diff --git a/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/CHANGELOG.md b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/CHANGELOG.md
new file mode 100644
index 000000000000..628743d283a9
--- /dev/null
+++ b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/CHANGELOG.md
@@ -0,0 +1,5 @@
+# Release History
+
+## 1.0.0b1 (1970-01-01)
+
+- Initial version
diff --git a/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/LICENSE b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/LICENSE
new file mode 100644
index 000000000000..63447fd8bbbf
--- /dev/null
+++ b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/LICENSE
@@ -0,0 +1,21 @@
+Copyright (c) Microsoft Corporation.
+
+MIT License
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED *AS IS*, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.
\ No newline at end of file
diff --git a/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/MANIFEST.in b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/MANIFEST.in
new file mode 100644
index 000000000000..38f1d18da062
--- /dev/null
+++ b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/MANIFEST.in
@@ -0,0 +1,5 @@
+include *.md
+include LICENSE
+include Azure.AI.Language.Authoring.Analyzeconversations/py.typed
+recursive-include tests *.py
+recursive-include samples *.py *.md
\ No newline at end of file
diff --git a/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/README.md b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/README.md
new file mode 100644
index 000000000000..1b5363f2af9d
--- /dev/null
+++ b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/README.md
@@ -0,0 +1,45 @@
+
+
+# Azure AI Language Authoring Analyzeconversations client library for Python
+
+
+## Getting started
+
+### Install the package
+
+```bash
+python -m pip install Azure.AI.Language.Authoring.Analyzeconversations
+```
+
+#### Prequisites
+
+- Python 3.8 or later is required to use this package.
+- You need an [Azure subscription][azure_sub] to use this package.
+- An existing Azure AI Language Authoring Analyzeconversations instance.
+
+## Contributing
+
+This project welcomes contributions and suggestions. Most contributions require
+you to agree to a Contributor License Agreement (CLA) declaring that you have
+the right to, and actually do, grant us the rights to use your contribution.
+For details, visit https://cla.microsoft.com.
+
+When you submit a pull request, a CLA-bot will automatically determine whether
+you need to provide a CLA and decorate the PR appropriately (e.g., label,
+comment). Simply follow the instructions provided by the bot. You will only
+need to do this once across all repos using our CLA.
+
+This project has adopted the
+[Microsoft Open Source Code of Conduct][code_of_conduct]. For more information,
+see the Code of Conduct FAQ or contact opencode@microsoft.com with any
+additional questions or comments.
+
+
+[code_of_conduct]: https://opensource.microsoft.com/codeofconduct/
+[authenticate_with_token]: https://docs.microsoft.com/azure/cognitive-services/authentication?tabs=powershell#authenticate-with-an-authentication-token
+[azure_identity_credentials]: https://github.com/Azure/azure-sdk-for-python/tree/main/sdk/identity/azure-identity#credentials
+[azure_identity_pip]: https://pypi.org/project/azure-identity/
+[default_azure_credential]: https://github.com/Azure/azure-sdk-for-python/tree/main/sdk/identity/azure-identity#defaultazurecredential
+[pip]: https://pypi.org/project/pip/
+[azure_sub]: https://azure.microsoft.com/free/
+
diff --git a/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/__init__.py b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/__init__.py
new file mode 100644
index 000000000000..d55ccad1f573
--- /dev/null
+++ b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/__init__.py
@@ -0,0 +1 @@
+__path__ = __import__("pkgutil").extend_path(__path__, __name__) # type: ignore
diff --git a/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/__init__.py b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/__init__.py
new file mode 100644
index 000000000000..d55ccad1f573
--- /dev/null
+++ b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/__init__.py
@@ -0,0 +1 @@
+__path__ = __import__("pkgutil").extend_path(__path__, __name__) # type: ignore
diff --git a/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/__init__.py b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/__init__.py
new file mode 100644
index 000000000000..d55ccad1f573
--- /dev/null
+++ b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/__init__.py
@@ -0,0 +1 @@
+__path__ = __import__("pkgutil").extend_path(__path__, __name__) # type: ignore
diff --git a/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/__init__.py b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/__init__.py
new file mode 100644
index 000000000000..d55ccad1f573
--- /dev/null
+++ b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/__init__.py
@@ -0,0 +1 @@
+__path__ = __import__("pkgutil").extend_path(__path__, __name__) # type: ignore
diff --git a/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/__init__.py b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/__init__.py
new file mode 100644
index 000000000000..ba4b19eb6e12
--- /dev/null
+++ b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/__init__.py
@@ -0,0 +1,26 @@
+# 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 ._client import ConversationsClient
+from ._version import VERSION
+
+__version__ = VERSION
+
+try:
+ from ._patch import __all__ as _patch_all
+ from ._patch import * # pylint: disable=unused-wildcard-import
+except ImportError:
+ _patch_all = []
+from ._patch import patch_sdk as _patch_sdk
+
+__all__ = [
+ "ConversationsClient",
+]
+__all__.extend([p for p in _patch_all if p not in __all__]) # pyright: ignore
+
+_patch_sdk()
diff --git a/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/_client.py b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/_client.py
new file mode 100644
index 000000000000..8518aef8ea2d
--- /dev/null
+++ b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/_client.py
@@ -0,0 +1,130 @@
+# 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 copy import deepcopy
+from typing import Any, TYPE_CHECKING, Union
+from typing_extensions import Self
+
+from azure.core import PipelineClient
+from azure.core.credentials import AzureKeyCredential
+from azure.core.pipeline import policies
+from azure.core.rest import HttpRequest, HttpResponse
+
+from ._configuration import ConversationsClientConfiguration
+from ._serialization import Deserializer, Serializer
+from .operations import ConversationalAnalysisAuthoringOperations
+
+if TYPE_CHECKING:
+ from azure.core.credentials import TokenCredential
+
+
+class ConversationsClient:
+ """The language service API is a suite of natural language processing (NLP) skills
+ built with best-in-class Microsoft machine learning algorithms. The API can be
+ used to analyze unstructured text for tasks such as sentiment analysis, key
+ phrase extraction, language detection and question answering. Further
+ documentation can be found in :code:`https://docs.microsoft.com/en-us/azure/cognitive-services/language-service/overview`.The
+ language service conversations API is a suite of natural language processing (NLP) skills that
+ can be used to analyze structured conversations (textual or spoken). The synchronous API in
+ this suite accepts a request and mediates among multiple language projects, such as LUIS
+ Generally Available, Question Answering, Conversational Language Understanding, and then calls
+ the best candidate service to handle the request. At last, it returns a response with the
+ candidate service's response as a payload.\\n\\n In some cases, this API needs to forward
+ requests and responses between the caller and an upstream service. The asynchronous APIs in
+ this suite enable tasks like Conversation Summarization and Conversational PII detection.
+
+ :ivar conversational_analysis_authoring: ConversationalAnalysisAuthoringOperations operations
+ :vartype conversational_analysis_authoring:
+ azure.ai.language.authoring.analyzeconversations.operations.ConversationalAnalysisAuthoringOperations
+ :param endpoint: Supported Cognitive Services endpoint (e.g.,
+ https://:code:``.api.cognitiveservices.azure.com). Required.
+ :type endpoint: str
+ :param endpoint: Required.
+ :type endpoint: str
+ :param credential: Credential used to authenticate requests to the service. 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
+ "2023-04-15-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, endpoint: str, credential: Union[AzureKeyCredential, "TokenCredential"], **kwargs: Any
+ ) -> None:
+ _endpoint = "{Endpoint}/language"
+ self._config = ConversationsClientConfiguration(
+ endpoint=endpoint, endpoint=endpoint, credential=credential, **kwargs
+ )
+ _policies = kwargs.pop("policies", None)
+ if _policies is None:
+ _policies = [
+ policies.RequestIdPolicy(**kwargs),
+ self._config.headers_policy,
+ self._config.user_agent_policy,
+ self._config.proxy_policy,
+ policies.ContentDecodePolicy(**kwargs),
+ self._config.redirect_policy,
+ self._config.retry_policy,
+ self._config.authentication_policy,
+ self._config.custom_hook_policy,
+ self._config.logging_policy,
+ policies.DistributedTracingPolicy(**kwargs),
+ policies.SensitiveHeaderCleanupPolicy(**kwargs) if self._config.redirect_policy else None,
+ self._config.http_logging_policy,
+ ]
+ self._client: PipelineClient = PipelineClient(base_url=_endpoint, policies=_policies, **kwargs)
+
+ self._serialize = Serializer()
+ self._deserialize = Deserializer()
+ self._serialize.client_side_validation = False
+ self.conversational_analysis_authoring = ConversationalAnalysisAuthoringOperations(
+ self._client, self._config, self._serialize, self._deserialize
+ )
+
+ def send_request(self, request: HttpRequest, *, stream: bool = False, **kwargs: Any) -> HttpResponse:
+ """Runs the network request through the client's chained policies.
+
+ >>> from azure.core.rest import HttpRequest
+ >>> request = HttpRequest("GET", "https://www.example.org/")
+
+ >>> response = client.send_request(request)
+
+
+ For more information on this code flow, see https://aka.ms/azsdk/dpcodegen/python/send_request
+
+ :param request: The network request you want to make. Required.
+ :type request: ~azure.core.rest.HttpRequest
+ :keyword bool stream: Whether the response payload will be streamed. Defaults to False.
+ :return: The response of your network call. Does not do error handling on your response.
+ :rtype: ~azure.core.rest.HttpResponse
+ """
+
+ request_copy = deepcopy(request)
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+
+ request_copy.url = self._client.format_url(request_copy.url, **path_format_arguments)
+ return self._client.send_request(request_copy, stream=stream, **kwargs) # type: ignore
+
+ def close(self) -> None:
+ self._client.close()
+
+ def __enter__(self) -> Self:
+ self._client.__enter__()
+ return self
+
+ def __exit__(self, *exc_details: Any) -> None:
+ self._client.__exit__(*exc_details)
diff --git a/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/_configuration.py b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/_configuration.py
new file mode 100644
index 000000000000..8870d17f9a51
--- /dev/null
+++ b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/_configuration.py
@@ -0,0 +1,80 @@
+# 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 typing import Any, TYPE_CHECKING, Union
+
+from azure.core.credentials import AzureKeyCredential
+from azure.core.pipeline import policies
+
+from ._version import VERSION
+
+if TYPE_CHECKING:
+ from azure.core.credentials import TokenCredential
+
+
+class ConversationsClientConfiguration: # pylint: disable=too-many-instance-attributes
+ """Configuration for ConversationsClient.
+
+ Note that all parameters used to create this instance are saved as instance
+ attributes.
+
+ :param endpoint: Supported Cognitive Services endpoint (e.g.,
+ https://:code:``.api.cognitiveservices.azure.com). Required.
+ :type endpoint: str
+ :param endpoint: Required.
+ :type endpoint: str
+ :param credential: Credential used to authenticate requests to the service. 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
+ "2023-04-15-preview". Note that overriding this default value may result in unsupported
+ behavior.
+ :paramtype api_version: str
+ """
+
+ def __init__(
+ self, endpoint: str, endpoint: str, credential: Union[AzureKeyCredential, "TokenCredential"], **kwargs: Any
+ ) -> None:
+ api_version: str = kwargs.pop("api_version", "2023-04-15-preview")
+
+ if endpoint is None:
+ raise ValueError("Parameter 'endpoint' must not be None.")
+ if endpoint is None:
+ raise ValueError("Parameter 'endpoint' must not be None.")
+ if credential is None:
+ raise ValueError("Parameter 'credential' must not be None.")
+
+ self.endpoint = endpoint
+ self.endpoint = endpoint
+ self.credential = credential
+ self.api_version = api_version
+ self.credential_scopes = kwargs.pop("credential_scopes", ["https://cognitiveservices.azure.com/.default"])
+ kwargs.setdefault("sdk_moniker", "Azure.AI.Language.Authoring.Analyzeconversations/{}".format(VERSION))
+ self.polling_interval = kwargs.get("polling_interval", 30)
+ self._configure(**kwargs)
+
+ def _infer_policy(self, **kwargs):
+ if isinstance(self.credential, AzureKeyCredential):
+ return policies.AzureKeyCredentialPolicy(self.credential, "Ocp-Apim-Subscription-Key", **kwargs)
+ if hasattr(self.credential, "get_token"):
+ return policies.BearerTokenCredentialPolicy(self.credential, *self.credential_scopes, **kwargs)
+ raise TypeError(f"Unsupported credential: {self.credential}")
+
+ def _configure(self, **kwargs: Any) -> None:
+ self.user_agent_policy = kwargs.get("user_agent_policy") or policies.UserAgentPolicy(**kwargs)
+ self.headers_policy = kwargs.get("headers_policy") or policies.HeadersPolicy(**kwargs)
+ self.proxy_policy = kwargs.get("proxy_policy") or policies.ProxyPolicy(**kwargs)
+ self.logging_policy = kwargs.get("logging_policy") or policies.NetworkTraceLoggingPolicy(**kwargs)
+ self.http_logging_policy = kwargs.get("http_logging_policy") or policies.HttpLoggingPolicy(**kwargs)
+ self.custom_hook_policy = kwargs.get("custom_hook_policy") or policies.CustomHookPolicy(**kwargs)
+ self.redirect_policy = kwargs.get("redirect_policy") or policies.RedirectPolicy(**kwargs)
+ self.retry_policy = kwargs.get("retry_policy") or policies.RetryPolicy(**kwargs)
+ self.authentication_policy = kwargs.get("authentication_policy")
+ if self.credential and not self.authentication_policy:
+ self.authentication_policy = self._infer_policy(**kwargs)
diff --git a/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/_model_base.py b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/_model_base.py
new file mode 100644
index 000000000000..9d401b0cf012
--- /dev/null
+++ b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/_model_base.py
@@ -0,0 +1,1159 @@
+# pylint: disable=too-many-lines
+# 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.
+# --------------------------------------------------------------------------
+# pylint: disable=protected-access, arguments-differ, signature-differs, broad-except, too-many-lines
+
+import copy
+import calendar
+import decimal
+import functools
+import sys
+import logging
+import base64
+import re
+import typing
+import enum
+import email.utils
+from datetime import datetime, date, time, timedelta, timezone
+from json import JSONEncoder
+import xml.etree.ElementTree as ET
+from typing_extensions import Self
+import isodate
+from azure.core.exceptions import DeserializationError
+from azure.core import CaseInsensitiveEnumMeta
+from azure.core.pipeline import PipelineResponse
+from azure.core.serialization import _Null
+
+if sys.version_info >= (3, 9):
+ from collections.abc import MutableMapping
+else:
+ from typing import MutableMapping
+
+_LOGGER = logging.getLogger(__name__)
+
+__all__ = ["SdkJSONEncoder", "Model", "rest_field", "rest_discriminator"]
+
+TZ_UTC = timezone.utc
+_T = typing.TypeVar("_T")
+
+
+def _timedelta_as_isostr(td: timedelta) -> str:
+ """Converts a datetime.timedelta object into an ISO 8601 formatted string, e.g. 'P4DT12H30M05S'
+
+ Function adapted from the Tin Can Python project: https://github.com/RusticiSoftware/TinCanPython
+
+ :param timedelta td: The timedelta to convert
+ :rtype: str
+ :return: ISO8601 version of this timedelta
+ """
+
+ # Split seconds to larger units
+ seconds = td.total_seconds()
+ minutes, seconds = divmod(seconds, 60)
+ hours, minutes = divmod(minutes, 60)
+ days, hours = divmod(hours, 24)
+
+ days, hours, minutes = list(map(int, (days, hours, minutes)))
+ seconds = round(seconds, 6)
+
+ # Build date
+ date_str = ""
+ if days:
+ date_str = "%sD" % days
+
+ if hours or minutes or seconds:
+ # Build time
+ time_str = "T"
+
+ # Hours
+ bigger_exists = date_str or hours
+ if bigger_exists:
+ time_str += "{:02}H".format(hours)
+
+ # Minutes
+ bigger_exists = bigger_exists or minutes
+ if bigger_exists:
+ time_str += "{:02}M".format(minutes)
+
+ # Seconds
+ try:
+ if seconds.is_integer():
+ seconds_string = "{:02}".format(int(seconds))
+ else:
+ # 9 chars long w/ leading 0, 6 digits after decimal
+ seconds_string = "%09.6f" % seconds
+ # Remove trailing zeros
+ seconds_string = seconds_string.rstrip("0")
+ except AttributeError: # int.is_integer() raises
+ seconds_string = "{:02}".format(seconds)
+
+ time_str += "{}S".format(seconds_string)
+ else:
+ time_str = ""
+
+ return "P" + date_str + time_str
+
+
+def _serialize_bytes(o, format: typing.Optional[str] = None) -> str:
+ encoded = base64.b64encode(o).decode()
+ if format == "base64url":
+ return encoded.strip("=").replace("+", "-").replace("/", "_")
+ return encoded
+
+
+def _serialize_datetime(o, format: typing.Optional[str] = None):
+ if hasattr(o, "year") and hasattr(o, "hour"):
+ if format == "rfc7231":
+ return email.utils.format_datetime(o, usegmt=True)
+ if format == "unix-timestamp":
+ return int(calendar.timegm(o.utctimetuple()))
+
+ # astimezone() fails for naive times in Python 2.7, so make make sure o is aware (tzinfo is set)
+ if not o.tzinfo:
+ iso_formatted = o.replace(tzinfo=TZ_UTC).isoformat()
+ else:
+ iso_formatted = o.astimezone(TZ_UTC).isoformat()
+ # Replace the trailing "+00:00" UTC offset with "Z" (RFC 3339: https://www.ietf.org/rfc/rfc3339.txt)
+ return iso_formatted.replace("+00:00", "Z")
+ # Next try datetime.date or datetime.time
+ return o.isoformat()
+
+
+def _is_readonly(p):
+ try:
+ return p._visibility == ["read"]
+ except AttributeError:
+ return False
+
+
+class SdkJSONEncoder(JSONEncoder):
+ """A JSON encoder that's capable of serializing datetime objects and bytes."""
+
+ def __init__(self, *args, exclude_readonly: bool = False, format: typing.Optional[str] = None, **kwargs):
+ super().__init__(*args, **kwargs)
+ self.exclude_readonly = exclude_readonly
+ self.format = format
+
+ def default(self, o): # pylint: disable=too-many-return-statements
+ if _is_model(o):
+ if self.exclude_readonly:
+ readonly_props = [p._rest_name for p in o._attr_to_rest_field.values() if _is_readonly(p)]
+ return {k: v for k, v in o.items() if k not in readonly_props}
+ return dict(o.items())
+ try:
+ return super(SdkJSONEncoder, self).default(o)
+ except TypeError:
+ if isinstance(o, _Null):
+ return None
+ if isinstance(o, decimal.Decimal):
+ return float(o)
+ if isinstance(o, (bytes, bytearray)):
+ return _serialize_bytes(o, self.format)
+ try:
+ # First try datetime.datetime
+ return _serialize_datetime(o, self.format)
+ except AttributeError:
+ pass
+ # Last, try datetime.timedelta
+ try:
+ return _timedelta_as_isostr(o)
+ except AttributeError:
+ # This will be raised when it hits value.total_seconds in the method above
+ pass
+ return super(SdkJSONEncoder, self).default(o)
+
+
+_VALID_DATE = re.compile(r"\d{4}[-]\d{2}[-]\d{2}T\d{2}:\d{2}:\d{2}" + r"\.?\d*Z?[-+]?[\d{2}]?:?[\d{2}]?")
+_VALID_RFC7231 = re.compile(
+ r"(Mon|Tue|Wed|Thu|Fri|Sat|Sun),\s\d{2}\s"
+ r"(Jan|Feb|Mar|Apr|May|Jun|Jul|Aug|Sep|Oct|Nov|Dec)\s\d{4}\s\d{2}:\d{2}:\d{2}\sGMT"
+)
+
+
+def _deserialize_datetime(attr: typing.Union[str, datetime]) -> datetime:
+ """Deserialize ISO-8601 formatted string into Datetime object.
+
+ :param str attr: response string to be deserialized.
+ :rtype: ~datetime.datetime
+ :returns: The datetime object from that input
+ """
+ if isinstance(attr, datetime):
+ # i'm already deserialized
+ return attr
+ attr = attr.upper()
+ match = _VALID_DATE.match(attr)
+ if not match:
+ raise ValueError("Invalid datetime string: " + attr)
+
+ check_decimal = attr.split(".")
+ if len(check_decimal) > 1:
+ decimal_str = ""
+ for digit in check_decimal[1]:
+ if digit.isdigit():
+ decimal_str += digit
+ else:
+ break
+ if len(decimal_str) > 6:
+ attr = attr.replace(decimal_str, decimal_str[0:6])
+
+ date_obj = isodate.parse_datetime(attr)
+ test_utc = date_obj.utctimetuple()
+ if test_utc.tm_year > 9999 or test_utc.tm_year < 1:
+ raise OverflowError("Hit max or min date")
+ return date_obj
+
+
+def _deserialize_datetime_rfc7231(attr: typing.Union[str, datetime]) -> datetime:
+ """Deserialize RFC7231 formatted string into Datetime object.
+
+ :param str attr: response string to be deserialized.
+ :rtype: ~datetime.datetime
+ :returns: The datetime object from that input
+ """
+ if isinstance(attr, datetime):
+ # i'm already deserialized
+ return attr
+ match = _VALID_RFC7231.match(attr)
+ if not match:
+ raise ValueError("Invalid datetime string: " + attr)
+
+ return email.utils.parsedate_to_datetime(attr)
+
+
+def _deserialize_datetime_unix_timestamp(attr: typing.Union[float, datetime]) -> datetime:
+ """Deserialize unix timestamp into Datetime object.
+
+ :param str attr: response string to be deserialized.
+ :rtype: ~datetime.datetime
+ :returns: The datetime object from that input
+ """
+ if isinstance(attr, datetime):
+ # i'm already deserialized
+ return attr
+ return datetime.fromtimestamp(attr, TZ_UTC)
+
+
+def _deserialize_date(attr: typing.Union[str, date]) -> date:
+ """Deserialize ISO-8601 formatted string into Date object.
+ :param str attr: response string to be deserialized.
+ :rtype: date
+ :returns: The date object from that input
+ """
+ # This must NOT use defaultmonth/defaultday. Using None ensure this raises an exception.
+ if isinstance(attr, date):
+ return attr
+ return isodate.parse_date(attr, defaultmonth=None, defaultday=None) # type: ignore
+
+
+def _deserialize_time(attr: typing.Union[str, time]) -> time:
+ """Deserialize ISO-8601 formatted string into time object.
+
+ :param str attr: response string to be deserialized.
+ :rtype: datetime.time
+ :returns: The time object from that input
+ """
+ if isinstance(attr, time):
+ return attr
+ return isodate.parse_time(attr)
+
+
+def _deserialize_bytes(attr):
+ if isinstance(attr, (bytes, bytearray)):
+ return attr
+ return bytes(base64.b64decode(attr))
+
+
+def _deserialize_bytes_base64(attr):
+ if isinstance(attr, (bytes, bytearray)):
+ return attr
+ padding = "=" * (3 - (len(attr) + 3) % 4) # type: ignore
+ attr = attr + padding # type: ignore
+ encoded = attr.replace("-", "+").replace("_", "/")
+ return bytes(base64.b64decode(encoded))
+
+
+def _deserialize_duration(attr):
+ if isinstance(attr, timedelta):
+ return attr
+ return isodate.parse_duration(attr)
+
+
+def _deserialize_decimal(attr):
+ if isinstance(attr, decimal.Decimal):
+ return attr
+ return decimal.Decimal(str(attr))
+
+
+def _deserialize_int_as_str(attr):
+ if isinstance(attr, int):
+ return attr
+ return int(attr)
+
+
+_DESERIALIZE_MAPPING = {
+ datetime: _deserialize_datetime,
+ date: _deserialize_date,
+ time: _deserialize_time,
+ bytes: _deserialize_bytes,
+ bytearray: _deserialize_bytes,
+ timedelta: _deserialize_duration,
+ typing.Any: lambda x: x,
+ decimal.Decimal: _deserialize_decimal,
+}
+
+_DESERIALIZE_MAPPING_WITHFORMAT = {
+ "rfc3339": _deserialize_datetime,
+ "rfc7231": _deserialize_datetime_rfc7231,
+ "unix-timestamp": _deserialize_datetime_unix_timestamp,
+ "base64": _deserialize_bytes,
+ "base64url": _deserialize_bytes_base64,
+}
+
+
+def get_deserializer(annotation: typing.Any, rf: typing.Optional["_RestField"] = None):
+ if annotation is int and rf and rf._format == "str":
+ return _deserialize_int_as_str
+ if rf and rf._format:
+ return _DESERIALIZE_MAPPING_WITHFORMAT.get(rf._format)
+ return _DESERIALIZE_MAPPING.get(annotation) # pyright: ignore
+
+
+def _get_type_alias_type(module_name: str, alias_name: str):
+ types = {
+ k: v
+ for k, v in sys.modules[module_name].__dict__.items()
+ if isinstance(v, typing._GenericAlias) # type: ignore
+ }
+ if alias_name not in types:
+ return alias_name
+ return types[alias_name]
+
+
+def _get_model(module_name: str, model_name: str):
+ models = {k: v for k, v in sys.modules[module_name].__dict__.items() if isinstance(v, type)}
+ module_end = module_name.rsplit(".", 1)[0]
+ models.update({k: v for k, v in sys.modules[module_end].__dict__.items() if isinstance(v, type)})
+ if isinstance(model_name, str):
+ model_name = model_name.split(".")[-1]
+ if model_name not in models:
+ return model_name
+ return models[model_name]
+
+
+_UNSET = object()
+
+
+class _MyMutableMapping(MutableMapping[str, typing.Any]): # pylint: disable=unsubscriptable-object
+ def __init__(self, data: typing.Dict[str, typing.Any]) -> None:
+ self._data = data
+
+ def __contains__(self, key: typing.Any) -> bool:
+ return key in self._data
+
+ def __getitem__(self, key: str) -> typing.Any:
+ return self._data.__getitem__(key)
+
+ def __setitem__(self, key: str, value: typing.Any) -> None:
+ self._data.__setitem__(key, value)
+
+ def __delitem__(self, key: str) -> None:
+ self._data.__delitem__(key)
+
+ def __iter__(self) -> typing.Iterator[typing.Any]:
+ return self._data.__iter__()
+
+ def __len__(self) -> int:
+ return self._data.__len__()
+
+ def __ne__(self, other: typing.Any) -> bool:
+ return not self.__eq__(other)
+
+ def keys(self) -> typing.KeysView[str]:
+ return self._data.keys()
+
+ def values(self) -> typing.ValuesView[typing.Any]:
+ return self._data.values()
+
+ def items(self) -> typing.ItemsView[str, typing.Any]:
+ return self._data.items()
+
+ def get(self, key: str, default: typing.Any = None) -> typing.Any:
+ try:
+ return self[key]
+ except KeyError:
+ return default
+
+ @typing.overload
+ def pop(self, key: str) -> typing.Any: ...
+
+ @typing.overload
+ def pop(self, key: str, default: _T) -> _T: ...
+
+ @typing.overload
+ def pop(self, key: str, default: typing.Any) -> typing.Any: ...
+
+ def pop(self, key: str, default: typing.Any = _UNSET) -> typing.Any:
+ if default is _UNSET:
+ return self._data.pop(key)
+ return self._data.pop(key, default)
+
+ def popitem(self) -> typing.Tuple[str, typing.Any]:
+ return self._data.popitem()
+
+ def clear(self) -> None:
+ self._data.clear()
+
+ def update(self, *args: typing.Any, **kwargs: typing.Any) -> None:
+ self._data.update(*args, **kwargs)
+
+ @typing.overload
+ def setdefault(self, key: str, default: None = None) -> None: ...
+
+ @typing.overload
+ def setdefault(self, key: str, default: typing.Any) -> typing.Any: ...
+
+ def setdefault(self, key: str, default: typing.Any = _UNSET) -> typing.Any:
+ if default is _UNSET:
+ return self._data.setdefault(key)
+ return self._data.setdefault(key, default)
+
+ def __eq__(self, other: typing.Any) -> bool:
+ try:
+ other_model = self.__class__(other)
+ except Exception:
+ return False
+ return self._data == other_model._data
+
+ def __repr__(self) -> str:
+ return str(self._data)
+
+
+def _is_model(obj: typing.Any) -> bool:
+ return getattr(obj, "_is_model", False)
+
+
+def _serialize(o, format: typing.Optional[str] = None): # pylint: disable=too-many-return-statements
+ if isinstance(o, list):
+ return [_serialize(x, format) for x in o]
+ if isinstance(o, dict):
+ return {k: _serialize(v, format) for k, v in o.items()}
+ if isinstance(o, set):
+ return {_serialize(x, format) for x in o}
+ if isinstance(o, tuple):
+ return tuple(_serialize(x, format) for x in o)
+ if isinstance(o, (bytes, bytearray)):
+ return _serialize_bytes(o, format)
+ if isinstance(o, decimal.Decimal):
+ return float(o)
+ if isinstance(o, enum.Enum):
+ return o.value
+ if isinstance(o, int):
+ if format == "str":
+ return str(o)
+ return o
+ try:
+ # First try datetime.datetime
+ return _serialize_datetime(o, format)
+ except AttributeError:
+ pass
+ # Last, try datetime.timedelta
+ try:
+ return _timedelta_as_isostr(o)
+ except AttributeError:
+ # This will be raised when it hits value.total_seconds in the method above
+ pass
+ return o
+
+
+def _get_rest_field(
+ attr_to_rest_field: typing.Dict[str, "_RestField"], rest_name: str
+) -> typing.Optional["_RestField"]:
+ try:
+ return next(rf for rf in attr_to_rest_field.values() if rf._rest_name == rest_name)
+ except StopIteration:
+ return None
+
+
+def _create_value(rf: typing.Optional["_RestField"], value: typing.Any) -> typing.Any:
+ if not rf:
+ return _serialize(value, None)
+ if rf._is_multipart_file_input:
+ return value
+ if rf._is_model:
+ return _deserialize(rf._type, value)
+ if isinstance(value, ET.Element):
+ value = _deserialize(rf._type, value)
+ return _serialize(value, rf._format)
+
+
+class Model(_MyMutableMapping):
+ _is_model = True
+ # label whether current class's _attr_to_rest_field has been calculated
+ # could not see _attr_to_rest_field directly because subclass inherits it from parent class
+ _calculated: typing.Set[str] = set()
+
+ def __init__(self, *args: typing.Any, **kwargs: typing.Any) -> None:
+ class_name = self.__class__.__name__
+ if len(args) > 1:
+ raise TypeError(f"{class_name}.__init__() takes 2 positional arguments but {len(args) + 1} were given")
+ dict_to_pass = {
+ rest_field._rest_name: rest_field._default
+ for rest_field in self._attr_to_rest_field.values()
+ if rest_field._default is not _UNSET
+ }
+ if args: # pylint: disable=too-many-nested-blocks
+ if isinstance(args[0], ET.Element):
+ existed_attr_keys = []
+ model_meta = getattr(self, "_xml", {})
+
+ for rf in self._attr_to_rest_field.values():
+ prop_meta = getattr(rf, "_xml", {})
+ xml_name = prop_meta.get("name", rf._rest_name)
+ xml_ns = prop_meta.get("ns", model_meta.get("ns", None))
+ if xml_ns:
+ xml_name = "{" + xml_ns + "}" + xml_name
+
+ # attribute
+ if prop_meta.get("attribute", False) and args[0].get(xml_name) is not None:
+ existed_attr_keys.append(xml_name)
+ dict_to_pass[rf._rest_name] = _deserialize(rf._type, args[0].get(xml_name))
+ continue
+
+ # unwrapped element is array
+ if prop_meta.get("unwrapped", False):
+ # unwrapped array could either use prop items meta/prop meta
+ if prop_meta.get("itemsName"):
+ xml_name = prop_meta.get("itemsName")
+ xml_ns = prop_meta.get("itemNs")
+ if xml_ns:
+ xml_name = "{" + xml_ns + "}" + xml_name
+ items = args[0].findall(xml_name) # pyright: ignore
+ if len(items) > 0:
+ existed_attr_keys.append(xml_name)
+ dict_to_pass[rf._rest_name] = _deserialize(rf._type, items)
+ continue
+
+ # text element is primitive type
+ if prop_meta.get("text", False):
+ if args[0].text is not None:
+ dict_to_pass[rf._rest_name] = _deserialize(rf._type, args[0].text)
+ continue
+
+ # wrapped element could be normal property or array, it should only have one element
+ item = args[0].find(xml_name)
+ if item is not None:
+ existed_attr_keys.append(xml_name)
+ dict_to_pass[rf._rest_name] = _deserialize(rf._type, item)
+
+ # rest thing is additional properties
+ for e in args[0]:
+ if e.tag not in existed_attr_keys:
+ dict_to_pass[e.tag] = _convert_element(e)
+ else:
+ dict_to_pass.update(
+ {k: _create_value(_get_rest_field(self._attr_to_rest_field, k), v) for k, v in args[0].items()}
+ )
+ else:
+ non_attr_kwargs = [k for k in kwargs if k not in self._attr_to_rest_field]
+ if non_attr_kwargs:
+ # actual type errors only throw the first wrong keyword arg they see, so following that.
+ raise TypeError(f"{class_name}.__init__() got an unexpected keyword argument '{non_attr_kwargs[0]}'")
+ dict_to_pass.update(
+ {
+ self._attr_to_rest_field[k]._rest_name: _create_value(self._attr_to_rest_field[k], v)
+ for k, v in kwargs.items()
+ if v is not None
+ }
+ )
+ super().__init__(dict_to_pass)
+
+ def copy(self) -> "Model":
+ return Model(self.__dict__)
+
+ def __new__(cls, *args: typing.Any, **kwargs: typing.Any) -> Self: # pylint: disable=unused-argument
+ 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'
+ mros = cls.__mro__[:-9][::-1] # ignore parents, and reverse the mro order
+ attr_to_rest_field: typing.Dict[str, _RestField] = { # map attribute name to rest_field property
+ k: v for mro_class in mros for k, v in mro_class.__dict__.items() if k[0] != "_" and hasattr(v, "_type")
+ }
+ 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
+ }
+ for attr, rf in attr_to_rest_field.items():
+ rf._module = cls.__module__
+ if not rf._type:
+ rf._type = rf._get_deserialize_callable_from_annotation(annotations.get(attr, None))
+ if not rf._rest_name_input:
+ rf._rest_name_input = attr
+ cls._attr_to_rest_field: typing.Dict[str, _RestField] = dict(attr_to_rest_field.items())
+ cls._calculated.add(f"{cls.__module__}.{cls.__qualname__}")
+
+ return super().__new__(cls) # pylint: disable=no-value-for-parameter
+
+ 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
+
+ @classmethod
+ def _get_discriminator(cls, exist_discriminators) -> typing.Optional["_RestField"]:
+ for v in cls.__dict__.values():
+ if isinstance(v, _RestField) and v._is_discriminator and v._rest_name not in exist_discriminators:
+ return v
+ return None
+
+ @classmethod
+ def _deserialize(cls, data, exist_discriminators):
+ if not hasattr(cls, "__mapping__"): # pylint: disable=no-member
+ return cls(data)
+ discriminator = cls._get_discriminator(exist_discriminators)
+ if discriminator is None:
+ return cls(data)
+ exist_discriminators.append(discriminator._rest_name)
+ if isinstance(data, ET.Element):
+ model_meta = getattr(cls, "_xml", {})
+ prop_meta = getattr(discriminator, "_xml", {})
+ xml_name = prop_meta.get("name", discriminator._rest_name)
+ xml_ns = prop_meta.get("ns", model_meta.get("ns", None))
+ if xml_ns:
+ xml_name = "{" + xml_ns + "}" + xml_name
+
+ if data.get(xml_name) is not None:
+ discriminator_value = data.get(xml_name)
+ else:
+ 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
+ return mapped_cls._deserialize(data, exist_discriminators)
+
+ def as_dict(self, *, exclude_readonly: bool = False) -> typing.Dict[str, typing.Any]:
+ """Return a dict that can be turned into json using json.dump.
+
+ :keyword bool exclude_readonly: Whether to remove the readonly properties.
+ :returns: A dict JSON compatible object
+ :rtype: dict
+ """
+
+ result = {}
+ readonly_props = []
+ if exclude_readonly:
+ readonly_props = [p._rest_name for p in self._attr_to_rest_field.values() if _is_readonly(p)]
+ for k, v in self.items():
+ if exclude_readonly and k in readonly_props: # pyright: ignore
+ continue
+ is_multipart_file_input = False
+ try:
+ is_multipart_file_input = next(
+ rf for rf in self._attr_to_rest_field.values() if rf._rest_name == k
+ )._is_multipart_file_input
+ except StopIteration:
+ pass
+ result[k] = v if is_multipart_file_input else Model._as_dict_value(v, exclude_readonly=exclude_readonly)
+ return result
+
+ @staticmethod
+ def _as_dict_value(v: typing.Any, exclude_readonly: bool = False) -> typing.Any:
+ if v is None or isinstance(v, _Null):
+ return None
+ if isinstance(v, (list, tuple, set)):
+ return type(v)(Model._as_dict_value(x, exclude_readonly=exclude_readonly) for x in v)
+ if isinstance(v, dict):
+ return {dk: Model._as_dict_value(dv, exclude_readonly=exclude_readonly) for dk, dv in v.items()}
+ return v.as_dict(exclude_readonly=exclude_readonly) if hasattr(v, "as_dict") else v
+
+
+def _deserialize_model(model_deserializer: typing.Optional[typing.Callable], obj):
+ if _is_model(obj):
+ return obj
+ return _deserialize(model_deserializer, obj)
+
+
+def _deserialize_with_optional(if_obj_deserializer: typing.Optional[typing.Callable], obj):
+ if obj is None:
+ return obj
+ return _deserialize_with_callable(if_obj_deserializer, obj)
+
+
+def _deserialize_with_union(deserializers, obj):
+ for deserializer in deserializers:
+ try:
+ return _deserialize(deserializer, obj)
+ except DeserializationError:
+ pass
+ raise DeserializationError()
+
+
+def _deserialize_dict(
+ value_deserializer: typing.Optional[typing.Callable],
+ module: typing.Optional[str],
+ obj: typing.Dict[typing.Any, typing.Any],
+):
+ if obj is None:
+ return obj
+ if isinstance(obj, ET.Element):
+ obj = {child.tag: child for child in obj}
+ return {k: _deserialize(value_deserializer, v, module) for k, v in obj.items()}
+
+
+def _deserialize_multiple_sequence(
+ entry_deserializers: typing.List[typing.Optional[typing.Callable]],
+ module: typing.Optional[str],
+ obj,
+):
+ if obj is None:
+ return obj
+ return type(obj)(_deserialize(deserializer, entry, module) for entry, deserializer in zip(obj, entry_deserializers))
+
+
+def _deserialize_sequence(
+ deserializer: typing.Optional[typing.Callable],
+ module: typing.Optional[str],
+ obj,
+):
+ if obj is None:
+ return obj
+ if isinstance(obj, ET.Element):
+ obj = list(obj)
+ return type(obj)(_deserialize(deserializer, entry, module) for entry in obj)
+
+
+def _sorted_annotations(types: typing.List[typing.Any]) -> typing.List[typing.Any]:
+ return sorted(
+ types,
+ key=lambda x: hasattr(x, "__name__") and x.__name__.lower() in ("str", "float", "int", "bool"),
+ )
+
+
+def _get_deserialize_callable_from_annotation( # pylint: disable=too-many-return-statements, too-many-branches
+ annotation: typing.Any,
+ module: typing.Optional[str],
+ rf: typing.Optional["_RestField"] = None,
+) -> typing.Optional[typing.Callable[[typing.Any], typing.Any]]:
+ if not annotation:
+ return None
+
+ # is it a type alias?
+ if isinstance(annotation, str):
+ if module is not None:
+ annotation = _get_type_alias_type(module, annotation)
+
+ # is it a forward ref / in quotes?
+ if isinstance(annotation, (str, typing.ForwardRef)):
+ try:
+ model_name = annotation.__forward_arg__ # type: ignore
+ except AttributeError:
+ model_name = annotation
+ if module is not None:
+ annotation = _get_model(module, model_name)
+
+ try:
+ if module and _is_model(annotation):
+ if rf:
+ rf._is_model = True
+
+ return functools.partial(_deserialize_model, annotation) # pyright: ignore
+ except Exception:
+ pass
+
+ # is it a literal?
+ try:
+ if annotation.__origin__ is typing.Literal: # pyright: ignore
+ return None
+ except AttributeError:
+ pass
+
+ # is it optional?
+ try:
+ if any(a for a in annotation.__args__ if a == type(None)): # pyright: ignore
+ if len(annotation.__args__) <= 2: # pyright: ignore
+ if_obj_deserializer = _get_deserialize_callable_from_annotation(
+ next(a for a in annotation.__args__ if a != type(None)), module, rf # pyright: ignore
+ )
+
+ return functools.partial(_deserialize_with_optional, if_obj_deserializer)
+ # the type is Optional[Union[...]], we need to remove the None type from the Union
+ annotation_copy = copy.copy(annotation)
+ annotation_copy.__args__ = [a for a in annotation_copy.__args__ if a != type(None)] # pyright: ignore
+ return _get_deserialize_callable_from_annotation(annotation_copy, module, rf)
+ except AttributeError:
+ pass
+
+ # is it union?
+ if getattr(annotation, "__origin__", None) is typing.Union:
+ # initial ordering is we make `string` the last deserialization option, because it is often them most generic
+ deserializers = [
+ _get_deserialize_callable_from_annotation(arg, module, rf)
+ for arg in _sorted_annotations(annotation.__args__) # pyright: ignore
+ ]
+
+ return functools.partial(_deserialize_with_union, deserializers)
+
+ try:
+ if annotation._name == "Dict": # pyright: ignore
+ value_deserializer = _get_deserialize_callable_from_annotation(
+ annotation.__args__[1], module, rf # pyright: ignore
+ )
+
+ return functools.partial(
+ _deserialize_dict,
+ value_deserializer,
+ module,
+ )
+ except (AttributeError, IndexError):
+ pass
+ try:
+ if annotation._name in ["List", "Set", "Tuple", "Sequence"]: # pyright: ignore
+ if len(annotation.__args__) > 1: # pyright: ignore
+ entry_deserializers = [
+ _get_deserialize_callable_from_annotation(dt, module, rf)
+ for dt in annotation.__args__ # pyright: ignore
+ ]
+ return functools.partial(_deserialize_multiple_sequence, entry_deserializers, module)
+ deserializer = _get_deserialize_callable_from_annotation(
+ annotation.__args__[0], module, rf # pyright: ignore
+ )
+
+ return functools.partial(_deserialize_sequence, deserializer, module)
+ except (TypeError, IndexError, AttributeError, SyntaxError):
+ pass
+
+ def _deserialize_default(
+ deserializer,
+ obj,
+ ):
+ if obj is None:
+ return obj
+ try:
+ return _deserialize_with_callable(deserializer, obj)
+ except Exception:
+ pass
+ return obj
+
+ if get_deserializer(annotation, rf):
+ return functools.partial(_deserialize_default, get_deserializer(annotation, rf))
+
+ return functools.partial(_deserialize_default, annotation)
+
+
+def _deserialize_with_callable(
+ deserializer: typing.Optional[typing.Callable[[typing.Any], typing.Any]],
+ value: typing.Any,
+): # pylint: disable=too-many-return-statements
+ try:
+ if value is None or isinstance(value, _Null):
+ return None
+ if isinstance(value, ET.Element):
+ if deserializer is str:
+ return value.text or ""
+ if deserializer is int:
+ return int(value.text) if value.text else None
+ if deserializer is float:
+ return float(value.text) if value.text else None
+ if deserializer is bool:
+ return value.text == "true" if value.text else None
+ if deserializer is None:
+ return value
+ if deserializer in [int, float, bool]:
+ return deserializer(value)
+ if isinstance(deserializer, CaseInsensitiveEnumMeta):
+ try:
+ return deserializer(value)
+ except ValueError:
+ # for unknown value, return raw value
+ return value
+ if isinstance(deserializer, type) and issubclass(deserializer, Model):
+ return deserializer._deserialize(value, [])
+ return typing.cast(typing.Callable[[typing.Any], typing.Any], deserializer)(value)
+ except Exception as e:
+ raise DeserializationError() from e
+
+
+def _deserialize(
+ deserializer: typing.Any,
+ value: typing.Any,
+ module: typing.Optional[str] = None,
+ rf: typing.Optional["_RestField"] = None,
+ format: typing.Optional[str] = None,
+) -> typing.Any:
+ if isinstance(value, PipelineResponse):
+ value = value.http_response.json()
+ if rf is None and format:
+ rf = _RestField(format=format)
+ if not isinstance(deserializer, functools.partial):
+ deserializer = _get_deserialize_callable_from_annotation(deserializer, module, rf)
+ return _deserialize_with_callable(deserializer, value)
+
+
+class _RestField:
+ def __init__(
+ self,
+ *,
+ name: typing.Optional[str] = None,
+ type: typing.Optional[typing.Callable] = None, # pylint: disable=redefined-builtin
+ is_discriminator: bool = False,
+ visibility: typing.Optional[typing.List[str]] = None,
+ default: typing.Any = _UNSET,
+ format: typing.Optional[str] = None,
+ is_multipart_file_input: bool = False,
+ xml: typing.Optional[typing.Dict[str, typing.Any]] = None,
+ ):
+ self._type = type
+ self._rest_name_input = name
+ self._module: typing.Optional[str] = None
+ self._is_discriminator = is_discriminator
+ self._visibility = visibility
+ self._is_model = False
+ self._default = default
+ self._format = format
+ self._is_multipart_file_input = is_multipart_file_input
+ self._xml = xml if xml is not None else {}
+
+ @property
+ def _class_type(self) -> typing.Any:
+ return getattr(self._type, "args", [None])[0]
+
+ @property
+ def _rest_name(self) -> str:
+ if self._rest_name_input is None:
+ raise ValueError("Rest name was never set")
+ return self._rest_name_input
+
+ def __get__(self, obj: Model, type=None): # pylint: disable=redefined-builtin
+ # by this point, type and rest_name will have a value bc we default
+ # them in __new__ of the Model class
+ item = obj.get(self._rest_name)
+ if item is None:
+ return item
+ if self._is_model:
+ return item
+ return _deserialize(self._type, _serialize(item, self._format), rf=self)
+
+ def __set__(self, obj: Model, value) -> None:
+ if value is None:
+ # we want to wipe out entries if users set attr to None
+ try:
+ obj.__delitem__(self._rest_name)
+ except KeyError:
+ pass
+ return
+ if self._is_model:
+ if not _is_model(value):
+ value = _deserialize(self._type, value)
+ obj.__setitem__(self._rest_name, value)
+ return
+ obj.__setitem__(self._rest_name, _serialize(value, self._format))
+
+ def _get_deserialize_callable_from_annotation(
+ self, annotation: typing.Any
+ ) -> typing.Optional[typing.Callable[[typing.Any], typing.Any]]:
+ return _get_deserialize_callable_from_annotation(annotation, self._module, self)
+
+
+def rest_field(
+ *,
+ name: typing.Optional[str] = None,
+ type: typing.Optional[typing.Callable] = None, # pylint: disable=redefined-builtin
+ visibility: typing.Optional[typing.List[str]] = None,
+ default: typing.Any = _UNSET,
+ format: typing.Optional[str] = None,
+ is_multipart_file_input: bool = False,
+ xml: typing.Optional[typing.Dict[str, typing.Any]] = None,
+) -> typing.Any:
+ return _RestField(
+ name=name,
+ type=type,
+ visibility=visibility,
+ default=default,
+ format=format,
+ is_multipart_file_input=is_multipart_file_input,
+ xml=xml,
+ )
+
+
+def rest_discriminator(
+ *,
+ name: typing.Optional[str] = None,
+ type: typing.Optional[typing.Callable] = None, # pylint: disable=redefined-builtin
+ visibility: typing.Optional[typing.List[str]] = None,
+ xml: typing.Optional[typing.Dict[str, typing.Any]] = None,
+) -> typing.Any:
+ return _RestField(name=name, type=type, is_discriminator=True, visibility=visibility, xml=xml)
+
+
+def serialize_xml(model: Model, exclude_readonly: bool = False) -> str:
+ """Serialize a model to XML.
+
+ :param Model model: The model to serialize.
+ :param bool exclude_readonly: Whether to exclude readonly properties.
+ :returns: The XML representation of the model.
+ :rtype: str
+ """
+ return ET.tostring(_get_element(model, exclude_readonly), encoding="unicode") # type: ignore
+
+
+def _get_element(
+ o: typing.Any,
+ exclude_readonly: bool = False,
+ parent_meta: typing.Optional[typing.Dict[str, typing.Any]] = None,
+ wrapped_element: typing.Optional[ET.Element] = None,
+) -> typing.Union[ET.Element, typing.List[ET.Element]]:
+ if _is_model(o):
+ model_meta = getattr(o, "_xml", {})
+
+ # if prop is a model, then use the prop element directly, else generate a wrapper of model
+ if wrapped_element is None:
+ wrapped_element = _create_xml_element(
+ model_meta.get("name", o.__class__.__name__),
+ model_meta.get("prefix"),
+ model_meta.get("ns"),
+ )
+
+ readonly_props = []
+ if exclude_readonly:
+ readonly_props = [p._rest_name for p in o._attr_to_rest_field.values() if _is_readonly(p)]
+
+ for k, v in o.items():
+ # do not serialize readonly properties
+ if exclude_readonly and k in readonly_props:
+ continue
+
+ prop_rest_field = _get_rest_field(o._attr_to_rest_field, k)
+ if prop_rest_field:
+ prop_meta = getattr(prop_rest_field, "_xml").copy()
+ # use the wire name as xml name if no specific name is set
+ if prop_meta.get("name") is None:
+ prop_meta["name"] = k
+ else:
+ # additional properties will not have rest field, use the wire name as xml name
+ prop_meta = {"name": k}
+
+ # if no ns for prop, use model's
+ if prop_meta.get("ns") is None and model_meta.get("ns"):
+ prop_meta["ns"] = model_meta.get("ns")
+ prop_meta["prefix"] = model_meta.get("prefix")
+
+ if prop_meta.get("unwrapped", False):
+ # unwrapped could only set on array
+ wrapped_element.extend(_get_element(v, exclude_readonly, prop_meta))
+ elif prop_meta.get("text", False):
+ # text could only set on primitive type
+ wrapped_element.text = _get_primitive_type_value(v)
+ elif prop_meta.get("attribute", False):
+ xml_name = prop_meta.get("name", k)
+ if prop_meta.get("ns"):
+ ET.register_namespace(prop_meta.get("prefix"), prop_meta.get("ns")) # pyright: ignore
+ xml_name = "{" + prop_meta.get("ns") + "}" + xml_name # pyright: ignore
+ # attribute should be primitive type
+ wrapped_element.set(xml_name, _get_primitive_type_value(v))
+ else:
+ # other wrapped prop element
+ wrapped_element.append(_get_wrapped_element(v, exclude_readonly, prop_meta))
+ return wrapped_element
+ if isinstance(o, list):
+ return [_get_element(x, exclude_readonly, parent_meta) for x in o] # type: ignore
+ if isinstance(o, dict):
+ result = []
+ for k, v in o.items():
+ result.append(
+ _get_wrapped_element(
+ v,
+ exclude_readonly,
+ {
+ "name": k,
+ "ns": parent_meta.get("ns") if parent_meta else None,
+ "prefix": parent_meta.get("prefix") if parent_meta else None,
+ },
+ )
+ )
+ return result
+
+ # primitive case need to create element based on parent_meta
+ if parent_meta:
+ return _get_wrapped_element(
+ o,
+ exclude_readonly,
+ {
+ "name": parent_meta.get("itemsName", parent_meta.get("name")),
+ "prefix": parent_meta.get("itemsPrefix", parent_meta.get("prefix")),
+ "ns": parent_meta.get("itemsNs", parent_meta.get("ns")),
+ },
+ )
+
+ raise ValueError("Could not serialize value into xml: " + o)
+
+
+def _get_wrapped_element(
+ v: typing.Any,
+ exclude_readonly: bool,
+ meta: typing.Optional[typing.Dict[str, typing.Any]],
+) -> ET.Element:
+ wrapped_element = _create_xml_element(
+ meta.get("name") if meta else None, meta.get("prefix") if meta else None, meta.get("ns") if meta else None
+ )
+ if isinstance(v, (dict, list)):
+ wrapped_element.extend(_get_element(v, exclude_readonly, meta))
+ elif _is_model(v):
+ _get_element(v, exclude_readonly, meta, wrapped_element)
+ else:
+ wrapped_element.text = _get_primitive_type_value(v)
+ return wrapped_element
+
+
+def _get_primitive_type_value(v) -> str:
+ if v is True:
+ return "true"
+ if v is False:
+ return "false"
+ if isinstance(v, _Null):
+ return ""
+ return str(v)
+
+
+def _create_xml_element(tag, prefix=None, ns=None):
+ if prefix and ns:
+ ET.register_namespace(prefix, ns)
+ if ns:
+ return ET.Element("{" + ns + "}" + tag)
+ return ET.Element(tag)
+
+
+def _deserialize_xml(
+ deserializer: typing.Any,
+ value: str,
+) -> typing.Any:
+ element = ET.fromstring(value) # nosec
+ return _deserialize(deserializer, element)
+
+
+def _convert_element(e: ET.Element):
+ # dict case
+ if len(e.attrib) > 0 or len({child.tag for child in e}) > 1:
+ dict_result: typing.Dict[str, typing.Any] = {}
+ for child in e:
+ if dict_result.get(child.tag) is not None:
+ if isinstance(dict_result[child.tag], list):
+ dict_result[child.tag].append(_convert_element(child))
+ else:
+ dict_result[child.tag] = [dict_result[child.tag], _convert_element(child)]
+ else:
+ dict_result[child.tag] = _convert_element(child)
+ dict_result.update(e.attrib)
+ return dict_result
+ # array case
+ if len(e) > 0:
+ array_result: typing.List[typing.Any] = []
+ for child in e:
+ array_result.append(_convert_element(child))
+ return array_result
+ # primitive case
+ return e.text
diff --git a/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/_patch.py b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/_patch.py
new file mode 100644
index 000000000000..f7dd32510333
--- /dev/null
+++ b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/_patch.py
@@ -0,0 +1,20 @@
+# ------------------------------------
+# Copyright (c) Microsoft Corporation.
+# Licensed under the MIT License.
+# ------------------------------------
+"""Customize generated code here.
+
+Follow our quickstart for examples: https://aka.ms/azsdk/python/dpcodegen/python/customize
+"""
+from typing import List
+
+__all__: List[str] = [] # Add all objects you want publicly available to users at this package level
+
+
+def patch_sdk():
+ """Do not remove from this file.
+
+ `patch_sdk` is a last resort escape hatch that allows you to do customizations
+ you can't accomplish using the techniques described in
+ https://aka.ms/azsdk/python/dpcodegen/python/customize
+ """
diff --git a/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/_serialization.py b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/_serialization.py
new file mode 100644
index 000000000000..480e941d758f
--- /dev/null
+++ b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/_serialization.py
@@ -0,0 +1,2114 @@
+# --------------------------------------------------------------------------
+#
+# Copyright (c) Microsoft Corporation. All rights reserved.
+#
+# The MIT License (MIT)
+#
+# Permission is hereby granted, free of charge, to any person obtaining a copy
+# of this software and associated documentation files (the ""Software""), to
+# deal in the Software without restriction, including without limitation the
+# rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+# sell copies of the Software, and to permit persons to whom the Software is
+# furnished to do so, subject to the following conditions:
+#
+# The above copyright notice and this permission notice shall be included in
+# all copies or substantial portions of the Software.
+#
+# THE SOFTWARE IS PROVIDED *AS IS*, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+# FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS
+# IN THE SOFTWARE.
+#
+# --------------------------------------------------------------------------
+
+# pyright: reportUnnecessaryTypeIgnoreComment=false
+
+from base64 import b64decode, b64encode
+import calendar
+import datetime
+import decimal
+import email
+from enum import Enum
+import json
+import logging
+import re
+import sys
+import codecs
+from typing import (
+ Dict,
+ Any,
+ cast,
+ Optional,
+ Union,
+ AnyStr,
+ IO,
+ Mapping,
+ Callable,
+ TypeVar,
+ MutableMapping,
+ Type,
+ List,
+)
+
+try:
+ from urllib import quote # type: ignore
+except ImportError:
+ from urllib.parse import quote
+import xml.etree.ElementTree as ET
+
+import isodate # type: ignore
+
+from azure.core.exceptions import DeserializationError, SerializationError
+from azure.core.serialization import NULL as CoreNull
+
+_BOM = codecs.BOM_UTF8.decode(encoding="utf-8")
+
+ModelType = TypeVar("ModelType", bound="Model")
+JSON = MutableMapping[str, Any]
+
+
+class RawDeserializer:
+
+ # Accept "text" because we're open minded people...
+ JSON_REGEXP = re.compile(r"^(application|text)/([a-z+.]+\+)?json$")
+
+ # Name used in context
+ CONTEXT_NAME = "deserialized_data"
+
+ @classmethod
+ def deserialize_from_text(cls, data: Optional[Union[AnyStr, IO]], content_type: Optional[str] = None) -> Any:
+ """Decode data according to content-type.
+
+ Accept a stream of data as well, but will be load at once in memory for now.
+
+ If no content-type, will return the string version (not bytes, not stream)
+
+ :param data: Input, could be bytes or stream (will be decoded with UTF8) or text
+ :type data: str or bytes or IO
+ :param str content_type: The content type.
+ :return: The deserialized data.
+ :rtype: object
+ """
+ if hasattr(data, "read"):
+ # Assume a stream
+ data = cast(IO, data).read()
+
+ if isinstance(data, bytes):
+ data_as_str = data.decode(encoding="utf-8-sig")
+ else:
+ # Explain to mypy the correct type.
+ data_as_str = cast(str, data)
+
+ # Remove Byte Order Mark if present in string
+ data_as_str = data_as_str.lstrip(_BOM)
+
+ if content_type is None:
+ return data
+
+ if cls.JSON_REGEXP.match(content_type):
+ try:
+ return json.loads(data_as_str)
+ except ValueError as err:
+ raise DeserializationError("JSON is invalid: {}".format(err), err) from err
+ elif "xml" in (content_type or []):
+ try:
+
+ try:
+ if isinstance(data, unicode): # type: ignore
+ # If I'm Python 2.7 and unicode XML will scream if I try a "fromstring" on unicode string
+ data_as_str = data_as_str.encode(encoding="utf-8") # type: ignore
+ except NameError:
+ pass
+
+ return ET.fromstring(data_as_str) # nosec
+ except ET.ParseError as err:
+ # It might be because the server has an issue, and returned JSON with
+ # content-type XML....
+ # So let's try a JSON load, and if it's still broken
+ # let's flow the initial exception
+ def _json_attemp(data):
+ try:
+ return True, json.loads(data)
+ except ValueError:
+ return False, None # Don't care about this one
+
+ success, json_result = _json_attemp(data)
+ if success:
+ return json_result
+ # If i'm here, it's not JSON, it's not XML, let's scream
+ # and raise the last context in this block (the XML exception)
+ # The function hack is because Py2.7 messes up with exception
+ # context otherwise.
+ _LOGGER.critical("Wasn't XML not JSON, failing")
+ raise DeserializationError("XML is invalid") from err
+ elif content_type.startswith("text/"):
+ return data_as_str
+ raise DeserializationError("Cannot deserialize content-type: {}".format(content_type))
+
+ @classmethod
+ def deserialize_from_http_generics(cls, body_bytes: Optional[Union[AnyStr, IO]], headers: Mapping) -> Any:
+ """Deserialize from HTTP response.
+
+ Use bytes and headers to NOT use any requests/aiohttp or whatever
+ specific implementation.
+ Headers will tested for "content-type"
+
+ :param bytes body_bytes: The body of the response.
+ :param dict headers: The headers of the response.
+ :returns: The deserialized data.
+ :rtype: object
+ """
+ # Try to use content-type from headers if available
+ content_type = None
+ if "content-type" in headers:
+ content_type = headers["content-type"].split(";")[0].strip().lower()
+ # Ouch, this server did not declare what it sent...
+ # Let's guess it's JSON...
+ # Also, since Autorest was considering that an empty body was a valid JSON,
+ # need that test as well....
+ else:
+ content_type = "application/json"
+
+ if body_bytes:
+ return cls.deserialize_from_text(body_bytes, content_type)
+ return None
+
+
+_LOGGER = logging.getLogger(__name__)
+
+try:
+ _long_type = long # type: ignore
+except NameError:
+ _long_type = int
+
+
+class UTC(datetime.tzinfo):
+ """Time Zone info for handling UTC"""
+
+ def utcoffset(self, dt):
+ """UTF offset for UTC is 0.
+
+ :param datetime.datetime dt: The datetime
+ :returns: The offset
+ :rtype: datetime.timedelta
+ """
+ return datetime.timedelta(0)
+
+ def tzname(self, dt):
+ """Timestamp representation.
+
+ :param datetime.datetime dt: The datetime
+ :returns: The timestamp representation
+ :rtype: str
+ """
+ return "Z"
+
+ def dst(self, dt):
+ """No daylight saving for UTC.
+
+ :param datetime.datetime dt: The datetime
+ :returns: The daylight saving time
+ :rtype: datetime.timedelta
+ """
+ return datetime.timedelta(hours=1)
+
+
+try:
+ from datetime import timezone as _FixedOffset # type: ignore
+except ImportError: # Python 2.7
+
+ class _FixedOffset(datetime.tzinfo): # type: ignore
+ """Fixed offset in minutes east from UTC.
+ Copy/pasted from Python doc
+ :param datetime.timedelta offset: offset in timedelta format
+ """
+
+ def __init__(self, offset) -> None:
+ self.__offset = offset
+
+ def utcoffset(self, dt):
+ return self.__offset
+
+ def tzname(self, dt):
+ return str(self.__offset.total_seconds() / 3600)
+
+ def __repr__(self):
+ return "".format(self.tzname(None))
+
+ def dst(self, dt):
+ return datetime.timedelta(0)
+
+ def __getinitargs__(self):
+ return (self.__offset,)
+
+
+try:
+ from datetime import timezone
+
+ TZ_UTC = timezone.utc
+except ImportError:
+ TZ_UTC = UTC() # type: ignore
+
+_FLATTEN = re.compile(r"(? None:
+ self.additional_properties: Optional[Dict[str, Any]] = {}
+ for k in kwargs: # pylint: disable=consider-using-dict-items
+ if k not in self._attribute_map:
+ _LOGGER.warning("%s is not a known attribute of class %s and will be ignored", k, self.__class__)
+ elif k in self._validation and self._validation[k].get("readonly", False):
+ _LOGGER.warning("Readonly attribute %s will be ignored in class %s", k, self.__class__)
+ else:
+ setattr(self, k, kwargs[k])
+
+ def __eq__(self, other: Any) -> bool:
+ """Compare objects by comparing all attributes.
+
+ :param object other: The object to compare
+ :returns: True if objects are equal
+ :rtype: bool
+ """
+ if isinstance(other, self.__class__):
+ return self.__dict__ == other.__dict__
+ return False
+
+ def __ne__(self, other: Any) -> bool:
+ """Compare objects by comparing all attributes.
+
+ :param object other: The object to compare
+ :returns: True if objects are not equal
+ :rtype: bool
+ """
+ return not self.__eq__(other)
+
+ def __str__(self) -> str:
+ return str(self.__dict__)
+
+ @classmethod
+ def enable_additional_properties_sending(cls) -> None:
+ cls._attribute_map["additional_properties"] = {"key": "", "type": "{object}"}
+
+ @classmethod
+ def is_xml_model(cls) -> bool:
+ try:
+ cls._xml_map # type: ignore
+ except AttributeError:
+ return False
+ return True
+
+ @classmethod
+ def _create_xml_node(cls):
+ """Create XML node.
+
+ :returns: The XML node
+ :rtype: xml.etree.ElementTree.Element
+ """
+ try:
+ xml_map = cls._xml_map # type: ignore
+ except AttributeError:
+ xml_map = {}
+
+ return _create_xml_node(xml_map.get("name", cls.__name__), xml_map.get("prefix", None), xml_map.get("ns", None))
+
+ def serialize(self, keep_readonly: bool = False, **kwargs: Any) -> JSON:
+ """Return the JSON that would be sent to server from this model.
+
+ This is an alias to `as_dict(full_restapi_key_transformer, keep_readonly=False)`.
+
+ If you want XML serialization, you can pass the kwargs is_xml=True.
+
+ :param bool keep_readonly: If you want to serialize the readonly attributes
+ :returns: A dict JSON compatible object
+ :rtype: dict
+ """
+ serializer = Serializer(self._infer_class_models())
+ return serializer._serialize( # type: ignore # pylint: disable=protected-access
+ self, keep_readonly=keep_readonly, **kwargs
+ )
+
+ def as_dict(
+ self,
+ keep_readonly: bool = True,
+ key_transformer: Callable[[str, Dict[str, Any], Any], Any] = attribute_transformer,
+ **kwargs: Any
+ ) -> JSON:
+ """Return a dict that can be serialized using json.dump.
+
+ Advanced usage might optionally use a callback as parameter:
+
+ .. code::python
+
+ def my_key_transformer(key, attr_desc, value):
+ return key
+
+ Key is the attribute name used in Python. Attr_desc
+ is a dict of metadata. Currently contains 'type' with the
+ msrest type and 'key' with the RestAPI encoded key.
+ Value is the current value in this object.
+
+ The string returned will be used to serialize the key.
+ If the return type is a list, this is considered hierarchical
+ result dict.
+
+ See the three examples in this file:
+
+ - attribute_transformer
+ - full_restapi_key_transformer
+ - last_restapi_key_transformer
+
+ If you want XML serialization, you can pass the kwargs is_xml=True.
+
+ :param bool keep_readonly: If you want to serialize the readonly attributes
+ :param function key_transformer: A key transformer function.
+ :returns: A dict JSON compatible object
+ :rtype: dict
+ """
+ serializer = Serializer(self._infer_class_models())
+ return serializer._serialize( # type: ignore # pylint: disable=protected-access
+ self, key_transformer=key_transformer, keep_readonly=keep_readonly, **kwargs
+ )
+
+ @classmethod
+ def _infer_class_models(cls):
+ try:
+ str_models = cls.__module__.rsplit(".", 1)[0]
+ models = sys.modules[str_models]
+ client_models = {k: v for k, v in models.__dict__.items() if isinstance(v, type)}
+ if cls.__name__ not in client_models:
+ raise ValueError("Not Autorest generated code")
+ except Exception: # pylint: disable=broad-exception-caught
+ # Assume it's not Autorest generated (tests?). Add ourselves as dependencies.
+ client_models = {cls.__name__: cls}
+ return client_models
+
+ @classmethod
+ def deserialize(cls: Type[ModelType], data: Any, content_type: Optional[str] = None) -> ModelType:
+ """Parse a str using the RestAPI syntax and return a model.
+
+ :param str data: A str using RestAPI structure. JSON by default.
+ :param str content_type: JSON by default, set application/xml if XML.
+ :returns: An instance of this model
+ :raises: DeserializationError if something went wrong
+ :rtype: ModelType
+ """
+ deserializer = Deserializer(cls._infer_class_models())
+ return deserializer(cls.__name__, data, content_type=content_type) # type: ignore
+
+ @classmethod
+ def from_dict(
+ cls: Type[ModelType],
+ data: Any,
+ key_extractors: Optional[Callable[[str, Dict[str, Any], Any], Any]] = None,
+ content_type: Optional[str] = None,
+ ) -> ModelType:
+ """Parse a dict using given key extractor return a model.
+
+ By default consider key
+ extractors (rest_key_case_insensitive_extractor, attribute_key_case_insensitive_extractor
+ and last_rest_key_case_insensitive_extractor)
+
+ :param dict data: A dict using RestAPI structure
+ :param function key_extractors: A key extractor function.
+ :param str content_type: JSON by default, set application/xml if XML.
+ :returns: An instance of this model
+ :raises: DeserializationError if something went wrong
+ :rtype: ModelType
+ """
+ deserializer = Deserializer(cls._infer_class_models())
+ deserializer.key_extractors = ( # type: ignore
+ [ # type: ignore
+ attribute_key_case_insensitive_extractor,
+ rest_key_case_insensitive_extractor,
+ last_rest_key_case_insensitive_extractor,
+ ]
+ if key_extractors is None
+ else key_extractors
+ )
+ return deserializer(cls.__name__, data, content_type=content_type) # type: ignore
+
+ @classmethod
+ def _flatten_subtype(cls, key, objects):
+ if "_subtype_map" not in cls.__dict__:
+ return {}
+ result = dict(cls._subtype_map[key])
+ for valuetype in cls._subtype_map[key].values():
+ result.update(objects[valuetype]._flatten_subtype(key, objects)) # pylint: disable=protected-access
+ return result
+
+ @classmethod
+ 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
+ :returns: The class to be used
+ :rtype: class
+ """
+ for subtype_key in cls.__dict__.get("_subtype_map", {}).keys():
+ subtype_value = None
+
+ 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)
+ else:
+ subtype_value = xml_key_extractor(subtype_key, cls._attribute_map[subtype_key], response)
+ if subtype_value:
+ # Try to match base class. Can be class name only
+ # (bug to fix in Autorest to support x-ms-discriminator-name)
+ if cls.__name__ == subtype_value:
+ return cls
+ flatten_mapping_type = cls._flatten_subtype(subtype_key, objects)
+ try:
+ return objects[flatten_mapping_type[subtype_value]] # type: ignore
+ except KeyError:
+ _LOGGER.warning(
+ "Subtype value %s has no mapping, use base class %s.",
+ subtype_value,
+ cls.__name__,
+ )
+ break
+ else:
+ _LOGGER.warning("Discriminator %s is absent or null, use base class %s.", subtype_key, cls.__name__)
+ break
+ return cls
+
+ @classmethod
+ def _get_rest_key_parts(cls, attr_key):
+ """Get the RestAPI key of this attr, split it and decode part
+ :param str attr_key: Attribute key must be in attribute_map.
+ :returns: A list of RestAPI part
+ :rtype: list
+ """
+ rest_split_key = _FLATTEN.split(cls._attribute_map[attr_key]["key"])
+ return [_decode_attribute_map_key(key_part) for key_part in rest_split_key]
+
+
+def _decode_attribute_map_key(key):
+ """This decode a key in an _attribute_map to the actual key we want to look at
+ inside the received data.
+
+ :param str key: A key string from the generated code
+ :returns: The decoded key
+ :rtype: str
+ """
+ return key.replace("\\.", ".")
+
+
+class Serializer(object): # pylint: disable=too-many-public-methods
+ """Request object model serializer."""
+
+ basic_types = {str: "str", int: "int", bool: "bool", float: "float"}
+
+ _xml_basic_types_serializers = {"bool": lambda x: str(x).lower()}
+ days = {0: "Mon", 1: "Tue", 2: "Wed", 3: "Thu", 4: "Fri", 5: "Sat", 6: "Sun"}
+ months = {
+ 1: "Jan",
+ 2: "Feb",
+ 3: "Mar",
+ 4: "Apr",
+ 5: "May",
+ 6: "Jun",
+ 7: "Jul",
+ 8: "Aug",
+ 9: "Sep",
+ 10: "Oct",
+ 11: "Nov",
+ 12: "Dec",
+ }
+ validation = {
+ "min_length": lambda x, y: len(x) < y,
+ "max_length": lambda x, y: len(x) > y,
+ "minimum": lambda x, y: x < y,
+ "maximum": lambda x, y: x > y,
+ "minimum_ex": lambda x, y: x <= y,
+ "maximum_ex": lambda x, y: x >= y,
+ "min_items": lambda x, y: len(x) < y,
+ "max_items": lambda x, y: len(x) > y,
+ "pattern": lambda x, y: not re.match(y, x, re.UNICODE),
+ "unique": lambda x, y: len(x) != len(set(x)),
+ "multiple": lambda x, y: x % y != 0,
+ }
+
+ def __init__(self, classes: Optional[Mapping[str, type]] = None) -> None:
+ self.serialize_type = {
+ "iso-8601": Serializer.serialize_iso,
+ "rfc-1123": Serializer.serialize_rfc,
+ "unix-time": Serializer.serialize_unix,
+ "duration": Serializer.serialize_duration,
+ "date": Serializer.serialize_date,
+ "time": Serializer.serialize_time,
+ "decimal": Serializer.serialize_decimal,
+ "long": Serializer.serialize_long,
+ "bytearray": Serializer.serialize_bytearray,
+ "base64": Serializer.serialize_base64,
+ "object": self.serialize_object,
+ "[]": self.serialize_iter,
+ "{}": self.serialize_dict,
+ }
+ self.dependencies: Dict[str, type] = dict(classes) if classes else {}
+ self.key_transformer = full_restapi_key_transformer
+ self.client_side_validation = True
+
+ def _serialize( # pylint: disable=too-many-nested-blocks, too-many-branches, too-many-statements, too-many-locals
+ self, target_obj, data_type=None, **kwargs
+ ):
+ """Serialize data into a string according to type.
+
+ :param object target_obj: The data to be serialized.
+ :param str data_type: The type to be serialized from.
+ :rtype: str, dict
+ :raises: SerializationError if serialization fails.
+ :returns: The serialized data.
+ """
+ key_transformer = kwargs.get("key_transformer", self.key_transformer)
+ keep_readonly = kwargs.get("keep_readonly", False)
+ if target_obj is None:
+ return None
+
+ attr_name = None
+ class_name = target_obj.__class__.__name__
+
+ if data_type:
+ return self.serialize_data(target_obj, data_type, **kwargs)
+
+ if not hasattr(target_obj, "_attribute_map"):
+ data_type = type(target_obj).__name__
+ if data_type in self.basic_types.values():
+ return self.serialize_data(target_obj, data_type, **kwargs)
+
+ # Force "is_xml" kwargs if we detect a XML model
+ try:
+ is_xml_model_serialization = kwargs["is_xml"]
+ except KeyError:
+ is_xml_model_serialization = kwargs.setdefault("is_xml", target_obj.is_xml_model())
+
+ serialized = {}
+ if is_xml_model_serialization:
+ serialized = target_obj._create_xml_node() # pylint: disable=protected-access
+ try:
+ attributes = target_obj._attribute_map # pylint: disable=protected-access
+ for attr, attr_desc in attributes.items():
+ attr_name = attr
+ if not keep_readonly and target_obj._validation.get( # pylint: disable=protected-access
+ attr_name, {}
+ ).get("readonly", False):
+ continue
+
+ if attr_name == "additional_properties" and attr_desc["key"] == "":
+ if target_obj.additional_properties is not None:
+ serialized.update(target_obj.additional_properties)
+ continue
+ try:
+
+ orig_attr = getattr(target_obj, attr)
+ if is_xml_model_serialization:
+ pass # Don't provide "transformer" for XML for now. Keep "orig_attr"
+ else: # JSON
+ keys, orig_attr = key_transformer(attr, attr_desc.copy(), orig_attr)
+ keys = keys if isinstance(keys, list) else [keys]
+
+ kwargs["serialization_ctxt"] = attr_desc
+ new_attr = self.serialize_data(orig_attr, attr_desc["type"], **kwargs)
+
+ if is_xml_model_serialization:
+ xml_desc = attr_desc.get("xml", {})
+ xml_name = xml_desc.get("name", attr_desc["key"])
+ xml_prefix = xml_desc.get("prefix", None)
+ xml_ns = xml_desc.get("ns", None)
+ if xml_desc.get("attr", False):
+ if xml_ns:
+ ET.register_namespace(xml_prefix, xml_ns)
+ xml_name = "{{{}}}{}".format(xml_ns, xml_name)
+ serialized.set(xml_name, new_attr) # type: ignore
+ continue
+ if xml_desc.get("text", False):
+ serialized.text = new_attr # type: ignore
+ continue
+ if isinstance(new_attr, list):
+ serialized.extend(new_attr) # type: ignore
+ elif isinstance(new_attr, ET.Element):
+ # If the down XML has no XML/Name,
+ # we MUST replace the tag with the local tag. But keeping the namespaces.
+ if "name" not in getattr(orig_attr, "_xml_map", {}):
+ splitted_tag = new_attr.tag.split("}")
+ if len(splitted_tag) == 2: # Namespace
+ new_attr.tag = "}".join([splitted_tag[0], xml_name])
+ else:
+ new_attr.tag = xml_name
+ serialized.append(new_attr) # type: ignore
+ else: # That's a basic type
+ # Integrate namespace if necessary
+ local_node = _create_xml_node(xml_name, xml_prefix, xml_ns)
+ local_node.text = str(new_attr)
+ serialized.append(local_node) # type: ignore
+ else: # JSON
+ for k in reversed(keys): # type: ignore
+ new_attr = {k: new_attr}
+
+ _new_attr = new_attr
+ _serialized = serialized
+ for k in keys: # type: ignore
+ if k not in _serialized:
+ _serialized.update(_new_attr) # type: ignore
+ _new_attr = _new_attr[k] # type: ignore
+ _serialized = _serialized[k]
+ except ValueError as err:
+ if isinstance(err, SerializationError):
+ raise
+
+ except (AttributeError, KeyError, TypeError) as err:
+ msg = "Attribute {} in object {} cannot be serialized.\n{}".format(attr_name, class_name, str(target_obj))
+ raise SerializationError(msg) from err
+ return serialized
+
+ def body(self, data, data_type, **kwargs):
+ """Serialize data intended for a request body.
+
+ :param object data: The data to be serialized.
+ :param str data_type: The type to be serialized from.
+ :rtype: dict
+ :raises: SerializationError if serialization fails.
+ :raises: ValueError if data is None
+ :returns: The serialized request body
+ """
+
+ # Just in case this is a dict
+ internal_data_type_str = data_type.strip("[]{}")
+ internal_data_type = self.dependencies.get(internal_data_type_str, None)
+ try:
+ is_xml_model_serialization = kwargs["is_xml"]
+ except KeyError:
+ if internal_data_type and issubclass(internal_data_type, Model):
+ is_xml_model_serialization = kwargs.setdefault("is_xml", internal_data_type.is_xml_model())
+ else:
+ is_xml_model_serialization = False
+ if internal_data_type and not isinstance(internal_data_type, Enum):
+ try:
+ deserializer = Deserializer(self.dependencies)
+ # Since it's on serialization, it's almost sure that format is not JSON REST
+ # We're not able to deal with additional properties for now.
+ deserializer.additional_properties_detection = False
+ if is_xml_model_serialization:
+ deserializer.key_extractors = [ # type: ignore
+ attribute_key_case_insensitive_extractor,
+ ]
+ else:
+ deserializer.key_extractors = [
+ rest_key_case_insensitive_extractor,
+ attribute_key_case_insensitive_extractor,
+ last_rest_key_case_insensitive_extractor,
+ ]
+ data = deserializer._deserialize(data_type, data) # pylint: disable=protected-access
+ except DeserializationError as err:
+ raise SerializationError("Unable to build a model: " + str(err)) from err
+
+ return self._serialize(data, data_type, **kwargs)
+
+ def url(self, name, data, data_type, **kwargs):
+ """Serialize data intended for a URL path.
+
+ :param str name: The name of the URL path parameter.
+ :param object data: The data to be serialized.
+ :param str data_type: The type to be serialized from.
+ :rtype: str
+ :returns: The serialized URL path
+ :raises: TypeError if serialization fails.
+ :raises: ValueError if data is None
+ """
+ try:
+ output = self.serialize_data(data, data_type, **kwargs)
+ if data_type == "bool":
+ output = json.dumps(output)
+
+ if kwargs.get("skip_quote") is True:
+ output = str(output)
+ output = output.replace("{", quote("{")).replace("}", quote("}"))
+ else:
+ output = quote(str(output), safe="")
+ except SerializationError as exc:
+ raise TypeError("{} must be type {}.".format(name, data_type)) from exc
+ return output
+
+ def query(self, name, data, data_type, **kwargs):
+ """Serialize data intended for a URL query.
+
+ :param str name: The name of the query parameter.
+ :param object data: The data to be serialized.
+ :param str data_type: The type to be serialized from.
+ :rtype: str, list
+ :raises: TypeError if serialization fails.
+ :raises: ValueError if data is None
+ :returns: The serialized query parameter
+ """
+ try:
+ # Treat the list aside, since we don't want to encode the div separator
+ if data_type.startswith("["):
+ internal_data_type = data_type[1:-1]
+ do_quote = not kwargs.get("skip_quote", False)
+ return self.serialize_iter(data, internal_data_type, do_quote=do_quote, **kwargs)
+
+ # Not a list, regular serialization
+ output = self.serialize_data(data, data_type, **kwargs)
+ if data_type == "bool":
+ output = json.dumps(output)
+ if kwargs.get("skip_quote") is True:
+ output = str(output)
+ else:
+ output = quote(str(output), safe="")
+ except SerializationError as exc:
+ raise TypeError("{} must be type {}.".format(name, data_type)) from exc
+ return str(output)
+
+ def header(self, name, data, data_type, **kwargs):
+ """Serialize data intended for a request header.
+
+ :param str name: The name of the header.
+ :param object data: The data to be serialized.
+ :param str data_type: The type to be serialized from.
+ :rtype: str
+ :raises: TypeError if serialization fails.
+ :raises: ValueError if data is None
+ :returns: The serialized header
+ """
+ try:
+ if data_type in ["[str]"]:
+ data = ["" if d is None else d for d in data]
+
+ output = self.serialize_data(data, data_type, **kwargs)
+ if data_type == "bool":
+ output = json.dumps(output)
+ except SerializationError as exc:
+ raise TypeError("{} must be type {}.".format(name, data_type)) from exc
+ return str(output)
+
+ def serialize_data(self, data, data_type, **kwargs):
+ """Serialize generic data according to supplied data type.
+
+ :param object data: The data to be serialized.
+ :param str data_type: The type to be serialized from.
+ :raises: AttributeError if required data is None.
+ :raises: ValueError if data is None
+ :raises: SerializationError if serialization fails.
+ :returns: The serialized data.
+ :rtype: str, int, float, bool, dict, list
+ """
+ if data is None:
+ raise ValueError("No value for given attribute")
+
+ try:
+ if data is CoreNull:
+ return None
+ if data_type in self.basic_types.values():
+ return self.serialize_basic(data, data_type, **kwargs)
+
+ if data_type in self.serialize_type:
+ return self.serialize_type[data_type](data, **kwargs)
+
+ # If dependencies is empty, try with current data class
+ # It has to be a subclass of Enum anyway
+ enum_type = self.dependencies.get(data_type, data.__class__)
+ if issubclass(enum_type, Enum):
+ return Serializer.serialize_enum(data, enum_obj=enum_type)
+
+ iter_type = data_type[0] + data_type[-1]
+ if iter_type in self.serialize_type:
+ return self.serialize_type[iter_type](data, data_type[1:-1], **kwargs)
+
+ except (ValueError, TypeError) as err:
+ msg = "Unable to serialize value: {!r} as type: {!r}."
+ raise SerializationError(msg.format(data, data_type)) from err
+ return self._serialize(data, **kwargs)
+
+ @classmethod
+ def _get_custom_serializers(cls, data_type, **kwargs): # pylint: disable=inconsistent-return-statements
+ custom_serializer = kwargs.get("basic_types_serializers", {}).get(data_type)
+ if custom_serializer:
+ return custom_serializer
+ if kwargs.get("is_xml", False):
+ return cls._xml_basic_types_serializers.get(data_type)
+
+ @classmethod
+ def serialize_basic(cls, data, data_type, **kwargs):
+ """Serialize basic builting data type.
+ Serializes objects to str, int, float or bool.
+
+ Possible kwargs:
+ - basic_types_serializers dict[str, callable] : If set, use the callable as serializer
+ - is_xml bool : If set, use xml_basic_types_serializers
+
+ :param obj data: Object to be serialized.
+ :param str data_type: Type of object in the iterable.
+ :rtype: str, int, float, bool
+ :return: serialized object
+ """
+ custom_serializer = cls._get_custom_serializers(data_type, **kwargs)
+ if custom_serializer:
+ return custom_serializer(data)
+ if data_type == "str":
+ return cls.serialize_unicode(data)
+ return eval(data_type)(data) # nosec # pylint: disable=eval-used
+
+ @classmethod
+ def serialize_unicode(cls, data):
+ """Special handling for serializing unicode strings in Py2.
+ Encode to UTF-8 if unicode, otherwise handle as a str.
+
+ :param str data: Object to be serialized.
+ :rtype: str
+ :return: serialized object
+ """
+ try: # If I received an enum, return its value
+ return data.value
+ except AttributeError:
+ pass
+
+ try:
+ if isinstance(data, unicode): # type: ignore
+ # Don't change it, JSON and XML ElementTree are totally able
+ # to serialize correctly u'' strings
+ return data
+ except NameError:
+ return str(data)
+ return str(data)
+
+ def serialize_iter(self, data, iter_type, div=None, **kwargs):
+ """Serialize iterable.
+
+ Supported kwargs:
+ - serialization_ctxt dict : The current entry of _attribute_map, or same format.
+ serialization_ctxt['type'] should be same as data_type.
+ - is_xml bool : If set, serialize as XML
+
+ :param list data: Object to be serialized.
+ :param str iter_type: Type of object in the iterable.
+ :param str div: If set, this str will be used to combine the elements
+ in the iterable into a combined string. Default is 'None'.
+ Defaults to False.
+ :rtype: list, str
+ :return: serialized iterable
+ """
+ if isinstance(data, str):
+ raise SerializationError("Refuse str type as a valid iter type.")
+
+ serialization_ctxt = kwargs.get("serialization_ctxt", {})
+ is_xml = kwargs.get("is_xml", False)
+
+ serialized = []
+ for d in data:
+ try:
+ serialized.append(self.serialize_data(d, iter_type, **kwargs))
+ except ValueError as err:
+ if isinstance(err, SerializationError):
+ raise
+ serialized.append(None)
+
+ if kwargs.get("do_quote", False):
+ serialized = ["" if s is None else quote(str(s), safe="") for s in serialized]
+
+ if div:
+ serialized = ["" if s is None else str(s) for s in serialized]
+ serialized = div.join(serialized)
+
+ if "xml" in serialization_ctxt or is_xml:
+ # XML serialization is more complicated
+ xml_desc = serialization_ctxt.get("xml", {})
+ xml_name = xml_desc.get("name")
+ if not xml_name:
+ xml_name = serialization_ctxt["key"]
+
+ # Create a wrap node if necessary (use the fact that Element and list have "append")
+ is_wrapped = xml_desc.get("wrapped", False)
+ node_name = xml_desc.get("itemsName", xml_name)
+ if is_wrapped:
+ final_result = _create_xml_node(xml_name, xml_desc.get("prefix", None), xml_desc.get("ns", None))
+ else:
+ final_result = []
+ # All list elements to "local_node"
+ for el in serialized:
+ if isinstance(el, ET.Element):
+ el_node = el
+ else:
+ el_node = _create_xml_node(node_name, xml_desc.get("prefix", None), xml_desc.get("ns", None))
+ if el is not None: # Otherwise it writes "None" :-p
+ el_node.text = str(el)
+ final_result.append(el_node)
+ return final_result
+ return serialized
+
+ def serialize_dict(self, attr, dict_type, **kwargs):
+ """Serialize a dictionary of objects.
+
+ :param dict attr: Object to be serialized.
+ :param str dict_type: Type of object in the dictionary.
+ :rtype: dict
+ :return: serialized dictionary
+ """
+ serialization_ctxt = kwargs.get("serialization_ctxt", {})
+ serialized = {}
+ for key, value in attr.items():
+ try:
+ serialized[self.serialize_unicode(key)] = self.serialize_data(value, dict_type, **kwargs)
+ except ValueError as err:
+ if isinstance(err, SerializationError):
+ raise
+ serialized[self.serialize_unicode(key)] = None
+
+ if "xml" in serialization_ctxt:
+ # XML serialization is more complicated
+ xml_desc = serialization_ctxt["xml"]
+ xml_name = xml_desc["name"]
+
+ final_result = _create_xml_node(xml_name, xml_desc.get("prefix", None), xml_desc.get("ns", None))
+ for key, value in serialized.items():
+ ET.SubElement(final_result, key).text = value
+ return final_result
+
+ return serialized
+
+ def serialize_object(self, attr, **kwargs): # pylint: disable=too-many-return-statements
+ """Serialize a generic object.
+ This will be handled as a dictionary. If object passed in is not
+ a basic type (str, int, float, dict, list) it will simply be
+ cast to str.
+
+ :param dict attr: Object to be serialized.
+ :rtype: dict or str
+ :return: serialized object
+ """
+ if attr is None:
+ return None
+ if isinstance(attr, ET.Element):
+ return attr
+ obj_type = type(attr)
+ if obj_type in self.basic_types:
+ return self.serialize_basic(attr, self.basic_types[obj_type], **kwargs)
+ if obj_type is _long_type:
+ return self.serialize_long(attr)
+ if obj_type is str:
+ return self.serialize_unicode(attr)
+ if obj_type is datetime.datetime:
+ return self.serialize_iso(attr)
+ if obj_type is datetime.date:
+ return self.serialize_date(attr)
+ if obj_type is datetime.time:
+ return self.serialize_time(attr)
+ if obj_type is datetime.timedelta:
+ return self.serialize_duration(attr)
+ if obj_type is decimal.Decimal:
+ return self.serialize_decimal(attr)
+
+ # If it's a model or I know this dependency, serialize as a Model
+ if obj_type in self.dependencies.values() or isinstance(attr, Model):
+ return self._serialize(attr)
+
+ if obj_type == dict:
+ serialized = {}
+ for key, value in attr.items():
+ try:
+ serialized[self.serialize_unicode(key)] = self.serialize_object(value, **kwargs)
+ except ValueError:
+ serialized[self.serialize_unicode(key)] = None
+ return serialized
+
+ if obj_type == list:
+ serialized = []
+ for obj in attr:
+ try:
+ serialized.append(self.serialize_object(obj, **kwargs))
+ except ValueError:
+ pass
+ return serialized
+ return str(attr)
+
+ @staticmethod
+ def serialize_enum(attr, enum_obj=None):
+ try:
+ result = attr.value
+ except AttributeError:
+ result = attr
+ try:
+ enum_obj(result) # type: ignore
+ return result
+ except ValueError as exc:
+ for enum_value in enum_obj: # type: ignore
+ if enum_value.value.lower() == str(attr).lower():
+ return enum_value.value
+ error = "{!r} is not valid value for enum {!r}"
+ raise SerializationError(error.format(attr, enum_obj)) from exc
+
+ @staticmethod
+ def serialize_bytearray(attr, **kwargs): # pylint: disable=unused-argument
+ """Serialize bytearray into base-64 string.
+
+ :param str attr: Object to be serialized.
+ :rtype: str
+ :return: serialized base64
+ """
+ return b64encode(attr).decode()
+
+ @staticmethod
+ def serialize_base64(attr, **kwargs): # pylint: disable=unused-argument
+ """Serialize str into base-64 string.
+
+ :param str attr: Object to be serialized.
+ :rtype: str
+ :return: serialized base64
+ """
+ encoded = b64encode(attr).decode("ascii")
+ return encoded.strip("=").replace("+", "-").replace("/", "_")
+
+ @staticmethod
+ def serialize_decimal(attr, **kwargs): # pylint: disable=unused-argument
+ """Serialize Decimal object to float.
+
+ :param decimal attr: Object to be serialized.
+ :rtype: float
+ :return: serialized decimal
+ """
+ return float(attr)
+
+ @staticmethod
+ def serialize_long(attr, **kwargs): # pylint: disable=unused-argument
+ """Serialize long (Py2) or int (Py3).
+
+ :param int attr: Object to be serialized.
+ :rtype: int/long
+ :return: serialized long
+ """
+ return _long_type(attr)
+
+ @staticmethod
+ def serialize_date(attr, **kwargs): # pylint: disable=unused-argument
+ """Serialize Date object into ISO-8601 formatted string.
+
+ :param Date attr: Object to be serialized.
+ :rtype: str
+ :return: serialized date
+ """
+ if isinstance(attr, str):
+ attr = isodate.parse_date(attr)
+ t = "{:04}-{:02}-{:02}".format(attr.year, attr.month, attr.day)
+ return t
+
+ @staticmethod
+ def serialize_time(attr, **kwargs): # pylint: disable=unused-argument
+ """Serialize Time object into ISO-8601 formatted string.
+
+ :param datetime.time attr: Object to be serialized.
+ :rtype: str
+ :return: serialized time
+ """
+ if isinstance(attr, str):
+ attr = isodate.parse_time(attr)
+ t = "{:02}:{:02}:{:02}".format(attr.hour, attr.minute, attr.second)
+ if attr.microsecond:
+ t += ".{:02}".format(attr.microsecond)
+ return t
+
+ @staticmethod
+ def serialize_duration(attr, **kwargs): # pylint: disable=unused-argument
+ """Serialize TimeDelta object into ISO-8601 formatted string.
+
+ :param TimeDelta attr: Object to be serialized.
+ :rtype: str
+ :return: serialized duration
+ """
+ if isinstance(attr, str):
+ attr = isodate.parse_duration(attr)
+ return isodate.duration_isoformat(attr)
+
+ @staticmethod
+ def serialize_rfc(attr, **kwargs): # pylint: disable=unused-argument
+ """Serialize Datetime object into RFC-1123 formatted string.
+
+ :param Datetime attr: Object to be serialized.
+ :rtype: str
+ :raises: TypeError if format invalid.
+ :return: serialized rfc
+ """
+ try:
+ if not attr.tzinfo:
+ _LOGGER.warning("Datetime with no tzinfo will be considered UTC.")
+ utc = attr.utctimetuple()
+ except AttributeError as exc:
+ raise TypeError("RFC1123 object must be valid Datetime object.") from exc
+
+ return "{}, {:02} {} {:04} {:02}:{:02}:{:02} GMT".format(
+ Serializer.days[utc.tm_wday],
+ utc.tm_mday,
+ Serializer.months[utc.tm_mon],
+ utc.tm_year,
+ utc.tm_hour,
+ utc.tm_min,
+ utc.tm_sec,
+ )
+
+ @staticmethod
+ def serialize_iso(attr, **kwargs): # pylint: disable=unused-argument
+ """Serialize Datetime object into ISO-8601 formatted string.
+
+ :param Datetime attr: Object to be serialized.
+ :rtype: str
+ :raises: SerializationError if format invalid.
+ :return: serialized iso
+ """
+ if isinstance(attr, str):
+ attr = isodate.parse_datetime(attr)
+ try:
+ if not attr.tzinfo:
+ _LOGGER.warning("Datetime with no tzinfo will be considered UTC.")
+ utc = attr.utctimetuple()
+ if utc.tm_year > 9999 or utc.tm_year < 1:
+ raise OverflowError("Hit max or min date")
+
+ microseconds = str(attr.microsecond).rjust(6, "0").rstrip("0").ljust(3, "0")
+ if microseconds:
+ microseconds = "." + microseconds
+ date = "{:04}-{:02}-{:02}T{:02}:{:02}:{:02}".format(
+ utc.tm_year, utc.tm_mon, utc.tm_mday, utc.tm_hour, utc.tm_min, utc.tm_sec
+ )
+ return date + microseconds + "Z"
+ except (ValueError, OverflowError) as err:
+ msg = "Unable to serialize datetime object."
+ raise SerializationError(msg) from err
+ except AttributeError as err:
+ msg = "ISO-8601 object must be valid Datetime object."
+ raise TypeError(msg) from err
+
+ @staticmethod
+ def serialize_unix(attr, **kwargs): # pylint: disable=unused-argument
+ """Serialize Datetime object into IntTime format.
+ This is represented as seconds.
+
+ :param Datetime attr: Object to be serialized.
+ :rtype: int
+ :raises: SerializationError if format invalid
+ :return: serialied unix
+ """
+ if isinstance(attr, int):
+ return attr
+ try:
+ if not attr.tzinfo:
+ _LOGGER.warning("Datetime with no tzinfo will be considered UTC.")
+ return int(calendar.timegm(attr.utctimetuple()))
+ except AttributeError as exc:
+ raise TypeError("Unix time object must be valid Datetime object.") from exc
+
+
+def rest_key_extractor(attr, attr_desc, data): # pylint: disable=unused-argument
+ key = attr_desc["key"]
+ working_data = data
+
+ while "." in key:
+ # Need the cast, as for some reasons "split" is typed as list[str | Any]
+ dict_keys = cast(List[str], _FLATTEN.split(key))
+ if len(dict_keys) == 1:
+ key = _decode_attribute_map_key(dict_keys[0])
+ break
+ working_key = _decode_attribute_map_key(dict_keys[0])
+ working_data = working_data.get(working_key, data)
+ if working_data is None:
+ # If at any point while following flatten JSON path see None, it means
+ # that all properties under are None as well
+ return None
+ key = ".".join(dict_keys[1:])
+
+ return working_data.get(key)
+
+
+def rest_key_case_insensitive_extractor( # pylint: disable=unused-argument, inconsistent-return-statements
+ attr, attr_desc, data
+):
+ key = attr_desc["key"]
+ working_data = data
+
+ while "." in key:
+ dict_keys = _FLATTEN.split(key)
+ if len(dict_keys) == 1:
+ key = _decode_attribute_map_key(dict_keys[0])
+ break
+ working_key = _decode_attribute_map_key(dict_keys[0])
+ working_data = attribute_key_case_insensitive_extractor(working_key, None, working_data)
+ if working_data is None:
+ # If at any point while following flatten JSON path see None, it means
+ # that all properties under are None as well
+ return None
+ key = ".".join(dict_keys[1:])
+
+ if working_data:
+ return attribute_key_case_insensitive_extractor(key, None, working_data)
+
+
+def last_rest_key_extractor(attr, attr_desc, data): # pylint: disable=unused-argument
+ """Extract the attribute in "data" based on the last part of the JSON path key.
+
+ :param str attr: The attribute to extract
+ :param dict attr_desc: The attribute description
+ :param dict data: The data to extract from
+ :rtype: object
+ :returns: The extracted attribute
+ """
+ key = attr_desc["key"]
+ dict_keys = _FLATTEN.split(key)
+ return attribute_key_extractor(dict_keys[-1], None, data)
+
+
+def last_rest_key_case_insensitive_extractor(attr, attr_desc, data): # pylint: disable=unused-argument
+ """Extract the attribute in "data" based on the last part of the JSON path key.
+
+ This is the case insensitive version of "last_rest_key_extractor"
+ :param str attr: The attribute to extract
+ :param dict attr_desc: The attribute description
+ :param dict data: The data to extract from
+ :rtype: object
+ :returns: The extracted attribute
+ """
+ key = attr_desc["key"]
+ dict_keys = _FLATTEN.split(key)
+ return attribute_key_case_insensitive_extractor(dict_keys[-1], None, data)
+
+
+def attribute_key_extractor(attr, _, data):
+ return data.get(attr)
+
+
+def attribute_key_case_insensitive_extractor(attr, _, data):
+ found_key = None
+ lower_attr = attr.lower()
+ for key in data:
+ if lower_attr == key.lower():
+ found_key = key
+ break
+
+ return data.get(found_key)
+
+
+def _extract_name_from_internal_type(internal_type):
+ """Given an internal type XML description, extract correct XML name with namespace.
+
+ :param dict internal_type: An model type
+ :rtype: tuple
+ :returns: A tuple XML name + namespace dict
+ """
+ internal_type_xml_map = getattr(internal_type, "_xml_map", {})
+ xml_name = internal_type_xml_map.get("name", internal_type.__name__)
+ xml_ns = internal_type_xml_map.get("ns", None)
+ if xml_ns:
+ xml_name = "{{{}}}{}".format(xml_ns, xml_name)
+ return xml_name
+
+
+def xml_key_extractor(attr, attr_desc, data): # pylint: disable=unused-argument,too-many-return-statements
+ if isinstance(data, dict):
+ return None
+
+ # Test if this model is XML ready first
+ if not isinstance(data, ET.Element):
+ return None
+
+ xml_desc = attr_desc.get("xml", {})
+ xml_name = xml_desc.get("name", attr_desc["key"])
+
+ # Look for a children
+ is_iter_type = attr_desc["type"].startswith("[")
+ is_wrapped = xml_desc.get("wrapped", False)
+ internal_type = attr_desc.get("internalType", None)
+ internal_type_xml_map = getattr(internal_type, "_xml_map", {})
+
+ # Integrate namespace if necessary
+ xml_ns = xml_desc.get("ns", internal_type_xml_map.get("ns", None))
+ if xml_ns:
+ xml_name = "{{{}}}{}".format(xml_ns, xml_name)
+
+ # If it's an attribute, that's simple
+ if xml_desc.get("attr", False):
+ return data.get(xml_name)
+
+ # If it's x-ms-text, that's simple too
+ if xml_desc.get("text", False):
+ return data.text
+
+ # Scenario where I take the local name:
+ # - Wrapped node
+ # - Internal type is an enum (considered basic types)
+ # - Internal type has no XML/Name node
+ if is_wrapped or (internal_type and (issubclass(internal_type, Enum) or "name" not in internal_type_xml_map)):
+ children = data.findall(xml_name)
+ # If internal type has a local name and it's not a list, I use that name
+ elif not is_iter_type and internal_type and "name" in internal_type_xml_map:
+ xml_name = _extract_name_from_internal_type(internal_type)
+ children = data.findall(xml_name)
+ # That's an array
+ else:
+ if internal_type: # Complex type, ignore itemsName and use the complex type name
+ items_name = _extract_name_from_internal_type(internal_type)
+ else:
+ items_name = xml_desc.get("itemsName", xml_name)
+ children = data.findall(items_name)
+
+ if len(children) == 0:
+ if is_iter_type:
+ if is_wrapped:
+ return None # is_wrapped no node, we want None
+ return [] # not wrapped, assume empty list
+ return None # Assume it's not there, maybe an optional node.
+
+ # If is_iter_type and not wrapped, return all found children
+ if is_iter_type:
+ if not is_wrapped:
+ return children
+ # Iter and wrapped, should have found one node only (the wrap one)
+ if len(children) != 1:
+ raise DeserializationError(
+ "Tried to deserialize an array not wrapped, and found several nodes '{}'. Maybe you should declare this array as wrapped?".format( # pylint: disable=line-too-long
+ xml_name
+ )
+ )
+ return list(children[0]) # Might be empty list and that's ok.
+
+ # Here it's not a itertype, we should have found one element only or empty
+ if len(children) > 1:
+ raise DeserializationError("Find several XML '{}' where it was not expected".format(xml_name))
+ return children[0]
+
+
+class Deserializer(object):
+ """Response object model deserializer.
+
+ :param dict classes: Class type dictionary for deserializing complex types.
+ :ivar list key_extractors: Ordered list of extractors to be used by this deserializer.
+ """
+
+ basic_types = {str: "str", int: "int", bool: "bool", float: "float"}
+
+ valid_date = re.compile(r"\d{4}[-]\d{2}[-]\d{2}T\d{2}:\d{2}:\d{2}\.?\d*Z?[-+]?[\d{2}]?:?[\d{2}]?")
+
+ def __init__(self, classes: Optional[Mapping[str, type]] = None) -> None:
+ self.deserialize_type = {
+ "iso-8601": Deserializer.deserialize_iso,
+ "rfc-1123": Deserializer.deserialize_rfc,
+ "unix-time": Deserializer.deserialize_unix,
+ "duration": Deserializer.deserialize_duration,
+ "date": Deserializer.deserialize_date,
+ "time": Deserializer.deserialize_time,
+ "decimal": Deserializer.deserialize_decimal,
+ "long": Deserializer.deserialize_long,
+ "bytearray": Deserializer.deserialize_bytearray,
+ "base64": Deserializer.deserialize_base64,
+ "object": self.deserialize_object,
+ "[]": self.deserialize_iter,
+ "{}": self.deserialize_dict,
+ }
+ self.deserialize_expected_types = {
+ "duration": (isodate.Duration, datetime.timedelta),
+ "iso-8601": (datetime.datetime),
+ }
+ self.dependencies: Dict[str, type] = dict(classes) if classes else {}
+ self.key_extractors = [rest_key_extractor, xml_key_extractor]
+ # Additional properties only works if the "rest_key_extractor" is used to
+ # extract the keys. Making it to work whatever the key extractor is too much
+ # complicated, with no real scenario for now.
+ # So adding a flag to disable additional properties detection. This flag should be
+ # used if your expect the deserialization to NOT come from a JSON REST syntax.
+ # Otherwise, result are unexpected
+ self.additional_properties_detection = True
+
+ def __call__(self, target_obj, response_data, content_type=None):
+ """Call the deserializer to process a REST response.
+
+ :param str target_obj: Target data type to deserialize to.
+ :param requests.Response response_data: REST response object.
+ :param str content_type: Swagger "produces" if available.
+ :raises: DeserializationError if deserialization fails.
+ :return: Deserialized object.
+ :rtype: object
+ """
+ data = self._unpack_content(response_data, content_type)
+ return self._deserialize(target_obj, data)
+
+ def _deserialize(self, target_obj, data): # pylint: disable=inconsistent-return-statements
+ """Call the deserializer on a model.
+
+ Data needs to be already deserialized as JSON or XML ElementTree
+
+ :param str target_obj: Target data type to deserialize to.
+ :param object data: Object to deserialize.
+ :raises: DeserializationError if deserialization fails.
+ :return: Deserialized object.
+ :rtype: object
+ """
+ # This is already a model, go recursive just in case
+ if hasattr(data, "_attribute_map"):
+ constants = [name for name, config in getattr(data, "_validation", {}).items() if config.get("constant")]
+ try:
+ for attr, mapconfig in data._attribute_map.items(): # pylint: disable=protected-access
+ if attr in constants:
+ continue
+ value = getattr(data, attr)
+ if value is None:
+ continue
+ local_type = mapconfig["type"]
+ internal_data_type = local_type.strip("[]{}")
+ if internal_data_type not in self.dependencies or isinstance(internal_data_type, Enum):
+ continue
+ setattr(data, attr, self._deserialize(local_type, value))
+ return data
+ except AttributeError:
+ return
+
+ response, class_name = self._classify_target(target_obj, data)
+
+ if isinstance(response, str):
+ return self.deserialize_data(data, response)
+ if isinstance(response, type) and issubclass(response, Enum):
+ return self.deserialize_enum(data, response)
+
+ if data is None or data is CoreNull:
+ return data
+ try:
+ attributes = response._attribute_map # type: ignore # pylint: disable=protected-access
+ d_attrs = {}
+ for attr, attr_desc in attributes.items():
+ # Check empty string. If it's not empty, someone has a real "additionalProperties"...
+ if attr == "additional_properties" and attr_desc["key"] == "":
+ continue
+ raw_value = None
+ # Enhance attr_desc with some dynamic data
+ attr_desc = attr_desc.copy() # Do a copy, do not change the real one
+ internal_data_type = attr_desc["type"].strip("[]{}")
+ if internal_data_type in self.dependencies:
+ attr_desc["internalType"] = self.dependencies[internal_data_type]
+
+ for key_extractor in self.key_extractors:
+ found_value = key_extractor(attr, attr_desc, data)
+ if found_value is not None:
+ if raw_value is not None and raw_value != found_value:
+ msg = (
+ "Ignoring extracted value '%s' from %s for key '%s'"
+ " (duplicate extraction, follow extractors order)"
+ )
+ _LOGGER.warning(msg, found_value, key_extractor, attr)
+ continue
+ raw_value = found_value
+
+ value = self.deserialize_data(raw_value, attr_desc["type"])
+ d_attrs[attr] = value
+ except (AttributeError, TypeError, KeyError) as err:
+ msg = "Unable to deserialize to object: " + class_name # type: ignore
+ raise DeserializationError(msg) from err
+ additional_properties = self._build_additional_properties(attributes, data)
+ return self._instantiate_model(response, d_attrs, additional_properties)
+
+ def _build_additional_properties(self, attribute_map, data):
+ if not self.additional_properties_detection:
+ return None
+ if "additional_properties" in attribute_map and attribute_map.get("additional_properties", {}).get("key") != "":
+ # Check empty string. If it's not empty, someone has a real "additionalProperties"
+ return None
+ if isinstance(data, ET.Element):
+ data = {el.tag: el.text for el in data}
+
+ known_keys = {
+ _decode_attribute_map_key(_FLATTEN.split(desc["key"])[0])
+ for desc in attribute_map.values()
+ if desc["key"] != ""
+ }
+ present_keys = set(data.keys())
+ missing_keys = present_keys - known_keys
+ return {key: data[key] for key in missing_keys}
+
+ def _classify_target(self, target, data):
+ """Check to see whether the deserialization target object can
+ be classified into a subclass.
+ Once classification has been determined, initialize object.
+
+ :param str target: The target object type to deserialize to.
+ :param str/dict data: The response data to deserialize.
+ :return: The classified target object and its class name.
+ :rtype: tuple
+ """
+ if target is None:
+ return None, None
+
+ if isinstance(target, str):
+ try:
+ target = self.dependencies[target]
+ except KeyError:
+ return target, target
+
+ try:
+ target = target._classify(data, self.dependencies) # type: ignore # pylint: disable=protected-access
+ except AttributeError:
+ pass # Target is not a Model, no classify
+ return target, target.__class__.__name__ # type: ignore
+
+ def failsafe_deserialize(self, target_obj, data, content_type=None):
+ """Ignores any errors encountered in deserialization,
+ and falls back to not deserializing the object. Recommended
+ for use in error deserialization, as we want to return the
+ HttpResponseError to users, and not have them deal with
+ a deserialization error.
+
+ :param str target_obj: The target object type to deserialize to.
+ :param str/dict data: The response data to deserialize.
+ :param str content_type: Swagger "produces" if available.
+ :return: Deserialized object.
+ :rtype: object
+ """
+ try:
+ return self(target_obj, data, content_type=content_type)
+ except: # pylint: disable=bare-except
+ _LOGGER.debug(
+ "Ran into a deserialization error. Ignoring since this is failsafe deserialization", exc_info=True
+ )
+ return None
+
+ @staticmethod
+ def _unpack_content(raw_data, content_type=None):
+ """Extract the correct structure for deserialization.
+
+ If raw_data is a PipelineResponse, try to extract the result of RawDeserializer.
+ if we can't, raise. Your Pipeline should have a RawDeserializer.
+
+ If not a pipeline response and raw_data is bytes or string, use content-type
+ to decode it. If no content-type, try JSON.
+
+ If raw_data is something else, bypass all logic and return it directly.
+
+ :param obj raw_data: Data to be processed.
+ :param str content_type: How to parse if raw_data is a string/bytes.
+ :raises JSONDecodeError: If JSON is requested and parsing is impossible.
+ :raises UnicodeDecodeError: If bytes is not UTF8
+ :rtype: object
+ :return: Unpacked content.
+ """
+ # Assume this is enough to detect a Pipeline Response without importing it
+ context = getattr(raw_data, "context", {})
+ if context:
+ if RawDeserializer.CONTEXT_NAME in context:
+ return context[RawDeserializer.CONTEXT_NAME]
+ raise ValueError("This pipeline didn't have the RawDeserializer policy; can't deserialize")
+
+ # Assume this is enough to recognize universal_http.ClientResponse without importing it
+ if hasattr(raw_data, "body"):
+ return RawDeserializer.deserialize_from_http_generics(raw_data.text(), raw_data.headers)
+
+ # Assume this enough to recognize requests.Response without importing it.
+ if hasattr(raw_data, "_content_consumed"):
+ return RawDeserializer.deserialize_from_http_generics(raw_data.text, raw_data.headers)
+
+ if isinstance(raw_data, (str, bytes)) or hasattr(raw_data, "read"):
+ return RawDeserializer.deserialize_from_text(raw_data, content_type) # type: ignore
+ return raw_data
+
+ def _instantiate_model(self, response, attrs, additional_properties=None):
+ """Instantiate a response model passing in deserialized args.
+
+ :param Response response: The response model class.
+ :param dict attrs: The deserialized response attributes.
+ :param dict additional_properties: Additional properties to be set.
+ :rtype: Response
+ :return: The instantiated response model.
+ """
+ if callable(response):
+ subtype = getattr(response, "_subtype_map", {})
+ try:
+ readonly = [
+ k for k, v in response._validation.items() if v.get("readonly") # pylint: disable=protected-access
+ ]
+ const = [
+ k for k, v in response._validation.items() if v.get("constant") # pylint: disable=protected-access
+ ]
+ 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
+ return response_obj
+ except TypeError as err:
+ msg = "Unable to deserialize {} into model {}. ".format(kwargs, response) # type: ignore
+ raise DeserializationError(msg + str(err)) from err
+ else:
+ try:
+ for attr, value in attrs.items():
+ setattr(response, attr, value)
+ return response
+ except Exception as exp:
+ msg = "Unable to populate response model. "
+ msg += "Type: {}, Error: {}".format(type(response), exp)
+ raise DeserializationError(msg) from exp
+
+ def deserialize_data(self, data, data_type): # pylint: disable=too-many-return-statements
+ """Process data for deserialization according to data type.
+
+ :param str data: The response string to be deserialized.
+ :param str data_type: The type to deserialize to.
+ :raises: DeserializationError if deserialization fails.
+ :return: Deserialized object.
+ :rtype: object
+ """
+ if data is None:
+ return data
+
+ try:
+ if not data_type:
+ return data
+ if data_type in self.basic_types.values():
+ return self.deserialize_basic(data, data_type)
+ if data_type in self.deserialize_type:
+ if isinstance(data, self.deserialize_expected_types.get(data_type, tuple())):
+ return data
+
+ is_a_text_parsing_type = lambda x: x not in [ # pylint: disable=unnecessary-lambda-assignment
+ "object",
+ "[]",
+ r"{}",
+ ]
+ if isinstance(data, ET.Element) and is_a_text_parsing_type(data_type) and not data.text:
+ return None
+ data_val = self.deserialize_type[data_type](data)
+ return data_val
+
+ iter_type = data_type[0] + data_type[-1]
+ if iter_type in self.deserialize_type:
+ return self.deserialize_type[iter_type](data, data_type[1:-1])
+
+ obj_type = self.dependencies[data_type]
+ if issubclass(obj_type, Enum):
+ if isinstance(data, ET.Element):
+ data = data.text
+ return self.deserialize_enum(data, obj_type)
+
+ except (ValueError, TypeError, AttributeError) as err:
+ msg = "Unable to deserialize response data."
+ msg += " Data: {}, {}".format(data, data_type)
+ raise DeserializationError(msg) from err
+ return self._deserialize(obj_type, data)
+
+ def deserialize_iter(self, attr, iter_type):
+ """Deserialize an iterable.
+
+ :param list attr: Iterable to be deserialized.
+ :param str iter_type: The type of object in the iterable.
+ :return: Deserialized iterable.
+ :rtype: list
+ """
+ if attr is None:
+ return None
+ if isinstance(attr, ET.Element): # If I receive an element here, get the children
+ attr = list(attr)
+ if not isinstance(attr, (list, set)):
+ raise DeserializationError("Cannot deserialize as [{}] an object of type {}".format(iter_type, type(attr)))
+ return [self.deserialize_data(a, iter_type) for a in attr]
+
+ def deserialize_dict(self, attr, dict_type):
+ """Deserialize a dictionary.
+
+ :param dict/list attr: Dictionary to be deserialized. Also accepts
+ a list of key, value pairs.
+ :param str dict_type: The object type of the items in the dictionary.
+ :return: Deserialized dictionary.
+ :rtype: dict
+ """
+ if isinstance(attr, list):
+ return {x["key"]: self.deserialize_data(x["value"], dict_type) for x in attr}
+
+ if isinstance(attr, ET.Element):
+ # Transform value into {"Key": "value"}
+ attr = {el.tag: el.text for el in attr}
+ return {k: self.deserialize_data(v, dict_type) for k, v in attr.items()}
+
+ def deserialize_object(self, attr, **kwargs): # pylint: disable=too-many-return-statements
+ """Deserialize a generic object.
+ This will be handled as a dictionary.
+
+ :param dict attr: Dictionary to be deserialized.
+ :return: Deserialized object.
+ :rtype: dict
+ :raises: TypeError if non-builtin datatype encountered.
+ """
+ if attr is None:
+ return None
+ if isinstance(attr, ET.Element):
+ # Do no recurse on XML, just return the tree as-is
+ return attr
+ if isinstance(attr, str):
+ return self.deserialize_basic(attr, "str")
+ obj_type = type(attr)
+ if obj_type in self.basic_types:
+ return self.deserialize_basic(attr, self.basic_types[obj_type])
+ if obj_type is _long_type:
+ return self.deserialize_long(attr)
+
+ if obj_type == dict:
+ deserialized = {}
+ for key, value in attr.items():
+ try:
+ deserialized[key] = self.deserialize_object(value, **kwargs)
+ except ValueError:
+ deserialized[key] = None
+ return deserialized
+
+ if obj_type == list:
+ deserialized = []
+ for obj in attr:
+ try:
+ deserialized.append(self.deserialize_object(obj, **kwargs))
+ except ValueError:
+ pass
+ return deserialized
+
+ error = "Cannot deserialize generic object with type: "
+ raise TypeError(error + str(obj_type))
+
+ def deserialize_basic(self, attr, data_type): # pylint: disable=too-many-return-statements
+ """Deserialize basic builtin data type from string.
+ Will attempt to convert to str, int, float and bool.
+ This function will also accept '1', '0', 'true' and 'false' as
+ valid bool values.
+
+ :param str attr: response string to be deserialized.
+ :param str data_type: deserialization data type.
+ :return: Deserialized basic type.
+ :rtype: str, int, float or bool
+ :raises: TypeError if string format is not valid.
+ """
+ # If we're here, data is supposed to be a basic type.
+ # If it's still an XML node, take the text
+ if isinstance(attr, ET.Element):
+ attr = attr.text
+ if not attr:
+ if data_type == "str":
+ # None or '', node is empty string.
+ return ""
+ # None or '', node with a strong type is None.
+ # Don't try to model "empty bool" or "empty int"
+ return None
+
+ if data_type == "bool":
+ if attr in [True, False, 1, 0]:
+ return bool(attr)
+ if isinstance(attr, str):
+ if attr.lower() in ["true", "1"]:
+ return True
+ if attr.lower() in ["false", "0"]:
+ return False
+ raise TypeError("Invalid boolean value: {}".format(attr))
+
+ if data_type == "str":
+ return self.deserialize_unicode(attr)
+ return eval(data_type)(attr) # nosec # pylint: disable=eval-used
+
+ @staticmethod
+ def deserialize_unicode(data):
+ """Preserve unicode objects in Python 2, otherwise return data
+ as a string.
+
+ :param str data: response string to be deserialized.
+ :return: Deserialized string.
+ :rtype: str or unicode
+ """
+ # We might be here because we have an enum modeled as string,
+ # and we try to deserialize a partial dict with enum inside
+ if isinstance(data, Enum):
+ return data
+
+ # Consider this is real string
+ try:
+ if isinstance(data, unicode): # type: ignore
+ return data
+ except NameError:
+ return str(data)
+ return str(data)
+
+ @staticmethod
+ def deserialize_enum(data, enum_obj):
+ """Deserialize string into enum object.
+
+ If the string is not a valid enum value it will be returned as-is
+ and a warning will be logged.
+
+ :param str data: Response string to be deserialized. If this value is
+ None or invalid it will be returned as-is.
+ :param Enum enum_obj: Enum object to deserialize to.
+ :return: Deserialized enum object.
+ :rtype: Enum
+ """
+ if isinstance(data, enum_obj) or data is None:
+ return data
+ if isinstance(data, Enum):
+ data = data.value
+ if isinstance(data, int):
+ # Workaround. We might consider remove it in the future.
+ try:
+ return list(enum_obj.__members__.values())[data]
+ except IndexError as exc:
+ error = "{!r} is not a valid index for enum {!r}"
+ raise DeserializationError(error.format(data, enum_obj)) from exc
+ try:
+ return enum_obj(str(data))
+ except ValueError:
+ for enum_value in enum_obj:
+ if enum_value.value.lower() == str(data).lower():
+ return enum_value
+ # We don't fail anymore for unknown value, we deserialize as a string
+ _LOGGER.warning("Deserializer is not able to find %s as valid enum in %s", data, enum_obj)
+ return Deserializer.deserialize_unicode(data)
+
+ @staticmethod
+ def deserialize_bytearray(attr):
+ """Deserialize string into bytearray.
+
+ :param str attr: response string to be deserialized.
+ :return: Deserialized bytearray
+ :rtype: bytearray
+ :raises: TypeError if string format invalid.
+ """
+ if isinstance(attr, ET.Element):
+ attr = attr.text
+ return bytearray(b64decode(attr)) # type: ignore
+
+ @staticmethod
+ def deserialize_base64(attr):
+ """Deserialize base64 encoded string into string.
+
+ :param str attr: response string to be deserialized.
+ :return: Deserialized base64 string
+ :rtype: bytearray
+ :raises: TypeError if string format invalid.
+ """
+ if isinstance(attr, ET.Element):
+ attr = attr.text
+ padding = "=" * (3 - (len(attr) + 3) % 4) # type: ignore
+ attr = attr + padding # type: ignore
+ encoded = attr.replace("-", "+").replace("_", "/")
+ return b64decode(encoded)
+
+ @staticmethod
+ def deserialize_decimal(attr):
+ """Deserialize string into Decimal object.
+
+ :param str attr: response string to be deserialized.
+ :return: Deserialized decimal
+ :raises: DeserializationError if string format invalid.
+ :rtype: decimal
+ """
+ if isinstance(attr, ET.Element):
+ attr = attr.text
+ try:
+ return decimal.Decimal(str(attr)) # type: ignore
+ except decimal.DecimalException as err:
+ msg = "Invalid decimal {}".format(attr)
+ raise DeserializationError(msg) from err
+
+ @staticmethod
+ def deserialize_long(attr):
+ """Deserialize string into long (Py2) or int (Py3).
+
+ :param str attr: response string to be deserialized.
+ :return: Deserialized int
+ :rtype: long or int
+ :raises: ValueError if string format invalid.
+ """
+ if isinstance(attr, ET.Element):
+ attr = attr.text
+ return _long_type(attr) # type: ignore
+
+ @staticmethod
+ def deserialize_duration(attr):
+ """Deserialize ISO-8601 formatted string into TimeDelta object.
+
+ :param str attr: response string to be deserialized.
+ :return: Deserialized duration
+ :rtype: TimeDelta
+ :raises: DeserializationError if string format invalid.
+ """
+ if isinstance(attr, ET.Element):
+ attr = attr.text
+ try:
+ duration = isodate.parse_duration(attr)
+ except (ValueError, OverflowError, AttributeError) as err:
+ msg = "Cannot deserialize duration object."
+ raise DeserializationError(msg) from err
+ return duration
+
+ @staticmethod
+ def deserialize_date(attr):
+ """Deserialize ISO-8601 formatted string into Date object.
+
+ :param str attr: response string to be deserialized.
+ :return: Deserialized date
+ :rtype: Date
+ :raises: DeserializationError if string format invalid.
+ """
+ if isinstance(attr, ET.Element):
+ attr = attr.text
+ if re.search(r"[^\W\d_]", attr, re.I + re.U): # type: ignore
+ raise DeserializationError("Date must have only digits and -. Received: %s" % attr)
+ # This must NOT use defaultmonth/defaultday. Using None ensure this raises an exception.
+ return isodate.parse_date(attr, defaultmonth=0, defaultday=0)
+
+ @staticmethod
+ def deserialize_time(attr):
+ """Deserialize ISO-8601 formatted string into time object.
+
+ :param str attr: response string to be deserialized.
+ :return: Deserialized time
+ :rtype: datetime.time
+ :raises: DeserializationError if string format invalid.
+ """
+ if isinstance(attr, ET.Element):
+ attr = attr.text
+ if re.search(r"[^\W\d_]", attr, re.I + re.U): # type: ignore
+ raise DeserializationError("Date must have only digits and -. Received: %s" % attr)
+ return isodate.parse_time(attr)
+
+ @staticmethod
+ def deserialize_rfc(attr):
+ """Deserialize RFC-1123 formatted string into Datetime object.
+
+ :param str attr: response string to be deserialized.
+ :return: Deserialized RFC datetime
+ :rtype: Datetime
+ :raises: DeserializationError if string format invalid.
+ """
+ if isinstance(attr, ET.Element):
+ attr = attr.text
+ try:
+ parsed_date = email.utils.parsedate_tz(attr) # type: ignore
+ date_obj = datetime.datetime(
+ *parsed_date[:6], tzinfo=_FixedOffset(datetime.timedelta(minutes=(parsed_date[9] or 0) / 60))
+ )
+ if not date_obj.tzinfo:
+ date_obj = date_obj.astimezone(tz=TZ_UTC)
+ except ValueError as err:
+ msg = "Cannot deserialize to rfc datetime object."
+ raise DeserializationError(msg) from err
+ return date_obj
+
+ @staticmethod
+ def deserialize_iso(attr):
+ """Deserialize ISO-8601 formatted string into Datetime object.
+
+ :param str attr: response string to be deserialized.
+ :return: Deserialized ISO datetime
+ :rtype: Datetime
+ :raises: DeserializationError if string format invalid.
+ """
+ if isinstance(attr, ET.Element):
+ attr = attr.text
+ try:
+ attr = attr.upper() # type: ignore
+ match = Deserializer.valid_date.match(attr)
+ if not match:
+ raise ValueError("Invalid datetime string: " + attr)
+
+ check_decimal = attr.split(".")
+ if len(check_decimal) > 1:
+ decimal_str = ""
+ for digit in check_decimal[1]:
+ if digit.isdigit():
+ decimal_str += digit
+ else:
+ break
+ if len(decimal_str) > 6:
+ attr = attr.replace(decimal_str, decimal_str[0:6])
+
+ date_obj = isodate.parse_datetime(attr)
+ test_utc = date_obj.utctimetuple()
+ if test_utc.tm_year > 9999 or test_utc.tm_year < 1:
+ raise OverflowError("Hit max or min date")
+ except (ValueError, OverflowError, AttributeError) as err:
+ msg = "Cannot deserialize datetime object."
+ raise DeserializationError(msg) from err
+ return date_obj
+
+ @staticmethod
+ def deserialize_unix(attr):
+ """Serialize Datetime object into IntTime format.
+ This is represented as seconds.
+
+ :param int attr: Object to be serialized.
+ :return: Deserialized datetime
+ :rtype: Datetime
+ :raises: DeserializationError if format invalid
+ """
+ if isinstance(attr, ET.Element):
+ attr = int(attr.text) # type: ignore
+ try:
+ attr = int(attr)
+ date_obj = datetime.datetime.fromtimestamp(attr, TZ_UTC)
+ except ValueError as err:
+ msg = "Cannot deserialize to unix datetime object."
+ raise DeserializationError(msg) from err
+ return date_obj
diff --git a/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/_validation.py b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/_validation.py
new file mode 100644
index 000000000000..752b2822f9d3
--- /dev/null
+++ b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/_validation.py
@@ -0,0 +1,50 @@
+# --------------------------------------------------------------------------
+# 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/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/_version.py b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/_version.py
new file mode 100644
index 000000000000..0ec13ea52bbf
--- /dev/null
+++ b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/_version.py
@@ -0,0 +1,9 @@
+# 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.
+# --------------------------------------------------------------------------
+
+VERSION = "1.0.0"
diff --git a/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/aio/__init__.py b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/aio/__init__.py
new file mode 100644
index 000000000000..35e2a98d1069
--- /dev/null
+++ b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/aio/__init__.py
@@ -0,0 +1,23 @@
+# 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 ._client import ConversationsClient
+
+try:
+ from ._patch import __all__ as _patch_all
+ from ._patch import * # pylint: disable=unused-wildcard-import
+except ImportError:
+ _patch_all = []
+from ._patch import patch_sdk as _patch_sdk
+
+__all__ = [
+ "ConversationsClient",
+]
+__all__.extend([p for p in _patch_all if p not in __all__]) # pyright: ignore
+
+_patch_sdk()
diff --git a/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/aio/_client.py b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/aio/_client.py
new file mode 100644
index 000000000000..b5c63d57c668
--- /dev/null
+++ b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/aio/_client.py
@@ -0,0 +1,132 @@
+# 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 copy import deepcopy
+from typing import Any, Awaitable, TYPE_CHECKING, Union
+from typing_extensions import Self
+
+from azure.core import AsyncPipelineClient
+from azure.core.credentials import AzureKeyCredential
+from azure.core.pipeline import policies
+from azure.core.rest import AsyncHttpResponse, HttpRequest
+
+from .._serialization import Deserializer, Serializer
+from ._configuration import ConversationsClientConfiguration
+from .operations import ConversationalAnalysisAuthoringOperations
+
+if TYPE_CHECKING:
+ from azure.core.credentials_async import AsyncTokenCredential
+
+
+class ConversationsClient:
+ """The language service API is a suite of natural language processing (NLP) skills
+ built with best-in-class Microsoft machine learning algorithms. The API can be
+ used to analyze unstructured text for tasks such as sentiment analysis, key
+ phrase extraction, language detection and question answering. Further
+ documentation can be found in :code:`https://docs.microsoft.com/en-us/azure/cognitive-services/language-service/overview`.The
+ language service conversations API is a suite of natural language processing (NLP) skills that
+ can be used to analyze structured conversations (textual or spoken). The synchronous API in
+ this suite accepts a request and mediates among multiple language projects, such as LUIS
+ Generally Available, Question Answering, Conversational Language Understanding, and then calls
+ the best candidate service to handle the request. At last, it returns a response with the
+ candidate service's response as a payload.\\n\\n In some cases, this API needs to forward
+ requests and responses between the caller and an upstream service. The asynchronous APIs in
+ this suite enable tasks like Conversation Summarization and Conversational PII detection.
+
+ :ivar conversational_analysis_authoring: ConversationalAnalysisAuthoringOperations operations
+ :vartype conversational_analysis_authoring:
+ azure.ai.language.authoring.analyzeconversations.aio.operations.ConversationalAnalysisAuthoringOperations
+ :param endpoint: Supported Cognitive Services endpoint (e.g.,
+ https://:code:``.api.cognitiveservices.azure.com). Required.
+ :type endpoint: str
+ :param endpoint: Required.
+ :type endpoint: str
+ :param credential: Credential used to authenticate requests to the service. 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
+ "2023-04-15-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, endpoint: str, credential: Union[AzureKeyCredential, "AsyncTokenCredential"], **kwargs: Any
+ ) -> None:
+ _endpoint = "{Endpoint}/language"
+ self._config = ConversationsClientConfiguration(
+ endpoint=endpoint, endpoint=endpoint, credential=credential, **kwargs
+ )
+ _policies = kwargs.pop("policies", None)
+ if _policies is None:
+ _policies = [
+ policies.RequestIdPolicy(**kwargs),
+ self._config.headers_policy,
+ self._config.user_agent_policy,
+ self._config.proxy_policy,
+ policies.ContentDecodePolicy(**kwargs),
+ self._config.redirect_policy,
+ self._config.retry_policy,
+ self._config.authentication_policy,
+ self._config.custom_hook_policy,
+ self._config.logging_policy,
+ policies.DistributedTracingPolicy(**kwargs),
+ policies.SensitiveHeaderCleanupPolicy(**kwargs) if self._config.redirect_policy else None,
+ self._config.http_logging_policy,
+ ]
+ self._client: AsyncPipelineClient = AsyncPipelineClient(base_url=_endpoint, policies=_policies, **kwargs)
+
+ self._serialize = Serializer()
+ self._deserialize = Deserializer()
+ self._serialize.client_side_validation = False
+ self.conversational_analysis_authoring = ConversationalAnalysisAuthoringOperations(
+ self._client, self._config, self._serialize, self._deserialize
+ )
+
+ def send_request(
+ self, request: HttpRequest, *, stream: bool = False, **kwargs: Any
+ ) -> Awaitable[AsyncHttpResponse]:
+ """Runs the network request through the client's chained policies.
+
+ >>> from azure.core.rest import HttpRequest
+ >>> request = HttpRequest("GET", "https://www.example.org/")
+
+ >>> response = await client.send_request(request)
+
+
+ For more information on this code flow, see https://aka.ms/azsdk/dpcodegen/python/send_request
+
+ :param request: The network request you want to make. Required.
+ :type request: ~azure.core.rest.HttpRequest
+ :keyword bool stream: Whether the response payload will be streamed. Defaults to False.
+ :return: The response of your network call. Does not do error handling on your response.
+ :rtype: ~azure.core.rest.AsyncHttpResponse
+ """
+
+ request_copy = deepcopy(request)
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+
+ request_copy.url = self._client.format_url(request_copy.url, **path_format_arguments)
+ return self._client.send_request(request_copy, stream=stream, **kwargs) # type: ignore
+
+ async def close(self) -> None:
+ await self._client.close()
+
+ async def __aenter__(self) -> Self:
+ await self._client.__aenter__()
+ return self
+
+ async def __aexit__(self, *exc_details: Any) -> None:
+ await self._client.__aexit__(*exc_details)
diff --git a/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/aio/_configuration.py b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/aio/_configuration.py
new file mode 100644
index 000000000000..b62a3b07a99e
--- /dev/null
+++ b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/aio/_configuration.py
@@ -0,0 +1,80 @@
+# 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 typing import Any, TYPE_CHECKING, Union
+
+from azure.core.credentials import AzureKeyCredential
+from azure.core.pipeline import policies
+
+from .._version import VERSION
+
+if TYPE_CHECKING:
+ from azure.core.credentials_async import AsyncTokenCredential
+
+
+class ConversationsClientConfiguration: # pylint: disable=too-many-instance-attributes
+ """Configuration for ConversationsClient.
+
+ Note that all parameters used to create this instance are saved as instance
+ attributes.
+
+ :param endpoint: Supported Cognitive Services endpoint (e.g.,
+ https://:code:``.api.cognitiveservices.azure.com). Required.
+ :type endpoint: str
+ :param endpoint: Required.
+ :type endpoint: str
+ :param credential: Credential used to authenticate requests to the service. 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
+ "2023-04-15-preview". Note that overriding this default value may result in unsupported
+ behavior.
+ :paramtype api_version: str
+ """
+
+ def __init__(
+ self, endpoint: str, endpoint: str, credential: Union[AzureKeyCredential, "AsyncTokenCredential"], **kwargs: Any
+ ) -> None:
+ api_version: str = kwargs.pop("api_version", "2023-04-15-preview")
+
+ if endpoint is None:
+ raise ValueError("Parameter 'endpoint' must not be None.")
+ if endpoint is None:
+ raise ValueError("Parameter 'endpoint' must not be None.")
+ if credential is None:
+ raise ValueError("Parameter 'credential' must not be None.")
+
+ self.endpoint = endpoint
+ self.endpoint = endpoint
+ self.credential = credential
+ self.api_version = api_version
+ self.credential_scopes = kwargs.pop("credential_scopes", ["https://cognitiveservices.azure.com/.default"])
+ kwargs.setdefault("sdk_moniker", "Azure.AI.Language.Authoring.Analyzeconversations/{}".format(VERSION))
+ self.polling_interval = kwargs.get("polling_interval", 30)
+ self._configure(**kwargs)
+
+ def _infer_policy(self, **kwargs):
+ if isinstance(self.credential, AzureKeyCredential):
+ return policies.AzureKeyCredentialPolicy(self.credential, "Ocp-Apim-Subscription-Key", **kwargs)
+ if hasattr(self.credential, "get_token"):
+ return policies.AsyncBearerTokenCredentialPolicy(self.credential, *self.credential_scopes, **kwargs)
+ raise TypeError(f"Unsupported credential: {self.credential}")
+
+ def _configure(self, **kwargs: Any) -> None:
+ self.user_agent_policy = kwargs.get("user_agent_policy") or policies.UserAgentPolicy(**kwargs)
+ self.headers_policy = kwargs.get("headers_policy") or policies.HeadersPolicy(**kwargs)
+ self.proxy_policy = kwargs.get("proxy_policy") or policies.ProxyPolicy(**kwargs)
+ self.logging_policy = kwargs.get("logging_policy") or policies.NetworkTraceLoggingPolicy(**kwargs)
+ self.http_logging_policy = kwargs.get("http_logging_policy") or policies.HttpLoggingPolicy(**kwargs)
+ self.custom_hook_policy = kwargs.get("custom_hook_policy") or policies.CustomHookPolicy(**kwargs)
+ self.redirect_policy = kwargs.get("redirect_policy") or policies.AsyncRedirectPolicy(**kwargs)
+ self.retry_policy = kwargs.get("retry_policy") or policies.AsyncRetryPolicy(**kwargs)
+ self.authentication_policy = kwargs.get("authentication_policy")
+ if self.credential and not self.authentication_policy:
+ self.authentication_policy = self._infer_policy(**kwargs)
diff --git a/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/aio/_patch.py b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/aio/_patch.py
new file mode 100644
index 000000000000..f7dd32510333
--- /dev/null
+++ b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/aio/_patch.py
@@ -0,0 +1,20 @@
+# ------------------------------------
+# Copyright (c) Microsoft Corporation.
+# Licensed under the MIT License.
+# ------------------------------------
+"""Customize generated code here.
+
+Follow our quickstart for examples: https://aka.ms/azsdk/python/dpcodegen/python/customize
+"""
+from typing import List
+
+__all__: List[str] = [] # Add all objects you want publicly available to users at this package level
+
+
+def patch_sdk():
+ """Do not remove from this file.
+
+ `patch_sdk` is a last resort escape hatch that allows you to do customizations
+ you can't accomplish using the techniques described in
+ https://aka.ms/azsdk/python/dpcodegen/python/customize
+ """
diff --git a/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/aio/operations/__init__.py b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/aio/operations/__init__.py
new file mode 100644
index 000000000000..e75712aae675
--- /dev/null
+++ b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/aio/operations/__init__.py
@@ -0,0 +1,19 @@
+# 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 ._operations import ConversationalAnalysisAuthoringOperations
+
+from ._patch import __all__ as _patch_all
+from ._patch import * # pylint: disable=unused-wildcard-import
+from ._patch import patch_sdk as _patch_sdk
+
+__all__ = [
+ "ConversationalAnalysisAuthoringOperations",
+]
+__all__.extend([p for p in _patch_all if p not in __all__]) # pyright: ignore
+_patch_sdk()
diff --git a/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/aio/operations/_operations.py b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/aio/operations/_operations.py
new file mode 100644
index 000000000000..83a9f932fe23
--- /dev/null
+++ b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/aio/operations/_operations.py
@@ -0,0 +1,5169 @@
+# pylint: disable=too-many-lines
+# 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 io import IOBase
+import json
+import sys
+from typing import Any, AsyncIterable, AsyncIterator, Callable, Dict, IO, List, Optional, TypeVar, Union, cast, overload
+import urllib.parse
+
+from azure.core.async_paging import AsyncItemPaged, AsyncList
+from azure.core.exceptions import (
+ ClientAuthenticationError,
+ HttpResponseError,
+ ResourceExistsError,
+ ResourceNotFoundError,
+ ResourceNotModifiedError,
+ StreamClosedError,
+ StreamConsumedError,
+ map_error,
+)
+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 import distributed_trace
+from azure.core.tracing.decorator_async import distributed_trace_async
+from azure.core.utils import case_insensitive_dict
+
+from ... import models as _models
+from ..._model_base import SdkJSONEncoder, _deserialize
+from ..._validation import api_version_validation
+from ...operations._operations import (
+ build_conversational_analysis_authoring_assign_deployment_resources_request,
+ build_conversational_analysis_authoring_cancel_training_job_request,
+ build_conversational_analysis_authoring_copy_project_authorization_request,
+ build_conversational_analysis_authoring_copy_project_request,
+ build_conversational_analysis_authoring_create_project_request,
+ build_conversational_analysis_authoring_delete_deployment_from_resources_request,
+ build_conversational_analysis_authoring_delete_deployment_request,
+ build_conversational_analysis_authoring_delete_project_request,
+ build_conversational_analysis_authoring_delete_trained_model_request,
+ build_conversational_analysis_authoring_deploy_project_request,
+ build_conversational_analysis_authoring_evaluate_model_request,
+ build_conversational_analysis_authoring_export_request,
+ build_conversational_analysis_authoring_get_assign_deployment_resources_status_request,
+ build_conversational_analysis_authoring_get_copy_project_status_request,
+ build_conversational_analysis_authoring_get_deployment_delete_from_resources_status_request,
+ build_conversational_analysis_authoring_get_deployment_request,
+ build_conversational_analysis_authoring_get_deployment_status_request,
+ build_conversational_analysis_authoring_get_evaluation_status_request,
+ build_conversational_analysis_authoring_get_export_status_request,
+ build_conversational_analysis_authoring_get_import_status_request,
+ build_conversational_analysis_authoring_get_load_snapshot_status_request,
+ build_conversational_analysis_authoring_get_model_evaluation_results_request,
+ build_conversational_analysis_authoring_get_model_evaluation_summary_request,
+ build_conversational_analysis_authoring_get_project_deletion_status_request,
+ build_conversational_analysis_authoring_get_project_request,
+ build_conversational_analysis_authoring_get_supported_languages_request,
+ build_conversational_analysis_authoring_get_supported_prebuilt_entities_request,
+ build_conversational_analysis_authoring_get_swap_deployments_status_request,
+ build_conversational_analysis_authoring_get_trained_model_request,
+ build_conversational_analysis_authoring_get_training_status_request,
+ build_conversational_analysis_authoring_get_unassign_deployment_resources_status_request,
+ build_conversational_analysis_authoring_import_method_request,
+ build_conversational_analysis_authoring_list_assigned_resource_deployments_request,
+ build_conversational_analysis_authoring_list_deployment_resources_request,
+ build_conversational_analysis_authoring_list_deployments_request,
+ build_conversational_analysis_authoring_list_projects_request,
+ build_conversational_analysis_authoring_list_trained_models_request,
+ build_conversational_analysis_authoring_list_training_config_versions_request,
+ build_conversational_analysis_authoring_list_training_jobs_request,
+ build_conversational_analysis_authoring_load_snapshot_request,
+ build_conversational_analysis_authoring_swap_deployments_request,
+ build_conversational_analysis_authoring_train_request,
+ build_conversational_analysis_authoring_unassign_deployment_resources_request,
+)
+
+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
+_Unset: Any = object()
+T = TypeVar("T")
+ClsType = Optional[Callable[[PipelineResponse[HttpRequest, AsyncHttpResponse], T, Dict[str, Any]], Any]]
+
+
+class ConversationalAnalysisAuthoringOperations: # pylint: disable=too-many-public-methods,name-too-long
+ """
+ .. warning::
+ **DO NOT** instantiate this class directly.
+
+ Instead, you should access the following operations through
+ :class:`~azure.ai.language.authoring.analyzeconversations.aio.ConversationsClient`'s
+ :attr:`conversational_analysis_authoring` attribute.
+ """
+
+ def __init__(self, *args, **kwargs) -> None:
+ input_args = list(args)
+ self._client = input_args.pop(0) if input_args else kwargs.pop("client")
+ self._config = input_args.pop(0) if input_args else kwargs.pop("config")
+ self._serialize = input_args.pop(0) if input_args else kwargs.pop("serializer")
+ self._deserialize = input_args.pop(0) if input_args else kwargs.pop("deserializer")
+
+ @distributed_trace
+ def list_projects(
+ self, *, top: Optional[int] = None, skip: Optional[int] = None, **kwargs: Any
+ ) -> AsyncIterable["_models.ConversationalAnalysisAuthoringProjectMetadata"]:
+ # pylint: disable=line-too-long
+ """Lists the existing projects.
+
+ :keyword top: The number of result items to return. Default value is None.
+ :paramtype top: int
+ :keyword skip: The number of result items to skip. Default value is None.
+ :paramtype skip: int
+ :return: An iterator like instance of ConversationalAnalysisAuthoringProjectMetadata
+ :rtype:
+ ~azure.core.async_paging.AsyncItemPaged[~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringProjectMetadata]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = kwargs.pop("params", {}) or {}
+
+ maxpagesize = kwargs.pop("maxpagesize", None)
+ cls: ClsType[List[_models.ConversationalAnalysisAuthoringProjectMetadata]] = 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_conversational_analysis_authoring_list_projects_request(
+ top=top,
+ skip=skip,
+ maxpagesize=maxpagesize,
+ api_version=self._config.api_version,
+ headers=_headers,
+ params=_params,
+ )
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _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"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _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.ConversationalAnalysisAuthoringProjectMetadata], 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( # 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ return pipeline_response
+
+ return AsyncItemPaged(get_next, extract_data)
+
+ @distributed_trace_async
+ async def get_project(
+ self, project_name: str, **kwargs: Any
+ ) -> _models.ConversationalAnalysisAuthoringProjectMetadata:
+ """Gets the details of a project.
+
+ :param project_name: The new project name. Required.
+ :type project_name: str
+ :return: ConversationalAnalysisAuthoringProjectMetadata. The
+ ConversationalAnalysisAuthoringProjectMetadata is compatible with MutableMapping
+ :rtype:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringProjectMetadata
+ :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[_models.ConversationalAnalysisAuthoringProjectMetadata] = kwargs.pop("cls", None)
+
+ _request = build_conversational_analysis_authoring_get_project_request(
+ project_name=project_name,
+ api_version=self._config.api_version,
+ headers=_headers,
+ params=_params,
+ )
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _stream = kwargs.pop("stream", False)
+ pipeline_response: PipelineResponse = await 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:
+ 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ if _stream:
+ deserialized = response.iter_bytes()
+ else:
+ deserialized = _deserialize(_models.ConversationalAnalysisAuthoringProjectMetadata, response.json())
+
+ if cls:
+ return cls(pipeline_response, deserialized, {}) # type: ignore
+
+ return deserialized # type: ignore
+
+ @overload
+ async def create_project(
+ self,
+ project_name: str,
+ body: _models.ConversationalAnalysisAuthoringCreateProjectOptions,
+ *,
+ content_type: str = "application/merge-patch+json",
+ **kwargs: Any
+ ) -> _models.ConversationalAnalysisAuthoringProjectMetadata:
+ """Creates a new project or updates an existing one.
+
+ :param project_name: The new project name. Required.
+ :type project_name: str
+ :param body: The request body. Required.
+ :type body:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringCreateProjectOptions
+ :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
+ Default value is "application/merge-patch+json".
+ :paramtype content_type: str
+ :return: ConversationalAnalysisAuthoringProjectMetadata. The
+ ConversationalAnalysisAuthoringProjectMetadata is compatible with MutableMapping
+ :rtype:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringProjectMetadata
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ async def create_project(
+ self, project_name: str, body: JSON, *, content_type: str = "application/merge-patch+json", **kwargs: Any
+ ) -> _models.ConversationalAnalysisAuthoringProjectMetadata:
+ """Creates a new project or updates an existing one.
+
+ :param project_name: The new project name. Required.
+ :type project_name: str
+ :param body: The request body. Required.
+ :type body: JSON
+ :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
+ Default value is "application/merge-patch+json".
+ :paramtype content_type: str
+ :return: ConversationalAnalysisAuthoringProjectMetadata. The
+ ConversationalAnalysisAuthoringProjectMetadata is compatible with MutableMapping
+ :rtype:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringProjectMetadata
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ async def create_project(
+ self, project_name: str, body: IO[bytes], *, content_type: str = "application/merge-patch+json", **kwargs: Any
+ ) -> _models.ConversationalAnalysisAuthoringProjectMetadata:
+ """Creates a new project or updates an existing one.
+
+ :param project_name: The new project name. Required.
+ :type project_name: str
+ :param body: The request body. Required.
+ :type body: IO[bytes]
+ :keyword content_type: Body Parameter content-type. Content type parameter for binary body.
+ Default value is "application/merge-patch+json".
+ :paramtype content_type: str
+ :return: ConversationalAnalysisAuthoringProjectMetadata. The
+ ConversationalAnalysisAuthoringProjectMetadata is compatible with MutableMapping
+ :rtype:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringProjectMetadata
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @distributed_trace_async
+ async def create_project(
+ self,
+ project_name: str,
+ body: Union[_models.ConversationalAnalysisAuthoringCreateProjectOptions, JSON, IO[bytes]],
+ **kwargs: Any
+ ) -> _models.ConversationalAnalysisAuthoringProjectMetadata:
+ """Creates a new project or updates an existing one.
+
+ :param project_name: The new project name. Required.
+ :type project_name: str
+ :param body: The request body. Is one of the following types:
+ ConversationalAnalysisAuthoringCreateProjectOptions, JSON, IO[bytes] Required.
+ :type body:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringCreateProjectOptions
+ or JSON or IO[bytes]
+ :return: ConversationalAnalysisAuthoringProjectMetadata. The
+ ConversationalAnalysisAuthoringProjectMetadata is compatible with MutableMapping
+ :rtype:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringProjectMetadata
+ :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 = 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.ConversationalAnalysisAuthoringProjectMetadata] = kwargs.pop("cls", None)
+
+ content_type = content_type or "application/merge-patch+json"
+ _content = None
+ if isinstance(body, (IOBase, bytes)):
+ _content = body
+ else:
+ _content = json.dumps(body, cls=SdkJSONEncoder, exclude_readonly=True) # type: ignore
+
+ _request = build_conversational_analysis_authoring_create_project_request(
+ project_name=project_name,
+ content_type=content_type,
+ api_version=self._config.api_version,
+ content=_content,
+ headers=_headers,
+ params=_params,
+ )
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _stream = kwargs.pop("stream", False)
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ _request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [200, 201]:
+ 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ if _stream:
+ deserialized = response.iter_bytes()
+ else:
+ deserialized = _deserialize(_models.ConversationalAnalysisAuthoringProjectMetadata, response.json())
+
+ if cls:
+ return cls(pipeline_response, deserialized, {}) # type: ignore
+
+ return deserialized # type: ignore
+
+ async def _delete_project_initial(self, project_name: str, **kwargs: Any) -> AsyncIterator[bytes]:
+ 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_conversational_analysis_authoring_delete_project_request(
+ project_name=project_name,
+ api_version=self._config.api_version,
+ headers=_headers,
+ params=_params,
+ )
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _stream = True
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ _request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [202]:
+ 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ response_headers = {}
+ response_headers["Operation-Location"] = self._deserialize("str", response.headers.get("Operation-Location"))
+
+ deserialized = response.iter_bytes()
+
+ if cls:
+ return cls(pipeline_response, deserialized, response_headers) # type: ignore
+
+ return deserialized # type: ignore
+
+ @distributed_trace_async
+ async def begin_delete_project(self, project_name: str, **kwargs: Any) -> AsyncLROPoller[None]:
+ """Deletes a project.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :return: An instance of AsyncLROPoller that returns None
+ :rtype: ~azure.core.polling.AsyncLROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = kwargs.pop("params", {}) or {}
+
+ cls: ClsType[None] = 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._delete_project_initial(
+ project_name=project_name, 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): # pylint: disable=inconsistent-return-statements
+ if cls:
+ return cls(pipeline_response, None, {}) # type: ignore
+
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+
+ 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[None].from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return AsyncLROPoller[None](self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ @overload
+ async def copy_project_authorization(
+ self, project_name: str, body: JSON, *, content_type: str = "application/json", **kwargs: Any
+ ) -> _models.ConversationalAnalysisAuthoringCopyProjectOptions:
+ """Generates a copy project operation authorization to the current target Azure
+ resource.
+
+ :param project_name: The new project name. Required.
+ :type project_name: str
+ :param body: 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: ConversationalAnalysisAuthoringCopyProjectOptions. The
+ ConversationalAnalysisAuthoringCopyProjectOptions is compatible with MutableMapping
+ :rtype:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringCopyProjectOptions
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ async def copy_project_authorization(
+ self,
+ project_name: str,
+ *,
+ project_kind: Union[str, _models.ProjectKind],
+ content_type: str = "application/json",
+ storage_input_container_name: Optional[str] = None,
+ allow_overwrite: Optional[bool] = None,
+ **kwargs: Any
+ ) -> _models.ConversationalAnalysisAuthoringCopyProjectOptions:
+ """Generates a copy project operation authorization to the current target Azure
+ resource.
+
+ :param project_name: The new project name. Required.
+ :type project_name: str
+ :keyword project_kind: Represents the project kind. Known values are: "Conversation",
+ "Orchestration", and "CustomConversationSummarization". Required.
+ :paramtype project_kind: str or
+ ~azure.ai.language.authoring.analyzeconversations.models.ProjectKind
+ :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword storage_input_container_name: The name of the storage container. Default value is
+ None.
+ :paramtype storage_input_container_name: str
+ :keyword allow_overwrite: Whether to allow an existing project to be overwritten using the
+ resulting copy authorization. Default value is None.
+ :paramtype allow_overwrite: bool
+ :return: ConversationalAnalysisAuthoringCopyProjectOptions. The
+ ConversationalAnalysisAuthoringCopyProjectOptions is compatible with MutableMapping
+ :rtype:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringCopyProjectOptions
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ async def copy_project_authorization(
+ self, project_name: str, body: IO[bytes], *, content_type: str = "application/json", **kwargs: Any
+ ) -> _models.ConversationalAnalysisAuthoringCopyProjectOptions:
+ """Generates a copy project operation authorization to the current target Azure
+ resource.
+
+ :param project_name: The new project name. Required.
+ :type project_name: str
+ :param body: 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: ConversationalAnalysisAuthoringCopyProjectOptions. The
+ ConversationalAnalysisAuthoringCopyProjectOptions is compatible with MutableMapping
+ :rtype:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringCopyProjectOptions
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @distributed_trace_async
+ @api_version_validation(
+ method_added_on="2023-04-15-preview",
+ params_added_on={"2023-04-15-preview": ["api_version", "project_name", "content_type", "accept"]},
+ )
+ async def copy_project_authorization(
+ self,
+ project_name: str,
+ body: Union[JSON, IO[bytes]] = _Unset,
+ *,
+ project_kind: Union[str, _models.ProjectKind] = _Unset,
+ storage_input_container_name: Optional[str] = None,
+ allow_overwrite: Optional[bool] = None,
+ **kwargs: Any
+ ) -> _models.ConversationalAnalysisAuthoringCopyProjectOptions:
+ """Generates a copy project operation authorization to the current target Azure
+ resource.
+
+ :param project_name: The new project name. Required.
+ :type project_name: str
+ :param body: Is either a JSON type or a IO[bytes] type. Required.
+ :type body: JSON or IO[bytes]
+ :keyword project_kind: Represents the project kind. Known values are: "Conversation",
+ "Orchestration", and "CustomConversationSummarization". Required.
+ :paramtype project_kind: str or
+ ~azure.ai.language.authoring.analyzeconversations.models.ProjectKind
+ :keyword storage_input_container_name: The name of the storage container. Default value is
+ None.
+ :paramtype storage_input_container_name: str
+ :keyword allow_overwrite: Whether to allow an existing project to be overwritten using the
+ resulting copy authorization. Default value is None.
+ :paramtype allow_overwrite: bool
+ :return: ConversationalAnalysisAuthoringCopyProjectOptions. The
+ ConversationalAnalysisAuthoringCopyProjectOptions is compatible with MutableMapping
+ :rtype:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringCopyProjectOptions
+ :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 = 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.ConversationalAnalysisAuthoringCopyProjectOptions] = kwargs.pop("cls", None)
+
+ if body is _Unset:
+ if project_kind is _Unset:
+ raise TypeError("missing required argument: project_kind")
+ body = {
+ "allowOverwrite": allow_overwrite,
+ "projectKind": project_kind,
+ "storageInputContainerName": storage_input_container_name,
+ }
+ body = {k: v for k, v in body.items() if v is not None}
+ content_type = content_type or "application/json"
+ _content = None
+ if isinstance(body, (IOBase, bytes)):
+ _content = body
+ else:
+ _content = json.dumps(body, cls=SdkJSONEncoder, exclude_readonly=True) # type: ignore
+
+ _request = build_conversational_analysis_authoring_copy_project_authorization_request(
+ project_name=project_name,
+ content_type=content_type,
+ api_version=self._config.api_version,
+ content=_content,
+ headers=_headers,
+ params=_params,
+ )
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _stream = kwargs.pop("stream", False)
+ pipeline_response: PipelineResponse = await 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:
+ 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ if _stream:
+ deserialized = response.iter_bytes()
+ else:
+ deserialized = _deserialize(_models.ConversationalAnalysisAuthoringCopyProjectOptions, response.json())
+
+ if cls:
+ return cls(pipeline_response, deserialized, {}) # type: ignore
+
+ return deserialized # type: ignore
+
+ @api_version_validation(
+ method_added_on="2023-04-15-preview",
+ params_added_on={"2023-04-15-preview": ["api_version", "project_name", "content_type", "accept"]},
+ )
+ async def _copy_project_initial(
+ self,
+ project_name: str,
+ body: Union[_models.ConversationalAnalysisAuthoringCopyProjectOptions, JSON, IO[bytes]],
+ **kwargs: Any
+ ) -> AsyncIterator[bytes]:
+ error_map: MutableMapping = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _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[AsyncIterator[bytes]] = kwargs.pop("cls", None)
+
+ content_type = content_type or "application/json"
+ _content = None
+ if isinstance(body, (IOBase, bytes)):
+ _content = body
+ else:
+ _content = json.dumps(body, cls=SdkJSONEncoder, exclude_readonly=True) # type: ignore
+
+ _request = build_conversational_analysis_authoring_copy_project_request(
+ project_name=project_name,
+ content_type=content_type,
+ api_version=self._config.api_version,
+ content=_content,
+ headers=_headers,
+ params=_params,
+ )
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _stream = True
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ _request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [202]:
+ 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ response_headers = {}
+ response_headers["Operation-Location"] = self._deserialize("str", response.headers.get("Operation-Location"))
+
+ deserialized = response.iter_bytes()
+
+ if cls:
+ return cls(pipeline_response, deserialized, response_headers) # type: ignore
+
+ return deserialized # type: ignore
+
+ @overload
+ async def begin_copy_project(
+ self,
+ project_name: str,
+ body: _models.ConversationalAnalysisAuthoringCopyProjectOptions,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> AsyncLROPoller[None]:
+ """Copies an existing project to another Azure resource.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param body: The copy project info. Required.
+ :type body:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringCopyProjectOptions
+ :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 AsyncLROPoller that returns None
+ :rtype: ~azure.core.polling.AsyncLROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ async def begin_copy_project(
+ self, project_name: str, body: JSON, *, content_type: str = "application/json", **kwargs: Any
+ ) -> AsyncLROPoller[None]:
+ """Copies an existing project to another Azure resource.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param body: The copy project info. 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: An instance of AsyncLROPoller that returns None
+ :rtype: ~azure.core.polling.AsyncLROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ async def begin_copy_project(
+ self, project_name: str, body: IO[bytes], *, content_type: str = "application/json", **kwargs: Any
+ ) -> AsyncLROPoller[None]:
+ """Copies an existing project to another Azure resource.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param body: The copy project info. 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: An instance of AsyncLROPoller that returns None
+ :rtype: ~azure.core.polling.AsyncLROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @distributed_trace_async
+ @api_version_validation(
+ method_added_on="2023-04-15-preview",
+ params_added_on={"2023-04-15-preview": ["api_version", "project_name", "content_type", "accept"]},
+ )
+ async def begin_copy_project(
+ self,
+ project_name: str,
+ body: Union[_models.ConversationalAnalysisAuthoringCopyProjectOptions, JSON, IO[bytes]],
+ **kwargs: Any
+ ) -> AsyncLROPoller[None]:
+ """Copies an existing project to another Azure resource.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param body: The copy project info. Is one of the following types:
+ ConversationalAnalysisAuthoringCopyProjectOptions, JSON, IO[bytes] Required.
+ :type body:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringCopyProjectOptions
+ or JSON or IO[bytes]
+ :return: An instance of AsyncLROPoller that returns None
+ :rtype: ~azure.core.polling.AsyncLROPoller[None]
+ :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[None] = 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_project_initial(
+ project_name=project_name,
+ 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)
+
+ def get_long_running_output(pipeline_response): # pylint: disable=inconsistent-return-statements
+ if cls:
+ return cls(pipeline_response, None, {}) # type: ignore
+
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+
+ 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[None].from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return AsyncLROPoller[None](self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ async def _export_initial(
+ self,
+ project_name: str,
+ *,
+ string_index_type: Union[str, _models.StringIndexType],
+ exported_project_format: Optional[Union[str, _models.ExportedProjectFormat]] = None,
+ asset_kind: Optional[str] = None,
+ trained_model_label: Optional[str] = None,
+ **kwargs: Any
+ ) -> AsyncIterator[bytes]:
+ 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_conversational_analysis_authoring_export_request(
+ project_name=project_name,
+ string_index_type=string_index_type,
+ exported_project_format=exported_project_format,
+ asset_kind=asset_kind,
+ trained_model_label=trained_model_label,
+ api_version=self._config.api_version,
+ headers=_headers,
+ params=_params,
+ )
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _stream = True
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ _request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [202]:
+ 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ response_headers = {}
+ response_headers["Operation-Location"] = self._deserialize("str", response.headers.get("Operation-Location"))
+
+ deserialized = response.iter_bytes()
+
+ if cls:
+ return cls(pipeline_response, deserialized, response_headers) # type: ignore
+
+ return deserialized # type: ignore
+
+ @distributed_trace_async
+ async def begin_export(
+ self,
+ project_name: str,
+ *,
+ string_index_type: Union[str, _models.StringIndexType],
+ exported_project_format: Optional[Union[str, _models.ExportedProjectFormat]] = None,
+ asset_kind: Optional[str] = None,
+ trained_model_label: Optional[str] = None,
+ **kwargs: Any
+ ) -> AsyncLROPoller[None]:
+ """Triggers a job to export a project's data.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :keyword string_index_type: Specifies the method used to interpret string offsets. For
+ additional
+ information see https://aka.ms/text-analytics-offsets. "Utf16CodeUnit" Required.
+ :paramtype string_index_type: str or
+ ~azure.ai.language.authoring.analyzeconversations.models.StringIndexType
+ :keyword exported_project_format: The format of the exported project file to use. Known values
+ are: "Conversation" and "Luis". Default value is None.
+ :paramtype exported_project_format: str or
+ ~azure.ai.language.authoring.analyzeconversations.models.ExportedProjectFormat
+ :keyword asset_kind: Kind of asset to export. Default value is None.
+ :paramtype asset_kind: str
+ :keyword trained_model_label: Trained model label to export. If the trainedModelLabel is null,
+ the default behavior is to export the current working copy. Default value is None.
+ :paramtype trained_model_label: str
+ :return: An instance of AsyncLROPoller that returns None
+ :rtype: ~azure.core.polling.AsyncLROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = kwargs.pop("params", {}) or {}
+
+ cls: ClsType[None] = 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._export_initial(
+ project_name=project_name,
+ string_index_type=string_index_type,
+ exported_project_format=exported_project_format,
+ asset_kind=asset_kind,
+ trained_model_label=trained_model_label,
+ 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): # pylint: disable=inconsistent-return-statements
+ if cls:
+ return cls(pipeline_response, None, {}) # type: ignore
+
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+
+ 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[None].from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return AsyncLROPoller[None](self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ async def _import_method_initial(
+ self,
+ project_name: str,
+ body: Union[_models.ConversationalAnalysisAuthoringExportedProject, JSON, IO[bytes]],
+ *,
+ exported_project_format: Optional[Union[str, _models.ExportedProjectFormat]] = None,
+ **kwargs: Any
+ ) -> AsyncIterator[bytes]:
+ error_map: MutableMapping = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _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[AsyncIterator[bytes]] = kwargs.pop("cls", None)
+
+ content_type = content_type or "application/json"
+ _content = None
+ if isinstance(body, (IOBase, bytes)):
+ _content = body
+ else:
+ _content = json.dumps(body, cls=SdkJSONEncoder, exclude_readonly=True) # type: ignore
+
+ _request = build_conversational_analysis_authoring_import_method_request(
+ project_name=project_name,
+ exported_project_format=exported_project_format,
+ content_type=content_type,
+ api_version=self._config.api_version,
+ content=_content,
+ headers=_headers,
+ params=_params,
+ )
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _stream = True
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ _request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [202]:
+ 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ response_headers = {}
+ response_headers["Operation-Location"] = self._deserialize("str", response.headers.get("Operation-Location"))
+
+ deserialized = response.iter_bytes()
+
+ if cls:
+ return cls(pipeline_response, deserialized, response_headers) # type: ignore
+
+ return deserialized # type: ignore
+
+ @overload
+ async def begin_import_method(
+ self,
+ project_name: str,
+ body: _models.ConversationalAnalysisAuthoringExportedProject,
+ *,
+ exported_project_format: Optional[Union[str, _models.ExportedProjectFormat]] = None,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> AsyncLROPoller[None]:
+ """Triggers a job to import a project. If a project with the same name already
+ exists, the data of that project is replaced.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param body: The project data to import. Required.
+ :type body:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringExportedProject
+ :keyword exported_project_format: The format of the exported project file to use. Known values
+ are: "Conversation" and "Luis". Default value is None.
+ :paramtype exported_project_format: str or
+ ~azure.ai.language.authoring.analyzeconversations.models.ExportedProjectFormat
+ :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 AsyncLROPoller that returns None
+ :rtype: ~azure.core.polling.AsyncLROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ async def begin_import_method(
+ self,
+ project_name: str,
+ body: JSON,
+ *,
+ exported_project_format: Optional[Union[str, _models.ExportedProjectFormat]] = None,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> AsyncLROPoller[None]:
+ """Triggers a job to import a project. If a project with the same name already
+ exists, the data of that project is replaced.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param body: The project data to import. Required.
+ :type body: JSON
+ :keyword exported_project_format: The format of the exported project file to use. Known values
+ are: "Conversation" and "Luis". Default value is None.
+ :paramtype exported_project_format: str or
+ ~azure.ai.language.authoring.analyzeconversations.models.ExportedProjectFormat
+ :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 AsyncLROPoller that returns None
+ :rtype: ~azure.core.polling.AsyncLROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ async def begin_import_method(
+ self,
+ project_name: str,
+ body: IO[bytes],
+ *,
+ exported_project_format: Optional[Union[str, _models.ExportedProjectFormat]] = None,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> AsyncLROPoller[None]:
+ """Triggers a job to import a project. If a project with the same name already
+ exists, the data of that project is replaced.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param body: The project data to import. Required.
+ :type body: IO[bytes]
+ :keyword exported_project_format: The format of the exported project file to use. Known values
+ are: "Conversation" and "Luis". Default value is None.
+ :paramtype exported_project_format: str or
+ ~azure.ai.language.authoring.analyzeconversations.models.ExportedProjectFormat
+ :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 AsyncLROPoller that returns None
+ :rtype: ~azure.core.polling.AsyncLROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @distributed_trace_async
+ async def begin_import_method(
+ self,
+ project_name: str,
+ body: Union[_models.ConversationalAnalysisAuthoringExportedProject, JSON, IO[bytes]],
+ *,
+ exported_project_format: Optional[Union[str, _models.ExportedProjectFormat]] = None,
+ **kwargs: Any
+ ) -> AsyncLROPoller[None]:
+ """Triggers a job to import a project. If a project with the same name already
+ exists, the data of that project is replaced.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param body: The project data to import. Is one of the following types:
+ ConversationalAnalysisAuthoringExportedProject, JSON, IO[bytes] Required.
+ :type body:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringExportedProject
+ or JSON or IO[bytes]
+ :keyword exported_project_format: The format of the exported project file to use. Known values
+ are: "Conversation" and "Luis". Default value is None.
+ :paramtype exported_project_format: str or
+ ~azure.ai.language.authoring.analyzeconversations.models.ExportedProjectFormat
+ :return: An instance of AsyncLROPoller that returns None
+ :rtype: ~azure.core.polling.AsyncLROPoller[None]
+ :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[None] = 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._import_method_initial(
+ project_name=project_name,
+ body=body,
+ exported_project_format=exported_project_format,
+ 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): # pylint: disable=inconsistent-return-statements
+ if cls:
+ return cls(pipeline_response, None, {}) # type: ignore
+
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+
+ 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[None].from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return AsyncLROPoller[None](self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ async def _train_initial(
+ self,
+ project_name: str,
+ body: Union[_models.ConversationalAnalysisAuthoringTrainingJobOptions, JSON, IO[bytes]],
+ **kwargs: Any
+ ) -> AsyncIterator[bytes]:
+ error_map: MutableMapping = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _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[AsyncIterator[bytes]] = kwargs.pop("cls", None)
+
+ content_type = content_type or "application/json"
+ _content = None
+ if isinstance(body, (IOBase, bytes)):
+ _content = body
+ else:
+ _content = json.dumps(body, cls=SdkJSONEncoder, exclude_readonly=True) # type: ignore
+
+ _request = build_conversational_analysis_authoring_train_request(
+ project_name=project_name,
+ content_type=content_type,
+ api_version=self._config.api_version,
+ content=_content,
+ headers=_headers,
+ params=_params,
+ )
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _stream = True
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ _request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [202]:
+ 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ response_headers = {}
+ response_headers["Operation-Location"] = self._deserialize("str", response.headers.get("Operation-Location"))
+
+ deserialized = response.iter_bytes()
+
+ if cls:
+ return cls(pipeline_response, deserialized, response_headers) # type: ignore
+
+ return deserialized # type: ignore
+
+ @overload
+ async def begin_train(
+ self,
+ project_name: str,
+ body: _models.ConversationalAnalysisAuthoringTrainingJobOptions,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> AsyncLROPoller[_models.ConversationalAnalysisAuthoringTrainingJobResult]:
+ # pylint: disable=line-too-long
+ """Triggers a training job for a project.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param body: The training input parameters. Required.
+ :type body:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringTrainingJobOptions
+ :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 AsyncLROPoller that returns
+ ConversationalAnalysisAuthoringTrainingJobResult. The
+ ConversationalAnalysisAuthoringTrainingJobResult is compatible with MutableMapping
+ :rtype:
+ ~azure.core.polling.AsyncLROPoller[~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringTrainingJobResult]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ async def begin_train(
+ self, project_name: str, body: JSON, *, content_type: str = "application/json", **kwargs: Any
+ ) -> AsyncLROPoller[_models.ConversationalAnalysisAuthoringTrainingJobResult]:
+ # pylint: disable=line-too-long
+ """Triggers a training job for a project.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param body: The training input 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: An instance of AsyncLROPoller that returns
+ ConversationalAnalysisAuthoringTrainingJobResult. The
+ ConversationalAnalysisAuthoringTrainingJobResult is compatible with MutableMapping
+ :rtype:
+ ~azure.core.polling.AsyncLROPoller[~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringTrainingJobResult]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ async def begin_train(
+ self, project_name: str, body: IO[bytes], *, content_type: str = "application/json", **kwargs: Any
+ ) -> AsyncLROPoller[_models.ConversationalAnalysisAuthoringTrainingJobResult]:
+ # pylint: disable=line-too-long
+ """Triggers a training job for a project.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param body: The training input 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: An instance of AsyncLROPoller that returns
+ ConversationalAnalysisAuthoringTrainingJobResult. The
+ ConversationalAnalysisAuthoringTrainingJobResult is compatible with MutableMapping
+ :rtype:
+ ~azure.core.polling.AsyncLROPoller[~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringTrainingJobResult]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @distributed_trace_async
+ async def begin_train(
+ self,
+ project_name: str,
+ body: Union[_models.ConversationalAnalysisAuthoringTrainingJobOptions, JSON, IO[bytes]],
+ **kwargs: Any
+ ) -> AsyncLROPoller[_models.ConversationalAnalysisAuthoringTrainingJobResult]:
+ # pylint: disable=line-too-long
+ """Triggers a training job for a project.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param body: The training input parameters. Is one of the following types:
+ ConversationalAnalysisAuthoringTrainingJobOptions, JSON, IO[bytes] Required.
+ :type body:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringTrainingJobOptions
+ or JSON or IO[bytes]
+ :return: An instance of AsyncLROPoller that returns
+ ConversationalAnalysisAuthoringTrainingJobResult. The
+ ConversationalAnalysisAuthoringTrainingJobResult is compatible with MutableMapping
+ :rtype:
+ ~azure.core.polling.AsyncLROPoller[~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringTrainingJobResult]
+ :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.ConversationalAnalysisAuthoringTrainingJobResult] = 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._train_initial(
+ project_name=project_name,
+ 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)
+
+ def get_long_running_output(pipeline_response):
+ response_headers = {}
+ response = pipeline_response.http_response
+ response_headers["Operation-Location"] = self._deserialize(
+ "str", response.headers.get("Operation-Location")
+ )
+
+ deserialized = _deserialize(
+ _models.ConversationalAnalysisAuthoringTrainingJobResult, response.json().get("result")
+ )
+ 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"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+
+ 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.ConversationalAnalysisAuthoringTrainingJobResult].from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return AsyncLROPoller[_models.ConversationalAnalysisAuthoringTrainingJobResult](
+ self._client, raw_result, get_long_running_output, polling_method # type: ignore
+ )
+
+ @distributed_trace_async
+ @api_version_validation(
+ method_added_on="2023-04-15-preview",
+ params_added_on={"2023-04-15-preview": ["api_version", "project_name", "job_id", "accept"]},
+ )
+ async def get_copy_project_status(
+ self, project_name: str, job_id: str, **kwargs: Any
+ ) -> _models.GetCopyProjectStatusResponse:
+ """Gets the status of an existing copy project job.
+
+ :param project_name: The new project name. Required.
+ :type project_name: str
+ :param job_id: The job ID. Required.
+ :type job_id: str
+ :return: GetCopyProjectStatusResponse. The GetCopyProjectStatusResponse is compatible with
+ MutableMapping
+ :rtype: ~azure.ai.language.authoring.analyzeconversations.models.GetCopyProjectStatusResponse
+ :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[_models.GetCopyProjectStatusResponse] = kwargs.pop("cls", None)
+
+ _request = build_conversational_analysis_authoring_get_copy_project_status_request(
+ project_name=project_name,
+ job_id=job_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"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _stream = kwargs.pop("stream", False)
+ pipeline_response: PipelineResponse = await 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:
+ 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ if _stream:
+ deserialized = response.iter_bytes()
+ else:
+ deserialized = _deserialize(_models.GetCopyProjectStatusResponse, response.json())
+
+ if cls:
+ return cls(pipeline_response, deserialized, {}) # type: ignore
+
+ return deserialized # type: ignore
+
+ @distributed_trace
+ def list_deployments(
+ self, project_name: str, *, top: Optional[int] = None, skip: Optional[int] = None, **kwargs: Any
+ ) -> AsyncIterable["_models.ConversationalAnalysisAuthoringProjectDeployment"]:
+ # pylint: disable=line-too-long
+ """Lists the deployments belonging to a project.
+
+ :param project_name: The new project name. Required.
+ :type project_name: str
+ :keyword top: The number of result items to return. Default value is None.
+ :paramtype top: int
+ :keyword skip: The number of result items to skip. Default value is None.
+ :paramtype skip: int
+ :return: An iterator like instance of ConversationalAnalysisAuthoringProjectDeployment
+ :rtype:
+ ~azure.core.async_paging.AsyncItemPaged[~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringProjectDeployment]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = kwargs.pop("params", {}) or {}
+
+ maxpagesize = kwargs.pop("maxpagesize", None)
+ cls: ClsType[List[_models.ConversationalAnalysisAuthoringProjectDeployment]] = 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_conversational_analysis_authoring_list_deployments_request(
+ project_name=project_name,
+ top=top,
+ skip=skip,
+ maxpagesize=maxpagesize,
+ api_version=self._config.api_version,
+ headers=_headers,
+ params=_params,
+ )
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _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"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _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.ConversationalAnalysisAuthoringProjectDeployment], 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( # 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ return pipeline_response
+
+ return AsyncItemPaged(get_next, extract_data)
+
+ async def _swap_deployments_initial(
+ self,
+ project_name: str,
+ body: Union[_models.ConversationalAnalysisAuthoringSwapDeploymentsOptions, JSON, IO[bytes]],
+ **kwargs: Any
+ ) -> AsyncIterator[bytes]:
+ error_map: MutableMapping = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _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[AsyncIterator[bytes]] = kwargs.pop("cls", None)
+
+ content_type = content_type or "application/json"
+ _content = None
+ if isinstance(body, (IOBase, bytes)):
+ _content = body
+ else:
+ _content = json.dumps(body, cls=SdkJSONEncoder, exclude_readonly=True) # type: ignore
+
+ _request = build_conversational_analysis_authoring_swap_deployments_request(
+ project_name=project_name,
+ content_type=content_type,
+ api_version=self._config.api_version,
+ content=_content,
+ headers=_headers,
+ params=_params,
+ )
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _stream = True
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ _request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [202]:
+ 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ response_headers = {}
+ response_headers["Operation-Location"] = self._deserialize("str", response.headers.get("Operation-Location"))
+
+ deserialized = response.iter_bytes()
+
+ if cls:
+ return cls(pipeline_response, deserialized, response_headers) # type: ignore
+
+ return deserialized # type: ignore
+
+ @overload
+ async def begin_swap_deployments(
+ self,
+ project_name: str,
+ body: _models.ConversationalAnalysisAuthoringSwapDeploymentsOptions,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> AsyncLROPoller[None]:
+ """Swaps two existing deployments with each other.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param body: The job object to swap two deployments. Required.
+ :type body:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringSwapDeploymentsOptions
+ :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 AsyncLROPoller that returns None
+ :rtype: ~azure.core.polling.AsyncLROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ async def begin_swap_deployments(
+ self, project_name: str, body: JSON, *, content_type: str = "application/json", **kwargs: Any
+ ) -> AsyncLROPoller[None]:
+ """Swaps two existing deployments with each other.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param body: The job object to swap two deployments. 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: An instance of AsyncLROPoller that returns None
+ :rtype: ~azure.core.polling.AsyncLROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ async def begin_swap_deployments(
+ self, project_name: str, body: IO[bytes], *, content_type: str = "application/json", **kwargs: Any
+ ) -> AsyncLROPoller[None]:
+ """Swaps two existing deployments with each other.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param body: The job object to swap two deployments. 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: An instance of AsyncLROPoller that returns None
+ :rtype: ~azure.core.polling.AsyncLROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @distributed_trace_async
+ async def begin_swap_deployments(
+ self,
+ project_name: str,
+ body: Union[_models.ConversationalAnalysisAuthoringSwapDeploymentsOptions, JSON, IO[bytes]],
+ **kwargs: Any
+ ) -> AsyncLROPoller[None]:
+ """Swaps two existing deployments with each other.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param body: The job object to swap two deployments. Is one of the following types:
+ ConversationalAnalysisAuthoringSwapDeploymentsOptions, JSON, IO[bytes] Required.
+ :type body:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringSwapDeploymentsOptions
+ or JSON or IO[bytes]
+ :return: An instance of AsyncLROPoller that returns None
+ :rtype: ~azure.core.polling.AsyncLROPoller[None]
+ :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[None] = 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._swap_deployments_initial(
+ project_name=project_name,
+ 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)
+
+ def get_long_running_output(pipeline_response): # pylint: disable=inconsistent-return-statements
+ if cls:
+ return cls(pipeline_response, None, {}) # type: ignore
+
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+
+ 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[None].from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return AsyncLROPoller[None](self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ @distributed_trace_async
+ async def get_deployment(
+ self, project_name: str, deployment_name: str, **kwargs: Any
+ ) -> _models.GetDeploymentResponse:
+ """Gets the details of a deployment.
+
+ :param project_name: The new project name. Required.
+ :type project_name: str
+ :param deployment_name: Represents deployment name. Required.
+ :type deployment_name: str
+ :return: GetDeploymentResponse. The GetDeploymentResponse is compatible with MutableMapping
+ :rtype: ~azure.ai.language.authoring.analyzeconversations.models.GetDeploymentResponse
+ :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[_models.GetDeploymentResponse] = kwargs.pop("cls", None)
+
+ _request = build_conversational_analysis_authoring_get_deployment_request(
+ project_name=project_name,
+ deployment_name=deployment_name,
+ api_version=self._config.api_version,
+ headers=_headers,
+ params=_params,
+ )
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _stream = kwargs.pop("stream", False)
+ pipeline_response: PipelineResponse = await 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:
+ 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ if _stream:
+ deserialized = response.iter_bytes()
+ else:
+ deserialized = _deserialize(_models.GetDeploymentResponse, response.json())
+
+ if cls:
+ return cls(pipeline_response, deserialized, {}) # type: ignore
+
+ return deserialized # type: ignore
+
+ async def _deploy_project_initial(
+ self,
+ project_name: str,
+ deployment_name: str,
+ body: Union[_models.ConversationalAnalysisAuthoringCreateDeploymentOptions, JSON, IO[bytes]],
+ **kwargs: Any
+ ) -> AsyncIterator[bytes]:
+ error_map: MutableMapping = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _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[AsyncIterator[bytes]] = kwargs.pop("cls", None)
+
+ content_type = content_type or "application/json"
+ _content = None
+ if isinstance(body, (IOBase, bytes)):
+ _content = body
+ else:
+ _content = json.dumps(body, cls=SdkJSONEncoder, exclude_readonly=True) # type: ignore
+
+ _request = build_conversational_analysis_authoring_deploy_project_request(
+ project_name=project_name,
+ deployment_name=deployment_name,
+ content_type=content_type,
+ api_version=self._config.api_version,
+ content=_content,
+ headers=_headers,
+ params=_params,
+ )
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _stream = True
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ _request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [202]:
+ 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ response_headers = {}
+ response_headers["Operation-Location"] = self._deserialize("str", response.headers.get("Operation-Location"))
+
+ deserialized = response.iter_bytes()
+
+ if cls:
+ return cls(pipeline_response, deserialized, response_headers) # type: ignore
+
+ return deserialized # type: ignore
+
+ @overload
+ async def begin_deploy_project(
+ self,
+ project_name: str,
+ deployment_name: str,
+ body: _models.ConversationalAnalysisAuthoringCreateDeploymentOptions,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> AsyncLROPoller[None]:
+ """Creates a new deployment or replaces an existing one.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param deployment_name: The name of the specific deployment of the project to use. Required.
+ :type deployment_name: str
+ :param body: The new deployment info. Required.
+ :type body:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringCreateDeploymentOptions
+ :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 AsyncLROPoller that returns None
+ :rtype: ~azure.core.polling.AsyncLROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ async def begin_deploy_project(
+ self,
+ project_name: str,
+ deployment_name: str,
+ body: JSON,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> AsyncLROPoller[None]:
+ """Creates a new deployment or replaces an existing one.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param deployment_name: The name of the specific deployment of the project to use. Required.
+ :type deployment_name: str
+ :param body: The new deployment info. 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: An instance of AsyncLROPoller that returns None
+ :rtype: ~azure.core.polling.AsyncLROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ async def begin_deploy_project(
+ self,
+ project_name: str,
+ deployment_name: str,
+ body: IO[bytes],
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> AsyncLROPoller[None]:
+ """Creates a new deployment or replaces an existing one.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param deployment_name: The name of the specific deployment of the project to use. Required.
+ :type deployment_name: str
+ :param body: The new deployment info. 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: An instance of AsyncLROPoller that returns None
+ :rtype: ~azure.core.polling.AsyncLROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @distributed_trace_async
+ async def begin_deploy_project(
+ self,
+ project_name: str,
+ deployment_name: str,
+ body: Union[_models.ConversationalAnalysisAuthoringCreateDeploymentOptions, JSON, IO[bytes]],
+ **kwargs: Any
+ ) -> AsyncLROPoller[None]:
+ """Creates a new deployment or replaces an existing one.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param deployment_name: The name of the specific deployment of the project to use. Required.
+ :type deployment_name: str
+ :param body: The new deployment info. Is one of the following types:
+ ConversationalAnalysisAuthoringCreateDeploymentOptions, JSON, IO[bytes] Required.
+ :type body:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringCreateDeploymentOptions
+ or JSON or IO[bytes]
+ :return: An instance of AsyncLROPoller that returns None
+ :rtype: ~azure.core.polling.AsyncLROPoller[None]
+ :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[None] = 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._deploy_project_initial(
+ project_name=project_name,
+ deployment_name=deployment_name,
+ 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)
+
+ def get_long_running_output(pipeline_response): # pylint: disable=inconsistent-return-statements
+ if cls:
+ return cls(pipeline_response, None, {}) # type: ignore
+
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+
+ 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[None].from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return AsyncLROPoller[None](self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ async def _delete_deployment_initial(
+ self, project_name: str, deployment_name: str, **kwargs: Any
+ ) -> AsyncIterator[bytes]:
+ 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_conversational_analysis_authoring_delete_deployment_request(
+ project_name=project_name,
+ deployment_name=deployment_name,
+ api_version=self._config.api_version,
+ headers=_headers,
+ params=_params,
+ )
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _stream = True
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ _request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [202]:
+ 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ response_headers = {}
+ response_headers["Operation-Location"] = self._deserialize("str", response.headers.get("Operation-Location"))
+
+ deserialized = response.iter_bytes()
+
+ if cls:
+ return cls(pipeline_response, deserialized, response_headers) # type: ignore
+
+ return deserialized # type: ignore
+
+ @distributed_trace_async
+ async def begin_delete_deployment(
+ self, project_name: str, deployment_name: str, **kwargs: Any
+ ) -> AsyncLROPoller[None]:
+ """Deletes a project deployment.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param deployment_name: The name of the specific deployment of the project to use. Required.
+ :type deployment_name: str
+ :return: An instance of AsyncLROPoller that returns None
+ :rtype: ~azure.core.polling.AsyncLROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = kwargs.pop("params", {}) or {}
+
+ cls: ClsType[None] = 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._delete_deployment_initial(
+ project_name=project_name,
+ deployment_name=deployment_name,
+ 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): # pylint: disable=inconsistent-return-statements
+ if cls:
+ return cls(pipeline_response, None, {}) # type: ignore
+
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+
+ 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[None].from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return AsyncLROPoller[None](self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ @api_version_validation(
+ method_added_on="2023-04-15-preview",
+ params_added_on={
+ "2023-04-15-preview": ["api_version", "project_name", "deployment_name", "content_type", "accept"]
+ },
+ ) # pylint: disable=name-too-long
+ async def _delete_deployment_from_resources_initial( # pylint: disable=name-too-long
+ self,
+ project_name: str,
+ deployment_name: str,
+ body: Union[_models.ConversationalAnalysisAuthoringDeleteDeploymentOptions, JSON, IO[bytes]],
+ **kwargs: Any
+ ) -> AsyncIterator[bytes]:
+ error_map: MutableMapping = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _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[AsyncIterator[bytes]] = kwargs.pop("cls", None)
+
+ content_type = content_type or "application/json"
+ _content = None
+ if isinstance(body, (IOBase, bytes)):
+ _content = body
+ else:
+ _content = json.dumps(body, cls=SdkJSONEncoder, exclude_readonly=True) # type: ignore
+
+ _request = build_conversational_analysis_authoring_delete_deployment_from_resources_request(
+ project_name=project_name,
+ deployment_name=deployment_name,
+ content_type=content_type,
+ api_version=self._config.api_version,
+ content=_content,
+ headers=_headers,
+ params=_params,
+ )
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _stream = True
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ _request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [202]:
+ 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ response_headers = {}
+ response_headers["Operation-Location"] = self._deserialize("str", response.headers.get("Operation-Location"))
+
+ deserialized = response.iter_bytes()
+
+ if cls:
+ return cls(pipeline_response, deserialized, response_headers) # type: ignore
+
+ return deserialized # type: ignore
+
+ @overload
+ async def begin_delete_deployment_from_resources(
+ self,
+ project_name: str,
+ deployment_name: str,
+ body: _models.ConversationalAnalysisAuthoringDeleteDeploymentOptions,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> AsyncLROPoller[None]:
+ """Deletes a project deployment from the specified assigned resources.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param deployment_name: The name of the specific deployment of the project to use. Required.
+ :type deployment_name: str
+ :param body: The options for deleting the deployment. Required.
+ :type body:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringDeleteDeploymentOptions
+ :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 AsyncLROPoller that returns None
+ :rtype: ~azure.core.polling.AsyncLROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ async def begin_delete_deployment_from_resources(
+ self,
+ project_name: str,
+ deployment_name: str,
+ body: JSON,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> AsyncLROPoller[None]:
+ """Deletes a project deployment from the specified assigned resources.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param deployment_name: The name of the specific deployment of the project to use. Required.
+ :type deployment_name: str
+ :param body: The options for deleting the deployment. 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: An instance of AsyncLROPoller that returns None
+ :rtype: ~azure.core.polling.AsyncLROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ async def begin_delete_deployment_from_resources(
+ self,
+ project_name: str,
+ deployment_name: str,
+ body: IO[bytes],
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> AsyncLROPoller[None]:
+ """Deletes a project deployment from the specified assigned resources.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param deployment_name: The name of the specific deployment of the project to use. Required.
+ :type deployment_name: str
+ :param body: The options for deleting the deployment. 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: An instance of AsyncLROPoller that returns None
+ :rtype: ~azure.core.polling.AsyncLROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @distributed_trace_async
+ @api_version_validation(
+ method_added_on="2023-04-15-preview",
+ params_added_on={
+ "2023-04-15-preview": ["api_version", "project_name", "deployment_name", "content_type", "accept"]
+ },
+ )
+ async def begin_delete_deployment_from_resources(
+ self,
+ project_name: str,
+ deployment_name: str,
+ body: Union[_models.ConversationalAnalysisAuthoringDeleteDeploymentOptions, JSON, IO[bytes]],
+ **kwargs: Any
+ ) -> AsyncLROPoller[None]:
+ """Deletes a project deployment from the specified assigned resources.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param deployment_name: The name of the specific deployment of the project to use. Required.
+ :type deployment_name: str
+ :param body: The options for deleting the deployment. Is one of the following types:
+ ConversationalAnalysisAuthoringDeleteDeploymentOptions, JSON, IO[bytes] Required.
+ :type body:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringDeleteDeploymentOptions
+ or JSON or IO[bytes]
+ :return: An instance of AsyncLROPoller that returns None
+ :rtype: ~azure.core.polling.AsyncLROPoller[None]
+ :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[None] = 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._delete_deployment_from_resources_initial(
+ project_name=project_name,
+ deployment_name=deployment_name,
+ 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)
+
+ def get_long_running_output(pipeline_response): # pylint: disable=inconsistent-return-statements
+ if cls:
+ return cls(pipeline_response, None, {}) # type: ignore
+
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+
+ 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[None].from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return AsyncLROPoller[None](self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ @distributed_trace_async
+ @api_version_validation(
+ method_added_on="2023-04-15-preview",
+ params_added_on={"2023-04-15-preview": ["api_version", "project_name", "deployment_name", "job_id", "accept"]},
+ ) # pylint: disable=name-too-long
+ async def get_deployment_delete_from_resources_status( # pylint: disable=name-too-long
+ self, project_name: str, deployment_name: str, job_id: str, **kwargs: Any
+ ) -> _models.GetDeploymentDeleteFromResourcesStatusResponse:
+ """Gets the status of an existing delete deployment from specific resources job.
+
+ :param project_name: The new project name. Required.
+ :type project_name: str
+ :param deployment_name: Represents deployment name. Required.
+ :type deployment_name: str
+ :param job_id: The job ID. Required.
+ :type job_id: str
+ :return: GetDeploymentDeleteFromResourcesStatusResponse. The
+ GetDeploymentDeleteFromResourcesStatusResponse is compatible with MutableMapping
+ :rtype:
+ ~azure.ai.language.authoring.analyzeconversations.models.GetDeploymentDeleteFromResourcesStatusResponse
+ :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[_models.GetDeploymentDeleteFromResourcesStatusResponse] = kwargs.pop("cls", None)
+
+ _request = build_conversational_analysis_authoring_get_deployment_delete_from_resources_status_request(
+ project_name=project_name,
+ deployment_name=deployment_name,
+ job_id=job_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"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _stream = kwargs.pop("stream", False)
+ pipeline_response: PipelineResponse = await 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:
+ 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ if _stream:
+ deserialized = response.iter_bytes()
+ else:
+ deserialized = _deserialize(_models.GetDeploymentDeleteFromResourcesStatusResponse, response.json())
+
+ if cls:
+ return cls(pipeline_response, deserialized, {}) # type: ignore
+
+ return deserialized # type: ignore
+
+ @distributed_trace_async
+ async def get_deployment_status(
+ self, project_name: str, deployment_name: str, job_id: str, **kwargs: Any
+ ) -> _models.GetDeploymentStatusResponse:
+ """Gets the status of an existing deployment job.
+
+ :param project_name: The new project name. Required.
+ :type project_name: str
+ :param deployment_name: Represents deployment name. Required.
+ :type deployment_name: str
+ :param job_id: The job ID. Required.
+ :type job_id: str
+ :return: GetDeploymentStatusResponse. The GetDeploymentStatusResponse is compatible with
+ MutableMapping
+ :rtype: ~azure.ai.language.authoring.analyzeconversations.models.GetDeploymentStatusResponse
+ :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[_models.GetDeploymentStatusResponse] = kwargs.pop("cls", None)
+
+ _request = build_conversational_analysis_authoring_get_deployment_status_request(
+ project_name=project_name,
+ deployment_name=deployment_name,
+ job_id=job_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"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _stream = kwargs.pop("stream", False)
+ pipeline_response: PipelineResponse = await 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:
+ 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ if _stream:
+ deserialized = response.iter_bytes()
+ else:
+ deserialized = _deserialize(_models.GetDeploymentStatusResponse, response.json())
+
+ if cls:
+ return cls(pipeline_response, deserialized, {}) # type: ignore
+
+ return deserialized # type: ignore
+
+ @distributed_trace_async
+ async def get_swap_deployments_status(
+ self, project_name: str, job_id: str, **kwargs: Any
+ ) -> _models.GetSwapDeploymentsStatusResponse:
+ """Gets the status of an existing swap deployment job.
+
+ :param project_name: The new project name. Required.
+ :type project_name: str
+ :param job_id: The job ID. Required.
+ :type job_id: str
+ :return: GetSwapDeploymentsStatusResponse. The GetSwapDeploymentsStatusResponse is compatible
+ with MutableMapping
+ :rtype:
+ ~azure.ai.language.authoring.analyzeconversations.models.GetSwapDeploymentsStatusResponse
+ :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[_models.GetSwapDeploymentsStatusResponse] = kwargs.pop("cls", None)
+
+ _request = build_conversational_analysis_authoring_get_swap_deployments_status_request(
+ project_name=project_name,
+ job_id=job_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"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _stream = kwargs.pop("stream", False)
+ pipeline_response: PipelineResponse = await 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:
+ 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ if _stream:
+ deserialized = response.iter_bytes()
+ else:
+ deserialized = _deserialize(_models.GetSwapDeploymentsStatusResponse, response.json())
+
+ if cls:
+ return cls(pipeline_response, deserialized, {}) # type: ignore
+
+ return deserialized # type: ignore
+
+ @distributed_trace_async
+ async def get_export_status(self, project_name: str, job_id: str, **kwargs: Any) -> _models.GetExportStatusResponse:
+ """Gets the status of an export job. Once job completes, returns the project
+ metadata, and assets.
+
+ :param project_name: The new project name. Required.
+ :type project_name: str
+ :param job_id: The job ID. Required.
+ :type job_id: str
+ :return: GetExportStatusResponse. The GetExportStatusResponse is compatible with MutableMapping
+ :rtype: ~azure.ai.language.authoring.analyzeconversations.models.GetExportStatusResponse
+ :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[_models.GetExportStatusResponse] = kwargs.pop("cls", None)
+
+ _request = build_conversational_analysis_authoring_get_export_status_request(
+ project_name=project_name,
+ job_id=job_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"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _stream = kwargs.pop("stream", False)
+ pipeline_response: PipelineResponse = await 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:
+ 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ if _stream:
+ deserialized = response.iter_bytes()
+ else:
+ deserialized = _deserialize(_models.GetExportStatusResponse, response.json())
+
+ if cls:
+ return cls(pipeline_response, deserialized, {}) # type: ignore
+
+ return deserialized # type: ignore
+
+ @distributed_trace_async
+ async def get_import_status(self, project_name: str, job_id: str, **kwargs: Any) -> _models.GetImportStatusResponse:
+ """Gets the status for an import.
+
+ :param project_name: The new project name. Required.
+ :type project_name: str
+ :param job_id: The job ID. Required.
+ :type job_id: str
+ :return: GetImportStatusResponse. The GetImportStatusResponse is compatible with MutableMapping
+ :rtype: ~azure.ai.language.authoring.analyzeconversations.models.GetImportStatusResponse
+ :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[_models.GetImportStatusResponse] = kwargs.pop("cls", None)
+
+ _request = build_conversational_analysis_authoring_get_import_status_request(
+ project_name=project_name,
+ job_id=job_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"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _stream = kwargs.pop("stream", False)
+ pipeline_response: PipelineResponse = await 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:
+ 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ if _stream:
+ deserialized = response.iter_bytes()
+ else:
+ deserialized = _deserialize(_models.GetImportStatusResponse, response.json())
+
+ if cls:
+ return cls(pipeline_response, deserialized, {}) # type: ignore
+
+ return deserialized # type: ignore
+
+ @distributed_trace
+ def list_trained_models(
+ self, project_name: str, *, top: Optional[int] = None, skip: Optional[int] = None, **kwargs: Any
+ ) -> AsyncIterable["_models.ConversationalAnalysisAuthoringProjectTrainedModel"]:
+ # pylint: disable=line-too-long
+ """Lists the trained models belonging to a project.
+
+ :param project_name: The new project name. Required.
+ :type project_name: str
+ :keyword top: The number of result items to return. Default value is None.
+ :paramtype top: int
+ :keyword skip: The number of result items to skip. Default value is None.
+ :paramtype skip: int
+ :return: An iterator like instance of ConversationalAnalysisAuthoringProjectTrainedModel
+ :rtype:
+ ~azure.core.async_paging.AsyncItemPaged[~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringProjectTrainedModel]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = kwargs.pop("params", {}) or {}
+
+ maxpagesize = kwargs.pop("maxpagesize", None)
+ cls: ClsType[List[_models.ConversationalAnalysisAuthoringProjectTrainedModel]] = 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_conversational_analysis_authoring_list_trained_models_request(
+ project_name=project_name,
+ top=top,
+ skip=skip,
+ maxpagesize=maxpagesize,
+ api_version=self._config.api_version,
+ headers=_headers,
+ params=_params,
+ )
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _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"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _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.ConversationalAnalysisAuthoringProjectTrainedModel], 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( # 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ return pipeline_response
+
+ return AsyncItemPaged(get_next, extract_data)
+
+ @distributed_trace_async
+ async def get_trained_model(
+ self, project_name: str, trained_model_label: str, **kwargs: Any
+ ) -> _models.GetTrainedModelResponse:
+ """Gets the details of a trained model.
+
+ :param project_name: The new project name. Required.
+ :type project_name: str
+ :param trained_model_label: The trained model label. Required.
+ :type trained_model_label: str
+ :return: GetTrainedModelResponse. The GetTrainedModelResponse is compatible with MutableMapping
+ :rtype: ~azure.ai.language.authoring.analyzeconversations.models.GetTrainedModelResponse
+ :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[_models.GetTrainedModelResponse] = kwargs.pop("cls", None)
+
+ _request = build_conversational_analysis_authoring_get_trained_model_request(
+ project_name=project_name,
+ trained_model_label=trained_model_label,
+ api_version=self._config.api_version,
+ headers=_headers,
+ params=_params,
+ )
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _stream = kwargs.pop("stream", False)
+ pipeline_response: PipelineResponse = await 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:
+ 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ if _stream:
+ deserialized = response.iter_bytes()
+ else:
+ deserialized = _deserialize(_models.GetTrainedModelResponse, response.json())
+
+ if cls:
+ return cls(pipeline_response, deserialized, {}) # type: ignore
+
+ return deserialized # type: ignore
+
+ @distributed_trace_async
+ async def delete_trained_model(self, project_name: str, trained_model_label: str, **kwargs: Any) -> None:
+ """Deletes an existing trained model.
+
+ :param project_name: The new project name. Required.
+ :type project_name: str
+ :param trained_model_label: The trained model label. Required.
+ :type trained_model_label: 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_conversational_analysis_authoring_delete_trained_model_request(
+ project_name=project_name,
+ trained_model_label=trained_model_label,
+ api_version=self._config.api_version,
+ headers=_headers,
+ params=_params,
+ )
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _stream = False
+ pipeline_response: PipelineResponse = await 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ if cls:
+ return cls(pipeline_response, None, {}) # type: ignore
+
+ @api_version_validation(
+ method_added_on="2023-04-15-preview",
+ params_added_on={
+ "2023-04-15-preview": ["api_version", "project_name", "trained_model_label", "content_type", "accept"]
+ },
+ )
+ async def _evaluate_model_initial(
+ self,
+ project_name: str,
+ trained_model_label: str,
+ body: Union[_models.ConversationalAnalysisAuthoringEvaluationOptions, JSON, IO[bytes]],
+ **kwargs: Any
+ ) -> AsyncIterator[bytes]:
+ error_map: MutableMapping = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _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[AsyncIterator[bytes]] = kwargs.pop("cls", None)
+
+ content_type = content_type or "application/json"
+ _content = None
+ if isinstance(body, (IOBase, bytes)):
+ _content = body
+ else:
+ _content = json.dumps(body, cls=SdkJSONEncoder, exclude_readonly=True) # type: ignore
+
+ _request = build_conversational_analysis_authoring_evaluate_model_request(
+ project_name=project_name,
+ trained_model_label=trained_model_label,
+ content_type=content_type,
+ api_version=self._config.api_version,
+ content=_content,
+ headers=_headers,
+ params=_params,
+ )
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _stream = True
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ _request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [202]:
+ 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ response_headers = {}
+ response_headers["Operation-Location"] = self._deserialize("str", response.headers.get("Operation-Location"))
+
+ deserialized = response.iter_bytes()
+
+ if cls:
+ return cls(pipeline_response, deserialized, response_headers) # type: ignore
+
+ return deserialized # type: ignore
+
+ @overload
+ async def begin_evaluate_model(
+ self,
+ project_name: str,
+ trained_model_label: str,
+ body: _models.ConversationalAnalysisAuthoringEvaluationOptions,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> AsyncLROPoller[_models.ConversationalAnalysisAuthoringEvaluationJobResult]:
+ # pylint: disable=line-too-long
+ """Triggers evaluation operation on a trained model.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param trained_model_label: The trained model label. Required.
+ :type trained_model_label: str
+ :param body: The training input parameters. Required.
+ :type body:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringEvaluationOptions
+ :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 AsyncLROPoller that returns
+ ConversationalAnalysisAuthoringEvaluationJobResult. The
+ ConversationalAnalysisAuthoringEvaluationJobResult is compatible with MutableMapping
+ :rtype:
+ ~azure.core.polling.AsyncLROPoller[~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringEvaluationJobResult]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ async def begin_evaluate_model(
+ self,
+ project_name: str,
+ trained_model_label: str,
+ body: JSON,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> AsyncLROPoller[_models.ConversationalAnalysisAuthoringEvaluationJobResult]:
+ # pylint: disable=line-too-long
+ """Triggers evaluation operation on a trained model.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param trained_model_label: The trained model label. Required.
+ :type trained_model_label: str
+ :param body: The training input 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: An instance of AsyncLROPoller that returns
+ ConversationalAnalysisAuthoringEvaluationJobResult. The
+ ConversationalAnalysisAuthoringEvaluationJobResult is compatible with MutableMapping
+ :rtype:
+ ~azure.core.polling.AsyncLROPoller[~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringEvaluationJobResult]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ async def begin_evaluate_model(
+ self,
+ project_name: str,
+ trained_model_label: str,
+ body: IO[bytes],
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> AsyncLROPoller[_models.ConversationalAnalysisAuthoringEvaluationJobResult]:
+ # pylint: disable=line-too-long
+ """Triggers evaluation operation on a trained model.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param trained_model_label: The trained model label. Required.
+ :type trained_model_label: str
+ :param body: The training input 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: An instance of AsyncLROPoller that returns
+ ConversationalAnalysisAuthoringEvaluationJobResult. The
+ ConversationalAnalysisAuthoringEvaluationJobResult is compatible with MutableMapping
+ :rtype:
+ ~azure.core.polling.AsyncLROPoller[~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringEvaluationJobResult]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @distributed_trace_async
+ @api_version_validation(
+ method_added_on="2023-04-15-preview",
+ params_added_on={
+ "2023-04-15-preview": ["api_version", "project_name", "trained_model_label", "content_type", "accept"]
+ },
+ )
+ async def begin_evaluate_model(
+ self,
+ project_name: str,
+ trained_model_label: str,
+ body: Union[_models.ConversationalAnalysisAuthoringEvaluationOptions, JSON, IO[bytes]],
+ **kwargs: Any
+ ) -> AsyncLROPoller[_models.ConversationalAnalysisAuthoringEvaluationJobResult]:
+ # pylint: disable=line-too-long
+ """Triggers evaluation operation on a trained model.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param trained_model_label: The trained model label. Required.
+ :type trained_model_label: str
+ :param body: The training input parameters. Is one of the following types:
+ ConversationalAnalysisAuthoringEvaluationOptions, JSON, IO[bytes] Required.
+ :type body:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringEvaluationOptions
+ or JSON or IO[bytes]
+ :return: An instance of AsyncLROPoller that returns
+ ConversationalAnalysisAuthoringEvaluationJobResult. The
+ ConversationalAnalysisAuthoringEvaluationJobResult is compatible with MutableMapping
+ :rtype:
+ ~azure.core.polling.AsyncLROPoller[~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringEvaluationJobResult]
+ :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.ConversationalAnalysisAuthoringEvaluationJobResult] = 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._evaluate_model_initial(
+ project_name=project_name,
+ trained_model_label=trained_model_label,
+ 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)
+
+ def get_long_running_output(pipeline_response):
+ response_headers = {}
+ response = pipeline_response.http_response
+ response_headers["Operation-Location"] = self._deserialize(
+ "str", response.headers.get("Operation-Location")
+ )
+
+ deserialized = _deserialize(
+ _models.ConversationalAnalysisAuthoringEvaluationJobResult, response.json().get("result")
+ )
+ 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"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+
+ 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.ConversationalAnalysisAuthoringEvaluationJobResult].from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return AsyncLROPoller[_models.ConversationalAnalysisAuthoringEvaluationJobResult](
+ self._client, raw_result, get_long_running_output, polling_method # type: ignore
+ )
+
+ async def _load_snapshot_initial(
+ self, project_name: str, trained_model_label: str, **kwargs: Any
+ ) -> AsyncIterator[bytes]:
+ 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_conversational_analysis_authoring_load_snapshot_request(
+ project_name=project_name,
+ trained_model_label=trained_model_label,
+ api_version=self._config.api_version,
+ headers=_headers,
+ params=_params,
+ )
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _stream = True
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ _request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [202]:
+ 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ response_headers = {}
+ response_headers["Operation-Location"] = self._deserialize("str", response.headers.get("Operation-Location"))
+
+ deserialized = response.iter_bytes()
+
+ if cls:
+ return cls(pipeline_response, deserialized, response_headers) # type: ignore
+
+ return deserialized # type: ignore
+
+ @distributed_trace_async
+ async def begin_load_snapshot(
+ self, project_name: str, trained_model_label: str, **kwargs: Any
+ ) -> AsyncLROPoller[None]:
+ """Restores the snapshot of this trained model to be the current working directory
+ of the project.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param trained_model_label: The trained model label. Required.
+ :type trained_model_label: str
+ :return: An instance of AsyncLROPoller that returns None
+ :rtype: ~azure.core.polling.AsyncLROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = kwargs.pop("params", {}) or {}
+
+ cls: ClsType[None] = 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._load_snapshot_initial(
+ project_name=project_name,
+ trained_model_label=trained_model_label,
+ 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): # pylint: disable=inconsistent-return-statements
+ if cls:
+ return cls(pipeline_response, None, {}) # type: ignore
+
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+
+ 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[None].from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return AsyncLROPoller[None](self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ @distributed_trace_async
+ @api_version_validation(
+ method_added_on="2023-04-15-preview",
+ params_added_on={
+ "2023-04-15-preview": ["api_version", "project_name", "trained_model_label", "job_id", "accept"]
+ },
+ )
+ async def get_evaluation_status(
+ self, project_name: str, trained_model_label: str, job_id: str, **kwargs: Any
+ ) -> _models.GetEvaluationStatusResponse:
+ """Gets the status for an evaluation job.
+
+ :param project_name: The new project name. Required.
+ :type project_name: str
+ :param trained_model_label: The trained model label. Required.
+ :type trained_model_label: str
+ :param job_id: The job ID. Required.
+ :type job_id: str
+ :return: GetEvaluationStatusResponse. The GetEvaluationStatusResponse is compatible with
+ MutableMapping
+ :rtype: ~azure.ai.language.authoring.analyzeconversations.models.GetEvaluationStatusResponse
+ :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[_models.GetEvaluationStatusResponse] = kwargs.pop("cls", None)
+
+ _request = build_conversational_analysis_authoring_get_evaluation_status_request(
+ project_name=project_name,
+ trained_model_label=trained_model_label,
+ job_id=job_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"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _stream = kwargs.pop("stream", False)
+ pipeline_response: PipelineResponse = await 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:
+ 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ if _stream:
+ deserialized = response.iter_bytes()
+ else:
+ deserialized = _deserialize(_models.GetEvaluationStatusResponse, response.json())
+
+ if cls:
+ return cls(pipeline_response, deserialized, {}) # type: ignore
+
+ return deserialized # type: ignore
+
+ @distributed_trace
+ def get_model_evaluation_results(
+ self,
+ project_name: str,
+ trained_model_label: str,
+ *,
+ string_index_type: Union[str, _models.StringIndexType],
+ top: Optional[int] = None,
+ skip: Optional[int] = None,
+ **kwargs: Any
+ ) -> AsyncIterable["_models.ConversationalAnalysisAuthoringUtteranceEvaluationResult"]:
+ # pylint: disable=line-too-long
+ """Gets the detailed results of the evaluation for a trained model. This includes
+ the raw inference results for the data included in the evaluation process.
+
+ :param project_name: The new project name. Required.
+ :type project_name: str
+ :param trained_model_label: The trained model label. Required.
+ :type trained_model_label: str
+ :keyword string_index_type: Specifies the method used to interpret string offsets. For
+ additional
+ information see https://aka.ms/text-analytics-offsets. "Utf16CodeUnit" Required.
+ :paramtype string_index_type: str or
+ ~azure.ai.language.authoring.analyzeconversations.models.StringIndexType
+ :keyword top: The number of result items to return. Default value is None.
+ :paramtype top: int
+ :keyword skip: The number of result items to skip. Default value is None.
+ :paramtype skip: int
+ :return: An iterator like instance of ConversationalAnalysisAuthoringUtteranceEvaluationResult
+ :rtype:
+ ~azure.core.async_paging.AsyncItemPaged[~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringUtteranceEvaluationResult]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = kwargs.pop("params", {}) or {}
+
+ maxpagesize = kwargs.pop("maxpagesize", None)
+ cls: ClsType[List[_models.ConversationalAnalysisAuthoringUtteranceEvaluationResult]] = 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_conversational_analysis_authoring_get_model_evaluation_results_request(
+ project_name=project_name,
+ trained_model_label=trained_model_label,
+ string_index_type=string_index_type,
+ top=top,
+ skip=skip,
+ maxpagesize=maxpagesize,
+ api_version=self._config.api_version,
+ headers=_headers,
+ params=_params,
+ )
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _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"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _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.ConversationalAnalysisAuthoringUtteranceEvaluationResult], 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( # 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ return pipeline_response
+
+ return AsyncItemPaged(get_next, extract_data)
+
+ @distributed_trace_async
+ async def get_model_evaluation_summary(
+ self, project_name: str, trained_model_label: str, **kwargs: Any
+ ) -> _models.ConversationalAnalysisAuthoringEvaluationSummary:
+ """Gets the evaluation summary of a trained model. The summary includes high level
+ performance measurements of the model e.g., F1, Precision, Recall, etc.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param trained_model_label: The trained model label. Required.
+ :type trained_model_label: str
+ :return: ConversationalAnalysisAuthoringEvaluationSummary. The
+ ConversationalAnalysisAuthoringEvaluationSummary is compatible with MutableMapping
+ :rtype:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringEvaluationSummary
+ :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[_models.ConversationalAnalysisAuthoringEvaluationSummary] = kwargs.pop("cls", None)
+
+ _request = build_conversational_analysis_authoring_get_model_evaluation_summary_request(
+ project_name=project_name,
+ trained_model_label=trained_model_label,
+ api_version=self._config.api_version,
+ headers=_headers,
+ params=_params,
+ )
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _stream = kwargs.pop("stream", False)
+ pipeline_response: PipelineResponse = await 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:
+ 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ if _stream:
+ deserialized = response.iter_bytes()
+ else:
+ deserialized = _deserialize(_models.ConversationalAnalysisAuthoringEvaluationSummary, response.json())
+
+ if cls:
+ return cls(pipeline_response, deserialized, {}) # type: ignore
+
+ return deserialized # type: ignore
+
+ @distributed_trace_async
+ async def get_load_snapshot_status(
+ self, project_name: str, trained_model_label: str, job_id: str, **kwargs: Any
+ ) -> _models.GetLoadSnapshotStatusResponse:
+ """Gets the status for loading a snapshot.
+
+ :param project_name: The new project name. Required.
+ :type project_name: str
+ :param trained_model_label: The trained model label. Required.
+ :type trained_model_label: str
+ :param job_id: The job ID. Required.
+ :type job_id: str
+ :return: GetLoadSnapshotStatusResponse. The GetLoadSnapshotStatusResponse is compatible with
+ MutableMapping
+ :rtype: ~azure.ai.language.authoring.analyzeconversations.models.GetLoadSnapshotStatusResponse
+ :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[_models.GetLoadSnapshotStatusResponse] = kwargs.pop("cls", None)
+
+ _request = build_conversational_analysis_authoring_get_load_snapshot_status_request(
+ project_name=project_name,
+ trained_model_label=trained_model_label,
+ job_id=job_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"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _stream = kwargs.pop("stream", False)
+ pipeline_response: PipelineResponse = await 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:
+ 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ if _stream:
+ deserialized = response.iter_bytes()
+ else:
+ deserialized = _deserialize(_models.GetLoadSnapshotStatusResponse, response.json())
+
+ if cls:
+ return cls(pipeline_response, deserialized, {}) # type: ignore
+
+ return deserialized # type: ignore
+
+ @distributed_trace
+ @api_version_validation(
+ method_added_on="2023-04-15-preview",
+ params_added_on={"2023-04-15-preview": ["api_version", "project_name", "top", "skip", "maxpagesize", "accept"]},
+ )
+ def list_deployment_resources(
+ self, project_name: str, *, top: Optional[int] = None, skip: Optional[int] = None, **kwargs: Any
+ ) -> AsyncIterable["_models.ConversationalAnalysisAuthoringAssignedDeploymentResource"]:
+ # pylint: disable=line-too-long
+ """Lists the deployments resources assigned to the project.
+
+ :param project_name: The new project name. Required.
+ :type project_name: str
+ :keyword top: The number of result items to return. Default value is None.
+ :paramtype top: int
+ :keyword skip: The number of result items to skip. Default value is None.
+ :paramtype skip: int
+ :return: An iterator like instance of ConversationalAnalysisAuthoringAssignedDeploymentResource
+ :rtype:
+ ~azure.core.async_paging.AsyncItemPaged[~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringAssignedDeploymentResource]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = kwargs.pop("params", {}) or {}
+
+ maxpagesize = kwargs.pop("maxpagesize", None)
+ cls: ClsType[List[_models.ConversationalAnalysisAuthoringAssignedDeploymentResource]] = 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_conversational_analysis_authoring_list_deployment_resources_request(
+ project_name=project_name,
+ top=top,
+ skip=skip,
+ maxpagesize=maxpagesize,
+ api_version=self._config.api_version,
+ headers=_headers,
+ params=_params,
+ )
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _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"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _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.ConversationalAnalysisAuthoringAssignedDeploymentResource], 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( # 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ return pipeline_response
+
+ return AsyncItemPaged(get_next, extract_data)
+
+ @api_version_validation(
+ method_added_on="2023-04-15-preview",
+ params_added_on={"2023-04-15-preview": ["api_version", "project_name", "content_type", "accept"]},
+ )
+ async def _assign_deployment_resources_initial(
+ self,
+ project_name: str,
+ body: Union[_models.ConversationalAnalysisAuthoringAssignDeploymentResourcesOptions, JSON, IO[bytes]],
+ **kwargs: Any
+ ) -> AsyncIterator[bytes]:
+ error_map: MutableMapping = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _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[AsyncIterator[bytes]] = kwargs.pop("cls", None)
+
+ content_type = content_type or "application/json"
+ _content = None
+ if isinstance(body, (IOBase, bytes)):
+ _content = body
+ else:
+ _content = json.dumps(body, cls=SdkJSONEncoder, exclude_readonly=True) # type: ignore
+
+ _request = build_conversational_analysis_authoring_assign_deployment_resources_request(
+ project_name=project_name,
+ content_type=content_type,
+ api_version=self._config.api_version,
+ content=_content,
+ headers=_headers,
+ params=_params,
+ )
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _stream = True
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ _request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [202]:
+ 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ response_headers = {}
+ response_headers["Operation-Location"] = self._deserialize("str", response.headers.get("Operation-Location"))
+
+ deserialized = response.iter_bytes()
+
+ if cls:
+ return cls(pipeline_response, deserialized, response_headers) # type: ignore
+
+ return deserialized # type: ignore
+
+ @overload
+ async def begin_assign_deployment_resources(
+ self,
+ project_name: str,
+ body: _models.ConversationalAnalysisAuthoringAssignDeploymentResourcesOptions,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> AsyncLROPoller[None]:
+ # pylint: disable=line-too-long
+ """Assign new Azure resources to a project to allow deploying new deployments to
+ them. This API is available only via AAD authentication and not supported via
+ subscription key authentication. For more details about AAD authentication,
+ check here:
+ https://learn.microsoft.com/en-us/azure/cognitive-services/authentication?tabs=powershell#authenticate-with-azure-active-directory.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param body: The new project resources info. Required.
+ :type body:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringAssignDeploymentResourcesOptions
+ :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 AsyncLROPoller that returns None
+ :rtype: ~azure.core.polling.AsyncLROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ async def begin_assign_deployment_resources(
+ self, project_name: str, body: JSON, *, content_type: str = "application/json", **kwargs: Any
+ ) -> AsyncLROPoller[None]:
+ """Assign new Azure resources to a project to allow deploying new deployments to
+ them. This API is available only via AAD authentication and not supported via
+ subscription key authentication. For more details about AAD authentication,
+ check here:
+ https://learn.microsoft.com/en-us/azure/cognitive-services/authentication?tabs=powershell#authenticate-with-azure-active-directory.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param body: The new project resources info. 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: An instance of AsyncLROPoller that returns None
+ :rtype: ~azure.core.polling.AsyncLROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ async def begin_assign_deployment_resources(
+ self, project_name: str, body: IO[bytes], *, content_type: str = "application/json", **kwargs: Any
+ ) -> AsyncLROPoller[None]:
+ """Assign new Azure resources to a project to allow deploying new deployments to
+ them. This API is available only via AAD authentication and not supported via
+ subscription key authentication. For more details about AAD authentication,
+ check here:
+ https://learn.microsoft.com/en-us/azure/cognitive-services/authentication?tabs=powershell#authenticate-with-azure-active-directory.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param body: The new project resources info. 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: An instance of AsyncLROPoller that returns None
+ :rtype: ~azure.core.polling.AsyncLROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @distributed_trace_async
+ @api_version_validation(
+ method_added_on="2023-04-15-preview",
+ params_added_on={"2023-04-15-preview": ["api_version", "project_name", "content_type", "accept"]},
+ )
+ async def begin_assign_deployment_resources(
+ self,
+ project_name: str,
+ body: Union[_models.ConversationalAnalysisAuthoringAssignDeploymentResourcesOptions, JSON, IO[bytes]],
+ **kwargs: Any
+ ) -> AsyncLROPoller[None]:
+ # pylint: disable=line-too-long
+ """Assign new Azure resources to a project to allow deploying new deployments to
+ them. This API is available only via AAD authentication and not supported via
+ subscription key authentication. For more details about AAD authentication,
+ check here:
+ https://learn.microsoft.com/en-us/azure/cognitive-services/authentication?tabs=powershell#authenticate-with-azure-active-directory.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param body: The new project resources info. Is one of the following types:
+ ConversationalAnalysisAuthoringAssignDeploymentResourcesOptions, JSON, IO[bytes] Required.
+ :type body:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringAssignDeploymentResourcesOptions
+ or JSON or IO[bytes]
+ :return: An instance of AsyncLROPoller that returns None
+ :rtype: ~azure.core.polling.AsyncLROPoller[None]
+ :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[None] = 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._assign_deployment_resources_initial(
+ project_name=project_name,
+ 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)
+
+ def get_long_running_output(pipeline_response): # pylint: disable=inconsistent-return-statements
+ if cls:
+ return cls(pipeline_response, None, {}) # type: ignore
+
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+
+ 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[None].from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return AsyncLROPoller[None](self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ @api_version_validation(
+ method_added_on="2023-04-15-preview",
+ params_added_on={"2023-04-15-preview": ["api_version", "project_name", "content_type", "accept"]},
+ )
+ async def _unassign_deployment_resources_initial(
+ self,
+ project_name: str,
+ body: Union[_models.ConversationalAnalysisAuthoringUnassignDeploymentResourcesOptions, JSON, IO[bytes]],
+ **kwargs: Any
+ ) -> AsyncIterator[bytes]:
+ error_map: MutableMapping = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _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[AsyncIterator[bytes]] = kwargs.pop("cls", None)
+
+ content_type = content_type or "application/json"
+ _content = None
+ if isinstance(body, (IOBase, bytes)):
+ _content = body
+ else:
+ _content = json.dumps(body, cls=SdkJSONEncoder, exclude_readonly=True) # type: ignore
+
+ _request = build_conversational_analysis_authoring_unassign_deployment_resources_request(
+ project_name=project_name,
+ content_type=content_type,
+ api_version=self._config.api_version,
+ content=_content,
+ headers=_headers,
+ params=_params,
+ )
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _stream = True
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ _request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [202]:
+ 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ response_headers = {}
+ response_headers["Operation-Location"] = self._deserialize("str", response.headers.get("Operation-Location"))
+
+ deserialized = response.iter_bytes()
+
+ if cls:
+ return cls(pipeline_response, deserialized, response_headers) # type: ignore
+
+ return deserialized # type: ignore
+
+ @overload
+ async def begin_unassign_deployment_resources(
+ self,
+ project_name: str,
+ body: _models.ConversationalAnalysisAuthoringUnassignDeploymentResourcesOptions,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> AsyncLROPoller[None]:
+ # pylint: disable=line-too-long
+ """Unassign resources from a project. This disallows deploying new deployments to
+ these resources, and deletes existing deployments assigned to them.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param body: The info for the deployment resources to be deleted. Required.
+ :type body:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringUnassignDeploymentResourcesOptions
+ :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 AsyncLROPoller that returns None
+ :rtype: ~azure.core.polling.AsyncLROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ async def begin_unassign_deployment_resources(
+ self, project_name: str, body: JSON, *, content_type: str = "application/json", **kwargs: Any
+ ) -> AsyncLROPoller[None]:
+ """Unassign resources from a project. This disallows deploying new deployments to
+ these resources, and deletes existing deployments assigned to them.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param body: The info for the deployment resources to be deleted. 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: An instance of AsyncLROPoller that returns None
+ :rtype: ~azure.core.polling.AsyncLROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ async def begin_unassign_deployment_resources(
+ self, project_name: str, body: IO[bytes], *, content_type: str = "application/json", **kwargs: Any
+ ) -> AsyncLROPoller[None]:
+ """Unassign resources from a project. This disallows deploying new deployments to
+ these resources, and deletes existing deployments assigned to them.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param body: The info for the deployment resources to be deleted. 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: An instance of AsyncLROPoller that returns None
+ :rtype: ~azure.core.polling.AsyncLROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @distributed_trace_async
+ @api_version_validation(
+ method_added_on="2023-04-15-preview",
+ params_added_on={"2023-04-15-preview": ["api_version", "project_name", "content_type", "accept"]},
+ )
+ async def begin_unassign_deployment_resources(
+ self,
+ project_name: str,
+ body: Union[_models.ConversationalAnalysisAuthoringUnassignDeploymentResourcesOptions, JSON, IO[bytes]],
+ **kwargs: Any
+ ) -> AsyncLROPoller[None]:
+ # pylint: disable=line-too-long
+ """Unassign resources from a project. This disallows deploying new deployments to
+ these resources, and deletes existing deployments assigned to them.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param body: The info for the deployment resources to be deleted. Is one of the following
+ types: ConversationalAnalysisAuthoringUnassignDeploymentResourcesOptions, JSON, IO[bytes]
+ Required.
+ :type body:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringUnassignDeploymentResourcesOptions
+ or JSON or IO[bytes]
+ :return: An instance of AsyncLROPoller that returns None
+ :rtype: ~azure.core.polling.AsyncLROPoller[None]
+ :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[None] = 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._unassign_deployment_resources_initial(
+ project_name=project_name,
+ 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)
+
+ def get_long_running_output(pipeline_response): # pylint: disable=inconsistent-return-statements
+ if cls:
+ return cls(pipeline_response, None, {}) # type: ignore
+
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+
+ 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[None].from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return AsyncLROPoller[None](self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ @distributed_trace_async
+ @api_version_validation(
+ method_added_on="2023-04-15-preview",
+ params_added_on={"2023-04-15-preview": ["api_version", "project_name", "job_id", "accept"]},
+ )
+ async def get_assign_deployment_resources_status(
+ self, project_name: str, job_id: str, **kwargs: Any
+ ) -> _models.GetAssignDeploymentResourcesStatusResponse:
+ """Gets the status of an existing assign deployment resources job.
+
+ :param project_name: The new project name. Required.
+ :type project_name: str
+ :param job_id: The job ID. Required.
+ :type job_id: str
+ :return: GetAssignDeploymentResourcesStatusResponse. The
+ GetAssignDeploymentResourcesStatusResponse is compatible with MutableMapping
+ :rtype:
+ ~azure.ai.language.authoring.analyzeconversations.models.GetAssignDeploymentResourcesStatusResponse
+ :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[_models.GetAssignDeploymentResourcesStatusResponse] = kwargs.pop("cls", None)
+
+ _request = build_conversational_analysis_authoring_get_assign_deployment_resources_status_request(
+ project_name=project_name,
+ job_id=job_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"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _stream = kwargs.pop("stream", False)
+ pipeline_response: PipelineResponse = await 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:
+ 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ if _stream:
+ deserialized = response.iter_bytes()
+ else:
+ deserialized = _deserialize(_models.GetAssignDeploymentResourcesStatusResponse, response.json())
+
+ if cls:
+ return cls(pipeline_response, deserialized, {}) # type: ignore
+
+ return deserialized # type: ignore
+
+ @distributed_trace_async
+ @api_version_validation(
+ method_added_on="2023-04-15-preview",
+ params_added_on={"2023-04-15-preview": ["api_version", "project_name", "job_id", "accept"]},
+ )
+ async def get_unassign_deployment_resources_status(
+ self, project_name: str, job_id: str, **kwargs: Any
+ ) -> _models.GetUnassignDeploymentResourcesStatusResponse:
+ """Gets the status of an existing unassign deployment resources job.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param job_id: The job ID. Required.
+ :type job_id: str
+ :return: GetUnassignDeploymentResourcesStatusResponse. The
+ GetUnassignDeploymentResourcesStatusResponse is compatible with MutableMapping
+ :rtype:
+ ~azure.ai.language.authoring.analyzeconversations.models.GetUnassignDeploymentResourcesStatusResponse
+ :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[_models.GetUnassignDeploymentResourcesStatusResponse] = kwargs.pop("cls", None)
+
+ _request = build_conversational_analysis_authoring_get_unassign_deployment_resources_status_request(
+ project_name=project_name,
+ job_id=job_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"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _stream = kwargs.pop("stream", False)
+ pipeline_response: PipelineResponse = await 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:
+ 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ if _stream:
+ deserialized = response.iter_bytes()
+ else:
+ deserialized = _deserialize(_models.GetUnassignDeploymentResourcesStatusResponse, response.json())
+
+ if cls:
+ return cls(pipeline_response, deserialized, {}) # type: ignore
+
+ return deserialized # type: ignore
+
+ @distributed_trace
+ def list_training_jobs(
+ self, project_name: str, *, top: Optional[int] = None, skip: Optional[int] = None, **kwargs: Any
+ ) -> AsyncIterable["_models.ConversationalAnalysisAuthoringTrainingJobState"]:
+ # pylint: disable=line-too-long
+ """Lists the non-expired training jobs created for a project.
+
+ :param project_name: The new project name. Required.
+ :type project_name: str
+ :keyword top: The number of result items to return. Default value is None.
+ :paramtype top: int
+ :keyword skip: The number of result items to skip. Default value is None.
+ :paramtype skip: int
+ :return: An iterator like instance of ConversationalAnalysisAuthoringTrainingJobState
+ :rtype:
+ ~azure.core.async_paging.AsyncItemPaged[~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringTrainingJobState]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = kwargs.pop("params", {}) or {}
+
+ maxpagesize = kwargs.pop("maxpagesize", None)
+ cls: ClsType[List[_models.ConversationalAnalysisAuthoringTrainingJobState]] = 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_conversational_analysis_authoring_list_training_jobs_request(
+ project_name=project_name,
+ top=top,
+ skip=skip,
+ maxpagesize=maxpagesize,
+ api_version=self._config.api_version,
+ headers=_headers,
+ params=_params,
+ )
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _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"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _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.ConversationalAnalysisAuthoringTrainingJobState], 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( # 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ return pipeline_response
+
+ return AsyncItemPaged(get_next, extract_data)
+
+ @distributed_trace_async
+ async def get_training_status(
+ self, project_name: str, job_id: str, **kwargs: Any
+ ) -> _models.GetTrainingStatusResponse:
+ """Gets the status for a training job.
+
+ :param project_name: The new project name. Required.
+ :type project_name: str
+ :param job_id: The job ID. Required.
+ :type job_id: str
+ :return: GetTrainingStatusResponse. The GetTrainingStatusResponse is compatible with
+ MutableMapping
+ :rtype: ~azure.ai.language.authoring.analyzeconversations.models.GetTrainingStatusResponse
+ :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[_models.GetTrainingStatusResponse] = kwargs.pop("cls", None)
+
+ _request = build_conversational_analysis_authoring_get_training_status_request(
+ project_name=project_name,
+ job_id=job_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"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _stream = kwargs.pop("stream", False)
+ pipeline_response: PipelineResponse = await 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:
+ 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ if _stream:
+ deserialized = response.iter_bytes()
+ else:
+ deserialized = _deserialize(_models.GetTrainingStatusResponse, response.json())
+
+ if cls:
+ return cls(pipeline_response, deserialized, {}) # type: ignore
+
+ return deserialized # type: ignore
+
+ async def _cancel_training_job_initial(self, project_name: str, job_id: str, **kwargs: Any) -> AsyncIterator[bytes]:
+ 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_conversational_analysis_authoring_cancel_training_job_request(
+ project_name=project_name,
+ job_id=job_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"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _stream = True
+ pipeline_response: PipelineResponse = await self._client._pipeline.run( # pylint: disable=protected-access
+ _request, stream=_stream, **kwargs
+ )
+
+ response = pipeline_response.http_response
+
+ if response.status_code not in [202]:
+ 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ response_headers = {}
+ response_headers["Operation-Location"] = self._deserialize("str", response.headers.get("Operation-Location"))
+
+ deserialized = response.iter_bytes()
+
+ if cls:
+ return cls(pipeline_response, deserialized, response_headers) # type: ignore
+
+ return deserialized # type: ignore
+
+ @distributed_trace_async
+ async def begin_cancel_training_job(
+ self, project_name: str, job_id: str, **kwargs: Any
+ ) -> AsyncLROPoller[_models.ConversationalAnalysisAuthoringTrainingJobResult]:
+ # pylint: disable=line-too-long
+ """Triggers a cancellation for a running training job.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param job_id: The job ID. Required.
+ :type job_id: str
+ :return: An instance of AsyncLROPoller that returns
+ ConversationalAnalysisAuthoringTrainingJobResult. The
+ ConversationalAnalysisAuthoringTrainingJobResult is compatible with MutableMapping
+ :rtype:
+ ~azure.core.polling.AsyncLROPoller[~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringTrainingJobResult]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = kwargs.pop("params", {}) or {}
+
+ cls: ClsType[_models.ConversationalAnalysisAuthoringTrainingJobResult] = 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._cancel_training_job_initial(
+ project_name=project_name,
+ job_id=job_id,
+ 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["Operation-Location"] = self._deserialize(
+ "str", response.headers.get("Operation-Location")
+ )
+
+ deserialized = _deserialize(
+ _models.ConversationalAnalysisAuthoringTrainingJobResult, response.json().get("result")
+ )
+ 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"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+
+ 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.ConversationalAnalysisAuthoringTrainingJobResult].from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return AsyncLROPoller[_models.ConversationalAnalysisAuthoringTrainingJobResult](
+ self._client, raw_result, get_long_running_output, polling_method # type: ignore
+ )
+
+ @distributed_trace_async
+ async def get_project_deletion_status(self, job_id: str, **kwargs: Any) -> _models.GetProjectDeletionStatusResponse:
+ """Gets the status for a project deletion job.
+
+ :param job_id: The job ID. Required.
+ :type job_id: str
+ :return: GetProjectDeletionStatusResponse. The GetProjectDeletionStatusResponse is compatible
+ with MutableMapping
+ :rtype:
+ ~azure.ai.language.authoring.analyzeconversations.models.GetProjectDeletionStatusResponse
+ :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[_models.GetProjectDeletionStatusResponse] = kwargs.pop("cls", None)
+
+ _request = build_conversational_analysis_authoring_get_project_deletion_status_request(
+ job_id=job_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"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _stream = kwargs.pop("stream", False)
+ pipeline_response: PipelineResponse = await 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:
+ 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ if _stream:
+ deserialized = response.iter_bytes()
+ else:
+ deserialized = _deserialize(_models.GetProjectDeletionStatusResponse, response.json())
+
+ if cls:
+ return cls(pipeline_response, deserialized, {}) # type: ignore
+
+ return deserialized # type: ignore
+
+ @distributed_trace_async
+ @api_version_validation(
+ method_added_on="2023-04-15-preview",
+ params_added_on={"2023-04-15-preview": ["api_version", "top", "skip", "maxpagesize", "accept"]},
+ )
+ async def list_assigned_resource_deployments(
+ self, *, top: Optional[int] = None, skip: Optional[int] = None, **kwargs: Any
+ ) -> _models.ConversationalAnalysisAuthoringAssignedResourceDeploymentsMetadata:
+ # pylint: disable=line-too-long
+ """Lists the deployments to which an Azure resource is assigned. This doesn't
+ return deployments belonging to projects owned by this resource. It only
+ returns deployments belonging to projects owned by other resources.
+
+ :keyword top: The maximum number of resources to return from the collection. Default value is
+ None.
+ :paramtype top: int
+ :keyword skip: An offset into the collection of the first resource to be returned. Default
+ value is None.
+ :paramtype skip: int
+ :return: ConversationalAnalysisAuthoringAssignedResourceDeploymentsMetadata. The
+ ConversationalAnalysisAuthoringAssignedResourceDeploymentsMetadata is compatible with
+ MutableMapping
+ :rtype:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringAssignedResourceDeploymentsMetadata
+ :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 {}
+
+ maxpagesize = kwargs.pop("maxpagesize", None)
+ cls: ClsType[_models.ConversationalAnalysisAuthoringAssignedResourceDeploymentsMetadata] = kwargs.pop(
+ "cls", None
+ )
+
+ _request = build_conversational_analysis_authoring_list_assigned_resource_deployments_request(
+ top=top,
+ skip=skip,
+ maxpagesize=maxpagesize,
+ api_version=self._config.api_version,
+ headers=_headers,
+ params=_params,
+ )
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _stream = kwargs.pop("stream", False)
+ pipeline_response: PipelineResponse = await 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:
+ 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ if _stream:
+ deserialized = response.iter_bytes()
+ else:
+ deserialized = _deserialize(
+ _models.ConversationalAnalysisAuthoringAssignedResourceDeploymentsMetadata, response.json()
+ )
+
+ if cls:
+ return cls(pipeline_response, deserialized, {}) # type: ignore
+
+ return deserialized # type: ignore
+
+ @distributed_trace_async
+ async def get_supported_languages(
+ self,
+ *,
+ project_kind: Union[str, _models.ProjectKind],
+ top: Optional[int] = None,
+ skip: Optional[int] = None,
+ **kwargs: Any
+ ) -> _models.ConversationalAnalysisAuthoringSupportedLanguages:
+ """Lists the supported languages for the given project type.
+
+ :keyword project_kind: The project kind. Known values are: "Conversation", "Orchestration", and
+ "CustomConversationSummarization". Required.
+ :paramtype project_kind: str or
+ ~azure.ai.language.authoring.analyzeconversations.models.ProjectKind
+ :keyword top: The maximum number of resources to return from the collection. Default value is
+ None.
+ :paramtype top: int
+ :keyword skip: An offset into the collection of the first resource to be returned. Default
+ value is None.
+ :paramtype skip: int
+ :return: ConversationalAnalysisAuthoringSupportedLanguages. The
+ ConversationalAnalysisAuthoringSupportedLanguages is compatible with MutableMapping
+ :rtype:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringSupportedLanguages
+ :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 {}
+
+ maxpagesize = kwargs.pop("maxpagesize", None)
+ cls: ClsType[_models.ConversationalAnalysisAuthoringSupportedLanguages] = kwargs.pop("cls", None)
+
+ _request = build_conversational_analysis_authoring_get_supported_languages_request(
+ project_kind=project_kind,
+ top=top,
+ skip=skip,
+ maxpagesize=maxpagesize,
+ api_version=self._config.api_version,
+ headers=_headers,
+ params=_params,
+ )
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _stream = kwargs.pop("stream", False)
+ pipeline_response: PipelineResponse = await 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:
+ 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ if _stream:
+ deserialized = response.iter_bytes()
+ else:
+ deserialized = _deserialize(_models.ConversationalAnalysisAuthoringSupportedLanguages, response.json())
+
+ if cls:
+ return cls(pipeline_response, deserialized, {}) # type: ignore
+
+ return deserialized # type: ignore
+
+ @distributed_trace_async
+ async def get_supported_prebuilt_entities(
+ self,
+ *,
+ language: Optional[str] = None,
+ multilingual: Optional[str] = None,
+ top: Optional[int] = None,
+ skip: Optional[int] = None,
+ **kwargs: Any
+ ) -> _models.ConversationalAnalysisAuthoringPrebuiltEntities:
+ """Lists the supported prebuilt entities that can be used while creating composed
+ entities.
+
+ :keyword language: The language to get supported prebuilt entities for. Required if
+ multilingual
+ is false. This is BCP-47 representation of a language. For example, use "en"
+ for English, "en-gb" for English (UK), "es" for Spanish etc. Default value is None.
+ :paramtype language: str
+ :keyword multilingual: Whether to get the support prebuilt entities for multilingual or
+ monolingual
+ projects. If true, the language parameter is ignored. Default value is None.
+ :paramtype multilingual: str
+ :keyword top: The maximum number of resources to return from the collection. Default value is
+ None.
+ :paramtype top: int
+ :keyword skip: An offset into the collection of the first resource to be returned. Default
+ value is None.
+ :paramtype skip: int
+ :return: ConversationalAnalysisAuthoringPrebuiltEntities. The
+ ConversationalAnalysisAuthoringPrebuiltEntities is compatible with MutableMapping
+ :rtype:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringPrebuiltEntities
+ :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 {}
+
+ maxpagesize = kwargs.pop("maxpagesize", None)
+ cls: ClsType[_models.ConversationalAnalysisAuthoringPrebuiltEntities] = kwargs.pop("cls", None)
+
+ _request = build_conversational_analysis_authoring_get_supported_prebuilt_entities_request(
+ language=language,
+ multilingual=multilingual,
+ top=top,
+ skip=skip,
+ maxpagesize=maxpagesize,
+ api_version=self._config.api_version,
+ headers=_headers,
+ params=_params,
+ )
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _stream = kwargs.pop("stream", False)
+ pipeline_response: PipelineResponse = await 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:
+ 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ if _stream:
+ deserialized = response.iter_bytes()
+ else:
+ deserialized = _deserialize(_models.ConversationalAnalysisAuthoringPrebuiltEntities, response.json())
+
+ if cls:
+ return cls(pipeline_response, deserialized, {}) # type: ignore
+
+ return deserialized # type: ignore
+
+ @distributed_trace_async
+ async def list_training_config_versions(
+ self,
+ *,
+ project_kind: Union[str, _models.ProjectKind],
+ top: Optional[int] = None,
+ skip: Optional[int] = None,
+ **kwargs: Any
+ ) -> _models.ConversationalAnalysisAuthoringTrainingConfigVersions:
+ """Lists the support training config version for a given project type.
+
+ :keyword project_kind: The project kind. Known values are: "Conversation", "Orchestration", and
+ "CustomConversationSummarization". Required.
+ :paramtype project_kind: str or
+ ~azure.ai.language.authoring.analyzeconversations.models.ProjectKind
+ :keyword top: The maximum number of resources to return from the collection. Default value is
+ None.
+ :paramtype top: int
+ :keyword skip: An offset into the collection of the first resource to be returned. Default
+ value is None.
+ :paramtype skip: int
+ :return: ConversationalAnalysisAuthoringTrainingConfigVersions. The
+ ConversationalAnalysisAuthoringTrainingConfigVersions is compatible with MutableMapping
+ :rtype:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringTrainingConfigVersions
+ :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 {}
+
+ maxpagesize = kwargs.pop("maxpagesize", None)
+ cls: ClsType[_models.ConversationalAnalysisAuthoringTrainingConfigVersions] = kwargs.pop("cls", None)
+
+ _request = build_conversational_analysis_authoring_list_training_config_versions_request(
+ project_kind=project_kind,
+ top=top,
+ skip=skip,
+ maxpagesize=maxpagesize,
+ api_version=self._config.api_version,
+ headers=_headers,
+ params=_params,
+ )
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _stream = kwargs.pop("stream", False)
+ pipeline_response: PipelineResponse = await 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:
+ 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ if _stream:
+ deserialized = response.iter_bytes()
+ else:
+ deserialized = _deserialize(_models.ConversationalAnalysisAuthoringTrainingConfigVersions, response.json())
+
+ if cls:
+ return cls(pipeline_response, deserialized, {}) # type: ignore
+
+ return deserialized # type: ignore
diff --git a/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/aio/operations/_patch.py b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/aio/operations/_patch.py
new file mode 100644
index 000000000000..f7dd32510333
--- /dev/null
+++ b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/aio/operations/_patch.py
@@ -0,0 +1,20 @@
+# ------------------------------------
+# Copyright (c) Microsoft Corporation.
+# Licensed under the MIT License.
+# ------------------------------------
+"""Customize generated code here.
+
+Follow our quickstart for examples: https://aka.ms/azsdk/python/dpcodegen/python/customize
+"""
+from typing import List
+
+__all__: List[str] = [] # Add all objects you want publicly available to users at this package level
+
+
+def patch_sdk():
+ """Do not remove from this file.
+
+ `patch_sdk` is a last resort escape hatch that allows you to do customizations
+ you can't accomplish using the techniques described in
+ https://aka.ms/azsdk/python/dpcodegen/python/customize
+ """
diff --git a/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/models/__init__.py b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/models/__init__.py
new file mode 100644
index 000000000000..ccec20119160
--- /dev/null
+++ b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/models/__init__.py
@@ -0,0 +1,203 @@
+# 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 ._models import ConversationalAnalysisAuthoringAssignDeploymentResourcesOptions
+from ._models import ConversationalAnalysisAuthoringAssignedDeploymentResource
+from ._models import ConversationalAnalysisAuthoringAssignedProjectDeploymentMetadata
+from ._models import ConversationalAnalysisAuthoringAssignedProjectDeploymentsMetadata
+from ._models import ConversationalAnalysisAuthoringAssignedResourceDeploymentsMetadata
+from ._models import ConversationalAnalysisAuthoringConfusionMatrix
+from ._models import ConversationalAnalysisAuthoringConfusionMatrixCell
+from ._models import ConversationalAnalysisAuthoringConfusionMatrixRow
+from ._models import ConversationalAnalysisAuthoringConversationExportedEntity
+from ._models import ConversationalAnalysisAuthoringConversationExportedIntent
+from ._models import ConversationalAnalysisAuthoringConversationExportedProjectAssets
+from ._models import ConversationalAnalysisAuthoringConversationExportedUtterance
+from ._models import ConversationalAnalysisAuthoringCopyProjectOptions
+from ._models import ConversationalAnalysisAuthoringCreateDeploymentOptions
+from ._models import ConversationalAnalysisAuthoringCreateProjectOptions
+from ._models import ConversationalAnalysisAuthoringDeleteDeploymentOptions
+from ._models import ConversationalAnalysisAuthoringDeploymentResource
+from ._models import ConversationalAnalysisAuthoringEntitiesEvaluationSummary
+from ._models import ConversationalAnalysisAuthoringEntityEvaluationSummary
+from ._models import ConversationalAnalysisAuthoringEvaluationJobResult
+from ._models import ConversationalAnalysisAuthoringEvaluationJobState
+from ._models import ConversationalAnalysisAuthoringEvaluationOptions
+from ._models import ConversationalAnalysisAuthoringEvaluationSummary
+from ._models import ConversationalAnalysisAuthoringExportedConversationOrchestration
+from ._models import ConversationalAnalysisAuthoringExportedConversationOrchestrationOptions
+from ._models import ConversationalAnalysisAuthoringExportedEntityList
+from ._models import ConversationalAnalysisAuthoringExportedEntityListSynonym
+from ._models import ConversationalAnalysisAuthoringExportedEntityRegex
+from ._models import ConversationalAnalysisAuthoringExportedEntityRegexExpression
+from ._models import ConversationalAnalysisAuthoringExportedEntitySublist
+from ._models import ConversationalAnalysisAuthoringExportedLuisOrchestration
+from ._models import ConversationalAnalysisAuthoringExportedLuisOrchestrationOptions
+from ._models import ConversationalAnalysisAuthoringExportedOrchestrationOptions
+from ._models import ConversationalAnalysisAuthoringExportedPrebuiltEntity
+from ._models import ConversationalAnalysisAuthoringExportedProject
+from ._models import ConversationalAnalysisAuthoringExportedProjectAssets
+from ._models import ConversationalAnalysisAuthoringExportedQuestionAnsweringOrchestration
+from ._models import ConversationalAnalysisAuthoringExportedQuestionAnsweringOrchestrationOptions
+from ._models import ConversationalAnalysisAuthoringExportedUtteranceEntityLabel
+from ._models import ConversationalAnalysisAuthoringIntentEvaluationSummary
+from ._models import ConversationalAnalysisAuthoringIntentsEvaluationSummary
+from ._models import ConversationalAnalysisAuthoringOrchestrationExportedIntent
+from ._models import ConversationalAnalysisAuthoringOrchestrationExportedProjectAssets
+from ._models import ConversationalAnalysisAuthoringOrchestrationExportedUtterance
+from ._models import ConversationalAnalysisAuthoringPrebuiltEntities
+from ._models import ConversationalAnalysisAuthoringPrebuiltEntity
+from ._models import ConversationalAnalysisAuthoringProjectDeployment
+from ._models import ConversationalAnalysisAuthoringProjectMetadata
+from ._models import ConversationalAnalysisAuthoringProjectSettings
+from ._models import ConversationalAnalysisAuthoringProjectTrainedModel
+from ._models import ConversationalAnalysisAuthoringResourceMetadata
+from ._models import ConversationalAnalysisAuthoringSubTrainingJobState
+from ._models import ConversationalAnalysisAuthoringSupportedLanguage
+from ._models import ConversationalAnalysisAuthoringSupportedLanguages
+from ._models import ConversationalAnalysisAuthoringSwapDeploymentsOptions
+from ._models import ConversationalAnalysisAuthoringTrainingConfigVersion
+from ._models import ConversationalAnalysisAuthoringTrainingConfigVersions
+from ._models import ConversationalAnalysisAuthoringTrainingJobOptions
+from ._models import ConversationalAnalysisAuthoringTrainingJobResult
+from ._models import ConversationalAnalysisAuthoringTrainingJobState
+from ._models import ConversationalAnalysisAuthoringUnassignDeploymentResourcesOptions
+from ._models import ConversationalAnalysisAuthoringUtteranceEntitiesEvaluationResult
+from ._models import ConversationalAnalysisAuthoringUtteranceEntityEvaluationResult
+from ._models import ConversationalAnalysisAuthoringUtteranceEvaluationResult
+from ._models import ConversationalAnalysisAuthoringUtteranceIntentsEvaluationResult
+from ._models import Error
+from ._models import ErrorResponse
+from ._models import GetAssignDeploymentResourcesStatusResponse
+from ._models import GetCopyProjectStatusResponse
+from ._models import GetDeploymentDeleteFromResourcesStatusResponse
+from ._models import GetDeploymentResponse
+from ._models import GetDeploymentStatusResponse
+from ._models import GetEvaluationStatusResponse
+from ._models import GetExportStatusResponse
+from ._models import GetImportStatusResponse
+from ._models import GetLoadSnapshotStatusResponse
+from ._models import GetProjectDeletionStatusResponse
+from ._models import GetSwapDeploymentsStatusResponse
+from ._models import GetTrainedModelResponse
+from ._models import GetTrainingStatusResponse
+from ._models import GetUnassignDeploymentResourcesStatusResponse
+from ._models import InnerErrorModel
+from ._models import Warning
+
+from ._enums import CompositionSetting
+from ._enums import ErrorCode
+from ._enums import EvaluationKind
+from ._enums import ExportedProjectFormat
+from ._enums import InnerErrorCode
+from ._enums import JobStatus
+from ._enums import OrchestrationTargetProjectKind
+from ._enums import ProjectKind
+from ._enums import StringIndexType
+from ._enums import TrainingMode
+from ._patch import __all__ as _patch_all
+from ._patch import * # pylint: disable=unused-wildcard-import
+from ._patch import patch_sdk as _patch_sdk
+
+__all__ = [
+ "ConversationalAnalysisAuthoringAssignDeploymentResourcesOptions",
+ "ConversationalAnalysisAuthoringAssignedDeploymentResource",
+ "ConversationalAnalysisAuthoringAssignedProjectDeploymentMetadata",
+ "ConversationalAnalysisAuthoringAssignedProjectDeploymentsMetadata",
+ "ConversationalAnalysisAuthoringAssignedResourceDeploymentsMetadata",
+ "ConversationalAnalysisAuthoringConfusionMatrix",
+ "ConversationalAnalysisAuthoringConfusionMatrixCell",
+ "ConversationalAnalysisAuthoringConfusionMatrixRow",
+ "ConversationalAnalysisAuthoringConversationExportedEntity",
+ "ConversationalAnalysisAuthoringConversationExportedIntent",
+ "ConversationalAnalysisAuthoringConversationExportedProjectAssets",
+ "ConversationalAnalysisAuthoringConversationExportedUtterance",
+ "ConversationalAnalysisAuthoringCopyProjectOptions",
+ "ConversationalAnalysisAuthoringCreateDeploymentOptions",
+ "ConversationalAnalysisAuthoringCreateProjectOptions",
+ "ConversationalAnalysisAuthoringDeleteDeploymentOptions",
+ "ConversationalAnalysisAuthoringDeploymentResource",
+ "ConversationalAnalysisAuthoringEntitiesEvaluationSummary",
+ "ConversationalAnalysisAuthoringEntityEvaluationSummary",
+ "ConversationalAnalysisAuthoringEvaluationJobResult",
+ "ConversationalAnalysisAuthoringEvaluationJobState",
+ "ConversationalAnalysisAuthoringEvaluationOptions",
+ "ConversationalAnalysisAuthoringEvaluationSummary",
+ "ConversationalAnalysisAuthoringExportedConversationOrchestration",
+ "ConversationalAnalysisAuthoringExportedConversationOrchestrationOptions",
+ "ConversationalAnalysisAuthoringExportedEntityList",
+ "ConversationalAnalysisAuthoringExportedEntityListSynonym",
+ "ConversationalAnalysisAuthoringExportedEntityRegex",
+ "ConversationalAnalysisAuthoringExportedEntityRegexExpression",
+ "ConversationalAnalysisAuthoringExportedEntitySublist",
+ "ConversationalAnalysisAuthoringExportedLuisOrchestration",
+ "ConversationalAnalysisAuthoringExportedLuisOrchestrationOptions",
+ "ConversationalAnalysisAuthoringExportedOrchestrationOptions",
+ "ConversationalAnalysisAuthoringExportedPrebuiltEntity",
+ "ConversationalAnalysisAuthoringExportedProject",
+ "ConversationalAnalysisAuthoringExportedProjectAssets",
+ "ConversationalAnalysisAuthoringExportedQuestionAnsweringOrchestration",
+ "ConversationalAnalysisAuthoringExportedQuestionAnsweringOrchestrationOptions",
+ "ConversationalAnalysisAuthoringExportedUtteranceEntityLabel",
+ "ConversationalAnalysisAuthoringIntentEvaluationSummary",
+ "ConversationalAnalysisAuthoringIntentsEvaluationSummary",
+ "ConversationalAnalysisAuthoringOrchestrationExportedIntent",
+ "ConversationalAnalysisAuthoringOrchestrationExportedProjectAssets",
+ "ConversationalAnalysisAuthoringOrchestrationExportedUtterance",
+ "ConversationalAnalysisAuthoringPrebuiltEntities",
+ "ConversationalAnalysisAuthoringPrebuiltEntity",
+ "ConversationalAnalysisAuthoringProjectDeployment",
+ "ConversationalAnalysisAuthoringProjectMetadata",
+ "ConversationalAnalysisAuthoringProjectSettings",
+ "ConversationalAnalysisAuthoringProjectTrainedModel",
+ "ConversationalAnalysisAuthoringResourceMetadata",
+ "ConversationalAnalysisAuthoringSubTrainingJobState",
+ "ConversationalAnalysisAuthoringSupportedLanguage",
+ "ConversationalAnalysisAuthoringSupportedLanguages",
+ "ConversationalAnalysisAuthoringSwapDeploymentsOptions",
+ "ConversationalAnalysisAuthoringTrainingConfigVersion",
+ "ConversationalAnalysisAuthoringTrainingConfigVersions",
+ "ConversationalAnalysisAuthoringTrainingJobOptions",
+ "ConversationalAnalysisAuthoringTrainingJobResult",
+ "ConversationalAnalysisAuthoringTrainingJobState",
+ "ConversationalAnalysisAuthoringUnassignDeploymentResourcesOptions",
+ "ConversationalAnalysisAuthoringUtteranceEntitiesEvaluationResult",
+ "ConversationalAnalysisAuthoringUtteranceEntityEvaluationResult",
+ "ConversationalAnalysisAuthoringUtteranceEvaluationResult",
+ "ConversationalAnalysisAuthoringUtteranceIntentsEvaluationResult",
+ "Error",
+ "ErrorResponse",
+ "GetAssignDeploymentResourcesStatusResponse",
+ "GetCopyProjectStatusResponse",
+ "GetDeploymentDeleteFromResourcesStatusResponse",
+ "GetDeploymentResponse",
+ "GetDeploymentStatusResponse",
+ "GetEvaluationStatusResponse",
+ "GetExportStatusResponse",
+ "GetImportStatusResponse",
+ "GetLoadSnapshotStatusResponse",
+ "GetProjectDeletionStatusResponse",
+ "GetSwapDeploymentsStatusResponse",
+ "GetTrainedModelResponse",
+ "GetTrainingStatusResponse",
+ "GetUnassignDeploymentResourcesStatusResponse",
+ "InnerErrorModel",
+ "Warning",
+ "CompositionSetting",
+ "ErrorCode",
+ "EvaluationKind",
+ "ExportedProjectFormat",
+ "InnerErrorCode",
+ "JobStatus",
+ "OrchestrationTargetProjectKind",
+ "ProjectKind",
+ "StringIndexType",
+ "TrainingMode",
+]
+__all__.extend([p for p in _patch_all if p not in __all__]) # pyright: ignore
+_patch_sdk()
diff --git a/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/models/_enums.py b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/models/_enums.py
new file mode 100644
index 000000000000..60d0180a1829
--- /dev/null
+++ b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/models/_enums.py
@@ -0,0 +1,141 @@
+# 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 enum import Enum
+from azure.core import CaseInsensitiveEnumMeta
+
+
+class CompositionSetting(str, Enum, metaclass=CaseInsensitiveEnumMeta):
+ """Type of CompositionSetting."""
+
+ RETURN_LONGEST_OVERLAP = "returnLongestOverlap"
+ """When two or more components are found in the text and overlap, the component
+ with the longest set of characters is returned."""
+ REQUIRE_EXACT_OVERLAP = "requireExactOverlap"
+ """All components must overlap at the exact same characters in the text for the
+ entity to return. If one of the defined components is not matched or predicted,
+ the entity will not return."""
+ SEPARATE_COMPONENTS = "separateComponents"
+ """Every component's match or prediction is returned as a separate instance of the
+ entity."""
+ COMBINE_COMPONENTS = "combineComponents"
+ """When two or more components are found in the text and overlap, the components'
+ spans are merged together into one span combining all of them."""
+
+
+class ErrorCode(str, Enum, metaclass=CaseInsensitiveEnumMeta):
+ """Human-readable error code."""
+
+ INVALID_REQUEST = "InvalidRequest"
+ INVALID_ARGUMENT = "InvalidArgument"
+ UNAUTHORIZED = "Unauthorized"
+ FORBIDDEN = "Forbidden"
+ NOT_FOUND = "NotFound"
+ PROJECT_NOT_FOUND = "ProjectNotFound"
+ OPERATION_NOT_FOUND = "OperationNotFound"
+ AZURE_COGNITIVE_SEARCH_NOT_FOUND = "AzureCognitiveSearchNotFound"
+ AZURE_COGNITIVE_SEARCH_INDEX_NOT_FOUND = "AzureCognitiveSearchIndexNotFound"
+ TOO_MANY_REQUESTS = "TooManyRequests"
+ AZURE_COGNITIVE_SEARCH_THROTTLING = "AzureCognitiveSearchThrottling"
+ AZURE_COGNITIVE_SEARCH_INDEX_LIMIT_REACHED = "AzureCognitiveSearchIndexLimitReached"
+ INTERNAL_SERVER_ERROR = "InternalServerError"
+ SERVICE_UNAVAILABLE = "ServiceUnavailable"
+ TIMEOUT = "Timeout"
+ QUOTA_EXCEEDED = "QuotaExceeded"
+ CONFLICT = "Conflict"
+ WARNING = "Warning"
+
+
+class EvaluationKind(str, Enum, metaclass=CaseInsensitiveEnumMeta):
+ """Type of EvaluationKind."""
+
+ PERCENTAGE = "percentage"
+ """Split the data into training and test sets according to user-defined
+ percentages."""
+ MANUAL = "manual"
+ """Split the data according to the chosen dataset for every example in the data."""
+
+
+class ExportedProjectFormat(str, Enum, metaclass=CaseInsensitiveEnumMeta):
+ """Type of ExportedProjectFormat."""
+
+ CONVERSATION = "Conversation"
+ """Specifies the format for a conversational project."""
+ LUIS = "Luis"
+ """Specifies the format for an application that was exported from LUIS."""
+
+
+class InnerErrorCode(str, Enum, metaclass=CaseInsensitiveEnumMeta):
+ """Human-readable error code."""
+
+ INVALID_REQUEST = "InvalidRequest"
+ INVALID_PARAMETER_VALUE = "InvalidParameterValue"
+ KNOWLEDGE_BASE_NOT_FOUND = "KnowledgeBaseNotFound"
+ AZURE_COGNITIVE_SEARCH_NOT_FOUND = "AzureCognitiveSearchNotFound"
+ AZURE_COGNITIVE_SEARCH_THROTTLING = "AzureCognitiveSearchThrottling"
+ EXTRACTION_FAILURE = "ExtractionFailure"
+ INVALID_REQUEST_BODY_FORMAT = "InvalidRequestBodyFormat"
+ EMPTY_REQUEST = "EmptyRequest"
+ MISSING_INPUT_DOCUMENTS = "MissingInputDocuments"
+ INVALID_DOCUMENT = "InvalidDocument"
+ MODEL_VERSION_INCORRECT = "ModelVersionIncorrect"
+ INVALID_DOCUMENT_BATCH = "InvalidDocumentBatch"
+ UNSUPPORTED_LANGUAGE_CODE = "UnsupportedLanguageCode"
+ INVALID_COUNTRY_HINT = "InvalidCountryHint"
+
+
+class JobStatus(str, Enum, metaclass=CaseInsensitiveEnumMeta):
+ """Type of JobStatus."""
+
+ NOT_STARTED = "notStarted"
+ RUNNING = "running"
+ SUCCEEDED = "succeeded"
+ FAILED = "failed"
+ CANCELLED = "cancelled"
+ CANCELLING = "cancelling"
+ PARTIALLY_COMPLETED = "partiallyCompleted"
+
+
+class OrchestrationTargetProjectKind(str, Enum, metaclass=CaseInsensitiveEnumMeta):
+ """Type of OrchestrationTargetProjectKind."""
+
+ LUIS = "Luis"
+ CONVERSATION = "Conversation"
+ QUESTION_ANSWERING = "QuestionAnswering"
+
+
+class ProjectKind(str, Enum, metaclass=CaseInsensitiveEnumMeta):
+ """Type of ProjectKind."""
+
+ CONVERSATION = "Conversation"
+ """A project to build natural language into apps, bots, and IoT devices."""
+ ORCHESTRATION = "Orchestration"
+ """A project to connect and orchestrate Conversation, Custom question answering and LUIS projects
+ together in one single project."""
+ CUSTOM_CONVERSATION_SUMMARIZATION = "CustomConversationSummarization"
+ """A project to build conversation summarization models which are able to summarize long
+ conversations."""
+
+
+class StringIndexType(str, Enum, metaclass=CaseInsensitiveEnumMeta):
+ """Type of StringIndexType."""
+
+ UTF16_CODE_UNIT = "Utf16CodeUnit"
+ """The offset and length values will correspond to UTF-16 code units. Use this
+ option if your application is written in a language that support Unicode, for
+ example Java, JavaScript."""
+
+
+class TrainingMode(str, Enum, metaclass=CaseInsensitiveEnumMeta):
+ """Type of TrainingMode."""
+
+ ADVANCED = "advanced"
+ """Trains using fine-tuned neural network transformer models. Can train
+ multilingual projects."""
+ STANDARD = "standard"
+ """Faster training times for quicker iterations."""
diff --git a/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/models/_models.py b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/models/_models.py
new file mode 100644
index 000000000000..a1ee8f9eca32
--- /dev/null
+++ b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/models/_models.py
@@ -0,0 +1,3876 @@
+# pylint: disable=too-many-lines
+# 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 datetime
+from typing import Any, Dict, List, Literal, Mapping, Optional, TYPE_CHECKING, Union, overload
+
+from .. import _model_base
+from .._model_base import rest_discriminator, rest_field
+from ._enums import OrchestrationTargetProjectKind, ProjectKind
+
+if TYPE_CHECKING:
+ from .. import models as _models
+
+
+class ConversationalAnalysisAuthoringAssignDeploymentResourcesOptions(
+ _model_base.Model
+): # pylint: disable=name-too-long
+ """Represents the options for assigning Azure resources to a project.
+
+ All required parameters must be populated in order to send to server.
+
+ :ivar resources_metadata: Represents the metadata for the resources to be assigned. Required.
+ :vartype resources_metadata:
+ list[~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringResourceMetadata]
+ """
+
+ resources_metadata: List["_models.ConversationalAnalysisAuthoringResourceMetadata"] = rest_field(
+ name="resourcesMetadata"
+ )
+ """Represents the metadata for the resources to be assigned. Required."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ resources_metadata: List["_models.ConversationalAnalysisAuthoringResourceMetadata"],
+ ) -> 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 ConversationalAnalysisAuthoringAssignedDeploymentResource(_model_base.Model): # pylint: disable=name-too-long
+ """Represents the assigned deployment resource.
+
+
+ :ivar azure_resource_id: The resource ID. Required.
+ :vartype azure_resource_id: str
+ :ivar region: The resource region. Required.
+ :vartype region: str
+ """
+
+ azure_resource_id: str = rest_field(name="azureResourceId")
+ """The resource ID. Required."""
+ region: str = rest_field()
+ """The resource region. Required."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ azure_resource_id: str,
+ region: str,
+ ) -> 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 ConversationalAnalysisAuthoringAssignedProjectDeploymentMetadata(
+ _model_base.Model
+): # pylint: disable=name-too-long
+ """Represents the metadata for an assigned deployment.
+
+
+ :ivar deployment_name: Represents the deployment name. Required.
+ :vartype deployment_name: str
+ :ivar last_deployed_date_time: Represents deployment last deployed time. Required.
+ :vartype last_deployed_date_time: ~datetime.datetime
+ :ivar deployment_expiration_date: Represents deployment expiration date in the runtime.
+ Required.
+ :vartype deployment_expiration_date: ~datetime.date
+ """
+
+ deployment_name: str = rest_field(name="deploymentName")
+ """Represents the deployment name. Required."""
+ last_deployed_date_time: datetime.datetime = rest_field(name="lastDeployedDateTime", format="rfc3339")
+ """Represents deployment last deployed time. Required."""
+ deployment_expiration_date: datetime.date = rest_field(name="deploymentExpirationDate")
+ """Represents deployment expiration date in the runtime. Required."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ deployment_name: str,
+ last_deployed_date_time: datetime.datetime,
+ deployment_expiration_date: datetime.date,
+ ) -> 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 ConversationalAnalysisAuthoringAssignedProjectDeploymentsMetadata(
+ _model_base.Model
+): # pylint: disable=name-too-long
+ """Represents the metadata for assigned deployments for a project.
+
+
+ :ivar project_name: Represents the project name. Required.
+ :vartype project_name: str
+ :ivar deployments_metadata: Represents the resource region. Required.
+ :vartype deployments_metadata:
+ list[~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringAssignedProjectDeploymentMetadata] # pylint: disable=line-too-long
+ """
+
+ project_name: str = rest_field(name="projectName")
+ """Represents the project name. Required."""
+ deployments_metadata: List["_models.ConversationalAnalysisAuthoringAssignedProjectDeploymentMetadata"] = rest_field(
+ name="deploymentsMetadata"
+ )
+ """Represents the resource region. Required."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ project_name: str,
+ deployments_metadata: List["_models.ConversationalAnalysisAuthoringAssignedProjectDeploymentMetadata"],
+ ) -> 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 ConversationalAnalysisAuthoringAssignedResourceDeploymentsMetadata(
+ _model_base.Model
+): # pylint: disable=name-too-long
+ """Represents the metadata for deployments assigned to a resource.
+
+
+ :ivar value: The list of retrieved assigned project deployments. Required.
+ :vartype value:
+ list[~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringAssignedProjectDeploymentsMetadata] # pylint: disable=line-too-long
+ :ivar next_link: The next page link.
+ :vartype next_link: str
+ """
+
+ value: List["_models.ConversationalAnalysisAuthoringAssignedProjectDeploymentsMetadata"] = rest_field()
+ """The list of retrieved assigned project deployments. Required."""
+ next_link: Optional[str] = rest_field(name="nextLink")
+ """The next page link."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ value: List["_models.ConversationalAnalysisAuthoringAssignedProjectDeploymentsMetadata"],
+ next_link: 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: # pylint: disable=useless-super-delegation
+ super().__init__(*args, **kwargs)
+
+
+class ConversationalAnalysisAuthoringConfusionMatrix(_model_base.Model): # pylint: disable=name-too-long
+ """ConversationalAnalysisAuthoringConfusionMatrix."""
+
+
+class ConversationalAnalysisAuthoringConfusionMatrixCell(_model_base.Model): # pylint: disable=name-too-long
+ """Represents a cell in a confusion matrix.
+
+
+ :ivar normalized_value: Represents normalized value in percentages. Required.
+ :vartype normalized_value: float
+ :ivar raw_value: Represents raw value. Required.
+ :vartype raw_value: float
+ """
+
+ normalized_value: float = rest_field(name="normalizedValue")
+ """Represents normalized value in percentages. Required."""
+ raw_value: float = rest_field(name="rawValue")
+ """Represents raw value. Required."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ normalized_value: float,
+ raw_value: float,
+ ) -> 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 ConversationalAnalysisAuthoringConfusionMatrixRow(_model_base.Model): # pylint: disable=name-too-long
+ """ConversationalAnalysisAuthoringConfusionMatrixRow."""
+
+
+class ConversationalAnalysisAuthoringConversationExportedEntity(_model_base.Model): # pylint: disable=name-too-long
+ """Represents an entity with its components.
+
+ All required parameters must be populated in order to send to server.
+
+ :ivar category: The category of the entity. Required.
+ :vartype category: str
+ :ivar composition_setting: The behavior to follow when the entity's components overlap with
+ each other. Known values are: "returnLongestOverlap", "requireExactOverlap",
+ "separateComponents", and "combineComponents".
+ :vartype composition_setting: str or
+ ~azure.ai.language.authoring.analyzeconversations.models.CompositionSetting
+ :ivar list: The list component of the entity.
+ :vartype list:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringExportedEntityList
+ :ivar prebuilts: The prebuilt entities components.
+ :vartype prebuilts:
+ list[~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringExportedPrebuiltEntity] # pylint: disable=line-too-long
+ :ivar regex: The regex component of the entity.
+ :vartype regex:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringExportedEntityRegex
+ :ivar required_components: The required components. Allowed values are 'learned', 'list',
+ 'prebuilts' and 'regex'.
+ :vartype required_components: list[str]
+ """
+
+ category: str = rest_field()
+ """The category of the entity. Required."""
+ composition_setting: Optional[Union[str, "_models.CompositionSetting"]] = rest_field(name="compositionSetting")
+ """The behavior to follow when the entity's components overlap with each other. Known values are:
+ \"returnLongestOverlap\", \"requireExactOverlap\", \"separateComponents\", and
+ \"combineComponents\"."""
+ list: Optional["_models.ConversationalAnalysisAuthoringExportedEntityList"] = rest_field()
+ """The list component of the entity."""
+ prebuilts: Optional[List["_models.ConversationalAnalysisAuthoringExportedPrebuiltEntity"]] = rest_field()
+ """The prebuilt entities components."""
+ regex: Optional["_models.ConversationalAnalysisAuthoringExportedEntityRegex"] = rest_field()
+ """The regex component of the entity."""
+ required_components: Optional[List[str]] = rest_field(name="requiredComponents")
+ """The required components. Allowed values are 'learned', 'list', 'prebuilts' and 'regex'."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ category: str,
+ composition_setting: Optional[Union[str, "_models.CompositionSetting"]] = None,
+ list: Optional["_models.ConversationalAnalysisAuthoringExportedEntityList"] = None,
+ prebuilts: Optional[List["_models.ConversationalAnalysisAuthoringExportedPrebuiltEntity"]] = None,
+ regex: Optional["_models.ConversationalAnalysisAuthoringExportedEntityRegex"] = None,
+ required_components: Optional[List[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: # pylint: disable=useless-super-delegation
+ super().__init__(*args, **kwargs)
+
+
+class ConversationalAnalysisAuthoringConversationExportedIntent(_model_base.Model): # pylint: disable=name-too-long
+ """Represents an exported intent of a conversational project.
+
+ All required parameters must be populated in order to send to server.
+
+ :ivar category: The intent category. Required.
+ :vartype category: str
+ """
+
+ category: str = rest_field()
+ """The intent category. Required."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ category: str,
+ ) -> 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 ConversationalAnalysisAuthoringExportedProjectAssets(_model_base.Model): # pylint: disable=name-too-long
+ """Represents the assets of an exported project.
+
+ You probably want to use the sub-classes and not this class directly. Known sub-classes are:
+ ConversationalAnalysisAuthoringConversationExportedProjectAssets,
+ ConversationalAnalysisAuthoringOrchestrationExportedProjectAssets
+
+ All required parameters must be populated in order to send to server.
+
+ :ivar project_kind: The type of project containing the assets. Required. Known values are:
+ "Conversation", "Orchestration", and "CustomConversationSummarization".
+ :vartype project_kind: str or
+ ~azure.ai.language.authoring.analyzeconversations.models.ProjectKind
+ """
+
+ __mapping__: Dict[str, _model_base.Model] = {}
+ project_kind: str = rest_discriminator(name="projectKind")
+ """The type of project containing the assets. Required. Known values are: \"Conversation\",
+ \"Orchestration\", and \"CustomConversationSummarization\"."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ project_kind: str,
+ ) -> 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 ConversationalAnalysisAuthoringConversationExportedProjectAssets(
+ ConversationalAnalysisAuthoringExportedProjectAssets, discriminator="Conversation"
+): # pylint: disable=name-too-long
+ """Represents the exported assets of a conversational project.
+
+ All required parameters must be populated in order to send to server.
+
+ :ivar intents: The intents defined in the project.
+ :vartype intents:
+ list[~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringConversationExportedIntent] # pylint: disable=line-too-long
+ :ivar entities: The entities defined in the project.
+ :vartype entities:
+ list[~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringConversationExportedEntity] # pylint: disable=line-too-long
+ :ivar utterances: The utterances defined in the project.
+ :vartype utterances:
+ list[~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringConversationExportedUtterance] # pylint: disable=line-too-long
+ :ivar project_kind: The type of project containing the assets. Required. A project to build
+ natural language into apps, bots, and IoT devices.
+ :vartype project_kind: str or
+ ~azure.ai.language.authoring.analyzeconversations.models.CONVERSATION
+ """
+
+ intents: Optional[List["_models.ConversationalAnalysisAuthoringConversationExportedIntent"]] = rest_field()
+ """The intents defined in the project."""
+ entities: Optional[List["_models.ConversationalAnalysisAuthoringConversationExportedEntity"]] = rest_field()
+ """The entities defined in the project."""
+ utterances: Optional[List["_models.ConversationalAnalysisAuthoringConversationExportedUtterance"]] = rest_field()
+ """The utterances defined in the project."""
+ project_kind: Literal[ProjectKind.CONVERSATION] = rest_discriminator(name="projectKind") # type: ignore
+ """The type of project containing the assets. Required. A project to build natural language into
+ apps, bots, and IoT devices."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ intents: Optional[List["_models.ConversationalAnalysisAuthoringConversationExportedIntent"]] = None,
+ entities: Optional[List["_models.ConversationalAnalysisAuthoringConversationExportedEntity"]] = None,
+ utterances: Optional[List["_models.ConversationalAnalysisAuthoringConversationExportedUtterance"]] = 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, project_kind=ProjectKind.CONVERSATION, **kwargs)
+
+
+class ConversationalAnalysisAuthoringConversationExportedUtterance(_model_base.Model): # pylint: disable=name-too-long
+ """Represents an exported utterance for a conversational project.
+
+ All required parameters must be populated in order to send to server.
+
+ :ivar entities: Represents the entity labels of the utterance.
+ :vartype entities:
+ list[~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringExportedUtteranceEntityLabel] # pylint: disable=line-too-long
+ :ivar text: The utterance text. Required.
+ :vartype text: str
+ :ivar language: Represents the utterance's language. This is BCP-47 representation of a
+ language. For example, use "en" for English, "en-gb" for English (UK), "es" for
+ Spanish etc.
+ :vartype language: str
+ :ivar intent: The intent of the utterance. Required.
+ :vartype intent: str
+ :ivar dataset: The dataset for this utterance. Allowed values are 'Train' and 'Test'.
+ :vartype dataset: str
+ """
+
+ entities: Optional[List["_models.ConversationalAnalysisAuthoringExportedUtteranceEntityLabel"]] = rest_field()
+ """Represents the entity labels of the utterance."""
+ text: str = rest_field()
+ """The utterance text. Required."""
+ language: Optional[str] = rest_field()
+ """Represents the utterance's language. This is BCP-47 representation of a
+ language. For example, use \"en\" for English, \"en-gb\" for English (UK), \"es\" for
+ Spanish etc."""
+ intent: str = rest_field()
+ """The intent of the utterance. Required."""
+ dataset: Optional[str] = rest_field()
+ """The dataset for this utterance. Allowed values are 'Train' and 'Test'."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ text: str,
+ intent: str,
+ entities: Optional[List["_models.ConversationalAnalysisAuthoringExportedUtteranceEntityLabel"]] = None,
+ language: Optional[str] = None,
+ dataset: 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: # pylint: disable=useless-super-delegation
+ super().__init__(*args, **kwargs)
+
+
+class ConversationalAnalysisAuthoringCopyProjectOptions(_model_base.Model): # pylint: disable=name-too-long
+ """Represents the options for copying an existing project to another Azure
+ resource.
+
+
+ :ivar project_kind: Represents the project kind. Required. Known values are: "Conversation",
+ "Orchestration", and "CustomConversationSummarization".
+ :vartype project_kind: str or
+ ~azure.ai.language.authoring.analyzeconversations.models.ProjectKind
+ :ivar target_project_name: The project name to be copied-into. Required.
+ :vartype target_project_name: str
+ :ivar access_token: The access token. Required.
+ :vartype access_token: str
+ :ivar expires_at: The expiration of the access token. Required.
+ :vartype expires_at: ~datetime.datetime
+ :ivar target_resource_id: Represents the target Azure resource ID. Required.
+ :vartype target_resource_id: str
+ :ivar target_resource_region: Represents the target Azure resource region. Required.
+ :vartype target_resource_region: str
+ """
+
+ project_kind: Union[str, "_models.ProjectKind"] = rest_field(name="projectKind")
+ """Represents the project kind. Required. Known values are: \"Conversation\", \"Orchestration\",
+ and \"CustomConversationSummarization\"."""
+ target_project_name: str = rest_field(name="targetProjectName")
+ """The project name to be copied-into. Required."""
+ access_token: str = rest_field(name="accessToken")
+ """The access token. Required."""
+ expires_at: datetime.datetime = rest_field(name="expiresAt", format="rfc3339")
+ """The expiration of the access token. Required."""
+ target_resource_id: str = rest_field(name="targetResourceId")
+ """Represents the target Azure resource ID. Required."""
+ target_resource_region: str = rest_field(name="targetResourceRegion")
+ """Represents the target Azure resource region. Required."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ project_kind: Union[str, "_models.ProjectKind"],
+ target_project_name: str,
+ access_token: str,
+ expires_at: datetime.datetime,
+ target_resource_id: str,
+ target_resource_region: str,
+ ) -> 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 ConversationalAnalysisAuthoringCreateDeploymentOptions(_model_base.Model): # pylint: disable=name-too-long
+ """Represents the options for creating or updating a project deployment.
+
+ All required parameters must be populated in order to send to server.
+
+ :ivar trained_model_label: Represents the trained model label. Required.
+ :vartype trained_model_label: str
+ :ivar assigned_resource_ids: Represents the resource IDs to be assigned to the deployment.
+ If provided, the deployment will be rolled out to the resources
+ provided here as well as the original resource in which the project is created.
+ :vartype assigned_resource_ids: list[str]
+ """
+
+ trained_model_label: str = rest_field(name="trainedModelLabel")
+ """Represents the trained model label. Required."""
+ assigned_resource_ids: Optional[List[str]] = rest_field(name="assignedResourceIds")
+ """Represents the resource IDs to be assigned to the deployment.
+ If provided, the deployment will be rolled out to the resources
+ provided here as well as the original resource in which the project is created."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ trained_model_label: str,
+ assigned_resource_ids: Optional[List[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: # pylint: disable=useless-super-delegation
+ super().__init__(*args, **kwargs)
+
+
+class ConversationalAnalysisAuthoringCreateProjectOptions(_model_base.Model): # pylint: disable=name-too-long
+ """Represents the options used to create or update a project.
+
+ All required parameters must be populated in order to send to server.
+
+ :ivar project_kind: Represents the project kind. Required. Known values are: "Conversation",
+ "Orchestration", and "CustomConversationSummarization".
+ :vartype project_kind: str or
+ ~azure.ai.language.authoring.analyzeconversations.models.ProjectKind
+ :ivar settings: The project settings.
+ :vartype settings:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringProjectSettings
+ :ivar storage_input_container_name: The storage container name in case of conversation
+ summarization.
+ :vartype storage_input_container_name: str
+ :ivar project_name: The new project name. Required.
+ :vartype project_name: str
+ :ivar multilingual: Whether the project would be used for multiple languages or not.
+ :vartype multilingual: bool
+ :ivar description: The project description.
+ :vartype description: str
+ :ivar language: The project language. This is BCP-47 representation of a language. For example,
+ use "en" for English, "en-gb" for English (UK), "es" for Spanish etc. Required.
+ :vartype language: str
+ """
+
+ project_kind: Union[str, "_models.ProjectKind"] = rest_field(name="projectKind")
+ """Represents the project kind. Required. Known values are: \"Conversation\", \"Orchestration\",
+ and \"CustomConversationSummarization\"."""
+ settings: Optional["_models.ConversationalAnalysisAuthoringProjectSettings"] = rest_field()
+ """The project settings."""
+ storage_input_container_name: Optional[str] = rest_field(name="storageInputContainerName")
+ """The storage container name in case of conversation summarization."""
+ project_name: str = rest_field(name="projectName")
+ """The new project name. Required."""
+ multilingual: Optional[bool] = rest_field()
+ """Whether the project would be used for multiple languages or not."""
+ description: Optional[str] = rest_field()
+ """The project description."""
+ language: str = rest_field()
+ """The project language. This is BCP-47 representation of a language. For example, use \"en\" for
+ English, \"en-gb\" for English (UK), \"es\" for Spanish etc. Required."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ project_kind: Union[str, "_models.ProjectKind"],
+ project_name: str,
+ language: str,
+ settings: Optional["_models.ConversationalAnalysisAuthoringProjectSettings"] = None,
+ storage_input_container_name: Optional[str] = None,
+ multilingual: Optional[bool] = None,
+ description: 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: # pylint: disable=useless-super-delegation
+ super().__init__(*args, **kwargs)
+
+
+class ConversationalAnalysisAuthoringDeleteDeploymentOptions(_model_base.Model): # pylint: disable=name-too-long
+ """Represents the options for deleting a project deployment.
+
+ :ivar assigned_resource_ids: Represents the resource IDs to delete the deployment from.
+ If not provided, the deployment will be rolled out from all the
+ resources it is deployed to.
+ If provided, it will delete the deployment only from the specified
+ assigned resources, and leave it for the rest.
+ :vartype assigned_resource_ids: list[str]
+ """
+
+ assigned_resource_ids: Optional[List[str]] = rest_field(name="assignedResourceIds")
+ """Represents the resource IDs to delete the deployment from.
+ If not provided, the deployment will be rolled out from all the
+ resources it is deployed to.
+ If provided, it will delete the deployment only from the specified
+ assigned resources, and leave it for the rest."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ assigned_resource_ids: Optional[List[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: # pylint: disable=useless-super-delegation
+ super().__init__(*args, **kwargs)
+
+
+class ConversationalAnalysisAuthoringDeploymentResource(_model_base.Model): # pylint: disable=name-too-long
+ """Represents an Azure resource assigned to a deployment.
+
+
+ :ivar resource_id: Represents the Azure resource Id. Required.
+ :vartype resource_id: str
+ :ivar region: Represents the resource region. Required.
+ :vartype region: str
+ """
+
+ resource_id: str = rest_field(name="resourceId")
+ """Represents the Azure resource Id. Required."""
+ region: str = rest_field()
+ """Represents the resource region. Required."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ resource_id: str,
+ region: str,
+ ) -> 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 ConversationalAnalysisAuthoringEntitiesEvaluationSummary(_model_base.Model): # pylint: disable=name-too-long
+ """Represents the evaluation result summary for the project's entities.
+
+
+ :ivar confusion_matrix: Represents the confusion matrix between two entities (the two entities
+ can be
+ the same). The matrix is between the entity that was labelled and the entity
+ that was predicted. Required.
+ :vartype confusion_matrix:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringConfusionMatrix
+ :ivar entities: Represents the entities evaluation summary. Required.
+ :vartype entities: dict[str,
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringEntityEvaluationSummary]
+ :ivar micro_f1: Represents the micro F1. Expected value is a float between 0 and 1 inclusive.
+ Required.
+ :vartype micro_f1: float
+ :ivar micro_precision: Represents the micro precision. Expected value is a float between 0 and
+ 1
+ inclusive. Required.
+ :vartype micro_precision: float
+ :ivar micro_recall: Represents the micro recall. Expected value is a float between 0 and 1
+ inclusive. Required.
+ :vartype micro_recall: float
+ :ivar macro_f1: Represents the macro F1. Expected value is a float between 0 and 1 inclusive.
+ Required.
+ :vartype macro_f1: float
+ :ivar macro_precision: Represents the macro precision. Expected value is a float between 0 and
+ 1
+ inclusive. Required.
+ :vartype macro_precision: float
+ :ivar macro_recall: Represents the macro recall. Expected value is a float between 0 and 1
+ inclusive. Required.
+ :vartype macro_recall: float
+ """
+
+ confusion_matrix: "_models.ConversationalAnalysisAuthoringConfusionMatrix" = rest_field(name="confusionMatrix")
+ """Represents the confusion matrix between two entities (the two entities can be
+ the same). The matrix is between the entity that was labelled and the entity
+ that was predicted. Required."""
+ entities: Dict[str, "_models.ConversationalAnalysisAuthoringEntityEvaluationSummary"] = rest_field()
+ """Represents the entities evaluation summary. Required."""
+ micro_f1: float = rest_field(name="microF1")
+ """Represents the micro F1. Expected value is a float between 0 and 1 inclusive. Required."""
+ micro_precision: float = rest_field(name="microPrecision")
+ """Represents the micro precision. Expected value is a float between 0 and 1
+ inclusive. Required."""
+ micro_recall: float = rest_field(name="microRecall")
+ """Represents the micro recall. Expected value is a float between 0 and 1
+ inclusive. Required."""
+ macro_f1: float = rest_field(name="macroF1")
+ """Represents the macro F1. Expected value is a float between 0 and 1 inclusive. Required."""
+ macro_precision: float = rest_field(name="macroPrecision")
+ """Represents the macro precision. Expected value is a float between 0 and 1
+ inclusive. Required."""
+ macro_recall: float = rest_field(name="macroRecall")
+ """Represents the macro recall. Expected value is a float between 0 and 1
+ inclusive. Required."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ confusion_matrix: "_models.ConversationalAnalysisAuthoringConfusionMatrix",
+ entities: Dict[str, "_models.ConversationalAnalysisAuthoringEntityEvaluationSummary"],
+ micro_f1: float,
+ micro_precision: float,
+ micro_recall: float,
+ macro_f1: float,
+ macro_precision: float,
+ macro_recall: float,
+ ) -> 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 ConversationalAnalysisAuthoringEntityEvaluationSummary(_model_base.Model): # pylint: disable=name-too-long
+ """Represents the evaluation result for an entity.
+
+
+ :ivar f1: Represents the model precision. Required.
+ :vartype f1: float
+ :ivar precision: Represents the model recall. Required.
+ :vartype precision: float
+ :ivar recall: Represents the model F1 score. Required.
+ :vartype recall: float
+ :ivar true_positive_count: Represents the count of true positive. Required.
+ :vartype true_positive_count: int
+ :ivar true_negative_count: Represents the count of true negative. Required.
+ :vartype true_negative_count: int
+ :ivar false_positive_count: Represents the count of false positive. Required.
+ :vartype false_positive_count: int
+ :ivar false_negative_count: Represents the count of false negative. Required.
+ :vartype false_negative_count: int
+ """
+
+ f1: float = rest_field()
+ """Represents the model precision. Required."""
+ precision: float = rest_field()
+ """Represents the model recall. Required."""
+ recall: float = rest_field()
+ """Represents the model F1 score. Required."""
+ true_positive_count: int = rest_field(name="truePositiveCount")
+ """Represents the count of true positive. Required."""
+ true_negative_count: int = rest_field(name="trueNegativeCount")
+ """Represents the count of true negative. Required."""
+ false_positive_count: int = rest_field(name="falsePositiveCount")
+ """Represents the count of false positive. Required."""
+ false_negative_count: int = rest_field(name="falseNegativeCount")
+ """Represents the count of false negative. Required."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ f1: float,
+ precision: float,
+ recall: float,
+ true_positive_count: int,
+ true_negative_count: int,
+ false_positive_count: int,
+ false_negative_count: int,
+ ) -> 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 ConversationalAnalysisAuthoringEvaluationJobResult(_model_base.Model): # pylint: disable=name-too-long
+ """ConversationalAnalysisAuthoringEvaluationJobResult.
+
+
+ :ivar evaluation_options: Represents the options used running the evaluation. Required.
+ :vartype evaluation_options:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringEvaluationOptions
+ :ivar model_label: Represents trained model label. Required.
+ :vartype model_label: str
+ :ivar training_config_version: Represents training config version. Required.
+ :vartype training_config_version: str
+ :ivar percent_complete: Represents progress percentage. Required.
+ :vartype percent_complete: int
+ """
+
+ evaluation_options: "_models.ConversationalAnalysisAuthoringEvaluationOptions" = rest_field(
+ name="evaluationOptions"
+ )
+ """Represents the options used running the evaluation. Required."""
+ model_label: str = rest_field(name="modelLabel")
+ """Represents trained model label. Required."""
+ training_config_version: str = rest_field(name="trainingConfigVersion")
+ """Represents training config version. Required."""
+ percent_complete: int = rest_field(name="percentComplete")
+ """Represents progress percentage. Required."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ evaluation_options: "_models.ConversationalAnalysisAuthoringEvaluationOptions",
+ model_label: str,
+ training_config_version: str,
+ percent_complete: int,
+ ) -> 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 ConversationalAnalysisAuthoringEvaluationJobState(_model_base.Model): # pylint: disable=name-too-long
+ """Represents the state of a evaluation job.
+
+
+ :ivar job_id: The job ID. Required.
+ :vartype job_id: str
+ :ivar created_date_time: The creation date time of the job. Required.
+ :vartype created_date_time: ~datetime.datetime
+ :ivar last_updated_date_time: The last date time the job was updated. Required.
+ :vartype last_updated_date_time: ~datetime.datetime
+ :ivar expiration_date_time: The expiration date time of the job.
+ :vartype expiration_date_time: ~datetime.datetime
+ :ivar status: The job status. Required. Known values are: "notStarted", "running", "succeeded",
+ "failed", "cancelled", "cancelling", and "partiallyCompleted".
+ :vartype status: str or ~azure.ai.language.authoring.analyzeconversations.models.JobStatus
+ :ivar warnings: The warnings that were encountered while executing the job.
+ :vartype warnings: list[~azure.ai.language.authoring.analyzeconversations.models.Warning]
+ :ivar errors: The errors encountered while executing the job.
+ :vartype errors: list[~azure.ai.language.authoring.analyzeconversations.models.Error]
+ :ivar result: Represents evaluation task detailed result. Required.
+ :vartype result:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringEvaluationJobResult
+ """
+
+ job_id: str = rest_field(name="jobId")
+ """The job ID. Required."""
+ created_date_time: datetime.datetime = rest_field(name="createdDateTime", format="rfc3339")
+ """The creation date time of the job. Required."""
+ last_updated_date_time: datetime.datetime = rest_field(name="lastUpdatedDateTime", format="rfc3339")
+ """The last date time the job was updated. Required."""
+ expiration_date_time: Optional[datetime.datetime] = rest_field(name="expirationDateTime", format="rfc3339")
+ """The expiration date time of the job."""
+ status: Union[str, "_models.JobStatus"] = rest_field()
+ """The job status. Required. Known values are: \"notStarted\", \"running\", \"succeeded\",
+ \"failed\", \"cancelled\", \"cancelling\", and \"partiallyCompleted\"."""
+ warnings: Optional[List["_models.Warning"]] = rest_field()
+ """The warnings that were encountered while executing the job."""
+ errors: Optional[List["_models.Error"]] = rest_field()
+ """The errors encountered while executing the job."""
+ result: "_models.ConversationalAnalysisAuthoringEvaluationJobResult" = rest_field()
+ """Represents evaluation task detailed result. Required."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ job_id: str,
+ created_date_time: datetime.datetime,
+ last_updated_date_time: datetime.datetime,
+ status: Union[str, "_models.JobStatus"],
+ result: "_models.ConversationalAnalysisAuthoringEvaluationJobResult",
+ expiration_date_time: Optional[datetime.datetime] = None,
+ warnings: Optional[List["_models.Warning"]] = None,
+ errors: Optional[List["_models.Error"]] = 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 ConversationalAnalysisAuthoringEvaluationOptions(_model_base.Model): # pylint: disable=name-too-long
+ """Represents the options used running the evaluation.
+
+ :ivar kind: Represents the evaluation kind. By default, the evaluation kind is set to
+ percentage. Known values are: "percentage" and "manual".
+ :vartype kind: str or ~azure.ai.language.authoring.analyzeconversations.models.EvaluationKind
+ :ivar training_split_percentage: Represents the training dataset split percentage. Only needed
+ in case the
+ evaluation kind is percentage.
+ :vartype training_split_percentage: int
+ :ivar testing_split_percentage: Represents the testing dataset split percentage. Only needed in
+ case the
+ evaluation kind is percentage.
+ :vartype testing_split_percentage: int
+ """
+
+ kind: Optional[Union[str, "_models.EvaluationKind"]] = rest_field()
+ """Represents the evaluation kind. By default, the evaluation kind is set to
+ percentage. Known values are: \"percentage\" and \"manual\"."""
+ training_split_percentage: Optional[int] = rest_field(name="trainingSplitPercentage")
+ """Represents the training dataset split percentage. Only needed in case the
+ evaluation kind is percentage."""
+ testing_split_percentage: Optional[int] = rest_field(name="testingSplitPercentage")
+ """Represents the testing dataset split percentage. Only needed in case the
+ evaluation kind is percentage."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ kind: Optional[Union[str, "_models.EvaluationKind"]] = None,
+ training_split_percentage: Optional[int] = None,
+ testing_split_percentage: Optional[int] = 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 ConversationalAnalysisAuthoringEvaluationSummary(_model_base.Model): # pylint: disable=name-too-long
+ """Represents the evaluation result summary.
+
+
+ :ivar entities_evaluation: Contains the data related to entities evaluation. Required.
+ :vartype entities_evaluation:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringEntitiesEvaluationSummary
+ :ivar intents_evaluation: Contains the data related to intents evaluation. Required.
+ :vartype intents_evaluation:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringIntentsEvaluationSummary
+ :ivar evaluation_options: The options that were used while running the evaluation.
+ :vartype evaluation_options:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringEvaluationOptions
+ """
+
+ entities_evaluation: "_models.ConversationalAnalysisAuthoringEntitiesEvaluationSummary" = rest_field(
+ name="entitiesEvaluation"
+ )
+ """Contains the data related to entities evaluation. Required."""
+ intents_evaluation: "_models.ConversationalAnalysisAuthoringIntentsEvaluationSummary" = rest_field(
+ name="intentsEvaluation"
+ )
+ """Contains the data related to intents evaluation. Required."""
+ evaluation_options: Optional["_models.ConversationalAnalysisAuthoringEvaluationOptions"] = rest_field(
+ name="evaluationOptions"
+ )
+ """The options that were used while running the evaluation."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ entities_evaluation: "_models.ConversationalAnalysisAuthoringEntitiesEvaluationSummary",
+ intents_evaluation: "_models.ConversationalAnalysisAuthoringIntentsEvaluationSummary",
+ evaluation_options: Optional["_models.ConversationalAnalysisAuthoringEvaluationOptions"] = 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 ConversationalAnalysisAuthoringExportedConversationOrchestration(
+ _model_base.Model
+): # pylint: disable=name-too-long
+ """Defines the orchestration details for a Conversational project target.
+
+ All required parameters must be populated in order to send to server.
+
+ :ivar project_name: The name of the targeted project. Required.
+ :vartype project_name: str
+ :ivar deployment_name: The name of the targeted deployment. Required.
+ :vartype deployment_name: str
+ """
+
+ project_name: str = rest_field(name="projectName")
+ """The name of the targeted project. Required."""
+ deployment_name: str = rest_field(name="deploymentName")
+ """The name of the targeted deployment. Required."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ project_name: str,
+ deployment_name: str,
+ ) -> 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 ConversationalAnalysisAuthoringExportedOrchestrationOptions(_model_base.Model): # pylint: disable=name-too-long
+ """Represents the options used to define the orchestration behavior of an intent.
+
+ You probably want to use the sub-classes and not this class directly. Known sub-classes are:
+ ConversationalAnalysisAuthoringExportedConversationOrchestrationOptions,
+ ConversationalAnalysisAuthoringExportedLuisOrchestrationOptions,
+ ConversationalAnalysisAuthoringExportedQuestionAnsweringOrchestrationOptions
+
+ All required parameters must be populated in order to send to server.
+
+ :ivar target_project_kind: Required. Known values are: "Luis", "Conversation", and
+ "QuestionAnswering".
+ :vartype target_project_kind: str or
+ ~azure.ai.language.authoring.analyzeconversations.models.OrchestrationTargetProjectKind
+ """
+
+ __mapping__: Dict[str, _model_base.Model] = {}
+ target_project_kind: str = rest_discriminator(name="targetProjectKind")
+ """Required. Known values are: \"Luis\", \"Conversation\", and \"QuestionAnswering\"."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ target_project_kind: str,
+ ) -> 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 ConversationalAnalysisAuthoringExportedConversationOrchestrationOptions(
+ ConversationalAnalysisAuthoringExportedOrchestrationOptions, discriminator="Conversation"
+): # pylint: disable=name-too-long
+ """Represents the orchestration options for a Conversational project target.
+
+ All required parameters must be populated in order to send to server.
+
+ :ivar conversation_orchestration: The Conversational project target details. Required.
+ :vartype conversation_orchestration:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringExportedConversationOrchestration # pylint: disable=line-too-long
+ :ivar target_project_kind: The kind of the target used in the orchestration flow. Required.
+ :vartype target_project_kind: str or
+ ~azure.ai.language.authoring.analyzeconversations.models.CONVERSATION
+ """
+
+ conversation_orchestration: "_models.ConversationalAnalysisAuthoringExportedConversationOrchestration" = rest_field(
+ name="conversationOrchestration"
+ )
+ """The Conversational project target details. Required."""
+ target_project_kind: Literal[OrchestrationTargetProjectKind.CONVERSATION] = rest_discriminator(name="targetProjectKind") # type: ignore
+ """The kind of the target used in the orchestration flow. Required."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ conversation_orchestration: "_models.ConversationalAnalysisAuthoringExportedConversationOrchestration",
+ ) -> 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, target_project_kind=OrchestrationTargetProjectKind.CONVERSATION, **kwargs)
+
+
+class ConversationalAnalysisAuthoringExportedEntityList(_model_base.Model): # pylint: disable=name-too-long
+ """Represents a list component of an entity.
+
+ :ivar sublists: The sub-lists of the list component.
+ :vartype sublists:
+ list[~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringExportedEntitySublist]
+ """
+
+ sublists: Optional[List["_models.ConversationalAnalysisAuthoringExportedEntitySublist"]] = rest_field()
+ """The sub-lists of the list component."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ sublists: Optional[List["_models.ConversationalAnalysisAuthoringExportedEntitySublist"]] = 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 ConversationalAnalysisAuthoringExportedEntityListSynonym(_model_base.Model): # pylint: disable=name-too-long
+ """Represents a list of synonyms inside a list component.
+
+ :ivar language: Represents the language of the synonyms. This is BCP-47 representation of a
+ language. For example, use "en" for English, "en-gb" for English (UK), "es" for
+ Spanish etc.
+ :vartype language: str
+ :ivar values_property: The list of synonyms.
+ :vartype values_property: list[str]
+ """
+
+ language: Optional[str] = rest_field()
+ """Represents the language of the synonyms. This is BCP-47 representation of a
+ language. For example, use \"en\" for English, \"en-gb\" for English (UK), \"es\" for
+ Spanish etc."""
+ values_property: Optional[List[str]] = rest_field(name="values")
+ """The list of synonyms."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ language: Optional[str] = None,
+ values_property: Optional[List[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: # pylint: disable=useless-super-delegation
+ super().__init__(*args, **kwargs)
+
+
+class ConversationalAnalysisAuthoringExportedEntityRegex(_model_base.Model): # pylint: disable=name-too-long
+ """Represents a regex component of an entity.
+
+ :ivar expressions: The regex expressions of the regex component. These expressions follow the
+ .NET
+ regex syntax. For reference, check here:
+ https://learn.microsoft.com/dotnet/standard/base-types/regular-expressions.
+ :vartype expressions:
+ list[~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringExportedEntityRegexExpression] # pylint: disable=line-too-long
+ """
+
+ expressions: Optional[List["_models.ConversationalAnalysisAuthoringExportedEntityRegexExpression"]] = rest_field()
+ """The regex expressions of the regex component. These expressions follow the .NET
+ regex syntax. For reference, check here:
+ https://learn.microsoft.com/dotnet/standard/base-types/regular-expressions."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ expressions: Optional[List["_models.ConversationalAnalysisAuthoringExportedEntityRegexExpression"]] = 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 ConversationalAnalysisAuthoringExportedEntityRegexExpression(_model_base.Model): # pylint: disable=name-too-long
+ """Represents a regex expression inside a regex component. This expression follows
+ the .NET regex syntax. For reference, check here:
+ https://learn.microsoft.com/dotnet/standard/base-types/regular-expressions.
+
+ :ivar regex_key: The key of the regex expression.
+ :vartype regex_key: str
+ :ivar language: Represents the language of the regex expression. This is BCP-47 representation
+ of a language. For example, use "en" for English, "en-gb" for English (UK),
+ "es" for Spanish etc.
+ :vartype language: str
+ :ivar regex_pattern: The regex pattern.
+ :vartype regex_pattern: str
+ """
+
+ regex_key: Optional[str] = rest_field(name="regexKey")
+ """The key of the regex expression."""
+ language: Optional[str] = rest_field()
+ """Represents the language of the regex expression. This is BCP-47 representation
+ of a language. For example, use \"en\" for English, \"en-gb\" for English (UK),
+ \"es\" for Spanish etc."""
+ regex_pattern: Optional[str] = rest_field(name="regexPattern")
+ """The regex pattern."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ regex_key: Optional[str] = None,
+ language: Optional[str] = None,
+ regex_pattern: 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: # pylint: disable=useless-super-delegation
+ super().__init__(*args, **kwargs)
+
+
+class ConversationalAnalysisAuthoringExportedEntitySublist(_model_base.Model): # pylint: disable=name-too-long
+ """Represents a sub-list inside a list component.
+
+ :ivar list_key: The key of the sub-list.
+ :vartype list_key: str
+ :ivar synonyms: The phrases of that correspond to the sub-list.
+ :vartype synonyms:
+ list[~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringExportedEntityListSynonym] # pylint: disable=line-too-long
+ """
+
+ list_key: Optional[str] = rest_field(name="listKey")
+ """The key of the sub-list."""
+ synonyms: Optional[List["_models.ConversationalAnalysisAuthoringExportedEntityListSynonym"]] = rest_field()
+ """The phrases of that correspond to the sub-list."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ list_key: Optional[str] = None,
+ synonyms: Optional[List["_models.ConversationalAnalysisAuthoringExportedEntityListSynonym"]] = 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 ConversationalAnalysisAuthoringExportedLuisOrchestration(_model_base.Model): # pylint: disable=name-too-long
+ """Defines the orchestration details for a LUIS application target.
+
+ All required parameters must be populated in order to send to server.
+
+ :ivar app_id: The LUIS application ID. Required.
+ :vartype app_id: str
+ :ivar app_version: The targeted version Id.
+ :vartype app_version: str
+ :ivar slot_name: The targeted slot name.
+ :vartype slot_name: str
+ """
+
+ app_id: str = rest_field(name="appId")
+ """The LUIS application ID. Required."""
+ app_version: Optional[str] = rest_field(name="appVersion")
+ """The targeted version Id."""
+ slot_name: Optional[str] = rest_field(name="slotName")
+ """The targeted slot name."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ app_id: str,
+ app_version: Optional[str] = None,
+ slot_name: 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: # pylint: disable=useless-super-delegation
+ super().__init__(*args, **kwargs)
+
+
+class ConversationalAnalysisAuthoringExportedLuisOrchestrationOptions(
+ ConversationalAnalysisAuthoringExportedOrchestrationOptions, discriminator="Luis"
+): # pylint: disable=name-too-long
+ """Represents the orchestration options for a LUIS application target.
+
+ All required parameters must be populated in order to send to server.
+
+ :ivar luis_orchestration: The LUIS application target details. Required.
+ :vartype luis_orchestration:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringExportedLuisOrchestration
+ :ivar target_project_kind: The kind of the target used in the orchestration flow. Required.
+ :vartype target_project_kind: str or
+ ~azure.ai.language.authoring.analyzeconversations.models.LUIS
+ """
+
+ luis_orchestration: "_models.ConversationalAnalysisAuthoringExportedLuisOrchestration" = rest_field(
+ name="luisOrchestration"
+ )
+ """The LUIS application target details. Required."""
+ target_project_kind: Literal[OrchestrationTargetProjectKind.LUIS] = rest_discriminator(name="targetProjectKind") # type: ignore # pylint: disable=line-too-long
+ """The kind of the target used in the orchestration flow. Required."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ luis_orchestration: "_models.ConversationalAnalysisAuthoringExportedLuisOrchestration",
+ ) -> 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, target_project_kind=OrchestrationTargetProjectKind.LUIS, **kwargs)
+
+
+class ConversationalAnalysisAuthoringExportedPrebuiltEntity(_model_base.Model): # pylint: disable=name-too-long
+ """Represents an exported prebuilt entity component.
+
+ All required parameters must be populated in order to send to server.
+
+ :ivar category: The prebuilt entity category. Required.
+ :vartype category: str
+ """
+
+ category: str = rest_field()
+ """The prebuilt entity category. Required."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ category: str,
+ ) -> 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 ConversationalAnalysisAuthoringExportedProject(_model_base.Model): # pylint: disable=name-too-long
+ """Represents an exported project.
+
+ All required parameters must be populated in order to send to server.
+
+ :ivar project_file_version: The version of the exported file. Required.
+ :vartype project_file_version: str
+ :ivar string_index_type: Specifies the method used to interpret string offsets. For additional
+ information see https://aka.ms/text-analytics-offsets. Required. "Utf16CodeUnit"
+ :vartype string_index_type: str or
+ ~azure.ai.language.authoring.analyzeconversations.models.StringIndexType
+ :ivar metadata: Represents the project metadata. Required.
+ :vartype metadata:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringCreateProjectOptions
+ :ivar assets: Represents the project assets.
+ :vartype assets:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringExportedProjectAssets
+ """
+
+ project_file_version: str = rest_field(name="projectFileVersion")
+ """The version of the exported file. Required."""
+ string_index_type: Union[str, "_models.StringIndexType"] = rest_field(name="stringIndexType")
+ """Specifies the method used to interpret string offsets. For additional
+ information see https://aka.ms/text-analytics-offsets. Required. \"Utf16CodeUnit\""""
+ metadata: "_models.ConversationalAnalysisAuthoringCreateProjectOptions" = rest_field()
+ """Represents the project metadata. Required."""
+ assets: Optional["_models.ConversationalAnalysisAuthoringExportedProjectAssets"] = rest_field()
+ """Represents the project assets."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ project_file_version: str,
+ string_index_type: Union[str, "_models.StringIndexType"],
+ metadata: "_models.ConversationalAnalysisAuthoringCreateProjectOptions",
+ assets: Optional["_models.ConversationalAnalysisAuthoringExportedProjectAssets"] = 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 ConversationalAnalysisAuthoringExportedQuestionAnsweringOrchestration(
+ _model_base.Model
+): # pylint: disable=name-too-long
+ """Defines the orchestration details for a Question Answering project target.
+
+ All required parameters must be populated in order to send to server.
+
+ :ivar project_name: The name of the target project. Required.
+ :vartype project_name: str
+ """
+
+ project_name: str = rest_field(name="projectName")
+ """The name of the target project. Required."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ project_name: str,
+ ) -> 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 ConversationalAnalysisAuthoringExportedQuestionAnsweringOrchestrationOptions(
+ ConversationalAnalysisAuthoringExportedOrchestrationOptions, discriminator="QuestionAnswering"
+): # pylint: disable=name-too-long
+ """Represents the orchestration options for a Question Answering project target.
+
+ All required parameters must be populated in order to send to server.
+
+ :ivar question_answering_orchestration: The Question Answering project details. Required.
+ :vartype question_answering_orchestration:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringExportedQuestionAnsweringOrchestration # pylint: disable=line-too-long
+ :ivar target_project_kind: The kind of the target used in the orchestration flow. Required.
+ :vartype target_project_kind: str or
+ ~azure.ai.language.authoring.analyzeconversations.models.QUESTION_ANSWERING
+ """
+
+ question_answering_orchestration: (
+ "_models.ConversationalAnalysisAuthoringExportedQuestionAnsweringOrchestration"
+ ) = rest_field(name="questionAnsweringOrchestration")
+ """The Question Answering project details. Required."""
+ target_project_kind: Literal[OrchestrationTargetProjectKind.QUESTION_ANSWERING] = rest_discriminator(name="targetProjectKind") # type: ignore
+ """The kind of the target used in the orchestration flow. Required."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ question_answering_orchestration: "_models.ConversationalAnalysisAuthoringExportedQuestionAnsweringOrchestration",
+ ) -> 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, target_project_kind=OrchestrationTargetProjectKind.QUESTION_ANSWERING, **kwargs)
+
+
+class ConversationalAnalysisAuthoringExportedUtteranceEntityLabel(_model_base.Model): # pylint: disable=name-too-long
+ """Represents an entity label for an utterance.
+
+ All required parameters must be populated in order to send to server.
+
+ :ivar category: The category of the entity label. Required.
+ :vartype category: str
+ :ivar offset: Start position for the entity text. Required.
+ :vartype offset: int
+ :ivar length: Length for the entity text. Required.
+ :vartype length: int
+ """
+
+ category: str = rest_field()
+ """The category of the entity label. Required."""
+ offset: int = rest_field()
+ """Start position for the entity text. Required."""
+ length: int = rest_field()
+ """Length for the entity text. Required."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ category: str,
+ offset: int,
+ length: int,
+ ) -> 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 ConversationalAnalysisAuthoringIntentEvaluationSummary(_model_base.Model): # pylint: disable=name-too-long
+ """The evaluation summary for an intent.
+
+
+ :ivar f1: Represents the model precision. Required.
+ :vartype f1: float
+ :ivar precision: Represents the model recall. Required.
+ :vartype precision: float
+ :ivar recall: Represents the model F1 score. Required.
+ :vartype recall: float
+ :ivar true_positive_count: Represents the count of true positive. Required.
+ :vartype true_positive_count: int
+ :ivar true_negative_count: Represents the count of true negative. Required.
+ :vartype true_negative_count: int
+ :ivar false_positive_count: Represents the count of false positive. Required.
+ :vartype false_positive_count: int
+ :ivar false_negative_count: Represents the count of false negative. Required.
+ :vartype false_negative_count: int
+ """
+
+ f1: float = rest_field()
+ """Represents the model precision. Required."""
+ precision: float = rest_field()
+ """Represents the model recall. Required."""
+ recall: float = rest_field()
+ """Represents the model F1 score. Required."""
+ true_positive_count: int = rest_field(name="truePositiveCount")
+ """Represents the count of true positive. Required."""
+ true_negative_count: int = rest_field(name="trueNegativeCount")
+ """Represents the count of true negative. Required."""
+ false_positive_count: int = rest_field(name="falsePositiveCount")
+ """Represents the count of false positive. Required."""
+ false_negative_count: int = rest_field(name="falseNegativeCount")
+ """Represents the count of false negative. Required."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ f1: float,
+ precision: float,
+ recall: float,
+ true_positive_count: int,
+ true_negative_count: int,
+ false_positive_count: int,
+ false_negative_count: int,
+ ) -> 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 ConversationalAnalysisAuthoringIntentsEvaluationSummary(_model_base.Model): # pylint: disable=name-too-long
+ """Represents the evaluation summary for the project's intents.
+
+
+ :ivar confusion_matrix: Represents the confusion matrix between two intents (the two intents
+ can be the
+ same). The matrix is between the intent that was labelled and the intent that
+ was predicted. Required.
+ :vartype confusion_matrix:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringConfusionMatrix
+ :ivar intents: Represents the intents evaluation summary. Required.
+ :vartype intents: dict[str,
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringIntentEvaluationSummary]
+ :ivar micro_f1: Represents the micro F1. Expected value is a float between 0 and 1 inclusive.
+ Required.
+ :vartype micro_f1: float
+ :ivar micro_precision: Represents the micro precision. Expected value is a float between 0 and
+ 1
+ inclusive. Required.
+ :vartype micro_precision: float
+ :ivar micro_recall: Represents the micro recall. Expected value is a float between 0 and 1
+ inclusive. Required.
+ :vartype micro_recall: float
+ :ivar macro_f1: Represents the macro F1. Expected value is a float between 0 and 1 inclusive.
+ Required.
+ :vartype macro_f1: float
+ :ivar macro_precision: Represents the macro precision. Expected value is a float between 0 and
+ 1
+ inclusive. Required.
+ :vartype macro_precision: float
+ :ivar macro_recall: Represents the macro recall. Expected value is a float between 0 and 1
+ inclusive. Required.
+ :vartype macro_recall: float
+ """
+
+ confusion_matrix: "_models.ConversationalAnalysisAuthoringConfusionMatrix" = rest_field(name="confusionMatrix")
+ """Represents the confusion matrix between two intents (the two intents can be the
+ same). The matrix is between the intent that was labelled and the intent that
+ was predicted. Required."""
+ intents: Dict[str, "_models.ConversationalAnalysisAuthoringIntentEvaluationSummary"] = rest_field()
+ """Represents the intents evaluation summary. Required."""
+ micro_f1: float = rest_field(name="microF1")
+ """Represents the micro F1. Expected value is a float between 0 and 1 inclusive. Required."""
+ micro_precision: float = rest_field(name="microPrecision")
+ """Represents the micro precision. Expected value is a float between 0 and 1
+ inclusive. Required."""
+ micro_recall: float = rest_field(name="microRecall")
+ """Represents the micro recall. Expected value is a float between 0 and 1
+ inclusive. Required."""
+ macro_f1: float = rest_field(name="macroF1")
+ """Represents the macro F1. Expected value is a float between 0 and 1 inclusive. Required."""
+ macro_precision: float = rest_field(name="macroPrecision")
+ """Represents the macro precision. Expected value is a float between 0 and 1
+ inclusive. Required."""
+ macro_recall: float = rest_field(name="macroRecall")
+ """Represents the macro recall. Expected value is a float between 0 and 1
+ inclusive. Required."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ confusion_matrix: "_models.ConversationalAnalysisAuthoringConfusionMatrix",
+ intents: Dict[str, "_models.ConversationalAnalysisAuthoringIntentEvaluationSummary"],
+ micro_f1: float,
+ micro_precision: float,
+ micro_recall: float,
+ macro_f1: float,
+ macro_precision: float,
+ macro_recall: float,
+ ) -> 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 ConversationalAnalysisAuthoringOrchestrationExportedIntent(_model_base.Model): # pylint: disable=name-too-long
+ """Represents an exported intent for an orchestration project.
+
+ All required parameters must be populated in order to send to server.
+
+ :ivar orchestration: Specifies the behavior of this intent in the orchestration flow.
+ :vartype orchestration:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringExportedOrchestrationOptions # pylint: disable=line-too-long
+ :ivar category: The intent category. Required.
+ :vartype category: str
+ """
+
+ orchestration: Optional["_models.ConversationalAnalysisAuthoringExportedOrchestrationOptions"] = rest_field()
+ """Specifies the behavior of this intent in the orchestration flow."""
+ category: str = rest_field()
+ """The intent category. Required."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ category: str,
+ orchestration: Optional["_models.ConversationalAnalysisAuthoringExportedOrchestrationOptions"] = 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 ConversationalAnalysisAuthoringOrchestrationExportedProjectAssets(
+ ConversationalAnalysisAuthoringExportedProjectAssets, discriminator="Orchestration"
+): # pylint: disable=name-too-long
+ """Represents the assets of an orchestration project.
+
+ All required parameters must be populated in order to send to server.
+
+ :ivar intents: Represents the intents of the project.
+ :vartype intents:
+ list[~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringOrchestrationExportedIntent] # pylint: disable=line-too-long
+ :ivar utterances: Represents the utterances of the project.
+ :vartype utterances:
+ list[~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringOrchestrationExportedUtterance] # pylint: disable=line-too-long
+ :ivar project_kind: The type of project containing the assets. Required. A project to connect
+ and orchestrate Conversation, Custom question answering and LUIS projects together in one
+ single project.
+ :vartype project_kind: str or
+ ~azure.ai.language.authoring.analyzeconversations.models.ORCHESTRATION
+ """
+
+ intents: Optional[List["_models.ConversationalAnalysisAuthoringOrchestrationExportedIntent"]] = rest_field()
+ """Represents the intents of the project."""
+ utterances: Optional[List["_models.ConversationalAnalysisAuthoringOrchestrationExportedUtterance"]] = rest_field()
+ """Represents the utterances of the project."""
+ project_kind: Literal[ProjectKind.ORCHESTRATION] = rest_discriminator(name="projectKind") # type: ignore
+ """The type of project containing the assets. Required. A project to connect and orchestrate
+ Conversation, Custom question answering and LUIS projects together in one single project."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ intents: Optional[List["_models.ConversationalAnalysisAuthoringOrchestrationExportedIntent"]] = None,
+ utterances: Optional[List["_models.ConversationalAnalysisAuthoringOrchestrationExportedUtterance"]] = 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, project_kind=ProjectKind.ORCHESTRATION, **kwargs)
+
+
+class ConversationalAnalysisAuthoringOrchestrationExportedUtterance(_model_base.Model): # pylint: disable=name-too-long
+ """Represents an utterance of an orchestration project.
+
+ All required parameters must be populated in order to send to server.
+
+ :ivar text: The utterance text. Required.
+ :vartype text: str
+ :ivar language: Represents the utterance's language. This is BCP-47 representation of a
+ language. For example, use "en" for English, "en-gb" for English (UK), "es" for
+ Spanish etc.
+ :vartype language: str
+ :ivar intent: The intent of the utterance. Required.
+ :vartype intent: str
+ :ivar dataset: The dataset for this utterance. Allowed values are 'Train' and 'Test'.
+ :vartype dataset: str
+ """
+
+ text: str = rest_field()
+ """The utterance text. Required."""
+ language: Optional[str] = rest_field()
+ """Represents the utterance's language. This is BCP-47 representation of a
+ language. For example, use \"en\" for English, \"en-gb\" for English (UK), \"es\" for
+ Spanish etc."""
+ intent: str = rest_field()
+ """The intent of the utterance. Required."""
+ dataset: Optional[str] = rest_field()
+ """The dataset for this utterance. Allowed values are 'Train' and 'Test'."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ text: str,
+ intent: str,
+ language: Optional[str] = None,
+ dataset: 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: # pylint: disable=useless-super-delegation
+ super().__init__(*args, **kwargs)
+
+
+class ConversationalAnalysisAuthoringPrebuiltEntities(_model_base.Model): # pylint: disable=name-too-long
+ """Represents a list of the retrieved supported prebuilt entities.
+
+
+ :ivar value: The supported prebuilt entities. Required.
+ :vartype value:
+ list[~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringPrebuiltEntity]
+ :ivar next_link: The next page link.
+ :vartype next_link: str
+ """
+
+ value: List["_models.ConversationalAnalysisAuthoringPrebuiltEntity"] = rest_field()
+ """The supported prebuilt entities. Required."""
+ next_link: Optional[str] = rest_field(name="nextLink")
+ """The next page link."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ value: List["_models.ConversationalAnalysisAuthoringPrebuiltEntity"],
+ next_link: 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: # pylint: disable=useless-super-delegation
+ super().__init__(*args, **kwargs)
+
+
+class ConversationalAnalysisAuthoringPrebuiltEntity(_model_base.Model): # pylint: disable=name-too-long
+ """Represents a supported prebuilt entity.
+
+
+ :ivar category: The prebuilt entity category. Required.
+ :vartype category: str
+ :ivar description: The description. Required.
+ :vartype description: str
+ :ivar examples: English examples for the entity. Required.
+ :vartype examples: str
+ """
+
+ category: str = rest_field()
+ """The prebuilt entity category. Required."""
+ description: str = rest_field()
+ """The description. Required."""
+ examples: str = rest_field()
+ """English examples for the entity. Required."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ category: str,
+ description: str,
+ examples: str,
+ ) -> 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 ConversationalAnalysisAuthoringProjectDeployment(_model_base.Model): # pylint: disable=name-too-long
+ """Represents a project deployment.
+
+
+ :ivar deployment_name: Represents deployment name. Required.
+ :vartype deployment_name: str
+ :ivar model_id: Represents deployment modelId. Required.
+ :vartype model_id: str
+ :ivar last_trained_date_time: Represents deployment last trained time. Required.
+ :vartype last_trained_date_time: ~datetime.datetime
+ :ivar last_deployed_date_time: Represents deployment last deployed time. Required.
+ :vartype last_deployed_date_time: ~datetime.datetime
+ :ivar deployment_expiration_date: Represents deployment expiration date in the runtime.
+ Required.
+ :vartype deployment_expiration_date: ~datetime.date
+ :ivar model_training_config_version: Represents model training config version. Required.
+ :vartype model_training_config_version: str
+ :ivar assigned_resources: Represents the metadata of the assigned Azure resources. Required.
+ :vartype assigned_resources:
+ list[~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringDeploymentResource]
+ """
+
+ deployment_name: str = rest_field(name="deploymentName")
+ """Represents deployment name. Required."""
+ model_id: str = rest_field(name="modelId")
+ """Represents deployment modelId. Required."""
+ last_trained_date_time: datetime.datetime = rest_field(name="lastTrainedDateTime", format="rfc3339")
+ """Represents deployment last trained time. Required."""
+ last_deployed_date_time: datetime.datetime = rest_field(name="lastDeployedDateTime", format="rfc3339")
+ """Represents deployment last deployed time. Required."""
+ deployment_expiration_date: datetime.date = rest_field(name="deploymentExpirationDate")
+ """Represents deployment expiration date in the runtime. Required."""
+ model_training_config_version: str = rest_field(name="modelTrainingConfigVersion")
+ """Represents model training config version. Required."""
+ assigned_resources: List["_models.ConversationalAnalysisAuthoringDeploymentResource"] = rest_field(
+ name="assignedResources"
+ )
+ """Represents the metadata of the assigned Azure resources. Required."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ deployment_name: str,
+ model_id: str,
+ last_trained_date_time: datetime.datetime,
+ last_deployed_date_time: datetime.datetime,
+ deployment_expiration_date: datetime.date,
+ model_training_config_version: str,
+ assigned_resources: List["_models.ConversationalAnalysisAuthoringDeploymentResource"],
+ ) -> 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 ConversationalAnalysisAuthoringProjectMetadata(
+ _model_base.Model
+): # pylint: disable=too-many-instance-attributes,name-too-long
+ """Represents the metadata of a project.
+
+
+ :ivar created_date_time: Represents the project creation datetime. Required.
+ :vartype created_date_time: ~datetime.datetime
+ :ivar last_modified_date_time: Represents the project creation datetime. Required.
+ :vartype last_modified_date_time: ~datetime.datetime
+ :ivar last_trained_date_time: Represents the project last trained datetime.
+ :vartype last_trained_date_time: ~datetime.datetime
+ :ivar last_deployed_date_time: Represents the project last deployed datetime.
+ :vartype last_deployed_date_time: ~datetime.datetime
+ :ivar project_kind: Represents the project kind. Required. Known values are: "Conversation",
+ "Orchestration", and "CustomConversationSummarization".
+ :vartype project_kind: str or
+ ~azure.ai.language.authoring.analyzeconversations.models.ProjectKind
+ :ivar settings: The project settings.
+ :vartype settings:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringProjectSettings
+ :ivar storage_input_container_name: The storage container name in case of conversation
+ summarization.
+ :vartype storage_input_container_name: str
+ :ivar project_name: The new project name. Required.
+ :vartype project_name: str
+ :ivar multilingual: Whether the project would be used for multiple languages or not.
+ :vartype multilingual: bool
+ :ivar description: The project description.
+ :vartype description: str
+ :ivar language: The project language. This is BCP-47 representation of a language. For example,
+ use "en" for English, "en-gb" for English (UK), "es" for Spanish etc. Required.
+ :vartype language: str
+ """
+
+ created_date_time: datetime.datetime = rest_field(name="createdDateTime", format="rfc3339")
+ """Represents the project creation datetime. Required."""
+ last_modified_date_time: datetime.datetime = rest_field(name="lastModifiedDateTime", format="rfc3339")
+ """Represents the project creation datetime. Required."""
+ last_trained_date_time: Optional[datetime.datetime] = rest_field(name="lastTrainedDateTime", format="rfc3339")
+ """Represents the project last trained datetime."""
+ last_deployed_date_time: Optional[datetime.datetime] = rest_field(name="lastDeployedDateTime", format="rfc3339")
+ """Represents the project last deployed datetime."""
+ project_kind: Union[str, "_models.ProjectKind"] = rest_field(name="projectKind", visibility=["read", "create"])
+ """Represents the project kind. Required. Known values are: \"Conversation\", \"Orchestration\",
+ and \"CustomConversationSummarization\"."""
+ settings: Optional["_models.ConversationalAnalysisAuthoringProjectSettings"] = rest_field(
+ visibility=["read", "create"]
+ )
+ """The project settings."""
+ storage_input_container_name: Optional[str] = rest_field(
+ name="storageInputContainerName", visibility=["read", "create"]
+ )
+ """The storage container name in case of conversation summarization."""
+ project_name: str = rest_field(name="projectName", visibility=["read", "create"])
+ """The new project name. Required."""
+ multilingual: Optional[bool] = rest_field(visibility=["read", "create"])
+ """Whether the project would be used for multiple languages or not."""
+ description: Optional[str] = rest_field(visibility=["read", "create"])
+ """The project description."""
+ language: str = rest_field(visibility=["read", "create"])
+ """The project language. This is BCP-47 representation of a language. For example, use \"en\" for
+ English, \"en-gb\" for English (UK), \"es\" for Spanish etc. Required."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ created_date_time: datetime.datetime,
+ last_modified_date_time: datetime.datetime,
+ project_kind: Union[str, "_models.ProjectKind"],
+ project_name: str,
+ language: str,
+ last_trained_date_time: Optional[datetime.datetime] = None,
+ last_deployed_date_time: Optional[datetime.datetime] = None,
+ settings: Optional["_models.ConversationalAnalysisAuthoringProjectSettings"] = None,
+ storage_input_container_name: Optional[str] = None,
+ multilingual: Optional[bool] = None,
+ description: 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: # pylint: disable=useless-super-delegation
+ super().__init__(*args, **kwargs)
+
+
+class ConversationalAnalysisAuthoringProjectSettings(_model_base.Model): # pylint: disable=name-too-long
+ """Represents the settings used to define the project behavior.
+
+
+ :ivar confidence_threshold: The threshold of the intent with the highest confidence, at which
+ the prediction will automatically be changed to "None". The value of the threshold should be
+ between 0 and 1 inclusive. Required.
+ :vartype confidence_threshold: float
+ """
+
+ confidence_threshold: float = rest_field(name="confidenceThreshold")
+ """The threshold of the intent with the highest confidence, at which the prediction will
+ automatically be changed to \"None\". The value of the threshold should be between 0 and 1
+ inclusive. Required."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ confidence_threshold: float,
+ ) -> 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 ConversationalAnalysisAuthoringProjectTrainedModel(_model_base.Model): # pylint: disable=name-too-long
+ """Represents a trained model.
+
+
+ :ivar label: The trained model label. Required.
+ :vartype label: str
+ :ivar model_id: The model ID. Required.
+ :vartype model_id: str
+ :ivar last_trained_date_time: The last trained date time of the model. Required.
+ :vartype last_trained_date_time: ~datetime.datetime
+ :ivar last_training_duration_in_seconds: The duration of the model's last training request in
+ seconds. Required.
+ :vartype last_training_duration_in_seconds: int
+ :ivar model_expiration_date: The model expiration date. Required.
+ :vartype model_expiration_date: ~datetime.date
+ :ivar model_training_config_version: The model training config version. Required.
+ :vartype model_training_config_version: str
+ :ivar has_snapshot: The flag to indicate if the trained model has a snapshot ready. Required.
+ :vartype has_snapshot: bool
+ """
+
+ label: str = rest_field()
+ """The trained model label. Required."""
+ model_id: str = rest_field(name="modelId")
+ """The model ID. Required."""
+ last_trained_date_time: datetime.datetime = rest_field(name="lastTrainedDateTime", format="rfc3339")
+ """The last trained date time of the model. Required."""
+ last_training_duration_in_seconds: int = rest_field(name="lastTrainingDurationInSeconds")
+ """The duration of the model's last training request in seconds. Required."""
+ model_expiration_date: datetime.date = rest_field(name="modelExpirationDate")
+ """The model expiration date. Required."""
+ model_training_config_version: str = rest_field(name="modelTrainingConfigVersion")
+ """The model training config version. Required."""
+ has_snapshot: bool = rest_field(name="hasSnapshot")
+ """The flag to indicate if the trained model has a snapshot ready. Required."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ label: str,
+ model_id: str,
+ last_trained_date_time: datetime.datetime,
+ last_training_duration_in_seconds: int,
+ model_expiration_date: datetime.date,
+ model_training_config_version: str,
+ has_snapshot: bool,
+ ) -> 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 ConversationalAnalysisAuthoringResourceMetadata(_model_base.Model): # pylint: disable=name-too-long
+ """Represents metadata for the Azure resource..
+
+ All required parameters must be populated in order to send to server.
+
+ :ivar azure_resource_id: Represents the Azure resource ID. Required.
+ :vartype azure_resource_id: str
+ :ivar custom_domain: Represents the Azure resource custom domain. Required.
+ :vartype custom_domain: str
+ :ivar region: Represents the Azure resource region. Required.
+ :vartype region: str
+ """
+
+ azure_resource_id: str = rest_field(name="azureResourceId")
+ """Represents the Azure resource ID. Required."""
+ custom_domain: str = rest_field(name="customDomain")
+ """Represents the Azure resource custom domain. Required."""
+ region: str = rest_field()
+ """Represents the Azure resource region. Required."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ azure_resource_id: str,
+ custom_domain: str,
+ region: str,
+ ) -> 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 ConversationalAnalysisAuthoringSubTrainingJobState(_model_base.Model): # pylint: disable=name-too-long
+ """Represents the detailed state of a training sub-operation.
+
+
+ :ivar percent_complete: Represents progress percentage. Required.
+ :vartype percent_complete: int
+ :ivar start_date_time: Represents the start date time.
+ :vartype start_date_time: ~datetime.datetime
+ :ivar end_date_time: Represents the end date time.
+ :vartype end_date_time: ~datetime.datetime
+ :ivar status: Represents the status of the sub-operation. Required. Known values are:
+ "notStarted", "running", "succeeded", "failed", "cancelled", "cancelling", and
+ "partiallyCompleted".
+ :vartype status: str or ~azure.ai.language.authoring.analyzeconversations.models.JobStatus
+ """
+
+ percent_complete: int = rest_field(name="percentComplete")
+ """Represents progress percentage. Required."""
+ start_date_time: Optional[datetime.datetime] = rest_field(name="startDateTime", format="rfc3339")
+ """Represents the start date time."""
+ end_date_time: Optional[datetime.datetime] = rest_field(name="endDateTime", format="rfc3339")
+ """Represents the end date time."""
+ status: Union[str, "_models.JobStatus"] = rest_field()
+ """Represents the status of the sub-operation. Required. Known values are: \"notStarted\",
+ \"running\", \"succeeded\", \"failed\", \"cancelled\", \"cancelling\", and
+ \"partiallyCompleted\"."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ percent_complete: int,
+ status: Union[str, "_models.JobStatus"],
+ start_date_time: Optional[datetime.datetime] = None,
+ end_date_time: Optional[datetime.datetime] = 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 ConversationalAnalysisAuthoringSupportedLanguage(_model_base.Model): # pylint: disable=name-too-long
+ """Represents a supported language.
+
+
+ :ivar language_name: The language name. Required.
+ :vartype language_name: str
+ :ivar language_code: The language code. This is BCP-47 representation of a language. For
+ example,
+ "en" for English, "en-gb" for English (UK), "es" for Spanish etc. Required.
+ :vartype language_code: str
+ """
+
+ language_name: str = rest_field(name="languageName")
+ """The language name. Required."""
+ language_code: str = rest_field(name="languageCode")
+ """The language code. This is BCP-47 representation of a language. For example,
+ \"en\" for English, \"en-gb\" for English (UK), \"es\" for Spanish etc. Required."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ language_name: str,
+ language_code: str,
+ ) -> 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 ConversationalAnalysisAuthoringSupportedLanguages(_model_base.Model): # pylint: disable=name-too-long
+ """Represents a list of retrieved languages.
+
+
+ :ivar value: The list of the languages. Required.
+ :vartype value:
+ list[~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringSupportedLanguage]
+ :ivar next_link: The next page link.
+ :vartype next_link: str
+ """
+
+ value: List["_models.ConversationalAnalysisAuthoringSupportedLanguage"] = rest_field()
+ """The list of the languages. Required."""
+ next_link: Optional[str] = rest_field(name="nextLink")
+ """The next page link."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ value: List["_models.ConversationalAnalysisAuthoringSupportedLanguage"],
+ next_link: 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: # pylint: disable=useless-super-delegation
+ super().__init__(*args, **kwargs)
+
+
+class ConversationalAnalysisAuthoringSwapDeploymentsOptions(_model_base.Model): # pylint: disable=name-too-long
+ """Represents the options for swapping two deployments together.
+
+ All required parameters must be populated in order to send to server.
+
+ :ivar first_deployment_name: Represents the first deployment name. Required.
+ :vartype first_deployment_name: str
+ :ivar second_deployment_name: Represents the second deployment name. Required.
+ :vartype second_deployment_name: str
+ """
+
+ first_deployment_name: str = rest_field(name="firstDeploymentName")
+ """Represents the first deployment name. Required."""
+ second_deployment_name: str = rest_field(name="secondDeploymentName")
+ """Represents the second deployment name. Required."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ first_deployment_name: str,
+ second_deployment_name: str,
+ ) -> 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 ConversationalAnalysisAuthoringTrainingConfigVersion(_model_base.Model): # pylint: disable=name-too-long
+ """Represents a training config version.
+
+
+ :ivar training_config_version: Represents the version of the config. Required.
+ :vartype training_config_version: str
+ :ivar model_expiration_date: Represents the training config version expiration date. Required.
+ :vartype model_expiration_date: ~datetime.date
+ """
+
+ training_config_version: str = rest_field(name="trainingConfigVersion")
+ """Represents the version of the config. Required."""
+ model_expiration_date: datetime.date = rest_field(name="modelExpirationDate")
+ """Represents the training config version expiration date. Required."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ training_config_version: str,
+ model_expiration_date: datetime.date,
+ ) -> 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 ConversationalAnalysisAuthoringTrainingConfigVersions(_model_base.Model): # pylint: disable=name-too-long
+ """Represents a list of training config versions.
+
+
+ :ivar value: The list of the training config versions. Required.
+ :vartype value:
+ list[~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringTrainingConfigVersion]
+ :ivar next_link: The next page link.
+ :vartype next_link: str
+ """
+
+ value: List["_models.ConversationalAnalysisAuthoringTrainingConfigVersion"] = rest_field()
+ """The list of the training config versions. Required."""
+ next_link: Optional[str] = rest_field(name="nextLink")
+ """The next page link."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ value: List["_models.ConversationalAnalysisAuthoringTrainingConfigVersion"],
+ next_link: 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: # pylint: disable=useless-super-delegation
+ super().__init__(*args, **kwargs)
+
+
+class ConversationalAnalysisAuthoringTrainingJobOptions(_model_base.Model): # pylint: disable=name-too-long
+ """Represents the options for starting a new training job.
+
+ All required parameters must be populated in order to send to server.
+
+ :ivar model_label: Represents the output model label. Required.
+ :vartype model_label: str
+ :ivar training_config_version: Represents training config version. By default, "latest" value
+ is used which
+ uses the latest released training config version.
+ :vartype training_config_version: str
+ :ivar training_mode: Represents the mode of the training operation. Required. Known values are:
+ "advanced" and "standard".
+ :vartype training_mode: str or
+ ~azure.ai.language.authoring.analyzeconversations.models.TrainingMode
+ :ivar evaluation_options: Represents the evaluation options. By default, the evaluation kind is
+ percentage, with training split percentage as 80, and testing split percentage
+ as 20.
+ :vartype evaluation_options:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringEvaluationOptions
+ """
+
+ model_label: str = rest_field(name="modelLabel")
+ """Represents the output model label. Required."""
+ training_config_version: Optional[str] = rest_field(name="trainingConfigVersion")
+ """Represents training config version. By default, \"latest\" value is used which
+ uses the latest released training config version."""
+ training_mode: Union[str, "_models.TrainingMode"] = rest_field(name="trainingMode")
+ """Represents the mode of the training operation. Required. Known values are: \"advanced\" and
+ \"standard\"."""
+ evaluation_options: Optional["_models.ConversationalAnalysisAuthoringEvaluationOptions"] = rest_field(
+ name="evaluationOptions"
+ )
+ """Represents the evaluation options. By default, the evaluation kind is
+ percentage, with training split percentage as 80, and testing split percentage
+ as 20."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ model_label: str,
+ training_mode: Union[str, "_models.TrainingMode"],
+ training_config_version: Optional[str] = None,
+ evaluation_options: Optional["_models.ConversationalAnalysisAuthoringEvaluationOptions"] = 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 ConversationalAnalysisAuthoringTrainingJobResult(_model_base.Model): # pylint: disable=name-too-long
+ """Represents the output of a training job.
+
+
+ :ivar model_label: Represents trained model label. Required.
+ :vartype model_label: str
+ :ivar training_config_version: Represents training config version. Required.
+ :vartype training_config_version: str
+ :ivar training_mode: Represents the mode of the training operation. Known values are:
+ "advanced" and "standard".
+ :vartype training_mode: str or
+ ~azure.ai.language.authoring.analyzeconversations.models.TrainingMode
+ :ivar training_status: Represents the model training status. Required.
+ :vartype training_status:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringSubTrainingJobState
+ :ivar evaluation_status: Represents model evaluation status.
+ :vartype evaluation_status:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringSubTrainingJobState
+ :ivar estimated_end_date_time: Represents the estimated end date time for training and
+ evaluation.
+ :vartype estimated_end_date_time: ~datetime.datetime
+ """
+
+ model_label: str = rest_field(name="modelLabel")
+ """Represents trained model label. Required."""
+ training_config_version: str = rest_field(name="trainingConfigVersion")
+ """Represents training config version. Required."""
+ training_mode: Optional[Union[str, "_models.TrainingMode"]] = rest_field(name="trainingMode")
+ """Represents the mode of the training operation. Known values are: \"advanced\" and \"standard\"."""
+ training_status: "_models.ConversationalAnalysisAuthoringSubTrainingJobState" = rest_field(name="trainingStatus")
+ """Represents the model training status. Required."""
+ evaluation_status: Optional["_models.ConversationalAnalysisAuthoringSubTrainingJobState"] = rest_field(
+ name="evaluationStatus"
+ )
+ """Represents model evaluation status."""
+ estimated_end_date_time: Optional[datetime.datetime] = rest_field(name="estimatedEndDateTime", format="rfc3339")
+ """Represents the estimated end date time for training and evaluation."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ model_label: str,
+ training_config_version: str,
+ training_status: "_models.ConversationalAnalysisAuthoringSubTrainingJobState",
+ training_mode: Optional[Union[str, "_models.TrainingMode"]] = None,
+ evaluation_status: Optional["_models.ConversationalAnalysisAuthoringSubTrainingJobState"] = None,
+ estimated_end_date_time: Optional[datetime.datetime] = 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 ConversationalAnalysisAuthoringTrainingJobState(_model_base.Model): # pylint: disable=name-too-long
+ """Represents the state of a training job.
+
+
+ :ivar job_id: The job ID. Required.
+ :vartype job_id: str
+ :ivar created_date_time: The creation date time of the job. Required.
+ :vartype created_date_time: ~datetime.datetime
+ :ivar last_updated_date_time: The last date time the job was updated. Required.
+ :vartype last_updated_date_time: ~datetime.datetime
+ :ivar expiration_date_time: The expiration date time of the job.
+ :vartype expiration_date_time: ~datetime.datetime
+ :ivar status: The job status. Required. Known values are: "notStarted", "running", "succeeded",
+ "failed", "cancelled", "cancelling", and "partiallyCompleted".
+ :vartype status: str or ~azure.ai.language.authoring.analyzeconversations.models.JobStatus
+ :ivar warnings: The warnings that were encountered while executing the job.
+ :vartype warnings: list[~azure.ai.language.authoring.analyzeconversations.models.Warning]
+ :ivar errors: The errors encountered while executing the job.
+ :vartype errors: list[~azure.ai.language.authoring.analyzeconversations.models.Error]
+ :ivar result: Represents training tasks detailed result. Required.
+ :vartype result:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringTrainingJobResult
+ """
+
+ job_id: str = rest_field(name="jobId")
+ """The job ID. Required."""
+ created_date_time: datetime.datetime = rest_field(name="createdDateTime", format="rfc3339")
+ """The creation date time of the job. Required."""
+ last_updated_date_time: datetime.datetime = rest_field(name="lastUpdatedDateTime", format="rfc3339")
+ """The last date time the job was updated. Required."""
+ expiration_date_time: Optional[datetime.datetime] = rest_field(name="expirationDateTime", format="rfc3339")
+ """The expiration date time of the job."""
+ status: Union[str, "_models.JobStatus"] = rest_field()
+ """The job status. Required. Known values are: \"notStarted\", \"running\", \"succeeded\",
+ \"failed\", \"cancelled\", \"cancelling\", and \"partiallyCompleted\"."""
+ warnings: Optional[List["_models.Warning"]] = rest_field()
+ """The warnings that were encountered while executing the job."""
+ errors: Optional[List["_models.Error"]] = rest_field()
+ """The errors encountered while executing the job."""
+ result: "_models.ConversationalAnalysisAuthoringTrainingJobResult" = rest_field()
+ """Represents training tasks detailed result. Required."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ job_id: str,
+ created_date_time: datetime.datetime,
+ last_updated_date_time: datetime.datetime,
+ status: Union[str, "_models.JobStatus"],
+ result: "_models.ConversationalAnalysisAuthoringTrainingJobResult",
+ expiration_date_time: Optional[datetime.datetime] = None,
+ warnings: Optional[List["_models.Warning"]] = None,
+ errors: Optional[List["_models.Error"]] = 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 ConversationalAnalysisAuthoringUnassignDeploymentResourcesOptions(
+ _model_base.Model
+): # pylint: disable=name-too-long
+ """Represents the options to unassign Azure resources from a project.
+
+ All required parameters must be populated in order to send to server.
+
+ :ivar assigned_resource_ids: Represents the assigned resource IDs to be unassigned. Required.
+ :vartype assigned_resource_ids: list[str]
+ """
+
+ assigned_resource_ids: List[str] = rest_field(name="assignedResourceIds")
+ """Represents the assigned resource IDs to be unassigned. Required."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ assigned_resource_ids: List[str],
+ ) -> 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 ConversationalAnalysisAuthoringUtteranceEntitiesEvaluationResult(
+ _model_base.Model
+): # pylint: disable=name-too-long
+ """Represents the comparison between the expected and predicted entities for an
+ utterance.
+
+
+ :ivar expected_entities: Represents the expected entity labels. Required.
+ :vartype expected_entities:
+ list[~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringUtteranceEntityEvaluationResult] # pylint: disable=line-too-long
+ :ivar predicted_entities: Represents the predicted entity labels. Required.
+ :vartype predicted_entities:
+ list[~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringUtteranceEntityEvaluationResult] # pylint: disable=line-too-long
+ """
+
+ expected_entities: List["_models.ConversationalAnalysisAuthoringUtteranceEntityEvaluationResult"] = rest_field(
+ name="expectedEntities"
+ )
+ """Represents the expected entity labels. Required."""
+ predicted_entities: List["_models.ConversationalAnalysisAuthoringUtteranceEntityEvaluationResult"] = rest_field(
+ name="predictedEntities"
+ )
+ """Represents the predicted entity labels. Required."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ expected_entities: List["_models.ConversationalAnalysisAuthoringUtteranceEntityEvaluationResult"],
+ predicted_entities: List["_models.ConversationalAnalysisAuthoringUtteranceEntityEvaluationResult"],
+ ) -> 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 ConversationalAnalysisAuthoringUtteranceEntityEvaluationResult(
+ _model_base.Model
+): # pylint: disable=name-too-long
+ """Represents the evaluation output of an entity label or prediction.
+
+
+ :ivar category: Represents the entity category. Required.
+ :vartype category: str
+ :ivar offset: Represents the entity offset index relative to the original text. Required.
+ :vartype offset: int
+ :ivar length: Represents the entity length. Required.
+ :vartype length: int
+ """
+
+ category: str = rest_field()
+ """Represents the entity category. Required."""
+ offset: int = rest_field()
+ """Represents the entity offset index relative to the original text. Required."""
+ length: int = rest_field()
+ """Represents the entity length. Required."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ category: str,
+ offset: int,
+ length: int,
+ ) -> 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 ConversationalAnalysisAuthoringUtteranceEvaluationResult(_model_base.Model): # pylint: disable=name-too-long
+ """Represents the evaluation result for an utterance.
+
+
+ :ivar text: Represents the utterance text. Required.
+ :vartype text: str
+ :ivar language: Represents the utterance language. This is BCP-47 representation of a language.
+ For example, use "en" for English, "en-gb" for English (UK), "es" for Spanish
+ etc. Required.
+ :vartype language: str
+ :ivar entities_result: Represents the entities results for the utterance. Required.
+ :vartype entities_result:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringUtteranceEntitiesEvaluationResult # pylint: disable=line-too-long
+ :ivar intents_result: Represents the intents results for the utterance. Required.
+ :vartype intents_result:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringUtteranceIntentsEvaluationResult # pylint: disable=line-too-long
+ """
+
+ text: str = rest_field()
+ """Represents the utterance text. Required."""
+ language: str = rest_field()
+ """Represents the utterance language. This is BCP-47 representation of a language.
+ For example, use \"en\" for English, \"en-gb\" for English (UK), \"es\" for Spanish
+ etc. Required."""
+ entities_result: "_models.ConversationalAnalysisAuthoringUtteranceEntitiesEvaluationResult" = rest_field(
+ name="entitiesResult"
+ )
+ """Represents the entities results for the utterance. Required."""
+ intents_result: "_models.ConversationalAnalysisAuthoringUtteranceIntentsEvaluationResult" = rest_field(
+ name="intentsResult"
+ )
+ """Represents the intents results for the utterance. Required."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ text: str,
+ language: str,
+ entities_result: "_models.ConversationalAnalysisAuthoringUtteranceEntitiesEvaluationResult",
+ intents_result: "_models.ConversationalAnalysisAuthoringUtteranceIntentsEvaluationResult",
+ ) -> 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 ConversationalAnalysisAuthoringUtteranceIntentsEvaluationResult(
+ _model_base.Model
+): # pylint: disable=name-too-long
+ """Represents the comparison between the expected and the predicted intent for an
+ utterance.
+
+
+ :ivar expected_intent: Represents the utterance's expected intent. Required.
+ :vartype expected_intent: str
+ :ivar predicted_intent: Represents the utterance's predicted intent. Required.
+ :vartype predicted_intent: str
+ """
+
+ expected_intent: str = rest_field(name="expectedIntent")
+ """Represents the utterance's expected intent. Required."""
+ predicted_intent: str = rest_field(name="predictedIntent")
+ """Represents the utterance's predicted intent. Required."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ expected_intent: str,
+ predicted_intent: str,
+ ) -> 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 Error(_model_base.Model):
+ """The error object.
+
+
+ :ivar code: One of a server-defined set of error codes. Required. Known values are:
+ "InvalidRequest", "InvalidArgument", "Unauthorized", "Forbidden", "NotFound",
+ "ProjectNotFound", "OperationNotFound", "AzureCognitiveSearchNotFound",
+ "AzureCognitiveSearchIndexNotFound", "TooManyRequests", "AzureCognitiveSearchThrottling",
+ "AzureCognitiveSearchIndexLimitReached", "InternalServerError", "ServiceUnavailable",
+ "Timeout", "QuotaExceeded", "Conflict", and "Warning".
+ :vartype code: str or ~azure.ai.language.authoring.analyzeconversations.models.ErrorCode
+ :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.language.authoring.analyzeconversations.models.Error]
+ :ivar innererror: An object containing more specific information than the current object about
+ the error.
+ :vartype innererror: ~azure.ai.language.authoring.analyzeconversations.models.InnerErrorModel
+ """
+
+ code: Union[str, "_models.ErrorCode"] = rest_field()
+ """One of a server-defined set of error codes. Required. Known values are: \"InvalidRequest\",
+ \"InvalidArgument\", \"Unauthorized\", \"Forbidden\", \"NotFound\", \"ProjectNotFound\",
+ \"OperationNotFound\", \"AzureCognitiveSearchNotFound\", \"AzureCognitiveSearchIndexNotFound\",
+ \"TooManyRequests\", \"AzureCognitiveSearchThrottling\",
+ \"AzureCognitiveSearchIndexLimitReached\", \"InternalServerError\", \"ServiceUnavailable\",
+ \"Timeout\", \"QuotaExceeded\", \"Conflict\", and \"Warning\"."""
+ 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.InnerErrorModel"] = rest_field()
+ """An object containing more specific information than the current object about
+ the error."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ code: Union[str, "_models.ErrorCode"],
+ message: str,
+ target: Optional[str] = None,
+ details: Optional[List["_models.Error"]] = None,
+ innererror: Optional["_models.InnerErrorModel"] = 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.
+
+
+ :ivar error: The error object. Required.
+ :vartype error: ~azure.ai.language.authoring.analyzeconversations.models.Error
+ """
+
+ error: "_models.Error" = rest_field()
+ """The error object. 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 GetAssignDeploymentResourcesStatusResponse(_model_base.Model): # pylint: disable=name-too-long
+ """GetAssignDeploymentResourcesStatusResponse.
+
+
+ :ivar created_date_time: The creation date time of the job. Required.
+ :vartype created_date_time: ~datetime.datetime
+ :ivar last_updated_date_time: The last date time the job was updated. Required.
+ :vartype last_updated_date_time: ~datetime.datetime
+ :ivar expiration_date_time: The expiration date time of the job.
+ :vartype expiration_date_time: ~datetime.datetime
+ :ivar status: The job status. Required. Known values are: "notStarted", "running", "succeeded",
+ "failed", "cancelled", "cancelling", and "partiallyCompleted".
+ :vartype status: str or ~azure.ai.language.authoring.analyzeconversations.models.JobStatus
+ :ivar warnings: The warnings that were encountered while executing the job.
+ :vartype warnings: list[~azure.ai.language.authoring.analyzeconversations.models.Warning]
+ :ivar errors: The errors encountered while executing the job.
+ :vartype errors: list[~azure.ai.language.authoring.analyzeconversations.models.Error]
+ """
+
+ created_date_time: datetime.datetime = rest_field(name="createdDateTime", format="rfc3339")
+ """The creation date time of the job. Required."""
+ last_updated_date_time: datetime.datetime = rest_field(name="lastUpdatedDateTime", format="rfc3339")
+ """The last date time the job was updated. Required."""
+ expiration_date_time: Optional[datetime.datetime] = rest_field(name="expirationDateTime", format="rfc3339")
+ """The expiration date time of the job."""
+ status: Union[str, "_models.JobStatus"] = rest_field()
+ """The job status. Required. Known values are: \"notStarted\", \"running\", \"succeeded\",
+ \"failed\", \"cancelled\", \"cancelling\", and \"partiallyCompleted\"."""
+ warnings: Optional[List["_models.Warning"]] = rest_field()
+ """The warnings that were encountered while executing the job."""
+ errors: Optional[List["_models.Error"]] = rest_field()
+ """The errors encountered while executing the job."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ created_date_time: datetime.datetime,
+ last_updated_date_time: datetime.datetime,
+ status: Union[str, "_models.JobStatus"],
+ expiration_date_time: Optional[datetime.datetime] = None,
+ warnings: Optional[List["_models.Warning"]] = None,
+ errors: Optional[List["_models.Error"]] = 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 GetCopyProjectStatusResponse(_model_base.Model):
+ """GetCopyProjectStatusResponse.
+
+
+ :ivar created_date_time: The creation date time of the job. Required.
+ :vartype created_date_time: ~datetime.datetime
+ :ivar last_updated_date_time: The last date time the job was updated. Required.
+ :vartype last_updated_date_time: ~datetime.datetime
+ :ivar expiration_date_time: The expiration date time of the job.
+ :vartype expiration_date_time: ~datetime.datetime
+ :ivar status: The job status. Required. Known values are: "notStarted", "running", "succeeded",
+ "failed", "cancelled", "cancelling", and "partiallyCompleted".
+ :vartype status: str or ~azure.ai.language.authoring.analyzeconversations.models.JobStatus
+ :ivar warnings: The warnings that were encountered while executing the job.
+ :vartype warnings: list[~azure.ai.language.authoring.analyzeconversations.models.Warning]
+ :ivar errors: The errors encountered while executing the job.
+ :vartype errors: list[~azure.ai.language.authoring.analyzeconversations.models.Error]
+ """
+
+ created_date_time: datetime.datetime = rest_field(name="createdDateTime", format="rfc3339")
+ """The creation date time of the job. Required."""
+ last_updated_date_time: datetime.datetime = rest_field(name="lastUpdatedDateTime", format="rfc3339")
+ """The last date time the job was updated. Required."""
+ expiration_date_time: Optional[datetime.datetime] = rest_field(name="expirationDateTime", format="rfc3339")
+ """The expiration date time of the job."""
+ status: Union[str, "_models.JobStatus"] = rest_field()
+ """The job status. Required. Known values are: \"notStarted\", \"running\", \"succeeded\",
+ \"failed\", \"cancelled\", \"cancelling\", and \"partiallyCompleted\"."""
+ warnings: Optional[List["_models.Warning"]] = rest_field()
+ """The warnings that were encountered while executing the job."""
+ errors: Optional[List["_models.Error"]] = rest_field()
+ """The errors encountered while executing the job."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ created_date_time: datetime.datetime,
+ last_updated_date_time: datetime.datetime,
+ status: Union[str, "_models.JobStatus"],
+ expiration_date_time: Optional[datetime.datetime] = None,
+ warnings: Optional[List["_models.Warning"]] = None,
+ errors: Optional[List["_models.Error"]] = 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 GetDeploymentDeleteFromResourcesStatusResponse(_model_base.Model): # pylint: disable=name-too-long
+ """GetDeploymentDeleteFromResourcesStatusResponse.
+
+
+ :ivar created_date_time: The creation date time of the job. Required.
+ :vartype created_date_time: ~datetime.datetime
+ :ivar last_updated_date_time: The last date time the job was updated. Required.
+ :vartype last_updated_date_time: ~datetime.datetime
+ :ivar expiration_date_time: The expiration date time of the job.
+ :vartype expiration_date_time: ~datetime.datetime
+ :ivar status: The job status. Required. Known values are: "notStarted", "running", "succeeded",
+ "failed", "cancelled", "cancelling", and "partiallyCompleted".
+ :vartype status: str or ~azure.ai.language.authoring.analyzeconversations.models.JobStatus
+ :ivar warnings: The warnings that were encountered while executing the job.
+ :vartype warnings: list[~azure.ai.language.authoring.analyzeconversations.models.Warning]
+ :ivar errors: The errors encountered while executing the job.
+ :vartype errors: list[~azure.ai.language.authoring.analyzeconversations.models.Error]
+ """
+
+ created_date_time: datetime.datetime = rest_field(name="createdDateTime", format="rfc3339")
+ """The creation date time of the job. Required."""
+ last_updated_date_time: datetime.datetime = rest_field(name="lastUpdatedDateTime", format="rfc3339")
+ """The last date time the job was updated. Required."""
+ expiration_date_time: Optional[datetime.datetime] = rest_field(name="expirationDateTime", format="rfc3339")
+ """The expiration date time of the job."""
+ status: Union[str, "_models.JobStatus"] = rest_field()
+ """The job status. Required. Known values are: \"notStarted\", \"running\", \"succeeded\",
+ \"failed\", \"cancelled\", \"cancelling\", and \"partiallyCompleted\"."""
+ warnings: Optional[List["_models.Warning"]] = rest_field()
+ """The warnings that were encountered while executing the job."""
+ errors: Optional[List["_models.Error"]] = rest_field()
+ """The errors encountered while executing the job."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ created_date_time: datetime.datetime,
+ last_updated_date_time: datetime.datetime,
+ status: Union[str, "_models.JobStatus"],
+ expiration_date_time: Optional[datetime.datetime] = None,
+ warnings: Optional[List["_models.Warning"]] = None,
+ errors: Optional[List["_models.Error"]] = 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 GetDeploymentResponse(_model_base.Model):
+ """GetDeploymentResponse.
+
+
+ :ivar model_id: Represents deployment modelId. Required.
+ :vartype model_id: str
+ :ivar last_trained_date_time: Represents deployment last trained time. Required.
+ :vartype last_trained_date_time: ~datetime.datetime
+ :ivar last_deployed_date_time: Represents deployment last deployed time. Required.
+ :vartype last_deployed_date_time: ~datetime.datetime
+ :ivar deployment_expiration_date: Represents deployment expiration date in the runtime.
+ Required.
+ :vartype deployment_expiration_date: ~datetime.date
+ :ivar model_training_config_version: Represents model training config version. Required.
+ :vartype model_training_config_version: str
+ :ivar assigned_resources: Represents the metadata of the assigned Azure resources. Required.
+ :vartype assigned_resources:
+ list[~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringDeploymentResource]
+ """
+
+ model_id: str = rest_field(name="modelId")
+ """Represents deployment modelId. Required."""
+ last_trained_date_time: datetime.datetime = rest_field(name="lastTrainedDateTime", format="rfc3339")
+ """Represents deployment last trained time. Required."""
+ last_deployed_date_time: datetime.datetime = rest_field(name="lastDeployedDateTime", format="rfc3339")
+ """Represents deployment last deployed time. Required."""
+ deployment_expiration_date: datetime.date = rest_field(name="deploymentExpirationDate")
+ """Represents deployment expiration date in the runtime. Required."""
+ model_training_config_version: str = rest_field(name="modelTrainingConfigVersion")
+ """Represents model training config version. Required."""
+ assigned_resources: List["_models.ConversationalAnalysisAuthoringDeploymentResource"] = rest_field(
+ name="assignedResources"
+ )
+ """Represents the metadata of the assigned Azure resources. Required."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ model_id: str,
+ last_trained_date_time: datetime.datetime,
+ last_deployed_date_time: datetime.datetime,
+ deployment_expiration_date: datetime.date,
+ model_training_config_version: str,
+ assigned_resources: List["_models.ConversationalAnalysisAuthoringDeploymentResource"],
+ ) -> 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 GetDeploymentStatusResponse(_model_base.Model):
+ """GetDeploymentStatusResponse.
+
+
+ :ivar created_date_time: The creation date time of the job. Required.
+ :vartype created_date_time: ~datetime.datetime
+ :ivar last_updated_date_time: The last date time the job was updated. Required.
+ :vartype last_updated_date_time: ~datetime.datetime
+ :ivar expiration_date_time: The expiration date time of the job.
+ :vartype expiration_date_time: ~datetime.datetime
+ :ivar status: The job status. Required. Known values are: "notStarted", "running", "succeeded",
+ "failed", "cancelled", "cancelling", and "partiallyCompleted".
+ :vartype status: str or ~azure.ai.language.authoring.analyzeconversations.models.JobStatus
+ :ivar warnings: The warnings that were encountered while executing the job.
+ :vartype warnings: list[~azure.ai.language.authoring.analyzeconversations.models.Warning]
+ :ivar errors: The errors encountered while executing the job.
+ :vartype errors: list[~azure.ai.language.authoring.analyzeconversations.models.Error]
+ """
+
+ created_date_time: datetime.datetime = rest_field(name="createdDateTime", format="rfc3339")
+ """The creation date time of the job. Required."""
+ last_updated_date_time: datetime.datetime = rest_field(name="lastUpdatedDateTime", format="rfc3339")
+ """The last date time the job was updated. Required."""
+ expiration_date_time: Optional[datetime.datetime] = rest_field(name="expirationDateTime", format="rfc3339")
+ """The expiration date time of the job."""
+ status: Union[str, "_models.JobStatus"] = rest_field()
+ """The job status. Required. Known values are: \"notStarted\", \"running\", \"succeeded\",
+ \"failed\", \"cancelled\", \"cancelling\", and \"partiallyCompleted\"."""
+ warnings: Optional[List["_models.Warning"]] = rest_field()
+ """The warnings that were encountered while executing the job."""
+ errors: Optional[List["_models.Error"]] = rest_field()
+ """The errors encountered while executing the job."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ created_date_time: datetime.datetime,
+ last_updated_date_time: datetime.datetime,
+ status: Union[str, "_models.JobStatus"],
+ expiration_date_time: Optional[datetime.datetime] = None,
+ warnings: Optional[List["_models.Warning"]] = None,
+ errors: Optional[List["_models.Error"]] = 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 GetEvaluationStatusResponse(_model_base.Model):
+ """GetEvaluationStatusResponse.
+
+
+ :ivar created_date_time: The creation date time of the job. Required.
+ :vartype created_date_time: ~datetime.datetime
+ :ivar last_updated_date_time: The last date time the job was updated. Required.
+ :vartype last_updated_date_time: ~datetime.datetime
+ :ivar expiration_date_time: The expiration date time of the job.
+ :vartype expiration_date_time: ~datetime.datetime
+ :ivar status: The job status. Required. Known values are: "notStarted", "running", "succeeded",
+ "failed", "cancelled", "cancelling", and "partiallyCompleted".
+ :vartype status: str or ~azure.ai.language.authoring.analyzeconversations.models.JobStatus
+ :ivar warnings: The warnings that were encountered while executing the job.
+ :vartype warnings: list[~azure.ai.language.authoring.analyzeconversations.models.Warning]
+ :ivar errors: The errors encountered while executing the job.
+ :vartype errors: list[~azure.ai.language.authoring.analyzeconversations.models.Error]
+ :ivar result: Represents evaluation task detailed result. Required.
+ :vartype result:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringEvaluationJobResult
+ """
+
+ created_date_time: datetime.datetime = rest_field(name="createdDateTime", format="rfc3339")
+ """The creation date time of the job. Required."""
+ last_updated_date_time: datetime.datetime = rest_field(name="lastUpdatedDateTime", format="rfc3339")
+ """The last date time the job was updated. Required."""
+ expiration_date_time: Optional[datetime.datetime] = rest_field(name="expirationDateTime", format="rfc3339")
+ """The expiration date time of the job."""
+ status: Union[str, "_models.JobStatus"] = rest_field()
+ """The job status. Required. Known values are: \"notStarted\", \"running\", \"succeeded\",
+ \"failed\", \"cancelled\", \"cancelling\", and \"partiallyCompleted\"."""
+ warnings: Optional[List["_models.Warning"]] = rest_field()
+ """The warnings that were encountered while executing the job."""
+ errors: Optional[List["_models.Error"]] = rest_field()
+ """The errors encountered while executing the job."""
+ result: "_models.ConversationalAnalysisAuthoringEvaluationJobResult" = rest_field()
+ """Represents evaluation task detailed result. Required."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ created_date_time: datetime.datetime,
+ last_updated_date_time: datetime.datetime,
+ status: Union[str, "_models.JobStatus"],
+ result: "_models.ConversationalAnalysisAuthoringEvaluationJobResult",
+ expiration_date_time: Optional[datetime.datetime] = None,
+ warnings: Optional[List["_models.Warning"]] = None,
+ errors: Optional[List["_models.Error"]] = 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 GetExportStatusResponse(_model_base.Model):
+ """GetExportStatusResponse.
+
+
+ :ivar created_date_time: The creation date time of the job. Required.
+ :vartype created_date_time: ~datetime.datetime
+ :ivar last_updated_date_time: The last date time the job was updated. Required.
+ :vartype last_updated_date_time: ~datetime.datetime
+ :ivar expiration_date_time: The expiration date time of the job.
+ :vartype expiration_date_time: ~datetime.datetime
+ :ivar status: The job status. Required. Known values are: "notStarted", "running", "succeeded",
+ "failed", "cancelled", "cancelling", and "partiallyCompleted".
+ :vartype status: str or ~azure.ai.language.authoring.analyzeconversations.models.JobStatus
+ :ivar warnings: The warnings that were encountered while executing the job.
+ :vartype warnings: list[~azure.ai.language.authoring.analyzeconversations.models.Warning]
+ :ivar errors: The errors encountered while executing the job.
+ :vartype errors: list[~azure.ai.language.authoring.analyzeconversations.models.Error]
+ :ivar result_url: The URL to use in order to download the exported project.
+ :vartype result_url: str
+ """
+
+ created_date_time: datetime.datetime = rest_field(name="createdDateTime", format="rfc3339")
+ """The creation date time of the job. Required."""
+ last_updated_date_time: datetime.datetime = rest_field(name="lastUpdatedDateTime", format="rfc3339")
+ """The last date time the job was updated. Required."""
+ expiration_date_time: Optional[datetime.datetime] = rest_field(name="expirationDateTime", format="rfc3339")
+ """The expiration date time of the job."""
+ status: Union[str, "_models.JobStatus"] = rest_field()
+ """The job status. Required. Known values are: \"notStarted\", \"running\", \"succeeded\",
+ \"failed\", \"cancelled\", \"cancelling\", and \"partiallyCompleted\"."""
+ warnings: Optional[List["_models.Warning"]] = rest_field()
+ """The warnings that were encountered while executing the job."""
+ errors: Optional[List["_models.Error"]] = rest_field()
+ """The errors encountered while executing the job."""
+ result_url: Optional[str] = rest_field(name="resultUrl")
+ """The URL to use in order to download the exported project."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ created_date_time: datetime.datetime,
+ last_updated_date_time: datetime.datetime,
+ status: Union[str, "_models.JobStatus"],
+ expiration_date_time: Optional[datetime.datetime] = None,
+ warnings: Optional[List["_models.Warning"]] = None,
+ errors: Optional[List["_models.Error"]] = None,
+ result_url: 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: # pylint: disable=useless-super-delegation
+ super().__init__(*args, **kwargs)
+
+
+class GetImportStatusResponse(_model_base.Model):
+ """GetImportStatusResponse.
+
+
+ :ivar created_date_time: The creation date time of the job. Required.
+ :vartype created_date_time: ~datetime.datetime
+ :ivar last_updated_date_time: The last date time the job was updated. Required.
+ :vartype last_updated_date_time: ~datetime.datetime
+ :ivar expiration_date_time: The expiration date time of the job.
+ :vartype expiration_date_time: ~datetime.datetime
+ :ivar status: The job status. Required. Known values are: "notStarted", "running", "succeeded",
+ "failed", "cancelled", "cancelling", and "partiallyCompleted".
+ :vartype status: str or ~azure.ai.language.authoring.analyzeconversations.models.JobStatus
+ :ivar warnings: The warnings that were encountered while executing the job.
+ :vartype warnings: list[~azure.ai.language.authoring.analyzeconversations.models.Warning]
+ :ivar errors: The errors encountered while executing the job.
+ :vartype errors: list[~azure.ai.language.authoring.analyzeconversations.models.Error]
+ """
+
+ created_date_time: datetime.datetime = rest_field(name="createdDateTime", format="rfc3339")
+ """The creation date time of the job. Required."""
+ last_updated_date_time: datetime.datetime = rest_field(name="lastUpdatedDateTime", format="rfc3339")
+ """The last date time the job was updated. Required."""
+ expiration_date_time: Optional[datetime.datetime] = rest_field(name="expirationDateTime", format="rfc3339")
+ """The expiration date time of the job."""
+ status: Union[str, "_models.JobStatus"] = rest_field()
+ """The job status. Required. Known values are: \"notStarted\", \"running\", \"succeeded\",
+ \"failed\", \"cancelled\", \"cancelling\", and \"partiallyCompleted\"."""
+ warnings: Optional[List["_models.Warning"]] = rest_field()
+ """The warnings that were encountered while executing the job."""
+ errors: Optional[List["_models.Error"]] = rest_field()
+ """The errors encountered while executing the job."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ created_date_time: datetime.datetime,
+ last_updated_date_time: datetime.datetime,
+ status: Union[str, "_models.JobStatus"],
+ expiration_date_time: Optional[datetime.datetime] = None,
+ warnings: Optional[List["_models.Warning"]] = None,
+ errors: Optional[List["_models.Error"]] = 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 GetLoadSnapshotStatusResponse(_model_base.Model):
+ """GetLoadSnapshotStatusResponse.
+
+
+ :ivar created_date_time: The creation date time of the job. Required.
+ :vartype created_date_time: ~datetime.datetime
+ :ivar last_updated_date_time: The last date time the job was updated. Required.
+ :vartype last_updated_date_time: ~datetime.datetime
+ :ivar expiration_date_time: The expiration date time of the job.
+ :vartype expiration_date_time: ~datetime.datetime
+ :ivar status: The job status. Required. Known values are: "notStarted", "running", "succeeded",
+ "failed", "cancelled", "cancelling", and "partiallyCompleted".
+ :vartype status: str or ~azure.ai.language.authoring.analyzeconversations.models.JobStatus
+ :ivar warnings: The warnings that were encountered while executing the job.
+ :vartype warnings: list[~azure.ai.language.authoring.analyzeconversations.models.Warning]
+ :ivar errors: The errors encountered while executing the job.
+ :vartype errors: list[~azure.ai.language.authoring.analyzeconversations.models.Error]
+ """
+
+ created_date_time: datetime.datetime = rest_field(name="createdDateTime", format="rfc3339")
+ """The creation date time of the job. Required."""
+ last_updated_date_time: datetime.datetime = rest_field(name="lastUpdatedDateTime", format="rfc3339")
+ """The last date time the job was updated. Required."""
+ expiration_date_time: Optional[datetime.datetime] = rest_field(name="expirationDateTime", format="rfc3339")
+ """The expiration date time of the job."""
+ status: Union[str, "_models.JobStatus"] = rest_field()
+ """The job status. Required. Known values are: \"notStarted\", \"running\", \"succeeded\",
+ \"failed\", \"cancelled\", \"cancelling\", and \"partiallyCompleted\"."""
+ warnings: Optional[List["_models.Warning"]] = rest_field()
+ """The warnings that were encountered while executing the job."""
+ errors: Optional[List["_models.Error"]] = rest_field()
+ """The errors encountered while executing the job."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ created_date_time: datetime.datetime,
+ last_updated_date_time: datetime.datetime,
+ status: Union[str, "_models.JobStatus"],
+ expiration_date_time: Optional[datetime.datetime] = None,
+ warnings: Optional[List["_models.Warning"]] = None,
+ errors: Optional[List["_models.Error"]] = 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 GetProjectDeletionStatusResponse(_model_base.Model):
+ """GetProjectDeletionStatusResponse.
+
+
+ :ivar created_date_time: The creation date time of the job. Required.
+ :vartype created_date_time: ~datetime.datetime
+ :ivar last_updated_date_time: The last date time the job was updated. Required.
+ :vartype last_updated_date_time: ~datetime.datetime
+ :ivar expiration_date_time: The expiration date time of the job.
+ :vartype expiration_date_time: ~datetime.datetime
+ :ivar status: The job status. Required. Known values are: "notStarted", "running", "succeeded",
+ "failed", "cancelled", "cancelling", and "partiallyCompleted".
+ :vartype status: str or ~azure.ai.language.authoring.analyzeconversations.models.JobStatus
+ :ivar warnings: The warnings that were encountered while executing the job.
+ :vartype warnings: list[~azure.ai.language.authoring.analyzeconversations.models.Warning]
+ :ivar errors: The errors encountered while executing the job.
+ :vartype errors: list[~azure.ai.language.authoring.analyzeconversations.models.Error]
+ """
+
+ created_date_time: datetime.datetime = rest_field(name="createdDateTime", format="rfc3339")
+ """The creation date time of the job. Required."""
+ last_updated_date_time: datetime.datetime = rest_field(name="lastUpdatedDateTime", format="rfc3339")
+ """The last date time the job was updated. Required."""
+ expiration_date_time: Optional[datetime.datetime] = rest_field(name="expirationDateTime", format="rfc3339")
+ """The expiration date time of the job."""
+ status: Union[str, "_models.JobStatus"] = rest_field()
+ """The job status. Required. Known values are: \"notStarted\", \"running\", \"succeeded\",
+ \"failed\", \"cancelled\", \"cancelling\", and \"partiallyCompleted\"."""
+ warnings: Optional[List["_models.Warning"]] = rest_field()
+ """The warnings that were encountered while executing the job."""
+ errors: Optional[List["_models.Error"]] = rest_field()
+ """The errors encountered while executing the job."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ created_date_time: datetime.datetime,
+ last_updated_date_time: datetime.datetime,
+ status: Union[str, "_models.JobStatus"],
+ expiration_date_time: Optional[datetime.datetime] = None,
+ warnings: Optional[List["_models.Warning"]] = None,
+ errors: Optional[List["_models.Error"]] = 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 GetSwapDeploymentsStatusResponse(_model_base.Model):
+ """GetSwapDeploymentsStatusResponse.
+
+
+ :ivar created_date_time: The creation date time of the job. Required.
+ :vartype created_date_time: ~datetime.datetime
+ :ivar last_updated_date_time: The last date time the job was updated. Required.
+ :vartype last_updated_date_time: ~datetime.datetime
+ :ivar expiration_date_time: The expiration date time of the job.
+ :vartype expiration_date_time: ~datetime.datetime
+ :ivar status: The job status. Required. Known values are: "notStarted", "running", "succeeded",
+ "failed", "cancelled", "cancelling", and "partiallyCompleted".
+ :vartype status: str or ~azure.ai.language.authoring.analyzeconversations.models.JobStatus
+ :ivar warnings: The warnings that were encountered while executing the job.
+ :vartype warnings: list[~azure.ai.language.authoring.analyzeconversations.models.Warning]
+ :ivar errors: The errors encountered while executing the job.
+ :vartype errors: list[~azure.ai.language.authoring.analyzeconversations.models.Error]
+ """
+
+ created_date_time: datetime.datetime = rest_field(name="createdDateTime", format="rfc3339")
+ """The creation date time of the job. Required."""
+ last_updated_date_time: datetime.datetime = rest_field(name="lastUpdatedDateTime", format="rfc3339")
+ """The last date time the job was updated. Required."""
+ expiration_date_time: Optional[datetime.datetime] = rest_field(name="expirationDateTime", format="rfc3339")
+ """The expiration date time of the job."""
+ status: Union[str, "_models.JobStatus"] = rest_field()
+ """The job status. Required. Known values are: \"notStarted\", \"running\", \"succeeded\",
+ \"failed\", \"cancelled\", \"cancelling\", and \"partiallyCompleted\"."""
+ warnings: Optional[List["_models.Warning"]] = rest_field()
+ """The warnings that were encountered while executing the job."""
+ errors: Optional[List["_models.Error"]] = rest_field()
+ """The errors encountered while executing the job."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ created_date_time: datetime.datetime,
+ last_updated_date_time: datetime.datetime,
+ status: Union[str, "_models.JobStatus"],
+ expiration_date_time: Optional[datetime.datetime] = None,
+ warnings: Optional[List["_models.Warning"]] = None,
+ errors: Optional[List["_models.Error"]] = 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 GetTrainedModelResponse(_model_base.Model):
+ """GetTrainedModelResponse.
+
+
+ :ivar model_id: The model ID. Required.
+ :vartype model_id: str
+ :ivar last_trained_date_time: The last trained date time of the model. Required.
+ :vartype last_trained_date_time: ~datetime.datetime
+ :ivar last_training_duration_in_seconds: The duration of the model's last training request in
+ seconds. Required.
+ :vartype last_training_duration_in_seconds: int
+ :ivar model_expiration_date: The model expiration date. Required.
+ :vartype model_expiration_date: ~datetime.date
+ :ivar model_training_config_version: The model training config version. Required.
+ :vartype model_training_config_version: str
+ :ivar has_snapshot: The flag to indicate if the trained model has a snapshot ready. Required.
+ :vartype has_snapshot: bool
+ """
+
+ model_id: str = rest_field(name="modelId")
+ """The model ID. Required."""
+ last_trained_date_time: datetime.datetime = rest_field(name="lastTrainedDateTime", format="rfc3339")
+ """The last trained date time of the model. Required."""
+ last_training_duration_in_seconds: int = rest_field(name="lastTrainingDurationInSeconds")
+ """The duration of the model's last training request in seconds. Required."""
+ model_expiration_date: datetime.date = rest_field(name="modelExpirationDate")
+ """The model expiration date. Required."""
+ model_training_config_version: str = rest_field(name="modelTrainingConfigVersion")
+ """The model training config version. Required."""
+ has_snapshot: bool = rest_field(name="hasSnapshot")
+ """The flag to indicate if the trained model has a snapshot ready. Required."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ model_id: str,
+ last_trained_date_time: datetime.datetime,
+ last_training_duration_in_seconds: int,
+ model_expiration_date: datetime.date,
+ model_training_config_version: str,
+ has_snapshot: bool,
+ ) -> 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 GetTrainingStatusResponse(_model_base.Model):
+ """GetTrainingStatusResponse.
+
+
+ :ivar created_date_time: The creation date time of the job. Required.
+ :vartype created_date_time: ~datetime.datetime
+ :ivar last_updated_date_time: The last date time the job was updated. Required.
+ :vartype last_updated_date_time: ~datetime.datetime
+ :ivar expiration_date_time: The expiration date time of the job.
+ :vartype expiration_date_time: ~datetime.datetime
+ :ivar status: The job status. Required. Known values are: "notStarted", "running", "succeeded",
+ "failed", "cancelled", "cancelling", and "partiallyCompleted".
+ :vartype status: str or ~azure.ai.language.authoring.analyzeconversations.models.JobStatus
+ :ivar warnings: The warnings that were encountered while executing the job.
+ :vartype warnings: list[~azure.ai.language.authoring.analyzeconversations.models.Warning]
+ :ivar errors: The errors encountered while executing the job.
+ :vartype errors: list[~azure.ai.language.authoring.analyzeconversations.models.Error]
+ :ivar result: Represents training tasks detailed result. Required.
+ :vartype result:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringTrainingJobResult
+ """
+
+ created_date_time: datetime.datetime = rest_field(name="createdDateTime", format="rfc3339")
+ """The creation date time of the job. Required."""
+ last_updated_date_time: datetime.datetime = rest_field(name="lastUpdatedDateTime", format="rfc3339")
+ """The last date time the job was updated. Required."""
+ expiration_date_time: Optional[datetime.datetime] = rest_field(name="expirationDateTime", format="rfc3339")
+ """The expiration date time of the job."""
+ status: Union[str, "_models.JobStatus"] = rest_field()
+ """The job status. Required. Known values are: \"notStarted\", \"running\", \"succeeded\",
+ \"failed\", \"cancelled\", \"cancelling\", and \"partiallyCompleted\"."""
+ warnings: Optional[List["_models.Warning"]] = rest_field()
+ """The warnings that were encountered while executing the job."""
+ errors: Optional[List["_models.Error"]] = rest_field()
+ """The errors encountered while executing the job."""
+ result: "_models.ConversationalAnalysisAuthoringTrainingJobResult" = rest_field()
+ """Represents training tasks detailed result. Required."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ created_date_time: datetime.datetime,
+ last_updated_date_time: datetime.datetime,
+ status: Union[str, "_models.JobStatus"],
+ result: "_models.ConversationalAnalysisAuthoringTrainingJobResult",
+ expiration_date_time: Optional[datetime.datetime] = None,
+ warnings: Optional[List["_models.Warning"]] = None,
+ errors: Optional[List["_models.Error"]] = 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 GetUnassignDeploymentResourcesStatusResponse(_model_base.Model): # pylint: disable=name-too-long
+ """GetUnassignDeploymentResourcesStatusResponse.
+
+
+ :ivar created_date_time: The creation date time of the job. Required.
+ :vartype created_date_time: ~datetime.datetime
+ :ivar last_updated_date_time: The last date time the job was updated. Required.
+ :vartype last_updated_date_time: ~datetime.datetime
+ :ivar expiration_date_time: The expiration date time of the job.
+ :vartype expiration_date_time: ~datetime.datetime
+ :ivar status: The job status. Required. Known values are: "notStarted", "running", "succeeded",
+ "failed", "cancelled", "cancelling", and "partiallyCompleted".
+ :vartype status: str or ~azure.ai.language.authoring.analyzeconversations.models.JobStatus
+ :ivar warnings: The warnings that were encountered while executing the job.
+ :vartype warnings: list[~azure.ai.language.authoring.analyzeconversations.models.Warning]
+ :ivar errors: The errors encountered while executing the job.
+ :vartype errors: list[~azure.ai.language.authoring.analyzeconversations.models.Error]
+ """
+
+ created_date_time: datetime.datetime = rest_field(name="createdDateTime", format="rfc3339")
+ """The creation date time of the job. Required."""
+ last_updated_date_time: datetime.datetime = rest_field(name="lastUpdatedDateTime", format="rfc3339")
+ """The last date time the job was updated. Required."""
+ expiration_date_time: Optional[datetime.datetime] = rest_field(name="expirationDateTime", format="rfc3339")
+ """The expiration date time of the job."""
+ status: Union[str, "_models.JobStatus"] = rest_field()
+ """The job status. Required. Known values are: \"notStarted\", \"running\", \"succeeded\",
+ \"failed\", \"cancelled\", \"cancelling\", and \"partiallyCompleted\"."""
+ warnings: Optional[List["_models.Warning"]] = rest_field()
+ """The warnings that were encountered while executing the job."""
+ errors: Optional[List["_models.Error"]] = rest_field()
+ """The errors encountered while executing the job."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ created_date_time: datetime.datetime,
+ last_updated_date_time: datetime.datetime,
+ status: Union[str, "_models.JobStatus"],
+ expiration_date_time: Optional[datetime.datetime] = None,
+ warnings: Optional[List["_models.Warning"]] = None,
+ errors: Optional[List["_models.Error"]] = 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 InnerErrorModel(_model_base.Model):
+ """An object containing more specific information about the error. As per
+ Microsoft One API guidelines -
+ https://github.com/Microsoft/api-guidelines/blob/vNext/Guidelines.md#7102-error-condition-responses.
+
+
+ :ivar code: One of a server-defined set of error codes. Required. Known values are:
+ "InvalidRequest", "InvalidParameterValue", "KnowledgeBaseNotFound",
+ "AzureCognitiveSearchNotFound", "AzureCognitiveSearchThrottling", "ExtractionFailure",
+ "InvalidRequestBodyFormat", "EmptyRequest", "MissingInputDocuments", "InvalidDocument",
+ "ModelVersionIncorrect", "InvalidDocumentBatch", "UnsupportedLanguageCode", and
+ "InvalidCountryHint".
+ :vartype code: str or ~azure.ai.language.authoring.analyzeconversations.models.InnerErrorCode
+ :ivar message: Error message. Required.
+ :vartype message: str
+ :ivar details: Error details.
+ :vartype details: dict[str, str]
+ :ivar target: Error target.
+ :vartype target: str
+ :ivar innererror: An object containing more specific information than the current object about
+ the error.
+ :vartype innererror: ~azure.ai.language.authoring.analyzeconversations.models.InnerErrorModel
+ """
+
+ code: Union[str, "_models.InnerErrorCode"] = rest_field()
+ """One of a server-defined set of error codes. Required. Known values are: \"InvalidRequest\",
+ \"InvalidParameterValue\", \"KnowledgeBaseNotFound\", \"AzureCognitiveSearchNotFound\",
+ \"AzureCognitiveSearchThrottling\", \"ExtractionFailure\", \"InvalidRequestBodyFormat\",
+ \"EmptyRequest\", \"MissingInputDocuments\", \"InvalidDocument\", \"ModelVersionIncorrect\",
+ \"InvalidDocumentBatch\", \"UnsupportedLanguageCode\", and \"InvalidCountryHint\"."""
+ message: str = rest_field()
+ """Error message. Required."""
+ details: Optional[Dict[str, str]] = rest_field()
+ """Error details."""
+ target: Optional[str] = rest_field()
+ """Error target."""
+ innererror: Optional["_models.InnerErrorModel"] = rest_field()
+ """An object containing more specific information than the current object about
+ the error."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ code: Union[str, "_models.InnerErrorCode"],
+ message: str,
+ details: Optional[Dict[str, str]] = None,
+ target: Optional[str] = None,
+ innererror: Optional["_models.InnerErrorModel"] = 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 Warning(_model_base.Model):
+ """Represents a warning that was encountered while executing the request.
+
+
+ :ivar code: The warning code. Required.
+ :vartype code: str
+ :ivar message: The warning message. Required.
+ :vartype message: str
+ """
+
+ code: str = rest_field()
+ """The warning code. Required."""
+ message: str = rest_field()
+ """The warning message. Required."""
+
+ @overload
+ def __init__(
+ self,
+ *,
+ code: str,
+ message: str,
+ ) -> 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)
diff --git a/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/models/_patch.py b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/models/_patch.py
new file mode 100644
index 000000000000..f7dd32510333
--- /dev/null
+++ b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/models/_patch.py
@@ -0,0 +1,20 @@
+# ------------------------------------
+# Copyright (c) Microsoft Corporation.
+# Licensed under the MIT License.
+# ------------------------------------
+"""Customize generated code here.
+
+Follow our quickstart for examples: https://aka.ms/azsdk/python/dpcodegen/python/customize
+"""
+from typing import List
+
+__all__: List[str] = [] # Add all objects you want publicly available to users at this package level
+
+
+def patch_sdk():
+ """Do not remove from this file.
+
+ `patch_sdk` is a last resort escape hatch that allows you to do customizations
+ you can't accomplish using the techniques described in
+ https://aka.ms/azsdk/python/dpcodegen/python/customize
+ """
diff --git a/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/operations/__init__.py b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/operations/__init__.py
new file mode 100644
index 000000000000..e75712aae675
--- /dev/null
+++ b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/operations/__init__.py
@@ -0,0 +1,19 @@
+# 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 ._operations import ConversationalAnalysisAuthoringOperations
+
+from ._patch import __all__ as _patch_all
+from ._patch import * # pylint: disable=unused-wildcard-import
+from ._patch import patch_sdk as _patch_sdk
+
+__all__ = [
+ "ConversationalAnalysisAuthoringOperations",
+]
+__all__.extend([p for p in _patch_all if p not in __all__]) # pyright: ignore
+_patch_sdk()
diff --git a/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/operations/_operations.py b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/operations/_operations.py
new file mode 100644
index 000000000000..63f07f7e0ae5
--- /dev/null
+++ b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/operations/_operations.py
@@ -0,0 +1,6385 @@
+# pylint: disable=too-many-lines
+# 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 io import IOBase
+import json
+import sys
+from typing import Any, Callable, Dict, IO, Iterable, Iterator, List, Optional, TypeVar, Union, cast, overload
+import urllib.parse
+
+from azure.core.exceptions import (
+ ClientAuthenticationError,
+ HttpResponseError,
+ ResourceExistsError,
+ ResourceNotFoundError,
+ ResourceNotModifiedError,
+ StreamClosedError,
+ StreamConsumedError,
+ map_error,
+)
+from azure.core.paging import ItemPaged
+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 .. import models as _models
+from .._model_base import SdkJSONEncoder, _deserialize
+from .._serialization import Serializer
+from .._validation import api_version_validation
+
+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
+_Unset: Any = object()
+T = TypeVar("T")
+ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]]
+
+_SERIALIZER = Serializer()
+_SERIALIZER.client_side_validation = False
+
+
+def build_conversational_analysis_authoring_list_projects_request( # pylint: disable=name-too-long
+ *, top: Optional[int] = None, skip: Optional[int] = None, maxpagesize: Optional[int] = None, **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", "2023-04-15-preview"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = "/authoring/analyze-conversations/projects"
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+ if top is not None:
+ _params["top"] = _SERIALIZER.query("top", top, "int")
+ if skip is not None:
+ _params["skip"] = _SERIALIZER.query("skip", skip, "int")
+ if maxpagesize is not None:
+ _params["maxpagesize"] = _SERIALIZER.query("maxpagesize", maxpagesize, "int")
+
+ # Construct headers
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="GET", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_conversational_analysis_authoring_get_project_request( # pylint: disable=name-too-long
+ project_name: 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", "2023-04-15-preview"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = "/authoring/analyze-conversations/projects/{projectName}"
+ path_format_arguments = {
+ "projectName": _SERIALIZER.url("project_name", project_name, "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_conversational_analysis_authoring_create_project_request( # pylint: disable=name-too-long
+ project_name: str, **kwargs: Any
+) -> HttpRequest:
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _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", "2023-04-15-preview"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = "/authoring/analyze-conversations/projects/{projectName}"
+ path_format_arguments = {
+ "projectName": _SERIALIZER.url("project_name", project_name, "str"),
+ }
+
+ _url: str = _url.format(**path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+
+ # Construct headers
+ if content_type is not None:
+ _headers["Content-Type"] = _SERIALIZER.header("content_type", content_type, "str")
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="PATCH", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_conversational_analysis_authoring_delete_project_request( # pylint: disable=name-too-long
+ project_name: 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", "2023-04-15-preview"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = "/authoring/analyze-conversations/projects/{projectName}"
+ path_format_arguments = {
+ "projectName": _SERIALIZER.url("project_name", project_name, "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_conversational_analysis_authoring_copy_project_authorization_request( # pylint: disable=name-too-long
+ project_name: str, **kwargs: Any
+) -> HttpRequest:
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _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", "2023-04-15-preview"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = "/authoring/analyze-conversations/projects/{projectName}/:authorize-copy"
+ path_format_arguments = {
+ "projectName": _SERIALIZER.url("project_name", project_name, "str"),
+ }
+
+ _url: str = _url.format(**path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+
+ # Construct headers
+ if content_type is not None:
+ _headers["Content-Type"] = _SERIALIZER.header("content_type", content_type, "str")
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="POST", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_conversational_analysis_authoring_copy_project_request( # pylint: disable=name-too-long
+ project_name: str, **kwargs: Any
+) -> HttpRequest:
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _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", "2023-04-15-preview"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = "/authoring/analyze-conversations/projects/{projectName}/:copy"
+ path_format_arguments = {
+ "projectName": _SERIALIZER.url("project_name", project_name, "str"),
+ }
+
+ _url: str = _url.format(**path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+
+ # Construct headers
+ if content_type is not None:
+ _headers["Content-Type"] = _SERIALIZER.header("content_type", content_type, "str")
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="POST", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_conversational_analysis_authoring_export_request( # pylint: disable=name-too-long
+ project_name: str,
+ *,
+ string_index_type: Union[str, _models.StringIndexType],
+ exported_project_format: Optional[Union[str, _models.ExportedProjectFormat]] = None,
+ asset_kind: Optional[str] = None,
+ trained_model_label: Optional[str] = None,
+ **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", "2023-04-15-preview"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = "/authoring/analyze-conversations/projects/{projectName}/:export"
+ path_format_arguments = {
+ "projectName": _SERIALIZER.url("project_name", project_name, "str"),
+ }
+
+ _url: str = _url.format(**path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+ if exported_project_format is not None:
+ _params["format"] = _SERIALIZER.query("exported_project_format", exported_project_format, "str")
+ _params["stringIndexType"] = _SERIALIZER.query("string_index_type", string_index_type, "str")
+ if asset_kind is not None:
+ _params["assetKind"] = _SERIALIZER.query("asset_kind", asset_kind, "str")
+ if trained_model_label is not None:
+ _params["trainedModelLabel"] = _SERIALIZER.query("trained_model_label", trained_model_label, "str")
+
+ # Construct headers
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="POST", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_conversational_analysis_authoring_import_method_request( # pylint: disable=name-too-long
+ project_name: str,
+ *,
+ exported_project_format: Optional[Union[str, _models.ExportedProjectFormat]] = None,
+ **kwargs: Any
+) -> HttpRequest:
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _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", "2023-04-15-preview"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = "/authoring/analyze-conversations/projects/{projectName}/:import"
+ path_format_arguments = {
+ "projectName": _SERIALIZER.url("project_name", project_name, "str"),
+ }
+
+ _url: str = _url.format(**path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+ if exported_project_format is not None:
+ _params["format"] = _SERIALIZER.query("exported_project_format", exported_project_format, "str")
+
+ # Construct headers
+ if content_type is not None:
+ _headers["Content-Type"] = _SERIALIZER.header("content_type", content_type, "str")
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="POST", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_conversational_analysis_authoring_train_request( # pylint: disable=name-too-long
+ project_name: str, **kwargs: Any
+) -> HttpRequest:
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _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", "2023-04-15-preview"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = "/authoring/analyze-conversations/projects/{projectName}/:train"
+ path_format_arguments = {
+ "projectName": _SERIALIZER.url("project_name", project_name, "str"),
+ }
+
+ _url: str = _url.format(**path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+
+ # Construct headers
+ if content_type is not None:
+ _headers["Content-Type"] = _SERIALIZER.header("content_type", content_type, "str")
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="POST", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_conversational_analysis_authoring_get_copy_project_status_request( # pylint: disable=name-too-long
+ project_name: str, job_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", "2023-04-15-preview"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = "/authoring/analyze-conversations/projects/{projectName}/copy/jobs/{jobId}"
+ path_format_arguments = {
+ "projectName": _SERIALIZER.url("project_name", project_name, "str"),
+ "jobId": _SERIALIZER.url("job_id", job_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_conversational_analysis_authoring_list_deployments_request( # pylint: disable=name-too-long
+ project_name: str,
+ *,
+ top: Optional[int] = None,
+ skip: Optional[int] = None,
+ maxpagesize: Optional[int] = None,
+ **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", "2023-04-15-preview"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = "/authoring/analyze-conversations/projects/{projectName}/deployments"
+ path_format_arguments = {
+ "projectName": _SERIALIZER.url("project_name", project_name, "str"),
+ }
+
+ _url: str = _url.format(**path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+ if top is not None:
+ _params["top"] = _SERIALIZER.query("top", top, "int")
+ if skip is not None:
+ _params["skip"] = _SERIALIZER.query("skip", skip, "int")
+ if maxpagesize is not None:
+ _params["maxpagesize"] = _SERIALIZER.query("maxpagesize", maxpagesize, "int")
+
+ # Construct headers
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="GET", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_conversational_analysis_authoring_swap_deployments_request( # pylint: disable=name-too-long
+ project_name: str, **kwargs: Any
+) -> HttpRequest:
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _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", "2023-04-15-preview"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = "/authoring/analyze-conversations/projects/{projectName}/deployments/:swap"
+ path_format_arguments = {
+ "projectName": _SERIALIZER.url("project_name", project_name, "str"),
+ }
+
+ _url: str = _url.format(**path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+
+ # Construct headers
+ if content_type is not None:
+ _headers["Content-Type"] = _SERIALIZER.header("content_type", content_type, "str")
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="POST", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_conversational_analysis_authoring_get_deployment_request( # pylint: disable=name-too-long
+ project_name: str, deployment_name: 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", "2023-04-15-preview"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = "/authoring/analyze-conversations/projects/{projectName}/deployments/{deploymentName}"
+ path_format_arguments = {
+ "projectName": _SERIALIZER.url("project_name", project_name, "str"),
+ "deploymentName": _SERIALIZER.url("deployment_name", deployment_name, "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_conversational_analysis_authoring_deploy_project_request( # pylint: disable=name-too-long
+ project_name: str, deployment_name: str, **kwargs: Any
+) -> HttpRequest:
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _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", "2023-04-15-preview"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = "/authoring/analyze-conversations/projects/{projectName}/deployments/{deploymentName}"
+ path_format_arguments = {
+ "projectName": _SERIALIZER.url("project_name", project_name, "str"),
+ "deploymentName": _SERIALIZER.url("deployment_name", deployment_name, "str"),
+ }
+
+ _url: str = _url.format(**path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+
+ # Construct headers
+ if content_type is not None:
+ _headers["Content-Type"] = _SERIALIZER.header("content_type", content_type, "str")
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="PUT", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_conversational_analysis_authoring_delete_deployment_request( # pylint: disable=name-too-long
+ project_name: str, deployment_name: 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", "2023-04-15-preview"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = "/authoring/analyze-conversations/projects/{projectName}/deployments/{deploymentName}"
+ path_format_arguments = {
+ "projectName": _SERIALIZER.url("project_name", project_name, "str"),
+ "deploymentName": _SERIALIZER.url("deployment_name", deployment_name, "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_conversational_analysis_authoring_delete_deployment_from_resources_request( # pylint: disable=name-too-long
+ project_name: str, deployment_name: str, **kwargs: Any
+) -> HttpRequest:
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _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", "2023-04-15-preview"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = "/authoring/analyze-conversations/projects/{projectName}/deployments/{deploymentName}/:delete-from-resources"
+ path_format_arguments = {
+ "projectName": _SERIALIZER.url("project_name", project_name, "str"),
+ "deploymentName": _SERIALIZER.url("deployment_name", deployment_name, "str"),
+ }
+
+ _url: str = _url.format(**path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+
+ # Construct headers
+ if content_type is not None:
+ _headers["Content-Type"] = _SERIALIZER.header("content_type", content_type, "str")
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="POST", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_conversational_analysis_authoring_get_deployment_delete_from_resources_status_request( # pylint: disable=name-too-long
+ project_name: str, deployment_name: str, job_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", "2023-04-15-preview"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = "/authoring/analyze-conversations/projects/{projectName}/deployments/{deploymentName}/delete-from-resources/jobs/{jobId}" # pylint: disable=line-too-long
+ path_format_arguments = {
+ "projectName": _SERIALIZER.url("project_name", project_name, "str"),
+ "deploymentName": _SERIALIZER.url("deployment_name", deployment_name, "str"),
+ "jobId": _SERIALIZER.url("job_id", job_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_conversational_analysis_authoring_get_deployment_status_request( # pylint: disable=name-too-long
+ project_name: str, deployment_name: str, job_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", "2023-04-15-preview"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = "/authoring/analyze-conversations/projects/{projectName}/deployments/{deploymentName}/jobs/{jobId}"
+ path_format_arguments = {
+ "projectName": _SERIALIZER.url("project_name", project_name, "str"),
+ "deploymentName": _SERIALIZER.url("deployment_name", deployment_name, "str"),
+ "jobId": _SERIALIZER.url("job_id", job_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_conversational_analysis_authoring_get_swap_deployments_status_request( # pylint: disable=name-too-long
+ project_name: str, job_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", "2023-04-15-preview"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = "/authoring/analyze-conversations/projects/{projectName}/deployments/swap/jobs/{jobId}"
+ path_format_arguments = {
+ "projectName": _SERIALIZER.url("project_name", project_name, "str"),
+ "jobId": _SERIALIZER.url("job_id", job_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_conversational_analysis_authoring_get_export_status_request( # pylint: disable=name-too-long
+ project_name: str, job_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", "2023-04-15-preview"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = "/authoring/analyze-conversations/projects/{projectName}/export/jobs/{jobId}"
+ path_format_arguments = {
+ "projectName": _SERIALIZER.url("project_name", project_name, "str"),
+ "jobId": _SERIALIZER.url("job_id", job_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_conversational_analysis_authoring_get_import_status_request( # pylint: disable=name-too-long
+ project_name: str, job_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", "2023-04-15-preview"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = "/authoring/analyze-conversations/projects/{projectName}/import/jobs/{jobId}"
+ path_format_arguments = {
+ "projectName": _SERIALIZER.url("project_name", project_name, "str"),
+ "jobId": _SERIALIZER.url("job_id", job_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_conversational_analysis_authoring_list_trained_models_request( # pylint: disable=name-too-long
+ project_name: str,
+ *,
+ top: Optional[int] = None,
+ skip: Optional[int] = None,
+ maxpagesize: Optional[int] = None,
+ **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", "2023-04-15-preview"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = "/authoring/analyze-conversations/projects/{projectName}/models"
+ path_format_arguments = {
+ "projectName": _SERIALIZER.url("project_name", project_name, "str"),
+ }
+
+ _url: str = _url.format(**path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+ if top is not None:
+ _params["top"] = _SERIALIZER.query("top", top, "int")
+ if skip is not None:
+ _params["skip"] = _SERIALIZER.query("skip", skip, "int")
+ if maxpagesize is not None:
+ _params["maxpagesize"] = _SERIALIZER.query("maxpagesize", maxpagesize, "int")
+
+ # Construct headers
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="GET", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_conversational_analysis_authoring_get_trained_model_request( # pylint: disable=name-too-long
+ project_name: str, trained_model_label: 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", "2023-04-15-preview"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = "/authoring/analyze-conversations/projects/{projectName}/models/{trainedModelLabel}"
+ path_format_arguments = {
+ "projectName": _SERIALIZER.url("project_name", project_name, "str"),
+ "trainedModelLabel": _SERIALIZER.url("trained_model_label", trained_model_label, "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_conversational_analysis_authoring_delete_trained_model_request( # pylint: disable=name-too-long
+ project_name: str, trained_model_label: 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", "2023-04-15-preview"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = "/authoring/analyze-conversations/projects/{projectName}/models/{trainedModelLabel}"
+ path_format_arguments = {
+ "projectName": _SERIALIZER.url("project_name", project_name, "str"),
+ "trainedModelLabel": _SERIALIZER.url("trained_model_label", trained_model_label, "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_conversational_analysis_authoring_evaluate_model_request( # pylint: disable=name-too-long
+ project_name: str, trained_model_label: str, **kwargs: Any
+) -> HttpRequest:
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _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", "2023-04-15-preview"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = "/authoring/analyze-conversations/projects/{projectName}/models/{trainedModelLabel}/:evaluate"
+ path_format_arguments = {
+ "projectName": _SERIALIZER.url("project_name", project_name, "str"),
+ "trainedModelLabel": _SERIALIZER.url("trained_model_label", trained_model_label, "str"),
+ }
+
+ _url: str = _url.format(**path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+
+ # Construct headers
+ if content_type is not None:
+ _headers["Content-Type"] = _SERIALIZER.header("content_type", content_type, "str")
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="POST", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_conversational_analysis_authoring_load_snapshot_request( # pylint: disable=name-too-long
+ project_name: str, trained_model_label: 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", "2023-04-15-preview"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = "/authoring/analyze-conversations/projects/{projectName}/models/{trainedModelLabel}/:load-snapshot"
+ path_format_arguments = {
+ "projectName": _SERIALIZER.url("project_name", project_name, "str"),
+ "trainedModelLabel": _SERIALIZER.url("trained_model_label", trained_model_label, "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="POST", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_conversational_analysis_authoring_get_evaluation_status_request( # pylint: disable=name-too-long
+ project_name: str, trained_model_label: str, job_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", "2023-04-15-preview"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = "/authoring/analyze-conversations/projects/{projectName}/models/{trainedModelLabel}/evaluate/jobs/{jobId}"
+ path_format_arguments = {
+ "projectName": _SERIALIZER.url("project_name", project_name, "str"),
+ "trainedModelLabel": _SERIALIZER.url("trained_model_label", trained_model_label, "str"),
+ "jobId": _SERIALIZER.url("job_id", job_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_conversational_analysis_authoring_get_model_evaluation_results_request( # pylint: disable=name-too-long
+ project_name: str,
+ trained_model_label: str,
+ *,
+ string_index_type: Union[str, _models.StringIndexType],
+ top: Optional[int] = None,
+ skip: Optional[int] = None,
+ maxpagesize: Optional[int] = None,
+ **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", "2023-04-15-preview"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = "/authoring/analyze-conversations/projects/{projectName}/models/{trainedModelLabel}/evaluation/result"
+ path_format_arguments = {
+ "projectName": _SERIALIZER.url("project_name", project_name, "str"),
+ "trainedModelLabel": _SERIALIZER.url("trained_model_label", trained_model_label, "str"),
+ }
+
+ _url: str = _url.format(**path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+ if top is not None:
+ _params["top"] = _SERIALIZER.query("top", top, "int")
+ if skip is not None:
+ _params["skip"] = _SERIALIZER.query("skip", skip, "int")
+ if maxpagesize is not None:
+ _params["maxpagesize"] = _SERIALIZER.query("maxpagesize", maxpagesize, "int")
+ _params["stringIndexType"] = _SERIALIZER.query("string_index_type", string_index_type, "str")
+
+ # Construct headers
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="GET", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_conversational_analysis_authoring_get_model_evaluation_summary_request( # pylint: disable=name-too-long
+ project_name: str, trained_model_label: 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", "2023-04-15-preview"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = (
+ "/authoring/analyze-conversations/projects/{projectName}/models/{trainedModelLabel}/evaluation/summary-result"
+ )
+ path_format_arguments = {
+ "projectName": _SERIALIZER.url("project_name", project_name, "str"),
+ "trainedModelLabel": _SERIALIZER.url("trained_model_label", trained_model_label, "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_conversational_analysis_authoring_get_load_snapshot_status_request( # pylint: disable=name-too-long
+ project_name: str, trained_model_label: str, job_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", "2023-04-15-preview"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = (
+ "/authoring/analyze-conversations/projects/{projectName}/models/{trainedModelLabel}/load-snapshot/jobs/{jobId}"
+ )
+ path_format_arguments = {
+ "projectName": _SERIALIZER.url("project_name", project_name, "str"),
+ "trainedModelLabel": _SERIALIZER.url("trained_model_label", trained_model_label, "str"),
+ "jobId": _SERIALIZER.url("job_id", job_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_conversational_analysis_authoring_list_deployment_resources_request( # pylint: disable=name-too-long
+ project_name: str,
+ *,
+ top: Optional[int] = None,
+ skip: Optional[int] = None,
+ maxpagesize: Optional[int] = None,
+ **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", "2023-04-15-preview"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = "/authoring/analyze-conversations/projects/{projectName}/resources"
+ path_format_arguments = {
+ "projectName": _SERIALIZER.url("project_name", project_name, "str"),
+ }
+
+ _url: str = _url.format(**path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+ if top is not None:
+ _params["top"] = _SERIALIZER.query("top", top, "int")
+ if skip is not None:
+ _params["skip"] = _SERIALIZER.query("skip", skip, "int")
+ if maxpagesize is not None:
+ _params["maxpagesize"] = _SERIALIZER.query("maxpagesize", maxpagesize, "int")
+
+ # Construct headers
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="GET", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_conversational_analysis_authoring_assign_deployment_resources_request( # pylint: disable=name-too-long
+ project_name: str, **kwargs: Any
+) -> HttpRequest:
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _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", "2023-04-15-preview"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = "/authoring/analyze-conversations/projects/{projectName}/resources/:assign"
+ path_format_arguments = {
+ "projectName": _SERIALIZER.url("project_name", project_name, "str"),
+ }
+
+ _url: str = _url.format(**path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+
+ # Construct headers
+ if content_type is not None:
+ _headers["Content-Type"] = _SERIALIZER.header("content_type", content_type, "str")
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="POST", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_conversational_analysis_authoring_unassign_deployment_resources_request( # pylint: disable=name-too-long
+ project_name: str, **kwargs: Any
+) -> HttpRequest:
+ _headers = case_insensitive_dict(kwargs.pop("headers", {}) or {})
+ _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", "2023-04-15-preview"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = "/authoring/analyze-conversations/projects/{projectName}/resources/:unassign"
+ path_format_arguments = {
+ "projectName": _SERIALIZER.url("project_name", project_name, "str"),
+ }
+
+ _url: str = _url.format(**path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+
+ # Construct headers
+ if content_type is not None:
+ _headers["Content-Type"] = _SERIALIZER.header("content_type", content_type, "str")
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="POST", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_conversational_analysis_authoring_get_assign_deployment_resources_status_request( # pylint: disable=name-too-long
+ project_name: str, job_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", "2023-04-15-preview"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = "/authoring/analyze-conversations/projects/{projectName}/resources/assign/jobs/{jobId}"
+ path_format_arguments = {
+ "projectName": _SERIALIZER.url("project_name", project_name, "str"),
+ "jobId": _SERIALIZER.url("job_id", job_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_conversational_analysis_authoring_get_unassign_deployment_resources_status_request( # pylint: disable=name-too-long
+ project_name: str, job_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", "2023-04-15-preview"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = "/authoring/analyze-conversations/projects/{projectName}/resources/unassign/jobs/{jobId}"
+ path_format_arguments = {
+ "projectName": _SERIALIZER.url("project_name", project_name, "str"),
+ "jobId": _SERIALIZER.url("job_id", job_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_conversational_analysis_authoring_list_training_jobs_request( # pylint: disable=name-too-long
+ project_name: str,
+ *,
+ top: Optional[int] = None,
+ skip: Optional[int] = None,
+ maxpagesize: Optional[int] = None,
+ **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", "2023-04-15-preview"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = "/authoring/analyze-conversations/projects/{projectName}/train/jobs"
+ path_format_arguments = {
+ "projectName": _SERIALIZER.url("project_name", project_name, "str"),
+ }
+
+ _url: str = _url.format(**path_format_arguments) # type: ignore
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+ if top is not None:
+ _params["top"] = _SERIALIZER.query("top", top, "int")
+ if skip is not None:
+ _params["skip"] = _SERIALIZER.query("skip", skip, "int")
+ if maxpagesize is not None:
+ _params["maxpagesize"] = _SERIALIZER.query("maxpagesize", maxpagesize, "int")
+
+ # Construct headers
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="GET", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_conversational_analysis_authoring_get_training_status_request( # pylint: disable=name-too-long
+ project_name: str, job_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", "2023-04-15-preview"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = "/authoring/analyze-conversations/projects/{projectName}/train/jobs/{jobId}"
+ path_format_arguments = {
+ "projectName": _SERIALIZER.url("project_name", project_name, "str"),
+ "jobId": _SERIALIZER.url("job_id", job_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_conversational_analysis_authoring_cancel_training_job_request( # pylint: disable=name-too-long
+ project_name: str, job_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", "2023-04-15-preview"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = "/authoring/analyze-conversations/projects/{projectName}/train/jobs/{jobId}/:cancel"
+ path_format_arguments = {
+ "projectName": _SERIALIZER.url("project_name", project_name, "str"),
+ "jobId": _SERIALIZER.url("job_id", job_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="POST", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_conversational_analysis_authoring_get_project_deletion_status_request( # pylint: disable=name-too-long
+ job_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", "2023-04-15-preview"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = "/authoring/analyze-conversations/projects/global/deletion-jobs/{jobId}"
+ path_format_arguments = {
+ "jobId": _SERIALIZER.url("job_id", job_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_conversational_analysis_authoring_list_assigned_resource_deployments_request( # pylint: disable=name-too-long
+ *, top: Optional[int] = None, skip: Optional[int] = None, maxpagesize: Optional[int] = None, **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", "2023-04-15-preview"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = "/authoring/analyze-conversations/projects/global/deployments/resources"
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+ if top is not None:
+ _params["top"] = _SERIALIZER.query("top", top, "int")
+ if skip is not None:
+ _params["skip"] = _SERIALIZER.query("skip", skip, "int")
+ if maxpagesize is not None:
+ _params["maxpagesize"] = _SERIALIZER.query("maxpagesize", maxpagesize, "int")
+
+ # Construct headers
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="GET", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_conversational_analysis_authoring_get_supported_languages_request( # pylint: disable=name-too-long
+ *,
+ project_kind: Union[str, _models.ProjectKind],
+ top: Optional[int] = None,
+ skip: Optional[int] = None,
+ maxpagesize: Optional[int] = None,
+ **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", "2023-04-15-preview"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = "/authoring/analyze-conversations/projects/global/languages"
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+ _params["projectKind"] = _SERIALIZER.query("project_kind", project_kind, "str")
+ if top is not None:
+ _params["top"] = _SERIALIZER.query("top", top, "int")
+ if skip is not None:
+ _params["skip"] = _SERIALIZER.query("skip", skip, "int")
+ if maxpagesize is not None:
+ _params["maxpagesize"] = _SERIALIZER.query("maxpagesize", maxpagesize, "int")
+
+ # Construct headers
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="GET", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_conversational_analysis_authoring_get_supported_prebuilt_entities_request( # pylint: disable=name-too-long
+ *,
+ language: Optional[str] = None,
+ multilingual: Optional[str] = None,
+ top: Optional[int] = None,
+ skip: Optional[int] = None,
+ maxpagesize: Optional[int] = None,
+ **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", "2023-04-15-preview"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = "/authoring/analyze-conversations/projects/global/prebuilt-entities"
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+ if language is not None:
+ _params["language"] = _SERIALIZER.query("language", language, "str")
+ if multilingual is not None:
+ _params["multilingual"] = _SERIALIZER.query("multilingual", multilingual, "str")
+ if top is not None:
+ _params["top"] = _SERIALIZER.query("top", top, "int")
+ if skip is not None:
+ _params["skip"] = _SERIALIZER.query("skip", skip, "int")
+ if maxpagesize is not None:
+ _params["maxpagesize"] = _SERIALIZER.query("maxpagesize", maxpagesize, "int")
+
+ # Construct headers
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="GET", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+def build_conversational_analysis_authoring_list_training_config_versions_request( # pylint: disable=name-too-long
+ *,
+ project_kind: Union[str, _models.ProjectKind],
+ top: Optional[int] = None,
+ skip: Optional[int] = None,
+ maxpagesize: Optional[int] = None,
+ **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", "2023-04-15-preview"))
+ accept = _headers.pop("Accept", "application/json")
+
+ # Construct URL
+ _url = "/authoring/analyze-conversations/projects/global/training-config-versions"
+
+ # Construct parameters
+ _params["api-version"] = _SERIALIZER.query("api_version", api_version, "str")
+ _params["projectKind"] = _SERIALIZER.query("project_kind", project_kind, "str")
+ if top is not None:
+ _params["top"] = _SERIALIZER.query("top", top, "int")
+ if skip is not None:
+ _params["skip"] = _SERIALIZER.query("skip", skip, "int")
+ if maxpagesize is not None:
+ _params["maxpagesize"] = _SERIALIZER.query("maxpagesize", maxpagesize, "int")
+
+ # Construct headers
+ _headers["Accept"] = _SERIALIZER.header("accept", accept, "str")
+
+ return HttpRequest(method="GET", url=_url, params=_params, headers=_headers, **kwargs)
+
+
+class ConversationalAnalysisAuthoringOperations: # pylint: disable=too-many-public-methods,name-too-long
+ """
+ .. warning::
+ **DO NOT** instantiate this class directly.
+
+ Instead, you should access the following operations through
+ :class:`~azure.ai.language.authoring.analyzeconversations.ConversationsClient`'s
+ :attr:`conversational_analysis_authoring` attribute.
+ """
+
+ def __init__(self, *args, **kwargs):
+ input_args = list(args)
+ self._client = input_args.pop(0) if input_args else kwargs.pop("client")
+ self._config = input_args.pop(0) if input_args else kwargs.pop("config")
+ self._serialize = input_args.pop(0) if input_args else kwargs.pop("serializer")
+ self._deserialize = input_args.pop(0) if input_args else kwargs.pop("deserializer")
+
+ @distributed_trace
+ def list_projects(
+ self, *, top: Optional[int] = None, skip: Optional[int] = None, **kwargs: Any
+ ) -> Iterable["_models.ConversationalAnalysisAuthoringProjectMetadata"]:
+ # pylint: disable=line-too-long
+ """Lists the existing projects.
+
+ :keyword top: The number of result items to return. Default value is None.
+ :paramtype top: int
+ :keyword skip: The number of result items to skip. Default value is None.
+ :paramtype skip: int
+ :return: An iterator like instance of ConversationalAnalysisAuthoringProjectMetadata
+ :rtype:
+ ~azure.core.paging.ItemPaged[~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringProjectMetadata]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = kwargs.pop("params", {}) or {}
+
+ maxpagesize = kwargs.pop("maxpagesize", None)
+ cls: ClsType[List[_models.ConversationalAnalysisAuthoringProjectMetadata]] = 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_conversational_analysis_authoring_list_projects_request(
+ top=top,
+ skip=skip,
+ maxpagesize=maxpagesize,
+ api_version=self._config.api_version,
+ headers=_headers,
+ params=_params,
+ )
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _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"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _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.ConversationalAnalysisAuthoringProjectMetadata], 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ return pipeline_response
+
+ return ItemPaged(get_next, extract_data)
+
+ @distributed_trace
+ def get_project(self, project_name: str, **kwargs: Any) -> _models.ConversationalAnalysisAuthoringProjectMetadata:
+ """Gets the details of a project.
+
+ :param project_name: The new project name. Required.
+ :type project_name: str
+ :return: ConversationalAnalysisAuthoringProjectMetadata. The
+ ConversationalAnalysisAuthoringProjectMetadata is compatible with MutableMapping
+ :rtype:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringProjectMetadata
+ :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[_models.ConversationalAnalysisAuthoringProjectMetadata] = kwargs.pop("cls", None)
+
+ _request = build_conversational_analysis_authoring_get_project_request(
+ project_name=project_name,
+ api_version=self._config.api_version,
+ headers=_headers,
+ params=_params,
+ )
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _stream = kwargs.pop("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
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ if _stream:
+ deserialized = response.iter_bytes()
+ else:
+ deserialized = _deserialize(_models.ConversationalAnalysisAuthoringProjectMetadata, response.json())
+
+ if cls:
+ return cls(pipeline_response, deserialized, {}) # type: ignore
+
+ return deserialized # type: ignore
+
+ @overload
+ def create_project(
+ self,
+ project_name: str,
+ body: _models.ConversationalAnalysisAuthoringCreateProjectOptions,
+ *,
+ content_type: str = "application/merge-patch+json",
+ **kwargs: Any
+ ) -> _models.ConversationalAnalysisAuthoringProjectMetadata:
+ """Creates a new project or updates an existing one.
+
+ :param project_name: The new project name. Required.
+ :type project_name: str
+ :param body: The request body. Required.
+ :type body:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringCreateProjectOptions
+ :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
+ Default value is "application/merge-patch+json".
+ :paramtype content_type: str
+ :return: ConversationalAnalysisAuthoringProjectMetadata. The
+ ConversationalAnalysisAuthoringProjectMetadata is compatible with MutableMapping
+ :rtype:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringProjectMetadata
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ def create_project(
+ self, project_name: str, body: JSON, *, content_type: str = "application/merge-patch+json", **kwargs: Any
+ ) -> _models.ConversationalAnalysisAuthoringProjectMetadata:
+ """Creates a new project or updates an existing one.
+
+ :param project_name: The new project name. Required.
+ :type project_name: str
+ :param body: The request body. Required.
+ :type body: JSON
+ :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
+ Default value is "application/merge-patch+json".
+ :paramtype content_type: str
+ :return: ConversationalAnalysisAuthoringProjectMetadata. The
+ ConversationalAnalysisAuthoringProjectMetadata is compatible with MutableMapping
+ :rtype:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringProjectMetadata
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ def create_project(
+ self, project_name: str, body: IO[bytes], *, content_type: str = "application/merge-patch+json", **kwargs: Any
+ ) -> _models.ConversationalAnalysisAuthoringProjectMetadata:
+ """Creates a new project or updates an existing one.
+
+ :param project_name: The new project name. Required.
+ :type project_name: str
+ :param body: The request body. Required.
+ :type body: IO[bytes]
+ :keyword content_type: Body Parameter content-type. Content type parameter for binary body.
+ Default value is "application/merge-patch+json".
+ :paramtype content_type: str
+ :return: ConversationalAnalysisAuthoringProjectMetadata. The
+ ConversationalAnalysisAuthoringProjectMetadata is compatible with MutableMapping
+ :rtype:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringProjectMetadata
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @distributed_trace
+ def create_project(
+ self,
+ project_name: str,
+ body: Union[_models.ConversationalAnalysisAuthoringCreateProjectOptions, JSON, IO[bytes]],
+ **kwargs: Any
+ ) -> _models.ConversationalAnalysisAuthoringProjectMetadata:
+ """Creates a new project or updates an existing one.
+
+ :param project_name: The new project name. Required.
+ :type project_name: str
+ :param body: The request body. Is one of the following types:
+ ConversationalAnalysisAuthoringCreateProjectOptions, JSON, IO[bytes] Required.
+ :type body:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringCreateProjectOptions
+ or JSON or IO[bytes]
+ :return: ConversationalAnalysisAuthoringProjectMetadata. The
+ ConversationalAnalysisAuthoringProjectMetadata is compatible with MutableMapping
+ :rtype:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringProjectMetadata
+ :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 = 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.ConversationalAnalysisAuthoringProjectMetadata] = kwargs.pop("cls", None)
+
+ content_type = content_type or "application/merge-patch+json"
+ _content = None
+ if isinstance(body, (IOBase, bytes)):
+ _content = body
+ else:
+ _content = json.dumps(body, cls=SdkJSONEncoder, exclude_readonly=True) # type: ignore
+
+ _request = build_conversational_analysis_authoring_create_project_request(
+ project_name=project_name,
+ content_type=content_type,
+ api_version=self._config.api_version,
+ content=_content,
+ headers=_headers,
+ params=_params,
+ )
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _stream = kwargs.pop("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, 201]:
+ 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ if _stream:
+ deserialized = response.iter_bytes()
+ else:
+ deserialized = _deserialize(_models.ConversationalAnalysisAuthoringProjectMetadata, response.json())
+
+ if cls:
+ return cls(pipeline_response, deserialized, {}) # type: ignore
+
+ return deserialized # type: ignore
+
+ def _delete_project_initial(self, project_name: str, **kwargs: Any) -> Iterator[bytes]:
+ 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_conversational_analysis_authoring_delete_project_request(
+ project_name=project_name,
+ api_version=self._config.api_version,
+ headers=_headers,
+ params=_params,
+ )
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _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 [202]:
+ 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ response_headers = {}
+ response_headers["Operation-Location"] = self._deserialize("str", response.headers.get("Operation-Location"))
+
+ deserialized = response.iter_bytes()
+
+ if cls:
+ return cls(pipeline_response, deserialized, response_headers) # type: ignore
+
+ return deserialized # type: ignore
+
+ @distributed_trace
+ def begin_delete_project(self, project_name: str, **kwargs: Any) -> LROPoller[None]:
+ """Deletes a project.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :return: An instance of LROPoller that returns None
+ :rtype: ~azure.core.polling.LROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = kwargs.pop("params", {}) or {}
+
+ cls: ClsType[None] = 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._delete_project_initial(
+ project_name=project_name, 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): # pylint: disable=inconsistent-return-statements
+ if cls:
+ return cls(pipeline_response, None, {}) # type: ignore
+
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+
+ 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[None].from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return LROPoller[None](self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ @overload
+ def copy_project_authorization(
+ self, project_name: str, body: JSON, *, content_type: str = "application/json", **kwargs: Any
+ ) -> _models.ConversationalAnalysisAuthoringCopyProjectOptions:
+ """Generates a copy project operation authorization to the current target Azure
+ resource.
+
+ :param project_name: The new project name. Required.
+ :type project_name: str
+ :param body: 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: ConversationalAnalysisAuthoringCopyProjectOptions. The
+ ConversationalAnalysisAuthoringCopyProjectOptions is compatible with MutableMapping
+ :rtype:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringCopyProjectOptions
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ def copy_project_authorization(
+ self,
+ project_name: str,
+ *,
+ project_kind: Union[str, _models.ProjectKind],
+ content_type: str = "application/json",
+ storage_input_container_name: Optional[str] = None,
+ allow_overwrite: Optional[bool] = None,
+ **kwargs: Any
+ ) -> _models.ConversationalAnalysisAuthoringCopyProjectOptions:
+ """Generates a copy project operation authorization to the current target Azure
+ resource.
+
+ :param project_name: The new project name. Required.
+ :type project_name: str
+ :keyword project_kind: Represents the project kind. Known values are: "Conversation",
+ "Orchestration", and "CustomConversationSummarization". Required.
+ :paramtype project_kind: str or
+ ~azure.ai.language.authoring.analyzeconversations.models.ProjectKind
+ :keyword content_type: Body Parameter content-type. Content type parameter for JSON body.
+ Default value is "application/json".
+ :paramtype content_type: str
+ :keyword storage_input_container_name: The name of the storage container. Default value is
+ None.
+ :paramtype storage_input_container_name: str
+ :keyword allow_overwrite: Whether to allow an existing project to be overwritten using the
+ resulting copy authorization. Default value is None.
+ :paramtype allow_overwrite: bool
+ :return: ConversationalAnalysisAuthoringCopyProjectOptions. The
+ ConversationalAnalysisAuthoringCopyProjectOptions is compatible with MutableMapping
+ :rtype:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringCopyProjectOptions
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ def copy_project_authorization(
+ self, project_name: str, body: IO[bytes], *, content_type: str = "application/json", **kwargs: Any
+ ) -> _models.ConversationalAnalysisAuthoringCopyProjectOptions:
+ """Generates a copy project operation authorization to the current target Azure
+ resource.
+
+ :param project_name: The new project name. Required.
+ :type project_name: str
+ :param body: 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: ConversationalAnalysisAuthoringCopyProjectOptions. The
+ ConversationalAnalysisAuthoringCopyProjectOptions is compatible with MutableMapping
+ :rtype:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringCopyProjectOptions
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @distributed_trace
+ @api_version_validation(
+ method_added_on="2023-04-15-preview",
+ params_added_on={"2023-04-15-preview": ["api_version", "project_name", "content_type", "accept"]},
+ )
+ def copy_project_authorization(
+ self,
+ project_name: str,
+ body: Union[JSON, IO[bytes]] = _Unset,
+ *,
+ project_kind: Union[str, _models.ProjectKind] = _Unset,
+ storage_input_container_name: Optional[str] = None,
+ allow_overwrite: Optional[bool] = None,
+ **kwargs: Any
+ ) -> _models.ConversationalAnalysisAuthoringCopyProjectOptions:
+ """Generates a copy project operation authorization to the current target Azure
+ resource.
+
+ :param project_name: The new project name. Required.
+ :type project_name: str
+ :param body: Is either a JSON type or a IO[bytes] type. Required.
+ :type body: JSON or IO[bytes]
+ :keyword project_kind: Represents the project kind. Known values are: "Conversation",
+ "Orchestration", and "CustomConversationSummarization". Required.
+ :paramtype project_kind: str or
+ ~azure.ai.language.authoring.analyzeconversations.models.ProjectKind
+ :keyword storage_input_container_name: The name of the storage container. Default value is
+ None.
+ :paramtype storage_input_container_name: str
+ :keyword allow_overwrite: Whether to allow an existing project to be overwritten using the
+ resulting copy authorization. Default value is None.
+ :paramtype allow_overwrite: bool
+ :return: ConversationalAnalysisAuthoringCopyProjectOptions. The
+ ConversationalAnalysisAuthoringCopyProjectOptions is compatible with MutableMapping
+ :rtype:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringCopyProjectOptions
+ :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 = 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.ConversationalAnalysisAuthoringCopyProjectOptions] = kwargs.pop("cls", None)
+
+ if body is _Unset:
+ if project_kind is _Unset:
+ raise TypeError("missing required argument: project_kind")
+ body = {
+ "allowOverwrite": allow_overwrite,
+ "projectKind": project_kind,
+ "storageInputContainerName": storage_input_container_name,
+ }
+ body = {k: v for k, v in body.items() if v is not None}
+ content_type = content_type or "application/json"
+ _content = None
+ if isinstance(body, (IOBase, bytes)):
+ _content = body
+ else:
+ _content = json.dumps(body, cls=SdkJSONEncoder, exclude_readonly=True) # type: ignore
+
+ _request = build_conversational_analysis_authoring_copy_project_authorization_request(
+ project_name=project_name,
+ content_type=content_type,
+ api_version=self._config.api_version,
+ content=_content,
+ headers=_headers,
+ params=_params,
+ )
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _stream = kwargs.pop("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
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ if _stream:
+ deserialized = response.iter_bytes()
+ else:
+ deserialized = _deserialize(_models.ConversationalAnalysisAuthoringCopyProjectOptions, response.json())
+
+ if cls:
+ return cls(pipeline_response, deserialized, {}) # type: ignore
+
+ return deserialized # type: ignore
+
+ @api_version_validation(
+ method_added_on="2023-04-15-preview",
+ params_added_on={"2023-04-15-preview": ["api_version", "project_name", "content_type", "accept"]},
+ )
+ def _copy_project_initial(
+ self,
+ project_name: str,
+ body: Union[_models.ConversationalAnalysisAuthoringCopyProjectOptions, JSON, IO[bytes]],
+ **kwargs: Any
+ ) -> Iterator[bytes]:
+ error_map: MutableMapping = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _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[Iterator[bytes]] = kwargs.pop("cls", None)
+
+ content_type = content_type or "application/json"
+ _content = None
+ if isinstance(body, (IOBase, bytes)):
+ _content = body
+ else:
+ _content = json.dumps(body, cls=SdkJSONEncoder, exclude_readonly=True) # type: ignore
+
+ _request = build_conversational_analysis_authoring_copy_project_request(
+ project_name=project_name,
+ content_type=content_type,
+ api_version=self._config.api_version,
+ content=_content,
+ headers=_headers,
+ params=_params,
+ )
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _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 [202]:
+ 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ response_headers = {}
+ response_headers["Operation-Location"] = self._deserialize("str", response.headers.get("Operation-Location"))
+
+ deserialized = response.iter_bytes()
+
+ if cls:
+ return cls(pipeline_response, deserialized, response_headers) # type: ignore
+
+ return deserialized # type: ignore
+
+ @overload
+ def begin_copy_project(
+ self,
+ project_name: str,
+ body: _models.ConversationalAnalysisAuthoringCopyProjectOptions,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> LROPoller[None]:
+ """Copies an existing project to another Azure resource.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param body: The copy project info. Required.
+ :type body:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringCopyProjectOptions
+ :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 LROPoller that returns None
+ :rtype: ~azure.core.polling.LROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ def begin_copy_project(
+ self, project_name: str, body: JSON, *, content_type: str = "application/json", **kwargs: Any
+ ) -> LROPoller[None]:
+ """Copies an existing project to another Azure resource.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param body: The copy project info. 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: An instance of LROPoller that returns None
+ :rtype: ~azure.core.polling.LROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ def begin_copy_project(
+ self, project_name: str, body: IO[bytes], *, content_type: str = "application/json", **kwargs: Any
+ ) -> LROPoller[None]:
+ """Copies an existing project to another Azure resource.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param body: The copy project info. 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: An instance of LROPoller that returns None
+ :rtype: ~azure.core.polling.LROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @distributed_trace
+ @api_version_validation(
+ method_added_on="2023-04-15-preview",
+ params_added_on={"2023-04-15-preview": ["api_version", "project_name", "content_type", "accept"]},
+ )
+ def begin_copy_project(
+ self,
+ project_name: str,
+ body: Union[_models.ConversationalAnalysisAuthoringCopyProjectOptions, JSON, IO[bytes]],
+ **kwargs: Any
+ ) -> LROPoller[None]:
+ """Copies an existing project to another Azure resource.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param body: The copy project info. Is one of the following types:
+ ConversationalAnalysisAuthoringCopyProjectOptions, JSON, IO[bytes] Required.
+ :type body:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringCopyProjectOptions
+ or JSON or IO[bytes]
+ :return: An instance of LROPoller that returns None
+ :rtype: ~azure.core.polling.LROPoller[None]
+ :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[None] = 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_project_initial(
+ project_name=project_name,
+ 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)
+
+ def get_long_running_output(pipeline_response): # pylint: disable=inconsistent-return-statements
+ if cls:
+ return cls(pipeline_response, None, {}) # type: ignore
+
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+
+ 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[None].from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return LROPoller[None](self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ def _export_initial(
+ self,
+ project_name: str,
+ *,
+ string_index_type: Union[str, _models.StringIndexType],
+ exported_project_format: Optional[Union[str, _models.ExportedProjectFormat]] = None,
+ asset_kind: Optional[str] = None,
+ trained_model_label: Optional[str] = None,
+ **kwargs: Any
+ ) -> Iterator[bytes]:
+ 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_conversational_analysis_authoring_export_request(
+ project_name=project_name,
+ string_index_type=string_index_type,
+ exported_project_format=exported_project_format,
+ asset_kind=asset_kind,
+ trained_model_label=trained_model_label,
+ api_version=self._config.api_version,
+ headers=_headers,
+ params=_params,
+ )
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _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 [202]:
+ 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ response_headers = {}
+ response_headers["Operation-Location"] = self._deserialize("str", response.headers.get("Operation-Location"))
+
+ deserialized = response.iter_bytes()
+
+ if cls:
+ return cls(pipeline_response, deserialized, response_headers) # type: ignore
+
+ return deserialized # type: ignore
+
+ @distributed_trace
+ def begin_export(
+ self,
+ project_name: str,
+ *,
+ string_index_type: Union[str, _models.StringIndexType],
+ exported_project_format: Optional[Union[str, _models.ExportedProjectFormat]] = None,
+ asset_kind: Optional[str] = None,
+ trained_model_label: Optional[str] = None,
+ **kwargs: Any
+ ) -> LROPoller[None]:
+ """Triggers a job to export a project's data.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :keyword string_index_type: Specifies the method used to interpret string offsets. For
+ additional
+ information see https://aka.ms/text-analytics-offsets. "Utf16CodeUnit" Required.
+ :paramtype string_index_type: str or
+ ~azure.ai.language.authoring.analyzeconversations.models.StringIndexType
+ :keyword exported_project_format: The format of the exported project file to use. Known values
+ are: "Conversation" and "Luis". Default value is None.
+ :paramtype exported_project_format: str or
+ ~azure.ai.language.authoring.analyzeconversations.models.ExportedProjectFormat
+ :keyword asset_kind: Kind of asset to export. Default value is None.
+ :paramtype asset_kind: str
+ :keyword trained_model_label: Trained model label to export. If the trainedModelLabel is null,
+ the default behavior is to export the current working copy. Default value is None.
+ :paramtype trained_model_label: str
+ :return: An instance of LROPoller that returns None
+ :rtype: ~azure.core.polling.LROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = kwargs.pop("params", {}) or {}
+
+ cls: ClsType[None] = 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._export_initial(
+ project_name=project_name,
+ string_index_type=string_index_type,
+ exported_project_format=exported_project_format,
+ asset_kind=asset_kind,
+ trained_model_label=trained_model_label,
+ 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): # pylint: disable=inconsistent-return-statements
+ if cls:
+ return cls(pipeline_response, None, {}) # type: ignore
+
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+
+ 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[None].from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return LROPoller[None](self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ def _import_method_initial(
+ self,
+ project_name: str,
+ body: Union[_models.ConversationalAnalysisAuthoringExportedProject, JSON, IO[bytes]],
+ *,
+ exported_project_format: Optional[Union[str, _models.ExportedProjectFormat]] = None,
+ **kwargs: Any
+ ) -> Iterator[bytes]:
+ error_map: MutableMapping = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _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[Iterator[bytes]] = kwargs.pop("cls", None)
+
+ content_type = content_type or "application/json"
+ _content = None
+ if isinstance(body, (IOBase, bytes)):
+ _content = body
+ else:
+ _content = json.dumps(body, cls=SdkJSONEncoder, exclude_readonly=True) # type: ignore
+
+ _request = build_conversational_analysis_authoring_import_method_request(
+ project_name=project_name,
+ exported_project_format=exported_project_format,
+ content_type=content_type,
+ api_version=self._config.api_version,
+ content=_content,
+ headers=_headers,
+ params=_params,
+ )
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _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 [202]:
+ 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ response_headers = {}
+ response_headers["Operation-Location"] = self._deserialize("str", response.headers.get("Operation-Location"))
+
+ deserialized = response.iter_bytes()
+
+ if cls:
+ return cls(pipeline_response, deserialized, response_headers) # type: ignore
+
+ return deserialized # type: ignore
+
+ @overload
+ def begin_import_method(
+ self,
+ project_name: str,
+ body: _models.ConversationalAnalysisAuthoringExportedProject,
+ *,
+ exported_project_format: Optional[Union[str, _models.ExportedProjectFormat]] = None,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> LROPoller[None]:
+ """Triggers a job to import a project. If a project with the same name already
+ exists, the data of that project is replaced.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param body: The project data to import. Required.
+ :type body:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringExportedProject
+ :keyword exported_project_format: The format of the exported project file to use. Known values
+ are: "Conversation" and "Luis". Default value is None.
+ :paramtype exported_project_format: str or
+ ~azure.ai.language.authoring.analyzeconversations.models.ExportedProjectFormat
+ :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 LROPoller that returns None
+ :rtype: ~azure.core.polling.LROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ def begin_import_method(
+ self,
+ project_name: str,
+ body: JSON,
+ *,
+ exported_project_format: Optional[Union[str, _models.ExportedProjectFormat]] = None,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> LROPoller[None]:
+ """Triggers a job to import a project. If a project with the same name already
+ exists, the data of that project is replaced.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param body: The project data to import. Required.
+ :type body: JSON
+ :keyword exported_project_format: The format of the exported project file to use. Known values
+ are: "Conversation" and "Luis". Default value is None.
+ :paramtype exported_project_format: str or
+ ~azure.ai.language.authoring.analyzeconversations.models.ExportedProjectFormat
+ :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 LROPoller that returns None
+ :rtype: ~azure.core.polling.LROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ def begin_import_method(
+ self,
+ project_name: str,
+ body: IO[bytes],
+ *,
+ exported_project_format: Optional[Union[str, _models.ExportedProjectFormat]] = None,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> LROPoller[None]:
+ """Triggers a job to import a project. If a project with the same name already
+ exists, the data of that project is replaced.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param body: The project data to import. Required.
+ :type body: IO[bytes]
+ :keyword exported_project_format: The format of the exported project file to use. Known values
+ are: "Conversation" and "Luis". Default value is None.
+ :paramtype exported_project_format: str or
+ ~azure.ai.language.authoring.analyzeconversations.models.ExportedProjectFormat
+ :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 LROPoller that returns None
+ :rtype: ~azure.core.polling.LROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @distributed_trace
+ def begin_import_method(
+ self,
+ project_name: str,
+ body: Union[_models.ConversationalAnalysisAuthoringExportedProject, JSON, IO[bytes]],
+ *,
+ exported_project_format: Optional[Union[str, _models.ExportedProjectFormat]] = None,
+ **kwargs: Any
+ ) -> LROPoller[None]:
+ """Triggers a job to import a project. If a project with the same name already
+ exists, the data of that project is replaced.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param body: The project data to import. Is one of the following types:
+ ConversationalAnalysisAuthoringExportedProject, JSON, IO[bytes] Required.
+ :type body:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringExportedProject
+ or JSON or IO[bytes]
+ :keyword exported_project_format: The format of the exported project file to use. Known values
+ are: "Conversation" and "Luis". Default value is None.
+ :paramtype exported_project_format: str or
+ ~azure.ai.language.authoring.analyzeconversations.models.ExportedProjectFormat
+ :return: An instance of LROPoller that returns None
+ :rtype: ~azure.core.polling.LROPoller[None]
+ :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[None] = 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._import_method_initial(
+ project_name=project_name,
+ body=body,
+ exported_project_format=exported_project_format,
+ 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): # pylint: disable=inconsistent-return-statements
+ if cls:
+ return cls(pipeline_response, None, {}) # type: ignore
+
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+
+ 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[None].from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return LROPoller[None](self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ def _train_initial(
+ self,
+ project_name: str,
+ body: Union[_models.ConversationalAnalysisAuthoringTrainingJobOptions, JSON, IO[bytes]],
+ **kwargs: Any
+ ) -> Iterator[bytes]:
+ error_map: MutableMapping = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _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[Iterator[bytes]] = kwargs.pop("cls", None)
+
+ content_type = content_type or "application/json"
+ _content = None
+ if isinstance(body, (IOBase, bytes)):
+ _content = body
+ else:
+ _content = json.dumps(body, cls=SdkJSONEncoder, exclude_readonly=True) # type: ignore
+
+ _request = build_conversational_analysis_authoring_train_request(
+ project_name=project_name,
+ content_type=content_type,
+ api_version=self._config.api_version,
+ content=_content,
+ headers=_headers,
+ params=_params,
+ )
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _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 [202]:
+ 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ response_headers = {}
+ response_headers["Operation-Location"] = self._deserialize("str", response.headers.get("Operation-Location"))
+
+ deserialized = response.iter_bytes()
+
+ if cls:
+ return cls(pipeline_response, deserialized, response_headers) # type: ignore
+
+ return deserialized # type: ignore
+
+ @overload
+ def begin_train(
+ self,
+ project_name: str,
+ body: _models.ConversationalAnalysisAuthoringTrainingJobOptions,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> LROPoller[_models.ConversationalAnalysisAuthoringTrainingJobResult]:
+ # pylint: disable=line-too-long
+ """Triggers a training job for a project.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param body: The training input parameters. Required.
+ :type body:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringTrainingJobOptions
+ :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 LROPoller that returns
+ ConversationalAnalysisAuthoringTrainingJobResult. The
+ ConversationalAnalysisAuthoringTrainingJobResult is compatible with MutableMapping
+ :rtype:
+ ~azure.core.polling.LROPoller[~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringTrainingJobResult]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ def begin_train(
+ self, project_name: str, body: JSON, *, content_type: str = "application/json", **kwargs: Any
+ ) -> LROPoller[_models.ConversationalAnalysisAuthoringTrainingJobResult]:
+ # pylint: disable=line-too-long
+ """Triggers a training job for a project.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param body: The training input 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: An instance of LROPoller that returns
+ ConversationalAnalysisAuthoringTrainingJobResult. The
+ ConversationalAnalysisAuthoringTrainingJobResult is compatible with MutableMapping
+ :rtype:
+ ~azure.core.polling.LROPoller[~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringTrainingJobResult]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ def begin_train(
+ self, project_name: str, body: IO[bytes], *, content_type: str = "application/json", **kwargs: Any
+ ) -> LROPoller[_models.ConversationalAnalysisAuthoringTrainingJobResult]:
+ # pylint: disable=line-too-long
+ """Triggers a training job for a project.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param body: The training input 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: An instance of LROPoller that returns
+ ConversationalAnalysisAuthoringTrainingJobResult. The
+ ConversationalAnalysisAuthoringTrainingJobResult is compatible with MutableMapping
+ :rtype:
+ ~azure.core.polling.LROPoller[~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringTrainingJobResult]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @distributed_trace
+ def begin_train(
+ self,
+ project_name: str,
+ body: Union[_models.ConversationalAnalysisAuthoringTrainingJobOptions, JSON, IO[bytes]],
+ **kwargs: Any
+ ) -> LROPoller[_models.ConversationalAnalysisAuthoringTrainingJobResult]:
+ # pylint: disable=line-too-long
+ """Triggers a training job for a project.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param body: The training input parameters. Is one of the following types:
+ ConversationalAnalysisAuthoringTrainingJobOptions, JSON, IO[bytes] Required.
+ :type body:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringTrainingJobOptions
+ or JSON or IO[bytes]
+ :return: An instance of LROPoller that returns
+ ConversationalAnalysisAuthoringTrainingJobResult. The
+ ConversationalAnalysisAuthoringTrainingJobResult is compatible with MutableMapping
+ :rtype:
+ ~azure.core.polling.LROPoller[~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringTrainingJobResult]
+ :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.ConversationalAnalysisAuthoringTrainingJobResult] = 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._train_initial(
+ project_name=project_name,
+ 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)
+
+ def get_long_running_output(pipeline_response):
+ response_headers = {}
+ response = pipeline_response.http_response
+ response_headers["Operation-Location"] = self._deserialize(
+ "str", response.headers.get("Operation-Location")
+ )
+
+ deserialized = _deserialize(
+ _models.ConversationalAnalysisAuthoringTrainingJobResult, response.json().get("result")
+ )
+ 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"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+
+ 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.ConversationalAnalysisAuthoringTrainingJobResult].from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return LROPoller[_models.ConversationalAnalysisAuthoringTrainingJobResult](
+ self._client, raw_result, get_long_running_output, polling_method # type: ignore
+ )
+
+ @distributed_trace
+ @api_version_validation(
+ method_added_on="2023-04-15-preview",
+ params_added_on={"2023-04-15-preview": ["api_version", "project_name", "job_id", "accept"]},
+ )
+ def get_copy_project_status(
+ self, project_name: str, job_id: str, **kwargs: Any
+ ) -> _models.GetCopyProjectStatusResponse:
+ """Gets the status of an existing copy project job.
+
+ :param project_name: The new project name. Required.
+ :type project_name: str
+ :param job_id: The job ID. Required.
+ :type job_id: str
+ :return: GetCopyProjectStatusResponse. The GetCopyProjectStatusResponse is compatible with
+ MutableMapping
+ :rtype: ~azure.ai.language.authoring.analyzeconversations.models.GetCopyProjectStatusResponse
+ :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[_models.GetCopyProjectStatusResponse] = kwargs.pop("cls", None)
+
+ _request = build_conversational_analysis_authoring_get_copy_project_status_request(
+ project_name=project_name,
+ job_id=job_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"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _stream = kwargs.pop("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
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ if _stream:
+ deserialized = response.iter_bytes()
+ else:
+ deserialized = _deserialize(_models.GetCopyProjectStatusResponse, response.json())
+
+ if cls:
+ return cls(pipeline_response, deserialized, {}) # type: ignore
+
+ return deserialized # type: ignore
+
+ @distributed_trace
+ def list_deployments(
+ self, project_name: str, *, top: Optional[int] = None, skip: Optional[int] = None, **kwargs: Any
+ ) -> Iterable["_models.ConversationalAnalysisAuthoringProjectDeployment"]:
+ # pylint: disable=line-too-long
+ """Lists the deployments belonging to a project.
+
+ :param project_name: The new project name. Required.
+ :type project_name: str
+ :keyword top: The number of result items to return. Default value is None.
+ :paramtype top: int
+ :keyword skip: The number of result items to skip. Default value is None.
+ :paramtype skip: int
+ :return: An iterator like instance of ConversationalAnalysisAuthoringProjectDeployment
+ :rtype:
+ ~azure.core.paging.ItemPaged[~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringProjectDeployment]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = kwargs.pop("params", {}) or {}
+
+ maxpagesize = kwargs.pop("maxpagesize", None)
+ cls: ClsType[List[_models.ConversationalAnalysisAuthoringProjectDeployment]] = 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_conversational_analysis_authoring_list_deployments_request(
+ project_name=project_name,
+ top=top,
+ skip=skip,
+ maxpagesize=maxpagesize,
+ api_version=self._config.api_version,
+ headers=_headers,
+ params=_params,
+ )
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _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"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _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.ConversationalAnalysisAuthoringProjectDeployment], 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ return pipeline_response
+
+ return ItemPaged(get_next, extract_data)
+
+ def _swap_deployments_initial(
+ self,
+ project_name: str,
+ body: Union[_models.ConversationalAnalysisAuthoringSwapDeploymentsOptions, JSON, IO[bytes]],
+ **kwargs: Any
+ ) -> Iterator[bytes]:
+ error_map: MutableMapping = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _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[Iterator[bytes]] = kwargs.pop("cls", None)
+
+ content_type = content_type or "application/json"
+ _content = None
+ if isinstance(body, (IOBase, bytes)):
+ _content = body
+ else:
+ _content = json.dumps(body, cls=SdkJSONEncoder, exclude_readonly=True) # type: ignore
+
+ _request = build_conversational_analysis_authoring_swap_deployments_request(
+ project_name=project_name,
+ content_type=content_type,
+ api_version=self._config.api_version,
+ content=_content,
+ headers=_headers,
+ params=_params,
+ )
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _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 [202]:
+ 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ response_headers = {}
+ response_headers["Operation-Location"] = self._deserialize("str", response.headers.get("Operation-Location"))
+
+ deserialized = response.iter_bytes()
+
+ if cls:
+ return cls(pipeline_response, deserialized, response_headers) # type: ignore
+
+ return deserialized # type: ignore
+
+ @overload
+ def begin_swap_deployments(
+ self,
+ project_name: str,
+ body: _models.ConversationalAnalysisAuthoringSwapDeploymentsOptions,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> LROPoller[None]:
+ """Swaps two existing deployments with each other.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param body: The job object to swap two deployments. Required.
+ :type body:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringSwapDeploymentsOptions
+ :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 LROPoller that returns None
+ :rtype: ~azure.core.polling.LROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ def begin_swap_deployments(
+ self, project_name: str, body: JSON, *, content_type: str = "application/json", **kwargs: Any
+ ) -> LROPoller[None]:
+ """Swaps two existing deployments with each other.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param body: The job object to swap two deployments. 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: An instance of LROPoller that returns None
+ :rtype: ~azure.core.polling.LROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ def begin_swap_deployments(
+ self, project_name: str, body: IO[bytes], *, content_type: str = "application/json", **kwargs: Any
+ ) -> LROPoller[None]:
+ """Swaps two existing deployments with each other.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param body: The job object to swap two deployments. 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: An instance of LROPoller that returns None
+ :rtype: ~azure.core.polling.LROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @distributed_trace
+ def begin_swap_deployments(
+ self,
+ project_name: str,
+ body: Union[_models.ConversationalAnalysisAuthoringSwapDeploymentsOptions, JSON, IO[bytes]],
+ **kwargs: Any
+ ) -> LROPoller[None]:
+ """Swaps two existing deployments with each other.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param body: The job object to swap two deployments. Is one of the following types:
+ ConversationalAnalysisAuthoringSwapDeploymentsOptions, JSON, IO[bytes] Required.
+ :type body:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringSwapDeploymentsOptions
+ or JSON or IO[bytes]
+ :return: An instance of LROPoller that returns None
+ :rtype: ~azure.core.polling.LROPoller[None]
+ :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[None] = 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._swap_deployments_initial(
+ project_name=project_name,
+ 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)
+
+ def get_long_running_output(pipeline_response): # pylint: disable=inconsistent-return-statements
+ if cls:
+ return cls(pipeline_response, None, {}) # type: ignore
+
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+
+ 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[None].from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return LROPoller[None](self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ @distributed_trace
+ def get_deployment(self, project_name: str, deployment_name: str, **kwargs: Any) -> _models.GetDeploymentResponse:
+ """Gets the details of a deployment.
+
+ :param project_name: The new project name. Required.
+ :type project_name: str
+ :param deployment_name: Represents deployment name. Required.
+ :type deployment_name: str
+ :return: GetDeploymentResponse. The GetDeploymentResponse is compatible with MutableMapping
+ :rtype: ~azure.ai.language.authoring.analyzeconversations.models.GetDeploymentResponse
+ :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[_models.GetDeploymentResponse] = kwargs.pop("cls", None)
+
+ _request = build_conversational_analysis_authoring_get_deployment_request(
+ project_name=project_name,
+ deployment_name=deployment_name,
+ api_version=self._config.api_version,
+ headers=_headers,
+ params=_params,
+ )
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _stream = kwargs.pop("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
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ if _stream:
+ deserialized = response.iter_bytes()
+ else:
+ deserialized = _deserialize(_models.GetDeploymentResponse, response.json())
+
+ if cls:
+ return cls(pipeline_response, deserialized, {}) # type: ignore
+
+ return deserialized # type: ignore
+
+ def _deploy_project_initial(
+ self,
+ project_name: str,
+ deployment_name: str,
+ body: Union[_models.ConversationalAnalysisAuthoringCreateDeploymentOptions, JSON, IO[bytes]],
+ **kwargs: Any
+ ) -> Iterator[bytes]:
+ error_map: MutableMapping = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _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[Iterator[bytes]] = kwargs.pop("cls", None)
+
+ content_type = content_type or "application/json"
+ _content = None
+ if isinstance(body, (IOBase, bytes)):
+ _content = body
+ else:
+ _content = json.dumps(body, cls=SdkJSONEncoder, exclude_readonly=True) # type: ignore
+
+ _request = build_conversational_analysis_authoring_deploy_project_request(
+ project_name=project_name,
+ deployment_name=deployment_name,
+ content_type=content_type,
+ api_version=self._config.api_version,
+ content=_content,
+ headers=_headers,
+ params=_params,
+ )
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _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 [202]:
+ 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ response_headers = {}
+ response_headers["Operation-Location"] = self._deserialize("str", response.headers.get("Operation-Location"))
+
+ deserialized = response.iter_bytes()
+
+ if cls:
+ return cls(pipeline_response, deserialized, response_headers) # type: ignore
+
+ return deserialized # type: ignore
+
+ @overload
+ def begin_deploy_project(
+ self,
+ project_name: str,
+ deployment_name: str,
+ body: _models.ConversationalAnalysisAuthoringCreateDeploymentOptions,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> LROPoller[None]:
+ """Creates a new deployment or replaces an existing one.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param deployment_name: The name of the specific deployment of the project to use. Required.
+ :type deployment_name: str
+ :param body: The new deployment info. Required.
+ :type body:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringCreateDeploymentOptions
+ :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 LROPoller that returns None
+ :rtype: ~azure.core.polling.LROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ def begin_deploy_project(
+ self,
+ project_name: str,
+ deployment_name: str,
+ body: JSON,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> LROPoller[None]:
+ """Creates a new deployment or replaces an existing one.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param deployment_name: The name of the specific deployment of the project to use. Required.
+ :type deployment_name: str
+ :param body: The new deployment info. 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: An instance of LROPoller that returns None
+ :rtype: ~azure.core.polling.LROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ def begin_deploy_project(
+ self,
+ project_name: str,
+ deployment_name: str,
+ body: IO[bytes],
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> LROPoller[None]:
+ """Creates a new deployment or replaces an existing one.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param deployment_name: The name of the specific deployment of the project to use. Required.
+ :type deployment_name: str
+ :param body: The new deployment info. 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: An instance of LROPoller that returns None
+ :rtype: ~azure.core.polling.LROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @distributed_trace
+ def begin_deploy_project(
+ self,
+ project_name: str,
+ deployment_name: str,
+ body: Union[_models.ConversationalAnalysisAuthoringCreateDeploymentOptions, JSON, IO[bytes]],
+ **kwargs: Any
+ ) -> LROPoller[None]:
+ """Creates a new deployment or replaces an existing one.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param deployment_name: The name of the specific deployment of the project to use. Required.
+ :type deployment_name: str
+ :param body: The new deployment info. Is one of the following types:
+ ConversationalAnalysisAuthoringCreateDeploymentOptions, JSON, IO[bytes] Required.
+ :type body:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringCreateDeploymentOptions
+ or JSON or IO[bytes]
+ :return: An instance of LROPoller that returns None
+ :rtype: ~azure.core.polling.LROPoller[None]
+ :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[None] = 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._deploy_project_initial(
+ project_name=project_name,
+ deployment_name=deployment_name,
+ 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)
+
+ def get_long_running_output(pipeline_response): # pylint: disable=inconsistent-return-statements
+ if cls:
+ return cls(pipeline_response, None, {}) # type: ignore
+
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+
+ 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[None].from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return LROPoller[None](self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ def _delete_deployment_initial(self, project_name: str, deployment_name: str, **kwargs: Any) -> Iterator[bytes]:
+ 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_conversational_analysis_authoring_delete_deployment_request(
+ project_name=project_name,
+ deployment_name=deployment_name,
+ api_version=self._config.api_version,
+ headers=_headers,
+ params=_params,
+ )
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _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 [202]:
+ 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ response_headers = {}
+ response_headers["Operation-Location"] = self._deserialize("str", response.headers.get("Operation-Location"))
+
+ deserialized = response.iter_bytes()
+
+ if cls:
+ return cls(pipeline_response, deserialized, response_headers) # type: ignore
+
+ return deserialized # type: ignore
+
+ @distributed_trace
+ def begin_delete_deployment(self, project_name: str, deployment_name: str, **kwargs: Any) -> LROPoller[None]:
+ """Deletes a project deployment.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param deployment_name: The name of the specific deployment of the project to use. Required.
+ :type deployment_name: str
+ :return: An instance of LROPoller that returns None
+ :rtype: ~azure.core.polling.LROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = kwargs.pop("params", {}) or {}
+
+ cls: ClsType[None] = 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._delete_deployment_initial(
+ project_name=project_name,
+ deployment_name=deployment_name,
+ 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): # pylint: disable=inconsistent-return-statements
+ if cls:
+ return cls(pipeline_response, None, {}) # type: ignore
+
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+
+ 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[None].from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return LROPoller[None](self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ @api_version_validation(
+ method_added_on="2023-04-15-preview",
+ params_added_on={
+ "2023-04-15-preview": ["api_version", "project_name", "deployment_name", "content_type", "accept"]
+ },
+ ) # pylint: disable=name-too-long
+ def _delete_deployment_from_resources_initial( # pylint: disable=name-too-long
+ self,
+ project_name: str,
+ deployment_name: str,
+ body: Union[_models.ConversationalAnalysisAuthoringDeleteDeploymentOptions, JSON, IO[bytes]],
+ **kwargs: Any
+ ) -> Iterator[bytes]:
+ error_map: MutableMapping = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _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[Iterator[bytes]] = kwargs.pop("cls", None)
+
+ content_type = content_type or "application/json"
+ _content = None
+ if isinstance(body, (IOBase, bytes)):
+ _content = body
+ else:
+ _content = json.dumps(body, cls=SdkJSONEncoder, exclude_readonly=True) # type: ignore
+
+ _request = build_conversational_analysis_authoring_delete_deployment_from_resources_request(
+ project_name=project_name,
+ deployment_name=deployment_name,
+ content_type=content_type,
+ api_version=self._config.api_version,
+ content=_content,
+ headers=_headers,
+ params=_params,
+ )
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _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 [202]:
+ 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ response_headers = {}
+ response_headers["Operation-Location"] = self._deserialize("str", response.headers.get("Operation-Location"))
+
+ deserialized = response.iter_bytes()
+
+ if cls:
+ return cls(pipeline_response, deserialized, response_headers) # type: ignore
+
+ return deserialized # type: ignore
+
+ @overload
+ def begin_delete_deployment_from_resources(
+ self,
+ project_name: str,
+ deployment_name: str,
+ body: _models.ConversationalAnalysisAuthoringDeleteDeploymentOptions,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> LROPoller[None]:
+ """Deletes a project deployment from the specified assigned resources.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param deployment_name: The name of the specific deployment of the project to use. Required.
+ :type deployment_name: str
+ :param body: The options for deleting the deployment. Required.
+ :type body:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringDeleteDeploymentOptions
+ :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 LROPoller that returns None
+ :rtype: ~azure.core.polling.LROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ def begin_delete_deployment_from_resources(
+ self,
+ project_name: str,
+ deployment_name: str,
+ body: JSON,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> LROPoller[None]:
+ """Deletes a project deployment from the specified assigned resources.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param deployment_name: The name of the specific deployment of the project to use. Required.
+ :type deployment_name: str
+ :param body: The options for deleting the deployment. 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: An instance of LROPoller that returns None
+ :rtype: ~azure.core.polling.LROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ def begin_delete_deployment_from_resources(
+ self,
+ project_name: str,
+ deployment_name: str,
+ body: IO[bytes],
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> LROPoller[None]:
+ """Deletes a project deployment from the specified assigned resources.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param deployment_name: The name of the specific deployment of the project to use. Required.
+ :type deployment_name: str
+ :param body: The options for deleting the deployment. 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: An instance of LROPoller that returns None
+ :rtype: ~azure.core.polling.LROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @distributed_trace
+ @api_version_validation(
+ method_added_on="2023-04-15-preview",
+ params_added_on={
+ "2023-04-15-preview": ["api_version", "project_name", "deployment_name", "content_type", "accept"]
+ },
+ )
+ def begin_delete_deployment_from_resources(
+ self,
+ project_name: str,
+ deployment_name: str,
+ body: Union[_models.ConversationalAnalysisAuthoringDeleteDeploymentOptions, JSON, IO[bytes]],
+ **kwargs: Any
+ ) -> LROPoller[None]:
+ """Deletes a project deployment from the specified assigned resources.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param deployment_name: The name of the specific deployment of the project to use. Required.
+ :type deployment_name: str
+ :param body: The options for deleting the deployment. Is one of the following types:
+ ConversationalAnalysisAuthoringDeleteDeploymentOptions, JSON, IO[bytes] Required.
+ :type body:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringDeleteDeploymentOptions
+ or JSON or IO[bytes]
+ :return: An instance of LROPoller that returns None
+ :rtype: ~azure.core.polling.LROPoller[None]
+ :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[None] = 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._delete_deployment_from_resources_initial(
+ project_name=project_name,
+ deployment_name=deployment_name,
+ 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)
+
+ def get_long_running_output(pipeline_response): # pylint: disable=inconsistent-return-statements
+ if cls:
+ return cls(pipeline_response, None, {}) # type: ignore
+
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+
+ 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[None].from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return LROPoller[None](self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ @distributed_trace
+ @api_version_validation(
+ method_added_on="2023-04-15-preview",
+ params_added_on={"2023-04-15-preview": ["api_version", "project_name", "deployment_name", "job_id", "accept"]},
+ ) # pylint: disable=name-too-long
+ def get_deployment_delete_from_resources_status( # pylint: disable=name-too-long
+ self, project_name: str, deployment_name: str, job_id: str, **kwargs: Any
+ ) -> _models.GetDeploymentDeleteFromResourcesStatusResponse:
+ """Gets the status of an existing delete deployment from specific resources job.
+
+ :param project_name: The new project name. Required.
+ :type project_name: str
+ :param deployment_name: Represents deployment name. Required.
+ :type deployment_name: str
+ :param job_id: The job ID. Required.
+ :type job_id: str
+ :return: GetDeploymentDeleteFromResourcesStatusResponse. The
+ GetDeploymentDeleteFromResourcesStatusResponse is compatible with MutableMapping
+ :rtype:
+ ~azure.ai.language.authoring.analyzeconversations.models.GetDeploymentDeleteFromResourcesStatusResponse
+ :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[_models.GetDeploymentDeleteFromResourcesStatusResponse] = kwargs.pop("cls", None)
+
+ _request = build_conversational_analysis_authoring_get_deployment_delete_from_resources_status_request(
+ project_name=project_name,
+ deployment_name=deployment_name,
+ job_id=job_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"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _stream = kwargs.pop("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
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ if _stream:
+ deserialized = response.iter_bytes()
+ else:
+ deserialized = _deserialize(_models.GetDeploymentDeleteFromResourcesStatusResponse, response.json())
+
+ if cls:
+ return cls(pipeline_response, deserialized, {}) # type: ignore
+
+ return deserialized # type: ignore
+
+ @distributed_trace
+ def get_deployment_status(
+ self, project_name: str, deployment_name: str, job_id: str, **kwargs: Any
+ ) -> _models.GetDeploymentStatusResponse:
+ """Gets the status of an existing deployment job.
+
+ :param project_name: The new project name. Required.
+ :type project_name: str
+ :param deployment_name: Represents deployment name. Required.
+ :type deployment_name: str
+ :param job_id: The job ID. Required.
+ :type job_id: str
+ :return: GetDeploymentStatusResponse. The GetDeploymentStatusResponse is compatible with
+ MutableMapping
+ :rtype: ~azure.ai.language.authoring.analyzeconversations.models.GetDeploymentStatusResponse
+ :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[_models.GetDeploymentStatusResponse] = kwargs.pop("cls", None)
+
+ _request = build_conversational_analysis_authoring_get_deployment_status_request(
+ project_name=project_name,
+ deployment_name=deployment_name,
+ job_id=job_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"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _stream = kwargs.pop("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
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ if _stream:
+ deserialized = response.iter_bytes()
+ else:
+ deserialized = _deserialize(_models.GetDeploymentStatusResponse, response.json())
+
+ if cls:
+ return cls(pipeline_response, deserialized, {}) # type: ignore
+
+ return deserialized # type: ignore
+
+ @distributed_trace
+ def get_swap_deployments_status(
+ self, project_name: str, job_id: str, **kwargs: Any
+ ) -> _models.GetSwapDeploymentsStatusResponse:
+ """Gets the status of an existing swap deployment job.
+
+ :param project_name: The new project name. Required.
+ :type project_name: str
+ :param job_id: The job ID. Required.
+ :type job_id: str
+ :return: GetSwapDeploymentsStatusResponse. The GetSwapDeploymentsStatusResponse is compatible
+ with MutableMapping
+ :rtype:
+ ~azure.ai.language.authoring.analyzeconversations.models.GetSwapDeploymentsStatusResponse
+ :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[_models.GetSwapDeploymentsStatusResponse] = kwargs.pop("cls", None)
+
+ _request = build_conversational_analysis_authoring_get_swap_deployments_status_request(
+ project_name=project_name,
+ job_id=job_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"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _stream = kwargs.pop("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
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ if _stream:
+ deserialized = response.iter_bytes()
+ else:
+ deserialized = _deserialize(_models.GetSwapDeploymentsStatusResponse, response.json())
+
+ if cls:
+ return cls(pipeline_response, deserialized, {}) # type: ignore
+
+ return deserialized # type: ignore
+
+ @distributed_trace
+ def get_export_status(self, project_name: str, job_id: str, **kwargs: Any) -> _models.GetExportStatusResponse:
+ """Gets the status of an export job. Once job completes, returns the project
+ metadata, and assets.
+
+ :param project_name: The new project name. Required.
+ :type project_name: str
+ :param job_id: The job ID. Required.
+ :type job_id: str
+ :return: GetExportStatusResponse. The GetExportStatusResponse is compatible with MutableMapping
+ :rtype: ~azure.ai.language.authoring.analyzeconversations.models.GetExportStatusResponse
+ :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[_models.GetExportStatusResponse] = kwargs.pop("cls", None)
+
+ _request = build_conversational_analysis_authoring_get_export_status_request(
+ project_name=project_name,
+ job_id=job_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"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _stream = kwargs.pop("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
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ if _stream:
+ deserialized = response.iter_bytes()
+ else:
+ deserialized = _deserialize(_models.GetExportStatusResponse, response.json())
+
+ if cls:
+ return cls(pipeline_response, deserialized, {}) # type: ignore
+
+ return deserialized # type: ignore
+
+ @distributed_trace
+ def get_import_status(self, project_name: str, job_id: str, **kwargs: Any) -> _models.GetImportStatusResponse:
+ """Gets the status for an import.
+
+ :param project_name: The new project name. Required.
+ :type project_name: str
+ :param job_id: The job ID. Required.
+ :type job_id: str
+ :return: GetImportStatusResponse. The GetImportStatusResponse is compatible with MutableMapping
+ :rtype: ~azure.ai.language.authoring.analyzeconversations.models.GetImportStatusResponse
+ :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[_models.GetImportStatusResponse] = kwargs.pop("cls", None)
+
+ _request = build_conversational_analysis_authoring_get_import_status_request(
+ project_name=project_name,
+ job_id=job_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"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _stream = kwargs.pop("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
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ if _stream:
+ deserialized = response.iter_bytes()
+ else:
+ deserialized = _deserialize(_models.GetImportStatusResponse, response.json())
+
+ if cls:
+ return cls(pipeline_response, deserialized, {}) # type: ignore
+
+ return deserialized # type: ignore
+
+ @distributed_trace
+ def list_trained_models(
+ self, project_name: str, *, top: Optional[int] = None, skip: Optional[int] = None, **kwargs: Any
+ ) -> Iterable["_models.ConversationalAnalysisAuthoringProjectTrainedModel"]:
+ # pylint: disable=line-too-long
+ """Lists the trained models belonging to a project.
+
+ :param project_name: The new project name. Required.
+ :type project_name: str
+ :keyword top: The number of result items to return. Default value is None.
+ :paramtype top: int
+ :keyword skip: The number of result items to skip. Default value is None.
+ :paramtype skip: int
+ :return: An iterator like instance of ConversationalAnalysisAuthoringProjectTrainedModel
+ :rtype:
+ ~azure.core.paging.ItemPaged[~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringProjectTrainedModel]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = kwargs.pop("params", {}) or {}
+
+ maxpagesize = kwargs.pop("maxpagesize", None)
+ cls: ClsType[List[_models.ConversationalAnalysisAuthoringProjectTrainedModel]] = 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_conversational_analysis_authoring_list_trained_models_request(
+ project_name=project_name,
+ top=top,
+ skip=skip,
+ maxpagesize=maxpagesize,
+ api_version=self._config.api_version,
+ headers=_headers,
+ params=_params,
+ )
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _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"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _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.ConversationalAnalysisAuthoringProjectTrainedModel], 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ return pipeline_response
+
+ return ItemPaged(get_next, extract_data)
+
+ @distributed_trace
+ def get_trained_model(
+ self, project_name: str, trained_model_label: str, **kwargs: Any
+ ) -> _models.GetTrainedModelResponse:
+ """Gets the details of a trained model.
+
+ :param project_name: The new project name. Required.
+ :type project_name: str
+ :param trained_model_label: The trained model label. Required.
+ :type trained_model_label: str
+ :return: GetTrainedModelResponse. The GetTrainedModelResponse is compatible with MutableMapping
+ :rtype: ~azure.ai.language.authoring.analyzeconversations.models.GetTrainedModelResponse
+ :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[_models.GetTrainedModelResponse] = kwargs.pop("cls", None)
+
+ _request = build_conversational_analysis_authoring_get_trained_model_request(
+ project_name=project_name,
+ trained_model_label=trained_model_label,
+ api_version=self._config.api_version,
+ headers=_headers,
+ params=_params,
+ )
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _stream = kwargs.pop("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
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ if _stream:
+ deserialized = response.iter_bytes()
+ else:
+ deserialized = _deserialize(_models.GetTrainedModelResponse, response.json())
+
+ if cls:
+ return cls(pipeline_response, deserialized, {}) # type: ignore
+
+ return deserialized # type: ignore
+
+ @distributed_trace
+ def delete_trained_model( # pylint: disable=inconsistent-return-statements
+ self, project_name: str, trained_model_label: str, **kwargs: Any
+ ) -> None:
+ """Deletes an existing trained model.
+
+ :param project_name: The new project name. Required.
+ :type project_name: str
+ :param trained_model_label: The trained model label. Required.
+ :type trained_model_label: 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_conversational_analysis_authoring_delete_trained_model_request(
+ project_name=project_name,
+ trained_model_label=trained_model_label,
+ api_version=self._config.api_version,
+ headers=_headers,
+ params=_params,
+ )
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ if cls:
+ return cls(pipeline_response, None, {}) # type: ignore
+
+ @api_version_validation(
+ method_added_on="2023-04-15-preview",
+ params_added_on={
+ "2023-04-15-preview": ["api_version", "project_name", "trained_model_label", "content_type", "accept"]
+ },
+ )
+ def _evaluate_model_initial(
+ self,
+ project_name: str,
+ trained_model_label: str,
+ body: Union[_models.ConversationalAnalysisAuthoringEvaluationOptions, JSON, IO[bytes]],
+ **kwargs: Any
+ ) -> Iterator[bytes]:
+ error_map: MutableMapping = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _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[Iterator[bytes]] = kwargs.pop("cls", None)
+
+ content_type = content_type or "application/json"
+ _content = None
+ if isinstance(body, (IOBase, bytes)):
+ _content = body
+ else:
+ _content = json.dumps(body, cls=SdkJSONEncoder, exclude_readonly=True) # type: ignore
+
+ _request = build_conversational_analysis_authoring_evaluate_model_request(
+ project_name=project_name,
+ trained_model_label=trained_model_label,
+ content_type=content_type,
+ api_version=self._config.api_version,
+ content=_content,
+ headers=_headers,
+ params=_params,
+ )
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _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 [202]:
+ 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ response_headers = {}
+ response_headers["Operation-Location"] = self._deserialize("str", response.headers.get("Operation-Location"))
+
+ deserialized = response.iter_bytes()
+
+ if cls:
+ return cls(pipeline_response, deserialized, response_headers) # type: ignore
+
+ return deserialized # type: ignore
+
+ @overload
+ def begin_evaluate_model(
+ self,
+ project_name: str,
+ trained_model_label: str,
+ body: _models.ConversationalAnalysisAuthoringEvaluationOptions,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> LROPoller[_models.ConversationalAnalysisAuthoringEvaluationJobResult]:
+ # pylint: disable=line-too-long
+ """Triggers evaluation operation on a trained model.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param trained_model_label: The trained model label. Required.
+ :type trained_model_label: str
+ :param body: The training input parameters. Required.
+ :type body:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringEvaluationOptions
+ :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 LROPoller that returns
+ ConversationalAnalysisAuthoringEvaluationJobResult. The
+ ConversationalAnalysisAuthoringEvaluationJobResult is compatible with MutableMapping
+ :rtype:
+ ~azure.core.polling.LROPoller[~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringEvaluationJobResult]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ def begin_evaluate_model(
+ self,
+ project_name: str,
+ trained_model_label: str,
+ body: JSON,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> LROPoller[_models.ConversationalAnalysisAuthoringEvaluationJobResult]:
+ # pylint: disable=line-too-long
+ """Triggers evaluation operation on a trained model.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param trained_model_label: The trained model label. Required.
+ :type trained_model_label: str
+ :param body: The training input 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: An instance of LROPoller that returns
+ ConversationalAnalysisAuthoringEvaluationJobResult. The
+ ConversationalAnalysisAuthoringEvaluationJobResult is compatible with MutableMapping
+ :rtype:
+ ~azure.core.polling.LROPoller[~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringEvaluationJobResult]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ def begin_evaluate_model(
+ self,
+ project_name: str,
+ trained_model_label: str,
+ body: IO[bytes],
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> LROPoller[_models.ConversationalAnalysisAuthoringEvaluationJobResult]:
+ # pylint: disable=line-too-long
+ """Triggers evaluation operation on a trained model.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param trained_model_label: The trained model label. Required.
+ :type trained_model_label: str
+ :param body: The training input 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: An instance of LROPoller that returns
+ ConversationalAnalysisAuthoringEvaluationJobResult. The
+ ConversationalAnalysisAuthoringEvaluationJobResult is compatible with MutableMapping
+ :rtype:
+ ~azure.core.polling.LROPoller[~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringEvaluationJobResult]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @distributed_trace
+ @api_version_validation(
+ method_added_on="2023-04-15-preview",
+ params_added_on={
+ "2023-04-15-preview": ["api_version", "project_name", "trained_model_label", "content_type", "accept"]
+ },
+ )
+ def begin_evaluate_model(
+ self,
+ project_name: str,
+ trained_model_label: str,
+ body: Union[_models.ConversationalAnalysisAuthoringEvaluationOptions, JSON, IO[bytes]],
+ **kwargs: Any
+ ) -> LROPoller[_models.ConversationalAnalysisAuthoringEvaluationJobResult]:
+ # pylint: disable=line-too-long
+ """Triggers evaluation operation on a trained model.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param trained_model_label: The trained model label. Required.
+ :type trained_model_label: str
+ :param body: The training input parameters. Is one of the following types:
+ ConversationalAnalysisAuthoringEvaluationOptions, JSON, IO[bytes] Required.
+ :type body:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringEvaluationOptions
+ or JSON or IO[bytes]
+ :return: An instance of LROPoller that returns
+ ConversationalAnalysisAuthoringEvaluationJobResult. The
+ ConversationalAnalysisAuthoringEvaluationJobResult is compatible with MutableMapping
+ :rtype:
+ ~azure.core.polling.LROPoller[~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringEvaluationJobResult]
+ :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.ConversationalAnalysisAuthoringEvaluationJobResult] = 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._evaluate_model_initial(
+ project_name=project_name,
+ trained_model_label=trained_model_label,
+ 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)
+
+ def get_long_running_output(pipeline_response):
+ response_headers = {}
+ response = pipeline_response.http_response
+ response_headers["Operation-Location"] = self._deserialize(
+ "str", response.headers.get("Operation-Location")
+ )
+
+ deserialized = _deserialize(
+ _models.ConversationalAnalysisAuthoringEvaluationJobResult, response.json().get("result")
+ )
+ 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"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+
+ 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.ConversationalAnalysisAuthoringEvaluationJobResult].from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return LROPoller[_models.ConversationalAnalysisAuthoringEvaluationJobResult](
+ self._client, raw_result, get_long_running_output, polling_method # type: ignore
+ )
+
+ def _load_snapshot_initial(self, project_name: str, trained_model_label: str, **kwargs: Any) -> Iterator[bytes]:
+ 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_conversational_analysis_authoring_load_snapshot_request(
+ project_name=project_name,
+ trained_model_label=trained_model_label,
+ api_version=self._config.api_version,
+ headers=_headers,
+ params=_params,
+ )
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _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 [202]:
+ 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ response_headers = {}
+ response_headers["Operation-Location"] = self._deserialize("str", response.headers.get("Operation-Location"))
+
+ deserialized = response.iter_bytes()
+
+ if cls:
+ return cls(pipeline_response, deserialized, response_headers) # type: ignore
+
+ return deserialized # type: ignore
+
+ @distributed_trace
+ def begin_load_snapshot(self, project_name: str, trained_model_label: str, **kwargs: Any) -> LROPoller[None]:
+ """Restores the snapshot of this trained model to be the current working directory
+ of the project.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param trained_model_label: The trained model label. Required.
+ :type trained_model_label: str
+ :return: An instance of LROPoller that returns None
+ :rtype: ~azure.core.polling.LROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = kwargs.pop("params", {}) or {}
+
+ cls: ClsType[None] = 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._load_snapshot_initial(
+ project_name=project_name,
+ trained_model_label=trained_model_label,
+ 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): # pylint: disable=inconsistent-return-statements
+ if cls:
+ return cls(pipeline_response, None, {}) # type: ignore
+
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+
+ 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[None].from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return LROPoller[None](self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ @distributed_trace
+ @api_version_validation(
+ method_added_on="2023-04-15-preview",
+ params_added_on={
+ "2023-04-15-preview": ["api_version", "project_name", "trained_model_label", "job_id", "accept"]
+ },
+ )
+ def get_evaluation_status(
+ self, project_name: str, trained_model_label: str, job_id: str, **kwargs: Any
+ ) -> _models.GetEvaluationStatusResponse:
+ """Gets the status for an evaluation job.
+
+ :param project_name: The new project name. Required.
+ :type project_name: str
+ :param trained_model_label: The trained model label. Required.
+ :type trained_model_label: str
+ :param job_id: The job ID. Required.
+ :type job_id: str
+ :return: GetEvaluationStatusResponse. The GetEvaluationStatusResponse is compatible with
+ MutableMapping
+ :rtype: ~azure.ai.language.authoring.analyzeconversations.models.GetEvaluationStatusResponse
+ :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[_models.GetEvaluationStatusResponse] = kwargs.pop("cls", None)
+
+ _request = build_conversational_analysis_authoring_get_evaluation_status_request(
+ project_name=project_name,
+ trained_model_label=trained_model_label,
+ job_id=job_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"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _stream = kwargs.pop("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
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ if _stream:
+ deserialized = response.iter_bytes()
+ else:
+ deserialized = _deserialize(_models.GetEvaluationStatusResponse, response.json())
+
+ if cls:
+ return cls(pipeline_response, deserialized, {}) # type: ignore
+
+ return deserialized # type: ignore
+
+ @distributed_trace
+ def get_model_evaluation_results(
+ self,
+ project_name: str,
+ trained_model_label: str,
+ *,
+ string_index_type: Union[str, _models.StringIndexType],
+ top: Optional[int] = None,
+ skip: Optional[int] = None,
+ **kwargs: Any
+ ) -> Iterable["_models.ConversationalAnalysisAuthoringUtteranceEvaluationResult"]:
+ # pylint: disable=line-too-long
+ """Gets the detailed results of the evaluation for a trained model. This includes
+ the raw inference results for the data included in the evaluation process.
+
+ :param project_name: The new project name. Required.
+ :type project_name: str
+ :param trained_model_label: The trained model label. Required.
+ :type trained_model_label: str
+ :keyword string_index_type: Specifies the method used to interpret string offsets. For
+ additional
+ information see https://aka.ms/text-analytics-offsets. "Utf16CodeUnit" Required.
+ :paramtype string_index_type: str or
+ ~azure.ai.language.authoring.analyzeconversations.models.StringIndexType
+ :keyword top: The number of result items to return. Default value is None.
+ :paramtype top: int
+ :keyword skip: The number of result items to skip. Default value is None.
+ :paramtype skip: int
+ :return: An iterator like instance of ConversationalAnalysisAuthoringUtteranceEvaluationResult
+ :rtype:
+ ~azure.core.paging.ItemPaged[~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringUtteranceEvaluationResult]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = kwargs.pop("params", {}) or {}
+
+ maxpagesize = kwargs.pop("maxpagesize", None)
+ cls: ClsType[List[_models.ConversationalAnalysisAuthoringUtteranceEvaluationResult]] = 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_conversational_analysis_authoring_get_model_evaluation_results_request(
+ project_name=project_name,
+ trained_model_label=trained_model_label,
+ string_index_type=string_index_type,
+ top=top,
+ skip=skip,
+ maxpagesize=maxpagesize,
+ api_version=self._config.api_version,
+ headers=_headers,
+ params=_params,
+ )
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _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"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _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.ConversationalAnalysisAuthoringUtteranceEvaluationResult], 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ return pipeline_response
+
+ return ItemPaged(get_next, extract_data)
+
+ @distributed_trace
+ def get_model_evaluation_summary(
+ self, project_name: str, trained_model_label: str, **kwargs: Any
+ ) -> _models.ConversationalAnalysisAuthoringEvaluationSummary:
+ """Gets the evaluation summary of a trained model. The summary includes high level
+ performance measurements of the model e.g., F1, Precision, Recall, etc.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param trained_model_label: The trained model label. Required.
+ :type trained_model_label: str
+ :return: ConversationalAnalysisAuthoringEvaluationSummary. The
+ ConversationalAnalysisAuthoringEvaluationSummary is compatible with MutableMapping
+ :rtype:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringEvaluationSummary
+ :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[_models.ConversationalAnalysisAuthoringEvaluationSummary] = kwargs.pop("cls", None)
+
+ _request = build_conversational_analysis_authoring_get_model_evaluation_summary_request(
+ project_name=project_name,
+ trained_model_label=trained_model_label,
+ api_version=self._config.api_version,
+ headers=_headers,
+ params=_params,
+ )
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _stream = kwargs.pop("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
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ if _stream:
+ deserialized = response.iter_bytes()
+ else:
+ deserialized = _deserialize(_models.ConversationalAnalysisAuthoringEvaluationSummary, response.json())
+
+ if cls:
+ return cls(pipeline_response, deserialized, {}) # type: ignore
+
+ return deserialized # type: ignore
+
+ @distributed_trace
+ def get_load_snapshot_status(
+ self, project_name: str, trained_model_label: str, job_id: str, **kwargs: Any
+ ) -> _models.GetLoadSnapshotStatusResponse:
+ """Gets the status for loading a snapshot.
+
+ :param project_name: The new project name. Required.
+ :type project_name: str
+ :param trained_model_label: The trained model label. Required.
+ :type trained_model_label: str
+ :param job_id: The job ID. Required.
+ :type job_id: str
+ :return: GetLoadSnapshotStatusResponse. The GetLoadSnapshotStatusResponse is compatible with
+ MutableMapping
+ :rtype: ~azure.ai.language.authoring.analyzeconversations.models.GetLoadSnapshotStatusResponse
+ :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[_models.GetLoadSnapshotStatusResponse] = kwargs.pop("cls", None)
+
+ _request = build_conversational_analysis_authoring_get_load_snapshot_status_request(
+ project_name=project_name,
+ trained_model_label=trained_model_label,
+ job_id=job_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"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _stream = kwargs.pop("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
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ if _stream:
+ deserialized = response.iter_bytes()
+ else:
+ deserialized = _deserialize(_models.GetLoadSnapshotStatusResponse, response.json())
+
+ if cls:
+ return cls(pipeline_response, deserialized, {}) # type: ignore
+
+ return deserialized # type: ignore
+
+ @distributed_trace
+ @api_version_validation(
+ method_added_on="2023-04-15-preview",
+ params_added_on={"2023-04-15-preview": ["api_version", "project_name", "top", "skip", "maxpagesize", "accept"]},
+ )
+ def list_deployment_resources(
+ self, project_name: str, *, top: Optional[int] = None, skip: Optional[int] = None, **kwargs: Any
+ ) -> Iterable["_models.ConversationalAnalysisAuthoringAssignedDeploymentResource"]:
+ # pylint: disable=line-too-long
+ """Lists the deployments resources assigned to the project.
+
+ :param project_name: The new project name. Required.
+ :type project_name: str
+ :keyword top: The number of result items to return. Default value is None.
+ :paramtype top: int
+ :keyword skip: The number of result items to skip. Default value is None.
+ :paramtype skip: int
+ :return: An iterator like instance of ConversationalAnalysisAuthoringAssignedDeploymentResource
+ :rtype:
+ ~azure.core.paging.ItemPaged[~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringAssignedDeploymentResource]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = kwargs.pop("params", {}) or {}
+
+ maxpagesize = kwargs.pop("maxpagesize", None)
+ cls: ClsType[List[_models.ConversationalAnalysisAuthoringAssignedDeploymentResource]] = 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_conversational_analysis_authoring_list_deployment_resources_request(
+ project_name=project_name,
+ top=top,
+ skip=skip,
+ maxpagesize=maxpagesize,
+ api_version=self._config.api_version,
+ headers=_headers,
+ params=_params,
+ )
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _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"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _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.ConversationalAnalysisAuthoringAssignedDeploymentResource], 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ return pipeline_response
+
+ return ItemPaged(get_next, extract_data)
+
+ @api_version_validation(
+ method_added_on="2023-04-15-preview",
+ params_added_on={"2023-04-15-preview": ["api_version", "project_name", "content_type", "accept"]},
+ )
+ def _assign_deployment_resources_initial(
+ self,
+ project_name: str,
+ body: Union[_models.ConversationalAnalysisAuthoringAssignDeploymentResourcesOptions, JSON, IO[bytes]],
+ **kwargs: Any
+ ) -> Iterator[bytes]:
+ error_map: MutableMapping = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _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[Iterator[bytes]] = kwargs.pop("cls", None)
+
+ content_type = content_type or "application/json"
+ _content = None
+ if isinstance(body, (IOBase, bytes)):
+ _content = body
+ else:
+ _content = json.dumps(body, cls=SdkJSONEncoder, exclude_readonly=True) # type: ignore
+
+ _request = build_conversational_analysis_authoring_assign_deployment_resources_request(
+ project_name=project_name,
+ content_type=content_type,
+ api_version=self._config.api_version,
+ content=_content,
+ headers=_headers,
+ params=_params,
+ )
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _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 [202]:
+ 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ response_headers = {}
+ response_headers["Operation-Location"] = self._deserialize("str", response.headers.get("Operation-Location"))
+
+ deserialized = response.iter_bytes()
+
+ if cls:
+ return cls(pipeline_response, deserialized, response_headers) # type: ignore
+
+ return deserialized # type: ignore
+
+ @overload
+ def begin_assign_deployment_resources(
+ self,
+ project_name: str,
+ body: _models.ConversationalAnalysisAuthoringAssignDeploymentResourcesOptions,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> LROPoller[None]:
+ # pylint: disable=line-too-long
+ """Assign new Azure resources to a project to allow deploying new deployments to
+ them. This API is available only via AAD authentication and not supported via
+ subscription key authentication. For more details about AAD authentication,
+ check here:
+ https://learn.microsoft.com/en-us/azure/cognitive-services/authentication?tabs=powershell#authenticate-with-azure-active-directory.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param body: The new project resources info. Required.
+ :type body:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringAssignDeploymentResourcesOptions
+ :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 LROPoller that returns None
+ :rtype: ~azure.core.polling.LROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ def begin_assign_deployment_resources(
+ self, project_name: str, body: JSON, *, content_type: str = "application/json", **kwargs: Any
+ ) -> LROPoller[None]:
+ """Assign new Azure resources to a project to allow deploying new deployments to
+ them. This API is available only via AAD authentication and not supported via
+ subscription key authentication. For more details about AAD authentication,
+ check here:
+ https://learn.microsoft.com/en-us/azure/cognitive-services/authentication?tabs=powershell#authenticate-with-azure-active-directory.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param body: The new project resources info. 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: An instance of LROPoller that returns None
+ :rtype: ~azure.core.polling.LROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ def begin_assign_deployment_resources(
+ self, project_name: str, body: IO[bytes], *, content_type: str = "application/json", **kwargs: Any
+ ) -> LROPoller[None]:
+ """Assign new Azure resources to a project to allow deploying new deployments to
+ them. This API is available only via AAD authentication and not supported via
+ subscription key authentication. For more details about AAD authentication,
+ check here:
+ https://learn.microsoft.com/en-us/azure/cognitive-services/authentication?tabs=powershell#authenticate-with-azure-active-directory.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param body: The new project resources info. 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: An instance of LROPoller that returns None
+ :rtype: ~azure.core.polling.LROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @distributed_trace
+ @api_version_validation(
+ method_added_on="2023-04-15-preview",
+ params_added_on={"2023-04-15-preview": ["api_version", "project_name", "content_type", "accept"]},
+ )
+ def begin_assign_deployment_resources(
+ self,
+ project_name: str,
+ body: Union[_models.ConversationalAnalysisAuthoringAssignDeploymentResourcesOptions, JSON, IO[bytes]],
+ **kwargs: Any
+ ) -> LROPoller[None]:
+ # pylint: disable=line-too-long
+ """Assign new Azure resources to a project to allow deploying new deployments to
+ them. This API is available only via AAD authentication and not supported via
+ subscription key authentication. For more details about AAD authentication,
+ check here:
+ https://learn.microsoft.com/en-us/azure/cognitive-services/authentication?tabs=powershell#authenticate-with-azure-active-directory.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param body: The new project resources info. Is one of the following types:
+ ConversationalAnalysisAuthoringAssignDeploymentResourcesOptions, JSON, IO[bytes] Required.
+ :type body:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringAssignDeploymentResourcesOptions
+ or JSON or IO[bytes]
+ :return: An instance of LROPoller that returns None
+ :rtype: ~azure.core.polling.LROPoller[None]
+ :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[None] = 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._assign_deployment_resources_initial(
+ project_name=project_name,
+ 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)
+
+ def get_long_running_output(pipeline_response): # pylint: disable=inconsistent-return-statements
+ if cls:
+ return cls(pipeline_response, None, {}) # type: ignore
+
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+
+ 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[None].from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return LROPoller[None](self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ @api_version_validation(
+ method_added_on="2023-04-15-preview",
+ params_added_on={"2023-04-15-preview": ["api_version", "project_name", "content_type", "accept"]},
+ )
+ def _unassign_deployment_resources_initial(
+ self,
+ project_name: str,
+ body: Union[_models.ConversationalAnalysisAuthoringUnassignDeploymentResourcesOptions, JSON, IO[bytes]],
+ **kwargs: Any
+ ) -> Iterator[bytes]:
+ error_map: MutableMapping = {
+ 401: ClientAuthenticationError,
+ 404: ResourceNotFoundError,
+ 409: ResourceExistsError,
+ 304: ResourceNotModifiedError,
+ }
+ error_map.update(kwargs.pop("error_map", {}) or {})
+
+ _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[Iterator[bytes]] = kwargs.pop("cls", None)
+
+ content_type = content_type or "application/json"
+ _content = None
+ if isinstance(body, (IOBase, bytes)):
+ _content = body
+ else:
+ _content = json.dumps(body, cls=SdkJSONEncoder, exclude_readonly=True) # type: ignore
+
+ _request = build_conversational_analysis_authoring_unassign_deployment_resources_request(
+ project_name=project_name,
+ content_type=content_type,
+ api_version=self._config.api_version,
+ content=_content,
+ headers=_headers,
+ params=_params,
+ )
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _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 [202]:
+ 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ response_headers = {}
+ response_headers["Operation-Location"] = self._deserialize("str", response.headers.get("Operation-Location"))
+
+ deserialized = response.iter_bytes()
+
+ if cls:
+ return cls(pipeline_response, deserialized, response_headers) # type: ignore
+
+ return deserialized # type: ignore
+
+ @overload
+ def begin_unassign_deployment_resources(
+ self,
+ project_name: str,
+ body: _models.ConversationalAnalysisAuthoringUnassignDeploymentResourcesOptions,
+ *,
+ content_type: str = "application/json",
+ **kwargs: Any
+ ) -> LROPoller[None]:
+ # pylint: disable=line-too-long
+ """Unassign resources from a project. This disallows deploying new deployments to
+ these resources, and deletes existing deployments assigned to them.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param body: The info for the deployment resources to be deleted. Required.
+ :type body:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringUnassignDeploymentResourcesOptions
+ :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 LROPoller that returns None
+ :rtype: ~azure.core.polling.LROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ def begin_unassign_deployment_resources(
+ self, project_name: str, body: JSON, *, content_type: str = "application/json", **kwargs: Any
+ ) -> LROPoller[None]:
+ """Unassign resources from a project. This disallows deploying new deployments to
+ these resources, and deletes existing deployments assigned to them.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param body: The info for the deployment resources to be deleted. 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: An instance of LROPoller that returns None
+ :rtype: ~azure.core.polling.LROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @overload
+ def begin_unassign_deployment_resources(
+ self, project_name: str, body: IO[bytes], *, content_type: str = "application/json", **kwargs: Any
+ ) -> LROPoller[None]:
+ """Unassign resources from a project. This disallows deploying new deployments to
+ these resources, and deletes existing deployments assigned to them.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param body: The info for the deployment resources to be deleted. 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: An instance of LROPoller that returns None
+ :rtype: ~azure.core.polling.LROPoller[None]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+
+ @distributed_trace
+ @api_version_validation(
+ method_added_on="2023-04-15-preview",
+ params_added_on={"2023-04-15-preview": ["api_version", "project_name", "content_type", "accept"]},
+ )
+ def begin_unassign_deployment_resources(
+ self,
+ project_name: str,
+ body: Union[_models.ConversationalAnalysisAuthoringUnassignDeploymentResourcesOptions, JSON, IO[bytes]],
+ **kwargs: Any
+ ) -> LROPoller[None]:
+ # pylint: disable=line-too-long
+ """Unassign resources from a project. This disallows deploying new deployments to
+ these resources, and deletes existing deployments assigned to them.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param body: The info for the deployment resources to be deleted. Is one of the following
+ types: ConversationalAnalysisAuthoringUnassignDeploymentResourcesOptions, JSON, IO[bytes]
+ Required.
+ :type body:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringUnassignDeploymentResourcesOptions
+ or JSON or IO[bytes]
+ :return: An instance of LROPoller that returns None
+ :rtype: ~azure.core.polling.LROPoller[None]
+ :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[None] = 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._unassign_deployment_resources_initial(
+ project_name=project_name,
+ 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)
+
+ def get_long_running_output(pipeline_response): # pylint: disable=inconsistent-return-statements
+ if cls:
+ return cls(pipeline_response, None, {}) # type: ignore
+
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+
+ 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[None].from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return LROPoller[None](self._client, raw_result, get_long_running_output, polling_method) # type: ignore
+
+ @distributed_trace
+ @api_version_validation(
+ method_added_on="2023-04-15-preview",
+ params_added_on={"2023-04-15-preview": ["api_version", "project_name", "job_id", "accept"]},
+ )
+ def get_assign_deployment_resources_status(
+ self, project_name: str, job_id: str, **kwargs: Any
+ ) -> _models.GetAssignDeploymentResourcesStatusResponse:
+ """Gets the status of an existing assign deployment resources job.
+
+ :param project_name: The new project name. Required.
+ :type project_name: str
+ :param job_id: The job ID. Required.
+ :type job_id: str
+ :return: GetAssignDeploymentResourcesStatusResponse. The
+ GetAssignDeploymentResourcesStatusResponse is compatible with MutableMapping
+ :rtype:
+ ~azure.ai.language.authoring.analyzeconversations.models.GetAssignDeploymentResourcesStatusResponse
+ :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[_models.GetAssignDeploymentResourcesStatusResponse] = kwargs.pop("cls", None)
+
+ _request = build_conversational_analysis_authoring_get_assign_deployment_resources_status_request(
+ project_name=project_name,
+ job_id=job_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"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _stream = kwargs.pop("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
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ if _stream:
+ deserialized = response.iter_bytes()
+ else:
+ deserialized = _deserialize(_models.GetAssignDeploymentResourcesStatusResponse, response.json())
+
+ if cls:
+ return cls(pipeline_response, deserialized, {}) # type: ignore
+
+ return deserialized # type: ignore
+
+ @distributed_trace
+ @api_version_validation(
+ method_added_on="2023-04-15-preview",
+ params_added_on={"2023-04-15-preview": ["api_version", "project_name", "job_id", "accept"]},
+ )
+ def get_unassign_deployment_resources_status(
+ self, project_name: str, job_id: str, **kwargs: Any
+ ) -> _models.GetUnassignDeploymentResourcesStatusResponse:
+ """Gets the status of an existing unassign deployment resources job.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param job_id: The job ID. Required.
+ :type job_id: str
+ :return: GetUnassignDeploymentResourcesStatusResponse. The
+ GetUnassignDeploymentResourcesStatusResponse is compatible with MutableMapping
+ :rtype:
+ ~azure.ai.language.authoring.analyzeconversations.models.GetUnassignDeploymentResourcesStatusResponse
+ :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[_models.GetUnassignDeploymentResourcesStatusResponse] = kwargs.pop("cls", None)
+
+ _request = build_conversational_analysis_authoring_get_unassign_deployment_resources_status_request(
+ project_name=project_name,
+ job_id=job_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"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _stream = kwargs.pop("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
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ if _stream:
+ deserialized = response.iter_bytes()
+ else:
+ deserialized = _deserialize(_models.GetUnassignDeploymentResourcesStatusResponse, response.json())
+
+ if cls:
+ return cls(pipeline_response, deserialized, {}) # type: ignore
+
+ return deserialized # type: ignore
+
+ @distributed_trace
+ def list_training_jobs(
+ self, project_name: str, *, top: Optional[int] = None, skip: Optional[int] = None, **kwargs: Any
+ ) -> Iterable["_models.ConversationalAnalysisAuthoringTrainingJobState"]:
+ # pylint: disable=line-too-long
+ """Lists the non-expired training jobs created for a project.
+
+ :param project_name: The new project name. Required.
+ :type project_name: str
+ :keyword top: The number of result items to return. Default value is None.
+ :paramtype top: int
+ :keyword skip: The number of result items to skip. Default value is None.
+ :paramtype skip: int
+ :return: An iterator like instance of ConversationalAnalysisAuthoringTrainingJobState
+ :rtype:
+ ~azure.core.paging.ItemPaged[~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringTrainingJobState]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = kwargs.pop("params", {}) or {}
+
+ maxpagesize = kwargs.pop("maxpagesize", None)
+ cls: ClsType[List[_models.ConversationalAnalysisAuthoringTrainingJobState]] = 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_conversational_analysis_authoring_list_training_jobs_request(
+ project_name=project_name,
+ top=top,
+ skip=skip,
+ maxpagesize=maxpagesize,
+ api_version=self._config.api_version,
+ headers=_headers,
+ params=_params,
+ )
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _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"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _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.ConversationalAnalysisAuthoringTrainingJobState], 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ return pipeline_response
+
+ return ItemPaged(get_next, extract_data)
+
+ @distributed_trace
+ def get_training_status(self, project_name: str, job_id: str, **kwargs: Any) -> _models.GetTrainingStatusResponse:
+ """Gets the status for a training job.
+
+ :param project_name: The new project name. Required.
+ :type project_name: str
+ :param job_id: The job ID. Required.
+ :type job_id: str
+ :return: GetTrainingStatusResponse. The GetTrainingStatusResponse is compatible with
+ MutableMapping
+ :rtype: ~azure.ai.language.authoring.analyzeconversations.models.GetTrainingStatusResponse
+ :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[_models.GetTrainingStatusResponse] = kwargs.pop("cls", None)
+
+ _request = build_conversational_analysis_authoring_get_training_status_request(
+ project_name=project_name,
+ job_id=job_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"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _stream = kwargs.pop("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
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ if _stream:
+ deserialized = response.iter_bytes()
+ else:
+ deserialized = _deserialize(_models.GetTrainingStatusResponse, response.json())
+
+ if cls:
+ return cls(pipeline_response, deserialized, {}) # type: ignore
+
+ return deserialized # type: ignore
+
+ def _cancel_training_job_initial(self, project_name: str, job_id: str, **kwargs: Any) -> Iterator[bytes]:
+ 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_conversational_analysis_authoring_cancel_training_job_request(
+ project_name=project_name,
+ job_id=job_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"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _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 [202]:
+ 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 = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ response_headers = {}
+ response_headers["Operation-Location"] = self._deserialize("str", response.headers.get("Operation-Location"))
+
+ deserialized = response.iter_bytes()
+
+ if cls:
+ return cls(pipeline_response, deserialized, response_headers) # type: ignore
+
+ return deserialized # type: ignore
+
+ @distributed_trace
+ def begin_cancel_training_job(
+ self, project_name: str, job_id: str, **kwargs: Any
+ ) -> LROPoller[_models.ConversationalAnalysisAuthoringTrainingJobResult]:
+ # pylint: disable=line-too-long
+ """Triggers a cancellation for a running training job.
+
+ :param project_name: The name of the project to use. Required.
+ :type project_name: str
+ :param job_id: The job ID. Required.
+ :type job_id: str
+ :return: An instance of LROPoller that returns
+ ConversationalAnalysisAuthoringTrainingJobResult. The
+ ConversationalAnalysisAuthoringTrainingJobResult is compatible with MutableMapping
+ :rtype:
+ ~azure.core.polling.LROPoller[~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringTrainingJobResult]
+ :raises ~azure.core.exceptions.HttpResponseError:
+ """
+ _headers = kwargs.pop("headers", {}) or {}
+ _params = kwargs.pop("params", {}) or {}
+
+ cls: ClsType[_models.ConversationalAnalysisAuthoringTrainingJobResult] = 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._cancel_training_job_initial(
+ project_name=project_name,
+ job_id=job_id,
+ 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["Operation-Location"] = self._deserialize(
+ "str", response.headers.get("Operation-Location")
+ )
+
+ deserialized = _deserialize(
+ _models.ConversationalAnalysisAuthoringTrainingJobResult, response.json().get("result")
+ )
+ 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"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+
+ 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.ConversationalAnalysisAuthoringTrainingJobResult].from_continuation_token(
+ polling_method=polling_method,
+ continuation_token=cont_token,
+ client=self._client,
+ deserialization_callback=get_long_running_output,
+ )
+ return LROPoller[_models.ConversationalAnalysisAuthoringTrainingJobResult](
+ self._client, raw_result, get_long_running_output, polling_method # type: ignore
+ )
+
+ @distributed_trace
+ def get_project_deletion_status(self, job_id: str, **kwargs: Any) -> _models.GetProjectDeletionStatusResponse:
+ """Gets the status for a project deletion job.
+
+ :param job_id: The job ID. Required.
+ :type job_id: str
+ :return: GetProjectDeletionStatusResponse. The GetProjectDeletionStatusResponse is compatible
+ with MutableMapping
+ :rtype:
+ ~azure.ai.language.authoring.analyzeconversations.models.GetProjectDeletionStatusResponse
+ :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[_models.GetProjectDeletionStatusResponse] = kwargs.pop("cls", None)
+
+ _request = build_conversational_analysis_authoring_get_project_deletion_status_request(
+ job_id=job_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"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _stream = kwargs.pop("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
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ if _stream:
+ deserialized = response.iter_bytes()
+ else:
+ deserialized = _deserialize(_models.GetProjectDeletionStatusResponse, response.json())
+
+ if cls:
+ return cls(pipeline_response, deserialized, {}) # type: ignore
+
+ return deserialized # type: ignore
+
+ @distributed_trace
+ @api_version_validation(
+ method_added_on="2023-04-15-preview",
+ params_added_on={"2023-04-15-preview": ["api_version", "top", "skip", "maxpagesize", "accept"]},
+ )
+ def list_assigned_resource_deployments(
+ self, *, top: Optional[int] = None, skip: Optional[int] = None, **kwargs: Any
+ ) -> _models.ConversationalAnalysisAuthoringAssignedResourceDeploymentsMetadata:
+ # pylint: disable=line-too-long
+ """Lists the deployments to which an Azure resource is assigned. This doesn't
+ return deployments belonging to projects owned by this resource. It only
+ returns deployments belonging to projects owned by other resources.
+
+ :keyword top: The maximum number of resources to return from the collection. Default value is
+ None.
+ :paramtype top: int
+ :keyword skip: An offset into the collection of the first resource to be returned. Default
+ value is None.
+ :paramtype skip: int
+ :return: ConversationalAnalysisAuthoringAssignedResourceDeploymentsMetadata. The
+ ConversationalAnalysisAuthoringAssignedResourceDeploymentsMetadata is compatible with
+ MutableMapping
+ :rtype:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringAssignedResourceDeploymentsMetadata
+ :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 {}
+
+ maxpagesize = kwargs.pop("maxpagesize", None)
+ cls: ClsType[_models.ConversationalAnalysisAuthoringAssignedResourceDeploymentsMetadata] = kwargs.pop(
+ "cls", None
+ )
+
+ _request = build_conversational_analysis_authoring_list_assigned_resource_deployments_request(
+ top=top,
+ skip=skip,
+ maxpagesize=maxpagesize,
+ api_version=self._config.api_version,
+ headers=_headers,
+ params=_params,
+ )
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _stream = kwargs.pop("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
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ if _stream:
+ deserialized = response.iter_bytes()
+ else:
+ deserialized = _deserialize(
+ _models.ConversationalAnalysisAuthoringAssignedResourceDeploymentsMetadata, response.json()
+ )
+
+ if cls:
+ return cls(pipeline_response, deserialized, {}) # type: ignore
+
+ return deserialized # type: ignore
+
+ @distributed_trace
+ def get_supported_languages(
+ self,
+ *,
+ project_kind: Union[str, _models.ProjectKind],
+ top: Optional[int] = None,
+ skip: Optional[int] = None,
+ **kwargs: Any
+ ) -> _models.ConversationalAnalysisAuthoringSupportedLanguages:
+ """Lists the supported languages for the given project type.
+
+ :keyword project_kind: The project kind. Known values are: "Conversation", "Orchestration", and
+ "CustomConversationSummarization". Required.
+ :paramtype project_kind: str or
+ ~azure.ai.language.authoring.analyzeconversations.models.ProjectKind
+ :keyword top: The maximum number of resources to return from the collection. Default value is
+ None.
+ :paramtype top: int
+ :keyword skip: An offset into the collection of the first resource to be returned. Default
+ value is None.
+ :paramtype skip: int
+ :return: ConversationalAnalysisAuthoringSupportedLanguages. The
+ ConversationalAnalysisAuthoringSupportedLanguages is compatible with MutableMapping
+ :rtype:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringSupportedLanguages
+ :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 {}
+
+ maxpagesize = kwargs.pop("maxpagesize", None)
+ cls: ClsType[_models.ConversationalAnalysisAuthoringSupportedLanguages] = kwargs.pop("cls", None)
+
+ _request = build_conversational_analysis_authoring_get_supported_languages_request(
+ project_kind=project_kind,
+ top=top,
+ skip=skip,
+ maxpagesize=maxpagesize,
+ api_version=self._config.api_version,
+ headers=_headers,
+ params=_params,
+ )
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _stream = kwargs.pop("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
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ if _stream:
+ deserialized = response.iter_bytes()
+ else:
+ deserialized = _deserialize(_models.ConversationalAnalysisAuthoringSupportedLanguages, response.json())
+
+ if cls:
+ return cls(pipeline_response, deserialized, {}) # type: ignore
+
+ return deserialized # type: ignore
+
+ @distributed_trace
+ def get_supported_prebuilt_entities(
+ self,
+ *,
+ language: Optional[str] = None,
+ multilingual: Optional[str] = None,
+ top: Optional[int] = None,
+ skip: Optional[int] = None,
+ **kwargs: Any
+ ) -> _models.ConversationalAnalysisAuthoringPrebuiltEntities:
+ """Lists the supported prebuilt entities that can be used while creating composed
+ entities.
+
+ :keyword language: The language to get supported prebuilt entities for. Required if
+ multilingual
+ is false. This is BCP-47 representation of a language. For example, use "en"
+ for English, "en-gb" for English (UK), "es" for Spanish etc. Default value is None.
+ :paramtype language: str
+ :keyword multilingual: Whether to get the support prebuilt entities for multilingual or
+ monolingual
+ projects. If true, the language parameter is ignored. Default value is None.
+ :paramtype multilingual: str
+ :keyword top: The maximum number of resources to return from the collection. Default value is
+ None.
+ :paramtype top: int
+ :keyword skip: An offset into the collection of the first resource to be returned. Default
+ value is None.
+ :paramtype skip: int
+ :return: ConversationalAnalysisAuthoringPrebuiltEntities. The
+ ConversationalAnalysisAuthoringPrebuiltEntities is compatible with MutableMapping
+ :rtype:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringPrebuiltEntities
+ :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 {}
+
+ maxpagesize = kwargs.pop("maxpagesize", None)
+ cls: ClsType[_models.ConversationalAnalysisAuthoringPrebuiltEntities] = kwargs.pop("cls", None)
+
+ _request = build_conversational_analysis_authoring_get_supported_prebuilt_entities_request(
+ language=language,
+ multilingual=multilingual,
+ top=top,
+ skip=skip,
+ maxpagesize=maxpagesize,
+ api_version=self._config.api_version,
+ headers=_headers,
+ params=_params,
+ )
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _stream = kwargs.pop("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
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ if _stream:
+ deserialized = response.iter_bytes()
+ else:
+ deserialized = _deserialize(_models.ConversationalAnalysisAuthoringPrebuiltEntities, response.json())
+
+ if cls:
+ return cls(pipeline_response, deserialized, {}) # type: ignore
+
+ return deserialized # type: ignore
+
+ @distributed_trace
+ def list_training_config_versions(
+ self,
+ *,
+ project_kind: Union[str, _models.ProjectKind],
+ top: Optional[int] = None,
+ skip: Optional[int] = None,
+ **kwargs: Any
+ ) -> _models.ConversationalAnalysisAuthoringTrainingConfigVersions:
+ """Lists the support training config version for a given project type.
+
+ :keyword project_kind: The project kind. Known values are: "Conversation", "Orchestration", and
+ "CustomConversationSummarization". Required.
+ :paramtype project_kind: str or
+ ~azure.ai.language.authoring.analyzeconversations.models.ProjectKind
+ :keyword top: The maximum number of resources to return from the collection. Default value is
+ None.
+ :paramtype top: int
+ :keyword skip: An offset into the collection of the first resource to be returned. Default
+ value is None.
+ :paramtype skip: int
+ :return: ConversationalAnalysisAuthoringTrainingConfigVersions. The
+ ConversationalAnalysisAuthoringTrainingConfigVersions is compatible with MutableMapping
+ :rtype:
+ ~azure.ai.language.authoring.analyzeconversations.models.ConversationalAnalysisAuthoringTrainingConfigVersions
+ :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 {}
+
+ maxpagesize = kwargs.pop("maxpagesize", None)
+ cls: ClsType[_models.ConversationalAnalysisAuthoringTrainingConfigVersions] = kwargs.pop("cls", None)
+
+ _request = build_conversational_analysis_authoring_list_training_config_versions_request(
+ project_kind=project_kind,
+ top=top,
+ skip=skip,
+ maxpagesize=maxpagesize,
+ api_version=self._config.api_version,
+ headers=_headers,
+ params=_params,
+ )
+ path_format_arguments = {
+ "endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ "Endpoint": self._serialize.url("self._config.endpoint", self._config.endpoint, "str"),
+ }
+ _request.url = self._client.format_url(_request.url, **path_format_arguments)
+
+ _stream = kwargs.pop("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
+ map_error(status_code=response.status_code, response=response, error_map=error_map)
+ error = _deserialize(_models.ErrorResponse, response.json())
+ raise HttpResponseError(response=response, model=error)
+
+ if _stream:
+ deserialized = response.iter_bytes()
+ else:
+ deserialized = _deserialize(_models.ConversationalAnalysisAuthoringTrainingConfigVersions, response.json())
+
+ if cls:
+ return cls(pipeline_response, deserialized, {}) # type: ignore
+
+ return deserialized # type: ignore
diff --git a/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/operations/_patch.py b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/operations/_patch.py
new file mode 100644
index 000000000000..f7dd32510333
--- /dev/null
+++ b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/operations/_patch.py
@@ -0,0 +1,20 @@
+# ------------------------------------
+# Copyright (c) Microsoft Corporation.
+# Licensed under the MIT License.
+# ------------------------------------
+"""Customize generated code here.
+
+Follow our quickstart for examples: https://aka.ms/azsdk/python/dpcodegen/python/customize
+"""
+from typing import List
+
+__all__: List[str] = [] # Add all objects you want publicly available to users at this package level
+
+
+def patch_sdk():
+ """Do not remove from this file.
+
+ `patch_sdk` is a last resort escape hatch that allows you to do customizations
+ you can't accomplish using the techniques described in
+ https://aka.ms/azsdk/python/dpcodegen/python/customize
+ """
diff --git a/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/py.typed b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/py.typed
new file mode 100644
index 000000000000..e5aff4f83af8
--- /dev/null
+++ b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/azure/ai/language/authoring/analyzeconversations/py.typed
@@ -0,0 +1 @@
+# Marker file for PEP 561.
\ No newline at end of file
diff --git a/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/dev_requirements.txt b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/dev_requirements.txt
new file mode 100644
index 000000000000..105486471444
--- /dev/null
+++ b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/dev_requirements.txt
@@ -0,0 +1,3 @@
+-e ../../../tools/azure-sdk-tools
+../../core/azure-core
+aiohttp
\ No newline at end of file
diff --git a/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/generated_tests/conftest.py b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/generated_tests/conftest.py
new file mode 100644
index 000000000000..5ce5501aa4da
--- /dev/null
+++ b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/generated_tests/conftest.py
@@ -0,0 +1,37 @@
+# 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):
+ conversations_subscription_id = os.environ.get(
+ "CONVERSATIONS_SUBSCRIPTION_ID", "00000000-0000-0000-0000-000000000000"
+ )
+ conversations_tenant_id = os.environ.get("CONVERSATIONS_TENANT_ID", "00000000-0000-0000-0000-000000000000")
+ conversations_client_id = os.environ.get("CONVERSATIONS_CLIENT_ID", "00000000-0000-0000-0000-000000000000")
+ conversations_client_secret = os.environ.get("CONVERSATIONS_CLIENT_SECRET", "00000000-0000-0000-0000-000000000000")
+ add_general_regex_sanitizer(regex=conversations_subscription_id, value="00000000-0000-0000-0000-000000000000")
+ add_general_regex_sanitizer(regex=conversations_tenant_id, value="00000000-0000-0000-0000-000000000000")
+ add_general_regex_sanitizer(regex=conversations_client_id, value="00000000-0000-0000-0000-000000000000")
+ add_general_regex_sanitizer(regex=conversations_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/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/generated_tests/test_conversations_conversational_analysis_authoring_operations.py b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/generated_tests/test_conversations_conversational_analysis_authoring_operations.py
new file mode 100644
index 000000000000..9bea2dfdcb41
--- /dev/null
+++ b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/generated_tests/test_conversations_conversational_analysis_authoring_operations.py
@@ -0,0 +1,555 @@
+# 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 ConversationsClientTestBase, ConversationsPreparer
+
+
+@pytest.mark.skip("you may need to update the auto-generated test case before run it")
+class TestConversationsConversationalAnalysisAuthoringOperations(ConversationsClientTestBase):
+ @ConversationsPreparer()
+ @recorded_by_proxy
+ def test_conversational_analysis_authoring_list_projects(self, conversations_endpoint):
+ client = self.create_client(endpoint=conversations_endpoint)
+ response = client.conversational_analysis_authoring.list_projects()
+ result = [r for r in response]
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy
+ def test_conversational_analysis_authoring_get_project(self, conversations_endpoint):
+ client = self.create_client(endpoint=conversations_endpoint)
+ response = client.conversational_analysis_authoring.get_project(
+ project_name="str",
+ )
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy
+ def test_conversational_analysis_authoring_create_project(self, conversations_endpoint):
+ client = self.create_client(endpoint=conversations_endpoint)
+ response = client.conversational_analysis_authoring.create_project(
+ project_name="str",
+ body={
+ "language": "str",
+ "projectKind": "str",
+ "projectName": "str",
+ "description": "str",
+ "multilingual": bool,
+ "settings": {"confidenceThreshold": 0.0},
+ "storageInputContainerName": "str",
+ },
+ )
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy
+ def test_conversational_analysis_authoring_begin_delete_project(self, conversations_endpoint):
+ client = self.create_client(endpoint=conversations_endpoint)
+ response = client.conversational_analysis_authoring.begin_delete_project(
+ project_name="str",
+ ).result() # call '.result()' to poll until service return final result
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy
+ def test_conversational_analysis_authoring_copy_project_authorization(self, conversations_endpoint):
+ client = self.create_client(endpoint=conversations_endpoint)
+ response = client.conversational_analysis_authoring.copy_project_authorization(
+ project_name="str",
+ body={"projectKind": "str", "allowOverwrite": bool, "storageInputContainerName": "str"},
+ project_kind="str",
+ )
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy
+ def test_conversational_analysis_authoring_begin_copy_project(self, conversations_endpoint):
+ client = self.create_client(endpoint=conversations_endpoint)
+ response = client.conversational_analysis_authoring.begin_copy_project(
+ project_name="str",
+ body={
+ "accessToken": "str",
+ "expiresAt": "2020-02-20 00:00:00",
+ "projectKind": "str",
+ "targetProjectName": "str",
+ "targetResourceId": "str",
+ "targetResourceRegion": "str",
+ },
+ ).result() # call '.result()' to poll until service return final result
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy
+ def test_conversational_analysis_authoring_begin_export(self, conversations_endpoint):
+ client = self.create_client(endpoint=conversations_endpoint)
+ response = client.conversational_analysis_authoring.begin_export(
+ project_name="str",
+ string_index_type="str",
+ ).result() # call '.result()' to poll until service return final result
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy
+ def test_conversational_analysis_authoring_begin_import_method(self, conversations_endpoint):
+ client = self.create_client(endpoint=conversations_endpoint)
+ response = client.conversational_analysis_authoring.begin_import_method(
+ project_name="str",
+ body={
+ "metadata": {
+ "language": "str",
+ "projectKind": "str",
+ "projectName": "str",
+ "description": "str",
+ "multilingual": bool,
+ "settings": {"confidenceThreshold": 0.0},
+ "storageInputContainerName": "str",
+ },
+ "projectFileVersion": "str",
+ "stringIndexType": "str",
+ "assets": "conversational_analysis_authoring_exported_project_assets",
+ },
+ ).result() # call '.result()' to poll until service return final result
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy
+ def test_conversational_analysis_authoring_begin_train(self, conversations_endpoint):
+ client = self.create_client(endpoint=conversations_endpoint)
+ response = client.conversational_analysis_authoring.begin_train(
+ project_name="str",
+ body={
+ "modelLabel": "str",
+ "trainingMode": "str",
+ "evaluationOptions": {"kind": "str", "testingSplitPercentage": 0, "trainingSplitPercentage": 0},
+ "trainingConfigVersion": "str",
+ },
+ ).result() # call '.result()' to poll until service return final result
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy
+ def test_conversational_analysis_authoring_get_copy_project_status(self, conversations_endpoint):
+ client = self.create_client(endpoint=conversations_endpoint)
+ response = client.conversational_analysis_authoring.get_copy_project_status(
+ project_name="str",
+ job_id="str",
+ )
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy
+ def test_conversational_analysis_authoring_list_deployments(self, conversations_endpoint):
+ client = self.create_client(endpoint=conversations_endpoint)
+ response = client.conversational_analysis_authoring.list_deployments(
+ project_name="str",
+ )
+ result = [r for r in response]
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy
+ def test_conversational_analysis_authoring_begin_swap_deployments(self, conversations_endpoint):
+ client = self.create_client(endpoint=conversations_endpoint)
+ response = client.conversational_analysis_authoring.begin_swap_deployments(
+ project_name="str",
+ body={"firstDeploymentName": "str", "secondDeploymentName": "str"},
+ ).result() # call '.result()' to poll until service return final result
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy
+ def test_conversational_analysis_authoring_get_deployment(self, conversations_endpoint):
+ client = self.create_client(endpoint=conversations_endpoint)
+ response = client.conversational_analysis_authoring.get_deployment(
+ project_name="str",
+ deployment_name="str",
+ )
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy
+ def test_conversational_analysis_authoring_begin_deploy_project(self, conversations_endpoint):
+ client = self.create_client(endpoint=conversations_endpoint)
+ response = client.conversational_analysis_authoring.begin_deploy_project(
+ project_name="str",
+ deployment_name="str",
+ body={"trainedModelLabel": "str", "assignedResourceIds": ["str"]},
+ ).result() # call '.result()' to poll until service return final result
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy
+ def test_conversational_analysis_authoring_begin_delete_deployment(self, conversations_endpoint):
+ client = self.create_client(endpoint=conversations_endpoint)
+ response = client.conversational_analysis_authoring.begin_delete_deployment(
+ project_name="str",
+ deployment_name="str",
+ ).result() # call '.result()' to poll until service return final result
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy
+ def test_conversational_analysis_authoring_begin_delete_deployment_from_resources(self, conversations_endpoint):
+ client = self.create_client(endpoint=conversations_endpoint)
+ response = client.conversational_analysis_authoring.begin_delete_deployment_from_resources(
+ project_name="str",
+ deployment_name="str",
+ body={"assignedResourceIds": ["str"]},
+ ).result() # call '.result()' to poll until service return final result
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy
+ def test_conversational_analysis_authoring_get_deployment_delete_from_resources_status(
+ self, conversations_endpoint
+ ):
+ client = self.create_client(endpoint=conversations_endpoint)
+ response = client.conversational_analysis_authoring.get_deployment_delete_from_resources_status(
+ project_name="str",
+ deployment_name="str",
+ job_id="str",
+ )
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy
+ def test_conversational_analysis_authoring_get_deployment_status(self, conversations_endpoint):
+ client = self.create_client(endpoint=conversations_endpoint)
+ response = client.conversational_analysis_authoring.get_deployment_status(
+ project_name="str",
+ deployment_name="str",
+ job_id="str",
+ )
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy
+ def test_conversational_analysis_authoring_get_swap_deployments_status(self, conversations_endpoint):
+ client = self.create_client(endpoint=conversations_endpoint)
+ response = client.conversational_analysis_authoring.get_swap_deployments_status(
+ project_name="str",
+ job_id="str",
+ )
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy
+ def test_conversational_analysis_authoring_get_export_status(self, conversations_endpoint):
+ client = self.create_client(endpoint=conversations_endpoint)
+ response = client.conversational_analysis_authoring.get_export_status(
+ project_name="str",
+ job_id="str",
+ )
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy
+ def test_conversational_analysis_authoring_get_import_status(self, conversations_endpoint):
+ client = self.create_client(endpoint=conversations_endpoint)
+ response = client.conversational_analysis_authoring.get_import_status(
+ project_name="str",
+ job_id="str",
+ )
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy
+ def test_conversational_analysis_authoring_list_trained_models(self, conversations_endpoint):
+ client = self.create_client(endpoint=conversations_endpoint)
+ response = client.conversational_analysis_authoring.list_trained_models(
+ project_name="str",
+ )
+ result = [r for r in response]
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy
+ def test_conversational_analysis_authoring_get_trained_model(self, conversations_endpoint):
+ client = self.create_client(endpoint=conversations_endpoint)
+ response = client.conversational_analysis_authoring.get_trained_model(
+ project_name="str",
+ trained_model_label="str",
+ )
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy
+ def test_conversational_analysis_authoring_delete_trained_model(self, conversations_endpoint):
+ client = self.create_client(endpoint=conversations_endpoint)
+ response = client.conversational_analysis_authoring.delete_trained_model(
+ project_name="str",
+ trained_model_label="str",
+ )
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy
+ def test_conversational_analysis_authoring_begin_evaluate_model(self, conversations_endpoint):
+ client = self.create_client(endpoint=conversations_endpoint)
+ response = client.conversational_analysis_authoring.begin_evaluate_model(
+ project_name="str",
+ trained_model_label="str",
+ body={"kind": "str", "testingSplitPercentage": 0, "trainingSplitPercentage": 0},
+ ).result() # call '.result()' to poll until service return final result
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy
+ def test_conversational_analysis_authoring_begin_load_snapshot(self, conversations_endpoint):
+ client = self.create_client(endpoint=conversations_endpoint)
+ response = client.conversational_analysis_authoring.begin_load_snapshot(
+ project_name="str",
+ trained_model_label="str",
+ ).result() # call '.result()' to poll until service return final result
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy
+ def test_conversational_analysis_authoring_get_evaluation_status(self, conversations_endpoint):
+ client = self.create_client(endpoint=conversations_endpoint)
+ response = client.conversational_analysis_authoring.get_evaluation_status(
+ project_name="str",
+ trained_model_label="str",
+ job_id="str",
+ )
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy
+ def test_conversational_analysis_authoring_get_model_evaluation_results(self, conversations_endpoint):
+ client = self.create_client(endpoint=conversations_endpoint)
+ response = client.conversational_analysis_authoring.get_model_evaluation_results(
+ project_name="str",
+ trained_model_label="str",
+ string_index_type="str",
+ )
+ result = [r for r in response]
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy
+ def test_conversational_analysis_authoring_get_model_evaluation_summary(self, conversations_endpoint):
+ client = self.create_client(endpoint=conversations_endpoint)
+ response = client.conversational_analysis_authoring.get_model_evaluation_summary(
+ project_name="str",
+ trained_model_label="str",
+ )
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy
+ def test_conversational_analysis_authoring_get_load_snapshot_status(self, conversations_endpoint):
+ client = self.create_client(endpoint=conversations_endpoint)
+ response = client.conversational_analysis_authoring.get_load_snapshot_status(
+ project_name="str",
+ trained_model_label="str",
+ job_id="str",
+ )
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy
+ def test_conversational_analysis_authoring_list_deployment_resources(self, conversations_endpoint):
+ client = self.create_client(endpoint=conversations_endpoint)
+ response = client.conversational_analysis_authoring.list_deployment_resources(
+ project_name="str",
+ )
+ result = [r for r in response]
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy
+ def test_conversational_analysis_authoring_begin_assign_deployment_resources(self, conversations_endpoint):
+ client = self.create_client(endpoint=conversations_endpoint)
+ response = client.conversational_analysis_authoring.begin_assign_deployment_resources(
+ project_name="str",
+ body={"resourcesMetadata": [{"azureResourceId": "str", "customDomain": "str", "region": "str"}]},
+ ).result() # call '.result()' to poll until service return final result
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy
+ def test_conversational_analysis_authoring_begin_unassign_deployment_resources(self, conversations_endpoint):
+ client = self.create_client(endpoint=conversations_endpoint)
+ response = client.conversational_analysis_authoring.begin_unassign_deployment_resources(
+ project_name="str",
+ body={"assignedResourceIds": ["str"]},
+ ).result() # call '.result()' to poll until service return final result
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy
+ def test_conversational_analysis_authoring_get_assign_deployment_resources_status(self, conversations_endpoint):
+ client = self.create_client(endpoint=conversations_endpoint)
+ response = client.conversational_analysis_authoring.get_assign_deployment_resources_status(
+ project_name="str",
+ job_id="str",
+ )
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy
+ def test_conversational_analysis_authoring_get_unassign_deployment_resources_status(self, conversations_endpoint):
+ client = self.create_client(endpoint=conversations_endpoint)
+ response = client.conversational_analysis_authoring.get_unassign_deployment_resources_status(
+ project_name="str",
+ job_id="str",
+ )
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy
+ def test_conversational_analysis_authoring_list_training_jobs(self, conversations_endpoint):
+ client = self.create_client(endpoint=conversations_endpoint)
+ response = client.conversational_analysis_authoring.list_training_jobs(
+ project_name="str",
+ )
+ result = [r for r in response]
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy
+ def test_conversational_analysis_authoring_get_training_status(self, conversations_endpoint):
+ client = self.create_client(endpoint=conversations_endpoint)
+ response = client.conversational_analysis_authoring.get_training_status(
+ project_name="str",
+ job_id="str",
+ )
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy
+ def test_conversational_analysis_authoring_begin_cancel_training_job(self, conversations_endpoint):
+ client = self.create_client(endpoint=conversations_endpoint)
+ response = client.conversational_analysis_authoring.begin_cancel_training_job(
+ project_name="str",
+ job_id="str",
+ ).result() # call '.result()' to poll until service return final result
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy
+ def test_conversational_analysis_authoring_get_project_deletion_status(self, conversations_endpoint):
+ client = self.create_client(endpoint=conversations_endpoint)
+ response = client.conversational_analysis_authoring.get_project_deletion_status(
+ job_id="str",
+ )
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy
+ def test_conversational_analysis_authoring_list_assigned_resource_deployments(self, conversations_endpoint):
+ client = self.create_client(endpoint=conversations_endpoint)
+ response = client.conversational_analysis_authoring.list_assigned_resource_deployments()
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy
+ def test_conversational_analysis_authoring_get_supported_languages(self, conversations_endpoint):
+ client = self.create_client(endpoint=conversations_endpoint)
+ response = client.conversational_analysis_authoring.get_supported_languages(
+ project_kind="str",
+ )
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy
+ def test_conversational_analysis_authoring_get_supported_prebuilt_entities(self, conversations_endpoint):
+ client = self.create_client(endpoint=conversations_endpoint)
+ response = client.conversational_analysis_authoring.get_supported_prebuilt_entities()
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy
+ def test_conversational_analysis_authoring_list_training_config_versions(self, conversations_endpoint):
+ client = self.create_client(endpoint=conversations_endpoint)
+ response = client.conversational_analysis_authoring.list_training_config_versions(
+ project_kind="str",
+ )
+
+ # please add some check logic here by yourself
+ # ...
diff --git a/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/generated_tests/test_conversations_conversational_analysis_authoring_operations_async.py b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/generated_tests/test_conversations_conversational_analysis_authoring_operations_async.py
new file mode 100644
index 000000000000..73ed7a7473b4
--- /dev/null
+++ b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/generated_tests/test_conversations_conversational_analysis_authoring_operations_async.py
@@ -0,0 +1,590 @@
+# 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 ConversationsPreparer
+from testpreparer_async import ConversationsClientTestBaseAsync
+
+
+@pytest.mark.skip("you may need to update the auto-generated test case before run it")
+class TestConversationsConversationalAnalysisAuthoringOperationsAsync(ConversationsClientTestBaseAsync):
+ @ConversationsPreparer()
+ @recorded_by_proxy_async
+ async def test_conversational_analysis_authoring_list_projects(self, conversations_endpoint):
+ client = self.create_async_client(endpoint=conversations_endpoint)
+ response = client.conversational_analysis_authoring.list_projects()
+ result = [r async for r in response]
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy_async
+ async def test_conversational_analysis_authoring_get_project(self, conversations_endpoint):
+ client = self.create_async_client(endpoint=conversations_endpoint)
+ response = await client.conversational_analysis_authoring.get_project(
+ project_name="str",
+ )
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy_async
+ async def test_conversational_analysis_authoring_create_project(self, conversations_endpoint):
+ client = self.create_async_client(endpoint=conversations_endpoint)
+ response = await client.conversational_analysis_authoring.create_project(
+ project_name="str",
+ body={
+ "language": "str",
+ "projectKind": "str",
+ "projectName": "str",
+ "description": "str",
+ "multilingual": bool,
+ "settings": {"confidenceThreshold": 0.0},
+ "storageInputContainerName": "str",
+ },
+ )
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy_async
+ async def test_conversational_analysis_authoring_begin_delete_project(self, conversations_endpoint):
+ client = self.create_async_client(endpoint=conversations_endpoint)
+ response = await (
+ await client.conversational_analysis_authoring.begin_delete_project(
+ project_name="str",
+ )
+ ).result() # call '.result()' to poll until service return final result
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy_async
+ async def test_conversational_analysis_authoring_copy_project_authorization(self, conversations_endpoint):
+ client = self.create_async_client(endpoint=conversations_endpoint)
+ response = await client.conversational_analysis_authoring.copy_project_authorization(
+ project_name="str",
+ body={"projectKind": "str", "allowOverwrite": bool, "storageInputContainerName": "str"},
+ project_kind="str",
+ )
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy_async
+ async def test_conversational_analysis_authoring_begin_copy_project(self, conversations_endpoint):
+ client = self.create_async_client(endpoint=conversations_endpoint)
+ response = await (
+ await client.conversational_analysis_authoring.begin_copy_project(
+ project_name="str",
+ body={
+ "accessToken": "str",
+ "expiresAt": "2020-02-20 00:00:00",
+ "projectKind": "str",
+ "targetProjectName": "str",
+ "targetResourceId": "str",
+ "targetResourceRegion": "str",
+ },
+ )
+ ).result() # call '.result()' to poll until service return final result
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy_async
+ async def test_conversational_analysis_authoring_begin_export(self, conversations_endpoint):
+ client = self.create_async_client(endpoint=conversations_endpoint)
+ response = await (
+ await client.conversational_analysis_authoring.begin_export(
+ project_name="str",
+ string_index_type="str",
+ )
+ ).result() # call '.result()' to poll until service return final result
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy_async
+ async def test_conversational_analysis_authoring_begin_import_method(self, conversations_endpoint):
+ client = self.create_async_client(endpoint=conversations_endpoint)
+ response = await (
+ await client.conversational_analysis_authoring.begin_import_method(
+ project_name="str",
+ body={
+ "metadata": {
+ "language": "str",
+ "projectKind": "str",
+ "projectName": "str",
+ "description": "str",
+ "multilingual": bool,
+ "settings": {"confidenceThreshold": 0.0},
+ "storageInputContainerName": "str",
+ },
+ "projectFileVersion": "str",
+ "stringIndexType": "str",
+ "assets": "conversational_analysis_authoring_exported_project_assets",
+ },
+ )
+ ).result() # call '.result()' to poll until service return final result
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy_async
+ async def test_conversational_analysis_authoring_begin_train(self, conversations_endpoint):
+ client = self.create_async_client(endpoint=conversations_endpoint)
+ response = await (
+ await client.conversational_analysis_authoring.begin_train(
+ project_name="str",
+ body={
+ "modelLabel": "str",
+ "trainingMode": "str",
+ "evaluationOptions": {"kind": "str", "testingSplitPercentage": 0, "trainingSplitPercentage": 0},
+ "trainingConfigVersion": "str",
+ },
+ )
+ ).result() # call '.result()' to poll until service return final result
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy_async
+ async def test_conversational_analysis_authoring_get_copy_project_status(self, conversations_endpoint):
+ client = self.create_async_client(endpoint=conversations_endpoint)
+ response = await client.conversational_analysis_authoring.get_copy_project_status(
+ project_name="str",
+ job_id="str",
+ )
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy_async
+ async def test_conversational_analysis_authoring_list_deployments(self, conversations_endpoint):
+ client = self.create_async_client(endpoint=conversations_endpoint)
+ response = client.conversational_analysis_authoring.list_deployments(
+ project_name="str",
+ )
+ result = [r async for r in response]
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy_async
+ async def test_conversational_analysis_authoring_begin_swap_deployments(self, conversations_endpoint):
+ client = self.create_async_client(endpoint=conversations_endpoint)
+ response = await (
+ await client.conversational_analysis_authoring.begin_swap_deployments(
+ project_name="str",
+ body={"firstDeploymentName": "str", "secondDeploymentName": "str"},
+ )
+ ).result() # call '.result()' to poll until service return final result
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy_async
+ async def test_conversational_analysis_authoring_get_deployment(self, conversations_endpoint):
+ client = self.create_async_client(endpoint=conversations_endpoint)
+ response = await client.conversational_analysis_authoring.get_deployment(
+ project_name="str",
+ deployment_name="str",
+ )
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy_async
+ async def test_conversational_analysis_authoring_begin_deploy_project(self, conversations_endpoint):
+ client = self.create_async_client(endpoint=conversations_endpoint)
+ response = await (
+ await client.conversational_analysis_authoring.begin_deploy_project(
+ project_name="str",
+ deployment_name="str",
+ body={"trainedModelLabel": "str", "assignedResourceIds": ["str"]},
+ )
+ ).result() # call '.result()' to poll until service return final result
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy_async
+ async def test_conversational_analysis_authoring_begin_delete_deployment(self, conversations_endpoint):
+ client = self.create_async_client(endpoint=conversations_endpoint)
+ response = await (
+ await client.conversational_analysis_authoring.begin_delete_deployment(
+ project_name="str",
+ deployment_name="str",
+ )
+ ).result() # call '.result()' to poll until service return final result
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy_async
+ async def test_conversational_analysis_authoring_begin_delete_deployment_from_resources(
+ self, conversations_endpoint
+ ):
+ client = self.create_async_client(endpoint=conversations_endpoint)
+ response = await (
+ await client.conversational_analysis_authoring.begin_delete_deployment_from_resources(
+ project_name="str",
+ deployment_name="str",
+ body={"assignedResourceIds": ["str"]},
+ )
+ ).result() # call '.result()' to poll until service return final result
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy_async
+ async def test_conversational_analysis_authoring_get_deployment_delete_from_resources_status(
+ self, conversations_endpoint
+ ):
+ client = self.create_async_client(endpoint=conversations_endpoint)
+ response = await client.conversational_analysis_authoring.get_deployment_delete_from_resources_status(
+ project_name="str",
+ deployment_name="str",
+ job_id="str",
+ )
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy_async
+ async def test_conversational_analysis_authoring_get_deployment_status(self, conversations_endpoint):
+ client = self.create_async_client(endpoint=conversations_endpoint)
+ response = await client.conversational_analysis_authoring.get_deployment_status(
+ project_name="str",
+ deployment_name="str",
+ job_id="str",
+ )
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy_async
+ async def test_conversational_analysis_authoring_get_swap_deployments_status(self, conversations_endpoint):
+ client = self.create_async_client(endpoint=conversations_endpoint)
+ response = await client.conversational_analysis_authoring.get_swap_deployments_status(
+ project_name="str",
+ job_id="str",
+ )
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy_async
+ async def test_conversational_analysis_authoring_get_export_status(self, conversations_endpoint):
+ client = self.create_async_client(endpoint=conversations_endpoint)
+ response = await client.conversational_analysis_authoring.get_export_status(
+ project_name="str",
+ job_id="str",
+ )
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy_async
+ async def test_conversational_analysis_authoring_get_import_status(self, conversations_endpoint):
+ client = self.create_async_client(endpoint=conversations_endpoint)
+ response = await client.conversational_analysis_authoring.get_import_status(
+ project_name="str",
+ job_id="str",
+ )
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy_async
+ async def test_conversational_analysis_authoring_list_trained_models(self, conversations_endpoint):
+ client = self.create_async_client(endpoint=conversations_endpoint)
+ response = client.conversational_analysis_authoring.list_trained_models(
+ project_name="str",
+ )
+ result = [r async for r in response]
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy_async
+ async def test_conversational_analysis_authoring_get_trained_model(self, conversations_endpoint):
+ client = self.create_async_client(endpoint=conversations_endpoint)
+ response = await client.conversational_analysis_authoring.get_trained_model(
+ project_name="str",
+ trained_model_label="str",
+ )
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy_async
+ async def test_conversational_analysis_authoring_delete_trained_model(self, conversations_endpoint):
+ client = self.create_async_client(endpoint=conversations_endpoint)
+ response = await client.conversational_analysis_authoring.delete_trained_model(
+ project_name="str",
+ trained_model_label="str",
+ )
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy_async
+ async def test_conversational_analysis_authoring_begin_evaluate_model(self, conversations_endpoint):
+ client = self.create_async_client(endpoint=conversations_endpoint)
+ response = await (
+ await client.conversational_analysis_authoring.begin_evaluate_model(
+ project_name="str",
+ trained_model_label="str",
+ body={"kind": "str", "testingSplitPercentage": 0, "trainingSplitPercentage": 0},
+ )
+ ).result() # call '.result()' to poll until service return final result
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy_async
+ async def test_conversational_analysis_authoring_begin_load_snapshot(self, conversations_endpoint):
+ client = self.create_async_client(endpoint=conversations_endpoint)
+ response = await (
+ await client.conversational_analysis_authoring.begin_load_snapshot(
+ project_name="str",
+ trained_model_label="str",
+ )
+ ).result() # call '.result()' to poll until service return final result
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy_async
+ async def test_conversational_analysis_authoring_get_evaluation_status(self, conversations_endpoint):
+ client = self.create_async_client(endpoint=conversations_endpoint)
+ response = await client.conversational_analysis_authoring.get_evaluation_status(
+ project_name="str",
+ trained_model_label="str",
+ job_id="str",
+ )
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy_async
+ async def test_conversational_analysis_authoring_get_model_evaluation_results(self, conversations_endpoint):
+ client = self.create_async_client(endpoint=conversations_endpoint)
+ response = client.conversational_analysis_authoring.get_model_evaluation_results(
+ project_name="str",
+ trained_model_label="str",
+ string_index_type="str",
+ )
+ result = [r async for r in response]
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy_async
+ async def test_conversational_analysis_authoring_get_model_evaluation_summary(self, conversations_endpoint):
+ client = self.create_async_client(endpoint=conversations_endpoint)
+ response = await client.conversational_analysis_authoring.get_model_evaluation_summary(
+ project_name="str",
+ trained_model_label="str",
+ )
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy_async
+ async def test_conversational_analysis_authoring_get_load_snapshot_status(self, conversations_endpoint):
+ client = self.create_async_client(endpoint=conversations_endpoint)
+ response = await client.conversational_analysis_authoring.get_load_snapshot_status(
+ project_name="str",
+ trained_model_label="str",
+ job_id="str",
+ )
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy_async
+ async def test_conversational_analysis_authoring_list_deployment_resources(self, conversations_endpoint):
+ client = self.create_async_client(endpoint=conversations_endpoint)
+ response = client.conversational_analysis_authoring.list_deployment_resources(
+ project_name="str",
+ )
+ result = [r async for r in response]
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy_async
+ async def test_conversational_analysis_authoring_begin_assign_deployment_resources(self, conversations_endpoint):
+ client = self.create_async_client(endpoint=conversations_endpoint)
+ response = await (
+ await client.conversational_analysis_authoring.begin_assign_deployment_resources(
+ project_name="str",
+ body={"resourcesMetadata": [{"azureResourceId": "str", "customDomain": "str", "region": "str"}]},
+ )
+ ).result() # call '.result()' to poll until service return final result
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy_async
+ async def test_conversational_analysis_authoring_begin_unassign_deployment_resources(self, conversations_endpoint):
+ client = self.create_async_client(endpoint=conversations_endpoint)
+ response = await (
+ await client.conversational_analysis_authoring.begin_unassign_deployment_resources(
+ project_name="str",
+ body={"assignedResourceIds": ["str"]},
+ )
+ ).result() # call '.result()' to poll until service return final result
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy_async
+ async def test_conversational_analysis_authoring_get_assign_deployment_resources_status(
+ self, conversations_endpoint
+ ):
+ client = self.create_async_client(endpoint=conversations_endpoint)
+ response = await client.conversational_analysis_authoring.get_assign_deployment_resources_status(
+ project_name="str",
+ job_id="str",
+ )
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy_async
+ async def test_conversational_analysis_authoring_get_unassign_deployment_resources_status(
+ self, conversations_endpoint
+ ):
+ client = self.create_async_client(endpoint=conversations_endpoint)
+ response = await client.conversational_analysis_authoring.get_unassign_deployment_resources_status(
+ project_name="str",
+ job_id="str",
+ )
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy_async
+ async def test_conversational_analysis_authoring_list_training_jobs(self, conversations_endpoint):
+ client = self.create_async_client(endpoint=conversations_endpoint)
+ response = client.conversational_analysis_authoring.list_training_jobs(
+ project_name="str",
+ )
+ result = [r async for r in response]
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy_async
+ async def test_conversational_analysis_authoring_get_training_status(self, conversations_endpoint):
+ client = self.create_async_client(endpoint=conversations_endpoint)
+ response = await client.conversational_analysis_authoring.get_training_status(
+ project_name="str",
+ job_id="str",
+ )
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy_async
+ async def test_conversational_analysis_authoring_begin_cancel_training_job(self, conversations_endpoint):
+ client = self.create_async_client(endpoint=conversations_endpoint)
+ response = await (
+ await client.conversational_analysis_authoring.begin_cancel_training_job(
+ project_name="str",
+ job_id="str",
+ )
+ ).result() # call '.result()' to poll until service return final result
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy_async
+ async def test_conversational_analysis_authoring_get_project_deletion_status(self, conversations_endpoint):
+ client = self.create_async_client(endpoint=conversations_endpoint)
+ response = await client.conversational_analysis_authoring.get_project_deletion_status(
+ job_id="str",
+ )
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy_async
+ async def test_conversational_analysis_authoring_list_assigned_resource_deployments(self, conversations_endpoint):
+ client = self.create_async_client(endpoint=conversations_endpoint)
+ response = await client.conversational_analysis_authoring.list_assigned_resource_deployments()
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy_async
+ async def test_conversational_analysis_authoring_get_supported_languages(self, conversations_endpoint):
+ client = self.create_async_client(endpoint=conversations_endpoint)
+ response = await client.conversational_analysis_authoring.get_supported_languages(
+ project_kind="str",
+ )
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy_async
+ async def test_conversational_analysis_authoring_get_supported_prebuilt_entities(self, conversations_endpoint):
+ client = self.create_async_client(endpoint=conversations_endpoint)
+ response = await client.conversational_analysis_authoring.get_supported_prebuilt_entities()
+
+ # please add some check logic here by yourself
+ # ...
+
+ @ConversationsPreparer()
+ @recorded_by_proxy_async
+ async def test_conversational_analysis_authoring_list_training_config_versions(self, conversations_endpoint):
+ client = self.create_async_client(endpoint=conversations_endpoint)
+ response = await client.conversational_analysis_authoring.list_training_config_versions(
+ project_kind="str",
+ )
+
+ # please add some check logic here by yourself
+ # ...
diff --git a/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/generated_tests/testpreparer.py b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/generated_tests/testpreparer.py
new file mode 100644
index 000000000000..0fab119f4583
--- /dev/null
+++ b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/generated_tests/testpreparer.py
@@ -0,0 +1,26 @@
+# 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.Language.Authoring.Analyzeconversations import ConversationsClient
+from devtools_testutils import AzureRecordedTestCase, PowerShellPreparer
+import functools
+
+
+class ConversationsClientTestBase(AzureRecordedTestCase):
+
+ def create_client(self, endpoint):
+ credential = self.get_credential(ConversationsClient)
+ return self.create_client_from_credential(
+ ConversationsClient,
+ credential=credential,
+ endpoint=endpoint,
+ )
+
+
+ConversationsPreparer = functools.partial(
+ PowerShellPreparer, "conversations", conversations_endpoint="https://fake_conversations_endpoint.com"
+)
diff --git a/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/generated_tests/testpreparer_async.py b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/generated_tests/testpreparer_async.py
new file mode 100644
index 000000000000..a55dce3911f6
--- /dev/null
+++ b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/generated_tests/testpreparer_async.py
@@ -0,0 +1,20 @@
+# 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.Language.Authoring.Analyzeconversations.aio import ConversationsClient
+from devtools_testutils import AzureRecordedTestCase
+
+
+class ConversationsClientTestBaseAsync(AzureRecordedTestCase):
+
+ def create_async_client(self, endpoint):
+ credential = self.get_credential(ConversationsClient, is_async=True)
+ return self.create_client_from_credential(
+ ConversationsClient,
+ credential=credential,
+ endpoint=endpoint,
+ )
diff --git a/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/setup.py b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/setup.py
new file mode 100644
index 000000000000..c020848a5d50
--- /dev/null
+++ b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/setup.py
@@ -0,0 +1,68 @@
+# 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.
+# --------------------------------------------------------------------------
+# coding: utf-8
+
+import os
+import re
+from setuptools import setup, find_packages
+
+
+PACKAGE_NAME = "azure.ai.language.authoring.analyzeconversations"
+PACKAGE_PPRINT_NAME = "Azure AI Language Authoring Analyzeconversations"
+
+# a-b-c => a/b/c
+package_folder_path = PACKAGE_NAME.replace("-", "/")
+
+# Version extraction inspired from 'requests'
+with open(os.path.join(package_folder_path, "_version.py"), "r") as fd:
+ version = re.search(r'^VERSION\s*=\s*[\'"]([^\'"]*)[\'"]', fd.read(), re.MULTILINE).group(1)
+
+if not version:
+ raise RuntimeError("Cannot find version information")
+
+
+setup(
+ name=PACKAGE_NAME,
+ version=version,
+ description="Microsoft {} Client Library for Python".format(PACKAGE_PPRINT_NAME),
+ long_description=open("README.md", "r").read(),
+ long_description_content_type="text/markdown",
+ license="MIT License",
+ author="Microsoft Corporation",
+ author_email="azpysdkhelp@microsoft.com",
+ url="https://github.com/Azure/azure-sdk-for-python/tree/main/sdk",
+ keywords="azure, azure sdk",
+ classifiers=[
+ "Development Status :: 5 - Production/Stable",
+ "Programming Language :: Python",
+ "Programming Language :: Python :: 3 :: Only",
+ "Programming Language :: Python :: 3",
+ "Programming Language :: Python :: 3.8",
+ "Programming Language :: Python :: 3.9",
+ "Programming Language :: Python :: 3.10",
+ "Programming Language :: Python :: 3.11",
+ "Programming Language :: Python :: 3.12",
+ "License :: OSI Approved :: MIT License",
+ ],
+ zip_safe=False,
+ packages=find_packages(
+ exclude=[
+ "tests",
+ ]
+ ),
+ include_package_data=True,
+ package_data={
+ "azure.ai.language.authoring.analyzeconversations": ["py.typed"],
+ },
+ install_requires=[
+ "isodate>=0.6.1",
+ "azure-core>=1.30.0",
+ "typing-extensions>=4.6.0",
+ ],
+ python_requires=">=3.8",
+)
diff --git a/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/tsp-location.yaml b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/tsp-location.yaml
new file mode 100644
index 000000000000..50ab0ae256a2
--- /dev/null
+++ b/sdk/cognitivelanguage/authoring/analyzeconversations/Azure.AI.Language.Authoring.Analyzeconversations/tsp-location.yaml
@@ -0,0 +1,4 @@
+directory: specification/cognitiveservices/Language.AnalyzeConversations-authoring
+commit: 74c718eba2bb548b6532f58c1de30f6c34b06c23
+repo: Azure/azure-rest-api-specs
+additionalDirectories: