumentModelDetails] = kwargs.pop("cls", None)
-        polling: Union[bool, PollingMethod] = kwargs.pop("polling", True)
-        lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
-        cont_token: Optional[str] = kwargs.pop("continuation_token", None)
-        if cont_token is None:
-            raw_result = self._compose_model_initial(
-                compose_request=compose_request,
-                content_type=content_type,
-                cls=lambda x, y, z: x,
-                headers=_headers,
-                params=_params,
-                **kwargs,
-            )
-            raw_result.http_response.read()  # type: ignore
-        kwargs.pop("error_map", None)
-
-        def get_long_running_output(pipeline_response):
-            response_headers = {}
-            response = pipeline_response.http_response
-            response_headers["Retry-After"] = self._deserialize("int", response.headers.get("Retry-After"))
-            response_headers["Operation-Location"] = self._deserialize(
-                "str", response.headers.get("Operation-Location")
-            )
-
-            deserialized = _deserialize(_models.DocumentModelDetails, response.json())
-            if cls:
-                return cls(pipeline_response, deserialized, response_headers)  # type: ignore
-            return deserialized
-
-        path_format_arguments = {
-            "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str", skip_quote=True),
-        }
-
-        if polling is True:
-            polling_method: PollingMethod = cast(
-                PollingMethod, LROBasePolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs)
-            )
-        elif polling is False:
-            polling_method = cast(PollingMethod, NoPolling())
-        else:
-            polling_method = polling
-        if cont_token:
-            return LROPoller[_models.DocumentModelDetails].from_continuation_token(
-                polling_method=polling_method,
-                continuation_token=cont_token,
-                client=self._client,
-                deserialization_callback=get_long_running_output,
-            )
-        return LROPoller[_models.DocumentModelDetails](
-            self._client, raw_result, get_long_running_output, polling_method  # type: ignore
-        )
-
-    @distributed_trace
-    def begin_copy_model_to(
-        self, model_id: str, copy_to_request: Union[_models.CopyAuthorization, JSON, IO[bytes]], **kwargs: Any
-    ) -> LROPoller[_models.DocumentModelDetails]:
-        _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
-        _params = kwargs.pop("params", {}) or {}
-
-        content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
-        cls: ClsType[_models.DocumentModelDetails] = kwargs.pop("cls", None)
-        polling: Union[bool, PollingMethod] = kwargs.pop("polling", True)
-        lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
-        cont_token: Optional[str] = kwargs.pop("continuation_token", None)
-        if cont_token is None:
-            raw_result = self._copy_model_to_initial(
-                model_id=model_id,
-                copy_to_request=copy_to_request,
-                content_type=content_type,
-                cls=lambda x, y, z: x,
-                headers=_headers,
-                params=_params,
-                **kwargs,
-            )
-            raw_result.http_response.read()  # type: ignore
-        kwargs.pop("error_map", None)
-
-        def get_long_running_output(pipeline_response):
-            response_headers = {}
-            response = pipeline_response.http_response
-            response_headers["Retry-After"] = self._deserialize("int", response.headers.get("Retry-After"))
-            response_headers["Operation-Location"] = self._deserialize(
-                "str", response.headers.get("Operation-Location")
-            )
-
-            deserialized = _deserialize(_models.DocumentModelDetails, response.json())
-            if cls:
-                return cls(pipeline_response, deserialized, response_headers)  # type: ignore
-            return deserialized
-
-        path_format_arguments = {
-            "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str", skip_quote=True),
-        }
-
-        if polling is True:
-            polling_method: PollingMethod = cast(
-                PollingMethod, LROBasePolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs)
-            )
-        elif polling is False:
-            polling_method = cast(PollingMethod, NoPolling())
-        else:
-            polling_method = polling
-        if cont_token:
-            return LROPoller[_models.DocumentModelDetails].from_continuation_token(
-                polling_method=polling_method,
-                continuation_token=cont_token,
-                client=self._client,
-                deserialization_callback=get_long_running_output,
-            )
-        return LROPoller[_models.DocumentModelDetails](
-            self._client, raw_result, get_long_running_output, polling_method  # type: ignore
-        )
-
-    @distributed_trace
-    def begin_copy_classifier_to(
-        self,
-        classifier_id: str,
-        copy_to_request: Union[_models.ClassifierCopyAuthorization, JSON, IO[bytes]],
-        **kwargs: Any,
-    ) -> LROPoller[_models.DocumentClassifierDetails]:
-        _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
-        _params = kwargs.pop("params", {}) or {}
-
-        content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
-        cls: ClsType[_models.DocumentClassifierDetails] = kwargs.pop("cls", None)
-        polling: Union[bool, PollingMethod] = kwargs.pop("polling", True)
-        lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
-        cont_token: Optional[str] = kwargs.pop("continuation_token", None)
-        if cont_token is None:
-            raw_result = self._copy_classifier_to_initial(
-                classifier_id=classifier_id,
-                copy_to_request=copy_to_request,
-                content_type=content_type,
-                cls=lambda x, y, z: x,
-                headers=_headers,
-                params=_params,
-                **kwargs,
-            )
-            raw_result.http_response.read()  # type: ignore
-        kwargs.pop("error_map", None)
-
-        def get_long_running_output(pipeline_response):
-            response_headers = {}
-            response = pipeline_response.http_response
-            response_headers["Retry-After"] = self._deserialize("int", response.headers.get("Retry-After"))
-            response_headers["Operation-Location"] = self._deserialize(
-                "str", response.headers.get("Operation-Location")
-            )
-
-            deserialized = _deserialize(_models.DocumentClassifierDetails, response.json())
-            if cls:
-                return cls(pipeline_response, deserialized, response_headers)  # type: ignore
-            return deserialized
-
-        path_format_arguments = {
-            "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str", skip_quote=True),
-        }
-
-        if polling is True:
-            polling_method: PollingMethod = cast(
-                PollingMethod, LROBasePolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs)
-            )
-        elif polling is False:
-            polling_method = cast(PollingMethod, NoPolling())
-        else:
-            polling_method = polling
-        if cont_token:
-            return LROPoller[_models.DocumentClassifierDetails].from_continuation_token(
-                polling_method=polling_method,
-                continuation_token=cont_token,
-                client=self._client,
-                deserialization_callback=get_long_running_output,
-            )
-        return LROPoller[_models.DocumentClassifierDetails](
-            self._client, raw_result, get_long_running_output, polling_method  # type: ignore
-        )
-
-
-class DocumentIntelligenceClientOperationsMixin(GeneratedDIClientOps):  # pylint: disable=name-too-long
-    @overload
-    def begin_analyze_document(
-        self,
-        model_id: str,
-        analyze_request: Optional[_models.AnalyzeDocumentRequest] = None,
-        *,
-        pages: Optional[str] = None,
-        locale: Optional[str] = None,
-        string_index_type: Optional[Union[str, _models.StringIndexType]] = None,
-        features: Optional[List[Union[str, _models.DocumentAnalysisFeature]]] = None,
-        query_fields: Optional[List[str]] = None,
-        output_content_format: Optional[Union[str, _models.ContentFormat]] = None,
-        output: Optional[List[Union[str, _models.AnalyzeOutputOption]]] = None,
-        content_type: str = "application/json",
-        **kwargs: Any,
-    ) -> AnalyzeDocumentLROPoller[_models.AnalyzeResult]:
-        """Analyzes document with document model.
-
-        :param model_id: Unique document model name. Required.
-        :type model_id: str
-        :param analyze_request: Analyze request parameters. Default value is None.
-        :type analyze_request: ~azure.ai.documentintelligence.models.AnalyzeDocumentRequest
-        :keyword pages: Range of 1-based page numbers to analyze.  Ex. "1-3,5,7-9". Default value is
-         None.
-        :paramtype pages: str
-        :keyword locale: Locale hint for text recognition and document analysis.  Value may contain
-         only
-         the language code (ex. "en", "fr") or BCP 47 language tag (ex. "en-US"). Default value is
-         None.
-        :paramtype locale: str
-        :keyword string_index_type: Method used to compute string offset and length. Known values are:
-         "textElements", "unicodeCodePoint", and "utf16CodeUnit". Default value is None.
-        :paramtype string_index_type: str or ~azure.ai.documentintelligence.models.StringIndexType
-        :keyword features: List of optional analysis features. Default value is None.
-        :paramtype features: list[str or ~azure.ai.documentintelligence.models.DocumentAnalysisFeature]
-        :keyword query_fields: List of additional fields to extract.  Ex. "NumberOfGuests,StoreNumber".
-         Default value is None.
-        :paramtype query_fields: list[str]
-        :keyword output_content_format: Format of the analyze result top-level content. Known values
-         are: "text" and "markdown". Default value is None.
-        :paramtype output_content_format: str or ~azure.ai.documentintelligence.models.ContentFormat
-        :keyword output: Additional outputs to generate during analysis. Default value is None.
-        :paramtype output: list[str or ~azure.ai.documentintelligence.models.AnalyzeOutputOption]
-        :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
-         Default value is "application/json".
-        :paramtype content_type: str
-        :return: An instance of AnalyzeDocumentLROPoller that returns AnalyzeResult. The AnalyzeResult is compatible
-         with MutableMapping
-        :rtype: AnalyzeDocumentLROPoller[~azure.ai.documentintelligence.models.AnalyzeResult]
-        :raises ~azure.core.exceptions.HttpResponseError:
-        """
-
-    @overload
-    def begin_analyze_document(
-        self,
-        model_id: str,
-        analyze_request: Optional[JSON] = None,
-        *,
-        pages: Optional[str] = None,
-        locale: Optional[str] = None,
-        string_index_type: Optional[Union[str, _models.StringIndexType]] = None,
-        features: Optional[List[Union[str, _models.DocumentAnalysisFeature]]] = None,
-        query_fields: Optional[List[str]] = None,
-        output_content_format: Optional[Union[str, _models.ContentFormat]] = None,
-        output: Optional[List[Union[str, _models.AnalyzeOutputOption]]] = None,
-        content_type: str = "application/json",
-        **kwargs: Any,
-    ) -> AnalyzeDocumentLROPoller[_models.AnalyzeResult]:
-        """Analyzes document with document model.
-
-        :param model_id: Unique document model name. Required.
-        :type model_id: str
-        :param analyze_request: Analyze request parameters. Default value is None.
-        :type analyze_request: JSON
-        :keyword pages: Range of 1-based page numbers to analyze.  Ex. "1-3,5,7-9". Default value is
-         None.
-        :paramtype pages: str
-        :keyword locale: Locale hint for text recognition and document analysis.  Value may contain
-         only
-         the language code (ex. "en", "fr") or BCP 47 language tag (ex. "en-US"). Default value is
-         None.
-        :paramtype locale: str
-        :keyword string_index_type: Method used to compute string offset and length. Known values are:
-         "textElements", "unicodeCodePoint", and "utf16CodeUnit". Default value is None.
-        :paramtype string_index_type: str or ~azure.ai.documentintelligence.models.StringIndexType
-        :keyword features: List of optional analysis features. Default value is None.
-        :paramtype features: list[str or ~azure.ai.documentintelligence.models.DocumentAnalysisFeature]
-        :keyword query_fields: List of additional fields to extract.  Ex. "NumberOfGuests,StoreNumber".
-         Default value is None.
-        :paramtype query_fields: list[str]
-        :keyword output_content_format: Format of the analyze result top-level content. Known values
-         are: "text" and "markdown". Default value is None.
-        :paramtype output_content_format: str or ~azure.ai.documentintelligence.models.ContentFormat
-        :keyword output: Additional outputs to generate during analysis. Default value is None.
-        :paramtype output: list[str or ~azure.ai.documentintelligence.models.AnalyzeOutputOption]
-        :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
-         Default value is "application/json".
-        :paramtype content_type: str
-        :return: An instance of AnalyzeDocumentLROPoller that returns AnalyzeResult. The AnalyzeResult is compatible
-         with MutableMapping
-        :rtype: AnalyzeDocumentLROPoller[~azure.ai.documentintelligence.models.AnalyzeResult]
-        :raises ~azure.core.exceptions.HttpResponseError:
-        """
-
-    @overload
-    def begin_analyze_document(
-        self,
-        model_id: str,
-        analyze_request: Optional[IO[bytes]] = None,
-        *,
-        pages: Optional[str] = None,
-        locale: Optional[str] = None,
-        string_index_type: Optional[Union[str, _models.StringIndexType]] = None,
-        features: Optional[List[Union[str, _models.DocumentAnalysisFeature]]] = None,
-        query_fields: Optional[List[str]] = None,
-        output_content_format: Optional[Union[str, _models.ContentFormat]] = None,
-        output: Optional[List[Union[str, _models.AnalyzeOutputOption]]] = None,
-        content_type: str = "application/json",
-        **kwargs: Any,
-    ) -> AnalyzeDocumentLROPoller[_models.AnalyzeResult]:
-        """Analyzes document with document model.
-
-        :param model_id: Unique document model name. Required.
-        :type model_id: str
-        :param analyze_request: Analyze request parameters. Default value is None.
-        :type analyze_request: IO[bytes]
-        :keyword pages: Range of 1-based page numbers to analyze.  Ex. "1-3,5,7-9". Default value is
-         None.
-        :paramtype pages: str
-        :keyword locale: Locale hint for text recognition and document analysis.  Value may contain
-         only
-         the language code (ex. "en", "fr") or BCP 47 language tag (ex. "en-US"). Default value is
-         None.
-        :paramtype locale: str
-        :keyword string_index_type: Method used to compute string offset and length. Known values are:
-         "textElements", "unicodeCodePoint", and "utf16CodeUnit". Default value is None.
-        :paramtype string_index_type: str or ~azure.ai.documentintelligence.models.StringIndexType
-        :keyword features: List of optional analysis features. Default value is None.
-        :paramtype features: list[str or ~azure.ai.documentintelligence.models.DocumentAnalysisFeature]
-        :keyword query_fields: List of additional fields to extract.  Ex. "NumberOfGuests,StoreNumber".
-         Default value is None.
-        :paramtype query_fields: list[str]
-        :keyword output_content_format: Format of the analyze result top-level content. Known values
-         are: "text" and "markdown". Default value is None.
-        :paramtype output_content_format: str or ~azure.ai.documentintelligence.models.ContentFormat
-        :keyword output: Additional outputs to generate during analysis. Default value is None.
-        :paramtype output: list[str or ~azure.ai.documentintelligence.models.AnalyzeOutputOption]
-        :keyword content_type: Body Parameter content-type. Content type parameter for binary body.
-         Default value is "application/json".
-        :paramtype content_type: str
-        :return: An instance of AnalyzeDocumentLROPoller that returns AnalyzeResult. The AnalyzeResult is compatible
-         with MutableMapping
-        :rtype: AnalyzeDocumentLROPoller[~azure.ai.documentintelligence.models.AnalyzeResult]
-        :raises ~azure.core.exceptions.HttpResponseError:
-        """
-
-    @distributed_trace
-    def begin_analyze_document(
-        self,
-        model_id: str,
-        analyze_request: Optional[Union[_models.AnalyzeDocumentRequest, JSON, IO[bytes]]] = None,
-        *,
-        pages: Optional[str] = None,
-        locale: Optional[str] = None,
-        string_index_type: Optional[Union[str, _models.StringIndexType]] = None,
-        features: Optional[List[Union[str, _models.DocumentAnalysisFeature]]] = None,
-        query_fields: Optional[List[str]] = None,
-        output_content_format: Optional[Union[str, _models.ContentFormat]] = None,
-        output: Optional[List[Union[str, _models.AnalyzeOutputOption]]] = None,
-        **kwargs: Any,
-    ) -> AnalyzeDocumentLROPoller[_models.AnalyzeResult]:
-        """Analyzes document with document model.
-
-        :param model_id: Unique document model name. Required.
-        :type model_id: str
-        :param analyze_request: Analyze request parameters. Is one of the following types:
-         AnalyzeDocumentRequest, JSON, IO[bytes] Default value is None.
-        :type analyze_request: ~azure.ai.documentintelligence.models.AnalyzeDocumentRequest or JSON or
-         IO[bytes]
-        :keyword pages: Range of 1-based page numbers to analyze.  Ex. "1-3,5,7-9". Default value is
-         None.
-        :paramtype pages: str
-        :keyword locale: Locale hint for text recognition and document analysis.  Value may contain
-         only
-         the language code (ex. "en", "fr") or BCP 47 language tag (ex. "en-US"). Default value is
-         None.
-        :paramtype locale: str
-        :keyword string_index_type: Method used to compute string offset and length. Known values are:
-         "textElements", "unicodeCodePoint", and "utf16CodeUnit". Default value is None.
-        :paramtype string_index_type: str or ~azure.ai.documentintelligence.models.StringIndexType
-        :keyword features: List of optional analysis features. Default value is None.
-        :paramtype features: list[str or ~azure.ai.documentintelligence.models.DocumentAnalysisFeature]
-        :keyword query_fields: List of additional fields to extract.  Ex. "NumberOfGuests,StoreNumber".
-         Default value is None.
-        :paramtype query_fields: list[str]
-        :keyword output_content_format: Format of the analyze result top-level content. Known values
-         are: "text" and "markdown". Default value is None.
-        :paramtype output_content_format: str or ~azure.ai.documentintelligence.models.ContentFormat
-        :keyword output: Additional outputs to generate during analysis. Default value is None.
-        :paramtype output: list[str or ~azure.ai.documentintelligence.models.AnalyzeOutputOption]
-        :return: An instance of AnalyzeDocumentLROPoller that returns AnalyzeResult. The AnalyzeResult is compatible
-         with MutableMapping
-        :rtype: AnalyzeDocumentLROPoller[~azure.ai.documentintelligence.models.AnalyzeResult]
-        :raises ~azure.core.exceptions.HttpResponseError:
-        """
-        _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
-        _params = kwargs.pop("params", {}) or {}
-
-        content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("content-type", None))
-        cls: ClsType[_models.AnalyzeResult] = kwargs.pop("cls", None)
-        polling: Union[bool, PollingMethod] = kwargs.pop("polling", True)
-        lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
-        cont_token: Optional[str] = kwargs.pop("continuation_token", None)
-        if cont_token is None:
-            raw_result = self._analyze_document_initial(
-                model_id=model_id,
-                analyze_request=analyze_request,
-                pages=pages,
-                locale=locale,
-                string_index_type=string_index_type,
-                features=features,
-                query_fields=query_fields,
-                output_content_format=output_content_format,
-                output=output,
-                content_type=content_type,
-                cls=lambda x, y, z: x,
-                headers=_headers,
-                params=_params,
-                **kwargs,
-            )
-            raw_result.http_response.read()  # type: ignore
-        kwargs.pop("error_map", None)
-
-        def get_long_running_output(pipeline_response):
-            response_headers = {}
-            response = pipeline_response.http_response
-            response_headers["Retry-After"] = self._deserialize("int", response.headers.get("Retry-After"))
-            response_headers["Operation-Location"] = self._deserialize(
-                "str", response.headers.get("Operation-Location")
-            )
-
-            deserialized = _deserialize(_models.AnalyzeResult, response.json().get("analyzeResult"))
-            if cls:
-                return cls(pipeline_response, deserialized, response_headers)  # type: ignore
-            return deserialized
-
-        path_format_arguments = {
-            "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str", skip_quote=True),
-        }
-
-        if polling is True:
-            polling_method: PollingMethod = cast(
-                PollingMethod, LROBasePolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs)
-            )
-        elif polling is False:
-            polling_method = cast(PollingMethod, NoPolling())
-        else:
-            polling_method = polling
-        if cont_token:
-            return AnalyzeDocumentLROPoller[_models.AnalyzeResult].from_continuation_token(
-                polling_method=polling_method,
-                continuation_token=cont_token,
-                client=self._client,
-                deserialization_callback=get_long_running_output,
-            )
-        return AnalyzeDocumentLROPoller[_models.AnalyzeResult](
-            self._client, raw_result, get_long_running_output, polling_method  # type: ignore
-        )
-
-    @distributed_trace
-    def begin_analyze_batch_documents(
-        self,
-        model_id: str,
-        analyze_batch_request: Optional[Union[_models.AnalyzeBatchDocumentsRequest, JSON, IO[bytes]]] = None,
-        *,
-        pages: Optional[str] = None,
-        locale: Optional[str] = None,
-        string_index_type: Optional[Union[str, _models.StringIndexType]] = None,
-        features: Optional[List[Union[str, _models.DocumentAnalysisFeature]]] = None,
-        query_fields: Optional[List[str]] = None,
-        output_content_format: Optional[Union[str, _models.ContentFormat]] = None,
-        output: Optional[List[Union[str, _models.AnalyzeOutputOption]]] = None,
-        **kwargs: Any,
-    ) -> LROPoller[_models.AnalyzeBatchResult]:
-        lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
-        return super().begin_analyze_batch_documents(
-            model_id=model_id,
-            analyze_batch_request=analyze_batch_request,
-            pages=pages,
-            locale=locale,
-            string_index_type=string_index_type,
-            features=features,
-            query_fields=query_fields,
-            output_content_format=output_content_format,
-            output=output,
-            polling=AnalyzeBatchDocumentsLROPollingMethod(timeout=lro_delay),
-            **kwargs,
-        )
-
-
-__all__: List[str] = [
-    "DocumentIntelligenceClientOperationsMixin",
-    "DocumentIntelligenceAdministrationClientOperationsMixin",
-]  # Add all objects you want publicly available to users at this package level
+__all__: List[str] = []  # Add all objects you want publicly available to users at this package level
 
 
 def patch_sdk():
diff --git a/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/_patch.py b/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/_patch.py
index 7ec98325b6140..f7dd32510333d 100644
--- a/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/_patch.py
+++ b/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/_patch.py
@@ -6,86 +6,9 @@
 
 Follow our quickstart for examples: https://aka.ms/azsdk/python/dpcodegen/python/customize
 """
-from typing import Any, List, Union
-from azure.core.credentials import AzureKeyCredential, TokenCredential
-from ._client import (
-    DocumentIntelligenceClient as DIClientGenerated,
-    DocumentIntelligenceAdministrationClient as DIAClientGenerated,
-)
-from ._operations._patch import AnalyzeDocumentLROPoller
+from typing import List
 
-
-class DocumentIntelligenceClient(DIClientGenerated):
-    """DocumentIntelligenceClient.
-
-    :param endpoint: The Document Intelligence service endpoint. Required.
-    :type endpoint: str
-    :param credential: Credential needed for the client to connect to Azure. Is either a
-     AzureKeyCredential type or a TokenCredential type. Required.
-    :type credential: ~azure.core.credentials.AzureKeyCredential or
-     ~azure.core.credentials.TokenCredential
-    :keyword api_version: The API version to use for this operation. Default value is
-     "2024-07-31-preview". Note that overriding this default value may result in unsupported
-     behavior.
-    :paramtype api_version: str
-    :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
-     Retry-After header is present.
-    """
-
-    def __init__(
-        self,
-        endpoint: str,
-        credential: Union[AzureKeyCredential, TokenCredential],
-        **kwargs: Any,
-    ) -> None:
-        # Patch the default polling interval to be 1s.
-        polling_interval = kwargs.pop("polling_interval", 1)
-        super().__init__(
-            endpoint=endpoint,
-            credential=credential,
-            polling_interval=polling_interval,
-            **kwargs,
-        )
-
-
-class DocumentIntelligenceAdministrationClient(DIAClientGenerated):
-    """DocumentIntelligenceAdministrationClient.
-
-    :param endpoint: The Document Intelligence service endpoint. Required.
-    :type endpoint: str
-    :param credential: Credential needed for the client to connect to Azure. Is either a
-     AzureKeyCredential type or a TokenCredential type. Required.
-    :type credential: ~azure.core.credentials.AzureKeyCredential or
-     ~azure.core.credentials.TokenCredential
-    :keyword api_version: The API version to use for this operation. Default value is
-     "2024-07-31-preview". Note that overriding this default value may result in unsupported
-     behavior.
-    :paramtype api_version: str
-    :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
-     Retry-After header is present.
-    """
-
-    def __init__(
-        self,
-        endpoint: str,
-        credential: Union[AzureKeyCredential, TokenCredential],
-        **kwargs: Any,
-    ) -> None:
-        # Patch the default polling interval to be 1s.
-        polling_interval = kwargs.pop("polling_interval", 1)
-        super().__init__(
-            endpoint=endpoint,
-            credential=credential,
-            polling_interval=polling_interval,
-            **kwargs,
-        )
-
-
-__all__: List[str] = [
-    "DocumentIntelligenceClient",
-    "DocumentIntelligenceAdministrationClient",
-    "AnalyzeDocumentLROPoller",
-]  # Add all objects you want publicly available to users at this package level
+__all__: List[str] = []  # Add all objects you want publicly available to users at this package level
 
 
 def patch_sdk():
diff --git a/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/_serialization.py b/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/_serialization.py
index 480e941d758f0..b24ab2885450d 100644
--- a/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/_serialization.py
+++ b/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/_serialization.py
@@ -1,3 +1,4 @@
+# pylint: disable=too-many-lines
 # --------------------------------------------------------------------------
 #
 # Copyright (c) Microsoft Corporation. All rights reserved.
@@ -309,7 +310,7 @@ def _create_xml_node(tag, prefix=None, ns=None):
     return ET.Element(tag)
 
 
-class Model(object):
+class Model:
     """Mixin for all client request body/response body models to support
     serialization and deserialization.
     """
@@ -506,7 +507,6 @@ def _flatten_subtype(cls, key, objects):
     def _classify(cls, response, objects):
         """Check the class _subtype_map for any child classes.
         We want to ignore any inherited _subtype_maps.
-        Remove the polymorphic key from the initial data.
 
         :param dict response: The initial data
         :param dict objects: The class objects
@@ -518,7 +518,7 @@ def _classify(cls, response, objects):
 
             if not isinstance(response, ET.Element):
                 rest_api_response_key = cls._get_rest_key_parts(subtype_key)[-1]
-                subtype_value = response.pop(rest_api_response_key, None) or response.pop(subtype_key, None)
+                subtype_value = response.get(rest_api_response_key, None) or response.get(subtype_key, None)
             else:
                 subtype_value = xml_key_extractor(subtype_key, cls._attribute_map[subtype_key], response)
             if subtype_value:
@@ -563,7 +563,7 @@ def _decode_attribute_map_key(key):
     return key.replace("\\.", ".")
 
 
-class Serializer(object):  # pylint: disable=too-many-public-methods
+class Serializer:  # pylint: disable=too-many-public-methods
     """Request object model serializer."""
 
     basic_types = {str: "str", int: "int", bool: "bool", float: "float"}
@@ -1441,7 +1441,7 @@ def xml_key_extractor(attr, attr_desc, data):  # pylint: disable=unused-argument
     return children[0]
 
 
-class Deserializer(object):
+class Deserializer:
     """Response object model deserializer.
 
     :param dict classes: Class type dictionary for deserializing complex types.
@@ -1683,17 +1683,21 @@ def _instantiate_model(self, response, attrs, additional_properties=None):
             subtype = getattr(response, "_subtype_map", {})
             try:
                 readonly = [
-                    k for k, v in response._validation.items() if v.get("readonly")  # pylint: disable=protected-access
+                    k
+                    for k, v in response._validation.items()  # pylint: disable=protected-access  # type: ignore
+                    if v.get("readonly")
                 ]
                 const = [
-                    k for k, v in response._validation.items() if v.get("constant")  # pylint: disable=protected-access
+                    k
+                    for k, v in response._validation.items()  # pylint: disable=protected-access  # type: ignore
+                    if v.get("constant")
                 ]
                 kwargs = {k: v for k, v in attrs.items() if k not in subtype and k not in readonly + const}
                 response_obj = response(**kwargs)
                 for attr in readonly:
                     setattr(response_obj, attr, attrs.get(attr))
                 if additional_properties:
-                    response_obj.additional_properties = additional_properties
+                    response_obj.additional_properties = additional_properties  # type: ignore
                 return response_obj
             except TypeError as err:
                 msg = "Unable to deserialize {} into model {}. ".format(kwargs, response)  # type: ignore
diff --git a/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/_validation.py b/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/_validation.py
deleted file mode 100644
index 752b2822f9d3e..0000000000000
--- a/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/_validation.py
+++ /dev/null
@@ -1,50 +0,0 @@
-# --------------------------------------------------------------------------
-# Copyright (c) Microsoft Corporation. All rights reserved.
-# Licensed under the MIT License. See License.txt in the project root for license information.
-# Code generated by Microsoft (R) Python Code Generator.
-# Changes may cause incorrect behavior and will be lost if the code is regenerated.
-# --------------------------------------------------------------------------
-import functools
-
-
-def api_version_validation(**kwargs):
-    params_added_on = kwargs.pop("params_added_on", {})
-    method_added_on = kwargs.pop("method_added_on", "")
-
-    def decorator(func):
-        @functools.wraps(func)
-        def wrapper(*args, **kwargs):
-            try:
-                # this assumes the client has an _api_version attribute
-                client = args[0]
-                client_api_version = client._config.api_version  # pylint: disable=protected-access
-            except AttributeError:
-                return func(*args, **kwargs)
-
-            if method_added_on > client_api_version:
-                raise ValueError(
-                    f"'{func.__name__}' is not available in API version "
-                    f"{client_api_version}. Pass service API version {method_added_on} or newer to your client."
-                )
-
-            unsupported = {
-                parameter: api_version
-                for api_version, parameters in params_added_on.items()
-                for parameter in parameters
-                if parameter in kwargs and api_version > client_api_version
-            }
-            if unsupported:
-                raise ValueError(
-                    "".join(
-                        [
-                            f"'{param}' is not available in API version {client_api_version}. "
-                            f"Use service API version {version} or newer.\n"
-                            for param, version in unsupported.items()
-                        ]
-                    )
-                )
-            return func(*args, **kwargs)
-
-        return wrapper
-
-    return decorator
diff --git a/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/_version.py b/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/_version.py
index c7d155d924dde..0ec13ea52bbf5 100644
--- a/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/_version.py
+++ b/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/_version.py
@@ -6,4 +6,4 @@
 # Changes may cause incorrect behavior and will be lost if the code is regenerated.
 # --------------------------------------------------------------------------
 
-VERSION = "1.0.0b5"
+VERSION = "1.0.0"
diff --git a/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/aio/__init__.py b/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/aio/__init__.py
index d42be0aa8a751..02790b905f25f 100644
--- a/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/aio/__init__.py
+++ b/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/aio/__init__.py
@@ -5,18 +5,27 @@
 # Code generated by Microsoft (R) Python Code Generator.
 # Changes may cause incorrect behavior and will be lost if the code is regenerated.
 # --------------------------------------------------------------------------
+# pylint: disable=wrong-import-position
 
-from ._patch import DocumentIntelligenceClient
-from ._patch import DocumentIntelligenceAdministrationClient
+from typing import TYPE_CHECKING
 
+if TYPE_CHECKING:
+    from ._patch import *  # pylint: disable=unused-wildcard-import
 
-from ._patch import AsyncAnalyzeDocumentLROPoller
+from ._client import DocumentIntelligenceClient  # type: ignore
+from ._client import DocumentIntelligenceAdministrationClient  # type: ignore
+
+try:
+    from ._patch import __all__ as _patch_all
+    from ._patch import *
+except ImportError:
+    _patch_all = []
 from ._patch import patch_sdk as _patch_sdk
 
 __all__ = [
-    "AsyncAnalyzeDocumentLROPoller",
     "DocumentIntelligenceClient",
     "DocumentIntelligenceAdministrationClient",
 ]
+__all__.extend([p for p in _patch_all if p not in __all__])  # pyright: ignore
 
 _patch_sdk()
diff --git a/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/aio/_client.py b/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/aio/_client.py
index 9ecaaa07990bf..3fd4e8d233003 100644
--- a/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/aio/_client.py
+++ b/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/aio/_client.py
@@ -38,9 +38,8 @@ class DocumentIntelligenceClient(DocumentIntelligenceClientOperationsMixin):
      AzureKeyCredential type or a TokenCredential type. Required.
     :type credential: ~azure.core.credentials.AzureKeyCredential or
      ~azure.core.credentials_async.AsyncTokenCredential
-    :keyword api_version: The API version to use for this operation. Default value is
-     "2024-07-31-preview". Note that overriding this default value may result in unsupported
-     behavior.
+    :keyword api_version: The API version to use for this operation. Default value is "2024-11-30".
+     Note that overriding this default value may result in unsupported behavior.
     :paramtype api_version: str
     :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
      Retry-After header is present.
@@ -122,9 +121,8 @@ class DocumentIntelligenceAdministrationClient(DocumentIntelligenceAdministratio
      AzureKeyCredential type or a TokenCredential type. Required.
     :type credential: ~azure.core.credentials.AzureKeyCredential or
      ~azure.core.credentials_async.AsyncTokenCredential
-    :keyword api_version: The API version to use for this operation. Default value is
-     "2024-07-31-preview". Note that overriding this default value may result in unsupported
-     behavior.
+    :keyword api_version: The API version to use for this operation. Default value is "2024-11-30".
+     Note that overriding this default value may result in unsupported behavior.
     :paramtype api_version: str
     :keyword int polling_interval: Default waiting time between two polls for LRO operations if no
      Retry-After header is present.
diff --git a/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/aio/_configuration.py b/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/aio/_configuration.py
index 9615be1e277ad..658a80cfa20c5 100644
--- a/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/aio/_configuration.py
+++ b/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/aio/_configuration.py
@@ -29,16 +29,15 @@ class DocumentIntelligenceClientConfiguration:  # pylint: disable=too-many-insta
      AzureKeyCredential type or a TokenCredential type. Required.
     :type credential: ~azure.core.credentials.AzureKeyCredential or
      ~azure.core.credentials_async.AsyncTokenCredential
-    :keyword api_version: The API version to use for this operation. Default value is
-     "2024-07-31-preview". Note that overriding this default value may result in unsupported
-     behavior.
+    :keyword api_version: The API version to use for this operation. Default value is "2024-11-30".
+     Note that overriding this default value may result in unsupported behavior.
     :paramtype api_version: str
     """
 
     def __init__(
         self, endpoint: str, credential: Union[AzureKeyCredential, "AsyncTokenCredential"], **kwargs: Any
     ) -> None:
-        api_version: str = kwargs.pop("api_version", "2024-07-31-preview")
+        api_version: str = kwargs.pop("api_version", "2024-11-30")
 
         if endpoint is None:
             raise ValueError("Parameter 'endpoint' must not be None.")
@@ -86,16 +85,15 @@ class DocumentIntelligenceAdministrationClientConfiguration:  # pylint: disable=
      AzureKeyCredential type or a TokenCredential type. Required.
     :type credential: ~azure.core.credentials.AzureKeyCredential or
      ~azure.core.credentials_async.AsyncTokenCredential
-    :keyword api_version: The API version to use for this operation. Default value is
-     "2024-07-31-preview". Note that overriding this default value may result in unsupported
-     behavior.
+    :keyword api_version: The API version to use for this operation. Default value is "2024-11-30".
+     Note that overriding this default value may result in unsupported behavior.
     :paramtype api_version: str
     """
 
     def __init__(
         self, endpoint: str, credential: Union[AzureKeyCredential, "AsyncTokenCredential"], **kwargs: Any
     ) -> None:
-        api_version: str = kwargs.pop("api_version", "2024-07-31-preview")
+        api_version: str = kwargs.pop("api_version", "2024-11-30")
 
         if endpoint is None:
             raise ValueError("Parameter 'endpoint' must not be None.")
diff --git a/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/aio/_operations/__init__.py b/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/aio/_operations/__init__.py
index 98b551bb5d272..63b6bbb81ed80 100644
--- a/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/aio/_operations/__init__.py
+++ b/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/aio/_operations/__init__.py
@@ -5,15 +5,23 @@
 # Code generated by Microsoft (R) Python Code Generator.
 # Changes may cause incorrect behavior and will be lost if the code is regenerated.
 # --------------------------------------------------------------------------
+# pylint: disable=wrong-import-position
 
-from ._patch import DocumentIntelligenceClientOperationsMixin
-from ._patch import DocumentIntelligenceAdministrationClientOperationsMixin
+from typing import TYPE_CHECKING
 
+if TYPE_CHECKING:
+    from ._patch import *  # pylint: disable=unused-wildcard-import
 
+from ._operations import DocumentIntelligenceClientOperationsMixin  # type: ignore
+from ._operations import DocumentIntelligenceAdministrationClientOperationsMixin  # type: ignore
+
+from ._patch import __all__ as _patch_all
+from ._patch import *
 from ._patch import patch_sdk as _patch_sdk
 
 __all__ = [
     "DocumentIntelligenceClientOperationsMixin",
     "DocumentIntelligenceAdministrationClientOperationsMixin",
 ]
+__all__.extend([p for p in _patch_all if p not in __all__])  # pyright: ignore
 _patch_sdk()
diff --git a/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/aio/_operations/_operations.py b/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/aio/_operations/_operations.py
index aa9dc521495f7..334e48906413e 100644
--- a/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/aio/_operations/_operations.py
+++ b/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/aio/_operations/_operations.py
@@ -32,7 +32,7 @@
 from azure.core.utils import case_insensitive_dict
 
 from ... import models as _models
-from ..._model_base import SdkJSONEncoder, _deserialize
+from ..._model_base import SdkJSONEncoder, _deserialize, _failsafe_deserialize
 from ..._operations._operations import (
     build_document_intelligence_administration_authorize_classifier_copy_request,
     build_document_intelligence_administration_authorize_model_copy_request,
@@ -46,15 +46,19 @@
     build_document_intelligence_administration_get_classifier_request,
     build_document_intelligence_administration_get_model_request,
     build_document_intelligence_administration_get_operation_request,
-    build_document_intelligence_administration_get_resource_info_request,
+    build_document_intelligence_administration_get_resource_details_request,
     build_document_intelligence_administration_list_classifiers_request,
     build_document_intelligence_administration_list_models_request,
     build_document_intelligence_administration_list_operations_request,
     build_document_intelligence_analyze_batch_documents_request,
     build_document_intelligence_analyze_document_request,
     build_document_intelligence_classify_document_request,
+    build_document_intelligence_delete_analyze_batch_result_request,
+    build_document_intelligence_delete_analyze_result_request,
+    build_document_intelligence_get_analyze_batch_result_request,
     build_document_intelligence_get_analyze_result_figure_request,
     build_document_intelligence_get_analyze_result_pdf_request,
+    build_document_intelligence_list_analyze_batch_results_request,
 )
 from .._vendor import DocumentIntelligenceAdministrationClientMixinABC, DocumentIntelligenceClientMixinABC
 
@@ -72,14 +76,14 @@ class DocumentIntelligenceClientOperationsMixin(DocumentIntelligenceClientMixinA
     async def _analyze_document_initial(
         self,
         model_id: str,
-        analyze_request: Optional[Union[_models.AnalyzeDocumentRequest, JSON, IO[bytes]]] = None,
+        body: Union[_models.AnalyzeDocumentRequest, JSON, IO[bytes]],
         *,
         pages: Optional[str] = None,
         locale: Optional[str] = None,
         string_index_type: Optional[Union[str, _models.StringIndexType]] = None,
         features: Optional[List[Union[str, _models.DocumentAnalysisFeature]]] = None,
         query_fields: Optional[List[str]] = None,
-        output_content_format: Optional[Union[str, _models.ContentFormat]] = None,
+        output_content_format: Optional[Union[str, _models.DocumentContentFormat]] = None,
         output: Optional[List[Union[str, _models.AnalyzeOutputOption]]] = None,
         **kwargs: Any
     ) -> AsyncIterator[bytes]:
@@ -99,13 +103,10 @@ async def _analyze_document_initial(
 
         content_type = content_type or "application/json"
         _content = None
-        if isinstance(analyze_request, (IOBase, bytes)):
-            _content = analyze_request
+        if isinstance(body, (IOBase, bytes)):
+            _content = body
         else:
-            if analyze_request is not None:
-                _content = json.dumps(analyze_request, cls=SdkJSONEncoder, exclude_readonly=True)  # type: ignore
-            else:
-                _content = None
+            _content = json.dumps(body, cls=SdkJSONEncoder, exclude_readonly=True)  # type: ignore
 
         _request = build_document_intelligence_analyze_document_request(
             model_id=model_id,
@@ -140,7 +141,7 @@ async def _analyze_document_initial(
             except (StreamConsumedError, StreamClosedError):
                 pass
             map_error(status_code=response.status_code, response=response, error_map=error_map)
-            error = _deserialize(_models.ErrorResponse, response.json())
+            error = _failsafe_deserialize(_models.DocumentIntelligenceErrorResponse, response.json())
             raise HttpResponseError(response=response, model=error)
 
         response_headers = {}
@@ -158,14 +159,14 @@ async def _analyze_document_initial(
     async def begin_analyze_document(
         self,
         model_id: str,
-        analyze_request: Optional[_models.AnalyzeDocumentRequest] = None,
+        body: _models.AnalyzeDocumentRequest,
         *,
         pages: Optional[str] = None,
         locale: Optional[str] = None,
         string_index_type: Optional[Union[str, _models.StringIndexType]] = None,
         features: Optional[List[Union[str, _models.DocumentAnalysisFeature]]] = None,
         query_fields: Optional[List[str]] = None,
-        output_content_format: Optional[Union[str, _models.ContentFormat]] = None,
+        output_content_format: Optional[Union[str, _models.DocumentContentFormat]] = None,
         output: Optional[List[Union[str, _models.AnalyzeOutputOption]]] = None,
         content_type: str = "application/json",
         **kwargs: Any
@@ -174,10 +175,9 @@ async def begin_analyze_document(
 
         :param model_id: Unique document model name. Required.
         :type model_id: str
-        :param analyze_request: Analyze request parameters. Default value is None.
-        :type analyze_request: ~azure.ai.documentintelligence.models.AnalyzeDocumentRequest
-        :keyword pages: Range of 1-based page numbers to analyze.  Ex. "1-3,5,7-9". Default value is
-         None.
+        :param body: Analyze request parameters. Required.
+        :type body: ~azure.ai.documentintelligence.models.AnalyzeDocumentRequest
+        :keyword pages: 1-based page numbers to analyze.  Ex. "1-3,5,7-9". Default value is None.
         :paramtype pages: str
         :keyword locale: Locale hint for text recognition and document analysis.  Value may contain
          only
@@ -194,7 +194,8 @@ async def begin_analyze_document(
         :paramtype query_fields: list[str]
         :keyword output_content_format: Format of the analyze result top-level content. Known values
          are: "text" and "markdown". Default value is None.
-        :paramtype output_content_format: str or ~azure.ai.documentintelligence.models.ContentFormat
+        :paramtype output_content_format: str or
+         ~azure.ai.documentintelligence.models.DocumentContentFormat
         :keyword output: Additional outputs to generate during analysis. Default value is None.
         :paramtype output: list[str or ~azure.ai.documentintelligence.models.AnalyzeOutputOption]
         :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
@@ -210,14 +211,14 @@ async def begin_analyze_document(
     async def begin_analyze_document(
         self,
         model_id: str,
-        analyze_request: Optional[JSON] = None,
+        body: JSON,
         *,
         pages: Optional[str] = None,
         locale: Optional[str] = None,
         string_index_type: Optional[Union[str, _models.StringIndexType]] = None,
         features: Optional[List[Union[str, _models.DocumentAnalysisFeature]]] = None,
         query_fields: Optional[List[str]] = None,
-        output_content_format: Optional[Union[str, _models.ContentFormat]] = None,
+        output_content_format: Optional[Union[str, _models.DocumentContentFormat]] = None,
         output: Optional[List[Union[str, _models.AnalyzeOutputOption]]] = None,
         content_type: str = "application/json",
         **kwargs: Any
@@ -226,10 +227,9 @@ async def begin_analyze_document(
 
         :param model_id: Unique document model name. Required.
         :type model_id: str
-        :param analyze_request: Analyze request parameters. Default value is None.
-        :type analyze_request: JSON
-        :keyword pages: Range of 1-based page numbers to analyze.  Ex. "1-3,5,7-9". Default value is
-         None.
+        :param body: Analyze request parameters. Required.
+        :type body: JSON
+        :keyword pages: 1-based page numbers to analyze.  Ex. "1-3,5,7-9". Default value is None.
         :paramtype pages: str
         :keyword locale: Locale hint for text recognition and document analysis.  Value may contain
          only
@@ -246,7 +246,8 @@ async def begin_analyze_document(
         :paramtype query_fields: list[str]
         :keyword output_content_format: Format of the analyze result top-level content. Known values
          are: "text" and "markdown". Default value is None.
-        :paramtype output_content_format: str or ~azure.ai.documentintelligence.models.ContentFormat
+        :paramtype output_content_format: str or
+         ~azure.ai.documentintelligence.models.DocumentContentFormat
         :keyword output: Additional outputs to generate during analysis. Default value is None.
         :paramtype output: list[str or ~azure.ai.documentintelligence.models.AnalyzeOutputOption]
         :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
@@ -262,14 +263,14 @@ async def begin_analyze_document(
     async def begin_analyze_document(
         self,
         model_id: str,
-        analyze_request: Optional[IO[bytes]] = None,
+        body: IO[bytes],
         *,
         pages: Optional[str] = None,
         locale: Optional[str] = None,
         string_index_type: Optional[Union[str, _models.StringIndexType]] = None,
         features: Optional[List[Union[str, _models.DocumentAnalysisFeature]]] = None,
         query_fields: Optional[List[str]] = None,
-        output_content_format: Optional[Union[str, _models.ContentFormat]] = None,
+        output_content_format: Optional[Union[str, _models.DocumentContentFormat]] = None,
         output: Optional[List[Union[str, _models.AnalyzeOutputOption]]] = None,
         content_type: str = "application/json",
         **kwargs: Any
@@ -278,10 +279,9 @@ async def begin_analyze_document(
 
         :param model_id: Unique document model name. Required.
         :type model_id: str
-        :param analyze_request: Analyze request parameters. Default value is None.
-        :type analyze_request: IO[bytes]
-        :keyword pages: Range of 1-based page numbers to analyze.  Ex. "1-3,5,7-9". Default value is
-         None.
+        :param body: Analyze request parameters. Required.
+        :type body: IO[bytes]
+        :keyword pages: 1-based page numbers to analyze.  Ex. "1-3,5,7-9". Default value is None.
         :paramtype pages: str
         :keyword locale: Locale hint for text recognition and document analysis.  Value may contain
          only
@@ -298,7 +298,8 @@ async def begin_analyze_document(
         :paramtype query_fields: list[str]
         :keyword output_content_format: Format of the analyze result top-level content. Known values
          are: "text" and "markdown". Default value is None.
-        :paramtype output_content_format: str or ~azure.ai.documentintelligence.models.ContentFormat
+        :paramtype output_content_format: str or
+         ~azure.ai.documentintelligence.models.DocumentContentFormat
         :keyword output: Additional outputs to generate during analysis. Default value is None.
         :paramtype output: list[str or ~azure.ai.documentintelligence.models.AnalyzeOutputOption]
         :keyword content_type: Body Parameter content-type. Content type parameter for binary body.
@@ -314,14 +315,14 @@ async def begin_analyze_document(
     async def begin_analyze_document(
         self,
         model_id: str,
-        analyze_request: Optional[Union[_models.AnalyzeDocumentRequest, JSON, IO[bytes]]] = None,
+        body: Union[_models.AnalyzeDocumentRequest, JSON, IO[bytes]],
         *,
         pages: Optional[str] = None,
         locale: Optional[str] = None,
         string_index_type: Optional[Union[str, _models.StringIndexType]] = None,
         features: Optional[List[Union[str, _models.DocumentAnalysisFeature]]] = None,
         query_fields: Optional[List[str]] = None,
-        output_content_format: Optional[Union[str, _models.ContentFormat]] = None,
+        output_content_format: Optional[Union[str, _models.DocumentContentFormat]] = None,
         output: Optional[List[Union[str, _models.AnalyzeOutputOption]]] = None,
         **kwargs: Any
     ) -> AsyncLROPoller[_models.AnalyzeResult]:
@@ -329,12 +330,10 @@ async def begin_analyze_document(
 
         :param model_id: Unique document model name. Required.
         :type model_id: str
-        :param analyze_request: Analyze request parameters. Is one of the following types:
-         AnalyzeDocumentRequest, JSON, IO[bytes] Default value is None.
-        :type analyze_request: ~azure.ai.documentintelligence.models.AnalyzeDocumentRequest or JSON or
-         IO[bytes]
-        :keyword pages: Range of 1-based page numbers to analyze.  Ex. "1-3,5,7-9". Default value is
-         None.
+        :param body: Analyze request parameters. Is one of the following types: AnalyzeDocumentRequest,
+         JSON, IO[bytes] Required.
+        :type body: ~azure.ai.documentintelligence.models.AnalyzeDocumentRequest or JSON or IO[bytes]
+        :keyword pages: 1-based page numbers to analyze.  Ex. "1-3,5,7-9". Default value is None.
         :paramtype pages: str
         :keyword locale: Locale hint for text recognition and document analysis.  Value may contain
          only
@@ -351,7 +350,8 @@ async def begin_analyze_document(
         :paramtype query_fields: list[str]
         :keyword output_content_format: Format of the analyze result top-level content. Known values
          are: "text" and "markdown". Default value is None.
-        :paramtype output_content_format: str or ~azure.ai.documentintelligence.models.ContentFormat
+        :paramtype output_content_format: str or
+         ~azure.ai.documentintelligence.models.DocumentContentFormat
         :keyword output: Additional outputs to generate during analysis. Default value is None.
         :paramtype output: list[str or ~azure.ai.documentintelligence.models.AnalyzeOutputOption]
         :return: An instance of AsyncLROPoller that returns AnalyzeResult. The AnalyzeResult is
@@ -370,7 +370,7 @@ async def begin_analyze_document(
         if cont_token is None:
             raw_result = await self._analyze_document_initial(
                 model_id=model_id,
-                analyze_request=analyze_request,
+                body=body,
                 pages=pages,
                 locale=locale,
                 string_index_type=string_index_type,
@@ -424,17 +424,202 @@ def get_long_running_output(pipeline_response):
             self._client, raw_result, get_long_running_output, polling_method  # type: ignore
         )
 
+    @distributed_trace_async
+    async def get_analyze_result_pdf(self, model_id: str, result_id: str, **kwargs: Any) -> AsyncIterator[bytes]:
+        """Gets the generated searchable PDF output from document analysis.
+
+        :param model_id: Unique document model name. Required.
+        :type model_id: str
+        :param result_id: Analyze operation result ID. Required.
+        :type result_id: str
+        :return: AsyncIterator[bytes]
+        :rtype: AsyncIterator[bytes]
+        :raises ~azure.core.exceptions.HttpResponseError:
+        """
+        error_map: MutableMapping = {
+            401: ClientAuthenticationError,
+            404: ResourceNotFoundError,
+            409: ResourceExistsError,
+            304: ResourceNotModifiedError,
+        }
+        error_map.update(kwargs.pop("error_map", {}) or {})
+
+        _headers = kwargs.pop("headers", {}) or {}
+        _params = kwargs.pop("params", {}) or {}
+
+        cls: ClsType[AsyncIterator[bytes]] = kwargs.pop("cls", None)
+
+        _request = build_document_intelligence_get_analyze_result_pdf_request(
+            model_id=model_id,
+            result_id=result_id,
+            api_version=self._config.api_version,
+            headers=_headers,
+            params=_params,
+        )
+        path_format_arguments = {
+            "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str", skip_quote=True),
+        }
+        _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+        _stream = kwargs.pop("stream", True)
+        pipeline_response: PipelineResponse = await self._client._pipeline.run(  # type: ignore # pylint: disable=protected-access
+            _request, stream=_stream, **kwargs
+        )
+
+        response = pipeline_response.http_response
+
+        if response.status_code not in [200]:
+            if _stream:
+                try:
+                    await response.read()  # Load the body in memory and close the socket
+                except (StreamConsumedError, StreamClosedError):
+                    pass
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            error = _failsafe_deserialize(_models.DocumentIntelligenceErrorResponse, response.json())
+            raise HttpResponseError(response=response, model=error)
+
+        response_headers = {}
+        response_headers["content-type"] = self._deserialize("str", response.headers.get("content-type"))
+
+        deserialized = response.iter_bytes()
+
+        if cls:
+            return cls(pipeline_response, deserialized, response_headers)  # type: ignore
+
+        return deserialized  # type: ignore
+
+    @distributed_trace_async
+    async def get_analyze_result_figure(
+        self, model_id: str, result_id: str, figure_id: str, **kwargs: Any
+    ) -> AsyncIterator[bytes]:
+        """Gets the generated cropped image of specified figure from document analysis.
+
+        :param model_id: Unique document model name. Required.
+        :type model_id: str
+        :param result_id: Analyze operation result ID. Required.
+        :type result_id: str
+        :param figure_id: Figure ID. Required.
+        :type figure_id: str
+        :return: AsyncIterator[bytes]
+        :rtype: AsyncIterator[bytes]
+        :raises ~azure.core.exceptions.HttpResponseError:
+        """
+        error_map: MutableMapping = {
+            401: ClientAuthenticationError,
+            404: ResourceNotFoundError,
+            409: ResourceExistsError,
+            304: ResourceNotModifiedError,
+        }
+        error_map.update(kwargs.pop("error_map", {}) or {})
+
+        _headers = kwargs.pop("headers", {}) or {}
+        _params = kwargs.pop("params", {}) or {}
+
+        cls: ClsType[AsyncIterator[bytes]] = kwargs.pop("cls", None)
+
+        _request = build_document_intelligence_get_analyze_result_figure_request(
+            model_id=model_id,
+            result_id=result_id,
+            figure_id=figure_id,
+            api_version=self._config.api_version,
+            headers=_headers,
+            params=_params,
+        )
+        path_format_arguments = {
+            "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str", skip_quote=True),
+        }
+        _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+        _stream = kwargs.pop("stream", True)
+        pipeline_response: PipelineResponse = await self._client._pipeline.run(  # type: ignore # pylint: disable=protected-access
+            _request, stream=_stream, **kwargs
+        )
+
+        response = pipeline_response.http_response
+
+        if response.status_code not in [200]:
+            if _stream:
+                try:
+                    await response.read()  # Load the body in memory and close the socket
+                except (StreamConsumedError, StreamClosedError):
+                    pass
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            error = _failsafe_deserialize(_models.DocumentIntelligenceErrorResponse, response.json())
+            raise HttpResponseError(response=response, model=error)
+
+        response_headers = {}
+        response_headers["content-type"] = self._deserialize("str", response.headers.get("content-type"))
+
+        deserialized = response.iter_bytes()
+
+        if cls:
+            return cls(pipeline_response, deserialized, response_headers)  # type: ignore
+
+        return deserialized  # type: ignore
+
+    @distributed_trace_async
+    async def delete_analyze_result(self, model_id: str, result_id: str, **kwargs: Any) -> None:
+        """Mark the result of document analysis for deletion.
+
+        :param model_id: Unique document model name. Required.
+        :type model_id: str
+        :param result_id: Analyze operation result ID. Required.
+        :type result_id: str
+        :return: None
+        :rtype: None
+        :raises ~azure.core.exceptions.HttpResponseError:
+        """
+        error_map: MutableMapping = {
+            401: ClientAuthenticationError,
+            404: ResourceNotFoundError,
+            409: ResourceExistsError,
+            304: ResourceNotModifiedError,
+        }
+        error_map.update(kwargs.pop("error_map", {}) or {})
+
+        _headers = kwargs.pop("headers", {}) or {}
+        _params = kwargs.pop("params", {}) or {}
+
+        cls: ClsType[None] = kwargs.pop("cls", None)
+
+        _request = build_document_intelligence_delete_analyze_result_request(
+            model_id=model_id,
+            result_id=result_id,
+            api_version=self._config.api_version,
+            headers=_headers,
+            params=_params,
+        )
+        path_format_arguments = {
+            "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str", skip_quote=True),
+        }
+        _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+        _stream = False
+        pipeline_response: PipelineResponse = await self._client._pipeline.run(  # type: ignore # pylint: disable=protected-access
+            _request, stream=_stream, **kwargs
+        )
+
+        response = pipeline_response.http_response
+
+        if response.status_code not in [204]:
+            map_error(status_code=response.status_code, response=response, error_map=error_map)
+            error = _failsafe_deserialize(_models.DocumentIntelligenceErrorResponse, response.json())
+            raise HttpResponseError(response=response, model=error)
+
+        if cls:
+            return cls(pipeline_response, None, {})  # type: ignore
+
     async def _analyze_batch_documents_initial(
         self,
         model_id: str,
-        analyze_batch_request: Optional[Union[_models.AnalyzeBatchDocumentsRequest, JSON, IO[bytes]]] = None,
+        body: Union[_models.AnalyzeBatchDocumentsRequest, JSON, IO[bytes]],
         *,
         pages: Optional[str] = None,
         locale: Optional[str] = None,
         string_index_type: Optional[Union[str, _models.StringIndexType]] = None,
         features: Optional[List[Union[str, _models.DocumentAnalysisFeature]]] = None,
         query_fields: Optional[List[str]] = None,
-        output_content_format: Optional[Union[str, _models.ContentFormat]] = None,
+        output_content_format: Optional[Union[str, _models.DocumentContentFormat]] = None,
         output: Optional[List[Union[str, _models.AnalyzeOutputOption]]] = None,
         **kwargs: Any
     ) -> AsyncIterator[bytes]:
@@ -454,13 +639,10 @@ async def _analyze_batch_documents_initial(
 
         content_type = content_type or "application/json"
         _content = None
-        if isinstance(analyze_batch_request, (IOBase, bytes)):
-            _content = analyze_batch_request
+        if isinstance(body, (IOBase, bytes)):
+            _content = body
         else:
-            if analyze_batch_request is not None:
-                _content = json.dumps(analyze_batch_request, cls=SdkJSONEncoder, exclude_readonly=True)  # type: ignore
-            else:
-                _content = None
+            _content = json.dumps(body, cls=SdkJSONEncoder, exclude_readonly=True)  # type: ignore
 
         _request = build_document_intelligence_analyze_batch_documents_request(
             model_id=model_id,
@@ -495,7 +677,7 @@ async def _analyze_batch_documents_initial(
             except (StreamConsumedError, StreamClosedError):
                 pass
             map_error(status_code=response.status_code, response=response, error_map=error_map)
-            error = _deserialize(_models.ErrorResponse, response.json())
+            error = _failsafe_deserialize(_models.DocumentIntelligenceErrorResponse, response.json())
             raise HttpResponseError(response=response, model=error)
 
         response_headers = {}
@@ -513,14 +695,14 @@ async def _analyze_batch_documents_initial(
     async def begin_analyze_batch_documents(
         self,
         model_id: str,
-        analyze_batch_request: Optional[_models.AnalyzeBatchDocumentsRequest] = None,
+        body: _models.AnalyzeBatchDocumentsRequest,
         *,
         pages: Optional[str] = None,
         locale: Optional[str] = None,
         string_index_type: Optional[Union[str, _models.StringIndexType]] = None,
         features: Optional[List[Union[str, _models.DocumentAnalysisFeature]]] = None,
         query_fields: Optional[List[str]] = None,
-        output_content_format: Optional[Union[str, _models.ContentFormat]] = None,
+        output_content_format: Optional[Union[str, _models.DocumentContentFormat]] = None,
         output: Optional[List[Union[str, _models.AnalyzeOutputOption]]] = None,
         content_type: str = "application/json",
         **kwargs: Any
@@ -529,10 +711,9 @@ async def begin_analyze_batch_documents(
 
         :param model_id: Unique document model name. Required.
         :type model_id: str
-        :param analyze_batch_request: Analyze batch request parameters. Default value is None.
-        :type analyze_batch_request: ~azure.ai.documentintelligence.models.AnalyzeBatchDocumentsRequest
-        :keyword pages: Range of 1-based page numbers to analyze.  Ex. "1-3,5,7-9". Default value is
-         None.
+        :param body: Analyze batch request parameters. Required.
+        :type body: ~azure.ai.documentintelligence.models.AnalyzeBatchDocumentsRequest
+        :keyword pages: 1-based page numbers to analyze.  Ex. "1-3,5,7-9". Default value is None.
         :paramtype pages: str
         :keyword locale: Locale hint for text recognition and document analysis.  Value may contain
          only
@@ -549,7 +730,8 @@ async def begin_analyze_batch_documents(
         :paramtype query_fields: list[str]
         :keyword output_content_format: Format of the analyze result top-level content. Known values
          are: "text" and "markdown". Default value is None.
-        :paramtype output_content_format: str or ~azure.ai.documentintelligence.models.ContentFormat
+        :paramtype output_content_format: str or
+         ~azure.ai.documentintelligence.models.DocumentContentFormat
         :keyword output: Additional outputs to generate during analysis. Default value is None.
         :paramtype output: list[str or ~azure.ai.documentintelligence.models.AnalyzeOutputOption]
         :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
@@ -566,14 +748,14 @@ async def begin_analyze_batch_documents(
     async def begin_analyze_batch_documents(
         self,
         model_id: str,
-        analyze_batch_request: Optional[JSON] = None,
+        body: JSON,
         *,
         pages: Optional[str] = None,
         locale: Optional[str] = None,
         string_index_type: Optional[Union[str, _models.StringIndexType]] = None,
         features: Optional[List[Union[str, _models.DocumentAnalysisFeature]]] = None,
         query_fields: Optional[List[str]] = None,
-        output_content_format: Optional[Union[str, _models.ContentFormat]] = None,
+        output_content_format: Optional[Union[str, _models.DocumentContentFormat]] = None,
         output: Optional[List[Union[str, _models.AnalyzeOutputOption]]] = None,
         content_type: str = "application/json",
         **kwargs: Any
@@ -582,10 +764,9 @@ async def begin_analyze_batch_documents(
 
         :param model_id: Unique document model name. Required.
         :type model_id: str
-        :param analyze_batch_request: Analyze batch request parameters. Default value is None.
-        :type analyze_batch_request: JSON
-        :keyword pages: Range of 1-based page numbers to analyze.  Ex. "1-3,5,7-9". Default value is
-         None.
+        :param body: Analyze batch request parameters. Required.
+        :type body: JSON
+        :keyword pages: 1-based page numbers to analyze.  Ex. "1-3,5,7-9". Default value is None.
         :paramtype pages: str
         :keyword locale: Locale hint for text recognition and document analysis.  Value may contain
          only
@@ -602,7 +783,8 @@ async def begin_analyze_batch_documents(
         :paramtype query_fields: list[str]
         :keyword output_content_format: Format of the analyze result top-level content. Known values
          are: "text" and "markdown". Default value is None.
-        :paramtype output_content_format: str or ~azure.ai.documentintelligence.models.ContentFormat
+        :paramtype output_content_format: str or
+         ~azure.ai.documentintelligence.models.DocumentContentFormat
         :keyword output: Additional outputs to generate during analysis. Default value is None.
         :paramtype output: list[str or ~azure.ai.documentintelligence.models.AnalyzeOutputOption]
         :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
@@ -619,14 +801,14 @@ async def begin_analyze_batch_documents(
     async def begin_analyze_batch_documents(
         self,
         model_id: str,
-        analyze_batch_request: Optional[IO[bytes]] = None,
+        body: IO[bytes],
         *,
         pages: Optional[str] = None,
         locale: Optional[str] = None,
         string_index_type: Optional[Union[str, _models.StringIndexType]] = None,
         features: Optional[List[Union[str, _models.DocumentAnalysisFeature]]] = None,
         query_fields: Optional[List[str]] = None,
-        output_content_format: Optional[Union[str, _models.ContentFormat]] = None,
+        output_content_format: Optional[Union[str, _models.DocumentContentFormat]] = None,
         output: Optional[List[Union[str, _models.AnalyzeOutputOption]]] = None,
         content_type: str = "application/json",
         **kwargs: Any
@@ -635,10 +817,9 @@ async def begin_analyze_batch_documents(
 
         :param model_id: Unique document model name. Required.
         :type model_id: str
-        :param analyze_batch_request: Analyze batch request parameters. Default value is None.
-        :type analyze_batch_request: IO[bytes]
-        :keyword pages: Range of 1-based page numbers to analyze.  Ex. "1-3,5,7-9". Default value is
-         None.
+        :param body: Analyze batch request parameters. Required.
+        :type body: IO[bytes]
+        :keyword pages: 1-based page numbers to analyze.  Ex. "1-3,5,7-9". Default value is None.
         :paramtype pages: str
         :keyword locale: Locale hint for text recognition and document analysis.  Value may contain
          only
@@ -655,7 +836,8 @@ async def begin_analyze_batch_documents(
         :paramtype query_fields: list[str]
         :keyword output_content_format: Format of the analyze result top-level content. Known values
          are: "text" and "markdown". Default value is None.
-        :paramtype output_content_format: str or ~azure.ai.documentintelligence.models.ContentFormat
+        :paramtype output_content_format: str or
+         ~azure.ai.documentintelligence.models.DocumentContentFormat
         :keyword output: Additional outputs to generate during analysis. Default value is None.
         :paramtype output: list[str or ~azure.ai.documentintelligence.models.AnalyzeOutputOption]
         :keyword content_type: Body Parameter content-type. Content type parameter for binary body.
@@ -672,14 +854,14 @@ async def begin_analyze_batch_documents(
     async def begin_analyze_batch_documents(
         self,
         model_id: str,
-        analyze_batch_request: Optional[Union[_models.AnalyzeBatchDocumentsRequest, JSON, IO[bytes]]] = None,
+        body: Union[_models.AnalyzeBatchDocumentsRequest, JSON, IO[bytes]],
         *,
         pages: Optional[str] = None,
         locale: Optional[str] = None,
         string_index_type: Optional[Union[str, _models.StringIndexType]] = None,
         features: Optional[List[Union[str, _models.DocumentAnalysisFeature]]] = None,
         query_fields: Optional[List[str]] = None,
-        output_content_format: Optional[Union[str, _models.ContentFormat]] = None,
+        output_content_format: Optional[Union[str, _models.DocumentContentFormat]] = None,
         output: Optional[List[Union[str, _models.AnalyzeOutputOption]]] = None,
         **kwargs: Any
     ) -> AsyncLROPoller[_models.AnalyzeBatchResult]:
@@ -687,12 +869,11 @@ async def begin_analyze_batch_documents(
 
         :param model_id: Unique document model name. Required.
         :type model_id: str
-        :param analyze_batch_request: Analyze batch request parameters. Is one of the following types:
-         AnalyzeBatchDocumentsRequest, JSON, IO[bytes] Default value is None.
-        :type analyze_batch_request: ~azure.ai.documentintelligence.models.AnalyzeBatchDocumentsRequest
-         or JSON or IO[bytes]
-        :keyword pages: Range of 1-based page numbers to analyze.  Ex. "1-3,5,7-9". Default value is
-         None.
+        :param body: Analyze batch request parameters. Is one of the following types:
+         AnalyzeBatchDocumentsRequest, JSON, IO[bytes] Required.
+        :type body: ~azure.ai.documentintelligence.models.AnalyzeBatchDocumentsRequest or JSON or
+         IO[bytes]
+        :keyword pages: 1-based page numbers to analyze.  Ex. "1-3,5,7-9". Default value is None.
         :paramtype pages: str
         :keyword locale: Locale hint for text recognition and document analysis.  Value may contain
          only
@@ -709,7 +890,8 @@ async def begin_analyze_batch_documents(
         :paramtype query_fields: list[str]
         :keyword output_content_format: Format of the analyze result top-level content. Known values
          are: "text" and "markdown". Default value is None.
-        :paramtype output_content_format: str or ~azure.ai.documentintelligence.models.ContentFormat
+        :paramtype output_content_format: str or
+         ~azure.ai.documentintelligence.models.DocumentContentFormat
         :keyword output: Additional outputs to generate during analysis. Default value is None.
         :paramtype output: list[str or ~azure.ai.documentintelligence.models.AnalyzeOutputOption]
         :return: An instance of AsyncLROPoller that returns AnalyzeBatchResult. The AnalyzeBatchResult
@@ -729,7 +911,7 @@ async def begin_analyze_batch_documents(
         if cont_token is None:
             raw_result = await self._analyze_batch_documents_initial(
                 model_id=model_id,
-                analyze_batch_request=analyze_batch_request,
+                body=body,
                 pages=pages,
                 locale=locale,
                 string_index_type=string_index_type,
@@ -783,16 +965,105 @@ def get_long_running_output(pipeline_response):
             self._client, raw_result, get_long_running_output, polling_method  # type: ignore
         )
 
+    @distributed_trace
+    def list_analyze_batch_results(
+        self, model_id: str, **kwargs: Any
+    ) -> AsyncIterable["_models.AnalyzeBatchOperation"]:
+        """List batch document analysis results.
+
+        :param model_id: Unique document model name. Required.
+        :type model_id: str
+        :return: An iterator like instance of AnalyzeBatchOperation
+        :rtype:
+         ~azure.core.async_paging.AsyncItemPaged[~azure.ai.documentintelligence.models.AnalyzeBatchOperation]
+        :raises ~azure.core.exceptions.HttpResponseError:
+        """
+        _headers = kwargs.pop("headers", {}) or {}
+        _params = kwargs.pop("params", {}) or {}
+
+        cls: ClsType[List[_models.AnalyzeBatchOperation]] = kwargs.pop("cls", None)
+
+        error_map: MutableMapping = {
+            401: ClientAuthenticationError,
+            404: ResourceNotFoundError,
+            409: ResourceExistsError,
+            304: ResourceNotModifiedError,
+        }
+        error_map.update(kwargs.pop("error_map", {}) or {})
+
+        def prepare_request(next_link=None):
+            if not next_link:
+
+                _request = build_document_intelligence_list_analyze_batch_results_request(
+                    model_id=model_id,
+                    api_version=self._config.api_version,
+                    headers=_headers,
+                    params=_params,
+                )
+                path_format_arguments = {
+                    "endpoint": self._serialize.url(
+                        "self._config.endpoint", self._config.endpoint, "str", skip_quote=True
+                    ),
+                }
+                _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+            else:
+                # make call to next link with the client's api-version
+                _parsed_next_link = urllib.parse.urlparse(next_link)
+                _next_request_params = case_insensitive_dict(
+                    {
+                        key: [urllib.parse.quote(v) for v in value]
+                        for key, value in urllib.parse.parse_qs(_parsed_next_link.query).items()
+                    }
+                )
+                _next_request_params["api-version"] = self._config.api_version
+                _request = HttpRequest(
+                    "GET", urllib.parse.urljoin(next_link, _parsed_next_link.path), params=_next_request_params
+                )
+                path_format_arguments = {
+                    "endpoint": self._serialize.url(
+                        "self._config.endpoint", self._config.endpoint, "str", skip_quote=True
+                    ),
+                }
+                _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+            return _request
+
+        async def extract_data(pipeline_response):
+            deserialized = pipeline_response.http_response.json()
+            list_of_elem = _deserialize(List[_models.AnalyzeBatchOperation], deserialized["value"])
+            if cls:
+                list_of_elem = cls(list_of_elem)  # type: ignore
+            return deserialized.get("nextLink") or None, AsyncList(list_of_elem)
+
+        async def get_next(next_link=None):
+            _request = prepare_request(next_link)
+
+            _stream = False
+            pipeline_response: PipelineResponse = await self._client._pipeline.run(  # type: ignore # pylint: disable=protected-access
+                _request, stream=_stream, **kwargs
+            )
+            response = pipeline_response.http_response
+
+            if response.status_code not in [200]:
+                map_error(status_code=response.status_code, response=response, error_map=error_map)
+                error = _failsafe_deserialize(_models.DocumentIntelligenceErrorResponse, response.json())
+                raise HttpResponseError(response=response, model=error)
+
+            return pipeline_response
+
+        return AsyncItemPaged(get_next, extract_data)
+
     @distributed_trace_async
-    async def get_analyze_result_pdf(self, model_id: str, result_id: str, **kwargs: Any) -> AsyncIterator[bytes]:
-        """Gets the generated searchable PDF output from document analysis.
+    async def delete_analyze_batch_result(self, model_id: str, result_id: str, **kwargs: Any) -> None:
+        """Mark the batch document analysis result for deletion.
 
         :param model_id: Unique document model name. Required.
         :type model_id: str
-        :param result_id: Analyze operation result ID. Required.
+        :param result_id: Analyze batch operation result ID. Required.
         :type result_id: str
-        :return: AsyncIterator[bytes]
-        :rtype: AsyncIterator[bytes]
+        :return: None
+        :rtype: None
         :raises ~azure.core.exceptions.HttpResponseError:
         """
         error_map: MutableMapping = {
@@ -806,9 +1077,9 @@ async def get_analyze_result_pdf(self, model_id: str, result_id: str, **kwargs:
         _headers = kwargs.pop("headers", {}) or {}
         _params = kwargs.pop("params", {}) or {}
 
-        cls: ClsType[AsyncIterator[bytes]] = kwargs.pop("cls", None)
+        cls: ClsType[None] = kwargs.pop("cls", None)
 
-        _request = build_document_intelligence_get_analyze_result_pdf_request(
+        _request = build_document_intelligence_delete_analyze_batch_result_request(
             model_id=model_id,
             result_id=result_id,
             api_version=self._config.api_version,
@@ -820,47 +1091,33 @@ async def get_analyze_result_pdf(self, model_id: str, result_id: str, **kwargs:
         }
         _request.url = self._client.format_url(_request.url, **path_format_arguments)
 
-        _stream = kwargs.pop("stream", True)
+        _stream = False
         pipeline_response: PipelineResponse = await self._client._pipeline.run(  # type: ignore # pylint: disable=protected-access
             _request, stream=_stream, **kwargs
         )
 
         response = pipeline_response.http_response
 
-        if response.status_code not in [200]:
-            if _stream:
-                try:
-                    await response.read()  # Load the body in memory and close the socket
-                except (StreamConsumedError, StreamClosedError):
-                    pass
+        if response.status_code not in [204]:
             map_error(status_code=response.status_code, response=response, error_map=error_map)
-            error = _deserialize(_models.ErrorResponse, response.json())
+            error = _failsafe_deserialize(_models.DocumentIntelligenceErrorResponse, response.json())
             raise HttpResponseError(response=response, model=error)
 
-        response_headers = {}
-        response_headers["content-type"] = self._deserialize("str", response.headers.get("content-type"))
-
-        deserialized = response.iter_bytes()
-
         if cls:
-            return cls(pipeline_response, deserialized, response_headers)  # type: ignore
-
-        return deserialized  # type: ignore
+            return cls(pipeline_response, None, {})  # type: ignore
 
     @distributed_trace_async
-    async def get_analyze_result_figure(
-        self, model_id: str, result_id: str, figure_id: str, **kwargs: Any
-    ) -> AsyncIterator[bytes]:
-        """Gets the generated cropped image of specified figure from document analysis.
+    async def get_analyze_batch_result(
+        self, model_id: str, result_id: str, **kwargs: Any
+    ) -> _models.AnalyzeBatchOperation:
+        """Gets the result of batch document analysis.
 
         :param model_id: Unique document model name. Required.
         :type model_id: str
-        :param result_id: Analyze operation result ID. Required.
+        :param result_id: Analyze batch operation result ID. Required.
         :type result_id: str
-        :param figure_id: Figure ID. Required.
-        :type figure_id: str
-        :return: AsyncIterator[bytes]
-        :rtype: AsyncIterator[bytes]
+        :return: AnalyzeBatchOperation. The AnalyzeBatchOperation is compatible with MutableMapping
+        :rtype: ~azure.ai.documentintelligence.models.AnalyzeBatchOperation
         :raises ~azure.core.exceptions.HttpResponseError:
         """
         error_map: MutableMapping = {
@@ -874,12 +1131,11 @@ async def get_analyze_result_figure(
         _headers = kwargs.pop("headers", {}) or {}
         _params = kwargs.pop("params", {}) or {}
 
-        cls: ClsType[AsyncIterator[bytes]] = kwargs.pop("cls", None)
+        cls: ClsType[_models.AnalyzeBatchOperation] = kwargs.pop("cls", None)
 
-        _request = build_document_intelligence_get_analyze_result_figure_request(
+        _request = build_document_intelligence_get_analyze_batch_result_request(
             model_id=model_id,
             result_id=result_id,
-            figure_id=figure_id,
             api_version=self._config.api_version,
             headers=_headers,
             params=_params,
@@ -889,7 +1145,7 @@ async def get_analyze_result_figure(
         }
         _request.url = self._client.format_url(_request.url, **path_format_arguments)
 
-        _stream = kwargs.pop("stream", True)
+        _stream = kwargs.pop("stream", False)
         pipeline_response: PipelineResponse = await self._client._pipeline.run(  # type: ignore # pylint: disable=protected-access
             _request, stream=_stream, **kwargs
         )
@@ -903,23 +1159,23 @@ async def get_analyze_result_figure(
                 except (StreamConsumedError, StreamClosedError):
                     pass
             map_error(status_code=response.status_code, response=response, error_map=error_map)
-            error = _deserialize(_models.ErrorResponse, response.json())
+            error = _failsafe_deserialize(_models.DocumentIntelligenceErrorResponse, response.json())
             raise HttpResponseError(response=response, model=error)
 
-        response_headers = {}
-        response_headers["content-type"] = self._deserialize("str", response.headers.get("content-type"))
-
-        deserialized = response.iter_bytes()
+        if _stream:
+            deserialized = response.iter_bytes()
+        else:
+            deserialized = _deserialize(_models.AnalyzeBatchOperation, response.json())
 
         if cls:
-            return cls(pipeline_response, deserialized, response_headers)  # type: ignore
+            return cls(pipeline_response, deserialized, {})  # type: ignore
 
         return deserialized  # type: ignore
 
     async def _classify_document_initial(
         self,
         classifier_id: str,
-        classify_request: Union[_models.ClassifyDocumentRequest, JSON, IO[bytes]],
+        body: Union[_models.ClassifyDocumentRequest, JSON, IO[bytes]],
         *,
         string_index_type: Optional[Union[str, _models.StringIndexType]] = None,
         split: Optional[Union[str, _models.SplitMode]] = None,
@@ -942,10 +1198,10 @@ async def _classify_document_initial(
 
         content_type = content_type or "application/json"
         _content = None
-        if isinstance(classify_request, (IOBase, bytes)):
-            _content = classify_request
+        if isinstance(body, (IOBase, bytes)):
+            _content = body
         else:
-            _content = json.dumps(classify_request, cls=SdkJSONEncoder, exclude_readonly=True)  # type: ignore
+            _content = json.dumps(body, cls=SdkJSONEncoder, exclude_readonly=True)  # type: ignore
 
         _request = build_document_intelligence_classify_document_request(
             classifier_id=classifier_id,
@@ -976,7 +1232,7 @@ async def _classify_document_initial(
             except (StreamConsumedError, StreamClosedError):
                 pass
             map_error(status_code=response.status_code, response=response, error_map=error_map)
-            error = _deserialize(_models.ErrorResponse, response.json())
+            error = _failsafe_deserialize(_models.DocumentIntelligenceErrorResponse, response.json())
             raise HttpResponseError(response=response, model=error)
 
         response_headers = {}
@@ -994,7 +1250,7 @@ async def _classify_document_initial(
     async def begin_classify_document(
         self,
         classifier_id: str,
-        classify_request: _models.ClassifyDocumentRequest,
+        body: _models.ClassifyDocumentRequest,
         *,
         string_index_type: Optional[Union[str, _models.StringIndexType]] = None,
         split: Optional[Union[str, _models.SplitMode]] = None,
@@ -1006,16 +1262,15 @@ async def begin_classify_document(
 
         :param classifier_id: Unique document classifier name. Required.
         :type classifier_id: str
-        :param classify_request: Classify request parameters. Required.
-        :type classify_request: ~azure.ai.documentintelligence.models.ClassifyDocumentRequest
+        :param body: Classify request parameters. Required.
+        :type body: ~azure.ai.documentintelligence.models.ClassifyDocumentRequest
         :keyword string_index_type: Method used to compute string offset and length. Known values are:
          "textElements", "unicodeCodePoint", and "utf16CodeUnit". Default value is None.
         :paramtype string_index_type: str or ~azure.ai.documentintelligence.models.StringIndexType
         :keyword split: Document splitting mode. Known values are: "auto", "none", and "perPage".
          Default value is None.
         :paramtype split: str or ~azure.ai.documentintelligence.models.SplitMode
-        :keyword pages: Range of 1-based page numbers to analyze.  Ex. "1-3,5,7-9". Default value is
-         None.
+        :keyword pages: 1-based page numbers to analyze.  Ex. "1-3,5,7-9". Default value is None.
         :paramtype pages: str
         :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
          Default value is "application/json".
@@ -1030,7 +1285,7 @@ async def begin_classify_document(
     async def begin_classify_document(
         self,
         classifier_id: str,
-        classify_request: JSON,
+        body: JSON,
         *,
         string_index_type: Optional[Union[str, _models.StringIndexType]] = None,
         split: Optional[Union[str, _models.SplitMode]] = None,
@@ -1042,16 +1297,15 @@ async def begin_classify_document(
 
         :param classifier_id: Unique document classifier name. Required.
         :type classifier_id: str
-        :param classify_request: Classify request parameters. Required.
-        :type classify_request: JSON
+        :param body: Classify request parameters. Required.
+        :type body: JSON
         :keyword string_index_type: Method used to compute string offset and length. Known values are:
          "textElements", "unicodeCodePoint", and "utf16CodeUnit". Default value is None.
         :paramtype string_index_type: str or ~azure.ai.documentintelligence.models.StringIndexType
         :keyword split: Document splitting mode. Known values are: "auto", "none", and "perPage".
          Default value is None.
         :paramtype split: str or ~azure.ai.documentintelligence.models.SplitMode
-        :keyword pages: Range of 1-based page numbers to analyze.  Ex. "1-3,5,7-9". Default value is
-         None.
+        :keyword pages: 1-based page numbers to analyze.  Ex. "1-3,5,7-9". Default value is None.
         :paramtype pages: str
         :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
          Default value is "application/json".
@@ -1066,7 +1320,7 @@ async def begin_classify_document(
     async def begin_classify_document(
         self,
         classifier_id: str,
-        classify_request: IO[bytes],
+        body: IO[bytes],
         *,
         string_index_type: Optional[Union[str, _models.StringIndexType]] = None,
         split: Optional[Union[str, _models.SplitMode]] = None,
@@ -1078,16 +1332,15 @@ async def begin_classify_document(
 
         :param classifier_id: Unique document classifier name. Required.
         :type classifier_id: str
-        :param classify_request: Classify request parameters. Required.
-        :type classify_request: IO[bytes]
+        :param body: Classify request parameters. Required.
+        :type body: IO[bytes]
         :keyword string_index_type: Method used to compute string offset and length. Known values are:
          "textElements", "unicodeCodePoint", and "utf16CodeUnit". Default value is None.
         :paramtype string_index_type: str or ~azure.ai.documentintelligence.models.StringIndexType
         :keyword split: Document splitting mode. Known values are: "auto", "none", and "perPage".
          Default value is None.
         :paramtype split: str or ~azure.ai.documentintelligence.models.SplitMode
-        :keyword pages: Range of 1-based page numbers to analyze.  Ex. "1-3,5,7-9". Default value is
-         None.
+        :keyword pages: 1-based page numbers to analyze.  Ex. "1-3,5,7-9". Default value is None.
         :paramtype pages: str
         :keyword content_type: Body Parameter content-type. Content type parameter for binary body.
          Default value is "application/json".
@@ -1102,7 +1355,7 @@ async def begin_classify_document(
     async def begin_classify_document(
         self,
         classifier_id: str,
-        classify_request: Union[_models.ClassifyDocumentRequest, JSON, IO[bytes]],
+        body: Union[_models.ClassifyDocumentRequest, JSON, IO[bytes]],
         *,
         string_index_type: Optional[Union[str, _models.StringIndexType]] = None,
         split: Optional[Union[str, _models.SplitMode]] = None,
@@ -1113,18 +1366,16 @@ async def begin_classify_document(
 
         :param classifier_id: Unique document classifier name. Required.
         :type classifier_id: str
-        :param classify_request: Classify request parameters. Is one of the following types:
+        :param body: Classify request parameters. Is one of the following types:
          ClassifyDocumentRequest, JSON, IO[bytes] Required.
-        :type classify_request: ~azure.ai.documentintelligence.models.ClassifyDocumentRequest or JSON
-         or IO[bytes]
+        :type body: ~azure.ai.documentintelligence.models.ClassifyDocumentRequest or JSON or IO[bytes]
         :keyword string_index_type: Method used to compute string offset and length. Known values are:
          "textElements", "unicodeCodePoint", and "utf16CodeUnit". Default value is None.
         :paramtype string_index_type: str or ~azure.ai.documentintelligence.models.StringIndexType
         :keyword split: Document splitting mode. Known values are: "auto", "none", and "perPage".
          Default value is None.
         :paramtype split: str or ~azure.ai.documentintelligence.models.SplitMode
-        :keyword pages: Range of 1-based page numbers to analyze.  Ex. "1-3,5,7-9". Default value is
-         None.
+        :keyword pages: 1-based page numbers to analyze.  Ex. "1-3,5,7-9". Default value is None.
         :paramtype pages: str
         :return: An instance of AsyncLROPoller that returns AnalyzeResult. The AnalyzeResult is
          compatible with MutableMapping
@@ -1142,7 +1393,7 @@ async def begin_classify_document(
         if cont_token is None:
             raw_result = await self._classify_document_initial(
                 classifier_id=classifier_id,
-                classify_request=classify_request,
+                body=body,
                 string_index_type=string_index_type,
                 split=split,
                 pages=pages,
@@ -1198,7 +1449,7 @@ class DocumentIntelligenceAdministrationClientOperationsMixin(  # pylint: disabl
 ):
 
     async def _build_document_model_initial(
-        self, build_request: Union[_models.BuildDocumentModelRequest, JSON, IO[bytes]], **kwargs: Any
+        self, body: Union[_models.BuildDocumentModelRequest, JSON, IO[bytes]], **kwargs: Any
     ) -> AsyncIterator[bytes]:
         error_map: MutableMapping = {
             401: ClientAuthenticationError,
@@ -1216,10 +1467,10 @@ async def _build_document_model_initial(
 
         content_type = content_type or "application/json"
         _content = None
-        if isinstance(build_request, (IOBase, bytes)):
-            _content = build_request
+        if isinstance(body, (IOBase, bytes)):
+            _content = body
         else:
-            _content = json.dumps(build_request, cls=SdkJSONEncoder, exclude_readonly=True)  # type: ignore
+            _content = json.dumps(body, cls=SdkJSONEncoder, exclude_readonly=True)  # type: ignore
 
         _request = build_document_intelligence_administration_build_document_model_request(
             content_type=content_type,
@@ -1246,7 +1497,7 @@ async def _build_document_model_initial(
             except (StreamConsumedError, StreamClosedError):
                 pass
             map_error(status_code=response.status_code, response=response, error_map=error_map)
-            error = _deserialize(_models.ErrorResponse, response.json())
+            error = _failsafe_deserialize(_models.DocumentIntelligenceErrorResponse, response.json())
             raise HttpResponseError(response=response, model=error)
 
         response_headers = {}
@@ -1262,12 +1513,12 @@ async def _build_document_model_initial(
 
     @overload
     async def begin_build_document_model(
-        self, build_request: _models.BuildDocumentModelRequest, *, content_type: str = "application/json", **kwargs: Any
+        self, body: _models.BuildDocumentModelRequest, *, content_type: str = "application/json", **kwargs: Any
     ) -> AsyncLROPoller[_models.DocumentModelDetails]:
         """Builds a custom document analysis model.
 
-        :param build_request: Build request parameters. Required.
-        :type build_request: ~azure.ai.documentintelligence.models.BuildDocumentModelRequest
+        :param body: Build request parameters. Required.
+        :type body: ~azure.ai.documentintelligence.models.BuildDocumentModelRequest
         :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
          Default value is "application/json".
         :paramtype content_type: str
@@ -1280,12 +1531,12 @@ async def begin_build_document_model(
 
     @overload
     async def begin_build_document_model(
-        self, build_request: JSON, *, content_type: str = "application/json", **kwargs: Any
+        self, body: JSON, *, content_type: str = "application/json", **kwargs: Any
     ) -> AsyncLROPoller[_models.DocumentModelDetails]:
         """Builds a custom document analysis model.
 
-        :param build_request: Build request parameters. Required.
-        :type build_request: JSON
+        :param body: Build request parameters. Required.
+        :type body: JSON
         :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
          Default value is "application/json".
         :paramtype content_type: str
@@ -1298,12 +1549,12 @@ async def begin_build_document_model(
 
     @overload
     async def begin_build_document_model(
-        self, build_request: IO[bytes], *, content_type: str = "application/json", **kwargs: Any
+        self, body: IO[bytes], *, content_type: str = "application/json", **kwargs: Any
     ) -> AsyncLROPoller[_models.DocumentModelDetails]:
         """Builds a custom document analysis model.
 
-        :param build_request: Build request parameters. Required.
-        :type build_request: IO[bytes]
+        :param body: Build request parameters. Required.
+        :type body: IO[bytes]
         :keyword content_type: Body Parameter content-type. Content type parameter for binary body.
          Default value is "application/json".
         :paramtype content_type: str
@@ -1316,13 +1567,13 @@ async def begin_build_document_model(
 
     @distributed_trace_async
     async def begin_build_document_model(
-        self, build_request: Union[_models.BuildDocumentModelRequest, JSON, IO[bytes]], **kwargs: Any
+        self, body: Union[_models.BuildDocumentModelRequest, JSON, IO[bytes]], **kwargs: Any
     ) -> AsyncLROPoller[_models.DocumentModelDetails]:
         """Builds a custom document analysis model.
 
-        :param build_request: Build request parameters. Is one of the following types:
+        :param body: Build request parameters. Is one of the following types:
          BuildDocumentModelRequest, JSON, IO[bytes] Required.
-        :type build_request: ~azure.ai.documentintelligence.models.BuildDocumentModelRequest or JSON or
+        :type body: ~azure.ai.documentintelligence.models.BuildDocumentModelRequest or JSON or
          IO[bytes]
         :return: An instance of AsyncLROPoller that returns DocumentModelDetails. The
          DocumentModelDetails is compatible with MutableMapping
@@ -1340,12 +1591,7 @@ async def begin_build_document_model(
         cont_token: Optional[str] = kwargs.pop("continuation_token", None)
         if cont_token is None:
             raw_result = await self._build_document_model_initial(
-                build_request=build_request,
-                content_type=content_type,
-                cls=lambda x, y, z: x,
-                headers=_headers,
-                params=_params,
-                **kwargs
+                body=body, content_type=content_type, cls=lambda x, y, z: x, headers=_headers, params=_params, **kwargs
             )
             await raw_result.http_response.read()  # type: ignore
         kwargs.pop("error_map", None)
@@ -1388,7 +1634,7 @@ def get_long_running_output(pipeline_response):
         )
 
     async def _compose_model_initial(
-        self, compose_request: Union[_models.ComposeDocumentModelRequest, JSON, IO[bytes]], **kwargs: Any
+        self, body: Union[_models.ComposeDocumentModelRequest, JSON, IO[bytes]], **kwargs: Any
     ) -> AsyncIterator[bytes]:
         error_map: MutableMapping = {
             401: ClientAuthenticationError,
@@ -1406,10 +1652,10 @@ async def _compose_model_initial(
 
         content_type = content_type or "application/json"
         _content = None
-        if isinstance(compose_request, (IOBase, bytes)):
-            _content = compose_request
+        if isinstance(body, (IOBase, bytes)):
+            _content = body
         else:
-            _content = json.dumps(compose_request, cls=SdkJSONEncoder, exclude_readonly=True)  # type: ignore
+            _content = json.dumps(body, cls=SdkJSONEncoder, exclude_readonly=True)  # type: ignore
 
         _request = build_document_intelligence_administration_compose_model_request(
             content_type=content_type,
@@ -1436,7 +1682,7 @@ async def _compose_model_initial(
             except (StreamConsumedError, StreamClosedError):
                 pass
             map_error(status_code=response.status_code, response=response, error_map=error_map)
-            error = _deserialize(_models.ErrorResponse, response.json())
+            error = _failsafe_deserialize(_models.DocumentIntelligenceErrorResponse, response.json())
             raise HttpResponseError(response=response, model=error)
 
         response_headers = {}
@@ -1452,16 +1698,12 @@ async def _compose_model_initial(
 
     @overload
     async def begin_compose_model(
-        self,
-        compose_request: _models.ComposeDocumentModelRequest,
-        *,
-        content_type: str = "application/json",
-        **kwargs: Any
+        self, body: _models.ComposeDocumentModelRequest, *, content_type: str = "application/json", **kwargs: Any
     ) -> AsyncLROPoller[_models.DocumentModelDetails]:
         """Creates a new document model from document types of existing document models.
 
-        :param compose_request: Compose request parameters. Required.
-        :type compose_request: ~azure.ai.documentintelligence.models.ComposeDocumentModelRequest
+        :param body: Compose request parameters. Required.
+        :type body: ~azure.ai.documentintelligence.models.ComposeDocumentModelRequest
         :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
          Default value is "application/json".
         :paramtype content_type: str
@@ -1474,12 +1716,12 @@ async def begin_compose_model(
 
     @overload
     async def begin_compose_model(
-        self, compose_request: JSON, *, content_type: str = "application/json", **kwargs: Any
+        self, body: JSON, *, content_type: str = "application/json", **kwargs: Any
     ) -> AsyncLROPoller[_models.DocumentModelDetails]:
         """Creates a new document model from document types of existing document models.
 
-        :param compose_request: Compose request parameters. Required.
-        :type compose_request: JSON
+        :param body: Compose request parameters. Required.
+        :type body: JSON
         :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
          Default value is "application/json".
         :paramtype content_type: str
@@ -1492,12 +1734,12 @@ async def begin_compose_model(
 
     @overload
     async def begin_compose_model(
-        self, compose_request: IO[bytes], *, content_type: str = "application/json", **kwargs: Any
+        self, body: IO[bytes], *, content_type: str = "application/json", **kwargs: Any
     ) -> AsyncLROPoller[_models.DocumentModelDetails]:
         """Creates a new document model from document types of existing document models.
 
-        :param compose_request: Compose request parameters. Required.
-        :type compose_request: IO[bytes]
+        :param body: Compose request parameters. Required.
+        :type body: IO[bytes]
         :keyword content_type: Body Parameter content-type. Content type parameter for binary body.
          Default value is "application/json".
         :paramtype content_type: str
@@ -1510,14 +1752,14 @@ async def begin_compose_model(
 
     @distributed_trace_async
     async def begin_compose_model(
-        self, compose_request: Union[_models.ComposeDocumentModelRequest, JSON, IO[bytes]], **kwargs: Any
+        self, body: Union[_models.ComposeDocumentModelRequest, JSON, IO[bytes]], **kwargs: Any
     ) -> AsyncLROPoller[_models.DocumentModelDetails]:
         """Creates a new document model from document types of existing document models.
 
-        :param compose_request: Compose request parameters. Is one of the following types:
+        :param body: Compose request parameters. Is one of the following types:
          ComposeDocumentModelRequest, JSON, IO[bytes] Required.
-        :type compose_request: ~azure.ai.documentintelligence.models.ComposeDocumentModelRequest or
-         JSON or IO[bytes]
+        :type body: ~azure.ai.documentintelligence.models.ComposeDocumentModelRequest or JSON or
+         IO[bytes]
         :return: An instance of AsyncLROPoller that returns DocumentModelDetails. The
          DocumentModelDetails is compatible with MutableMapping
         :rtype:
@@ -1534,12 +1776,7 @@ async def begin_compose_model(
         cont_token: Optional[str] = kwargs.pop("continuation_token", None)
         if cont_token is None:
             raw_result = await self._compose_model_initial(
-                compose_request=compose_request,
-                content_type=content_type,
-                cls=lambda x, y, z: x,
-                headers=_headers,
-                params=_params,
-                **kwargs
+                body=body, content_type=content_type, cls=lambda x, y, z: x, headers=_headers, params=_params, **kwargs
             )
             await raw_result.http_response.read()  # type: ignore
         kwargs.pop("error_map", None)
@@ -1583,72 +1820,67 @@ def get_long_running_output(pipeline_response):
 
     @overload
     async def authorize_model_copy(
-        self,
-        authorize_copy_request: _models.AuthorizeCopyRequest,
-        *,
-        content_type: str = "application/json",
-        **kwargs: Any
-    ) -> _models.CopyAuthorization:
+        self, body: _models.AuthorizeCopyRequest, *, content_type: str = "application/json", **kwargs: Any
+    ) -> _models.ModelCopyAuthorization:
         """Generates authorization to copy a document model to this location with
         specified modelId and optional description.
 
-        :param authorize_copy_request: Authorize copy request parameters. Required.
-        :type authorize_copy_request: ~azure.ai.documentintelligence.models.AuthorizeCopyRequest
+        :param body: Authorize copy request parameters. Required.
+        :type body: ~azure.ai.documentintelligence.models.AuthorizeCopyRequest
         :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
          Default value is "application/json".
         :paramtype content_type: str
-        :return: CopyAuthorization. The CopyAuthorization is compatible with MutableMapping
-        :rtype: ~azure.ai.documentintelligence.models.CopyAuthorization
+        :return: ModelCopyAuthorization. The ModelCopyAuthorization is compatible with MutableMapping
+        :rtype: ~azure.ai.documentintelligence.models.ModelCopyAuthorization
         :raises ~azure.core.exceptions.HttpResponseError:
         """
 
     @overload
     async def authorize_model_copy(
-        self, authorize_copy_request: JSON, *, content_type: str = "application/json", **kwargs: Any
-    ) -> _models.CopyAuthorization:
+        self, body: JSON, *, content_type: str = "application/json", **kwargs: Any
+    ) -> _models.ModelCopyAuthorization:
         """Generates authorization to copy a document model to this location with
         specified modelId and optional description.
 
-        :param authorize_copy_request: Authorize copy request parameters. Required.
-        :type authorize_copy_request: JSON
+        :param body: Authorize copy request parameters. Required.
+        :type body: JSON
         :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
          Default value is "application/json".
         :paramtype content_type: str
-        :return: CopyAuthorization. The CopyAuthorization is compatible with MutableMapping
-        :rtype: ~azure.ai.documentintelligence.models.CopyAuthorization
+        :return: ModelCopyAuthorization. The ModelCopyAuthorization is compatible with MutableMapping
+        :rtype: ~azure.ai.documentintelligence.models.ModelCopyAuthorization
         :raises ~azure.core.exceptions.HttpResponseError:
         """
 
     @overload
     async def authorize_model_copy(
-        self, authorize_copy_request: IO[bytes], *, content_type: str = "application/json", **kwargs: Any
-    ) -> _models.CopyAuthorization:
+        self, body: IO[bytes], *, content_type: str = "application/json", **kwargs: Any
+    ) -> _models.ModelCopyAuthorization:
         """Generates authorization to copy a document model to this location with
         specified modelId and optional description.
 
-        :param authorize_copy_request: Authorize copy request parameters. Required.
-        :type authorize_copy_request: IO[bytes]
+        :param body: Authorize copy request parameters. Required.
+        :type body: IO[bytes]
         :keyword content_type: Body Parameter content-type. Content type parameter for binary body.
          Default value is "application/json".
         :paramtype content_type: str
-        :return: CopyAuthorization. The CopyAuthorization is compatible with MutableMapping
-        :rtype: ~azure.ai.documentintelligence.models.CopyAuthorization
+        :return: ModelCopyAuthorization. The ModelCopyAuthorization is compatible with MutableMapping
+        :rtype: ~azure.ai.documentintelligence.models.ModelCopyAuthorization
         :raises ~azure.core.exceptions.HttpResponseError:
         """
 
     @distributed_trace_async
     async def authorize_model_copy(
-        self, authorize_copy_request: Union[_models.AuthorizeCopyRequest, JSON, IO[bytes]], **kwargs: Any
-    ) -> _models.CopyAuthorization:
+        self, body: Union[_models.AuthorizeCopyRequest, JSON, IO[bytes]], **kwargs: Any
+    ) -> _models.ModelCopyAuthorization:
         """Generates authorization to copy a document model to this location with
         specified modelId and optional description.
 
-        :param authorize_copy_request: Authorize copy request parameters. Is one of the following
-         types: AuthorizeCopyRequest, JSON, IO[bytes] Required.
-        :type authorize_copy_request: ~azure.ai.documentintelligence.models.AuthorizeCopyRequest or
-         JSON or IO[bytes]
-        :return: CopyAuthorization. The CopyAuthorization is compatible with MutableMapping
-        :rtype: ~azure.ai.documentintelligence.models.CopyAuthorization
+        :param body: Authorize copy request parameters. Is one of the following types:
+         AuthorizeCopyRequest, JSON, IO[bytes] Required.
+        :type body: ~azure.ai.documentintelligence.models.AuthorizeCopyRequest or JSON or IO[bytes]
+        :return: ModelCopyAuthorization. The ModelCopyAuthorization is compatible with MutableMapping
+        :rtype: ~azure.ai.documentintelligence.models.ModelCopyAuthorization
         :raises ~azure.core.exceptions.HttpResponseError:
         """
         error_map: MutableMapping = {
@@ -1663,14 +1895,14 @@ async def authorize_model_copy(
         _params = kwargs.pop("params", {}) or {}
 
         content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
-        cls: ClsType[_models.CopyAuthorization] = kwargs.pop("cls", None)
+        cls: ClsType[_models.ModelCopyAuthorization] = kwargs.pop("cls", None)
 
         content_type = content_type or "application/json"
         _content = None
-        if isinstance(authorize_copy_request, (IOBase, bytes)):
-            _content = authorize_copy_request
+        if isinstance(body, (IOBase, bytes)):
+            _content = body
         else:
-            _content = json.dumps(authorize_copy_request, cls=SdkJSONEncoder, exclude_readonly=True)  # type: ignore
+            _content = json.dumps(body, cls=SdkJSONEncoder, exclude_readonly=True)  # type: ignore
 
         _request = build_document_intelligence_administration_authorize_model_copy_request(
             content_type=content_type,
@@ -1698,13 +1930,13 @@ async def authorize_model_copy(
                 except (StreamConsumedError, StreamClosedError):
                     pass
             map_error(status_code=response.status_code, response=response, error_map=error_map)
-            error = _deserialize(_models.ErrorResponse, response.json())
+            error = _failsafe_deserialize(_models.DocumentIntelligenceErrorResponse, response.json())
             raise HttpResponseError(response=response, model=error)
 
         if _stream:
             deserialized = response.iter_bytes()
         else:
-            deserialized = _deserialize(_models.CopyAuthorization, response.json())
+            deserialized = _deserialize(_models.ModelCopyAuthorization, response.json())
 
         if cls:
             return cls(pipeline_response, deserialized, {})  # type: ignore
@@ -1712,7 +1944,7 @@ async def authorize_model_copy(
         return deserialized  # type: ignore
 
     async def _copy_model_to_initial(
-        self, model_id: str, copy_to_request: Union[_models.CopyAuthorization, JSON, IO[bytes]], **kwargs: Any
+        self, model_id: str, body: Union[_models.ModelCopyAuthorization, JSON, IO[bytes]], **kwargs: Any
     ) -> AsyncIterator[bytes]:
         error_map: MutableMapping = {
             401: ClientAuthenticationError,
@@ -1730,10 +1962,10 @@ async def _copy_model_to_initial(
 
         content_type = content_type or "application/json"
         _content = None
-        if isinstance(copy_to_request, (IOBase, bytes)):
-            _content = copy_to_request
+        if isinstance(body, (IOBase, bytes)):
+            _content = body
         else:
-            _content = json.dumps(copy_to_request, cls=SdkJSONEncoder, exclude_readonly=True)  # type: ignore
+            _content = json.dumps(body, cls=SdkJSONEncoder, exclude_readonly=True)  # type: ignore
 
         _request = build_document_intelligence_administration_copy_model_to_request(
             model_id=model_id,
@@ -1761,7 +1993,7 @@ async def _copy_model_to_initial(
             except (StreamConsumedError, StreamClosedError):
                 pass
             map_error(status_code=response.status_code, response=response, error_map=error_map)
-            error = _deserialize(_models.ErrorResponse, response.json())
+            error = _failsafe_deserialize(_models.DocumentIntelligenceErrorResponse, response.json())
             raise HttpResponseError(response=response, model=error)
 
         response_headers = {}
@@ -1779,7 +2011,7 @@ async def _copy_model_to_initial(
     async def begin_copy_model_to(
         self,
         model_id: str,
-        copy_to_request: _models.CopyAuthorization,
+        body: _models.ModelCopyAuthorization,
         *,
         content_type: str = "application/json",
         **kwargs: Any
@@ -1788,8 +2020,8 @@ async def begin_copy_model_to(
 
         :param model_id: Unique document model name. Required.
         :type model_id: str
-        :param copy_to_request: Copy to request parameters. Required.
-        :type copy_to_request: ~azure.ai.documentintelligence.models.CopyAuthorization
+        :param body: Copy to request parameters. Required.
+        :type body: ~azure.ai.documentintelligence.models.ModelCopyAuthorization
         :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
          Default value is "application/json".
         :paramtype content_type: str
@@ -1802,14 +2034,14 @@ async def begin_copy_model_to(
 
     @overload
     async def begin_copy_model_to(
-        self, model_id: str, copy_to_request: JSON, *, content_type: str = "application/json", **kwargs: Any
+        self, model_id: str, body: JSON, *, content_type: str = "application/json", **kwargs: Any
     ) -> AsyncLROPoller[_models.DocumentModelDetails]:
         """Copies document model to the target resource, region, and modelId.
 
         :param model_id: Unique document model name. Required.
         :type model_id: str
-        :param copy_to_request: Copy to request parameters. Required.
-        :type copy_to_request: JSON
+        :param body: Copy to request parameters. Required.
+        :type body: JSON
         :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
          Default value is "application/json".
         :paramtype content_type: str
@@ -1822,14 +2054,14 @@ async def begin_copy_model_to(
 
     @overload
     async def begin_copy_model_to(
-        self, model_id: str, copy_to_request: IO[bytes], *, content_type: str = "application/json", **kwargs: Any
+        self, model_id: str, body: IO[bytes], *, content_type: str = "application/json", **kwargs: Any
     ) -> AsyncLROPoller[_models.DocumentModelDetails]:
         """Copies document model to the target resource, region, and modelId.
 
         :param model_id: Unique document model name. Required.
         :type model_id: str
-        :param copy_to_request: Copy to request parameters. Required.
-        :type copy_to_request: IO[bytes]
+        :param body: Copy to request parameters. Required.
+        :type body: IO[bytes]
         :keyword content_type: Body Parameter content-type. Content type parameter for binary body.
          Default value is "application/json".
         :paramtype content_type: str
@@ -1842,16 +2074,15 @@ async def begin_copy_model_to(
 
     @distributed_trace_async
     async def begin_copy_model_to(
-        self, model_id: str, copy_to_request: Union[_models.CopyAuthorization, JSON, IO[bytes]], **kwargs: Any
+        self, model_id: str, body: Union[_models.ModelCopyAuthorization, JSON, IO[bytes]], **kwargs: Any
     ) -> AsyncLROPoller[_models.DocumentModelDetails]:
         """Copies document model to the target resource, region, and modelId.
 
         :param model_id: Unique document model name. Required.
         :type model_id: str
-        :param copy_to_request: Copy to request parameters. Is one of the following types:
-         CopyAuthorization, JSON, IO[bytes] Required.
-        :type copy_to_request: ~azure.ai.documentintelligence.models.CopyAuthorization or JSON or
-         IO[bytes]
+        :param body: Copy to request parameters. Is one of the following types: ModelCopyAuthorization,
+         JSON, IO[bytes] Required.
+        :type body: ~azure.ai.documentintelligence.models.ModelCopyAuthorization or JSON or IO[bytes]
         :return: An instance of AsyncLROPoller that returns DocumentModelDetails. The
          DocumentModelDetails is compatible with MutableMapping
         :rtype:
@@ -1869,7 +2100,7 @@ async def begin_copy_model_to(
         if cont_token is None:
             raw_result = await self._copy_model_to_initial(
                 model_id=model_id,
-                copy_to_request=copy_to_request,
+                body=body,
                 content_type=content_type,
                 cls=lambda x, y, z: x,
                 headers=_headers,
@@ -1964,7 +2195,7 @@ async def get_model(self, model_id: str, **kwargs: Any) -> _models.DocumentModel
                 except (StreamConsumedError, StreamClosedError):
                     pass
             map_error(status_code=response.status_code, response=response, error_map=error_map)
-            error = _deserialize(_models.ErrorResponse, response.json())
+            error = _failsafe_deserialize(_models.DocumentIntelligenceErrorResponse, response.json())
             raise HttpResponseError(response=response, model=error)
 
         response_headers = {}
@@ -2059,7 +2290,7 @@ async def get_next(next_link=None):
 
             if response.status_code not in [200]:
                 map_error(status_code=response.status_code, response=response, error_map=error_map)
-                error = _deserialize(_models.ErrorResponse, response.json())
+                error = _failsafe_deserialize(_models.DocumentIntelligenceErrorResponse, response.json())
                 raise HttpResponseError(response=response, model=error)
 
             return pipeline_response
@@ -2109,7 +2340,7 @@ async def delete_model(self, model_id: str, **kwargs: Any) -> None:
 
         if response.status_code not in [204]:
             map_error(status_code=response.status_code, response=response, error_map=error_map)
-            error = _deserialize(_models.ErrorResponse, response.json())
+            error = _failsafe_deserialize(_models.DocumentIntelligenceErrorResponse, response.json())
             raise HttpResponseError(response=response, model=error)
 
         response_headers = {}
@@ -2121,11 +2352,12 @@ async def delete_model(self, model_id: str, **kwargs: Any) -> None:
             return cls(pipeline_response, None, response_headers)  # type: ignore
 
     @distributed_trace_async
-    async def get_resource_info(self, **kwargs: Any) -> _models.ResourceDetails:
+    async def get_resource_details(self, **kwargs: Any) -> _models.DocumentIntelligenceResourceDetails:
         """Return information about the current resource.
 
-        :return: ResourceDetails. The ResourceDetails is compatible with MutableMapping
-        :rtype: ~azure.ai.documentintelligence.models.ResourceDetails
+        :return: DocumentIntelligenceResourceDetails. The DocumentIntelligenceResourceDetails is
+         compatible with MutableMapping
+        :rtype: ~azure.ai.documentintelligence.models.DocumentIntelligenceResourceDetails
         :raises ~azure.core.exceptions.HttpResponseError:
         """
         error_map: MutableMapping = {
@@ -2139,9 +2371,9 @@ async def get_resource_info(self, **kwargs: Any) -> _models.ResourceDetails:
         _headers = kwargs.pop("headers", {}) or {}
         _params = kwargs.pop("params", {}) or {}
 
-        cls: ClsType[_models.ResourceDetails] = kwargs.pop("cls", None)
+        cls: ClsType[_models.DocumentIntelligenceResourceDetails] = kwargs.pop("cls", None)
 
-        _request = build_document_intelligence_administration_get_resource_info_request(
+        _request = build_document_intelligence_administration_get_resource_details_request(
             api_version=self._config.api_version,
             headers=_headers,
             params=_params,
@@ -2165,13 +2397,13 @@ async def get_resource_info(self, **kwargs: Any) -> _models.ResourceDetails:
                 except (StreamConsumedError, StreamClosedError):
                     pass
             map_error(status_code=response.status_code, response=response, error_map=error_map)
-            error = _deserialize(_models.ErrorResponse, response.json())
+            error = _failsafe_deserialize(_models.DocumentIntelligenceErrorResponse, response.json())
             raise HttpResponseError(response=response, model=error)
 
         if _stream:
             deserialized = response.iter_bytes()
         else:
-            deserialized = _deserialize(_models.ResourceDetails, response.json())
+            deserialized = _deserialize(_models.DocumentIntelligenceResourceDetails, response.json())
 
         if cls:
             return cls(pipeline_response, deserialized, {})  # type: ignore
@@ -2179,13 +2411,14 @@ async def get_resource_info(self, **kwargs: Any) -> _models.ResourceDetails:
         return deserialized  # type: ignore
 
     @distributed_trace_async
-    async def get_operation(self, operation_id: str, **kwargs: Any) -> _models.OperationDetails:
+    async def get_operation(self, operation_id: str, **kwargs: Any) -> _models.DocumentIntelligenceOperationDetails:
         """Gets operation info.
 
         :param operation_id: Operation ID. Required.
         :type operation_id: str
-        :return: OperationDetails. The OperationDetails is compatible with MutableMapping
-        :rtype: ~azure.ai.documentintelligence.models.OperationDetails
+        :return: DocumentIntelligenceOperationDetails. The DocumentIntelligenceOperationDetails is
+         compatible with MutableMapping
+        :rtype: ~azure.ai.documentintelligence.models.DocumentIntelligenceOperationDetails
         :raises ~azure.core.exceptions.HttpResponseError:
         """
         error_map: MutableMapping = {
@@ -2199,7 +2432,7 @@ async def get_operation(self, operation_id: str, **kwargs: Any) -> _models.Opera
         _headers = kwargs.pop("headers", {}) or {}
         _params = kwargs.pop("params", {}) or {}
 
-        cls: ClsType[_models.OperationDetails] = kwargs.pop("cls", None)
+        cls: ClsType[_models.DocumentIntelligenceOperationDetails] = kwargs.pop("cls", None)
 
         _request = build_document_intelligence_administration_get_operation_request(
             operation_id=operation_id,
@@ -2226,7 +2459,7 @@ async def get_operation(self, operation_id: str, **kwargs: Any) -> _models.Opera
                 except (StreamConsumedError, StreamClosedError):
                     pass
             map_error(status_code=response.status_code, response=response, error_map=error_map)
-            error = _deserialize(_models.ErrorResponse, response.json())
+            error = _failsafe_deserialize(_models.DocumentIntelligenceErrorResponse, response.json())
             raise HttpResponseError(response=response, model=error)
 
         response_headers = {}
@@ -2237,7 +2470,7 @@ async def get_operation(self, operation_id: str, **kwargs: Any) -> _models.Opera
         if _stream:
             deserialized = response.iter_bytes()
         else:
-            deserialized = _deserialize(_models.OperationDetails, response.json())
+            deserialized = _deserialize(_models.DocumentIntelligenceOperationDetails, response.json())
 
         if cls:
             return cls(pipeline_response, deserialized, response_headers)  # type: ignore
@@ -2245,18 +2478,19 @@ async def get_operation(self, operation_id: str, **kwargs: Any) -> _models.Opera
         return deserialized  # type: ignore
 
     @distributed_trace
-    def list_operations(self, **kwargs: Any) -> AsyncIterable["_models.OperationDetails"]:
+    def list_operations(self, **kwargs: Any) -> AsyncIterable["_models.DocumentIntelligenceOperationDetails"]:
+        # pylint: disable=line-too-long
         """Lists all operations.
 
-        :return: An iterator like instance of OperationDetails
+        :return: An iterator like instance of DocumentIntelligenceOperationDetails
         :rtype:
-         ~azure.core.async_paging.AsyncItemPaged[~azure.ai.documentintelligence.models.OperationDetails]
+         ~azure.core.async_paging.AsyncItemPaged[~azure.ai.documentintelligence.models.DocumentIntelligenceOperationDetails]
         :raises ~azure.core.exceptions.HttpResponseError:
         """
         _headers = kwargs.pop("headers", {}) or {}
         _params = kwargs.pop("params", {}) or {}
 
-        cls: ClsType[List[_models.OperationDetails]] = kwargs.pop("cls", None)
+        cls: ClsType[List[_models.DocumentIntelligenceOperationDetails]] = kwargs.pop("cls", None)
 
         error_map: MutableMapping = {
             401: ClientAuthenticationError,
@@ -2305,7 +2539,7 @@ def prepare_request(next_link=None):
 
         async def extract_data(pipeline_response):
             deserialized = pipeline_response.http_response.json()
-            list_of_elem = _deserialize(List[_models.OperationDetails], deserialized["value"])
+            list_of_elem = _deserialize(List[_models.DocumentIntelligenceOperationDetails], deserialized["value"])
             if cls:
                 list_of_elem = cls(list_of_elem)  # type: ignore
             return deserialized.get("nextLink") or None, AsyncList(list_of_elem)
@@ -2321,7 +2555,7 @@ async def get_next(next_link=None):
 
             if response.status_code not in [200]:
                 map_error(status_code=response.status_code, response=response, error_map=error_map)
-                error = _deserialize(_models.ErrorResponse, response.json())
+                error = _failsafe_deserialize(_models.DocumentIntelligenceErrorResponse, response.json())
                 raise HttpResponseError(response=response, model=error)
 
             return pipeline_response
@@ -2329,7 +2563,7 @@ async def get_next(next_link=None):
         return AsyncItemPaged(get_next, extract_data)
 
     async def _build_classifier_initial(
-        self, build_request: Union[_models.BuildDocumentClassifierRequest, JSON, IO[bytes]], **kwargs: Any
+        self, body: Union[_models.BuildDocumentClassifierRequest, JSON, IO[bytes]], **kwargs: Any
     ) -> AsyncIterator[bytes]:
         error_map: MutableMapping = {
             401: ClientAuthenticationError,
@@ -2347,10 +2581,10 @@ async def _build_classifier_initial(
 
         content_type = content_type or "application/json"
         _content = None
-        if isinstance(build_request, (IOBase, bytes)):
-            _content = build_request
+        if isinstance(body, (IOBase, bytes)):
+            _content = body
         else:
-            _content = json.dumps(build_request, cls=SdkJSONEncoder, exclude_readonly=True)  # type: ignore
+            _content = json.dumps(body, cls=SdkJSONEncoder, exclude_readonly=True)  # type: ignore
 
         _request = build_document_intelligence_administration_build_classifier_request(
             content_type=content_type,
@@ -2377,7 +2611,7 @@ async def _build_classifier_initial(
             except (StreamConsumedError, StreamClosedError):
                 pass
             map_error(status_code=response.status_code, response=response, error_map=error_map)
-            error = _deserialize(_models.ErrorResponse, response.json())
+            error = _failsafe_deserialize(_models.DocumentIntelligenceErrorResponse, response.json())
             raise HttpResponseError(response=response, model=error)
 
         response_headers = {}
@@ -2393,16 +2627,12 @@ async def _build_classifier_initial(
 
     @overload
     async def begin_build_classifier(
-        self,
-        build_request: _models.BuildDocumentClassifierRequest,
-        *,
-        content_type: str = "application/json",
-        **kwargs: Any
+        self, body: _models.BuildDocumentClassifierRequest, *, content_type: str = "application/json", **kwargs: Any
     ) -> AsyncLROPoller[_models.DocumentClassifierDetails]:
         """Builds a custom document classifier.
 
-        :param build_request: Build request parameters. Required.
-        :type build_request: ~azure.ai.documentintelligence.models.BuildDocumentClassifierRequest
+        :param body: Build request parameters. Required.
+        :type body: ~azure.ai.documentintelligence.models.BuildDocumentClassifierRequest
         :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
          Default value is "application/json".
         :paramtype content_type: str
@@ -2415,12 +2645,12 @@ async def begin_build_classifier(
 
     @overload
     async def begin_build_classifier(
-        self, build_request: JSON, *, content_type: str = "application/json", **kwargs: Any
+        self, body: JSON, *, content_type: str = "application/json", **kwargs: Any
     ) -> AsyncLROPoller[_models.DocumentClassifierDetails]:
         """Builds a custom document classifier.
 
-        :param build_request: Build request parameters. Required.
-        :type build_request: JSON
+        :param body: Build request parameters. Required.
+        :type body: JSON
         :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
          Default value is "application/json".
         :paramtype content_type: str
@@ -2433,12 +2663,12 @@ async def begin_build_classifier(
 
     @overload
     async def begin_build_classifier(
-        self, build_request: IO[bytes], *, content_type: str = "application/json", **kwargs: Any
+        self, body: IO[bytes], *, content_type: str = "application/json", **kwargs: Any
     ) -> AsyncLROPoller[_models.DocumentClassifierDetails]:
         """Builds a custom document classifier.
 
-        :param build_request: Build request parameters. Required.
-        :type build_request: IO[bytes]
+        :param body: Build request parameters. Required.
+        :type body: IO[bytes]
         :keyword content_type: Body Parameter content-type. Content type parameter for binary body.
          Default value is "application/json".
         :paramtype content_type: str
@@ -2451,14 +2681,14 @@ async def begin_build_classifier(
 
     @distributed_trace_async
     async def begin_build_classifier(
-        self, build_request: Union[_models.BuildDocumentClassifierRequest, JSON, IO[bytes]], **kwargs: Any
+        self, body: Union[_models.BuildDocumentClassifierRequest, JSON, IO[bytes]], **kwargs: Any
     ) -> AsyncLROPoller[_models.DocumentClassifierDetails]:
         """Builds a custom document classifier.
 
-        :param build_request: Build request parameters. Is one of the following types:
+        :param body: Build request parameters. Is one of the following types:
          BuildDocumentClassifierRequest, JSON, IO[bytes] Required.
-        :type build_request: ~azure.ai.documentintelligence.models.BuildDocumentClassifierRequest or
-         JSON or IO[bytes]
+        :type body: ~azure.ai.documentintelligence.models.BuildDocumentClassifierRequest or JSON or
+         IO[bytes]
         :return: An instance of AsyncLROPoller that returns DocumentClassifierDetails. The
          DocumentClassifierDetails is compatible with MutableMapping
         :rtype:
@@ -2475,12 +2705,7 @@ async def begin_build_classifier(
         cont_token: Optional[str] = kwargs.pop("continuation_token", None)
         if cont_token is None:
             raw_result = await self._build_classifier_initial(
-                build_request=build_request,
-                content_type=content_type,
-                cls=lambda x, y, z: x,
-                headers=_headers,
-                params=_params,
-                **kwargs
+                body=body, content_type=content_type, cls=lambda x, y, z: x, headers=_headers, params=_params, **kwargs
             )
             await raw_result.http_response.read()  # type: ignore
         kwargs.pop("error_map", None)
@@ -2524,18 +2749,13 @@ def get_long_running_output(pipeline_response):
 
     @overload
     async def authorize_classifier_copy(
-        self,
-        authorize_copy_request: _models.AuthorizeClassifierCopyRequest,
-        *,
-        content_type: str = "application/json",
-        **kwargs: Any
+        self, body: _models.AuthorizeClassifierCopyRequest, *, content_type: str = "application/json", **kwargs: Any
     ) -> _models.ClassifierCopyAuthorization:
         """Generates authorization to copy a document classifier to this location with
         specified classifierId and optional description.
 
-        :param authorize_copy_request: Authorize copy request parameters. Required.
-        :type authorize_copy_request:
-         ~azure.ai.documentintelligence.models.AuthorizeClassifierCopyRequest
+        :param body: Authorize copy request parameters. Required.
+        :type body: ~azure.ai.documentintelligence.models.AuthorizeClassifierCopyRequest
         :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
          Default value is "application/json".
         :paramtype content_type: str
@@ -2547,13 +2767,13 @@ async def authorize_classifier_copy(
 
     @overload
     async def authorize_classifier_copy(
-        self, authorize_copy_request: JSON, *, content_type: str = "application/json", **kwargs: Any
+        self, body: JSON, *, content_type: str = "application/json", **kwargs: Any
     ) -> _models.ClassifierCopyAuthorization:
         """Generates authorization to copy a document classifier to this location with
         specified classifierId and optional description.
 
-        :param authorize_copy_request: Authorize copy request parameters. Required.
-        :type authorize_copy_request: JSON
+        :param body: Authorize copy request parameters. Required.
+        :type body: JSON
         :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
          Default value is "application/json".
         :paramtype content_type: str
@@ -2565,13 +2785,13 @@ async def authorize_classifier_copy(
 
     @overload
     async def authorize_classifier_copy(
-        self, authorize_copy_request: IO[bytes], *, content_type: str = "application/json", **kwargs: Any
+        self, body: IO[bytes], *, content_type: str = "application/json", **kwargs: Any
     ) -> _models.ClassifierCopyAuthorization:
         """Generates authorization to copy a document classifier to this location with
         specified classifierId and optional description.
 
-        :param authorize_copy_request: Authorize copy request parameters. Required.
-        :type authorize_copy_request: IO[bytes]
+        :param body: Authorize copy request parameters. Required.
+        :type body: IO[bytes]
         :keyword content_type: Body Parameter content-type. Content type parameter for binary body.
          Default value is "application/json".
         :paramtype content_type: str
@@ -2583,15 +2803,15 @@ async def authorize_classifier_copy(
 
     @distributed_trace_async
     async def authorize_classifier_copy(
-        self, authorize_copy_request: Union[_models.AuthorizeClassifierCopyRequest, JSON, IO[bytes]], **kwargs: Any
+        self, body: Union[_models.AuthorizeClassifierCopyRequest, JSON, IO[bytes]], **kwargs: Any
     ) -> _models.ClassifierCopyAuthorization:
         """Generates authorization to copy a document classifier to this location with
         specified classifierId and optional description.
 
-        :param authorize_copy_request: Authorize copy request parameters. Is one of the following
-         types: AuthorizeClassifierCopyRequest, JSON, IO[bytes] Required.
-        :type authorize_copy_request:
-         ~azure.ai.documentintelligence.models.AuthorizeClassifierCopyRequest or JSON or IO[bytes]
+        :param body: Authorize copy request parameters. Is one of the following types:
+         AuthorizeClassifierCopyRequest, JSON, IO[bytes] Required.
+        :type body: ~azure.ai.documentintelligence.models.AuthorizeClassifierCopyRequest or JSON or
+         IO[bytes]
         :return: ClassifierCopyAuthorization. The ClassifierCopyAuthorization is compatible with
          MutableMapping
         :rtype: ~azure.ai.documentintelligence.models.ClassifierCopyAuthorization
@@ -2613,10 +2833,10 @@ async def authorize_classifier_copy(
 
         content_type = content_type or "application/json"
         _content = None
-        if isinstance(authorize_copy_request, (IOBase, bytes)):
-            _content = authorize_copy_request
+        if isinstance(body, (IOBase, bytes)):
+            _content = body
         else:
-            _content = json.dumps(authorize_copy_request, cls=SdkJSONEncoder, exclude_readonly=True)  # type: ignore
+            _content = json.dumps(body, cls=SdkJSONEncoder, exclude_readonly=True)  # type: ignore
 
         _request = build_document_intelligence_administration_authorize_classifier_copy_request(
             content_type=content_type,
@@ -2644,7 +2864,7 @@ async def authorize_classifier_copy(
                 except (StreamConsumedError, StreamClosedError):
                     pass
             map_error(status_code=response.status_code, response=response, error_map=error_map)
-            error = _deserialize(_models.ErrorResponse, response.json())
+            error = _failsafe_deserialize(_models.DocumentIntelligenceErrorResponse, response.json())
             raise HttpResponseError(response=response, model=error)
 
         if _stream:
@@ -2658,10 +2878,7 @@ async def authorize_classifier_copy(
         return deserialized  # type: ignore
 
     async def _copy_classifier_to_initial(
-        self,
-        classifier_id: str,
-        copy_to_request: Union[_models.ClassifierCopyAuthorization, JSON, IO[bytes]],
-        **kwargs: Any
+        self, classifier_id: str, body: Union[_models.ClassifierCopyAuthorization, JSON, IO[bytes]], **kwargs: Any
     ) -> AsyncIterator[bytes]:
         error_map: MutableMapping = {
             401: ClientAuthenticationError,
@@ -2679,10 +2896,10 @@ async def _copy_classifier_to_initial(
 
         content_type = content_type or "application/json"
         _content = None
-        if isinstance(copy_to_request, (IOBase, bytes)):
-            _content = copy_to_request
+        if isinstance(body, (IOBase, bytes)):
+            _content = body
         else:
-            _content = json.dumps(copy_to_request, cls=SdkJSONEncoder, exclude_readonly=True)  # type: ignore
+            _content = json.dumps(body, cls=SdkJSONEncoder, exclude_readonly=True)  # type: ignore
 
         _request = build_document_intelligence_administration_copy_classifier_to_request(
             classifier_id=classifier_id,
@@ -2710,7 +2927,7 @@ async def _copy_classifier_to_initial(
             except (StreamConsumedError, StreamClosedError):
                 pass
             map_error(status_code=response.status_code, response=response, error_map=error_map)
-            error = _deserialize(_models.ErrorResponse, response.json())
+            error = _failsafe_deserialize(_models.DocumentIntelligenceErrorResponse, response.json())
             raise HttpResponseError(response=response, model=error)
 
         response_headers = {}
@@ -2728,7 +2945,7 @@ async def _copy_classifier_to_initial(
     async def begin_copy_classifier_to(
         self,
         classifier_id: str,
-        copy_to_request: _models.ClassifierCopyAuthorization,
+        body: _models.ClassifierCopyAuthorization,
         *,
         content_type: str = "application/json",
         **kwargs: Any
@@ -2737,8 +2954,8 @@ async def begin_copy_classifier_to(
 
         :param classifier_id: Unique document classifier name. Required.
         :type classifier_id: str
-        :param copy_to_request: Copy to request parameters. Required.
-        :type copy_to_request: ~azure.ai.documentintelligence.models.ClassifierCopyAuthorization
+        :param body: Copy to request parameters. Required.
+        :type body: ~azure.ai.documentintelligence.models.ClassifierCopyAuthorization
         :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
          Default value is "application/json".
         :paramtype content_type: str
@@ -2751,14 +2968,14 @@ async def begin_copy_classifier_to(
 
     @overload
     async def begin_copy_classifier_to(
-        self, classifier_id: str, copy_to_request: JSON, *, content_type: str = "application/json", **kwargs: Any
+        self, classifier_id: str, body: JSON, *, content_type: str = "application/json", **kwargs: Any
     ) -> AsyncLROPoller[_models.DocumentClassifierDetails]:
         """Copies document classifier to the target resource, region, and classifierId.
 
         :param classifier_id: Unique document classifier name. Required.
         :type classifier_id: str
-        :param copy_to_request: Copy to request parameters. Required.
-        :type copy_to_request: JSON
+        :param body: Copy to request parameters. Required.
+        :type body: JSON
         :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
          Default value is "application/json".
         :paramtype content_type: str
@@ -2771,14 +2988,14 @@ async def begin_copy_classifier_to(
 
     @overload
     async def begin_copy_classifier_to(
-        self, classifier_id: str, copy_to_request: IO[bytes], *, content_type: str = "application/json", **kwargs: Any
+        self, classifier_id: str, body: IO[bytes], *, content_type: str = "application/json", **kwargs: Any
     ) -> AsyncLROPoller[_models.DocumentClassifierDetails]:
         """Copies document classifier to the target resource, region, and classifierId.
 
         :param classifier_id: Unique document classifier name. Required.
         :type classifier_id: str
-        :param copy_to_request: Copy to request parameters. Required.
-        :type copy_to_request: IO[bytes]
+        :param body: Copy to request parameters. Required.
+        :type body: IO[bytes]
         :keyword content_type: Body Parameter content-type. Content type parameter for binary body.
          Default value is "application/json".
         :paramtype content_type: str
@@ -2791,19 +3008,16 @@ async def begin_copy_classifier_to(
 
     @distributed_trace_async
     async def begin_copy_classifier_to(
-        self,
-        classifier_id: str,
-        copy_to_request: Union[_models.ClassifierCopyAuthorization, JSON, IO[bytes]],
-        **kwargs: Any
+        self, classifier_id: str, body: Union[_models.ClassifierCopyAuthorization, JSON, IO[bytes]], **kwargs: Any
     ) -> AsyncLROPoller[_models.DocumentClassifierDetails]:
         """Copies document classifier to the target resource, region, and classifierId.
 
         :param classifier_id: Unique document classifier name. Required.
         :type classifier_id: str
-        :param copy_to_request: Copy to request parameters. Is one of the following types:
+        :param body: Copy to request parameters. Is one of the following types:
          ClassifierCopyAuthorization, JSON, IO[bytes] Required.
-        :type copy_to_request: ~azure.ai.documentintelligence.models.ClassifierCopyAuthorization or
-         JSON or IO[bytes]
+        :type body: ~azure.ai.documentintelligence.models.ClassifierCopyAuthorization or JSON or
+         IO[bytes]
         :return: An instance of AsyncLROPoller that returns DocumentClassifierDetails. The
          DocumentClassifierDetails is compatible with MutableMapping
         :rtype:
@@ -2821,7 +3035,7 @@ async def begin_copy_classifier_to(
         if cont_token is None:
             raw_result = await self._copy_classifier_to_initial(
                 classifier_id=classifier_id,
-                copy_to_request=copy_to_request,
+                body=body,
                 content_type=content_type,
                 cls=lambda x, y, z: x,
                 headers=_headers,
@@ -2917,7 +3131,7 @@ async def get_classifier(self, classifier_id: str, **kwargs: Any) -> _models.Doc
                 except (StreamConsumedError, StreamClosedError):
                     pass
             map_error(status_code=response.status_code, response=response, error_map=error_map)
-            error = _deserialize(_models.ErrorResponse, response.json())
+            error = _failsafe_deserialize(_models.DocumentIntelligenceErrorResponse, response.json())
             raise HttpResponseError(response=response, model=error)
 
         response_headers = {}
@@ -3012,7 +3226,7 @@ async def get_next(next_link=None):
 
             if response.status_code not in [200]:
                 map_error(status_code=response.status_code, response=response, error_map=error_map)
-                error = _deserialize(_models.ErrorResponse, response.json())
+                error = _failsafe_deserialize(_models.DocumentIntelligenceErrorResponse, response.json())
                 raise HttpResponseError(response=response, model=error)
 
             return pipeline_response
@@ -3062,7 +3276,7 @@ async def delete_classifier(self, classifier_id: str, **kwargs: Any) -> None:
 
         if response.status_code not in [204]:
             map_error(status_code=response.status_code, response=response, error_map=error_map)
-            error = _deserialize(_models.ErrorResponse, response.json())
+            error = _failsafe_deserialize(_models.DocumentIntelligenceErrorResponse, response.json())
             raise HttpResponseError(response=response, model=error)
 
         response_headers = {}
diff --git a/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/aio/_operations/_patch.py b/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/aio/_operations/_patch.py
index 3a4d0b5277e7b..f7dd32510333d 100644
--- a/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/aio/_operations/_patch.py
+++ b/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/aio/_operations/_patch.py
@@ -6,690 +6,9 @@
 
 Follow our quickstart for examples: https://aka.ms/azsdk/python/dpcodegen/python/customize
 """
-import sys
-from typing import Any, Callable, Dict, IO, List, Optional, TypeVar, Union, Mapping, cast, overload
+from typing import List
 
-from azure.core.pipeline import PipelineResponse
-from azure.core.polling import AsyncLROPoller, AsyncNoPolling, AsyncPollingMethod
-from azure.core.polling.async_base_polling import AsyncLROBasePolling
-from azure.core.rest import AsyncHttpResponse, HttpRequest
-from azure.core.tracing.decorator_async import distributed_trace_async
-from azure.core.utils import case_insensitive_dict
-
-from ._operations import (
-    DocumentIntelligenceClientOperationsMixin as GeneratedDIClientOps,
-    DocumentIntelligenceAdministrationClientOperationsMixin as GeneratedDIAdminClientOps,
-)
-from ... import models as _models
-from ..._model_base import _deserialize
-from ..._operations._patch import PollingReturnType_co, _parse_operation_id, _finished
-
-if sys.version_info >= (3, 9):
-    from collections.abc import MutableMapping
-else:
-    from typing import MutableMapping  # type: ignore
-JSON = MutableMapping[str, Any]  # pylint: disable=unsubscriptable-object
-T = TypeVar("T")
-ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]]
-
-
-class AsyncAnalyzeDocumentLROPoller(AsyncLROPoller[PollingReturnType_co]):
-    @property
-    def details(self) -> Mapping[str, Any]:
-        """Returns metadata associated with the long-running operation.
-
-        :return: Returns metadata associated with the long-running operation.
-        :rtype: Mapping[str, Any]
-        """
-        return {
-            "operation_id": _parse_operation_id(
-                self.polling_method()._initial_response.http_response.headers["Operation-Location"]  # type: ignore # pylint: disable=protected-access
-            ),
-        }
-
-    @classmethod
-    def from_continuation_token(
-        cls, polling_method: AsyncPollingMethod[PollingReturnType_co], continuation_token: str, **kwargs: Any
-    ) -> "AsyncAnalyzeDocumentLROPoller":
-        (
-            client,
-            initial_response,
-            deserialization_callback,
-        ) = polling_method.from_continuation_token(continuation_token, **kwargs)
-
-        return cls(client, initial_response, deserialization_callback, polling_method)
-
-
-class AsyncAnalyzeBatchDocumentsLROPollingMethod(AsyncLROBasePolling):  # pylint: disable=name-too-long
-    def finished(self) -> bool:
-        """Is this polling finished?
-
-        :return: Whether the polling finished or not.
-        :rtype: bool
-        """
-        return _finished(self.status())
-
-
-class DocumentIntelligenceAdministrationClientOperationsMixin(
-    GeneratedDIAdminClientOps
-):  # pylint: disable=name-too-long
-    @distributed_trace_async
-    async def begin_build_classifier(  # type: ignore[override]
-        self, build_request: Union[_models.BuildDocumentClassifierRequest, JSON, IO[bytes]], **kwargs: Any
-    ) -> AsyncLROPoller[_models.DocumentClassifierDetails]:
-        _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
-        _params = kwargs.pop("params", {}) or {}
-
-        content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
-        cls: ClsType[_models.DocumentClassifierDetails] = kwargs.pop("cls", None)
-        polling: Union[bool, AsyncPollingMethod] = kwargs.pop("polling", True)
-        lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
-        cont_token: Optional[str] = kwargs.pop("continuation_token", None)
-        if cont_token is None:
-            raw_result = await self._build_classifier_initial(
-                build_request=build_request,
-                content_type=content_type,
-                cls=lambda x, y, z: x,
-                headers=_headers,
-                params=_params,
-                **kwargs
-            )
-            await raw_result.http_response.read()  # type: ignore
-        kwargs.pop("error_map", None)
-
-        def get_long_running_output(pipeline_response):
-            response_headers = {}
-            response = pipeline_response.http_response
-            response_headers["Retry-After"] = self._deserialize("int", response.headers.get("Retry-After"))
-            response_headers["Operation-Location"] = self._deserialize(
-                "str", response.headers.get("Operation-Location")
-            )
-
-            deserialized = _deserialize(_models.DocumentClassifierDetails, response.json())
-            if cls:
-                return cls(pipeline_response, deserialized, response_headers)  # type: ignore
-            return deserialized
-
-        path_format_arguments = {
-            "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str", skip_quote=True),
-        }
-
-        if polling is True:
-            polling_method: AsyncPollingMethod = cast(
-                AsyncPollingMethod,
-                AsyncLROBasePolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs),
-            )
-        elif polling is False:
-            polling_method = cast(AsyncPollingMethod, AsyncNoPolling())
-        else:
-            polling_method = polling
-        if cont_token:
-            return AsyncLROPoller[_models.DocumentClassifierDetails].from_continuation_token(
-                polling_method=polling_method,
-                continuation_token=cont_token,
-                client=self._client,
-                deserialization_callback=get_long_running_output,
-            )
-        return AsyncLROPoller[_models.DocumentClassifierDetails](
-            self._client, raw_result, get_long_running_output, polling_method  # type: ignore
-        )
-
-    @distributed_trace_async
-    async def begin_build_document_model(  # type: ignore[override]
-        self, build_request: Union[_models.BuildDocumentModelRequest, JSON, IO[bytes]], **kwargs: Any
-    ) -> AsyncLROPoller[_models.DocumentModelDetails]:
-        _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
-        _params = kwargs.pop("params", {}) or {}
-
-        content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
-        cls: ClsType[_models.DocumentModelDetails] = kwargs.pop("cls", None)
-        polling: Union[bool, AsyncPollingMethod] = kwargs.pop("polling", True)
-        lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
-        cont_token: Optional[str] = kwargs.pop("continuation_token", None)
-        if cont_token is None:
-            raw_result = await self._build_document_model_initial(
-                build_request=build_request,
-                content_type=content_type,
-                cls=lambda x, y, z: x,
-                headers=_headers,
-                params=_params,
-                **kwargs
-            )
-            await raw_result.http_response.read()  # type: ignore
-        kwargs.pop("error_map", None)
-
-        def get_long_running_output(pipeline_response):
-            response_headers = {}
-            response = pipeline_response.http_response
-            response_headers["Retry-After"] = self._deserialize("int", response.headers.get("Retry-After"))
-            response_headers["Operation-Location"] = self._deserialize(
-                "str", response.headers.get("Operation-Location")
-            )
-
-            deserialized = _deserialize(_models.DocumentModelDetails, response.json())
-            if cls:
-                return cls(pipeline_response, deserialized, response_headers)  # type: ignore
-            return deserialized
-
-        path_format_arguments = {
-            "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str", skip_quote=True),
-        }
-
-        if polling is True:
-            polling_method: AsyncPollingMethod = cast(
-                AsyncPollingMethod,
-                AsyncLROBasePolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs),
-            )
-        elif polling is False:
-            polling_method = cast(AsyncPollingMethod, AsyncNoPolling())
-        else:
-            polling_method = polling
-        if cont_token:
-            return AsyncLROPoller[_models.DocumentModelDetails].from_continuation_token(
-                polling_method=polling_method,
-                continuation_token=cont_token,
-                client=self._client,
-                deserialization_callback=get_long_running_output,
-            )
-        return AsyncLROPoller[_models.DocumentModelDetails](
-            self._client, raw_result, get_long_running_output, polling_method  # type: ignore
-        )
-
-    @distributed_trace_async
-    async def begin_compose_model(  # type: ignore[override]
-        self, compose_request: Union[_models.ComposeDocumentModelRequest, JSON, IO[bytes]], **kwargs: Any
-    ) -> AsyncLROPoller[_models.DocumentModelDetails]:
-        _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
-        _params = kwargs.pop("params", {}) or {}
-
-        content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
-        cls: ClsType[_models.DocumentModelDetails] = kwargs.pop("cls", None)
-        polling: Union[bool, AsyncPollingMethod] = kwargs.pop("polling", True)
-        lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
-        cont_token: Optional[str] = kwargs.pop("continuation_token", None)
-        if cont_token is None:
-            raw_result = await self._compose_model_initial(
-                compose_request=compose_request,
-                content_type=content_type,
-                cls=lambda x, y, z: x,
-                headers=_headers,
-                params=_params,
-                **kwargs
-            )
-            await raw_result.http_response.read()  # type: ignore
-        kwargs.pop("error_map", None)
-
-        def get_long_running_output(pipeline_response):
-            response_headers = {}
-            response = pipeline_response.http_response
-            response_headers["Retry-After"] = self._deserialize("int", response.headers.get("Retry-After"))
-            response_headers["Operation-Location"] = self._deserialize(
-                "str", response.headers.get("Operation-Location")
-            )
-
-            deserialized = _deserialize(_models.DocumentModelDetails, response.json())
-            if cls:
-                return cls(pipeline_response, deserialized, response_headers)  # type: ignore
-            return deserialized
-
-        path_format_arguments = {
-            "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str", skip_quote=True),
-        }
-
-        if polling is True:
-            polling_method: AsyncPollingMethod = cast(
-                AsyncPollingMethod,
-                AsyncLROBasePolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs),
-            )
-        elif polling is False:
-            polling_method = cast(AsyncPollingMethod, AsyncNoPolling())
-        else:
-            polling_method = polling
-        if cont_token:
-            return AsyncLROPoller[_models.DocumentModelDetails].from_continuation_token(
-                polling_method=polling_method,
-                continuation_token=cont_token,
-                client=self._client,
-                deserialization_callback=get_long_running_output,
-            )
-        return AsyncLROPoller[_models.DocumentModelDetails](
-            self._client, raw_result, get_long_running_output, polling_method  # type: ignore
-        )
-
-    @distributed_trace_async
-    async def begin_copy_model_to(  # type: ignore[override]
-        self, model_id: str, copy_to_request: Union[_models.CopyAuthorization, JSON, IO[bytes]], **kwargs: Any
-    ) -> AsyncLROPoller[_models.DocumentModelDetails]:
-        _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
-        _params = kwargs.pop("params", {}) or {}
-
-        content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
-        cls: ClsType[_models.DocumentModelDetails] = kwargs.pop("cls", None)
-        polling: Union[bool, AsyncPollingMethod] = kwargs.pop("polling", True)
-        lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
-        cont_token: Optional[str] = kwargs.pop("continuation_token", None)
-        if cont_token is None:
-            raw_result = await self._copy_model_to_initial(
-                model_id=model_id,
-                copy_to_request=copy_to_request,
-                content_type=content_type,
-                cls=lambda x, y, z: x,
-                headers=_headers,
-                params=_params,
-                **kwargs
-            )
-            await raw_result.http_response.read()  # type: ignore
-        kwargs.pop("error_map", None)
-
-        def get_long_running_output(pipeline_response):
-            response_headers = {}
-            response = pipeline_response.http_response
-            response_headers["Retry-After"] = self._deserialize("int", response.headers.get("Retry-After"))
-            response_headers["Operation-Location"] = self._deserialize(
-                "str", response.headers.get("Operation-Location")
-            )
-
-            deserialized = _deserialize(_models.DocumentModelDetails, response.json())
-            if cls:
-                return cls(pipeline_response, deserialized, response_headers)  # type: ignore
-            return deserialized
-
-        path_format_arguments = {
-            "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str", skip_quote=True),
-        }
-
-        if polling is True:
-            polling_method: AsyncPollingMethod = cast(
-                AsyncPollingMethod,
-                AsyncLROBasePolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs),
-            )
-        elif polling is False:
-            polling_method = cast(AsyncPollingMethod, AsyncNoPolling())
-        else:
-            polling_method = polling
-        if cont_token:
-            return AsyncLROPoller[_models.DocumentModelDetails].from_continuation_token(
-                polling_method=polling_method,
-                continuation_token=cont_token,
-                client=self._client,
-                deserialization_callback=get_long_running_output,
-            )
-        return AsyncLROPoller[_models.DocumentModelDetails](
-            self._client, raw_result, get_long_running_output, polling_method  # type: ignore
-        )
-
-    @distributed_trace_async
-    async def begin_copy_classifier_to(  # type: ignore[override]
-        self,
-        classifier_id: str,
-        copy_to_request: Union[_models.ClassifierCopyAuthorization, JSON, IO[bytes]],
-        **kwargs: Any
-    ) -> AsyncLROPoller[_models.DocumentClassifierDetails]:
-        _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
-        _params = kwargs.pop("params", {}) or {}
-
-        content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("Content-Type", None))
-        cls: ClsType[_models.DocumentClassifierDetails] = kwargs.pop("cls", None)
-        polling: Union[bool, AsyncPollingMethod] = kwargs.pop("polling", True)
-        lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
-        cont_token: Optional[str] = kwargs.pop("continuation_token", None)
-        if cont_token is None:
-            raw_result = await self._copy_classifier_to_initial(
-                classifier_id=classifier_id,
-                copy_to_request=copy_to_request,
-                content_type=content_type,
-                cls=lambda x, y, z: x,
-                headers=_headers,
-                params=_params,
-                **kwargs
-            )
-            await raw_result.http_response.read()  # type: ignore
-        kwargs.pop("error_map", None)
-
-        def get_long_running_output(pipeline_response):
-            response_headers = {}
-            response = pipeline_response.http_response
-            response_headers["Retry-After"] = self._deserialize("int", response.headers.get("Retry-After"))
-            response_headers["Operation-Location"] = self._deserialize(
-                "str", response.headers.get("Operation-Location")
-            )
-
-            deserialized = _deserialize(_models.DocumentClassifierDetails, response.json())
-            if cls:
-                return cls(pipeline_response, deserialized, response_headers)  # type: ignore
-            return deserialized
-
-        path_format_arguments = {
-            "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str", skip_quote=True),
-        }
-
-        if polling is True:
-            polling_method: AsyncPollingMethod = cast(
-                AsyncPollingMethod,
-                AsyncLROBasePolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs),
-            )
-        elif polling is False:
-            polling_method = cast(AsyncPollingMethod, AsyncNoPolling())
-        else:
-            polling_method = polling
-        if cont_token:
-            return AsyncLROPoller[_models.DocumentClassifierDetails].from_continuation_token(
-                polling_method=polling_method,
-                continuation_token=cont_token,
-                client=self._client,
-                deserialization_callback=get_long_running_output,
-            )
-        return AsyncLROPoller[_models.DocumentClassifierDetails](
-            self._client, raw_result, get_long_running_output, polling_method  # type: ignore
-        )
-
-
-class DocumentIntelligenceClientOperationsMixin(GeneratedDIClientOps):  # pylint: disable=name-too-long
-    @overload
-    async def begin_analyze_document(
-        self,
-        model_id: str,
-        analyze_request: Optional[_models.AnalyzeDocumentRequest] = None,
-        *,
-        pages: Optional[str] = None,
-        locale: Optional[str] = None,
-        string_index_type: Optional[Union[str, _models.StringIndexType]] = None,
-        features: Optional[List[Union[str, _models.DocumentAnalysisFeature]]] = None,
-        query_fields: Optional[List[str]] = None,
-        output_content_format: Optional[Union[str, _models.ContentFormat]] = None,
-        output: Optional[List[Union[str, _models.AnalyzeOutputOption]]] = None,
-        content_type: str = "application/json",
-        **kwargs: Any
-    ) -> AsyncAnalyzeDocumentLROPoller[_models.AnalyzeResult]:
-        """Analyzes document with document model.
-
-        :param model_id: Unique document model name. Required.
-        :type model_id: str
-        :param analyze_request: Analyze request parameters. Default value is None.
-        :type analyze_request: ~azure.ai.documentintelligence.models.AnalyzeDocumentRequest
-        :keyword pages: Range of 1-based page numbers to analyze.  Ex. "1-3,5,7-9". Default value is
-         None.
-        :paramtype pages: str
-        :keyword locale: Locale hint for text recognition and document analysis.  Value may contain
-         only
-         the language code (ex. "en", "fr") or BCP 47 language tag (ex. "en-US"). Default value is
-         None.
-        :paramtype locale: str
-        :keyword string_index_type: Method used to compute string offset and length. Known values are:
-         "textElements", "unicodeCodePoint", and "utf16CodeUnit". Default value is None.
-        :paramtype string_index_type: str or ~azure.ai.documentintelligence.models.StringIndexType
-        :keyword features: List of optional analysis features. Default value is None.
-        :paramtype features: list[str or ~azure.ai.documentintelligence.models.DocumentAnalysisFeature]
-        :keyword query_fields: List of additional fields to extract.  Ex. "NumberOfGuests,StoreNumber".
-         Default value is None.
-        :paramtype query_fields: list[str]
-        :keyword output_content_format: Format of the analyze result top-level content. Known values
-         are: "text" and "markdown". Default value is None.
-        :paramtype output_content_format: str or ~azure.ai.documentintelligence.models.ContentFormat
-        :keyword output: Additional outputs to generate during analysis. Default value is None.
-        :paramtype output: list[str or ~azure.ai.documentintelligence.models.AnalyzeOutputOption]
-        :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
-         Default value is "application/json".
-        :paramtype content_type: str
-        :return: An instance of AsyncAnalyzeDocumentLROPoller that returns AnalyzeResult. The AnalyzeResult is
-         compatible with MutableMapping
-        :rtype: AsyncAnalyzeDocumentLROPoller[~azure.ai.documentintelligence.models.AnalyzeResult]
-        :raises ~azure.core.exceptions.HttpResponseError:
-        """
-
-    @overload
-    async def begin_analyze_document(
-        self,
-        model_id: str,
-        analyze_request: Optional[JSON] = None,
-        *,
-        pages: Optional[str] = None,
-        locale: Optional[str] = None,
-        string_index_type: Optional[Union[str, _models.StringIndexType]] = None,
-        features: Optional[List[Union[str, _models.DocumentAnalysisFeature]]] = None,
-        query_fields: Optional[List[str]] = None,
-        output_content_format: Optional[Union[str, _models.ContentFormat]] = None,
-        output: Optional[List[Union[str, _models.AnalyzeOutputOption]]] = None,
-        content_type: str = "application/json",
-        **kwargs: Any
-    ) -> AsyncAnalyzeDocumentLROPoller[_models.AnalyzeResult]:
-        """Analyzes document with document model.
-
-        :param model_id: Unique document model name. Required.
-        :type model_id: str
-        :param analyze_request: Analyze request parameters. Default value is None.
-        :type analyze_request: JSON
-        :keyword pages: Range of 1-based page numbers to analyze.  Ex. "1-3,5,7-9". Default value is
-         None.
-        :paramtype pages: str
-        :keyword locale: Locale hint for text recognition and document analysis.  Value may contain
-         only
-         the language code (ex. "en", "fr") or BCP 47 language tag (ex. "en-US"). Default value is
-         None.
-        :paramtype locale: str
-        :keyword string_index_type: Method used to compute string offset and length. Known values are:
-         "textElements", "unicodeCodePoint", and "utf16CodeUnit". Default value is None.
-        :paramtype string_index_type: str or ~azure.ai.documentintelligence.models.StringIndexType
-        :keyword features: List of optional analysis features. Default value is None.
-        :paramtype features: list[str or ~azure.ai.documentintelligence.models.DocumentAnalysisFeature]
-        :keyword query_fields: List of additional fields to extract.  Ex. "NumberOfGuests,StoreNumber".
-         Default value is None.
-        :paramtype query_fields: list[str]
-        :keyword output_content_format: Format of the analyze result top-level content. Known values
-         are: "text" and "markdown". Default value is None.
-        :paramtype output_content_format: str or ~azure.ai.documentintelligence.models.ContentFormat
-        :keyword output: Additional outputs to generate during analysis. Default value is None.
-        :paramtype output: list[str or ~azure.ai.documentintelligence.models.AnalyzeOutputOption]
-        :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
-         Default value is "application/json".
-        :paramtype content_type: str
-        :return: An instance of AsyncAnalyzeDocumentLROPoller that returns AnalyzeResult. The AnalyzeResult is
-         compatible with MutableMapping
-        :rtype: AsyncAnalyzeDocumentLROPoller[~azure.ai.documentintelligence.models.AnalyzeResult]
-        :raises ~azure.core.exceptions.HttpResponseError:
-        """
-
-    @overload
-    async def begin_analyze_document(
-        self,
-        model_id: str,
-        analyze_request: Optional[IO[bytes]] = None,
-        *,
-        pages: Optional[str] = None,
-        locale: Optional[str] = None,
-        string_index_type: Optional[Union[str, _models.StringIndexType]] = None,
-        features: Optional[List[Union[str, _models.DocumentAnalysisFeature]]] = None,
-        query_fields: Optional[List[str]] = None,
-        output_content_format: Optional[Union[str, _models.ContentFormat]] = None,
-        output: Optional[List[Union[str, _models.AnalyzeOutputOption]]] = None,
-        content_type: str = "application/json",
-        **kwargs: Any
-    ) -> AsyncAnalyzeDocumentLROPoller[_models.AnalyzeResult]:
-        """Analyzes document with document model.
-
-        :param model_id: Unique document model name. Required.
-        :type model_id: str
-        :param analyze_request: Analyze request parameters. Default value is None.
-        :type analyze_request: IO[bytes]
-        :keyword pages: Range of 1-based page numbers to analyze.  Ex. "1-3,5,7-9". Default value is
-         None.
-        :paramtype pages: str
-        :keyword locale: Locale hint for text recognition and document analysis.  Value may contain
-         only
-         the language code (ex. "en", "fr") or BCP 47 language tag (ex. "en-US"). Default value is
-         None.
-        :paramtype locale: str
-        :keyword string_index_type: Method used to compute string offset and length. Known values are:
-         "textElements", "unicodeCodePoint", and "utf16CodeUnit". Default value is None.
-        :paramtype string_index_type: str or ~azure.ai.documentintelligence.models.StringIndexType
-        :keyword features: List of optional analysis features. Default value is None.
-        :paramtype features: list[str or ~azure.ai.documentintelligence.models.DocumentAnalysisFeature]
-        :keyword query_fields: List of additional fields to extract.  Ex. "NumberOfGuests,StoreNumber".
-         Default value is None.
-        :paramtype query_fields: list[str]
-        :keyword output_content_format: Format of the analyze result top-level content. Known values
-         are: "text" and "markdown". Default value is None.
-        :paramtype output_content_format: str or ~azure.ai.documentintelligence.models.ContentFormat
-        :keyword output: Additional outputs to generate during analysis. Default value is None.
-        :paramtype output: list[str or ~azure.ai.documentintelligence.models.AnalyzeOutputOption]
-        :keyword content_type: Body Parameter content-type. Content type parameter for binary body.
-         Default value is "application/json".
-        :paramtype content_type: str
-        :return: An instance of AsyncAnalyzeDocumentLROPoller that returns AnalyzeResult. The AnalyzeResult is
-         compatible with MutableMapping
-        :rtype: AsyncAnalyzeDocumentLROPoller[~azure.ai.documentintelligence.models.AnalyzeResult]
-        :raises ~azure.core.exceptions.HttpResponseError:
-        """
-
-    @distributed_trace_async
-    async def begin_analyze_document(  # type: ignore[override]
-        self,
-        model_id: str,
-        analyze_request: Optional[Union[_models.AnalyzeDocumentRequest, JSON, IO[bytes]]] = None,
-        *,
-        pages: Optional[str] = None,
-        locale: Optional[str] = None,
-        string_index_type: Optional[Union[str, _models.StringIndexType]] = None,
-        features: Optional[List[Union[str, _models.DocumentAnalysisFeature]]] = None,
-        query_fields: Optional[List[str]] = None,
-        output_content_format: Optional[Union[str, _models.ContentFormat]] = None,
-        output: Optional[List[Union[str, _models.AnalyzeOutputOption]]] = None,
-        **kwargs: Any
-    ) -> AsyncAnalyzeDocumentLROPoller[_models.AnalyzeResult]:
-        """Analyzes document with document model.
-
-        :param model_id: Unique document model name. Required.
-        :type model_id: str
-        :param analyze_request: Analyze request parameters. Is one of the following types:
-         AnalyzeDocumentRequest, JSON, IO[bytes] Default value is None.
-        :type analyze_request: ~azure.ai.documentintelligence.models.AnalyzeDocumentRequest or JSON or
-         IO[bytes]
-        :keyword pages: Range of 1-based page numbers to analyze.  Ex. "1-3,5,7-9". Default value is
-         None.
-        :paramtype pages: str
-        :keyword locale: Locale hint for text recognition and document analysis.  Value may contain
-         only
-         the language code (ex. "en", "fr") or BCP 47 language tag (ex. "en-US"). Default value is
-         None.
-        :paramtype locale: str
-        :keyword string_index_type: Method used to compute string offset and length. Known values are:
-         "textElements", "unicodeCodePoint", and "utf16CodeUnit". Default value is None.
-        :paramtype string_index_type: str or ~azure.ai.documentintelligence.models.StringIndexType
-        :keyword features: List of optional analysis features. Default value is None.
-        :paramtype features: list[str or ~azure.ai.documentintelligence.models.DocumentAnalysisFeature]
-        :keyword query_fields: List of additional fields to extract.  Ex. "NumberOfGuests,StoreNumber".
-         Default value is None.
-        :paramtype query_fields: list[str]
-        :keyword output_content_format: Format of the analyze result top-level content. Known values
-         are: "text" and "markdown". Default value is None.
-        :paramtype output_content_format: str or ~azure.ai.documentintelligence.models.ContentFormat
-        :keyword output: Additional outputs to generate during analysis. Default value is None.
-        :paramtype output: list[str or ~azure.ai.documentintelligence.models.AnalyzeOutputOption]
-        :return: An instance of AsyncAnalyzeDocumentLROPoller that returns AnalyzeResult. The AnalyzeResult is
-         compatible with MutableMapping
-        :rtype: AsyncAnalyzeDocumentLROPoller[~azure.ai.documentintelligence.models.AnalyzeResult]
-        :raises ~azure.core.exceptions.HttpResponseError:
-        """
-        _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
-        _params = kwargs.pop("params", {}) or {}
-
-        content_type: Optional[str] = kwargs.pop("content_type", _headers.pop("content-type", None))
-        cls: ClsType[_models.AnalyzeResult] = kwargs.pop("cls", None)
-        polling: Union[bool, AsyncPollingMethod] = kwargs.pop("polling", True)
-        lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
-        cont_token: Optional[str] = kwargs.pop("continuation_token", None)
-        if cont_token is None:
-            raw_result = await self._analyze_document_initial(
-                model_id=model_id,
-                analyze_request=analyze_request,
-                pages=pages,
-                locale=locale,
-                string_index_type=string_index_type,
-                features=features,
-                query_fields=query_fields,
-                output_content_format=output_content_format,
-                output=output,
-                content_type=content_type,
-                cls=lambda x, y, z: x,
-                headers=_headers,
-                params=_params,
-                **kwargs
-            )
-            await raw_result.http_response.read()  # type: ignore
-        kwargs.pop("error_map", None)
-
-        def get_long_running_output(pipeline_response):
-            response_headers = {}
-            response = pipeline_response.http_response
-            response_headers["Retry-After"] = self._deserialize("int", response.headers.get("Retry-After"))
-            response_headers["Operation-Location"] = self._deserialize(
-                "str", response.headers.get("Operation-Location")
-            )
-
-            deserialized = _deserialize(_models.AnalyzeResult, response.json().get("analyzeResult"))
-            if cls:
-                return cls(pipeline_response, deserialized, response_headers)  # type: ignore
-            return deserialized
-
-        path_format_arguments = {
-            "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str", skip_quote=True),
-        }
-
-        if polling is True:
-            polling_method: AsyncPollingMethod = cast(
-                AsyncPollingMethod,
-                AsyncLROBasePolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs),
-            )
-        elif polling is False:
-            polling_method = cast(AsyncPollingMethod, AsyncNoPolling())
-        else:
-            polling_method = polling
-        if cont_token:
-            return AsyncAnalyzeDocumentLROPoller[_models.AnalyzeBatchResult].from_continuation_token(
-                polling_method=polling_method,
-                continuation_token=cont_token,
-                client=self._client,
-                deserialization_callback=get_long_running_output,
-            )
-        return AsyncAnalyzeDocumentLROPoller[_models.AnalyzeResult](
-            self._client, raw_result, get_long_running_output, polling_method  # type: ignore
-        )
-
-    @distributed_trace_async
-    async def begin_analyze_batch_documents(  # type: ignore[override]
-        self,
-        model_id: str,
-        analyze_batch_request: Optional[Union[_models.AnalyzeBatchDocumentsRequest, JSON, IO[bytes]]] = None,
-        *,
-        pages: Optional[str] = None,
-        locale: Optional[str] = None,
-        string_index_type: Optional[Union[str, _models.StringIndexType]] = None,
-        features: Optional[List[Union[str, _models.DocumentAnalysisFeature]]] = None,
-        query_fields: Optional[List[str]] = None,
-        output_content_format: Optional[Union[str, _models.ContentFormat]] = None,
-        output: Optional[List[Union[str, _models.AnalyzeOutputOption]]] = None,
-        **kwargs: Any
-    ) -> AsyncLROPoller[_models.AnalyzeBatchResult]:
-        lro_delay = kwargs.pop("polling_interval", self._config.polling_interval)
-        return await super().begin_analyze_batch_documents(
-            model_id=model_id,
-            analyze_batch_request=analyze_batch_request,
-            pages=pages,
-            locale=locale,
-            string_index_type=string_index_type,
-            features=features,
-            query_fields=query_fields,
-            output_content_format=output_content_format,
-            output=output,
-            polling=AsyncAnalyzeBatchDocumentsLROPollingMethod(timeout=lro_delay),
-            **kwargs
-        )
-
-
-__all__: List[str] = [
-    "DocumentIntelligenceClientOperationsMixin",
-    "DocumentIntelligenceAdministrationClientOperationsMixin",
-]  # Add all objects you want publicly available to users at this package level
+__all__: List[str] = []  # Add all objects you want publicly available to users at this package level
 
 
 def patch_sdk():
diff --git a/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/aio/_patch.py b/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/aio/_patch.py
index 821d56fb6891d..f7dd32510333d 100644
--- a/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/aio/_patch.py
+++ b/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/aio/_patch.py
@@ -6,85 +6,9 @@
 
 Follow our quickstart for examples: https://aka.ms/azsdk/python/dpcodegen/python/customize
 """
-from typing import Any, List, Union
+from typing import List
 
-from azure.core.credentials import AzureKeyCredential
-from azure.core.credentials_async import AsyncTokenCredential
-
-from ._client import (
-    DocumentIntelligenceClient as DIClientGenerated,
-    DocumentIntelligenceAdministrationClient as DIAClientGenerated,
-)
-from ..aio._operations._patch import AsyncAnalyzeDocumentLROPoller
-
-
-class DocumentIntelligenceClient(DIClientGenerated):
-    """DocumentIntelligenceClient.
-
-    :param endpoint: The Document Intelligence service endpoint. Required.
-    :type endpoint: str
-    :param credential: Credential needed for the client to connect to Azure. Is either a
-     AzureKeyCredential type or a TokenCredential type. Required.
-    :type credential: ~azure.core.credentials.AzureKeyCredential or
-     ~azure.core.credentials_async.AsyncTokenCredential
-    :keyword api_version: The API version to use for this operation. Default value is
-     "2024-07-31-preview". Note that overriding this default value may result in unsupported
-     behavior.
-    :paramtype api_version: str
-    """
-
-    def __init__(
-        self,
-        endpoint: str,
-        credential: Union[AzureKeyCredential, AsyncTokenCredential],
-        **kwargs: Any,
-    ) -> None:
-        # Patch the default polling interval to be 1s.
-        polling_interval = kwargs.pop("polling_interval", 1)
-        super().__init__(
-            endpoint=endpoint,
-            credential=credential,
-            polling_interval=polling_interval,
-            **kwargs,
-        )
-
-
-class DocumentIntelligenceAdministrationClient(DIAClientGenerated):
-    """DocumentIntelligenceAdministrationClient.
-
-    :param endpoint: The Document Intelligence service endpoint. Required.
-    :type endpoint: str
-    :param credential: Credential needed for the client to connect to Azure. Is either a
-     AzureKeyCredential type or a TokenCredential type. Required.
-    :type credential: ~azure.core.credentials.AzureKeyCredential or
-     ~azure.core.credentials_async.AsyncTokenCredential
-    :keyword api_version: The API version to use for this operation. Default value is
-     "2024-07-31-preview". Note that overriding this default value may result in unsupported
-     behavior.
-    :paramtype api_version: str
-    """
-
-    def __init__(
-        self,
-        endpoint: str,
-        credential: Union[AzureKeyCredential, AsyncTokenCredential],
-        **kwargs: Any,
-    ) -> None:
-        # Patch the default polling interval to be 1s.
-        polling_interval = kwargs.pop("polling_interval", 1)
-        super().__init__(
-            endpoint=endpoint,
-            credential=credential,
-            polling_interval=polling_interval,
-            **kwargs,
-        )
-
-
-__all__: List[str] = [
-    "DocumentIntelligenceClient",
-    "DocumentIntelligenceAdministrationClient",
-    "AsyncAnalyzeDocumentLROPoller",
-]  # Add all objects you want publicly available to users at this package level
+__all__: List[str] = []  # Add all objects you want publicly available to users at this package level
 
 
 def patch_sdk():
diff --git a/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/models/__init__.py b/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/models/__init__.py
index 2f7221ee110ab..b1942899448f2 100644
--- a/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/models/__init__.py
+++ b/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/models/__init__.py
@@ -5,96 +5,107 @@
 # Code generated by Microsoft (R) Python Code Generator.
 # Changes may cause incorrect behavior and will be lost if the code is regenerated.
 # --------------------------------------------------------------------------
+# pylint: disable=wrong-import-position
 
-from ._models import AddressValue
-from ._models import AnalyzeBatchDocumentsRequest
-from ._models import AnalyzeBatchOperationDetail
-from ._models import AnalyzeBatchResult
-from ._models import AnalyzeBatchResultOperation
-from ._patch import AnalyzeDocumentRequest
-from ._models import AnalyzeResult
-from ._models import AnalyzeResultOperation
-from ._models import AuthorizeClassifierCopyRequest
-from ._models import AuthorizeCopyRequest
-from ._models import AzureBlobContentSource
-from ._models import AzureBlobFileListContentSource
-from ._models import BoundingRegion
-from ._models import BuildDocumentClassifierRequest
-from ._models import BuildDocumentModelRequest
-from ._models import ClassifierCopyAuthorization
-from ._models import ClassifierDocumentTypeDetails
-from ._patch import ClassifyDocumentRequest
-from ._models import ComposeDocumentModelRequest
-from ._models import CopyAuthorization
-from ._models import CurrencyValue
-from ._models import CustomDocumentModelsDetails
-from ._models import Document
-from ._models import DocumentBarcode
-from ._models import DocumentCaption
-from ._models import DocumentClassifierBuildOperationDetails
-from ._models import DocumentClassifierCopyToOperationDetails
-from ._models import DocumentClassifierDetails
-from ._models import DocumentField
-from ._models import DocumentFieldSchema
-from ._models import DocumentFigure
-from ._models import DocumentFootnote
-from ._models import DocumentFormula
-from ._models import DocumentKeyValueElement
-from ._models import DocumentKeyValuePair
-from ._models import DocumentLanguage
-from ._models import DocumentLine
-from ._models import DocumentModelBuildOperationDetails
-from ._models import DocumentModelComposeOperationDetails
-from ._models import DocumentModelCopyToOperationDetails
-from ._models import DocumentModelDetails
-from ._models import DocumentPage
-from ._models import DocumentParagraph
-from ._models import DocumentSection
-from ._models import DocumentSelectionMark
-from ._models import DocumentSpan
-from ._models import DocumentStyle
-from ._models import DocumentTable
-from ._models import DocumentTableCell
-from ._models import DocumentTypeDetails
-from ._models import DocumentWord
-from ._models import Error
-from ._models import ErrorResponse
-from ._models import InnerError
-from ._models import OperationDetails
-from ._models import ResourceDetails
-from ._models import Warning
+from typing import TYPE_CHECKING
 
-from ._enums import AnalyzeOutputOption
-from ._enums import ContentFormat
-from ._enums import ContentSourceKind
-from ._enums import DocumentAnalysisFeature
-from ._enums import DocumentBarcodeKind
-from ._enums import DocumentBuildMode
-from ._enums import DocumentFieldType
-from ._enums import DocumentFormulaKind
-from ._enums import DocumentSelectionMarkState
-from ._enums import DocumentSignatureType
-from ._enums import DocumentTableCellKind
-from ._enums import FontStyle
-from ._enums import FontWeight
-from ._enums import LengthUnit
-from ._enums import OperationKind
-from ._enums import OperationStatus
-from ._enums import ParagraphRole
-from ._enums import SplitMode
-from ._enums import StringIndexType
+if TYPE_CHECKING:
+    from ._patch import *  # pylint: disable=unused-wildcard-import
 
+
+from ._models import (  # type: ignore
+    AddressValue,
+    AnalyzeBatchDocumentsRequest,
+    AnalyzeBatchOperation,
+    AnalyzeBatchOperationDetail,
+    AnalyzeBatchResult,
+    AnalyzeDocumentRequest,
+    AnalyzeResult,
+    AnalyzedDocument,
+    AuthorizeClassifierCopyRequest,
+    AuthorizeCopyRequest,
+    AzureBlobContentSource,
+    AzureBlobFileListContentSource,
+    BoundingRegion,
+    BuildDocumentClassifierRequest,
+    BuildDocumentModelRequest,
+    ClassifierCopyAuthorization,
+    ClassifierDocumentTypeDetails,
+    ClassifyDocumentRequest,
+    ComposeDocumentModelRequest,
+    CurrencyValue,
+    CustomDocumentModelsDetails,
+    DocumentBarcode,
+    DocumentCaption,
+    DocumentClassifierBuildOperationDetails,
+    DocumentClassifierCopyToOperationDetails,
+    DocumentClassifierDetails,
+    DocumentField,
+    DocumentFieldSchema,
+    DocumentFigure,
+    DocumentFootnote,
+    DocumentFormula,
+    DocumentIntelligenceError,
+    DocumentIntelligenceErrorResponse,
+    DocumentIntelligenceInnerError,
+    DocumentIntelligenceOperationDetails,
+    DocumentIntelligenceResourceDetails,
+    DocumentIntelligenceWarning,
+    DocumentKeyValueElement,
+    DocumentKeyValuePair,
+    DocumentLanguage,
+    DocumentLine,
+    DocumentModelBuildOperationDetails,
+    DocumentModelComposeOperationDetails,
+    DocumentModelCopyToOperationDetails,
+    DocumentModelDetails,
+    DocumentPage,
+    DocumentParagraph,
+    DocumentSection,
+    DocumentSelectionMark,
+    DocumentSpan,
+    DocumentStyle,
+    DocumentTable,
+    DocumentTableCell,
+    DocumentTypeDetails,
+    DocumentWord,
+    ModelCopyAuthorization,
+)
+
+from ._enums import (  # type: ignore
+    AnalyzeOutputOption,
+    ContentSourceKind,
+    DocumentAnalysisFeature,
+    DocumentBarcodeKind,
+    DocumentBuildMode,
+    DocumentContentFormat,
+    DocumentFieldType,
+    DocumentFontStyle,
+    DocumentFontWeight,
+    DocumentFormulaKind,
+    DocumentIntelligenceOperationStatus,
+    DocumentSelectionMarkState,
+    DocumentSignatureType,
+    DocumentTableCellKind,
+    LengthUnit,
+    OperationKind,
+    ParagraphRole,
+    SplitMode,
+    StringIndexType,
+)
+from ._patch import __all__ as _patch_all
+from ._patch import *
 from ._patch import patch_sdk as _patch_sdk
 
 __all__ = [
     "AddressValue",
     "AnalyzeBatchDocumentsRequest",
+    "AnalyzeBatchOperation",
     "AnalyzeBatchOperationDetail",
     "AnalyzeBatchResult",
-    "AnalyzeBatchResultOperation",
     "AnalyzeDocumentRequest",
     "AnalyzeResult",
-    "AnalyzeResultOperation",
+    "AnalyzedDocument",
     "AuthorizeClassifierCopyRequest",
     "AuthorizeCopyRequest",
     "AzureBlobContentSource",
@@ -106,10 +117,8 @@
     "ClassifierDocumentTypeDetails",
     "ClassifyDocumentRequest",
     "ComposeDocumentModelRequest",
-    "CopyAuthorization",
     "CurrencyValue",
     "CustomDocumentModelsDetails",
-    "Document",
     "DocumentBarcode",
     "DocumentCaption",
     "DocumentClassifierBuildOperationDetails",
@@ -120,6 +129,12 @@
     "DocumentFigure",
     "DocumentFootnote",
     "DocumentFormula",
+    "DocumentIntelligenceError",
+    "DocumentIntelligenceErrorResponse",
+    "DocumentIntelligenceInnerError",
+    "DocumentIntelligenceOperationDetails",
+    "DocumentIntelligenceResourceDetails",
+    "DocumentIntelligenceWarning",
     "DocumentKeyValueElement",
     "DocumentKeyValuePair",
     "DocumentLanguage",
@@ -138,30 +153,26 @@
     "DocumentTableCell",
     "DocumentTypeDetails",
     "DocumentWord",
-    "Error",
-    "ErrorResponse",
-    "InnerError",
-    "OperationDetails",
-    "ResourceDetails",
-    "Warning",
+    "ModelCopyAuthorization",
     "AnalyzeOutputOption",
-    "ContentFormat",
     "ContentSourceKind",
     "DocumentAnalysisFeature",
     "DocumentBarcodeKind",
     "DocumentBuildMode",
+    "DocumentContentFormat",
     "DocumentFieldType",
+    "DocumentFontStyle",
+    "DocumentFontWeight",
     "DocumentFormulaKind",
+    "DocumentIntelligenceOperationStatus",
     "DocumentSelectionMarkState",
     "DocumentSignatureType",
     "DocumentTableCellKind",
-    "FontStyle",
-    "FontWeight",
     "LengthUnit",
     "OperationKind",
-    "OperationStatus",
     "ParagraphRole",
     "SplitMode",
     "StringIndexType",
 ]
+__all__.extend([p for p in _patch_all if p not in __all__])  # pyright: ignore
 _patch_sdk()
diff --git a/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/models/_enums.py b/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/models/_enums.py
index de21b9aa550e1..b9c14c8b13dcf 100644
--- a/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/models/_enums.py
+++ b/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/models/_enums.py
@@ -19,16 +19,6 @@ class AnalyzeOutputOption(str, Enum, metaclass=CaseInsensitiveEnumMeta):
     """Generate cropped images of detected figures."""
 
 
-class ContentFormat(str, Enum, metaclass=CaseInsensitiveEnumMeta):
-    """Format of the content in analyzed result."""
-
-    TEXT = "text"
-    """Plain text representation of the document content without any formatting."""
-    MARKDOWN = "markdown"
-    """Markdown representation of the document content with section headings, tables,
-    etc."""
-
-
 class ContentSourceKind(str, Enum, metaclass=CaseInsensitiveEnumMeta):
     """Type of content source."""
 
@@ -107,8 +97,16 @@ class DocumentBuildMode(str, Enum, metaclass=CaseInsensitiveEnumMeta):
     """Target documents with similar visual templates."""
     NEURAL = "neural"
     """Support documents with diverse visual templates."""
-    GENERATIVE = "generative"
-    """Enable documents of all types using generative AI techniques."""
+
+
+class DocumentContentFormat(str, Enum, metaclass=CaseInsensitiveEnumMeta):
+    """Format of the content in analyzed result."""
+
+    TEXT = "text"
+    """Plain text representation of the document content without any formatting."""
+    MARKDOWN = "markdown"
+    """Markdown representation of the document content with section headings, tables,
+    etc."""
 
 
 class DocumentFieldType(str, Enum, metaclass=CaseInsensitiveEnumMeta):
@@ -146,6 +144,24 @@ class DocumentFieldType(str, Enum, metaclass=CaseInsensitiveEnumMeta):
     """Array of selected string values."""
 
 
+class DocumentFontStyle(str, Enum, metaclass=CaseInsensitiveEnumMeta):
+    """Font style."""
+
+    NORMAL = "normal"
+    """Characters are represented normally."""
+    ITALIC = "italic"
+    """Characters are visually slanted to the right."""
+
+
+class DocumentFontWeight(str, Enum, metaclass=CaseInsensitiveEnumMeta):
+    """Font weight."""
+
+    NORMAL = "normal"
+    """Characters are represented normally."""
+    BOLD = "bold"
+    """Characters are represented with thicker strokes."""
+
+
 class DocumentFormulaKind(str, Enum, metaclass=CaseInsensitiveEnumMeta):
     """Formula kind."""
 
@@ -155,6 +171,23 @@ class DocumentFormulaKind(str, Enum, metaclass=CaseInsensitiveEnumMeta):
     """A formula in display mode that takes up an entire line."""
 
 
+class DocumentIntelligenceOperationStatus(str, Enum, metaclass=CaseInsensitiveEnumMeta):
+    """Operation status."""
+
+    NOT_STARTED = "notStarted"
+    """The operation has not started yet."""
+    RUNNING = "running"
+    """The operation is in progress."""
+    FAILED = "failed"
+    """The operation has failed."""
+    SUCCEEDED = "succeeded"
+    """The operation has succeeded."""
+    CANCELED = "canceled"
+    """The operation has been canceled."""
+    SKIPPED = "skipped"
+    """The operation has been skipped."""
+
+
 class DocumentSelectionMarkState(str, Enum, metaclass=CaseInsensitiveEnumMeta):
     """State of the selection mark."""
 
@@ -189,24 +222,6 @@ class DocumentTableCellKind(str, Enum, metaclass=CaseInsensitiveEnumMeta):
     """Describes the content in (parts of) the table."""
 
 
-class FontStyle(str, Enum, metaclass=CaseInsensitiveEnumMeta):
-    """Font style."""
-
-    NORMAL = "normal"
-    """Characters are represented normally."""
-    ITALIC = "italic"
-    """Characters are visually slanted to the right."""
-
-
-class FontWeight(str, Enum, metaclass=CaseInsensitiveEnumMeta):
-    """Font weight."""
-
-    NORMAL = "normal"
-    """Characters are represented normally."""
-    BOLD = "bold"
-    """Characters are represented with thicker strokes."""
-
-
 class LengthUnit(str, Enum, metaclass=CaseInsensitiveEnumMeta):
     """The unit used by the width, height, and polygon properties. For images, the unit is "pixel".
     For PDF, the unit is "inch".
@@ -235,23 +250,6 @@ class OperationKind(str, Enum, metaclass=CaseInsensitiveEnumMeta):
     """Build a new custom classifier model."""
 
 
-class OperationStatus(str, Enum, metaclass=CaseInsensitiveEnumMeta):
-    """Operation status."""
-
-    NOT_STARTED = "notStarted"
-    """The operation has not started yet."""
-    RUNNING = "running"
-    """The operation is in progress."""
-    FAILED = "failed"
-    """The operation has failed."""
-    SUCCEEDED = "succeeded"
-    """The operation has succeeded."""
-    COMPLETED = "completed"
-    """The operation has completed."""
-    CANCELED = "canceled"
-    """The operation has been canceled."""
-
-
 class ParagraphRole(str, Enum, metaclass=CaseInsensitiveEnumMeta):
     """Semantic role of the paragraph."""
 
diff --git a/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/models/_models.py b/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/models/_models.py
index 95af408671b00..b19eff689606b 100644
--- a/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/models/_models.py
+++ b/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/models/_models.py
@@ -6,6 +6,7 @@
 # Code generated by Microsoft (R) Python Code Generator.
 # Changes may cause incorrect behavior and will be lost if the code is regenerated.
 # --------------------------------------------------------------------------
+# pylint: disable=useless-super-delegation
 
 import datetime
 from typing import Any, Dict, List, Literal, Mapping, Optional, TYPE_CHECKING, Union, overload
@@ -18,7 +19,7 @@
     from .. import models as _models
 
 
-class AddressValue(_model_base.Model):  # pylint: disable=too-many-instance-attributes
+class AddressValue(_model_base.Model):
     """Address field value.
 
     :ivar house_number: House or building number.
@@ -111,7 +112,7 @@ def __init__(self, mapping: Mapping[str, Any]) -> None:
         :type mapping: Mapping[str, Any]
         """
 
-    def __init__(self, *args: Any, **kwargs: Any) -> None:  # pylint: disable=useless-super-delegation
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
         super().__init__(*args, **kwargs)
 
 
@@ -170,7 +171,69 @@ def __init__(self, mapping: Mapping[str, Any]) -> None:
         :type mapping: Mapping[str, Any]
         """
 
-    def __init__(self, *args: Any, **kwargs: Any) -> None:  # pylint: disable=useless-super-delegation
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
+        super().__init__(*args, **kwargs)
+
+
+class AnalyzeBatchOperation(_model_base.Model):
+    """Status and result of the analyze batch operation.
+
+
+    :ivar result_id: Analyze batch operation result ID.
+    :vartype result_id: str
+    :ivar status: Operation status.  notStarted, running, succeeded, or failed. Required. Known
+     values are: "notStarted", "running", "failed", "succeeded", "canceled", and "skipped".
+    :vartype status: str or
+     ~azure.ai.documentintelligence.models.DocumentIntelligenceOperationStatus
+    :ivar created_date_time: Date and time (UTC) when the operation was submitted. Required.
+    :vartype created_date_time: ~datetime.datetime
+    :ivar last_updated_date_time: Date and time (UTC) when the status was last updated. Required.
+    :vartype last_updated_date_time: ~datetime.datetime
+    :ivar percent_completed: Operation progress (0-100).
+    :vartype percent_completed: int
+    :ivar error: Encountered error during batch document analysis.
+    :vartype error: ~azure.ai.documentintelligence.models.DocumentIntelligenceError
+    :ivar result: Batch document analysis result.
+    :vartype result: ~azure.ai.documentintelligence.models.AnalyzeBatchResult
+    """
+
+    result_id: Optional[str] = rest_field(name="resultId")
+    """Analyze batch operation result ID."""
+    status: Union[str, "_models.DocumentIntelligenceOperationStatus"] = rest_field()
+    """Operation status.  notStarted, running, succeeded, or failed. Required. Known values are:
+     \"notStarted\", \"running\", \"failed\", \"succeeded\", \"canceled\", and \"skipped\"."""
+    created_date_time: datetime.datetime = rest_field(name="createdDateTime", format="rfc3339")
+    """Date and time (UTC) when the operation was submitted. Required."""
+    last_updated_date_time: datetime.datetime = rest_field(name="lastUpdatedDateTime", format="rfc3339")
+    """Date and time (UTC) when the status was last updated. Required."""
+    percent_completed: Optional[int] = rest_field(name="percentCompleted")
+    """Operation progress (0-100)."""
+    error: Optional["_models.DocumentIntelligenceError"] = rest_field()
+    """Encountered error during batch document analysis."""
+    result: Optional["_models.AnalyzeBatchResult"] = rest_field()
+    """Batch document analysis result."""
+
+    @overload
+    def __init__(
+        self,
+        *,
+        status: Union[str, "_models.DocumentIntelligenceOperationStatus"],
+        created_date_time: datetime.datetime,
+        last_updated_date_time: datetime.datetime,
+        result_id: Optional[str] = None,
+        percent_completed: Optional[int] = None,
+        error: Optional["_models.DocumentIntelligenceError"] = None,
+        result: Optional["_models.AnalyzeBatchResult"] = None,
+    ) -> None: ...
+
+    @overload
+    def __init__(self, mapping: Mapping[str, Any]) -> None:
+        """
+        :param mapping: raw JSON to initialize the model.
+        :type mapping: Mapping[str, Any]
+        """
+
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
         super().__init__(*args, **kwargs)
 
 
@@ -179,34 +242,35 @@ class AnalyzeBatchOperationDetail(_model_base.Model):
 
 
     :ivar status: Analyze status.  succeeded, failed, or skipped. Required. Known values are:
-     "notStarted", "running", "failed", "succeeded", "completed", and "canceled".
-    :vartype status: str or ~azure.ai.documentintelligence.models.OperationStatus
+     "notStarted", "running", "failed", "succeeded", "canceled", and "skipped".
+    :vartype status: str or
+     ~azure.ai.documentintelligence.models.DocumentIntelligenceOperationStatus
     :ivar source_url: URL of the source document. Required.
     :vartype source_url: str
     :ivar result_url: URL of the analyze result JSON.
     :vartype result_url: str
     :ivar error: Encountered error.
-    :vartype error: ~azure.ai.documentintelligence.models.Error
+    :vartype error: ~azure.ai.documentintelligence.models.DocumentIntelligenceError
     """
 
-    status: Union[str, "_models.OperationStatus"] = rest_field()
+    status: Union[str, "_models.DocumentIntelligenceOperationStatus"] = rest_field()
     """Analyze status.  succeeded, failed, or skipped. Required. Known values are: \"notStarted\",
-     \"running\", \"failed\", \"succeeded\", \"completed\", and \"canceled\"."""
+     \"running\", \"failed\", \"succeeded\", \"canceled\", and \"skipped\"."""
     source_url: str = rest_field(name="sourceUrl")
     """URL of the source document. Required."""
     result_url: Optional[str] = rest_field(name="resultUrl")
     """URL of the analyze result JSON."""
-    error: Optional["_models.Error"] = rest_field()
+    error: Optional["_models.DocumentIntelligenceError"] = rest_field()
     """Encountered error."""
 
     @overload
     def __init__(
         self,
         *,
-        status: Union[str, "_models.OperationStatus"],
+        status: Union[str, "_models.DocumentIntelligenceOperationStatus"],
         source_url: str,
         result_url: Optional[str] = None,
-        error: Optional["_models.Error"] = None,
+        error: Optional["_models.DocumentIntelligenceError"] = None,
     ) -> None: ...
 
     @overload
@@ -216,7 +280,7 @@ def __init__(self, mapping: Mapping[str, Any]) -> None:
         :type mapping: Mapping[str, Any]
         """
 
-    def __init__(self, *args: Any, **kwargs: Any) -> None:  # pylint: disable=useless-super-delegation
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
         super().__init__(*args, **kwargs)
 
 
@@ -230,7 +294,7 @@ class AnalyzeBatchResult(_model_base.Model):
     :vartype failed_count: int
     :ivar skipped_count: Number of documents that completed with status skipped. Required.
     :vartype skipped_count: int
-    :ivar details: Operation detail for each document in the batch. Required.
+    :ivar details: Operation detail for each document in the batch.
     :vartype details: list[~azure.ai.documentintelligence.models.AnalyzeBatchOperationDetail]
     """
 
@@ -240,8 +304,8 @@ class AnalyzeBatchResult(_model_base.Model):
     """Number of documents that completed with status failed. Required."""
     skipped_count: int = rest_field(name="skippedCount")
     """Number of documents that completed with status skipped. Required."""
-    details: List["_models.AnalyzeBatchOperationDetail"] = rest_field()
-    """Operation detail for each document in the batch. Required."""
+    details: Optional[List["_models.AnalyzeBatchOperationDetail"]] = rest_field()
+    """Operation detail for each document in the batch."""
 
     @overload
     def __init__(
@@ -250,7 +314,7 @@ def __init__(
         succeeded_count: int,
         failed_count: int,
         skipped_count: int,
-        details: List["_models.AnalyzeBatchOperationDetail"],
+        details: Optional[List["_models.AnalyzeBatchOperationDetail"]] = None,
     ) -> None: ...
 
     @overload
@@ -260,53 +324,46 @@ def __init__(self, mapping: Mapping[str, Any]) -> None:
         :type mapping: Mapping[str, Any]
         """
 
-    def __init__(self, *args: Any, **kwargs: Any) -> None:  # pylint: disable=useless-super-delegation
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
         super().__init__(*args, **kwargs)
 
 
-class AnalyzeBatchResultOperation(_model_base.Model):
-    """Status and result of the analyze batch operation.
+class AnalyzedDocument(_model_base.Model):
+    """An object describing the location and semantic content of a document.
 
 
-    :ivar status: Operation status.  notStarted, running, completed, or failed. Required. Known
-     values are: "notStarted", "running", "failed", "succeeded", "completed", and "canceled".
-    :vartype status: str or ~azure.ai.documentintelligence.models.OperationStatus
-    :ivar created_date_time: Date and time (UTC) when the operation was submitted. Required.
-    :vartype created_date_time: ~datetime.datetime
-    :ivar last_updated_date_time: Date and time (UTC) when the status was last updated. Required.
-    :vartype last_updated_date_time: ~datetime.datetime
-    :ivar percent_completed: Operation progress (0-100).
-    :vartype percent_completed: int
-    :ivar error: Encountered error during batch document analysis.
-    :vartype error: ~azure.ai.documentintelligence.models.Error
-    :ivar result: Batch document analysis result.
-    :vartype result: ~azure.ai.documentintelligence.models.AnalyzeBatchResult
+    :ivar doc_type: Document type. Required.
+    :vartype doc_type: str
+    :ivar bounding_regions: Bounding regions covering the document.
+    :vartype bounding_regions: list[~azure.ai.documentintelligence.models.BoundingRegion]
+    :ivar spans: Location of the document in the reading order concatenated content. Required.
+    :vartype spans: list[~azure.ai.documentintelligence.models.DocumentSpan]
+    :ivar fields: Dictionary of named field values.
+    :vartype fields: dict[str, ~azure.ai.documentintelligence.models.DocumentField]
+    :ivar confidence: Confidence of correctly extracting the document. Required.
+    :vartype confidence: float
     """
 
-    status: Union[str, "_models.OperationStatus"] = rest_field()
-    """Operation status.  notStarted, running, completed, or failed. Required. Known values are:
-     \"notStarted\", \"running\", \"failed\", \"succeeded\", \"completed\", and \"canceled\"."""
-    created_date_time: datetime.datetime = rest_field(name="createdDateTime", format="rfc3339")
-    """Date and time (UTC) when the operation was submitted. Required."""
-    last_updated_date_time: datetime.datetime = rest_field(name="lastUpdatedDateTime", format="rfc3339")
-    """Date and time (UTC) when the status was last updated. Required."""
-    percent_completed: Optional[int] = rest_field(name="percentCompleted")
-    """Operation progress (0-100)."""
-    error: Optional["_models.Error"] = rest_field()
-    """Encountered error during batch document analysis."""
-    result: Optional["_models.AnalyzeBatchResult"] = rest_field()
-    """Batch document analysis result."""
+    doc_type: str = rest_field(name="docType")
+    """Document type. Required."""
+    bounding_regions: Optional[List["_models.BoundingRegion"]] = rest_field(name="boundingRegions")
+    """Bounding regions covering the document."""
+    spans: List["_models.DocumentSpan"] = rest_field()
+    """Location of the document in the reading order concatenated content. Required."""
+    fields: Optional[Dict[str, "_models.DocumentField"]] = rest_field()
+    """Dictionary of named field values."""
+    confidence: float = rest_field()
+    """Confidence of correctly extracting the document. Required."""
 
     @overload
     def __init__(
         self,
         *,
-        status: Union[str, "_models.OperationStatus"],
-        created_date_time: datetime.datetime,
-        last_updated_date_time: datetime.datetime,
-        percent_completed: Optional[int] = None,
-        error: Optional["_models.Error"] = None,
-        result: Optional["_models.AnalyzeBatchResult"] = None,
+        doc_type: str,
+        spans: List["_models.DocumentSpan"],
+        confidence: float,
+        bounding_regions: Optional[List["_models.BoundingRegion"]] = None,
+        fields: Optional[Dict[str, "_models.DocumentField"]] = None,
     ) -> None: ...
 
     @overload
@@ -316,7 +373,7 @@ def __init__(self, mapping: Mapping[str, Any]) -> None:
         :type mapping: Mapping[str, Any]
         """
 
-    def __init__(self, *args: Any, **kwargs: Any) -> None:  # pylint: disable=useless-super-delegation
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
         super().__init__(*args, **kwargs)
 
 
@@ -352,11 +409,11 @@ def __init__(self, mapping: Mapping[str, Any]) -> None:
         :type mapping: Mapping[str, Any]
         """
 
-    def __init__(self, *args: Any, **kwargs: Any) -> None:  # pylint: disable=useless-super-delegation
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
         super().__init__(*args, **kwargs)
 
 
-class AnalyzeResult(_model_base.Model):  # pylint: disable=too-many-instance-attributes
+class AnalyzeResult(_model_base.Model):
     """Document analysis result.
 
 
@@ -369,7 +426,7 @@ class AnalyzeResult(_model_base.Model):  # pylint: disable=too-many-instance-att
     :vartype string_index_type: str or ~azure.ai.documentintelligence.models.StringIndexType
     :ivar content_format: Format of the analyze result top-level content. Known values are: "text"
      and "markdown".
-    :vartype content_format: str or ~azure.ai.documentintelligence.models.ContentFormat
+    :vartype content_format: str or ~azure.ai.documentintelligence.models.DocumentContentFormat
     :ivar content: Concatenate string representation of all textual and visual elements in reading
      order. Required.
     :vartype content: str
@@ -390,9 +447,9 @@ class AnalyzeResult(_model_base.Model):  # pylint: disable=too-many-instance-att
     :ivar languages: Detected languages.
     :vartype languages: list[~azure.ai.documentintelligence.models.DocumentLanguage]
     :ivar documents: Extracted documents.
-    :vartype documents: list[~azure.ai.documentintelligence.models.Document]
+    :vartype documents: list[~azure.ai.documentintelligence.models.AnalyzedDocument]
     :ivar warnings: List of warnings encountered.
-    :vartype warnings: list[~azure.ai.documentintelligence.models.Warning]
+    :vartype warnings: list[~azure.ai.documentintelligence.models.DocumentIntelligenceWarning]
     """
 
     api_version: str = rest_field(name="apiVersion")
@@ -402,7 +459,7 @@ class AnalyzeResult(_model_base.Model):  # pylint: disable=too-many-instance-att
     string_index_type: Union[str, "_models.StringIndexType"] = rest_field(name="stringIndexType")
     """Method used to compute string offset and length. Required. Known values are: \"textElements\",
      \"unicodeCodePoint\", and \"utf16CodeUnit\"."""
-    content_format: Optional[Union[str, "_models.ContentFormat"]] = rest_field(name="contentFormat")
+    content_format: Optional[Union[str, "_models.DocumentContentFormat"]] = rest_field(name="contentFormat")
     """Format of the analyze result top-level content. Known values are: \"text\" and \"markdown\"."""
     content: str = rest_field()
     """Concatenate string representation of all textual and visual elements in reading
@@ -423,9 +480,9 @@ class AnalyzeResult(_model_base.Model):  # pylint: disable=too-many-instance-att
     """Extracted font styles."""
     languages: Optional[List["_models.DocumentLanguage"]] = rest_field()
     """Detected languages."""
-    documents: Optional[List["_models.Document"]] = rest_field()
+    documents: Optional[List["_models.AnalyzedDocument"]] = rest_field()
     """Extracted documents."""
-    warnings: Optional[List["_models.Warning"]] = rest_field()
+    warnings: Optional[List["_models.DocumentIntelligenceWarning"]] = rest_field()
     """List of warnings encountered."""
 
     @overload
@@ -437,7 +494,7 @@ def __init__(
         string_index_type: Union[str, "_models.StringIndexType"],
         content: str,
         pages: List["_models.DocumentPage"],
-        content_format: Optional[Union[str, "_models.ContentFormat"]] = None,
+        content_format: Optional[Union[str, "_models.DocumentContentFormat"]] = None,
         paragraphs: Optional[List["_models.DocumentParagraph"]] = None,
         tables: Optional[List["_models.DocumentTable"]] = None,
         figures: Optional[List["_models.DocumentFigure"]] = None,
@@ -445,60 +502,8 @@ def __init__(
         key_value_pairs: Optional[List["_models.DocumentKeyValuePair"]] = None,
         styles: Optional[List["_models.DocumentStyle"]] = None,
         languages: Optional[List["_models.DocumentLanguage"]] = None,
-        documents: Optional[List["_models.Document"]] = None,
-        warnings: Optional[List["_models.Warning"]] = None,
-    ) -> None: ...
-
-    @overload
-    def __init__(self, mapping: Mapping[str, Any]) -> None:
-        """
-        :param mapping: raw JSON to initialize the model.
-        :type mapping: Mapping[str, Any]
-        """
-
-    def __init__(self, *args: Any, **kwargs: Any) -> None:  # pylint: disable=useless-super-delegation
-        super().__init__(*args, **kwargs)
-
-
-class AnalyzeResultOperation(_model_base.Model):
-    """Status and result of the analyze operation.
-
-
-    :ivar status: Operation status.  notStarted, running, succeeded, or failed. Required. Known
-     values are: "notStarted", "running", "failed", "succeeded", "completed", and "canceled".
-    :vartype status: str or ~azure.ai.documentintelligence.models.OperationStatus
-    :ivar created_date_time: Date and time (UTC) when the analyze operation was submitted.
-     Required.
-    :vartype created_date_time: ~datetime.datetime
-    :ivar last_updated_date_time: Date and time (UTC) when the status was last updated. Required.
-    :vartype last_updated_date_time: ~datetime.datetime
-    :ivar error: Encountered error during document analysis.
-    :vartype error: ~azure.ai.documentintelligence.models.Error
-    :ivar analyze_result: Document analysis result.
-    :vartype analyze_result: ~azure.ai.documentintelligence.models.AnalyzeResult
-    """
-
-    status: Union[str, "_models.OperationStatus"] = rest_field()
-    """Operation status.  notStarted, running, succeeded, or failed. Required. Known values are:
-     \"notStarted\", \"running\", \"failed\", \"succeeded\", \"completed\", and \"canceled\"."""
-    created_date_time: datetime.datetime = rest_field(name="createdDateTime", format="rfc3339")
-    """Date and time (UTC) when the analyze operation was submitted. Required."""
-    last_updated_date_time: datetime.datetime = rest_field(name="lastUpdatedDateTime", format="rfc3339")
-    """Date and time (UTC) when the status was last updated. Required."""
-    error: Optional["_models.Error"] = rest_field()
-    """Encountered error during document analysis."""
-    analyze_result: Optional["_models.AnalyzeResult"] = rest_field(name="analyzeResult")
-    """Document analysis result."""
-
-    @overload
-    def __init__(
-        self,
-        *,
-        status: Union[str, "_models.OperationStatus"],
-        created_date_time: datetime.datetime,
-        last_updated_date_time: datetime.datetime,
-        error: Optional["_models.Error"] = None,
-        analyze_result: Optional["_models.AnalyzeResult"] = None,
+        documents: Optional[List["_models.AnalyzedDocument"]] = None,
+        warnings: Optional[List["_models.DocumentIntelligenceWarning"]] = None,
     ) -> None: ...
 
     @overload
@@ -508,7 +513,7 @@ def __init__(self, mapping: Mapping[str, Any]) -> None:
         :type mapping: Mapping[str, Any]
         """
 
-    def __init__(self, *args: Any, **kwargs: Any) -> None:  # pylint: disable=useless-super-delegation
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
         super().__init__(*args, **kwargs)
 
 
@@ -548,7 +553,7 @@ def __init__(self, mapping: Mapping[str, Any]) -> None:
         :type mapping: Mapping[str, Any]
         """
 
-    def __init__(self, *args: Any, **kwargs: Any) -> None:  # pylint: disable=useless-super-delegation
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
         super().__init__(*args, **kwargs)
 
 
@@ -588,7 +593,7 @@ def __init__(self, mapping: Mapping[str, Any]) -> None:
         :type mapping: Mapping[str, Any]
         """
 
-    def __init__(self, *args: Any, **kwargs: Any) -> None:  # pylint: disable=useless-super-delegation
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
         super().__init__(*args, **kwargs)
 
 
@@ -622,7 +627,7 @@ def __init__(self, mapping: Mapping[str, Any]) -> None:
         :type mapping: Mapping[str, Any]
         """
 
-    def __init__(self, *args: Any, **kwargs: Any) -> None:  # pylint: disable=useless-super-delegation
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
         super().__init__(*args, **kwargs)
 
 
@@ -657,7 +662,7 @@ def __init__(self, mapping: Mapping[str, Any]) -> None:
         :type mapping: Mapping[str, Any]
         """
 
-    def __init__(self, *args: Any, **kwargs: Any) -> None:  # pylint: disable=useless-super-delegation
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
         super().__init__(*args, **kwargs)
 
 
@@ -697,7 +702,7 @@ def __init__(self, mapping: Mapping[str, Any]) -> None:
         :type mapping: Mapping[str, Any]
         """
 
-    def __init__(self, *args: Any, **kwargs: Any) -> None:  # pylint: disable=useless-super-delegation
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
         super().__init__(*args, **kwargs)
 
 
@@ -748,7 +753,7 @@ def __init__(self, mapping: Mapping[str, Any]) -> None:
         :type mapping: Mapping[str, Any]
         """
 
-    def __init__(self, *args: Any, **kwargs: Any) -> None:  # pylint: disable=useless-super-delegation
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
         super().__init__(*args, **kwargs)
 
 
@@ -761,8 +766,8 @@ class BuildDocumentModelRequest(_model_base.Model):
     :vartype model_id: str
     :ivar description: Document model description.
     :vartype description: str
-    :ivar build_mode: Custom document model build mode. Required. Known values are: "template",
-     "neural", and "generative".
+    :ivar build_mode: Custom document model build mode. Required. Known values are: "template" and
+     "neural".
     :vartype build_mode: str or ~azure.ai.documentintelligence.models.DocumentBuildMode
     :ivar azure_blob_source: Azure Blob Storage location containing the training data.  Either
      azureBlobSource or azureBlobFileListSource must be specified.
@@ -786,8 +791,7 @@ class BuildDocumentModelRequest(_model_base.Model):
     description: Optional[str] = rest_field()
     """Document model description."""
     build_mode: Union[str, "_models.DocumentBuildMode"] = rest_field(name="buildMode")
-    """Custom document model build mode. Required. Known values are: \"template\", \"neural\", and
-     \"generative\"."""
+    """Custom document model build mode. Required. Known values are: \"template\" and \"neural\"."""
     azure_blob_source: Optional["_models.AzureBlobContentSource"] = rest_field(name="azureBlobSource")
     """Azure Blob Storage location containing the training data.  Either
      azureBlobSource or azureBlobFileListSource must be specified."""
@@ -824,7 +828,7 @@ def __init__(self, mapping: Mapping[str, Any]) -> None:
         :type mapping: Mapping[str, Any]
         """
 
-    def __init__(self, *args: Any, **kwargs: Any) -> None:  # pylint: disable=useless-super-delegation
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
         super().__init__(*args, **kwargs)
 
 
@@ -884,7 +888,7 @@ def __init__(self, mapping: Mapping[str, Any]) -> None:
         :type mapping: Mapping[str, Any]
         """
 
-    def __init__(self, *args: Any, **kwargs: Any) -> None:  # pylint: disable=useless-super-delegation
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
         super().__init__(*args, **kwargs)
 
 
@@ -937,7 +941,7 @@ def __init__(self, mapping: Mapping[str, Any]) -> None:
         :type mapping: Mapping[str, Any]
         """
 
-    def __init__(self, *args: Any, **kwargs: Any) -> None:  # pylint: disable=useless-super-delegation
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
         super().__init__(*args, **kwargs)
 
 
@@ -974,7 +978,7 @@ def __init__(self, mapping: Mapping[str, Any]) -> None:
         :type mapping: Mapping[str, Any]
         """
 
-    def __init__(self, *args: Any, **kwargs: Any) -> None:  # pylint: disable=useless-super-delegation
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
         super().__init__(*args, **kwargs)
 
 
@@ -1030,66 +1034,7 @@ def __init__(self, mapping: Mapping[str, Any]) -> None:
         :type mapping: Mapping[str, Any]
         """
 
-    def __init__(self, *args: Any, **kwargs: Any) -> None:  # pylint: disable=useless-super-delegation
-        super().__init__(*args, **kwargs)
-
-
-class CopyAuthorization(_model_base.Model):
-    """Authorization to copy a document model to the specified target resource and
-    modelId.
-
-
-    :ivar target_resource_id: ID of the target Azure resource where the document model should be
-     copied to. Required.
-    :vartype target_resource_id: str
-    :ivar target_resource_region: Location of the target Azure resource where the document model
-     should be copied
-     to. Required.
-    :vartype target_resource_region: str
-    :ivar target_model_id: Identifier of the target document model. Required.
-    :vartype target_model_id: str
-    :ivar target_model_location: URL of the copied document model in the target account. Required.
-    :vartype target_model_location: str
-    :ivar access_token: Token used to authorize the request. Required.
-    :vartype access_token: str
-    :ivar expiration_date_time: Date/time when the access token expires. Required.
-    :vartype expiration_date_time: ~datetime.datetime
-    """
-
-    target_resource_id: str = rest_field(name="targetResourceId")
-    """ID of the target Azure resource where the document model should be copied to. Required."""
-    target_resource_region: str = rest_field(name="targetResourceRegion")
-    """Location of the target Azure resource where the document model should be copied
-     to. Required."""
-    target_model_id: str = rest_field(name="targetModelId")
-    """Identifier of the target document model. Required."""
-    target_model_location: str = rest_field(name="targetModelLocation")
-    """URL of the copied document model in the target account. Required."""
-    access_token: str = rest_field(name="accessToken")
-    """Token used to authorize the request. Required."""
-    expiration_date_time: datetime.datetime = rest_field(name="expirationDateTime", format="rfc3339")
-    """Date/time when the access token expires. Required."""
-
-    @overload
-    def __init__(
-        self,
-        *,
-        target_resource_id: str,
-        target_resource_region: str,
-        target_model_id: str,
-        target_model_location: str,
-        access_token: str,
-        expiration_date_time: datetime.datetime,
-    ) -> None: ...
-
-    @overload
-    def __init__(self, mapping: Mapping[str, Any]) -> None:
-        """
-        :param mapping: raw JSON to initialize the model.
-        :type mapping: Mapping[str, Any]
-        """
-
-    def __init__(self, *args: Any, **kwargs: Any) -> None:  # pylint: disable=useless-super-delegation
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
         super().__init__(*args, **kwargs)
 
 
@@ -1128,7 +1073,7 @@ def __init__(self, mapping: Mapping[str, Any]) -> None:
         :type mapping: Mapping[str, Any]
         """
 
-    def __init__(self, *args: Any, **kwargs: Any) -> None:  # pylint: disable=useless-super-delegation
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
         super().__init__(*args, **kwargs)
 
 
@@ -1163,56 +1108,7 @@ def __init__(self, mapping: Mapping[str, Any]) -> None:
         :type mapping: Mapping[str, Any]
         """
 
-    def __init__(self, *args: Any, **kwargs: Any) -> None:  # pylint: disable=useless-super-delegation
-        super().__init__(*args, **kwargs)
-
-
-class Document(_model_base.Model):
-    """An object describing the location and semantic content of a document.
-
-
-    :ivar doc_type: Document type. Required.
-    :vartype doc_type: str
-    :ivar bounding_regions: Bounding regions covering the document.
-    :vartype bounding_regions: list[~azure.ai.documentintelligence.models.BoundingRegion]
-    :ivar spans: Location of the document in the reading order concatenated content. Required.
-    :vartype spans: list[~azure.ai.documentintelligence.models.DocumentSpan]
-    :ivar fields: Dictionary of named field values.
-    :vartype fields: dict[str, ~azure.ai.documentintelligence.models.DocumentField]
-    :ivar confidence: Confidence of correctly extracting the document. Required.
-    :vartype confidence: float
-    """
-
-    doc_type: str = rest_field(name="docType")
-    """Document type. Required."""
-    bounding_regions: Optional[List["_models.BoundingRegion"]] = rest_field(name="boundingRegions")
-    """Bounding regions covering the document."""
-    spans: List["_models.DocumentSpan"] = rest_field()
-    """Location of the document in the reading order concatenated content. Required."""
-    fields: Optional[Dict[str, "_models.DocumentField"]] = rest_field()
-    """Dictionary of named field values."""
-    confidence: float = rest_field()
-    """Confidence of correctly extracting the document. Required."""
-
-    @overload
-    def __init__(
-        self,
-        *,
-        doc_type: str,
-        spans: List["_models.DocumentSpan"],
-        confidence: float,
-        bounding_regions: Optional[List["_models.BoundingRegion"]] = None,
-        fields: Optional[Dict[str, "_models.DocumentField"]] = None,
-    ) -> None: ...
-
-    @overload
-    def __init__(self, mapping: Mapping[str, Any]) -> None:
-        """
-        :param mapping: raw JSON to initialize the model.
-        :type mapping: Mapping[str, Any]
-        """
-
-    def __init__(self, *args: Any, **kwargs: Any) -> None:  # pylint: disable=useless-super-delegation
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
         super().__init__(*args, **kwargs)
 
 
@@ -1271,7 +1167,7 @@ def __init__(self, mapping: Mapping[str, Any]) -> None:
         :type mapping: Mapping[str, Any]
         """
 
-    def __init__(self, *args: Any, **kwargs: Any) -> None:  # pylint: disable=useless-super-delegation
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
         super().__init__(*args, **kwargs)
 
 
@@ -1315,11 +1211,11 @@ def __init__(self, mapping: Mapping[str, Any]) -> None:
         :type mapping: Mapping[str, Any]
         """
 
-    def __init__(self, *args: Any, **kwargs: Any) -> None:  # pylint: disable=useless-super-delegation
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
         super().__init__(*args, **kwargs)
 
 
-class OperationDetails(_model_base.Model):
+class DocumentIntelligenceOperationDetails(_model_base.Model):
     """Operation info.
 
     You probably want to use the sub-classes and not this class directly. Known sub-classes are:
@@ -1331,8 +1227,9 @@ class OperationDetails(_model_base.Model):
     :ivar operation_id: Operation ID. Required.
     :vartype operation_id: str
     :ivar status: Operation status.  notStarted, running, completed, or failed. Required. Known
-     values are: "notStarted", "running", "failed", "succeeded", "completed", and "canceled".
-    :vartype status: str or ~azure.ai.documentintelligence.models.OperationStatus
+     values are: "notStarted", "running", "failed", "succeeded", "canceled", and "skipped".
+    :vartype status: str or
+     ~azure.ai.documentintelligence.models.DocumentIntelligenceOperationStatus
     :ivar percent_completed: Operation progress (0-100).
     :vartype percent_completed: int
     :ivar created_date_time: Date and time (UTC) when the operation was created. Required.
@@ -1350,15 +1247,15 @@ class OperationDetails(_model_base.Model):
     :ivar tags: List of key-value tag attributes associated with the document model.
     :vartype tags: dict[str, str]
     :ivar error: Encountered error.
-    :vartype error: ~azure.ai.documentintelligence.models.Error
+    :vartype error: ~azure.ai.documentintelligence.models.DocumentIntelligenceError
     """
 
     __mapping__: Dict[str, _model_base.Model] = {}
     operation_id: str = rest_field(name="operationId", visibility=["read", "create"])
     """Operation ID. Required."""
-    status: Union[str, "_models.OperationStatus"] = rest_field()
+    status: Union[str, "_models.DocumentIntelligenceOperationStatus"] = rest_field()
     """Operation status.  notStarted, running, completed, or failed. Required. Known values are:
-     \"notStarted\", \"running\", \"failed\", \"succeeded\", \"completed\", and \"canceled\"."""
+     \"notStarted\", \"running\", \"failed\", \"succeeded\", \"canceled\", and \"skipped\"."""
     percent_completed: Optional[int] = rest_field(name="percentCompleted")
     """Operation progress (0-100)."""
     created_date_time: datetime.datetime = rest_field(name="createdDateTime", format="rfc3339")
@@ -1375,7 +1272,7 @@ class OperationDetails(_model_base.Model):
     """API version used to create this operation."""
     tags: Optional[Dict[str, str]] = rest_field()
     """List of key-value tag attributes associated with the document model."""
-    error: Optional["_models.Error"] = rest_field()
+    error: Optional["_models.DocumentIntelligenceError"] = rest_field()
     """Encountered error."""
 
     @overload
@@ -1383,7 +1280,7 @@ def __init__(
         self,
         *,
         operation_id: str,
-        status: Union[str, "_models.OperationStatus"],
+        status: Union[str, "_models.DocumentIntelligenceOperationStatus"],
         created_date_time: datetime.datetime,
         last_updated_date_time: datetime.datetime,
         kind: str,
@@ -1391,7 +1288,7 @@ def __init__(
         percent_completed: Optional[int] = None,
         api_version: Optional[str] = None,
         tags: Optional[Dict[str, str]] = None,
-        error: Optional["_models.Error"] = None,
+        error: Optional["_models.DocumentIntelligenceError"] = None,
     ) -> None: ...
 
     @overload
@@ -1401,21 +1298,22 @@ def __init__(self, mapping: Mapping[str, Any]) -> None:
         :type mapping: Mapping[str, Any]
         """
 
-    def __init__(self, *args: Any, **kwargs: Any) -> None:  # pylint: disable=useless-super-delegation
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
         super().__init__(*args, **kwargs)
 
 
 class DocumentClassifierBuildOperationDetails(
-    OperationDetails, discriminator="documentClassifierBuild"
-):  # pylint: disable=too-many-instance-attributes
+    DocumentIntelligenceOperationDetails, discriminator="documentClassifierBuild"
+):
     """Get Operation response object.
 
 
     :ivar operation_id: Operation ID. Required.
     :vartype operation_id: str
     :ivar status: Operation status.  notStarted, running, completed, or failed. Required. Known
-     values are: "notStarted", "running", "failed", "succeeded", "completed", and "canceled".
-    :vartype status: str or ~azure.ai.documentintelligence.models.OperationStatus
+     values are: "notStarted", "running", "failed", "succeeded", "canceled", and "skipped".
+    :vartype status: str or
+     ~azure.ai.documentintelligence.models.DocumentIntelligenceOperationStatus
     :ivar percent_completed: Operation progress (0-100).
     :vartype percent_completed: int
     :ivar created_date_time: Date and time (UTC) when the operation was created. Required.
@@ -1429,7 +1327,7 @@ class DocumentClassifierBuildOperationDetails(
     :ivar tags: List of key-value tag attributes associated with the document model.
     :vartype tags: dict[str, str]
     :ivar error: Encountered error.
-    :vartype error: ~azure.ai.documentintelligence.models.Error
+    :vartype error: ~azure.ai.documentintelligence.models.DocumentIntelligenceError
     :ivar result: Operation result upon success.
     :vartype result: ~azure.ai.documentintelligence.models.DocumentClassifierDetails
     :ivar kind: Type of operation. Required. Build a new custom classifier model.
@@ -1446,14 +1344,14 @@ def __init__(
         self,
         *,
         operation_id: str,
-        status: Union[str, "_models.OperationStatus"],
+        status: Union[str, "_models.DocumentIntelligenceOperationStatus"],
         created_date_time: datetime.datetime,
         last_updated_date_time: datetime.datetime,
         resource_location: str,
         percent_completed: Optional[int] = None,
         api_version: Optional[str] = None,
         tags: Optional[Dict[str, str]] = None,
-        error: Optional["_models.Error"] = None,
+        error: Optional["_models.DocumentIntelligenceError"] = None,
         result: Optional["_models.DocumentClassifierDetails"] = None,
     ) -> None: ...
 
@@ -1464,21 +1362,22 @@ def __init__(self, mapping: Mapping[str, Any]) -> None:
         :type mapping: Mapping[str, Any]
         """
 
-    def __init__(self, *args: Any, **kwargs: Any) -> None:  # pylint: disable=useless-super-delegation
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
         super().__init__(*args, kind=OperationKind.DOCUMENT_CLASSIFIER_BUILD, **kwargs)
 
 
 class DocumentClassifierCopyToOperationDetails(
-    OperationDetails, discriminator="documentClassifierCopyTo"
-):  # pylint: disable=too-many-instance-attributes
+    DocumentIntelligenceOperationDetails, discriminator="documentClassifierCopyTo"
+):
     """Get Operation response object.
 
 
     :ivar operation_id: Operation ID. Required.
     :vartype operation_id: str
     :ivar status: Operation status.  notStarted, running, completed, or failed. Required. Known
-     values are: "notStarted", "running", "failed", "succeeded", "completed", and "canceled".
-    :vartype status: str or ~azure.ai.documentintelligence.models.OperationStatus
+     values are: "notStarted", "running", "failed", "succeeded", "canceled", and "skipped".
+    :vartype status: str or
+     ~azure.ai.documentintelligence.models.DocumentIntelligenceOperationStatus
     :ivar percent_completed: Operation progress (0-100).
     :vartype percent_completed: int
     :ivar created_date_time: Date and time (UTC) when the operation was created. Required.
@@ -1492,7 +1391,7 @@ class DocumentClassifierCopyToOperationDetails(
     :ivar tags: List of key-value tag attributes associated with the document model.
     :vartype tags: dict[str, str]
     :ivar error: Encountered error.
-    :vartype error: ~azure.ai.documentintelligence.models.Error
+    :vartype error: ~azure.ai.documentintelligence.models.DocumentIntelligenceError
     :ivar result: Operation result upon success.
     :vartype result: ~azure.ai.documentintelligence.models.DocumentClassifierDetails
     :ivar kind: Type of operation. Required. Copy an existing document classifier to potentially a
@@ -1513,14 +1412,14 @@ def __init__(
         self,
         *,
         operation_id: str,
-        status: Union[str, "_models.OperationStatus"],
+        status: Union[str, "_models.DocumentIntelligenceOperationStatus"],
         created_date_time: datetime.datetime,
         last_updated_date_time: datetime.datetime,
         resource_location: str,
         percent_completed: Optional[int] = None,
         api_version: Optional[str] = None,
         tags: Optional[Dict[str, str]] = None,
-        error: Optional["_models.Error"] = None,
+        error: Optional["_models.DocumentIntelligenceError"] = None,
         result: Optional["_models.DocumentClassifierDetails"] = None,
     ) -> None: ...
 
@@ -1531,13 +1430,15 @@ def __init__(self, mapping: Mapping[str, Any]) -> None:
         :type mapping: Mapping[str, Any]
         """
 
-    def __init__(self, *args: Any, **kwargs: Any) -> None:  # pylint: disable=useless-super-delegation
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
         super().__init__(*args, kind=OperationKind.DOCUMENT_CLASSIFIER_COPY_TO, **kwargs)
 
 
 class DocumentClassifierDetails(_model_base.Model):
     """Document classifier info.
 
+    Readonly variables are only populated by the server, and will be ignored when sending a request.
+
 
     :ivar classifier_id: Unique document classifier name. Required.
     :vartype classifier_id: str
@@ -1548,6 +1449,8 @@ class DocumentClassifierDetails(_model_base.Model):
     :vartype created_date_time: ~datetime.datetime
     :ivar expiration_date_time: Date and time (UTC) when the document classifier will expire.
     :vartype expiration_date_time: ~datetime.datetime
+    :ivar modified_date_time: Date and time (UTC) when the document model was last modified.
+    :vartype modified_date_time: ~datetime.datetime
     :ivar api_version: API version used to create this document classifier. Required.
     :vartype api_version: str
     :ivar base_classifier_id: Base classifierId on top of which the classifier was trained.
@@ -1556,7 +1459,7 @@ class DocumentClassifierDetails(_model_base.Model):
     :vartype doc_types: dict[str,
      ~azure.ai.documentintelligence.models.ClassifierDocumentTypeDetails]
     :ivar warnings: List of warnings encountered while building the classifier.
-    :vartype warnings: list[~azure.ai.documentintelligence.models.Warning]
+    :vartype warnings: list[~azure.ai.documentintelligence.models.DocumentIntelligenceWarning]
     """
 
     classifier_id: str = rest_field(name="classifierId", visibility=["read", "create"])
@@ -1567,13 +1470,17 @@ class DocumentClassifierDetails(_model_base.Model):
     """Date and time (UTC) when the document classifier was created. Required."""
     expiration_date_time: Optional[datetime.datetime] = rest_field(name="expirationDateTime", format="rfc3339")
     """Date and time (UTC) when the document classifier will expire."""
+    modified_date_time: Optional[datetime.datetime] = rest_field(
+        name="modifiedDateTime", visibility=["read"], format="rfc3339"
+    )
+    """Date and time (UTC) when the document model was last modified."""
     api_version: str = rest_field(name="apiVersion")
     """API version used to create this document classifier. Required."""
     base_classifier_id: Optional[str] = rest_field(name="baseClassifierId")
     """Base classifierId on top of which the classifier was trained."""
     doc_types: Dict[str, "_models.ClassifierDocumentTypeDetails"] = rest_field(name="docTypes")
     """List of document types to classify against. Required."""
-    warnings: Optional[List["_models.Warning"]] = rest_field()
+    warnings: Optional[List["_models.DocumentIntelligenceWarning"]] = rest_field()
     """List of warnings encountered while building the classifier."""
 
     @overload
@@ -1587,7 +1494,7 @@ def __init__(
         description: Optional[str] = None,
         expiration_date_time: Optional[datetime.datetime] = None,
         base_classifier_id: Optional[str] = None,
-        warnings: Optional[List["_models.Warning"]] = None,
+        warnings: Optional[List["_models.DocumentIntelligenceWarning"]] = None,
     ) -> None: ...
 
     @overload
@@ -1597,11 +1504,11 @@ def __init__(self, mapping: Mapping[str, Any]) -> None:
         :type mapping: Mapping[str, Any]
         """
 
-    def __init__(self, *args: Any, **kwargs: Any) -> None:  # pylint: disable=useless-super-delegation
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
         super().__init__(*args, **kwargs)
 
 
-class DocumentField(_model_base.Model):  # pylint: disable=too-many-instance-attributes
+class DocumentField(_model_base.Model):
     """An object representing the content and location of a field value.
 
 
@@ -1729,7 +1636,7 @@ def __init__(self, mapping: Mapping[str, Any]) -> None:
         :type mapping: Mapping[str, Any]
         """
 
-    def __init__(self, *args: Any, **kwargs: Any) -> None:  # pylint: disable=useless-super-delegation
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
         super().__init__(*args, **kwargs)
 
 
@@ -1745,8 +1652,8 @@ class DocumentFieldSchema(_model_base.Model):
     :vartype description: str
     :ivar example: Example field content.
     :vartype example: str
-    :ivar items_property: Field type schema of each array element.
-    :vartype items_property: ~azure.ai.documentintelligence.models.DocumentFieldSchema
+    :ivar items_schema: Field type schema of each array element.
+    :vartype items_schema: ~azure.ai.documentintelligence.models.DocumentFieldSchema
     :ivar properties: Named sub-fields of the object field.
     :vartype properties: dict[str, ~azure.ai.documentintelligence.models.DocumentFieldSchema]
     """
@@ -1760,7 +1667,7 @@ class DocumentFieldSchema(_model_base.Model):
     """Field description."""
     example: Optional[str] = rest_field()
     """Example field content."""
-    items_property: Optional["_models.DocumentFieldSchema"] = rest_field(name="items")
+    items_schema: Optional["_models.DocumentFieldSchema"] = rest_field(name="items")
     """Field type schema of each array element."""
     properties: Optional[Dict[str, "_models.DocumentFieldSchema"]] = rest_field()
     """Named sub-fields of the object field."""
@@ -1772,7 +1679,7 @@ def __init__(
         type: Union[str, "_models.DocumentFieldType"],
         description: Optional[str] = None,
         example: Optional[str] = None,
-        items_property: Optional["_models.DocumentFieldSchema"] = None,
+        items_schema: Optional["_models.DocumentFieldSchema"] = None,
         properties: Optional[Dict[str, "_models.DocumentFieldSchema"]] = None,
     ) -> None: ...
 
@@ -1783,7 +1690,7 @@ def __init__(self, mapping: Mapping[str, Any]) -> None:
         :type mapping: Mapping[str, Any]
         """
 
-    def __init__(self, *args: Any, **kwargs: Any) -> None:  # pylint: disable=useless-super-delegation
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
         super().__init__(*args, **kwargs)
 
 
@@ -1837,7 +1744,7 @@ def __init__(self, mapping: Mapping[str, Any]) -> None:
         :type mapping: Mapping[str, Any]
         """
 
-    def __init__(self, *args: Any, **kwargs: Any) -> None:  # pylint: disable=useless-super-delegation
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
         super().__init__(*args, **kwargs)
 
 
@@ -1881,7 +1788,7 @@ def __init__(self, mapping: Mapping[str, Any]) -> None:
         :type mapping: Mapping[str, Any]
         """
 
-    def __init__(self, *args: Any, **kwargs: Any) -> None:  # pylint: disable=useless-super-delegation
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
         super().__init__(*args, **kwargs)
 
 
@@ -1936,24 +1843,211 @@ def __init__(self, mapping: Mapping[str, Any]) -> None:
         :type mapping: Mapping[str, Any]
         """
 
-    def __init__(self, *args: Any, **kwargs: Any) -> None:  # pylint: disable=useless-super-delegation
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
         super().__init__(*args, **kwargs)
 
 
-class DocumentKeyValueElement(_model_base.Model):
-    """An object representing the field key or value in a key-value pair.
+class DocumentIntelligenceError(_model_base.Model):
+    """The error object.
 
 
-    :ivar content: Concatenated content of the key-value element in reading order. Required.
-    :vartype content: str
-    :ivar bounding_regions: Bounding regions covering the key-value element.
-    :vartype bounding_regions: list[~azure.ai.documentintelligence.models.BoundingRegion]
-    :ivar spans: Location of the key-value element in the reading order concatenated content.
-     Required.
-    :vartype spans: list[~azure.ai.documentintelligence.models.DocumentSpan]
+    :ivar code: One of a server-defined set of error codes. Required.
+    :vartype code: str
+    :ivar message: A human-readable representation of the error. Required.
+    :vartype message: str
+    :ivar target: The target of the error.
+    :vartype target: str
+    :ivar details: An array of details about specific errors that led to this reported error.
+    :vartype details: list[~azure.ai.documentintelligence.models.DocumentIntelligenceError]
+    :ivar innererror: An object containing more specific information than the current object about
+     the error.
+    :vartype innererror: ~azure.ai.documentintelligence.models.DocumentIntelligenceInnerError
     """
 
-    content: str = rest_field()
+    code: str = rest_field()
+    """One of a server-defined set of error codes. Required."""
+    message: str = rest_field()
+    """A human-readable representation of the error. Required."""
+    target: Optional[str] = rest_field()
+    """The target of the error."""
+    details: Optional[List["_models.DocumentIntelligenceError"]] = rest_field()
+    """An array of details about specific errors that led to this reported error."""
+    innererror: Optional["_models.DocumentIntelligenceInnerError"] = rest_field()
+    """An object containing more specific information than the current object about the error."""
+
+    @overload
+    def __init__(
+        self,
+        *,
+        code: str,
+        message: str,
+        target: Optional[str] = None,
+        details: Optional[List["_models.DocumentIntelligenceError"]] = None,
+        innererror: Optional["_models.DocumentIntelligenceInnerError"] = None,
+    ) -> None: ...
+
+    @overload
+    def __init__(self, mapping: Mapping[str, Any]) -> None:
+        """
+        :param mapping: raw JSON to initialize the model.
+        :type mapping: Mapping[str, Any]
+        """
+
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
+        super().__init__(*args, **kwargs)
+
+
+class DocumentIntelligenceErrorResponse(_model_base.Model):
+    """Error response object.
+
+    All required parameters must be populated in order to send to server.
+
+    :ivar error: Error info. Required.
+    :vartype error: ~azure.ai.documentintelligence.models.DocumentIntelligenceError
+    """
+
+    error: "_models.DocumentIntelligenceError" = rest_field()
+    """Error info. Required."""
+
+    @overload
+    def __init__(
+        self,
+        *,
+        error: "_models.DocumentIntelligenceError",
+    ) -> None: ...
+
+    @overload
+    def __init__(self, mapping: Mapping[str, Any]) -> None:
+        """
+        :param mapping: raw JSON to initialize the model.
+        :type mapping: Mapping[str, Any]
+        """
+
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
+        super().__init__(*args, **kwargs)
+
+
+class DocumentIntelligenceInnerError(_model_base.Model):
+    """An object containing more specific information about the error.
+
+    :ivar code: One of a server-defined set of error codes.
+    :vartype code: str
+    :ivar message: A human-readable representation of the error.
+    :vartype message: str
+    :ivar innererror: Inner error.
+    :vartype innererror: ~azure.ai.documentintelligence.models.DocumentIntelligenceInnerError
+    """
+
+    code: Optional[str] = rest_field()
+    """One of a server-defined set of error codes."""
+    message: Optional[str] = rest_field()
+    """A human-readable representation of the error."""
+    innererror: Optional["_models.DocumentIntelligenceInnerError"] = rest_field()
+    """Inner error."""
+
+    @overload
+    def __init__(
+        self,
+        *,
+        code: Optional[str] = None,
+        message: Optional[str] = None,
+        innererror: Optional["_models.DocumentIntelligenceInnerError"] = None,
+    ) -> None: ...
+
+    @overload
+    def __init__(self, mapping: Mapping[str, Any]) -> None:
+        """
+        :param mapping: raw JSON to initialize the model.
+        :type mapping: Mapping[str, Any]
+        """
+
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
+        super().__init__(*args, **kwargs)
+
+
+class DocumentIntelligenceResourceDetails(_model_base.Model):
+    """General information regarding the current resource.
+
+
+    :ivar custom_document_models: Details regarding custom document models. Required.
+    :vartype custom_document_models:
+     ~azure.ai.documentintelligence.models.CustomDocumentModelsDetails
+    """
+
+    custom_document_models: "_models.CustomDocumentModelsDetails" = rest_field(name="customDocumentModels")
+    """Details regarding custom document models. Required."""
+
+    @overload
+    def __init__(
+        self,
+        *,
+        custom_document_models: "_models.CustomDocumentModelsDetails",
+    ) -> None: ...
+
+    @overload
+    def __init__(self, mapping: Mapping[str, Any]) -> None:
+        """
+        :param mapping: raw JSON to initialize the model.
+        :type mapping: Mapping[str, Any]
+        """
+
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
+        super().__init__(*args, **kwargs)
+
+
+class DocumentIntelligenceWarning(_model_base.Model):
+    """The error object.
+
+
+    :ivar code: One of a server-defined set of warning codes. Required.
+    :vartype code: str
+    :ivar message: A human-readable representation of the warning. Required.
+    :vartype message: str
+    :ivar target: The target of the error.
+    :vartype target: str
+    """
+
+    code: str = rest_field()
+    """One of a server-defined set of warning codes. Required."""
+    message: str = rest_field()
+    """A human-readable representation of the warning. Required."""
+    target: Optional[str] = rest_field()
+    """The target of the error."""
+
+    @overload
+    def __init__(
+        self,
+        *,
+        code: str,
+        message: str,
+        target: Optional[str] = None,
+    ) -> None: ...
+
+    @overload
+    def __init__(self, mapping: Mapping[str, Any]) -> None:
+        """
+        :param mapping: raw JSON to initialize the model.
+        :type mapping: Mapping[str, Any]
+        """
+
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
+        super().__init__(*args, **kwargs)
+
+
+class DocumentKeyValueElement(_model_base.Model):
+    """An object representing the field key or value in a key-value pair.
+
+
+    :ivar content: Concatenated content of the key-value element in reading order. Required.
+    :vartype content: str
+    :ivar bounding_regions: Bounding regions covering the key-value element.
+    :vartype bounding_regions: list[~azure.ai.documentintelligence.models.BoundingRegion]
+    :ivar spans: Location of the key-value element in the reading order concatenated content.
+     Required.
+    :vartype spans: list[~azure.ai.documentintelligence.models.DocumentSpan]
+    """
+
+    content: str = rest_field()
     """Concatenated content of the key-value element in reading order. Required."""
     bounding_regions: Optional[List["_models.BoundingRegion"]] = rest_field(name="boundingRegions")
     """Bounding regions covering the key-value element."""
@@ -1976,7 +2070,7 @@ def __init__(self, mapping: Mapping[str, Any]) -> None:
         :type mapping: Mapping[str, Any]
         """
 
-    def __init__(self, *args: Any, **kwargs: Any) -> None:  # pylint: disable=useless-super-delegation
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
         super().__init__(*args, **kwargs)
 
 
@@ -2016,7 +2110,7 @@ def __init__(self, mapping: Mapping[str, Any]) -> None:
         :type mapping: Mapping[str, Any]
         """
 
-    def __init__(self, *args: Any, **kwargs: Any) -> None:  # pylint: disable=useless-super-delegation
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
         super().__init__(*args, **kwargs)
 
 
@@ -2059,7 +2153,7 @@ def __init__(self, mapping: Mapping[str, Any]) -> None:
         :type mapping: Mapping[str, Any]
         """
 
-    def __init__(self, *args: Any, **kwargs: Any) -> None:  # pylint: disable=useless-super-delegation
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
         super().__init__(*args, **kwargs)
 
 
@@ -2105,21 +2199,20 @@ def __init__(self, mapping: Mapping[str, Any]) -> None:
         :type mapping: Mapping[str, Any]
         """
 
-    def __init__(self, *args: Any, **kwargs: Any) -> None:  # pylint: disable=useless-super-delegation
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
         super().__init__(*args, **kwargs)
 
 
-class DocumentModelBuildOperationDetails(
-    OperationDetails, discriminator="documentModelBuild"
-):  # pylint: disable=too-many-instance-attributes
+class DocumentModelBuildOperationDetails(DocumentIntelligenceOperationDetails, discriminator="documentModelBuild"):
     """Get Operation response object.
 
 
     :ivar operation_id: Operation ID. Required.
     :vartype operation_id: str
     :ivar status: Operation status.  notStarted, running, completed, or failed. Required. Known
-     values are: "notStarted", "running", "failed", "succeeded", "completed", and "canceled".
-    :vartype status: str or ~azure.ai.documentintelligence.models.OperationStatus
+     values are: "notStarted", "running", "failed", "succeeded", "canceled", and "skipped".
+    :vartype status: str or
+     ~azure.ai.documentintelligence.models.DocumentIntelligenceOperationStatus
     :ivar percent_completed: Operation progress (0-100).
     :vartype percent_completed: int
     :ivar created_date_time: Date and time (UTC) when the operation was created. Required.
@@ -2133,7 +2226,7 @@ class DocumentModelBuildOperationDetails(
     :ivar tags: List of key-value tag attributes associated with the document model.
     :vartype tags: dict[str, str]
     :ivar error: Encountered error.
-    :vartype error: ~azure.ai.documentintelligence.models.Error
+    :vartype error: ~azure.ai.documentintelligence.models.DocumentIntelligenceError
     :ivar result: Operation result upon success.
     :vartype result: ~azure.ai.documentintelligence.models.DocumentModelDetails
     :ivar kind: Type of operation. Required. Build a new custom document model.
@@ -2150,14 +2243,14 @@ def __init__(
         self,
         *,
         operation_id: str,
-        status: Union[str, "_models.OperationStatus"],
+        status: Union[str, "_models.DocumentIntelligenceOperationStatus"],
         created_date_time: datetime.datetime,
         last_updated_date_time: datetime.datetime,
         resource_location: str,
         percent_completed: Optional[int] = None,
         api_version: Optional[str] = None,
         tags: Optional[Dict[str, str]] = None,
-        error: Optional["_models.Error"] = None,
+        error: Optional["_models.DocumentIntelligenceError"] = None,
         result: Optional["_models.DocumentModelDetails"] = None,
     ) -> None: ...
 
@@ -2168,21 +2261,20 @@ def __init__(self, mapping: Mapping[str, Any]) -> None:
         :type mapping: Mapping[str, Any]
         """
 
-    def __init__(self, *args: Any, **kwargs: Any) -> None:  # pylint: disable=useless-super-delegation
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
         super().__init__(*args, kind=OperationKind.DOCUMENT_MODEL_BUILD, **kwargs)
 
 
-class DocumentModelComposeOperationDetails(
-    OperationDetails, discriminator="documentModelCompose"
-):  # pylint: disable=too-many-instance-attributes
+class DocumentModelComposeOperationDetails(DocumentIntelligenceOperationDetails, discriminator="documentModelCompose"):
     """Get Operation response object.
 
 
     :ivar operation_id: Operation ID. Required.
     :vartype operation_id: str
     :ivar status: Operation status.  notStarted, running, completed, or failed. Required. Known
-     values are: "notStarted", "running", "failed", "succeeded", "completed", and "canceled".
-    :vartype status: str or ~azure.ai.documentintelligence.models.OperationStatus
+     values are: "notStarted", "running", "failed", "succeeded", "canceled", and "skipped".
+    :vartype status: str or
+     ~azure.ai.documentintelligence.models.DocumentIntelligenceOperationStatus
     :ivar percent_completed: Operation progress (0-100).
     :vartype percent_completed: int
     :ivar created_date_time: Date and time (UTC) when the operation was created. Required.
@@ -2196,7 +2288,7 @@ class DocumentModelComposeOperationDetails(
     :ivar tags: List of key-value tag attributes associated with the document model.
     :vartype tags: dict[str, str]
     :ivar error: Encountered error.
-    :vartype error: ~azure.ai.documentintelligence.models.Error
+    :vartype error: ~azure.ai.documentintelligence.models.DocumentIntelligenceError
     :ivar result: Operation result upon success.
     :vartype result: ~azure.ai.documentintelligence.models.DocumentModelDetails
     :ivar kind: Type of operation. Required. Compose a new custom document model from existing
@@ -2214,14 +2306,14 @@ def __init__(
         self,
         *,
         operation_id: str,
-        status: Union[str, "_models.OperationStatus"],
+        status: Union[str, "_models.DocumentIntelligenceOperationStatus"],
         created_date_time: datetime.datetime,
         last_updated_date_time: datetime.datetime,
         resource_location: str,
         percent_completed: Optional[int] = None,
         api_version: Optional[str] = None,
         tags: Optional[Dict[str, str]] = None,
-        error: Optional["_models.Error"] = None,
+        error: Optional["_models.DocumentIntelligenceError"] = None,
         result: Optional["_models.DocumentModelDetails"] = None,
     ) -> None: ...
 
@@ -2232,21 +2324,20 @@ def __init__(self, mapping: Mapping[str, Any]) -> None:
         :type mapping: Mapping[str, Any]
         """
 
-    def __init__(self, *args: Any, **kwargs: Any) -> None:  # pylint: disable=useless-super-delegation
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
         super().__init__(*args, kind=OperationKind.DOCUMENT_MODEL_COMPOSE, **kwargs)
 
 
-class DocumentModelCopyToOperationDetails(
-    OperationDetails, discriminator="documentModelCopyTo"
-):  # pylint: disable=too-many-instance-attributes
+class DocumentModelCopyToOperationDetails(DocumentIntelligenceOperationDetails, discriminator="documentModelCopyTo"):
     """Get Operation response object.
 
 
     :ivar operation_id: Operation ID. Required.
     :vartype operation_id: str
     :ivar status: Operation status.  notStarted, running, completed, or failed. Required. Known
-     values are: "notStarted", "running", "failed", "succeeded", "completed", and "canceled".
-    :vartype status: str or ~azure.ai.documentintelligence.models.OperationStatus
+     values are: "notStarted", "running", "failed", "succeeded", "canceled", and "skipped".
+    :vartype status: str or
+     ~azure.ai.documentintelligence.models.DocumentIntelligenceOperationStatus
     :ivar percent_completed: Operation progress (0-100).
     :vartype percent_completed: int
     :ivar created_date_time: Date and time (UTC) when the operation was created. Required.
@@ -2260,7 +2351,7 @@ class DocumentModelCopyToOperationDetails(
     :ivar tags: List of key-value tag attributes associated with the document model.
     :vartype tags: dict[str, str]
     :ivar error: Encountered error.
-    :vartype error: ~azure.ai.documentintelligence.models.Error
+    :vartype error: ~azure.ai.documentintelligence.models.DocumentIntelligenceError
     :ivar result: Operation result upon success.
     :vartype result: ~azure.ai.documentintelligence.models.DocumentModelDetails
     :ivar kind: Type of operation. Required. Copy an existing document model to potentially a
@@ -2281,14 +2372,14 @@ def __init__(
         self,
         *,
         operation_id: str,
-        status: Union[str, "_models.OperationStatus"],
+        status: Union[str, "_models.DocumentIntelligenceOperationStatus"],
         created_date_time: datetime.datetime,
         last_updated_date_time: datetime.datetime,
         resource_location: str,
         percent_completed: Optional[int] = None,
         api_version: Optional[str] = None,
         tags: Optional[Dict[str, str]] = None,
-        error: Optional["_models.Error"] = None,
+        error: Optional["_models.DocumentIntelligenceError"] = None,
         result: Optional["_models.DocumentModelDetails"] = None,
     ) -> None: ...
 
@@ -2299,11 +2390,11 @@ def __init__(self, mapping: Mapping[str, Any]) -> None:
         :type mapping: Mapping[str, Any]
         """
 
-    def __init__(self, *args: Any, **kwargs: Any) -> None:  # pylint: disable=useless-super-delegation
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
         super().__init__(*args, kind=OperationKind.DOCUMENT_MODEL_COPY_TO, **kwargs)
 
 
-class DocumentModelDetails(_model_base.Model):  # pylint: disable=too-many-instance-attributes
+class DocumentModelDetails(_model_base.Model):
     """Document model info.
 
     Readonly variables are only populated by the server, and will be ignored when sending a request.
@@ -2317,12 +2408,13 @@ class DocumentModelDetails(_model_base.Model):  # pylint: disable=too-many-insta
     :vartype created_date_time: ~datetime.datetime
     :ivar expiration_date_time: Date and time (UTC) when the document model will expire.
     :vartype expiration_date_time: ~datetime.datetime
+    :ivar modified_date_time: Date and time (UTC) when the document model was last modified.
+    :vartype modified_date_time: ~datetime.datetime
     :ivar api_version: API version used to create this document model.
     :vartype api_version: str
     :ivar tags: List of key-value tag attributes associated with the document model.
     :vartype tags: dict[str, str]
-    :ivar build_mode: Custom document model build mode. Known values are: "template", "neural", and
-     "generative".
+    :ivar build_mode: Custom document model build mode. Known values are: "template" and "neural".
     :vartype build_mode: str or ~azure.ai.documentintelligence.models.DocumentBuildMode
     :ivar azure_blob_source: Azure Blob Storage location containing the training data.  Either
      azureBlobSource or azureBlobFileListSource must be specified.
@@ -2341,7 +2433,7 @@ class DocumentModelDetails(_model_base.Model):  # pylint: disable=too-many-insta
     :ivar doc_types: Supported document types.
     :vartype doc_types: dict[str, ~azure.ai.documentintelligence.models.DocumentTypeDetails]
     :ivar warnings: List of warnings encountered while building the model.
-    :vartype warnings: list[~azure.ai.documentintelligence.models.Warning]
+    :vartype warnings: list[~azure.ai.documentintelligence.models.DocumentIntelligenceWarning]
     :ivar training_hours: Number of V100-equivalent GPU hours consumed for model training.
     :vartype training_hours: float
     """
@@ -2356,13 +2448,16 @@ class DocumentModelDetails(_model_base.Model):  # pylint: disable=too-many-insta
         name="expirationDateTime", visibility=["read"], format="rfc3339"
     )
     """Date and time (UTC) when the document model will expire."""
+    modified_date_time: Optional[datetime.datetime] = rest_field(
+        name="modifiedDateTime", visibility=["read"], format="rfc3339"
+    )
+    """Date and time (UTC) when the document model was last modified."""
     api_version: Optional[str] = rest_field(name="apiVersion", visibility=["read"])
     """API version used to create this document model."""
     tags: Optional[Dict[str, str]] = rest_field()
     """List of key-value tag attributes associated with the document model."""
     build_mode: Optional[Union[str, "_models.DocumentBuildMode"]] = rest_field(name="buildMode", visibility=["read"])
-    """Custom document model build mode. Known values are: \"template\", \"neural\", and
-     \"generative\"."""
+    """Custom document model build mode. Known values are: \"template\" and \"neural\"."""
     azure_blob_source: Optional["_models.AzureBlobContentSource"] = rest_field(
         name="azureBlobSource", visibility=["read"]
     )
@@ -2380,7 +2475,7 @@ class DocumentModelDetails(_model_base.Model):  # pylint: disable=too-many-insta
      \"perPage\"."""
     doc_types: Optional[Dict[str, "_models.DocumentTypeDetails"]] = rest_field(name="docTypes", visibility=["read"])
     """Supported document types."""
-    warnings: Optional[List["_models.Warning"]] = rest_field(visibility=["read"])
+    warnings: Optional[List["_models.DocumentIntelligenceWarning"]] = rest_field(visibility=["read"])
     """List of warnings encountered while building the model."""
     training_hours: Optional[float] = rest_field(name="trainingHours", visibility=["read"])
     """Number of V100-equivalent GPU hours consumed for model training."""
@@ -2403,11 +2498,11 @@ def __init__(self, mapping: Mapping[str, Any]) -> None:
         :type mapping: Mapping[str, Any]
         """
 
-    def __init__(self, *args: Any, **kwargs: Any) -> None:  # pylint: disable=useless-super-delegation
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
         super().__init__(*args, **kwargs)
 
 
-class DocumentPage(_model_base.Model):  # pylint: disable=too-many-instance-attributes
+class DocumentPage(_model_base.Model):
     """Content and layout elements extracted from a page from the input.
 
 
@@ -2488,7 +2583,7 @@ def __init__(self, mapping: Mapping[str, Any]) -> None:
         :type mapping: Mapping[str, Any]
         """
 
-    def __init__(self, *args: Any, **kwargs: Any) -> None:  # pylint: disable=useless-super-delegation
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
         super().__init__(*args, **kwargs)
 
 
@@ -2535,7 +2630,7 @@ def __init__(self, mapping: Mapping[str, Any]) -> None:
         :type mapping: Mapping[str, Any]
         """
 
-    def __init__(self, *args: Any, **kwargs: Any) -> None:  # pylint: disable=useless-super-delegation
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
         super().__init__(*args, **kwargs)
 
 
@@ -2569,7 +2664,7 @@ def __init__(self, mapping: Mapping[str, Any]) -> None:
         :type mapping: Mapping[str, Any]
         """
 
-    def __init__(self, *args: Any, **kwargs: Any) -> None:  # pylint: disable=useless-super-delegation
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
         super().__init__(*args, **kwargs)
 
 
@@ -2621,7 +2716,7 @@ def __init__(self, mapping: Mapping[str, Any]) -> None:
         :type mapping: Mapping[str, Any]
         """
 
-    def __init__(self, *args: Any, **kwargs: Any) -> None:  # pylint: disable=useless-super-delegation
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
         super().__init__(*args, **kwargs)
 
 
@@ -2656,7 +2751,7 @@ def __init__(self, mapping: Mapping[str, Any]) -> None:
         :type mapping: Mapping[str, Any]
         """
 
-    def __init__(self, *args: Any, **kwargs: Any) -> None:  # pylint: disable=useless-super-delegation
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
         super().__init__(*args, **kwargs)
 
 
@@ -2671,9 +2766,9 @@ class DocumentStyle(_model_base.Model):
      fallback fonts following CSS convention (ex. 'Arial, sans-serif').
     :vartype similar_font_family: str
     :ivar font_style: Font style. Known values are: "normal" and "italic".
-    :vartype font_style: str or ~azure.ai.documentintelligence.models.FontStyle
+    :vartype font_style: str or ~azure.ai.documentintelligence.models.DocumentFontStyle
     :ivar font_weight: Font weight. Known values are: "normal" and "bold".
-    :vartype font_weight: str or ~azure.ai.documentintelligence.models.FontWeight
+    :vartype font_weight: str or ~azure.ai.documentintelligence.models.DocumentFontWeight
     :ivar color: Foreground color in #rrggbb hexadecimal format.
     :vartype color: str
     :ivar background_color: Background color in #rrggbb hexadecimal format..
@@ -2690,9 +2785,9 @@ class DocumentStyle(_model_base.Model):
     similar_font_family: Optional[str] = rest_field(name="similarFontFamily")
     """Visually most similar font from among the set of supported font families, with
      fallback fonts following CSS convention (ex. 'Arial, sans-serif')."""
-    font_style: Optional[Union[str, "_models.FontStyle"]] = rest_field(name="fontStyle")
+    font_style: Optional[Union[str, "_models.DocumentFontStyle"]] = rest_field(name="fontStyle")
     """Font style. Known values are: \"normal\" and \"italic\"."""
-    font_weight: Optional[Union[str, "_models.FontWeight"]] = rest_field(name="fontWeight")
+    font_weight: Optional[Union[str, "_models.DocumentFontWeight"]] = rest_field(name="fontWeight")
     """Font weight. Known values are: \"normal\" and \"bold\"."""
     color: Optional[str] = rest_field()
     """Foreground color in #rrggbb hexadecimal format."""
@@ -2711,8 +2806,8 @@ def __init__(
         confidence: float,
         is_handwritten: Optional[bool] = None,
         similar_font_family: Optional[str] = None,
-        font_style: Optional[Union[str, "_models.FontStyle"]] = None,
-        font_weight: Optional[Union[str, "_models.FontWeight"]] = None,
+        font_style: Optional[Union[str, "_models.DocumentFontStyle"]] = None,
+        font_weight: Optional[Union[str, "_models.DocumentFontWeight"]] = None,
         color: Optional[str] = None,
         background_color: Optional[str] = None,
     ) -> None: ...
@@ -2724,7 +2819,7 @@ def __init__(self, mapping: Mapping[str, Any]) -> None:
         :type mapping: Mapping[str, Any]
         """
 
-    def __init__(self, *args: Any, **kwargs: Any) -> None:  # pylint: disable=useless-super-delegation
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
         super().__init__(*args, **kwargs)
 
 
@@ -2783,7 +2878,7 @@ def __init__(self, mapping: Mapping[str, Any]) -> None:
         :type mapping: Mapping[str, Any]
         """
 
-    def __init__(self, *args: Any, **kwargs: Any) -> None:  # pylint: disable=useless-super-delegation
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
         super().__init__(*args, **kwargs)
 
 
@@ -2854,7 +2949,7 @@ def __init__(self, mapping: Mapping[str, Any]) -> None:
         :type mapping: Mapping[str, Any]
         """
 
-    def __init__(self, *args: Any, **kwargs: Any) -> None:  # pylint: disable=useless-super-delegation
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
         super().__init__(*args, **kwargs)
 
 
@@ -2863,8 +2958,7 @@ class DocumentTypeDetails(_model_base.Model):
 
     :ivar description: Document model description.
     :vartype description: str
-    :ivar build_mode: Custom document model build mode. Known values are: "template", "neural", and
-     "generative".
+    :ivar build_mode: Custom document model build mode. Known values are: "template" and "neural".
     :vartype build_mode: str or ~azure.ai.documentintelligence.models.DocumentBuildMode
     :ivar field_schema: Description of the document semantic schema using a JSON Schema style
      syntax.
@@ -2887,8 +2981,7 @@ class DocumentTypeDetails(_model_base.Model):
     description: Optional[str] = rest_field()
     """Document model description."""
     build_mode: Optional[Union[str, "_models.DocumentBuildMode"]] = rest_field(name="buildMode")
-    """Custom document model build mode. Known values are: \"template\", \"neural\", and
-     \"generative\"."""
+    """Custom document model build mode. Known values are: \"template\" and \"neural\"."""
     field_schema: Optional[Dict[str, "_models.DocumentFieldSchema"]] = rest_field(name="fieldSchema")
     """Description of the document semantic schema using a JSON Schema style syntax."""
     field_confidence: Optional[Dict[str, float]] = rest_field(name="fieldConfidence")
@@ -2926,7 +3019,7 @@ def __init__(self, mapping: Mapping[str, Any]) -> None:
         :type mapping: Mapping[str, Any]
         """
 
-    def __init__(self, *args: Any, **kwargs: Any) -> None:  # pylint: disable=useless-super-delegation
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
         super().__init__(*args, **kwargs)
 
 
@@ -2978,183 +3071,56 @@ def __init__(self, mapping: Mapping[str, Any]) -> None:
         :type mapping: Mapping[str, Any]
         """
 
-    def __init__(self, *args: Any, **kwargs: Any) -> None:  # pylint: disable=useless-super-delegation
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
         super().__init__(*args, **kwargs)
 
 
-class Error(_model_base.Model):
-    """The error object.
-
-
-    :ivar code: One of a server-defined set of error codes. Required.
-    :vartype code: str
-    :ivar message: A human-readable representation of the error. Required.
-    :vartype message: str
-    :ivar target: The target of the error.
-    :vartype target: str
-    :ivar details: An array of details about specific errors that led to this reported error.
-    :vartype details: list[~azure.ai.documentintelligence.models.Error]
-    :ivar innererror: An object containing more specific information than the current object about
-     the error.
-    :vartype innererror: ~azure.ai.documentintelligence.models.InnerError
-    """
-
-    code: str = rest_field()
-    """One of a server-defined set of error codes. Required."""
-    message: str = rest_field()
-    """A human-readable representation of the error. Required."""
-    target: Optional[str] = rest_field()
-    """The target of the error."""
-    details: Optional[List["_models.Error"]] = rest_field()
-    """An array of details about specific errors that led to this reported error."""
-    innererror: Optional["_models.InnerError"] = rest_field()
-    """An object containing more specific information than the current object about the error."""
-
-    @overload
-    def __init__(
-        self,
-        *,
-        code: str,
-        message: str,
-        target: Optional[str] = None,
-        details: Optional[List["_models.Error"]] = None,
-        innererror: Optional["_models.InnerError"] = None,
-    ) -> None: ...
-
-    @overload
-    def __init__(self, mapping: Mapping[str, Any]) -> None:
-        """
-        :param mapping: raw JSON to initialize the model.
-        :type mapping: Mapping[str, Any]
-        """
-
-    def __init__(self, *args: Any, **kwargs: Any) -> None:  # pylint: disable=useless-super-delegation
-        super().__init__(*args, **kwargs)
-
-
-class ErrorResponse(_model_base.Model):
-    """Error response object.
-
-
-    :ivar error: Error info. Required.
-    :vartype error: ~azure.ai.documentintelligence.models.Error
-    """
-
-    error: "_models.Error" = rest_field()
-    """Error info. Required."""
-
-    @overload
-    def __init__(
-        self,
-        *,
-        error: "_models.Error",
-    ) -> None: ...
-
-    @overload
-    def __init__(self, mapping: Mapping[str, Any]) -> None:
-        """
-        :param mapping: raw JSON to initialize the model.
-        :type mapping: Mapping[str, Any]
-        """
-
-    def __init__(self, *args: Any, **kwargs: Any) -> None:  # pylint: disable=useless-super-delegation
-        super().__init__(*args, **kwargs)
-
-
-class InnerError(_model_base.Model):
-    """An object containing more specific information about the error.
-
-    :ivar code: One of a server-defined set of error codes.
-    :vartype code: str
-    :ivar message: A human-readable representation of the error.
-    :vartype message: str
-    :ivar innererror: Inner error.
-    :vartype innererror: ~azure.ai.documentintelligence.models.InnerError
-    """
-
-    code: Optional[str] = rest_field()
-    """One of a server-defined set of error codes."""
-    message: Optional[str] = rest_field()
-    """A human-readable representation of the error."""
-    innererror: Optional["_models.InnerError"] = rest_field()
-    """Inner error."""
-
-    @overload
-    def __init__(
-        self,
-        *,
-        code: Optional[str] = None,
-        message: Optional[str] = None,
-        innererror: Optional["_models.InnerError"] = None,
-    ) -> None: ...
-
-    @overload
-    def __init__(self, mapping: Mapping[str, Any]) -> None:
-        """
-        :param mapping: raw JSON to initialize the model.
-        :type mapping: Mapping[str, Any]
-        """
-
-    def __init__(self, *args: Any, **kwargs: Any) -> None:  # pylint: disable=useless-super-delegation
-        super().__init__(*args, **kwargs)
-
-
-class ResourceDetails(_model_base.Model):
-    """General information regarding the current resource.
-
-
-    :ivar custom_document_models: Details regarding custom document models. Required.
-    :vartype custom_document_models:
-     ~azure.ai.documentintelligence.models.CustomDocumentModelsDetails
-    """
-
-    custom_document_models: "_models.CustomDocumentModelsDetails" = rest_field(name="customDocumentModels")
-    """Details regarding custom document models. Required."""
-
-    @overload
-    def __init__(
-        self,
-        *,
-        custom_document_models: "_models.CustomDocumentModelsDetails",
-    ) -> None: ...
-
-    @overload
-    def __init__(self, mapping: Mapping[str, Any]) -> None:
-        """
-        :param mapping: raw JSON to initialize the model.
-        :type mapping: Mapping[str, Any]
-        """
-
-    def __init__(self, *args: Any, **kwargs: Any) -> None:  # pylint: disable=useless-super-delegation
-        super().__init__(*args, **kwargs)
-
-
-class Warning(_model_base.Model):
-    """The error object.
+class ModelCopyAuthorization(_model_base.Model):
+    """Authorization to copy a document model to the specified target resource and
+    modelId.
 
 
-    :ivar code: One of a server-defined set of warning codes. Required.
-    :vartype code: str
-    :ivar message: A human-readable representation of the warning. Required.
-    :vartype message: str
-    :ivar target: The target of the error.
-    :vartype target: str
+    :ivar target_resource_id: ID of the target Azure resource where the document model should be
+     copied to. Required.
+    :vartype target_resource_id: str
+    :ivar target_resource_region: Location of the target Azure resource where the document model
+     should be copied
+     to. Required.
+    :vartype target_resource_region: str
+    :ivar target_model_id: Identifier of the target document model. Required.
+    :vartype target_model_id: str
+    :ivar target_model_location: URL of the copied document model in the target account. Required.
+    :vartype target_model_location: str
+    :ivar access_token: Token used to authorize the request. Required.
+    :vartype access_token: str
+    :ivar expiration_date_time: Date/time when the access token expires. Required.
+    :vartype expiration_date_time: ~datetime.datetime
     """
 
-    code: str = rest_field()
-    """One of a server-defined set of warning codes. Required."""
-    message: str = rest_field()
-    """A human-readable representation of the warning. Required."""
-    target: Optional[str] = rest_field()
-    """The target of the error."""
+    target_resource_id: str = rest_field(name="targetResourceId")
+    """ID of the target Azure resource where the document model should be copied to. Required."""
+    target_resource_region: str = rest_field(name="targetResourceRegion")
+    """Location of the target Azure resource where the document model should be copied
+     to. Required."""
+    target_model_id: str = rest_field(name="targetModelId")
+    """Identifier of the target document model. Required."""
+    target_model_location: str = rest_field(name="targetModelLocation")
+    """URL of the copied document model in the target account. Required."""
+    access_token: str = rest_field(name="accessToken")
+    """Token used to authorize the request. Required."""
+    expiration_date_time: datetime.datetime = rest_field(name="expirationDateTime", format="rfc3339")
+    """Date/time when the access token expires. Required."""
 
     @overload
     def __init__(
         self,
         *,
-        code: str,
-        message: str,
-        target: Optional[str] = None,
+        target_resource_id: str,
+        target_resource_region: str,
+        target_model_id: str,
+        target_model_location: str,
+        access_token: str,
+        expiration_date_time: datetime.datetime,
     ) -> None: ...
 
     @overload
@@ -3164,5 +3130,5 @@ def __init__(self, mapping: Mapping[str, Any]) -> None:
         :type mapping: Mapping[str, Any]
         """
 
-    def __init__(self, *args: Any, **kwargs: Any) -> None:  # pylint: disable=useless-super-delegation
+    def __init__(self, *args: Any, **kwargs: Any) -> None:
         super().__init__(*args, **kwargs)
diff --git a/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/models/_patch.py b/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/models/_patch.py
index c385980aebd50..f7dd32510333d 100644
--- a/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/models/_patch.py
+++ b/sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/models/_patch.py
@@ -6,45 +6,9 @@
 
 Follow our quickstart for examples: https://aka.ms/azsdk/python/dpcodegen/python/customize
 """
-from typing import List, Optional
-from ._models import (
-    AnalyzeDocumentRequest as GeneratedAnalyzeDocumentRequest,
-    ClassifyDocumentRequest as GeneratedClassifyDocumentRequest,
-)
-from .._model_base import rest_field
+from typing import List
 
-
-class AnalyzeDocumentRequest(GeneratedAnalyzeDocumentRequest):
-    """Document analysis parameters.
-
-    :ivar url_source: Document URL to analyze.  Either url_source or bytes_source must be specified.
-    :vartype url_source: str
-    :ivar bytes_source: Document bytes to analyze.  Either url_source or bytes_source must be specified.
-    :vartype bytes_source: bytes
-    """
-
-    bytes_source: Optional[bytes] = rest_field(name="base64Source", format="base64")
-    """Document bytes to analyze.  Either url_source or bytes_source must be specified."""
-
-
-class ClassifyDocumentRequest(GeneratedClassifyDocumentRequest):
-    """Document classification parameters.
-
-    :ivar url_source: Document URL to classify.  Either url_source or bytes_source must be
-     specified.
-    :vartype url_source: str
-    :ivar bytes_source: Document bytes to classify.  Either url_source or bytes_source must be specified.
-    :vartype bytes_source: bytes
-    """
-
-    bytes_source: Optional[bytes] = rest_field(name="base64Source", format="base64")
-    """Document bytes to classify.  Either url_source or bytes_source must be specified."""
-
-
-__all__: List[str] = [
-    "AnalyzeDocumentRequest",
-    "ClassifyDocumentRequest",
-]  # Add all objects you want publicly available to users at this package level
+__all__: List[str] = []  # Add all objects you want publicly available to users at this package level
 
 
 def patch_sdk():
diff --git a/sdk/documentintelligence/azure-ai-documentintelligence/generated_samples/delete_analyze_batch_documents_result.py b/sdk/documentintelligence/azure-ai-documentintelligence/generated_samples/delete_analyze_batch_documents_result.py
new file mode 100644
index 0000000000000..e6cc5eeb045a5
--- /dev/null
+++ b/sdk/documentintelligence/azure-ai-documentintelligence/generated_samples/delete_analyze_batch_documents_result.py
@@ -0,0 +1,33 @@
+# 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.
+# Code generated by Microsoft (R) Python Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+
+from azure.ai.documentintelligence import DocumentIntelligenceClient
+
+"""
+# PREREQUISITES
+    pip install azure-ai-documentintelligence
+# USAGE
+    python delete_analyze_batch_documents_result.py
+"""
+
+
+def main():
+    client = DocumentIntelligenceClient(
+        endpoint="https://myendpoint.cognitiveservices.azure.com",
+        credential="CREDENTIAL",
+    )
+
+    client.delete_analyze_batch_result(
+        model_id="prebuilt-invoice",
+        result_id="3b31320d-8bab-4f88-b19c-2322a7f11034",
+    )
+
+
+# x-ms-original-file: 2024-11-30/DeleteAnalyzeBatchDocumentsResult.json
+if __name__ == "__main__":
+    main()
diff --git a/sdk/documentintelligence/azure-ai-documentintelligence/generated_samples/delete_analyze_document_result.py b/sdk/documentintelligence/azure-ai-documentintelligence/generated_samples/delete_analyze_document_result.py
new file mode 100644
index 0000000000000..a52452fbe3242
--- /dev/null
+++ b/sdk/documentintelligence/azure-ai-documentintelligence/generated_samples/delete_analyze_document_result.py
@@ -0,0 +1,33 @@
+# 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.
+# Code generated by Microsoft (R) Python Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+
+from azure.ai.documentintelligence import DocumentIntelligenceClient
+
+"""
+# PREREQUISITES
+    pip install azure-ai-documentintelligence
+# USAGE
+    python delete_analyze_document_result.py
+"""
+
+
+def main():
+    client = DocumentIntelligenceClient(
+        endpoint="https://myendpoint.cognitiveservices.azure.com",
+        credential="CREDENTIAL",
+    )
+
+    client.delete_analyze_result(
+        model_id="myCustomModel",
+        result_id="3b31320d-8bab-4f88-b19c-2322a7f11034",
+    )
+
+
+# x-ms-original-file: 2024-11-30/DeleteAnalyzeDocumentResult.json
+if __name__ == "__main__":
+    main()
diff --git a/sdk/documentintelligence/azure-ai-documentintelligence/generated_samples/delete_document_classifier.py b/sdk/documentintelligence/azure-ai-documentintelligence/generated_samples/delete_document_classifier.py
new file mode 100644
index 0000000000000..9e5e32890f4dd
--- /dev/null
+++ b/sdk/documentintelligence/azure-ai-documentintelligence/generated_samples/delete_document_classifier.py
@@ -0,0 +1,32 @@
+# 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.
+# Code generated by Microsoft (R) Python Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+
+from azure.ai.documentintelligence import DocumentIntelligenceClient
+
+"""
+# PREREQUISITES
+    pip install azure-ai-documentintelligence
+# USAGE
+    python delete_document_classifier.py
+"""
+
+
+def main():
+    client = DocumentIntelligenceClient(
+        endpoint="https://myendpoint.cognitiveservices.azure.com",
+        credential="CREDENTIAL",
+    )
+
+    client.delete_classifier(
+        classifier_id="myClassifier",
+    )
+
+
+# x-ms-original-file: 2024-11-30/DeleteDocumentClassifier.json
+if __name__ == "__main__":
+    main()
diff --git a/sdk/documentintelligence/azure-ai-documentintelligence/generated_samples/delete_document_model.py b/sdk/documentintelligence/azure-ai-documentintelligence/generated_samples/delete_document_model.py
new file mode 100644
index 0000000000000..87c28058fbbd5
--- /dev/null
+++ b/sdk/documentintelligence/azure-ai-documentintelligence/generated_samples/delete_document_model.py
@@ -0,0 +1,32 @@
+# 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.
+# Code generated by Microsoft (R) Python Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+
+from azure.ai.documentintelligence import DocumentIntelligenceClient
+
+"""
+# PREREQUISITES
+    pip install azure-ai-documentintelligence
+# USAGE
+    python delete_document_model.py
+"""
+
+
+def main():
+    client = DocumentIntelligenceClient(
+        endpoint="https://myendpoint.cognitiveservices.azure.com",
+        credential="CREDENTIAL",
+    )
+
+    client.delete_model(
+        model_id="myCustomModel",
+    )
+
+
+# x-ms-original-file: 2024-11-30/DeleteDocumentModel.json
+if __name__ == "__main__":
+    main()
diff --git a/sdk/documentintelligence/azure-ai-documentintelligence/generated_samples/get_analyze_batch_documents_result.py b/sdk/documentintelligence/azure-ai-documentintelligence/generated_samples/get_analyze_batch_documents_result.py
new file mode 100644
index 0000000000000..7be38a8f67d49
--- /dev/null
+++ b/sdk/documentintelligence/azure-ai-documentintelligence/generated_samples/get_analyze_batch_documents_result.py
@@ -0,0 +1,34 @@
+# 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.
+# Code generated by Microsoft (R) Python Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+
+from azure.ai.documentintelligence import DocumentIntelligenceClient
+
+"""
+# PREREQUISITES
+    pip install azure-ai-documentintelligence
+# USAGE
+    python get_analyze_batch_documents_result.py
+"""
+
+
+def main():
+    client = DocumentIntelligenceClient(
+        endpoint="https://myendpoint.cognitiveservices.azure.com",
+        credential="CREDENTIAL",
+    )
+
+    response = client.get_analyze_batch_result(
+        model_id="prebuilt-invoice",
+        result_id="3b31320d-8bab-4f88-b19c-2322a7f11034",
+    )
+    print(response)
+
+
+# x-ms-original-file: 2024-11-30/GetAnalyzeBatchDocumentsResult.json
+if __name__ == "__main__":
+    main()
diff --git a/sdk/documentintelligence/azure-ai-documentintelligence/generated_samples/get_analyze_batch_documents_results.py b/sdk/documentintelligence/azure-ai-documentintelligence/generated_samples/get_analyze_batch_documents_results.py
new file mode 100644
index 0000000000000..cd25ea958178d
--- /dev/null
+++ b/sdk/documentintelligence/azure-ai-documentintelligence/generated_samples/get_analyze_batch_documents_results.py
@@ -0,0 +1,34 @@
+# 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.
+# Code generated by Microsoft (R) Python Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+
+from azure.ai.documentintelligence import DocumentIntelligenceClient
+
+"""
+# PREREQUISITES
+    pip install azure-ai-documentintelligence
+# USAGE
+    python get_analyze_batch_documents_results.py
+"""
+
+
+def main():
+    client = DocumentIntelligenceClient(
+        endpoint="https://myendpoint.cognitiveservices.azure.com",
+        credential="CREDENTIAL",
+    )
+
+    response = client.list_analyze_batch_results(
+        model_id="prebuilt-invoice",
+    )
+    for item in response:
+        print(item)
+
+
+# x-ms-original-file: 2024-11-30/GetAnalyzeBatchDocumentsResults.json
+if __name__ == "__main__":
+    main()
diff --git a/sdk/documentintelligence/azure-ai-documentintelligence/generated_samples/get_analyze_document_result_figure.py b/sdk/documentintelligence/azure-ai-documentintelligence/generated_samples/get_analyze_document_result_figure.py
new file mode 100644
index 0000000000000..d8d3868c3b21a
--- /dev/null
+++ b/sdk/documentintelligence/azure-ai-documentintelligence/generated_samples/get_analyze_document_result_figure.py
@@ -0,0 +1,35 @@
+# 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.
+# Code generated by Microsoft (R) Python Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+
+from azure.ai.documentintelligence import DocumentIntelligenceClient
+
+"""
+# PREREQUISITES
+    pip install azure-ai-documentintelligence
+# USAGE
+    python get_analyze_document_result_figure.py
+"""
+
+
+def main():
+    client = DocumentIntelligenceClient(
+        endpoint="https://myendpoint.cognitiveservices.azure.com",
+        credential="CREDENTIAL",
+    )
+
+    response = client.get_analyze_result_figure(
+        model_id="prebuilt-invoice",
+        result_id="3b31320d-8bab-4f88-b19c-2322a7f11034",
+        figure_id="1.0",
+    )
+    print(response)
+
+
+# x-ms-original-file: 2024-11-30/GetAnalyzeDocumentResultFigure.json
+if __name__ == "__main__":
+    main()
diff --git a/sdk/documentintelligence/azure-ai-documentintelligence/generated_samples/get_analyze_document_result_fpdf.py b/sdk/documentintelligence/azure-ai-documentintelligence/generated_samples/get_analyze_document_result_fpdf.py
new file mode 100644
index 0000000000000..6a88b0888e07b
--- /dev/null
+++ b/sdk/documentintelligence/azure-ai-documentintelligence/generated_samples/get_analyze_document_result_fpdf.py
@@ -0,0 +1,34 @@
+# 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.
+# Code generated by Microsoft (R) Python Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+
+from azure.ai.documentintelligence import DocumentIntelligenceClient
+
+"""
+# PREREQUISITES
+    pip install azure-ai-documentintelligence
+# USAGE
+    python get_analyze_document_result_fpdf.py
+"""
+
+
+def main():
+    client = DocumentIntelligenceClient(
+        endpoint="https://myendpoint.cognitiveservices.azure.com",
+        credential="CREDENTIAL",
+    )
+
+    response = client.get_analyze_result_pdf(
+        model_id="prebuilt-invoice",
+        result_id="3b31320d-8bab-4f88-b19c-2322a7f11034",
+    )
+    print(response)
+
+
+# x-ms-original-file: 2024-11-30/GetAnalyzeDocumentResultFPdf.json
+if __name__ == "__main__":
+    main()
diff --git a/sdk/documentintelligence/azure-ai-documentintelligence/generated_samples/get_document_classifier.py b/sdk/documentintelligence/azure-ai-documentintelligence/generated_samples/get_document_classifier.py
new file mode 100644
index 0000000000000..76c5b95742260
--- /dev/null
+++ b/sdk/documentintelligence/azure-ai-documentintelligence/generated_samples/get_document_classifier.py
@@ -0,0 +1,33 @@
+# 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.
+# Code generated by Microsoft (R) Python Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+
+from azure.ai.documentintelligence import DocumentIntelligenceClient
+
+"""
+# PREREQUISITES
+    pip install azure-ai-documentintelligence
+# USAGE
+    python get_document_classifier.py
+"""
+
+
+def main():
+    client = DocumentIntelligenceClient(
+        endpoint="https://myendpoint.cognitiveservices.azure.com",
+        credential="CREDENTIAL",
+    )
+
+    response = client.get_classifier(
+        classifier_id="myClassifier",
+    )
+    print(response)
+
+
+# x-ms-original-file: 2024-11-30/GetDocumentClassifier.json
+if __name__ == "__main__":
+    main()
diff --git a/sdk/documentintelligence/azure-ai-documentintelligence/generated_samples/get_document_classifiers.py b/sdk/documentintelligence/azure-ai-documentintelligence/generated_samples/get_document_classifiers.py
new file mode 100644
index 0000000000000..a02085b9c0bad
--- /dev/null
+++ b/sdk/documentintelligence/azure-ai-documentintelligence/generated_samples/get_document_classifiers.py
@@ -0,0 +1,32 @@
+# 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.
+# Code generated by Microsoft (R) Python Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+
+from azure.ai.documentintelligence import DocumentIntelligenceClient
+
+"""
+# PREREQUISITES
+    pip install azure-ai-documentintelligence
+# USAGE
+    python get_document_classifiers.py
+"""
+
+
+def main():
+    client = DocumentIntelligenceClient(
+        endpoint="https://myendpoint.cognitiveservices.azure.com",
+        credential="CREDENTIAL",
+    )
+
+    response = client.list_classifiers()
+    for item in response:
+        print(item)
+
+
+# x-ms-original-file: 2024-11-30/GetDocumentClassifiers.json
+if __name__ == "__main__":
+    main()
diff --git a/sdk/documentintelligence/azure-ai-documentintelligence/generated_samples/get_document_model_custom.py b/sdk/documentintelligence/azure-ai-documentintelligence/generated_samples/get_document_model_custom.py
new file mode 100644
index 0000000000000..d12fae573bf97
--- /dev/null
+++ b/sdk/documentintelligence/azure-ai-documentintelligence/generated_samples/get_document_model_custom.py
@@ -0,0 +1,33 @@
+# 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.
+# Code generated by Microsoft (R) Python Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+
+from azure.ai.documentintelligence import DocumentIntelligenceClient
+
+"""
+# PREREQUISITES
+    pip install azure-ai-documentintelligence
+# USAGE
+    python get_document_model_custom.py
+"""
+
+
+def main():
+    client = DocumentIntelligenceClient(
+        endpoint="https://myendpoint.cognitiveservices.azure.com",
+        credential="CREDENTIAL",
+    )
+
+    response = client.get_model(
+        model_id="myCustomModel",
+    )
+    print(response)
+
+
+# x-ms-original-file: 2024-11-30/GetDocumentModel_Custom.json
+if __name__ == "__main__":
+    main()
diff --git a/sdk/documentintelligence/azure-ai-documentintelligence/generated_samples/get_document_model_prebuilt.py b/sdk/documentintelligence/azure-ai-documentintelligence/generated_samples/get_document_model_prebuilt.py
new file mode 100644
index 0000000000000..c96ac2ee5c46a
--- /dev/null
+++ b/sdk/documentintelligence/azure-ai-documentintelligence/generated_samples/get_document_model_prebuilt.py
@@ -0,0 +1,33 @@
+# 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.
+# Code generated by Microsoft (R) Python Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+
+from azure.ai.documentintelligence import DocumentIntelligenceClient
+
+"""
+# PREREQUISITES
+    pip install azure-ai-documentintelligence
+# USAGE
+    python get_document_model_prebuilt.py
+"""
+
+
+def main():
+    client = DocumentIntelligenceClient(
+        endpoint="https://myendpoint.cognitiveservices.azure.com",
+        credential="CREDENTIAL",
+    )
+
+    response = client.get_model(
+        model_id="prebuilt-invoice",
+    )
+    print(response)
+
+
+# x-ms-original-file: 2024-11-30/GetDocumentModel_Prebuilt.json
+if __name__ == "__main__":
+    main()
diff --git a/sdk/documentintelligence/azure-ai-documentintelligence/generated_samples/get_document_models.py b/sdk/documentintelligence/azure-ai-documentintelligence/generated_samples/get_document_models.py
new file mode 100644
index 0000000000000..fdaeb7f783385
--- /dev/null
+++ b/sdk/documentintelligence/azure-ai-documentintelligence/generated_samples/get_document_models.py
@@ -0,0 +1,32 @@
+# 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.
+# Code generated by Microsoft (R) Python Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+
+from azure.ai.documentintelligence import DocumentIntelligenceClient
+
+"""
+# PREREQUISITES
+    pip install azure-ai-documentintelligence
+# USAGE
+    python get_document_models.py
+"""
+
+
+def main():
+    client = DocumentIntelligenceClient(
+        endpoint="https://myendpoint.cognitiveservices.azure.com",
+        credential="CREDENTIAL",
+    )
+
+    response = client.list_models()
+    for item in response:
+        print(item)
+
+
+# x-ms-original-file: 2024-11-30/GetDocumentModels.json
+if __name__ == "__main__":
+    main()
diff --git a/sdk/documentintelligence/azure-ai-documentintelligence/generated_samples/get_operation.py b/sdk/documentintelligence/azure-ai-documentintelligence/generated_samples/get_operation.py
new file mode 100644
index 0000000000000..ca6341e11ef72
--- /dev/null
+++ b/sdk/documentintelligence/azure-ai-documentintelligence/generated_samples/get_operation.py
@@ -0,0 +1,33 @@
+# 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.
+# Code generated by Microsoft (R) Python Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+
+from azure.ai.documentintelligence import DocumentIntelligenceClient
+
+"""
+# PREREQUISITES
+    pip install azure-ai-documentintelligence
+# USAGE
+    python get_operation.py
+"""
+
+
+def main():
+    client = DocumentIntelligenceClient(
+        endpoint="https://myendpoint.cognitiveservices.azure.com",
+        credential="CREDENTIAL",
+    )
+
+    response = client.get_operation(
+        operation_id="b704bb00-d130-4f3f-a1d8-ca96de3eabb4",
+    )
+    print(response)
+
+
+# x-ms-original-file: 2024-11-30/GetOperation.json
+if __name__ == "__main__":
+    main()
diff --git a/sdk/documentintelligence/azure-ai-documentintelligence/generated_samples/get_operations.py b/sdk/documentintelligence/azure-ai-documentintelligence/generated_samples/get_operations.py
new file mode 100644
index 0000000000000..0b7758a41a6bd
--- /dev/null
+++ b/sdk/documentintelligence/azure-ai-documentintelligence/generated_samples/get_operations.py
@@ -0,0 +1,32 @@
+# 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.
+# Code generated by Microsoft (R) Python Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+
+from azure.ai.documentintelligence import DocumentIntelligenceClient
+
+"""
+# PREREQUISITES
+    pip install azure-ai-documentintelligence
+# USAGE
+    python get_operations.py
+"""
+
+
+def main():
+    client = DocumentIntelligenceClient(
+        endpoint="https://myendpoint.cognitiveservices.azure.com",
+        credential="CREDENTIAL",
+    )
+
+    response = client.list_operations()
+    for item in response:
+        print(item)
+
+
+# x-ms-original-file: 2024-11-30/GetOperations.json
+if __name__ == "__main__":
+    main()
diff --git a/sdk/documentintelligence/azure-ai-documentintelligence/generated_samples/get_resource_details.py b/sdk/documentintelligence/azure-ai-documentintelligence/generated_samples/get_resource_details.py
new file mode 100644
index 0000000000000..ea49a684e457f
--- /dev/null
+++ b/sdk/documentintelligence/azure-ai-documentintelligence/generated_samples/get_resource_details.py
@@ -0,0 +1,31 @@
+# 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.
+# Code generated by Microsoft (R) Python Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+
+from azure.ai.documentintelligence import DocumentIntelligenceClient
+
+"""
+# PREREQUISITES
+    pip install azure-ai-documentintelligence
+# USAGE
+    python get_resource_details.py
+"""
+
+
+def main():
+    client = DocumentIntelligenceClient(
+        endpoint="https://myendpoint.cognitiveservices.azure.com",
+        credential="CREDENTIAL",
+    )
+
+    response = client.get_resource_details()
+    print(response)
+
+
+# x-ms-original-file: 2024-11-30/GetResourceDetails.json
+if __name__ == "__main__":
+    main()
diff --git a/sdk/documentintelligence/azure-ai-documentintelligence/generated_tests/conftest.py b/sdk/documentintelligence/azure-ai-documentintelligence/generated_tests/conftest.py
new file mode 100644
index 0000000000000..d647c5afe1fcc
--- /dev/null
+++ b/sdk/documentintelligence/azure-ai-documentintelligence/generated_tests/conftest.py
@@ -0,0 +1,70 @@
+# 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.
+# Code generated by Microsoft (R) Python Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+import os
+import pytest
+from dotenv import load_dotenv
+from devtools_testutils import (
+    test_proxy,
+    add_general_regex_sanitizer,
+    add_body_key_sanitizer,
+    add_header_regex_sanitizer,
+)
+
+load_dotenv()
+
+
+# For security, please avoid record sensitive identity information in recordings
+@pytest.fixture(scope="session", autouse=True)
+def add_sanitizers(test_proxy):
+    documentintelligence_subscription_id = os.environ.get(
+        "DOCUMENTINTELLIGENCE_SUBSCRIPTION_ID", "00000000-0000-0000-0000-000000000000"
+    )
+    documentintelligence_tenant_id = os.environ.get(
+        "DOCUMENTINTELLIGENCE_TENANT_ID", "00000000-0000-0000-0000-000000000000"
+    )
+    documentintelligence_client_id = os.environ.get(
+        "DOCUMENTINTELLIGENCE_CLIENT_ID", "00000000-0000-0000-0000-000000000000"
+    )
+    documentintelligence_client_secret = os.environ.get(
+        "DOCUMENTINTELLIGENCE_CLIENT_SECRET", "00000000-0000-0000-0000-000000000000"
+    )
+    add_general_regex_sanitizer(
+        regex=documentintelligence_subscription_id, value="00000000-0000-0000-0000-000000000000"
+    )
+    add_general_regex_sanitizer(regex=documentintelligence_tenant_id, value="00000000-0000-0000-0000-000000000000")
+    add_general_regex_sanitizer(regex=documentintelligence_client_id, value="00000000-0000-0000-0000-000000000000")
+    add_general_regex_sanitizer(regex=documentintelligence_client_secret, value="00000000-0000-0000-0000-000000000000")
+
+    documentintelligenceadministration_subscription_id = os.environ.get(
+        "DOCUMENTINTELLIGENCEADMINISTRATION_SUBSCRIPTION_ID", "00000000-0000-0000-0000-000000000000"
+    )
+    documentintelligenceadministration_tenant_id = os.environ.get(
+        "DOCUMENTINTELLIGENCEADMINISTRATION_TENANT_ID", "00000000-0000-0000-0000-000000000000"
+    )
+    documentintelligenceadministration_client_id = os.environ.get(
+        "DOCUMENTINTELLIGENCEADMINISTRATION_CLIENT_ID", "00000000-0000-0000-0000-000000000000"
+    )
+    documentintelligenceadministration_client_secret = os.environ.get(
+        "DOCUMENTINTELLIGENCEADMINISTRATION_CLIENT_SECRET", "00000000-0000-0000-0000-000000000000"
+    )
+    add_general_regex_sanitizer(
+        regex=documentintelligenceadministration_subscription_id, value="00000000-0000-0000-0000-000000000000"
+    )
+    add_general_regex_sanitizer(
+        regex=documentintelligenceadministration_tenant_id, value="00000000-0000-0000-0000-000000000000"
+    )
+    add_general_regex_sanitizer(
+        regex=documentintelligenceadministration_client_id, value="00000000-0000-0000-0000-000000000000"
+    )
+    add_general_regex_sanitizer(
+        regex=documentintelligenceadministration_client_secret, value="00000000-0000-0000-0000-000000000000"
+    )
+
+    add_header_regex_sanitizer(key="Set-Cookie", value="[set-cookie;]")
+    add_header_regex_sanitizer(key="Cookie", value="cookie;")
+    add_body_key_sanitizer(json_path="$..access_token", value="access_token")
diff --git a/sdk/documentintelligence/azure-ai-documentintelligence/generated_tests/test_document_intelligence.py b/sdk/documentintelligence/azure-ai-documentintelligence/generated_tests/test_document_intelligence.py
new file mode 100644
index 0000000000000..bafbd67767a55
--- /dev/null
+++ b/sdk/documentintelligence/azure-ai-documentintelligence/generated_tests/test_document_intelligence.py
@@ -0,0 +1,127 @@
+# 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.
+# Code generated by Microsoft (R) Python Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+import pytest
+from devtools_testutils import recorded_by_proxy
+from testpreparer import DocumentIntelligenceClientTestBase, DocumentIntelligencePreparer
+
+
+@pytest.mark.skip("you may need to update the auto-generated test case before run it")
+class TestDocumentIntelligence(DocumentIntelligenceClientTestBase):
+    @DocumentIntelligencePreparer()
+    @recorded_by_proxy
+    def test_begin_analyze_document(self, documentintelligence_endpoint):
+        client = self.create_client(endpoint=documentintelligence_endpoint)
+        response = client.begin_analyze_document(
+            model_id="str",
+            body={"base64Source": bytes("bytes", encoding="utf-8"), "urlSource": "str"},
+        ).result()  # call '.result()' to poll until service return final result
+
+        # please add some check logic here by yourself
+        # ...
+
+    @DocumentIntelligencePreparer()
+    @recorded_by_proxy
+    def test_get_analyze_result_pdf(self, documentintelligence_endpoint):
+        client = self.create_client(endpoint=documentintelligence_endpoint)
+        response = client.get_analyze_result_pdf(
+            model_id="str",
+            result_id="str",
+        )
+
+        # please add some check logic here by yourself
+        # ...
+
+    @DocumentIntelligencePreparer()
+    @recorded_by_proxy
+    def test_get_analyze_result_figure(self, documentintelligence_endpoint):
+        client = self.create_client(endpoint=documentintelligence_endpoint)
+        response = client.get_analyze_result_figure(
+            model_id="str",
+            result_id="str",
+            figure_id="str",
+        )
+
+        # please add some check logic here by yourself
+        # ...
+
+    @DocumentIntelligencePreparer()
+    @recorded_by_proxy
+    def test_delete_analyze_result(self, documentintelligence_endpoint):
+        client = self.create_client(endpoint=documentintelligence_endpoint)
+        response = client.delete_analyze_result(
+            model_id="str",
+            result_id="str",
+        )
+
+        # please add some check logic here by yourself
+        # ...
+
+    @DocumentIntelligencePreparer()
+    @recorded_by_proxy
+    def test_begin_analyze_batch_documents(self, documentintelligence_endpoint):
+        client = self.create_client(endpoint=documentintelligence_endpoint)
+        response = client.begin_analyze_batch_documents(
+            model_id="str",
+            body={
+                "resultContainerUrl": "str",
+                "azureBlobFileListSource": {"containerUrl": "str", "fileList": "str"},
+                "azureBlobSource": {"containerUrl": "str", "prefix": "str"},
+                "overwriteExisting": bool,
+                "resultPrefix": "str",
+            },
+        ).result()  # call '.result()' to poll until service return final result
+
+        # please add some check logic here by yourself
+        # ...
+
+    @DocumentIntelligencePreparer()
+    @recorded_by_proxy
+    def test_list_analyze_batch_results(self, documentintelligence_endpoint):
+        client = self.create_client(endpoint=documentintelligence_endpoint)
+        response = client.list_analyze_batch_results(
+            model_id="str",
+        )
+        result = [r for r in response]
+        # please add some check logic here by yourself
+        # ...
+
+    @DocumentIntelligencePreparer()
+    @recorded_by_proxy
+    def test_delete_analyze_batch_result(self, documentintelligence_endpoint):
+        client = self.create_client(endpoint=documentintelligence_endpoint)
+        response = client.delete_analyze_batch_result(
+            model_id="str",
+            result_id="str",
+        )
+
+        # please add some check logic here by yourself
+        # ...
+
+    @DocumentIntelligencePreparer()
+    @recorded_by_proxy
+    def test_get_analyze_batch_result(self, documentintelligence_endpoint):
+        client = self.create_client(endpoint=documentintelligence_endpoint)
+        response = client.get_analyze_batch_result(
+            model_id="str",
+            result_id="str",
+        )
+
+        # please add some check logic here by yourself
+        # ...
+
+    @DocumentIntelligencePreparer()
+    @recorded_by_proxy
+    def test_begin_classify_document(self, documentintelligence_endpoint):
+        client = self.create_client(endpoint=documentintelligence_endpoint)
+        response = client.begin_classify_document(
+            classifier_id="str",
+            body={"base64Source": bytes("bytes", encoding="utf-8"), "urlSource": "str"},
+        ).result()  # call '.result()' to poll until service return final result
+
+        # please add some check logic here by yourself
+        # ...
diff --git a/sdk/documentintelligence/azure-ai-documentintelligence/generated_tests/test_document_intelligence_administration.py b/sdk/documentintelligence/azure-ai-documentintelligence/generated_tests/test_document_intelligence_administration.py
new file mode 100644
index 0000000000000..e1e2126bb6b61
--- /dev/null
+++ b/sdk/documentintelligence/azure-ai-documentintelligence/generated_tests/test_document_intelligence_administration.py
@@ -0,0 +1,245 @@
+# 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.
+# Code generated by Microsoft (R) Python Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+import pytest
+from devtools_testutils import recorded_by_proxy
+from testpreparer import DocumentIntelligenceAdministrationClientTestBase, DocumentIntelligenceAdministrationPreparer
+
+
+@pytest.mark.skip("you may need to update the auto-generated test case before run it")
+class TestDocumentIntelligenceAdministration(DocumentIntelligenceAdministrationClientTestBase):
+    @DocumentIntelligenceAdministrationPreparer()
+    @recorded_by_proxy
+    def test_begin_build_document_model(self, documentintelligenceadministration_endpoint):
+        client = self.create_client(endpoint=documentintelligenceadministration_endpoint)
+        response = client.begin_build_document_model(
+            body={
+                "buildMode": "str",
+                "modelId": "str",
+                "allowOverwrite": bool,
+                "azureBlobFileListSource": {"containerUrl": "str", "fileList": "str"},
+                "azureBlobSource": {"containerUrl": "str", "prefix": "str"},
+                "description": "str",
+                "maxTrainingHours": 0.0,
+                "tags": {"str": "str"},
+            },
+        ).result()  # call '.result()' to poll until service return final result
+
+        # please add some check logic here by yourself
+        # ...
+
+    @DocumentIntelligenceAdministrationPreparer()
+    @recorded_by_proxy
+    def test_begin_compose_model(self, documentintelligenceadministration_endpoint):
+        client = self.create_client(endpoint=documentintelligenceadministration_endpoint)
+        response = client.begin_compose_model(
+            body={
+                "classifierId": "str",
+                "docTypes": {
+                    "str": {
+                        "buildMode": "str",
+                        "confidenceThreshold": 0.0,
+                        "description": "str",
+                        "features": ["str"],
+                        "fieldConfidence": {"str": 0.0},
+                        "fieldSchema": {
+                            "str": {
+                                "type": "str",
+                                "description": "str",
+                                "example": "str",
+                                "items": ...,
+                                "properties": {"str": ...},
+                            }
+                        },
+                        "maxDocumentsToAnalyze": 0,
+                        "modelId": "str",
+                        "queryFields": ["str"],
+                    }
+                },
+                "modelId": "str",
+                "description": "str",
+                "split": "str",
+                "tags": {"str": "str"},
+            },
+        ).result()  # call '.result()' to poll until service return final result
+
+        # please add some check logic here by yourself
+        # ...
+
+    @DocumentIntelligenceAdministrationPreparer()
+    @recorded_by_proxy
+    def test_authorize_model_copy(self, documentintelligenceadministration_endpoint):
+        client = self.create_client(endpoint=documentintelligenceadministration_endpoint)
+        response = client.authorize_model_copy(
+            body={"modelId": "str", "description": "str", "tags": {"str": "str"}},
+        )
+
+        # please add some check logic here by yourself
+        # ...
+
+    @DocumentIntelligenceAdministrationPreparer()
+    @recorded_by_proxy
+    def test_begin_copy_model_to(self, documentintelligenceadministration_endpoint):
+        client = self.create_client(endpoint=documentintelligenceadministration_endpoint)
+        response = client.begin_copy_model_to(
+            model_id="str",
+            body={
+                "accessToken": "str",
+                "expirationDateTime": "2020-02-20 00:00:00",
+                "targetModelId": "str",
+                "targetModelLocation": "str",
+                "targetResourceId": "str",
+                "targetResourceRegion": "str",
+            },
+        ).result()  # call '.result()' to poll until service return final result
+
+        # please add some check logic here by yourself
+        # ...
+
+    @DocumentIntelligenceAdministrationPreparer()
+    @recorded_by_proxy
+    def test_get_model(self, documentintelligenceadministration_endpoint):
+        client = self.create_client(endpoint=documentintelligenceadministration_endpoint)
+        response = client.get_model(
+            model_id="str",
+        )
+
+        # please add some check logic here by yourself
+        # ...
+
+    @DocumentIntelligenceAdministrationPreparer()
+    @recorded_by_proxy
+    def test_list_models(self, documentintelligenceadministration_endpoint):
+        client = self.create_client(endpoint=documentintelligenceadministration_endpoint)
+        response = client.list_models()
+        result = [r for r in response]
+        # please add some check logic here by yourself
+        # ...
+
+    @DocumentIntelligenceAdministrationPreparer()
+    @recorded_by_proxy
+    def test_delete_model(self, documentintelligenceadministration_endpoint):
+        client = self.create_client(endpoint=documentintelligenceadministration_endpoint)
+        response = client.delete_model(
+            model_id="str",
+        )
+
+        # please add some check logic here by yourself
+        # ...
+
+    @DocumentIntelligenceAdministrationPreparer()
+    @recorded_by_proxy
+    def test_get_resource_details(self, documentintelligenceadministration_endpoint):
+        client = self.create_client(endpoint=documentintelligenceadministration_endpoint)
+        response = client.get_resource_details()
+
+        # please add some check logic here by yourself
+        # ...
+
+    @DocumentIntelligenceAdministrationPreparer()
+    @recorded_by_proxy
+    def test_get_operation(self, documentintelligenceadministration_endpoint):
+        client = self.create_client(endpoint=documentintelligenceadministration_endpoint)
+        response = client.get_operation(
+            operation_id="str",
+        )
+
+        # please add some check logic here by yourself
+        # ...
+
+    @DocumentIntelligenceAdministrationPreparer()
+    @recorded_by_proxy
+    def test_list_operations(self, documentintelligenceadministration_endpoint):
+        client = self.create_client(endpoint=documentintelligenceadministration_endpoint)
+        response = client.list_operations()
+        result = [r for r in response]
+        # please add some check logic here by yourself
+        # ...
+
+    @DocumentIntelligenceAdministrationPreparer()
+    @recorded_by_proxy
+    def test_begin_build_classifier(self, documentintelligenceadministration_endpoint):
+        client = self.create_client(endpoint=documentintelligenceadministration_endpoint)
+        response = client.begin_build_classifier(
+            body={
+                "classifierId": "str",
+                "docTypes": {
+                    "str": {
+                        "azureBlobFileListSource": {"containerUrl": "str", "fileList": "str"},
+                        "azureBlobSource": {"containerUrl": "str", "prefix": "str"},
+                        "sourceKind": "str",
+                    }
+                },
+                "allowOverwrite": bool,
+                "baseClassifierId": "str",
+                "description": "str",
+            },
+        ).result()  # call '.result()' to poll until service return final result
+
+        # please add some check logic here by yourself
+        # ...
+
+    @DocumentIntelligenceAdministrationPreparer()
+    @recorded_by_proxy
+    def test_authorize_classifier_copy(self, documentintelligenceadministration_endpoint):
+        client = self.create_client(endpoint=documentintelligenceadministration_endpoint)
+        response = client.authorize_classifier_copy(
+            body={"classifierId": "str", "description": "str", "tags": {"str": "str"}},
+        )
+
+        # please add some check logic here by yourself
+        # ...
+
+    @DocumentIntelligenceAdministrationPreparer()
+    @recorded_by_proxy
+    def test_begin_copy_classifier_to(self, documentintelligenceadministration_endpoint):
+        client = self.create_client(endpoint=documentintelligenceadministration_endpoint)
+        response = client.begin_copy_classifier_to(
+            classifier_id="str",
+            body={
+                "accessToken": "str",
+                "expirationDateTime": "2020-02-20 00:00:00",
+                "targetClassifierId": "str",
+                "targetClassifierLocation": "str",
+                "targetResourceId": "str",
+                "targetResourceRegion": "str",
+            },
+        ).result()  # call '.result()' to poll until service return final result
+
+        # please add some check logic here by yourself
+        # ...
+
+    @DocumentIntelligenceAdministrationPreparer()
+    @recorded_by_proxy
+    def test_get_classifier(self, documentintelligenceadministration_endpoint):
+        client = self.create_client(endpoint=documentintelligenceadministration_endpoint)
+        response = client.get_classifier(
+            classifier_id="str",
+        )
+
+        # please add some check logic here by yourself
+        # ...
+
+    @DocumentIntelligenceAdministrationPreparer()
+    @recorded_by_proxy
+    def test_list_classifiers(self, documentintelligenceadministration_endpoint):
+        client = self.create_client(endpoint=documentintelligenceadministration_endpoint)
+        response = client.list_classifiers()
+        result = [r for r in response]
+        # please add some check logic here by yourself
+        # ...
+
+    @DocumentIntelligenceAdministrationPreparer()
+    @recorded_by_proxy
+    def test_delete_classifier(self, documentintelligenceadministration_endpoint):
+        client = self.create_client(endpoint=documentintelligenceadministration_endpoint)
+        response = client.delete_classifier(
+            classifier_id="str",
+        )
+
+        # please add some check logic here by yourself
+        # ...
diff --git a/sdk/documentintelligence/azure-ai-documentintelligence/generated_tests/test_document_intelligence_administration_async.py b/sdk/documentintelligence/azure-ai-documentintelligence/generated_tests/test_document_intelligence_administration_async.py
new file mode 100644
index 0000000000000..1522ffe7c182c
--- /dev/null
+++ b/sdk/documentintelligence/azure-ai-documentintelligence/generated_tests/test_document_intelligence_administration_async.py
@@ -0,0 +1,256 @@
+# 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.
+# Code generated by Microsoft (R) Python Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+import pytest
+from devtools_testutils.aio import recorded_by_proxy_async
+from testpreparer import DocumentIntelligenceAdministrationPreparer
+from testpreparer_async import DocumentIntelligenceAdministrationClientTestBaseAsync
+
+
+@pytest.mark.skip("you may need to update the auto-generated test case before run it")
+class TestDocumentIntelligenceAdministrationAsync(DocumentIntelligenceAdministrationClientTestBaseAsync):
+    @DocumentIntelligenceAdministrationPreparer()
+    @recorded_by_proxy_async
+    async def test_begin_build_document_model(self, documentintelligenceadministration_endpoint):
+        client = self.create_async_client(endpoint=documentintelligenceadministration_endpoint)
+        response = await (
+            await client.begin_build_document_model(
+                body={
+                    "buildMode": "str",
+                    "modelId": "str",
+                    "allowOverwrite": bool,
+                    "azureBlobFileListSource": {"containerUrl": "str", "fileList": "str"},
+                    "azureBlobSource": {"containerUrl": "str", "prefix": "str"},
+                    "description": "str",
+                    "maxTrainingHours": 0.0,
+                    "tags": {"str": "str"},
+                },
+            )
+        ).result()  # call '.result()' to poll until service return final result
+
+        # please add some check logic here by yourself
+        # ...
+
+    @DocumentIntelligenceAdministrationPreparer()
+    @recorded_by_proxy_async
+    async def test_begin_compose_model(self, documentintelligenceadministration_endpoint):
+        client = self.create_async_client(endpoint=documentintelligenceadministration_endpoint)
+        response = await (
+            await client.begin_compose_model(
+                body={
+                    "classifierId": "str",
+                    "docTypes": {
+                        "str": {
+                            "buildMode": "str",
+                            "confidenceThreshold": 0.0,
+                            "description": "str",
+                            "features": ["str"],
+                            "fieldConfidence": {"str": 0.0},
+                            "fieldSchema": {
+                                "str": {
+                                    "type": "str",
+                                    "description": "str",
+                                    "example": "str",
+                                    "items": ...,
+                                    "properties": {"str": ...},
+                                }
+                            },
+                            "maxDocumentsToAnalyze": 0,
+                            "modelId": "str",
+                            "queryFields": ["str"],
+                        }
+                    },
+                    "modelId": "str",
+                    "description": "str",
+                    "split": "str",
+                    "tags": {"str": "str"},
+                },
+            )
+        ).result()  # call '.result()' to poll until service return final result
+
+        # please add some check logic here by yourself
+        # ...
+
+    @DocumentIntelligenceAdministrationPreparer()
+    @recorded_by_proxy_async
+    async def test_authorize_model_copy(self, documentintelligenceadministration_endpoint):
+        client = self.create_async_client(endpoint=documentintelligenceadministration_endpoint)
+        response = await client.authorize_model_copy(
+            body={"modelId": "str", "description": "str", "tags": {"str": "str"}},
+        )
+
+        # please add some check logic here by yourself
+        # ...
+
+    @DocumentIntelligenceAdministrationPreparer()
+    @recorded_by_proxy_async
+    async def test_begin_copy_model_to(self, documentintelligenceadministration_endpoint):
+        client = self.create_async_client(endpoint=documentintelligenceadministration_endpoint)
+        response = await (
+            await client.begin_copy_model_to(
+                model_id="str",
+                body={
+                    "accessToken": "str",
+                    "expirationDateTime": "2020-02-20 00:00:00",
+                    "targetModelId": "str",
+                    "targetModelLocation": "str",
+                    "targetResourceId": "str",
+                    "targetResourceRegion": "str",
+                },
+            )
+        ).result()  # call '.result()' to poll until service return final result
+
+        # please add some check logic here by yourself
+        # ...
+
+    @DocumentIntelligenceAdministrationPreparer()
+    @recorded_by_proxy_async
+    async def test_get_model(self, documentintelligenceadministration_endpoint):
+        client = self.create_async_client(endpoint=documentintelligenceadministration_endpoint)
+        response = await client.get_model(
+            model_id="str",
+        )
+
+        # please add some check logic here by yourself
+        # ...
+
+    @DocumentIntelligenceAdministrationPreparer()
+    @recorded_by_proxy_async
+    async def test_list_models(self, documentintelligenceadministration_endpoint):
+        client = self.create_async_client(endpoint=documentintelligenceadministration_endpoint)
+        response = client.list_models()
+        result = [r async for r in response]
+        # please add some check logic here by yourself
+        # ...
+
+    @DocumentIntelligenceAdministrationPreparer()
+    @recorded_by_proxy_async
+    async def test_delete_model(self, documentintelligenceadministration_endpoint):
+        client = self.create_async_client(endpoint=documentintelligenceadministration_endpoint)
+        response = await client.delete_model(
+            model_id="str",
+        )
+
+        # please add some check logic here by yourself
+        # ...
+
+    @DocumentIntelligenceAdministrationPreparer()
+    @recorded_by_proxy_async
+    async def test_get_resource_details(self, documentintelligenceadministration_endpoint):
+        client = self.create_async_client(endpoint=documentintelligenceadministration_endpoint)
+        response = await client.get_resource_details()
+
+        # please add some check logic here by yourself
+        # ...
+
+    @DocumentIntelligenceAdministrationPreparer()
+    @recorded_by_proxy_async
+    async def test_get_operation(self, documentintelligenceadministration_endpoint):
+        client = self.create_async_client(endpoint=documentintelligenceadministration_endpoint)
+        response = await client.get_operation(
+            operation_id="str",
+        )
+
+        # please add some check logic here by yourself
+        # ...
+
+    @DocumentIntelligenceAdministrationPreparer()
+    @recorded_by_proxy_async
+    async def test_list_operations(self, documentintelligenceadministration_endpoint):
+        client = self.create_async_client(endpoint=documentintelligenceadministration_endpoint)
+        response = client.list_operations()
+        result = [r async for r in response]
+        # please add some check logic here by yourself
+        # ...
+
+    @DocumentIntelligenceAdministrationPreparer()
+    @recorded_by_proxy_async
+    async def test_begin_build_classifier(self, documentintelligenceadministration_endpoint):
+        client = self.create_async_client(endpoint=documentintelligenceadministration_endpoint)
+        response = await (
+            await client.begin_build_classifier(
+                body={
+                    "classifierId": "str",
+                    "docTypes": {
+                        "str": {
+                            "azureBlobFileListSource": {"containerUrl": "str", "fileList": "str"},
+                            "azureBlobSource": {"containerUrl": "str", "prefix": "str"},
+                            "sourceKind": "str",
+                        }
+                    },
+                    "allowOverwrite": bool,
+                    "baseClassifierId": "str",
+                    "description": "str",
+                },
+            )
+        ).result()  # call '.result()' to poll until service return final result
+
+        # please add some check logic here by yourself
+        # ...
+
+    @DocumentIntelligenceAdministrationPreparer()
+    @recorded_by_proxy_async
+    async def test_authorize_classifier_copy(self, documentintelligenceadministration_endpoint):
+        client = self.create_async_client(endpoint=documentintelligenceadministration_endpoint)
+        response = await client.authorize_classifier_copy(
+            body={"classifierId": "str", "description": "str", "tags": {"str": "str"}},
+        )
+
+        # please add some check logic here by yourself
+        # ...
+
+    @DocumentIntelligenceAdministrationPreparer()
+    @recorded_by_proxy_async
+    async def test_begin_copy_classifier_to(self, documentintelligenceadministration_endpoint):
+        client = self.create_async_client(endpoint=documentintelligenceadministration_endpoint)
+        response = await (
+            await client.begin_copy_classifier_to(
+                classifier_id="str",
+                body={
+                    "accessToken": "str",
+                    "expirationDateTime": "2020-02-20 00:00:00",
+                    "targetClassifierId": "str",
+                    "targetClassifierLocation": "str",
+                    "targetResourceId": "str",
+                    "targetResourceRegion": "str",
+                },
+            )
+        ).result()  # call '.result()' to poll until service return final result
+
+        # please add some check logic here by yourself
+        # ...
+
+    @DocumentIntelligenceAdministrationPreparer()
+    @recorded_by_proxy_async
+    async def test_get_classifier(self, documentintelligenceadministration_endpoint):
+        client = self.create_async_client(endpoint=documentintelligenceadministration_endpoint)
+        response = await client.get_classifier(
+            classifier_id="str",
+        )
+
+        # please add some check logic here by yourself
+        # ...
+
+    @DocumentIntelligenceAdministrationPreparer()
+    @recorded_by_proxy_async
+    async def test_list_classifiers(self, documentintelligenceadministration_endpoint):
+        client = self.create_async_client(endpoint=documentintelligenceadministration_endpoint)
+        response = client.list_classifiers()
+        result = [r async for r in response]
+        # please add some check logic here by yourself
+        # ...
+
+    @DocumentIntelligenceAdministrationPreparer()
+    @recorded_by_proxy_async
+    async def test_delete_classifier(self, documentintelligenceadministration_endpoint):
+        client = self.create_async_client(endpoint=documentintelligenceadministration_endpoint)
+        response = await client.delete_classifier(
+            classifier_id="str",
+        )
+
+        # please add some check logic here by yourself
+        # ...
diff --git a/sdk/documentintelligence/azure-ai-documentintelligence/generated_tests/test_document_intelligence_async.py b/sdk/documentintelligence/azure-ai-documentintelligence/generated_tests/test_document_intelligence_async.py
new file mode 100644
index 0000000000000..8f826ada97636
--- /dev/null
+++ b/sdk/documentintelligence/azure-ai-documentintelligence/generated_tests/test_document_intelligence_async.py
@@ -0,0 +1,134 @@
+# 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.
+# Code generated by Microsoft (R) Python Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+import pytest
+from devtools_testutils.aio import recorded_by_proxy_async
+from testpreparer import DocumentIntelligencePreparer
+from testpreparer_async import DocumentIntelligenceClientTestBaseAsync
+
+
+@pytest.mark.skip("you may need to update the auto-generated test case before run it")
+class TestDocumentIntelligenceAsync(DocumentIntelligenceClientTestBaseAsync):
+    @DocumentIntelligencePreparer()
+    @recorded_by_proxy_async
+    async def test_begin_analyze_document(self, documentintelligence_endpoint):
+        client = self.create_async_client(endpoint=documentintelligence_endpoint)
+        response = await (
+            await client.begin_analyze_document(
+                model_id="str",
+                body={"base64Source": bytes("bytes", encoding="utf-8"), "urlSource": "str"},
+            )
+        ).result()  # call '.result()' to poll until service return final result
+
+        # please add some check logic here by yourself
+        # ...
+
+    @DocumentIntelligencePreparer()
+    @recorded_by_proxy_async
+    async def test_get_analyze_result_pdf(self, documentintelligence_endpoint):
+        client = self.create_async_client(endpoint=documentintelligence_endpoint)
+        response = await client.get_analyze_result_pdf(
+            model_id="str",
+            result_id="str",
+        )
+
+        # please add some check logic here by yourself
+        # ...
+
+    @DocumentIntelligencePreparer()
+    @recorded_by_proxy_async
+    async def test_get_analyze_result_figure(self, documentintelligence_endpoint):
+        client = self.create_async_client(endpoint=documentintelligence_endpoint)
+        response = await client.get_analyze_result_figure(
+            model_id="str",
+            result_id="str",
+            figure_id="str",
+        )
+
+        # please add some check logic here by yourself
+        # ...
+
+    @DocumentIntelligencePreparer()
+    @recorded_by_proxy_async
+    async def test_delete_analyze_result(self, documentintelligence_endpoint):
+        client = self.create_async_client(endpoint=documentintelligence_endpoint)
+        response = await client.delete_analyze_result(
+            model_id="str",
+            result_id="str",
+        )
+
+        # please add some check logic here by yourself
+        # ...
+
+    @DocumentIntelligencePreparer()
+    @recorded_by_proxy_async
+    async def test_begin_analyze_batch_documents(self, documentintelligence_endpoint):
+        client = self.create_async_client(endpoint=documentintelligence_endpoint)
+        response = await (
+            await client.begin_analyze_batch_documents(
+                model_id="str",
+                body={
+                    "resultContainerUrl": "str",
+                    "azureBlobFileListSource": {"containerUrl": "str", "fileList": "str"},
+                    "azureBlobSource": {"containerUrl": "str", "prefix": "str"},
+                    "overwriteExisting": bool,
+                    "resultPrefix": "str",
+                },
+            )
+        ).result()  # call '.result()' to poll until service return final result
+
+        # please add some check logic here by yourself
+        # ...
+
+    @DocumentIntelligencePreparer()
+    @recorded_by_proxy_async
+    async def test_list_analyze_batch_results(self, documentintelligence_endpoint):
+        client = self.create_async_client(endpoint=documentintelligence_endpoint)
+        response = client.list_analyze_batch_results(
+            model_id="str",
+        )
+        result = [r async for r in response]
+        # please add some check logic here by yourself
+        # ...
+
+    @DocumentIntelligencePreparer()
+    @recorded_by_proxy_async
+    async def test_delete_analyze_batch_result(self, documentintelligence_endpoint):
+        client = self.create_async_client(endpoint=documentintelligence_endpoint)
+        response = await client.delete_analyze_batch_result(
+            model_id="str",
+            result_id="str",
+        )
+
+        # please add some check logic here by yourself
+        # ...
+
+    @DocumentIntelligencePreparer()
+    @recorded_by_proxy_async
+    async def test_get_analyze_batch_result(self, documentintelligence_endpoint):
+        client = self.create_async_client(endpoint=documentintelligence_endpoint)
+        response = await client.get_analyze_batch_result(
+            model_id="str",
+            result_id="str",
+        )
+
+        # please add some check logic here by yourself
+        # ...
+
+    @DocumentIntelligencePreparer()
+    @recorded_by_proxy_async
+    async def test_begin_classify_document(self, documentintelligence_endpoint):
+        client = self.create_async_client(endpoint=documentintelligence_endpoint)
+        response = await (
+            await client.begin_classify_document(
+                classifier_id="str",
+                body={"base64Source": bytes("bytes", encoding="utf-8"), "urlSource": "str"},
+            )
+        ).result()  # call '.result()' to poll until service return final result
+
+        # please add some check logic here by yourself
+        # ...
diff --git a/sdk/documentintelligence/azure-ai-documentintelligence/generated_tests/testpreparer.py b/sdk/documentintelligence/azure-ai-documentintelligence/generated_tests/testpreparer.py
new file mode 100644
index 0000000000000..ed3b18488bf5d
--- /dev/null
+++ b/sdk/documentintelligence/azure-ai-documentintelligence/generated_tests/testpreparer.py
@@ -0,0 +1,46 @@
+# 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.
+# Code generated by Microsoft (R) Python Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+from azure.ai.documentintelligence import DocumentIntelligenceAdministrationClient, DocumentIntelligenceClient
+from devtools_testutils import AzureRecordedTestCase, PowerShellPreparer
+import functools
+
+
+class DocumentIntelligenceClientTestBase(AzureRecordedTestCase):
+
+    def create_client(self, endpoint):
+        credential = self.get_credential(DocumentIntelligenceClient)
+        return self.create_client_from_credential(
+            DocumentIntelligenceClient,
+            credential=credential,
+            endpoint=endpoint,
+        )
+
+
+DocumentIntelligencePreparer = functools.partial(
+    PowerShellPreparer,
+    "documentintelligence",
+    documentintelligence_endpoint="https://fake_documentintelligence_endpoint.com",
+)
+
+
+class DocumentIntelligenceAdministrationClientTestBase(AzureRecordedTestCase):
+
+    def create_client(self, endpoint):
+        credential = self.get_credential(DocumentIntelligenceAdministrationClient)
+        return self.create_client_from_credential(
+            DocumentIntelligenceAdministrationClient,
+            credential=credential,
+            endpoint=endpoint,
+        )
+
+
+DocumentIntelligenceAdministrationPreparer = functools.partial(
+    PowerShellPreparer,
+    "documentintelligenceadministration",
+    documentintelligenceadministration_endpoint="https://fake_documentintelligenceadministration_endpoint.com",
+)
diff --git a/sdk/documentintelligence/azure-ai-documentintelligence/generated_tests/testpreparer_async.py b/sdk/documentintelligence/azure-ai-documentintelligence/generated_tests/testpreparer_async.py
new file mode 100644
index 0000000000000..fece6c220e812
--- /dev/null
+++ b/sdk/documentintelligence/azure-ai-documentintelligence/generated_tests/testpreparer_async.py
@@ -0,0 +1,31 @@
+# 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.
+# Code generated by Microsoft (R) Python Code Generator.
+# Changes may cause incorrect behavior and will be lost if the code is regenerated.
+# --------------------------------------------------------------------------
+from azure.ai.documentintelligence.aio import DocumentIntelligenceAdministrationClient, DocumentIntelligenceClient
+from devtools_testutils import AzureRecordedTestCase
+
+
+class DocumentIntelligenceClientTestBaseAsync(AzureRecordedTestCase):
+
+    def create_async_client(self, endpoint):
+        credential = self.get_credential(DocumentIntelligenceClient, is_async=True)
+        return self.create_client_from_credential(
+            DocumentIntelligenceClient,
+            credential=credential,
+            endpoint=endpoint,
+        )
+
+
+class DocumentIntelligenceAdministrationClientTestBaseAsync(AzureRecordedTestCase):
+
+    def create_async_client(self, endpoint):
+        credential = self.get_credential(DocumentIntelligenceAdministrationClient, is_async=True)
+        return self.create_client_from_credential(
+            DocumentIntelligenceAdministrationClient,
+            credential=credential,
+            endpoint=endpoint,
+        )
diff --git a/sdk/documentintelligence/azure-ai-documentintelligence/sdk_packaging.toml b/sdk/documentintelligence/azure-ai-documentintelligence/sdk_packaging.toml
new file mode 100644
index 0000000000000..e7687fdae93bc
--- /dev/null
+++ b/sdk/documentintelligence/azure-ai-documentintelligence/sdk_packaging.toml
@@ -0,0 +1,2 @@
+[packaging]
+auto_update = false
\ No newline at end of file
diff --git a/sdk/documentintelligence/azure-ai-documentintelligence/setup.py b/sdk/documentintelligence/azure-ai-documentintelligence/setup.py
index 2eddf25a28820..efc94a2193752 100644
--- a/sdk/documentintelligence/azure-ai-documentintelligence/setup.py
+++ b/sdk/documentintelligence/azure-ai-documentintelligence/setup.py
@@ -38,7 +38,7 @@
     url="https://github.com/Azure/azure-sdk-for-python/tree/main/sdk",
     keywords="azure, azure sdk",
     classifiers=[
-        "Development Status :: 4 - Beta",
+        "Development Status :: 5 - Production/Stable",
         "Programming Language :: Python",
         "Programming Language :: Python :: 3 :: Only",
         "Programming Language :: Python :: 3",
diff --git a/sdk/documentintelligence/azure-ai-documentintelligence/tsp-location.yaml b/sdk/documentintelligence/azure-ai-documentintelligence/tsp-location.yaml
index 18b1c4b0e7f44..d53a49cb26250 100644
--- a/sdk/documentintelligence/azure-ai-documentintelligence/tsp-location.yaml
+++ b/sdk/documentintelligence/azure-ai-documentintelligence/tsp-location.yaml
@@ -1,4 +1,4 @@
 directory: specification/ai/DocumentIntelligence
-commit: ec2a81edaecf3970e5938936e8256759905163e6
-additionalDirectories: []
+commit: dd0459d5a8d99b8a15dcbc33fd5b7befe5494897
 repo: Azure/azure-rest-api-specs
+additionalDirectories: