diff --git a/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/CHANGELOG.md b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/CHANGELOG.md new file mode 100644 index 000000000000..628743d283a9 --- /dev/null +++ b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/CHANGELOG.md @@ -0,0 +1,5 @@ +# Release History + +## 1.0.0b1 (1970-01-01) + +- Initial version diff --git a/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/LICENSE b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/LICENSE new file mode 100644 index 000000000000..63447fd8bbbf --- /dev/null +++ b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/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/azure-ai-language-conversations-authoring/MANIFEST.in b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/MANIFEST.in new file mode 100644 index 000000000000..9de0c69aa920 --- /dev/null +++ b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/MANIFEST.in @@ -0,0 +1,9 @@ +include *.md +include LICENSE +include azure/ai/language/conversations/authoring/py.typed +recursive-include tests *.py +recursive-include samples *.py *.md +include azure/__init__.py +include azure/ai/__init__.py +include azure/ai/language/__init__.py +include azure/ai/language/conversations/__init__.py \ No newline at end of file diff --git a/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/README.md b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/README.md new file mode 100644 index 000000000000..e566b380c73d --- /dev/null +++ b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/README.md @@ -0,0 +1,45 @@ + + +# Azure Ai Language Conversations Authoring client library for Python + + +## Getting started + +### Install the package + +```bash +python -m pip install azure-ai-language-conversations-authoring +``` + +#### 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 Conversations Authoring 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/azure-ai-language-conversations-authoring/_meta.json b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/_meta.json new file mode 100644 index 000000000000..07843f0981bc --- /dev/null +++ b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/_meta.json @@ -0,0 +1,6 @@ +{ + "commit": "9bc056657f7b73ede802cee645b0aeb98c6d33cd", + "repository_url": "https://github.com/Azure/azure-rest-api-specs", + "typespec_src": "specification/cognitiveservices/Language.AnalyzeConversations-authoring", + "@azure-tools/typespec-python": "0.38.4" +} \ No newline at end of file diff --git a/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/apiview-properties.json b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/apiview-properties.json new file mode 100644 index 000000000000..e83cab2545bf --- /dev/null +++ b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/apiview-properties.json @@ -0,0 +1,144 @@ +{ + "CrossLanguagePackageId": "Language.Conversations.Authoring", + "CrossLanguageDefinitionId": { + "azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringAssignDeploymentResourcesOptions": 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"azure.ai.language.conversations.authoring.AuthoringClient.analyze_conversation_authoring.begin_evaluate_model": "Language.Conversations.Authoring.AnalyzeConversationAuthoring.evaluateModel", + "azure.ai.language.conversations.authoring.AuthoringClient.analyze_conversation_authoring.begin_load_snapshot": "Language.Conversations.Authoring.AnalyzeConversationAuthoring.loadSnapshot", + "azure.ai.language.conversations.authoring.AuthoringClient.analyze_conversation_authoring.get_evaluation_status": "Language.Conversations.Authoring.AnalyzeConversationAuthoring.getEvaluationStatus", + "azure.ai.language.conversations.authoring.AuthoringClient.analyze_conversation_authoring.get_model_evaluation_results": "Language.Conversations.Authoring.AnalyzeConversationAuthoring.getModelEvaluationResults", + "azure.ai.language.conversations.authoring.AuthoringClient.analyze_conversation_authoring.get_model_evaluation_summary": "Language.Conversations.Authoring.AnalyzeConversationAuthoring.getModelEvaluationSummary", + "azure.ai.language.conversations.authoring.AuthoringClient.analyze_conversation_authoring.get_load_snapshot_status": "Language.Conversations.Authoring.AnalyzeConversationAuthoring.getLoadSnapshotStatus", + "azure.ai.language.conversations.authoring.AuthoringClient.analyze_conversation_authoring.list_deployment_resources": "Language.Conversations.Authoring.AnalyzeConversationAuthoring.listDeploymentResources", + "azure.ai.language.conversations.authoring.AuthoringClient.analyze_conversation_authoring.begin_assign_deployment_resources": "Language.Conversations.Authoring.AnalyzeConversationAuthoring.assignDeploymentResources", + "azure.ai.language.conversations.authoring.AuthoringClient.analyze_conversation_authoring.begin_unassign_deployment_resources": "Language.Conversations.Authoring.AnalyzeConversationAuthoring.unassignDeploymentResources", + "azure.ai.language.conversations.authoring.AuthoringClient.analyze_conversation_authoring.get_assign_deployment_resources_status": "Language.Conversations.Authoring.AnalyzeConversationAuthoring.getAssignDeploymentResourcesStatus", + "azure.ai.language.conversations.authoring.AuthoringClient.analyze_conversation_authoring.get_unassign_deployment_resources_status": "Language.Conversations.Authoring.AnalyzeConversationAuthoring.getUnassignDeploymentResourcesStatus", + "azure.ai.language.conversations.authoring.AuthoringClient.analyze_conversation_authoring.list_training_jobs": "Language.Conversations.Authoring.AnalyzeConversationAuthoring.listTrainingJobs", + "azure.ai.language.conversations.authoring.AuthoringClient.analyze_conversation_authoring.get_training_status": "Language.Conversations.Authoring.AnalyzeConversationAuthoring.getTrainingStatus", + "azure.ai.language.conversations.authoring.AuthoringClient.analyze_conversation_authoring.begin_cancel_training_job": "Language.Conversations.Authoring.AnalyzeConversationAuthoring.cancelTrainingJob", + "azure.ai.language.conversations.authoring.AuthoringClient.analyze_conversation_authoring.get_project_deletion_status": "Language.Conversations.Authoring.AnalyzeConversationAuthoring.getProjectDeletionStatus", + "azure.ai.language.conversations.authoring.AuthoringClient.analyze_conversation_authoring.list_assigned_resource_deployments": "Language.Conversations.Authoring.AnalyzeConversationAuthoring.listAssignedResourceDeployments", + "azure.ai.language.conversations.authoring.AuthoringClient.analyze_conversation_authoring.get_supported_languages": "Language.Conversations.Authoring.AnalyzeConversationAuthoring.getSupportedLanguages", + "azure.ai.language.conversations.authoring.AuthoringClient.analyze_conversation_authoring.get_supported_prebuilt_entities": "Language.Conversations.Authoring.AnalyzeConversationAuthoring.getSupportedPrebuiltEntities", + "azure.ai.language.conversations.authoring.AuthoringClient.analyze_conversation_authoring.list_training_config_versions": "Language.Conversations.Authoring.AnalyzeConversationAuthoring.listTrainingConfigVersions", + "azure.ai.language.conversations.authoring.AuthoringClient.analyze_conversation_authoring.get_exported_model": "Language.Conversations.Authoring.AnalyzeConversationAuthoring.getExportedModel", + "azure.ai.language.conversations.authoring.AuthoringClient.analyze_conversation_authoring.list_exported_models": "Language.Conversations.Authoring.AnalyzeConversationAuthoring.listExportedModels", + "azure.ai.language.conversations.authoring.AuthoringClient.analyze_conversation_authoring.begin_delete_exported_model": "Language.Conversations.Authoring.AnalyzeConversationAuthoring.deleteExportedModel", + "azure.ai.language.conversations.authoring.AuthoringClient.analyze_conversation_authoring.begin_create_or_update_exported_model": "Language.Conversations.Authoring.AnalyzeConversationAuthoring.createOrUpdateExportedModel", + "azure.ai.language.conversations.authoring.AuthoringClient.analyze_conversation_authoring.get_exported_model_job_status": "Language.Conversations.Authoring.AnalyzeConversationAuthoring.getExportedModelJobStatus" + } +} \ No newline at end of file diff --git a/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/__init__.py b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/__init__.py new file mode 100644 index 000000000000..d55ccad1f573 --- /dev/null +++ b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/__init__.py @@ -0,0 +1 @@ +__path__ = __import__("pkgutil").extend_path(__path__, __name__) # type: ignore diff --git a/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/__init__.py b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/__init__.py new file mode 100644 index 000000000000..d55ccad1f573 --- /dev/null +++ b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/__init__.py @@ -0,0 +1 @@ +__path__ = __import__("pkgutil").extend_path(__path__, __name__) # type: ignore diff --git a/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/language/__init__.py b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/language/__init__.py new file mode 100644 index 000000000000..d55ccad1f573 --- /dev/null +++ b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/language/__init__.py @@ -0,0 +1 @@ +__path__ = __import__("pkgutil").extend_path(__path__, __name__) # type: ignore diff --git a/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/language/conversations/__init__.py b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/language/conversations/__init__.py new file mode 100644 index 000000000000..d55ccad1f573 --- /dev/null +++ b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/language/conversations/__init__.py @@ -0,0 +1 @@ +__path__ = __import__("pkgutil").extend_path(__path__, __name__) # type: ignore diff --git a/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/__init__.py b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/__init__.py new file mode 100644 index 000000000000..ce08a8f13349 --- /dev/null +++ b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/__init__.py @@ -0,0 +1,32 @@ +# coding=utf-8 +# -------------------------------------------------------------------------- +# Copyright (c) Microsoft Corporation. All rights reserved. +# Licensed under the MIT License. See License.txt in the project root for license information. +# Code generated by Microsoft (R) Python Code Generator. +# Changes may cause incorrect behavior and will be lost if the code is regenerated. +# -------------------------------------------------------------------------- +# pylint: disable=wrong-import-position + +from typing import TYPE_CHECKING + +if TYPE_CHECKING: + from ._patch import * # pylint: disable=unused-wildcard-import + +from ._client import AuthoringClient # type: ignore +from ._version import VERSION + +__version__ = VERSION + +try: + from ._patch import __all__ as _patch_all + from ._patch import * +except ImportError: + _patch_all = [] +from ._patch import patch_sdk as _patch_sdk + +__all__ = [ + "AuthoringClient", +] +__all__.extend([p for p in _patch_all if p not in __all__]) # pyright: ignore + +_patch_sdk() diff --git a/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/_client.py b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/_client.py new file mode 100644 index 000000000000..99cff5e6bded --- /dev/null +++ b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/_client.py @@ -0,0 +1,115 @@ +# pylint: disable=line-too-long,useless-suppression +# 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 AuthoringClientConfiguration +from ._serialization import Deserializer, Serializer +from .operations import AnalyzeConversationAuthoringOperations + +if TYPE_CHECKING: + from azure.core.credentials import TokenCredential + + +class AuthoringClient: + """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://learn.microsoft.com/en-us/azure/cognitive-services/language-service/overview`. + + :ivar analyze_conversation_authoring: AnalyzeConversationAuthoringOperations operations + :vartype analyze_conversation_authoring: + azure.ai.language.conversations.authoring.operations.AnalyzeConversationAuthoringOperations + :param endpoint: Supported Cognitive Services endpoint e.g., https://\\\\ + :code:``.api.cognitiveservices.azure.com. Required. + :type endpoint: str + :param credential: Credential used to authenticate requests to the service. Is either a key + credential type or a token credential type. Required. + :type credential: ~azure.core.credentials.AzureKeyCredential or + ~azure.core.credentials.TokenCredential + :keyword api_version: The API version to use for this operation. Default value is + "2024-11-15-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, credential: Union[AzureKeyCredential, "TokenCredential"], **kwargs: Any) -> None: + _endpoint = "{Endpoint}/language" + self._config = AuthoringClientConfiguration(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.analyze_conversation_authoring = AnalyzeConversationAuthoringOperations( + 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", skip_quote=True), + } + + 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/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/_configuration.py b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/_configuration.py new file mode 100644 index 000000000000..5a970874f700 --- /dev/null +++ b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/_configuration.py @@ -0,0 +1,73 @@ +# 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 AuthoringClientConfiguration: # pylint: disable=too-many-instance-attributes + """Configuration for AuthoringClient. + + 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 credential: Credential used to authenticate requests to the service. Is either a key + credential type or a token credential type. Required. + :type credential: ~azure.core.credentials.AzureKeyCredential or + ~azure.core.credentials.TokenCredential + :keyword api_version: The API version to use for this operation. Default value is + "2024-11-15-preview". Note that overriding this default value may result in unsupported + behavior. + :paramtype api_version: str + """ + + def __init__(self, endpoint: str, credential: Union[AzureKeyCredential, "TokenCredential"], **kwargs: Any) -> None: + api_version: str = kwargs.pop("api_version", "2024-11-15-preview") + + 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.credential = credential + self.api_version = api_version + self.credential_scopes = kwargs.pop("credential_scopes", ["https://cognitiveservices.azure.com/.default"]) + kwargs.setdefault("sdk_moniker", "ai-language-conversations-authoring/{}".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/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/_model_base.py b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/_model_base.py new file mode 100644 index 000000000000..3072ee252ed9 --- /dev/null +++ b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/_model_base.py @@ -0,0 +1,1235 @@ +# 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, broad-except + +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]: + """ + :returns: a set-like object providing a view on D's keys + :rtype: ~typing.KeysView + """ + return self._data.keys() + + def values(self) -> typing.ValuesView[typing.Any]: + """ + :returns: an object providing a view on D's values + :rtype: ~typing.ValuesView + """ + return self._data.values() + + def items(self) -> typing.ItemsView[str, typing.Any]: + """ + :returns: set-like object providing a view on D's items + :rtype: ~typing.ItemsView + """ + return self._data.items() + + def get(self, key: str, default: typing.Any = None) -> typing.Any: + """ + Get the value for key if key is in the dictionary, else default. + :param str key: The key to look up. + :param any default: The value to return if key is not in the dictionary. Defaults to None + :returns: D[k] if k in D, else d. + :rtype: 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: + """ + Removes specified key and return the corresponding value. + :param str key: The key to pop. + :param any default: The value to return if key is not in the dictionary + :returns: The value corresponding to the key. + :rtype: any + :raises KeyError: If key is not found and default is not given. + """ + if default is _UNSET: + return self._data.pop(key) + return self._data.pop(key, default) + + def popitem(self) -> typing.Tuple[str, typing.Any]: + """ + Removes and returns some (key, value) pair + :returns: The (key, value) pair. + :rtype: tuple + :raises KeyError: if D is empty. + """ + return self._data.popitem() + + def clear(self) -> None: + """ + Remove all items from D. + """ + self._data.clear() + + def update(self, *args: typing.Any, **kwargs: typing.Any) -> None: + """ + Updates D from mapping/iterable E and F. + :param any args: Either a mapping object or an iterable of key-value pairs. + """ + 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: + """ + Same as calling D.get(k, d), and setting D[k]=d if k not found + :param str key: The key to look up. + :param any default: The value to set if key is not in the dictionary + :returns: D[k] if k in D, else d. + :rtype: 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: + 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__") + for k, v in mro_class.__annotations__.items() + } + 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__"): + base.__mapping__[discriminator or cls.__name__] = cls # type: ignore + + @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__"): + 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 + 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) # type: ignore + + 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) + + +def _failsafe_deserialize( + deserializer: typing.Any, + value: typing.Any, + module: typing.Optional[str] = None, + rf: typing.Optional["_RestField"] = None, + format: typing.Optional[str] = None, +) -> typing.Any: + try: + return _deserialize(deserializer, value, module, rf, format) + except DeserializationError: + _LOGGER.warning( + "Ran into a deserialization error. Ignoring since this is failsafe deserialization", exc_info=True + ) + return None + + +def _failsafe_deserialize_xml( + deserializer: typing.Any, + value: typing.Any, +) -> typing.Any: + try: + return _deserialize_xml(deserializer, value) + except DeserializationError: + _LOGGER.warning( + "Ran into a deserialization error. Ignoring since this is failsafe deserialization", exc_info=True + ) + return None + + +class _RestField: + def __init__( + self, + *, + 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/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/_patch.py b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/_patch.py new file mode 100644 index 000000000000..f7dd32510333 --- /dev/null +++ b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/_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/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/_serialization.py b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/_serialization.py new file mode 100644 index 000000000000..e2a20b1d534c --- /dev/null +++ b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/_serialization.py @@ -0,0 +1,2050 @@ +# pylint: disable=line-too-long,useless-suppression,too-many-lines +# -------------------------------------------------------------------------- +# +# 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, + MutableMapping, + 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 typing_extensions import Self + +from azure.core.exceptions import DeserializationError, SerializationError +from azure.core.serialization import NULL as CoreNull + +_BOM = codecs.BOM_UTF8.decode(encoding="utf-8") + +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 + +TZ_UTC = datetime.timezone.utc + +_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, data: Any, content_type: Optional[str] = None) -> Self: + """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: Self + """ + deserializer = Deserializer(cls._infer_class_models()) + return deserializer(cls.__name__, data, content_type=content_type) # type: ignore + + @classmethod + def from_dict( + cls, + data: Any, + key_extractors: Optional[Callable[[str, Dict[str, Any], Any], Any]] = None, + content_type: Optional[str] = None, + ) -> Self: + """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: Self + """ + 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. + + :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.get(rest_api_response_key, None) or response.get(subtype_key, None) + else: + subtype_value = xml_key_extractor(subtype_key, cls._attribute_map[subtype_key], response) + if subtype_value: + # 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: # 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( + 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: + """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() # pylint: disable=protected-access # type: ignore + if v.get("readonly") + ] + const = [ + k + for k, v in response._validation.items() # pylint: disable=protected-access # type: ignore + if v.get("constant") + ] + kwargs = {k: v for k, v in attrs.items() if k not in subtype and k not in readonly + const} + response_obj = response(**kwargs) + for attr in readonly: + setattr(response_obj, attr, attrs.get(attr)) + if additional_properties: + response_obj.additional_properties = additional_properties # type: ignore + 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=datetime.timezone(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/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/_validation.py b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/_validation.py new file mode 100644 index 000000000000..752b2822f9d3 --- /dev/null +++ b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/_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/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/_version.py b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/_version.py new file mode 100644 index 000000000000..be71c81bd282 --- /dev/null +++ b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/_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 = "1.0.0b1" diff --git a/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/aio/__init__.py b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/aio/__init__.py new file mode 100644 index 000000000000..9212a0141270 --- /dev/null +++ b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/aio/__init__.py @@ -0,0 +1,29 @@ +# 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. +# -------------------------------------------------------------------------- +# pylint: disable=wrong-import-position + +from typing import TYPE_CHECKING + +if TYPE_CHECKING: + from ._patch import * # pylint: disable=unused-wildcard-import + +from ._client import AuthoringClient # type: ignore + +try: + from ._patch import __all__ as _patch_all + from ._patch import * +except ImportError: + _patch_all = [] +from ._patch import patch_sdk as _patch_sdk + +__all__ = [ + "AuthoringClient", +] +__all__.extend([p for p in _patch_all if p not in __all__]) # pyright: ignore + +_patch_sdk() diff --git a/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/aio/_client.py b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/aio/_client.py new file mode 100644 index 000000000000..b762b8cce6f9 --- /dev/null +++ b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/aio/_client.py @@ -0,0 +1,119 @@ +# pylint: disable=line-too-long,useless-suppression +# 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 AuthoringClientConfiguration +from .operations import AnalyzeConversationAuthoringOperations + +if TYPE_CHECKING: + from azure.core.credentials_async import AsyncTokenCredential + + +class AuthoringClient: + """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://learn.microsoft.com/en-us/azure/cognitive-services/language-service/overview`. + + :ivar analyze_conversation_authoring: AnalyzeConversationAuthoringOperations operations + :vartype analyze_conversation_authoring: + azure.ai.language.conversations.authoring.aio.operations.AnalyzeConversationAuthoringOperations + :param endpoint: Supported Cognitive Services endpoint e.g., https://\\\\ + :code:``.api.cognitiveservices.azure.com. Required. + :type endpoint: str + :param credential: Credential used to authenticate requests to the service. Is either a key + credential type or a token credential type. Required. + :type credential: ~azure.core.credentials.AzureKeyCredential or + ~azure.core.credentials_async.AsyncTokenCredential + :keyword api_version: The API version to use for this operation. Default value is + "2024-11-15-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, credential: Union[AzureKeyCredential, "AsyncTokenCredential"], **kwargs: Any + ) -> None: + _endpoint = "{Endpoint}/language" + self._config = AuthoringClientConfiguration(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.analyze_conversation_authoring = AnalyzeConversationAuthoringOperations( + 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", skip_quote=True), + } + + 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/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/aio/_configuration.py b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/aio/_configuration.py new file mode 100644 index 000000000000..e171bfc0217f --- /dev/null +++ b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/aio/_configuration.py @@ -0,0 +1,75 @@ +# 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 AuthoringClientConfiguration: # pylint: disable=too-many-instance-attributes + """Configuration for AuthoringClient. + + 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 credential: Credential used to authenticate requests to the service. Is either a key + credential type or a token credential type. Required. + :type credential: ~azure.core.credentials.AzureKeyCredential or + ~azure.core.credentials_async.AsyncTokenCredential + :keyword api_version: The API version to use for this operation. Default value is + "2024-11-15-preview". Note that overriding this default value may result in unsupported + behavior. + :paramtype api_version: str + """ + + def __init__( + self, endpoint: str, credential: Union[AzureKeyCredential, "AsyncTokenCredential"], **kwargs: Any + ) -> None: + api_version: str = kwargs.pop("api_version", "2024-11-15-preview") + + 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.credential = credential + self.api_version = api_version + self.credential_scopes = kwargs.pop("credential_scopes", ["https://cognitiveservices.azure.com/.default"]) + kwargs.setdefault("sdk_moniker", "ai-language-conversations-authoring/{}".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/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/aio/_patch.py b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/aio/_patch.py new file mode 100644 index 000000000000..f7dd32510333 --- /dev/null +++ b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/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/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/aio/operations/__init__.py b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/aio/operations/__init__.py new file mode 100644 index 000000000000..b1edaad8b818 --- /dev/null +++ b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/aio/operations/__init__.py @@ -0,0 +1,25 @@ +# 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. +# -------------------------------------------------------------------------- +# pylint: disable=wrong-import-position + +from typing import TYPE_CHECKING + +if TYPE_CHECKING: + from ._patch import * # pylint: disable=unused-wildcard-import + +from ._operations import AnalyzeConversationAuthoringOperations # type: ignore + +from ._patch import __all__ as _patch_all +from ._patch import * +from ._patch import patch_sdk as _patch_sdk + +__all__ = [ + "AnalyzeConversationAuthoringOperations", +] +__all__.extend([p for p in _patch_all if p not in __all__]) # pyright: ignore +_patch_sdk() diff --git a/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/aio/operations/_operations.py b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/aio/operations/_operations.py new file mode 100644 index 000000000000..cd50f5d7e5a0 --- /dev/null +++ b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/aio/operations/_operations.py @@ -0,0 +1,5726 @@ +# pylint: disable=line-too-long,useless-suppression,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 import AsyncPipelineClient +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, _failsafe_deserialize +from ..._serialization import Deserializer, Serializer +from ..._validation import api_version_validation +from ...operations._operations import ( + build_analyze_conversation_authoring_assign_deployment_resources_request, + build_analyze_conversation_authoring_cancel_training_job_request, + build_analyze_conversation_authoring_copy_project_authorization_request, + build_analyze_conversation_authoring_copy_project_request, + build_analyze_conversation_authoring_create_or_update_exported_model_request, + build_analyze_conversation_authoring_create_project_request, + build_analyze_conversation_authoring_delete_deployment_from_resources_request, + build_analyze_conversation_authoring_delete_deployment_request, + build_analyze_conversation_authoring_delete_exported_model_request, + build_analyze_conversation_authoring_delete_project_request, + build_analyze_conversation_authoring_delete_trained_model_request, + build_analyze_conversation_authoring_deploy_project_request, + build_analyze_conversation_authoring_evaluate_model_request, + build_analyze_conversation_authoring_export_request, + build_analyze_conversation_authoring_get_assign_deployment_resources_status_request, + build_analyze_conversation_authoring_get_copy_project_status_request, + build_analyze_conversation_authoring_get_deployment_delete_from_resources_status_request, + build_analyze_conversation_authoring_get_deployment_request, + build_analyze_conversation_authoring_get_deployment_status_request, + build_analyze_conversation_authoring_get_evaluation_status_request, + build_analyze_conversation_authoring_get_export_status_request, + build_analyze_conversation_authoring_get_exported_model_job_status_request, + build_analyze_conversation_authoring_get_exported_model_request, + build_analyze_conversation_authoring_get_import_status_request, + build_analyze_conversation_authoring_get_load_snapshot_status_request, + build_analyze_conversation_authoring_get_model_evaluation_results_request, + build_analyze_conversation_authoring_get_model_evaluation_summary_request, + build_analyze_conversation_authoring_get_project_deletion_status_request, + build_analyze_conversation_authoring_get_project_request, + build_analyze_conversation_authoring_get_supported_languages_request, + build_analyze_conversation_authoring_get_supported_prebuilt_entities_request, + build_analyze_conversation_authoring_get_swap_deployments_status_request, + build_analyze_conversation_authoring_get_trained_model_request, + build_analyze_conversation_authoring_get_training_status_request, + build_analyze_conversation_authoring_get_unassign_deployment_resources_status_request, + build_analyze_conversation_authoring_import_method_request, + build_analyze_conversation_authoring_list_assigned_resource_deployments_request, + build_analyze_conversation_authoring_list_deployment_resources_request, + build_analyze_conversation_authoring_list_deployments_request, + build_analyze_conversation_authoring_list_exported_models_request, + build_analyze_conversation_authoring_list_projects_request, + build_analyze_conversation_authoring_list_trained_models_request, + build_analyze_conversation_authoring_list_training_config_versions_request, + build_analyze_conversation_authoring_list_training_jobs_request, + build_analyze_conversation_authoring_load_snapshot_request, + build_analyze_conversation_authoring_swap_deployments_request, + build_analyze_conversation_authoring_train_request, + build_analyze_conversation_authoring_unassign_deployment_resources_request, +) +from .._configuration import AuthoringClientConfiguration + +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 AnalyzeConversationAuthoringOperations: # pylint: disable=too-many-public-methods + """ + .. warning:: + **DO NOT** instantiate this class directly. + + Instead, you should access the following operations through + :class:`~azure.ai.language.conversations.authoring.aio.AuthoringClient`'s + :attr:`analyze_conversation_authoring` attribute. + """ + + def __init__(self, *args, **kwargs) -> None: + input_args = list(args) + self._client: AsyncPipelineClient = input_args.pop(0) if input_args else kwargs.pop("client") + self._config: AuthoringClientConfiguration = input_args.pop(0) if input_args else kwargs.pop("config") + self._serialize: Serializer = input_args.pop(0) if input_args else kwargs.pop("serializer") + self._deserialize: Deserializer = 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.AnalyzeConversationAuthoringProjectMetadata"]: + """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 AnalyzeConversationAuthoringProjectMetadata + :rtype: + ~azure.core.async_paging.AsyncItemPaged[~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringProjectMetadata] + :raises ~azure.core.exceptions.HttpResponseError: + """ + _headers = kwargs.pop("headers", {}) or {} + _params = kwargs.pop("params", {}) or {} + + maxpagesize = kwargs.pop("maxpagesize", None) + cls: ClsType[List[_models.AnalyzeConversationAuthoringProjectMetadata]] = 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_analyze_conversation_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", skip_quote=True + ), + } + _request.url = self._client.format_url(_request.url, **path_format_arguments) + + else: + # make call to next link with the client's api-version + _parsed_next_link = urllib.parse.urlparse(next_link) + _next_request_params = case_insensitive_dict( + { + key: [urllib.parse.quote(v) for v in value] + for key, value in urllib.parse.parse_qs(_parsed_next_link.query).items() + } + ) + _next_request_params["api-version"] = self._config.api_version + _request = HttpRequest( + "GET", urllib.parse.urljoin(next_link, _parsed_next_link.path), params=_next_request_params + ) + path_format_arguments = { + "Endpoint": self._serialize.url( + "self._config.endpoint", self._config.endpoint, "str", skip_quote=True + ), + } + _request.url = self._client.format_url(_request.url, **path_format_arguments) + + return _request + + async def extract_data(pipeline_response): + deserialized = pipeline_response.http_response.json() + list_of_elem = _deserialize( + List[_models.AnalyzeConversationAuthoringProjectMetadata], 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 = _failsafe_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.AnalyzeConversationAuthoringProjectMetadata: + """Gets the details of a project. + + :param project_name: The new project name. Required. + :type project_name: str + :return: AnalyzeConversationAuthoringProjectMetadata. The + AnalyzeConversationAuthoringProjectMetadata is compatible with MutableMapping + :rtype: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringProjectMetadata + :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.AnalyzeConversationAuthoringProjectMetadata] = kwargs.pop("cls", None) + + _request = build_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_deserialize(_models.ErrorResponse, response.json()) + raise HttpResponseError(response=response, model=error) + + if _stream: + deserialized = response.iter_bytes() + else: + deserialized = _deserialize(_models.AnalyzeConversationAuthoringProjectMetadata, 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.AnalyzeConversationAuthoringCreateProjectOptions, + *, + content_type: str = "application/merge-patch+json", + **kwargs: Any + ) -> _models.AnalyzeConversationAuthoringProjectMetadata: + """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.conversations.authoring.models.AnalyzeConversationAuthoringCreateProjectOptions + :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: AnalyzeConversationAuthoringProjectMetadata. The + AnalyzeConversationAuthoringProjectMetadata is compatible with MutableMapping + :rtype: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringProjectMetadata + :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.AnalyzeConversationAuthoringProjectMetadata: + """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: AnalyzeConversationAuthoringProjectMetadata. The + AnalyzeConversationAuthoringProjectMetadata is compatible with MutableMapping + :rtype: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringProjectMetadata + :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.AnalyzeConversationAuthoringProjectMetadata: + """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: AnalyzeConversationAuthoringProjectMetadata. The + AnalyzeConversationAuthoringProjectMetadata is compatible with MutableMapping + :rtype: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringProjectMetadata + :raises ~azure.core.exceptions.HttpResponseError: + """ + + @distributed_trace_async + async def create_project( + self, + project_name: str, + body: Union[_models.AnalyzeConversationAuthoringCreateProjectOptions, JSON, IO[bytes]], + **kwargs: Any + ) -> _models.AnalyzeConversationAuthoringProjectMetadata: + """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: + AnalyzeConversationAuthoringCreateProjectOptions, JSON, IO[bytes] Required. + :type body: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringCreateProjectOptions + or JSON or IO[bytes] + :return: AnalyzeConversationAuthoringProjectMetadata. The + AnalyzeConversationAuthoringProjectMetadata is compatible with MutableMapping + :rtype: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringProjectMetadata + :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.AnalyzeConversationAuthoringProjectMetadata] = 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_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_deserialize(_models.ErrorResponse, response.json()) + raise HttpResponseError(response=response, model=error) + + if _stream: + deserialized = response.iter_bytes() + else: + deserialized = _deserialize(_models.AnalyzeConversationAuthoringProjectMetadata, 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_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_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", skip_quote=True), + } + + if polling is True: + polling_method: AsyncPollingMethod = cast( + AsyncPollingMethod, + AsyncLROBasePolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs), + ) + elif polling is False: + polling_method = cast(AsyncPollingMethod, AsyncNoPolling()) + else: + polling_method = polling + if cont_token: + return AsyncLROPoller[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, + *, + 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.AnalyzeConversationAuthoringCopyProjectOptions: + """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.conversations.authoring.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: AnalyzeConversationAuthoringCopyProjectOptions. The + AnalyzeConversationAuthoringCopyProjectOptions is compatible with MutableMapping + :rtype: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringCopyProjectOptions + :raises ~azure.core.exceptions.HttpResponseError: + """ + + @overload + async def copy_project_authorization( + self, project_name: str, body: JSON, *, content_type: str = "application/json", **kwargs: Any + ) -> _models.AnalyzeConversationAuthoringCopyProjectOptions: + """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: AnalyzeConversationAuthoringCopyProjectOptions. The + AnalyzeConversationAuthoringCopyProjectOptions is compatible with MutableMapping + :rtype: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringCopyProjectOptions + :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.AnalyzeConversationAuthoringCopyProjectOptions: + """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: AnalyzeConversationAuthoringCopyProjectOptions. The + AnalyzeConversationAuthoringCopyProjectOptions is compatible with MutableMapping + :rtype: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringCopyProjectOptions + :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.AnalyzeConversationAuthoringCopyProjectOptions: + """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.conversations.authoring.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: AnalyzeConversationAuthoringCopyProjectOptions. The + AnalyzeConversationAuthoringCopyProjectOptions is compatible with MutableMapping + :rtype: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringCopyProjectOptions + :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.AnalyzeConversationAuthoringCopyProjectOptions] = 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_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_deserialize(_models.ErrorResponse, response.json()) + raise HttpResponseError(response=response, model=error) + + if _stream: + deserialized = response.iter_bytes() + else: + deserialized = _deserialize(_models.AnalyzeConversationAuthoringCopyProjectOptions, 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.AnalyzeConversationAuthoringCopyProjectOptions, 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_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_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.AnalyzeConversationAuthoringCopyProjectOptions, + *, + 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.conversations.authoring.models.AnalyzeConversationAuthoringCopyProjectOptions + :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.AnalyzeConversationAuthoringCopyProjectOptions, 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: + AnalyzeConversationAuthoringCopyProjectOptions, JSON, IO[bytes] Required. + :type body: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringCopyProjectOptions + 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", skip_quote=True), + } + + if polling is True: + polling_method: AsyncPollingMethod = cast( + AsyncPollingMethod, + AsyncLROBasePolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs), + ) + elif polling is False: + polling_method = cast(AsyncPollingMethod, AsyncNoPolling()) + else: + polling_method = polling + if cont_token: + return AsyncLROPoller[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_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_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.conversations.authoring.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.conversations.authoring.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", skip_quote=True), + } + + if polling is True: + polling_method: AsyncPollingMethod = cast( + AsyncPollingMethod, + AsyncLROBasePolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs), + ) + elif polling is False: + polling_method = cast(AsyncPollingMethod, AsyncNoPolling()) + else: + polling_method = polling + if cont_token: + return AsyncLROPoller[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.AnalyzeConversationAuthoringExportedProject, 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_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_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.AnalyzeConversationAuthoringExportedProject, + *, + 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.conversations.authoring.models.AnalyzeConversationAuthoringExportedProject + :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.conversations.authoring.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.conversations.authoring.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.conversations.authoring.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.AnalyzeConversationAuthoringExportedProject, 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: + AnalyzeConversationAuthoringExportedProject, JSON, IO[bytes] Required. + :type body: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringExportedProject + 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.conversations.authoring.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", skip_quote=True), + } + + if polling is True: + polling_method: AsyncPollingMethod = cast( + AsyncPollingMethod, + AsyncLROBasePolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs), + ) + elif polling is False: + polling_method = cast(AsyncPollingMethod, AsyncNoPolling()) + else: + polling_method = polling + if cont_token: + return AsyncLROPoller[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.AnalyzeConversationAuthoringTrainingJobOptions, 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_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_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.AnalyzeConversationAuthoringTrainingJobOptions, + *, + content_type: str = "application/json", + **kwargs: Any + ) -> AsyncLROPoller[_models.AnalyzeConversationAuthoringTrainingJobResult]: + """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.conversations.authoring.models.AnalyzeConversationAuthoringTrainingJobOptions + :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 + AnalyzeConversationAuthoringTrainingJobResult. The + AnalyzeConversationAuthoringTrainingJobResult is compatible with MutableMapping + :rtype: + ~azure.core.polling.AsyncLROPoller[~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringTrainingJobResult] + :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.AnalyzeConversationAuthoringTrainingJobResult]: + """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 + AnalyzeConversationAuthoringTrainingJobResult. The + AnalyzeConversationAuthoringTrainingJobResult is compatible with MutableMapping + :rtype: + ~azure.core.polling.AsyncLROPoller[~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringTrainingJobResult] + :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.AnalyzeConversationAuthoringTrainingJobResult]: + """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 + AnalyzeConversationAuthoringTrainingJobResult. The + AnalyzeConversationAuthoringTrainingJobResult is compatible with MutableMapping + :rtype: + ~azure.core.polling.AsyncLROPoller[~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringTrainingJobResult] + :raises ~azure.core.exceptions.HttpResponseError: + """ + + @distributed_trace_async + async def begin_train( + self, + project_name: str, + body: Union[_models.AnalyzeConversationAuthoringTrainingJobOptions, JSON, IO[bytes]], + **kwargs: Any + ) -> AsyncLROPoller[_models.AnalyzeConversationAuthoringTrainingJobResult]: + """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: + AnalyzeConversationAuthoringTrainingJobOptions, JSON, IO[bytes] Required. + :type body: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringTrainingJobOptions + or JSON or IO[bytes] + :return: An instance of AsyncLROPoller that returns + AnalyzeConversationAuthoringTrainingJobResult. The + AnalyzeConversationAuthoringTrainingJobResult is compatible with MutableMapping + :rtype: + ~azure.core.polling.AsyncLROPoller[~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringTrainingJobResult] + :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.AnalyzeConversationAuthoringTrainingJobResult] = 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.AnalyzeConversationAuthoringTrainingJobResult, 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", skip_quote=True), + } + + if polling is True: + polling_method: AsyncPollingMethod = cast( + AsyncPollingMethod, + AsyncLROBasePolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs), + ) + elif polling is False: + polling_method = cast(AsyncPollingMethod, AsyncNoPolling()) + else: + polling_method = polling + if cont_token: + return AsyncLROPoller[_models.AnalyzeConversationAuthoringTrainingJobResult].from_continuation_token( + polling_method=polling_method, + continuation_token=cont_token, + client=self._client, + deserialization_callback=get_long_running_output, + ) + return AsyncLROPoller[_models.AnalyzeConversationAuthoringTrainingJobResult]( + 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.AnalyzeConversationAuthoringCopyProjectJobState: + """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: AnalyzeConversationAuthoringCopyProjectJobState. The + AnalyzeConversationAuthoringCopyProjectJobState is compatible with MutableMapping + :rtype: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringCopyProjectJobState + :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.AnalyzeConversationAuthoringCopyProjectJobState] = kwargs.pop("cls", None) + + _request = build_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_deserialize(_models.ErrorResponse, response.json()) + raise HttpResponseError(response=response, model=error) + + if _stream: + deserialized = response.iter_bytes() + else: + deserialized = _deserialize(_models.AnalyzeConversationAuthoringCopyProjectJobState, 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.AnalyzeConversationAuthoringProjectDeployment"]: + """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 AnalyzeConversationAuthoringProjectDeployment + :rtype: + ~azure.core.async_paging.AsyncItemPaged[~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringProjectDeployment] + :raises ~azure.core.exceptions.HttpResponseError: + """ + _headers = kwargs.pop("headers", {}) or {} + _params = kwargs.pop("params", {}) or {} + + maxpagesize = kwargs.pop("maxpagesize", None) + cls: ClsType[List[_models.AnalyzeConversationAuthoringProjectDeployment]] = 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_analyze_conversation_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", skip_quote=True + ), + } + _request.url = self._client.format_url(_request.url, **path_format_arguments) + + else: + # make call to next link with the client's api-version + _parsed_next_link = urllib.parse.urlparse(next_link) + _next_request_params = case_insensitive_dict( + { + key: [urllib.parse.quote(v) for v in value] + for key, value in urllib.parse.parse_qs(_parsed_next_link.query).items() + } + ) + _next_request_params["api-version"] = self._config.api_version + _request = HttpRequest( + "GET", urllib.parse.urljoin(next_link, _parsed_next_link.path), params=_next_request_params + ) + path_format_arguments = { + "Endpoint": self._serialize.url( + "self._config.endpoint", self._config.endpoint, "str", skip_quote=True + ), + } + _request.url = self._client.format_url(_request.url, **path_format_arguments) + + return _request + + async def extract_data(pipeline_response): + deserialized = pipeline_response.http_response.json() + list_of_elem = _deserialize( + List[_models.AnalyzeConversationAuthoringProjectDeployment], 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 = _failsafe_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.AnalyzeConversationAuthoringSwapDeploymentsOptions, 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_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_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.AnalyzeConversationAuthoringSwapDeploymentsOptions, + *, + 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.conversations.authoring.models.AnalyzeConversationAuthoringSwapDeploymentsOptions + :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.AnalyzeConversationAuthoringSwapDeploymentsOptions, 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: + AnalyzeConversationAuthoringSwapDeploymentsOptions, JSON, IO[bytes] Required. + :type body: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringSwapDeploymentsOptions + 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", skip_quote=True), + } + + if polling is True: + polling_method: AsyncPollingMethod = cast( + AsyncPollingMethod, + AsyncLROBasePolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs), + ) + elif polling is False: + polling_method = cast(AsyncPollingMethod, AsyncNoPolling()) + else: + polling_method = polling + if cont_token: + return AsyncLROPoller[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.AnalyzeConversationAuthoringProjectDeployment: + """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: AnalyzeConversationAuthoringProjectDeployment. The + AnalyzeConversationAuthoringProjectDeployment is compatible with MutableMapping + :rtype: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringProjectDeployment + :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.AnalyzeConversationAuthoringProjectDeployment] = kwargs.pop("cls", None) + + _request = build_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_deserialize(_models.ErrorResponse, response.json()) + raise HttpResponseError(response=response, model=error) + + if _stream: + deserialized = response.iter_bytes() + else: + deserialized = _deserialize(_models.AnalyzeConversationAuthoringProjectDeployment, 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.AnalyzeConversationAuthoringCreateDeploymentOptions, 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_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_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.AnalyzeConversationAuthoringCreateDeploymentOptions, + *, + 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.conversations.authoring.models.AnalyzeConversationAuthoringCreateDeploymentOptions + :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.AnalyzeConversationAuthoringCreateDeploymentOptions, 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: + AnalyzeConversationAuthoringCreateDeploymentOptions, JSON, IO[bytes] Required. + :type body: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringCreateDeploymentOptions + 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", skip_quote=True), + } + + if polling is True: + polling_method: AsyncPollingMethod = cast( + AsyncPollingMethod, + AsyncLROBasePolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs), + ) + elif polling is False: + polling_method = cast(AsyncPollingMethod, AsyncNoPolling()) + else: + polling_method = polling + if cont_token: + return AsyncLROPoller[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_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_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", skip_quote=True), + } + + if polling is True: + polling_method: AsyncPollingMethod = cast( + AsyncPollingMethod, + AsyncLROBasePolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs), + ) + elif polling is False: + polling_method = cast(AsyncPollingMethod, AsyncNoPolling()) + else: + polling_method = polling + if cont_token: + return AsyncLROPoller[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"] + }, + ) + async def _delete_deployment_from_resources_initial( # pylint: disable=name-too-long + self, + project_name: str, + deployment_name: str, + body: Union[_models.AnalyzeConversationAuthoringDeleteDeploymentOptions, 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_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_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.AnalyzeConversationAuthoringDeleteDeploymentOptions, + *, + 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.conversations.authoring.models.AnalyzeConversationAuthoringDeleteDeploymentOptions + :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.AnalyzeConversationAuthoringDeleteDeploymentOptions, 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: + AnalyzeConversationAuthoringDeleteDeploymentOptions, JSON, IO[bytes] Required. + :type body: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringDeleteDeploymentOptions + 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", skip_quote=True), + } + + if polling is True: + polling_method: AsyncPollingMethod = cast( + AsyncPollingMethod, + AsyncLROBasePolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs), + ) + elif polling is False: + polling_method = cast(AsyncPollingMethod, AsyncNoPolling()) + else: + polling_method = polling + if cont_token: + return AsyncLROPoller[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"]}, + ) + 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.AnalyzeConversationAuthoringDeploymentDeleteFromResourcesJobState: + """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: AnalyzeConversationAuthoringDeploymentDeleteFromResourcesJobState. The + AnalyzeConversationAuthoringDeploymentDeleteFromResourcesJobState is compatible with + MutableMapping + :rtype: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringDeploymentDeleteFromResourcesJobState + :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.AnalyzeConversationAuthoringDeploymentDeleteFromResourcesJobState] = kwargs.pop( + "cls", None + ) + + _request = build_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_deserialize(_models.ErrorResponse, response.json()) + raise HttpResponseError(response=response, model=error) + + if _stream: + deserialized = response.iter_bytes() + else: + deserialized = _deserialize( + _models.AnalyzeConversationAuthoringDeploymentDeleteFromResourcesJobState, 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.AnalyzeConversationAuthoringDeploymentJobState: + """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: AnalyzeConversationAuthoringDeploymentJobState. The + AnalyzeConversationAuthoringDeploymentJobState is compatible with MutableMapping + :rtype: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringDeploymentJobState + :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.AnalyzeConversationAuthoringDeploymentJobState] = kwargs.pop("cls", None) + + _request = build_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_deserialize(_models.ErrorResponse, response.json()) + raise HttpResponseError(response=response, model=error) + + if _stream: + deserialized = response.iter_bytes() + else: + deserialized = _deserialize(_models.AnalyzeConversationAuthoringDeploymentJobState, 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.AnalyzeConversationAuthoringSwapDeploymentsJobState: + """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: AnalyzeConversationAuthoringSwapDeploymentsJobState. The + AnalyzeConversationAuthoringSwapDeploymentsJobState is compatible with MutableMapping + :rtype: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringSwapDeploymentsJobState + :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.AnalyzeConversationAuthoringSwapDeploymentsJobState] = kwargs.pop("cls", None) + + _request = build_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_deserialize(_models.ErrorResponse, response.json()) + raise HttpResponseError(response=response, model=error) + + if _stream: + deserialized = response.iter_bytes() + else: + deserialized = _deserialize(_models.AnalyzeConversationAuthoringSwapDeploymentsJobState, 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.AnalyzeConversationAuthoringExportProjectJobState: + """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: AnalyzeConversationAuthoringExportProjectJobState. The + AnalyzeConversationAuthoringExportProjectJobState is compatible with MutableMapping + :rtype: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringExportProjectJobState + :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.AnalyzeConversationAuthoringExportProjectJobState] = kwargs.pop("cls", None) + + _request = build_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_deserialize(_models.ErrorResponse, response.json()) + raise HttpResponseError(response=response, model=error) + + if _stream: + deserialized = response.iter_bytes() + else: + deserialized = _deserialize(_models.AnalyzeConversationAuthoringExportProjectJobState, 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.AnalyzeConversationAuthoringImportProjectJobState: + """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: AnalyzeConversationAuthoringImportProjectJobState. The + AnalyzeConversationAuthoringImportProjectJobState is compatible with MutableMapping + :rtype: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringImportProjectJobState + :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.AnalyzeConversationAuthoringImportProjectJobState] = kwargs.pop("cls", None) + + _request = build_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_deserialize(_models.ErrorResponse, response.json()) + raise HttpResponseError(response=response, model=error) + + if _stream: + deserialized = response.iter_bytes() + else: + deserialized = _deserialize(_models.AnalyzeConversationAuthoringImportProjectJobState, 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.AnalyzeConversationAuthoringProjectTrainedModel"]: + """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 AnalyzeConversationAuthoringProjectTrainedModel + :rtype: + ~azure.core.async_paging.AsyncItemPaged[~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringProjectTrainedModel] + :raises ~azure.core.exceptions.HttpResponseError: + """ + _headers = kwargs.pop("headers", {}) or {} + _params = kwargs.pop("params", {}) or {} + + maxpagesize = kwargs.pop("maxpagesize", None) + cls: ClsType[List[_models.AnalyzeConversationAuthoringProjectTrainedModel]] = 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_analyze_conversation_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", skip_quote=True + ), + } + _request.url = self._client.format_url(_request.url, **path_format_arguments) + + else: + # make call to next link with the client's api-version + _parsed_next_link = urllib.parse.urlparse(next_link) + _next_request_params = case_insensitive_dict( + { + key: [urllib.parse.quote(v) for v in value] + for key, value in urllib.parse.parse_qs(_parsed_next_link.query).items() + } + ) + _next_request_params["api-version"] = self._config.api_version + _request = HttpRequest( + "GET", urllib.parse.urljoin(next_link, _parsed_next_link.path), params=_next_request_params + ) + path_format_arguments = { + "Endpoint": self._serialize.url( + "self._config.endpoint", self._config.endpoint, "str", skip_quote=True + ), + } + _request.url = self._client.format_url(_request.url, **path_format_arguments) + + return _request + + async def extract_data(pipeline_response): + deserialized = pipeline_response.http_response.json() + list_of_elem = _deserialize( + List[_models.AnalyzeConversationAuthoringProjectTrainedModel], 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 = _failsafe_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.AnalyzeConversationAuthoringProjectTrainedModel: + """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: AnalyzeConversationAuthoringProjectTrainedModel. The + AnalyzeConversationAuthoringProjectTrainedModel is compatible with MutableMapping + :rtype: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringProjectTrainedModel + :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.AnalyzeConversationAuthoringProjectTrainedModel] = kwargs.pop("cls", None) + + _request = build_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_deserialize(_models.ErrorResponse, response.json()) + raise HttpResponseError(response=response, model=error) + + if _stream: + deserialized = response.iter_bytes() + else: + deserialized = _deserialize(_models.AnalyzeConversationAuthoringProjectTrainedModel, 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_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_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.AnalyzeConversationAuthoringEvaluationOptions, 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_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_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.AnalyzeConversationAuthoringEvaluationOptions, + *, + content_type: str = "application/json", + **kwargs: Any + ) -> AsyncLROPoller[_models.AnalyzeConversationAuthoringEvaluationJobResult]: + """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.conversations.authoring.models.AnalyzeConversationAuthoringEvaluationOptions + :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 + AnalyzeConversationAuthoringEvaluationJobResult. The + AnalyzeConversationAuthoringEvaluationJobResult is compatible with MutableMapping + :rtype: + ~azure.core.polling.AsyncLROPoller[~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringEvaluationJobResult] + :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.AnalyzeConversationAuthoringEvaluationJobResult]: + """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 + AnalyzeConversationAuthoringEvaluationJobResult. The + AnalyzeConversationAuthoringEvaluationJobResult is compatible with MutableMapping + :rtype: + ~azure.core.polling.AsyncLROPoller[~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringEvaluationJobResult] + :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.AnalyzeConversationAuthoringEvaluationJobResult]: + """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 + AnalyzeConversationAuthoringEvaluationJobResult. The + AnalyzeConversationAuthoringEvaluationJobResult is compatible with MutableMapping + :rtype: + ~azure.core.polling.AsyncLROPoller[~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringEvaluationJobResult] + :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.AnalyzeConversationAuthoringEvaluationOptions, JSON, IO[bytes]], + **kwargs: Any + ) -> AsyncLROPoller[_models.AnalyzeConversationAuthoringEvaluationJobResult]: + """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: + AnalyzeConversationAuthoringEvaluationOptions, JSON, IO[bytes] Required. + :type body: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringEvaluationOptions + or JSON or IO[bytes] + :return: An instance of AsyncLROPoller that returns + AnalyzeConversationAuthoringEvaluationJobResult. The + AnalyzeConversationAuthoringEvaluationJobResult is compatible with MutableMapping + :rtype: + ~azure.core.polling.AsyncLROPoller[~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringEvaluationJobResult] + :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.AnalyzeConversationAuthoringEvaluationJobResult] = 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.AnalyzeConversationAuthoringEvaluationJobResult, 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", skip_quote=True), + } + + if polling is True: + polling_method: AsyncPollingMethod = cast( + AsyncPollingMethod, + AsyncLROBasePolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs), + ) + elif polling is False: + polling_method = cast(AsyncPollingMethod, AsyncNoPolling()) + else: + polling_method = polling + if cont_token: + return AsyncLROPoller[_models.AnalyzeConversationAuthoringEvaluationJobResult].from_continuation_token( + polling_method=polling_method, + continuation_token=cont_token, + client=self._client, + deserialization_callback=get_long_running_output, + ) + return AsyncLROPoller[_models.AnalyzeConversationAuthoringEvaluationJobResult]( + 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_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_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", skip_quote=True), + } + + if polling is True: + polling_method: AsyncPollingMethod = cast( + AsyncPollingMethod, + AsyncLROBasePolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs), + ) + elif polling is False: + polling_method = cast(AsyncPollingMethod, AsyncNoPolling()) + else: + polling_method = polling + if cont_token: + return AsyncLROPoller[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.AnalyzeConversationAuthoringEvaluationJobState: + """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: AnalyzeConversationAuthoringEvaluationJobState. The + AnalyzeConversationAuthoringEvaluationJobState is compatible with MutableMapping + :rtype: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringEvaluationJobState + :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.AnalyzeConversationAuthoringEvaluationJobState] = kwargs.pop("cls", None) + + _request = build_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_deserialize(_models.ErrorResponse, response.json()) + raise HttpResponseError(response=response, model=error) + + if _stream: + deserialized = response.iter_bytes() + else: + deserialized = _deserialize(_models.AnalyzeConversationAuthoringEvaluationJobState, 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.AnalyzeConversationAuthoringUtteranceEvaluationResult"]: + """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.conversations.authoring.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 AnalyzeConversationAuthoringUtteranceEvaluationResult + :rtype: + ~azure.core.async_paging.AsyncItemPaged[~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringUtteranceEvaluationResult] + :raises ~azure.core.exceptions.HttpResponseError: + """ + _headers = kwargs.pop("headers", {}) or {} + _params = kwargs.pop("params", {}) or {} + + maxpagesize = kwargs.pop("maxpagesize", None) + cls: ClsType[List[_models.AnalyzeConversationAuthoringUtteranceEvaluationResult]] = 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_analyze_conversation_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", skip_quote=True + ), + } + _request.url = self._client.format_url(_request.url, **path_format_arguments) + + else: + # make call to next link with the client's api-version + _parsed_next_link = urllib.parse.urlparse(next_link) + _next_request_params = case_insensitive_dict( + { + key: [urllib.parse.quote(v) for v in value] + for key, value in urllib.parse.parse_qs(_parsed_next_link.query).items() + } + ) + _next_request_params["api-version"] = self._config.api_version + _request = HttpRequest( + "GET", urllib.parse.urljoin(next_link, _parsed_next_link.path), params=_next_request_params + ) + path_format_arguments = { + "Endpoint": self._serialize.url( + "self._config.endpoint", self._config.endpoint, "str", skip_quote=True + ), + } + _request.url = self._client.format_url(_request.url, **path_format_arguments) + + return _request + + async def extract_data(pipeline_response): + deserialized = pipeline_response.http_response.json() + list_of_elem = _deserialize( + List[_models.AnalyzeConversationAuthoringUtteranceEvaluationResult], 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 = _failsafe_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.AnalyzeConversationAuthoringEvaluationSummary: + """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: AnalyzeConversationAuthoringEvaluationSummary. The + AnalyzeConversationAuthoringEvaluationSummary is compatible with MutableMapping + :rtype: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringEvaluationSummary + :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.AnalyzeConversationAuthoringEvaluationSummary] = kwargs.pop("cls", None) + + _request = build_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_deserialize(_models.ErrorResponse, response.json()) + raise HttpResponseError(response=response, model=error) + + if _stream: + deserialized = response.iter_bytes() + else: + deserialized = _deserialize(_models.AnalyzeConversationAuthoringEvaluationSummary, 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.AnalyzeConversationAuthoringLoadSnapshotJobState: + """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: AnalyzeConversationAuthoringLoadSnapshotJobState. The + AnalyzeConversationAuthoringLoadSnapshotJobState is compatible with MutableMapping + :rtype: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringLoadSnapshotJobState + :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.AnalyzeConversationAuthoringLoadSnapshotJobState] = kwargs.pop("cls", None) + + _request = build_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_deserialize(_models.ErrorResponse, response.json()) + raise HttpResponseError(response=response, model=error) + + if _stream: + deserialized = response.iter_bytes() + else: + deserialized = _deserialize(_models.AnalyzeConversationAuthoringLoadSnapshotJobState, 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.AnalyzeConversationAuthoringAssignedDeploymentResource"]: + """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 AnalyzeConversationAuthoringAssignedDeploymentResource + :rtype: + ~azure.core.async_paging.AsyncItemPaged[~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringAssignedDeploymentResource] + :raises ~azure.core.exceptions.HttpResponseError: + """ + _headers = kwargs.pop("headers", {}) or {} + _params = kwargs.pop("params", {}) or {} + + maxpagesize = kwargs.pop("maxpagesize", None) + cls: ClsType[List[_models.AnalyzeConversationAuthoringAssignedDeploymentResource]] = 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_analyze_conversation_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", skip_quote=True + ), + } + _request.url = self._client.format_url(_request.url, **path_format_arguments) + + else: + # make call to next link with the client's api-version + _parsed_next_link = urllib.parse.urlparse(next_link) + _next_request_params = case_insensitive_dict( + { + key: [urllib.parse.quote(v) for v in value] + for key, value in urllib.parse.parse_qs(_parsed_next_link.query).items() + } + ) + _next_request_params["api-version"] = self._config.api_version + _request = HttpRequest( + "GET", urllib.parse.urljoin(next_link, _parsed_next_link.path), params=_next_request_params + ) + path_format_arguments = { + "Endpoint": self._serialize.url( + "self._config.endpoint", self._config.endpoint, "str", skip_quote=True + ), + } + _request.url = self._client.format_url(_request.url, **path_format_arguments) + + return _request + + async def extract_data(pipeline_response): + deserialized = pipeline_response.http_response.json() + list_of_elem = _deserialize( + List[_models.AnalyzeConversationAuthoringAssignedDeploymentResource], 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 = _failsafe_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.AnalyzeConversationAuthoringAssignDeploymentResourcesOptions, 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_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_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.AnalyzeConversationAuthoringAssignDeploymentResourcesOptions, + *, + 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: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringAssignDeploymentResourcesOptions + :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.AnalyzeConversationAuthoringAssignDeploymentResourcesOptions, JSON, IO[bytes]], + **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. Is one of the following types: + AnalyzeConversationAuthoringAssignDeploymentResourcesOptions, JSON, IO[bytes] Required. + :type body: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringAssignDeploymentResourcesOptions + 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", skip_quote=True), + } + + if polling is True: + polling_method: AsyncPollingMethod = cast( + AsyncPollingMethod, + AsyncLROBasePolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs), + ) + elif polling is False: + polling_method = cast(AsyncPollingMethod, AsyncNoPolling()) + else: + polling_method = polling + if cont_token: + return AsyncLROPoller[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.AnalyzeConversationAuthoringUnassignDeploymentResourcesOptions, 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_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_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.AnalyzeConversationAuthoringUnassignDeploymentResourcesOptions, + *, + 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: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringUnassignDeploymentResourcesOptions + :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.AnalyzeConversationAuthoringUnassignDeploymentResourcesOptions, JSON, IO[bytes]], + **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. Is one of the following + types: AnalyzeConversationAuthoringUnassignDeploymentResourcesOptions, JSON, IO[bytes] + Required. + :type body: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringUnassignDeploymentResourcesOptions + 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", skip_quote=True), + } + + if polling is True: + polling_method: AsyncPollingMethod = cast( + AsyncPollingMethod, + AsyncLROBasePolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs), + ) + elif polling is False: + polling_method = cast(AsyncPollingMethod, AsyncNoPolling()) + else: + polling_method = polling + if cont_token: + return AsyncLROPoller[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.AnalyzeConversationAuthoringDeploymentResourcesJobState: + """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: AnalyzeConversationAuthoringDeploymentResourcesJobState. The + AnalyzeConversationAuthoringDeploymentResourcesJobState is compatible with MutableMapping + :rtype: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringDeploymentResourcesJobState + :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.AnalyzeConversationAuthoringDeploymentResourcesJobState] = kwargs.pop("cls", None) + + _request = build_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_deserialize(_models.ErrorResponse, response.json()) + raise HttpResponseError(response=response, model=error) + + if _stream: + deserialized = response.iter_bytes() + else: + deserialized = _deserialize( + _models.AnalyzeConversationAuthoringDeploymentResourcesJobState, 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.AnalyzeConversationAuthoringDeploymentResourcesJobState: + """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: AnalyzeConversationAuthoringDeploymentResourcesJobState. The + AnalyzeConversationAuthoringDeploymentResourcesJobState is compatible with MutableMapping + :rtype: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringDeploymentResourcesJobState + :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.AnalyzeConversationAuthoringDeploymentResourcesJobState] = kwargs.pop("cls", None) + + _request = build_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_deserialize(_models.ErrorResponse, response.json()) + raise HttpResponseError(response=response, model=error) + + if _stream: + deserialized = response.iter_bytes() + else: + deserialized = _deserialize( + _models.AnalyzeConversationAuthoringDeploymentResourcesJobState, 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.AnalyzeConversationAuthoringTrainingJobState"]: + """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 AnalyzeConversationAuthoringTrainingJobState + :rtype: + ~azure.core.async_paging.AsyncItemPaged[~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringTrainingJobState] + :raises ~azure.core.exceptions.HttpResponseError: + """ + _headers = kwargs.pop("headers", {}) or {} + _params = kwargs.pop("params", {}) or {} + + maxpagesize = kwargs.pop("maxpagesize", None) + cls: ClsType[List[_models.AnalyzeConversationAuthoringTrainingJobState]] = 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_analyze_conversation_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", skip_quote=True + ), + } + _request.url = self._client.format_url(_request.url, **path_format_arguments) + + else: + # make call to next link with the client's api-version + _parsed_next_link = urllib.parse.urlparse(next_link) + _next_request_params = case_insensitive_dict( + { + key: [urllib.parse.quote(v) for v in value] + for key, value in urllib.parse.parse_qs(_parsed_next_link.query).items() + } + ) + _next_request_params["api-version"] = self._config.api_version + _request = HttpRequest( + "GET", urllib.parse.urljoin(next_link, _parsed_next_link.path), params=_next_request_params + ) + path_format_arguments = { + "Endpoint": self._serialize.url( + "self._config.endpoint", self._config.endpoint, "str", skip_quote=True + ), + } + _request.url = self._client.format_url(_request.url, **path_format_arguments) + + return _request + + async def extract_data(pipeline_response): + deserialized = pipeline_response.http_response.json() + list_of_elem = _deserialize( + List[_models.AnalyzeConversationAuthoringTrainingJobState], 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 = _failsafe_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.AnalyzeConversationAuthoringTrainingJobState: + """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: AnalyzeConversationAuthoringTrainingJobState. The + AnalyzeConversationAuthoringTrainingJobState is compatible with MutableMapping + :rtype: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringTrainingJobState + :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.AnalyzeConversationAuthoringTrainingJobState] = kwargs.pop("cls", None) + + _request = build_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_deserialize(_models.ErrorResponse, response.json()) + raise HttpResponseError(response=response, model=error) + + if _stream: + deserialized = response.iter_bytes() + else: + deserialized = _deserialize(_models.AnalyzeConversationAuthoringTrainingJobState, 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_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_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.AnalyzeConversationAuthoringTrainingJobResult]: + """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 + AnalyzeConversationAuthoringTrainingJobResult. The + AnalyzeConversationAuthoringTrainingJobResult is compatible with MutableMapping + :rtype: + ~azure.core.polling.AsyncLROPoller[~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringTrainingJobResult] + :raises ~azure.core.exceptions.HttpResponseError: + """ + _headers = kwargs.pop("headers", {}) or {} + _params = kwargs.pop("params", {}) or {} + + cls: ClsType[_models.AnalyzeConversationAuthoringTrainingJobResult] = 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.AnalyzeConversationAuthoringTrainingJobResult, 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", skip_quote=True), + } + + if polling is True: + polling_method: AsyncPollingMethod = cast( + AsyncPollingMethod, + AsyncLROBasePolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs), + ) + elif polling is False: + polling_method = cast(AsyncPollingMethod, AsyncNoPolling()) + else: + polling_method = polling + if cont_token: + return AsyncLROPoller[_models.AnalyzeConversationAuthoringTrainingJobResult].from_continuation_token( + polling_method=polling_method, + continuation_token=cont_token, + client=self._client, + deserialization_callback=get_long_running_output, + ) + return AsyncLROPoller[_models.AnalyzeConversationAuthoringTrainingJobResult]( + 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.AnalyzeConversationAuthoringProjectDeletionJobState: + """Gets the status for a project deletion job. + + :param job_id: The job ID. Required. + :type job_id: str + :return: AnalyzeConversationAuthoringProjectDeletionJobState. The + AnalyzeConversationAuthoringProjectDeletionJobState is compatible with MutableMapping + :rtype: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringProjectDeletionJobState + :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.AnalyzeConversationAuthoringProjectDeletionJobState] = kwargs.pop("cls", None) + + _request = build_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_deserialize(_models.ErrorResponse, response.json()) + raise HttpResponseError(response=response, model=error) + + if _stream: + deserialized = response.iter_bytes() + else: + deserialized = _deserialize(_models.AnalyzeConversationAuthoringProjectDeletionJobState, 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.AnalyzeConversationAuthoringAssignedResourceDeploymentsMetadata: + """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: AnalyzeConversationAuthoringAssignedResourceDeploymentsMetadata. The + AnalyzeConversationAuthoringAssignedResourceDeploymentsMetadata is compatible with + MutableMapping + :rtype: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringAssignedResourceDeploymentsMetadata + :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.AnalyzeConversationAuthoringAssignedResourceDeploymentsMetadata] = kwargs.pop("cls", None) + + _request = build_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_deserialize(_models.ErrorResponse, response.json()) + raise HttpResponseError(response=response, model=error) + + if _stream: + deserialized = response.iter_bytes() + else: + deserialized = _deserialize( + _models.AnalyzeConversationAuthoringAssignedResourceDeploymentsMetadata, 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.AnalyzeConversationAuthoringSupportedLanguages: + """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.conversations.authoring.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: AnalyzeConversationAuthoringSupportedLanguages. The + AnalyzeConversationAuthoringSupportedLanguages is compatible with MutableMapping + :rtype: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringSupportedLanguages + :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.AnalyzeConversationAuthoringSupportedLanguages] = kwargs.pop("cls", None) + + _request = build_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_deserialize(_models.ErrorResponse, response.json()) + raise HttpResponseError(response=response, model=error) + + if _stream: + deserialized = response.iter_bytes() + else: + deserialized = _deserialize(_models.AnalyzeConversationAuthoringSupportedLanguages, 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.AnalyzeConversationAuthoringPrebuiltEntities: + """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: AnalyzeConversationAuthoringPrebuiltEntities. The + AnalyzeConversationAuthoringPrebuiltEntities is compatible with MutableMapping + :rtype: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringPrebuiltEntities + :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.AnalyzeConversationAuthoringPrebuiltEntities] = kwargs.pop("cls", None) + + _request = build_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_deserialize(_models.ErrorResponse, response.json()) + raise HttpResponseError(response=response, model=error) + + if _stream: + deserialized = response.iter_bytes() + else: + deserialized = _deserialize(_models.AnalyzeConversationAuthoringPrebuiltEntities, 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.AnalyzeConversationAuthoringTrainingConfigVersions: + """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.conversations.authoring.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: AnalyzeConversationAuthoringTrainingConfigVersions. The + AnalyzeConversationAuthoringTrainingConfigVersions is compatible with MutableMapping + :rtype: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringTrainingConfigVersions + :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.AnalyzeConversationAuthoringTrainingConfigVersions] = kwargs.pop("cls", None) + + _request = build_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_deserialize(_models.ErrorResponse, response.json()) + raise HttpResponseError(response=response, model=error) + + if _stream: + deserialized = response.iter_bytes() + else: + deserialized = _deserialize(_models.AnalyzeConversationAuthoringTrainingConfigVersions, response.json()) + + if cls: + return cls(pipeline_response, deserialized, {}) # type: ignore + + return deserialized # type: ignore + + @distributed_trace_async + @api_version_validation( + method_added_on="2024-11-15-preview", + params_added_on={"2024-11-15-preview": ["api_version", "project_name", "exported_model_name", "accept"]}, + ) + async def get_exported_model( + self, project_name: str, exported_model_name: str, **kwargs: Any + ) -> _models.AnalyzeConversationAuthoringExportedTrainedModel: + """Gets the details of an exported model. + + :param project_name: The new project name. Required. + :type project_name: str + :param exported_model_name: The exported model name. Required. + :type exported_model_name: str + :return: AnalyzeConversationAuthoringExportedTrainedModel. The + AnalyzeConversationAuthoringExportedTrainedModel is compatible with MutableMapping + :rtype: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringExportedTrainedModel + :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.AnalyzeConversationAuthoringExportedTrainedModel] = kwargs.pop("cls", None) + + _request = build_analyze_conversation_authoring_get_exported_model_request( + project_name=project_name, + exported_model_name=exported_model_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", skip_quote=True), + } + _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 = _failsafe_deserialize(_models.ErrorResponse, response.json()) + raise HttpResponseError(response=response, model=error) + + if _stream: + deserialized = response.iter_bytes() + else: + deserialized = _deserialize(_models.AnalyzeConversationAuthoringExportedTrainedModel, response.json()) + + if cls: + return cls(pipeline_response, deserialized, {}) # type: ignore + + return deserialized # type: ignore + + @distributed_trace + @api_version_validation( + method_added_on="2024-11-15-preview", + params_added_on={"2024-11-15-preview": ["api_version", "project_name", "top", "skip", "maxpagesize", "accept"]}, + ) + def list_exported_models( + self, project_name: str, *, top: Optional[int] = None, skip: Optional[int] = None, **kwargs: Any + ) -> AsyncIterable["_models.AnalyzeConversationAuthoringExportedTrainedModel"]: + """Lists the exported 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 AnalyzeConversationAuthoringExportedTrainedModel + :rtype: + ~azure.core.async_paging.AsyncItemPaged[~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringExportedTrainedModel] + :raises ~azure.core.exceptions.HttpResponseError: + """ + _headers = kwargs.pop("headers", {}) or {} + _params = kwargs.pop("params", {}) or {} + + maxpagesize = kwargs.pop("maxpagesize", None) + cls: ClsType[List[_models.AnalyzeConversationAuthoringExportedTrainedModel]] = 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_analyze_conversation_authoring_list_exported_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", skip_quote=True + ), + } + _request.url = self._client.format_url(_request.url, **path_format_arguments) + + else: + # make call to next link with the client's api-version + _parsed_next_link = urllib.parse.urlparse(next_link) + _next_request_params = case_insensitive_dict( + { + key: [urllib.parse.quote(v) for v in value] + for key, value in urllib.parse.parse_qs(_parsed_next_link.query).items() + } + ) + _next_request_params["api-version"] = self._config.api_version + _request = HttpRequest( + "GET", urllib.parse.urljoin(next_link, _parsed_next_link.path), params=_next_request_params + ) + path_format_arguments = { + "Endpoint": self._serialize.url( + "self._config.endpoint", self._config.endpoint, "str", skip_quote=True + ), + } + _request.url = self._client.format_url(_request.url, **path_format_arguments) + + return _request + + async def extract_data(pipeline_response): + deserialized = pipeline_response.http_response.json() + list_of_elem = _deserialize( + List[_models.AnalyzeConversationAuthoringExportedTrainedModel], 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 = _failsafe_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="2024-11-15-preview", + params_added_on={"2024-11-15-preview": ["api_version", "project_name", "exported_model_name", "accept"]}, + ) + async def _delete_exported_model_initial( + self, project_name: str, exported_model_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_analyze_conversation_authoring_delete_exported_model_request( + project_name=project_name, + exported_model_name=exported_model_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", skip_quote=True), + } + _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 = _failsafe_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 + @api_version_validation( + method_added_on="2024-11-15-preview", + params_added_on={"2024-11-15-preview": ["api_version", "project_name", "exported_model_name", "accept"]}, + ) + async def begin_delete_exported_model( + self, project_name: str, exported_model_name: str, **kwargs: Any + ) -> AsyncLROPoller[None]: + """Deletes an existing exported model. + + :param project_name: The name of the project to use. Required. + :type project_name: str + :param exported_model_name: The exported model name. Required. + :type exported_model_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_exported_model_initial( + project_name=project_name, + exported_model_name=exported_model_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", skip_quote=True), + } + + if polling is True: + polling_method: AsyncPollingMethod = cast( + AsyncPollingMethod, + AsyncLROBasePolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs), + ) + elif polling is False: + polling_method = cast(AsyncPollingMethod, AsyncNoPolling()) + else: + polling_method = polling + if cont_token: + return AsyncLROPoller[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="2024-11-15-preview", + params_added_on={ + "2024-11-15-preview": ["api_version", "project_name", "exported_model_name", "content_type", "accept"] + }, + ) + async def _create_or_update_exported_model_initial( + self, + project_name: str, + exported_model_name: str, + body: Union[_models.ExportedModelOptions, 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_analyze_conversation_authoring_create_or_update_exported_model_request( + project_name=project_name, + exported_model_name=exported_model_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", skip_quote=True), + } + _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 = _failsafe_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_create_or_update_exported_model( + self, + project_name: str, + exported_model_name: str, + body: _models.ExportedModelOptions, + *, + content_type: str = "application/json", + **kwargs: Any + ) -> AsyncLROPoller[None]: + """Creates a new exported model or replaces an existing one. + + :param project_name: The name of the project to use. Required. + :type project_name: str + :param exported_model_name: The exported model name. Required. + :type exported_model_name: str + :param body: The exported model info. Required. + :type body: ~azure.ai.language.conversations.authoring.models.ExportedModelOptions + :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_create_or_update_exported_model( + self, + project_name: str, + exported_model_name: str, + body: JSON, + *, + content_type: str = "application/json", + **kwargs: Any + ) -> AsyncLROPoller[None]: + """Creates a new exported model or replaces an existing one. + + :param project_name: The name of the project to use. Required. + :type project_name: str + :param exported_model_name: The exported model name. Required. + :type exported_model_name: str + :param body: The exported model 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_create_or_update_exported_model( + self, + project_name: str, + exported_model_name: str, + body: IO[bytes], + *, + content_type: str = "application/json", + **kwargs: Any + ) -> AsyncLROPoller[None]: + """Creates a new exported model or replaces an existing one. + + :param project_name: The name of the project to use. Required. + :type project_name: str + :param exported_model_name: The exported model name. Required. + :type exported_model_name: str + :param body: The exported model 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="2024-11-15-preview", + params_added_on={ + "2024-11-15-preview": ["api_version", "project_name", "exported_model_name", "content_type", "accept"] + }, + ) + async def begin_create_or_update_exported_model( + self, + project_name: str, + exported_model_name: str, + body: Union[_models.ExportedModelOptions, JSON, IO[bytes]], + **kwargs: Any + ) -> AsyncLROPoller[None]: + """Creates a new exported model or replaces an existing one. + + :param project_name: The name of the project to use. Required. + :type project_name: str + :param exported_model_name: The exported model name. Required. + :type exported_model_name: str + :param body: The exported model info. Is one of the following types: ExportedModelOptions, + JSON, IO[bytes] Required. + :type body: ~azure.ai.language.conversations.authoring.models.ExportedModelOptions 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._create_or_update_exported_model_initial( + project_name=project_name, + exported_model_name=exported_model_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", skip_quote=True), + } + + if polling is True: + polling_method: AsyncPollingMethod = cast( + AsyncPollingMethod, + AsyncLROBasePolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs), + ) + elif polling is False: + polling_method = cast(AsyncPollingMethod, AsyncNoPolling()) + else: + polling_method = polling + if cont_token: + return AsyncLROPoller[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="2024-11-15-preview", + params_added_on={ + "2024-11-15-preview": ["api_version", "project_name", "exported_model_name", "job_id", "accept"] + }, + ) + async def get_exported_model_job_status( + self, project_name: str, exported_model_name: str, job_id: str, **kwargs: Any + ) -> _models.AnalyzeConversationAuthoringExportedModelJobState: + """Gets the status for an existing job to create or update an exported model. + + :param project_name: The new project name. Required. + :type project_name: str + :param exported_model_name: The exported model name. Required. + :type exported_model_name: str + :param job_id: The job ID. Required. + :type job_id: str + :return: AnalyzeConversationAuthoringExportedModelJobState. The + AnalyzeConversationAuthoringExportedModelJobState is compatible with MutableMapping + :rtype: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringExportedModelJobState + :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.AnalyzeConversationAuthoringExportedModelJobState] = kwargs.pop("cls", None) + + _request = build_analyze_conversation_authoring_get_exported_model_job_status_request( + project_name=project_name, + exported_model_name=exported_model_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", skip_quote=True), + } + _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 = _failsafe_deserialize(_models.ErrorResponse, response.json()) + raise HttpResponseError(response=response, model=error) + + if _stream: + deserialized = response.iter_bytes() + else: + deserialized = _deserialize(_models.AnalyzeConversationAuthoringExportedModelJobState, response.json()) + + if cls: + return cls(pipeline_response, deserialized, {}) # type: ignore + + return deserialized # type: ignore diff --git a/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/aio/operations/_patch.py b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/aio/operations/_patch.py new file mode 100644 index 000000000000..f7dd32510333 --- /dev/null +++ b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/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/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/models/__init__.py b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/models/__init__.py new file mode 100644 index 000000000000..af9b2cb09dc2 --- /dev/null +++ b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/models/__init__.py @@ -0,0 +1,210 @@ +# 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. +# -------------------------------------------------------------------------- +# pylint: disable=wrong-import-position + +from typing import TYPE_CHECKING + +if TYPE_CHECKING: + from ._patch import * # pylint: disable=unused-wildcard-import + + +from ._models import ( # type: ignore + AnalyzeConversationAuthoringAssignDeploymentResourcesOptions, + AnalyzeConversationAuthoringAssignedDeploymentResource, + AnalyzeConversationAuthoringAssignedProjectDeploymentMetadata, + AnalyzeConversationAuthoringAssignedProjectDeploymentsMetadata, + AnalyzeConversationAuthoringAssignedResourceDeploymentsMetadata, + AnalyzeConversationAuthoringConfusionMatrix, + AnalyzeConversationAuthoringConfusionMatrixCell, + AnalyzeConversationAuthoringConfusionMatrixRow, + AnalyzeConversationAuthoringConversationExportedEntity, + AnalyzeConversationAuthoringConversationExportedIntent, + AnalyzeConversationAuthoringConversationExportedProjectAssets, + AnalyzeConversationAuthoringConversationExportedUtterance, + AnalyzeConversationAuthoringCopyProjectJobState, + AnalyzeConversationAuthoringCopyProjectOptions, + AnalyzeConversationAuthoringCreateDeploymentOptions, + AnalyzeConversationAuthoringCreateProjectOptions, + AnalyzeConversationAuthoringDeleteDeploymentOptions, + AnalyzeConversationAuthoringDeploymentDeleteFromResourcesJobState, + AnalyzeConversationAuthoringDeploymentJobState, + AnalyzeConversationAuthoringDeploymentResource, + AnalyzeConversationAuthoringDeploymentResourcesJobState, + AnalyzeConversationAuthoringEntitiesEvaluationSummary, + AnalyzeConversationAuthoringEntityEvaluationSummary, + AnalyzeConversationAuthoringEvaluationJobResult, + AnalyzeConversationAuthoringEvaluationJobState, + AnalyzeConversationAuthoringEvaluationOptions, + AnalyzeConversationAuthoringEvaluationSummary, + AnalyzeConversationAuthoringExportProjectJobState, + AnalyzeConversationAuthoringExportedConversationOrchestration, + AnalyzeConversationAuthoringExportedConversationOrchestrationOptions, + AnalyzeConversationAuthoringExportedEntityList, + AnalyzeConversationAuthoringExportedEntityListSynonym, + AnalyzeConversationAuthoringExportedEntityRegex, + AnalyzeConversationAuthoringExportedEntityRegexExpression, + AnalyzeConversationAuthoringExportedEntitySublist, + AnalyzeConversationAuthoringExportedLuisOrchestration, + AnalyzeConversationAuthoringExportedLuisOrchestrationOptions, + AnalyzeConversationAuthoringExportedModelJobState, + AnalyzeConversationAuthoringExportedOrchestrationOptions, + AnalyzeConversationAuthoringExportedPrebuiltEntity, + AnalyzeConversationAuthoringExportedProject, + AnalyzeConversationAuthoringExportedProjectAssets, + AnalyzeConversationAuthoringExportedQuestionAnsweringOrchestration, + AnalyzeConversationAuthoringExportedQuestionAnsweringOrchestrationOptions, + AnalyzeConversationAuthoringExportedTrainedModel, + AnalyzeConversationAuthoringExportedUtteranceEntityLabel, + AnalyzeConversationAuthoringImportProjectJobState, + AnalyzeConversationAuthoringIntentEvaluationSummary, + AnalyzeConversationAuthoringIntentsEvaluationSummary, + AnalyzeConversationAuthoringLoadSnapshotJobState, + AnalyzeConversationAuthoringOrchestrationExportedIntent, + AnalyzeConversationAuthoringOrchestrationExportedProjectAssets, + AnalyzeConversationAuthoringOrchestrationExportedUtterance, + AnalyzeConversationAuthoringPrebuiltEntities, + AnalyzeConversationAuthoringPrebuiltEntity, + AnalyzeConversationAuthoringProjectDeletionJobState, + AnalyzeConversationAuthoringProjectDeployment, + AnalyzeConversationAuthoringProjectMetadata, + AnalyzeConversationAuthoringProjectSettings, + AnalyzeConversationAuthoringProjectTrainedModel, + AnalyzeConversationAuthoringResourceMetadata, + AnalyzeConversationAuthoringSubTrainingJobState, + AnalyzeConversationAuthoringSupportedLanguage, + AnalyzeConversationAuthoringSupportedLanguages, + AnalyzeConversationAuthoringSwapDeploymentsJobState, + AnalyzeConversationAuthoringSwapDeploymentsOptions, + AnalyzeConversationAuthoringTrainingConfigVersion, + AnalyzeConversationAuthoringTrainingConfigVersions, + AnalyzeConversationAuthoringTrainingJobOptions, + AnalyzeConversationAuthoringTrainingJobResult, + AnalyzeConversationAuthoringTrainingJobState, + AnalyzeConversationAuthoringUnassignDeploymentResourcesOptions, + AnalyzeConversationAuthoringUtteranceEntitiesEvaluationResult, + AnalyzeConversationAuthoringUtteranceEntityEvaluationResult, + AnalyzeConversationAuthoringUtteranceEvaluationResult, + AnalyzeConversationAuthoringUtteranceIntentsEvaluationResult, + Error, + ErrorResponse, + ExportedModelOptions, + InnerErrorModel, + Warning, +) + +from ._enums import ( # type: ignore + CompositionSetting, + ErrorCode, + EvaluationKind, + ExportedProjectFormat, + InnerErrorCode, + JobStatus, + OrchestrationTargetProjectKind, + ProjectKind, + StringIndexType, + TrainingMode, +) +from ._patch import __all__ as _patch_all +from ._patch import * +from ._patch import patch_sdk as _patch_sdk + +__all__ = [ + "AnalyzeConversationAuthoringAssignDeploymentResourcesOptions", + "AnalyzeConversationAuthoringAssignedDeploymentResource", + "AnalyzeConversationAuthoringAssignedProjectDeploymentMetadata", + "AnalyzeConversationAuthoringAssignedProjectDeploymentsMetadata", + "AnalyzeConversationAuthoringAssignedResourceDeploymentsMetadata", + "AnalyzeConversationAuthoringConfusionMatrix", + "AnalyzeConversationAuthoringConfusionMatrixCell", + "AnalyzeConversationAuthoringConfusionMatrixRow", + "AnalyzeConversationAuthoringConversationExportedEntity", + "AnalyzeConversationAuthoringConversationExportedIntent", + "AnalyzeConversationAuthoringConversationExportedProjectAssets", + "AnalyzeConversationAuthoringConversationExportedUtterance", + "AnalyzeConversationAuthoringCopyProjectJobState", + "AnalyzeConversationAuthoringCopyProjectOptions", + "AnalyzeConversationAuthoringCreateDeploymentOptions", + "AnalyzeConversationAuthoringCreateProjectOptions", + "AnalyzeConversationAuthoringDeleteDeploymentOptions", + "AnalyzeConversationAuthoringDeploymentDeleteFromResourcesJobState", + "AnalyzeConversationAuthoringDeploymentJobState", + "AnalyzeConversationAuthoringDeploymentResource", + "AnalyzeConversationAuthoringDeploymentResourcesJobState", + "AnalyzeConversationAuthoringEntitiesEvaluationSummary", + "AnalyzeConversationAuthoringEntityEvaluationSummary", + "AnalyzeConversationAuthoringEvaluationJobResult", + "AnalyzeConversationAuthoringEvaluationJobState", + "AnalyzeConversationAuthoringEvaluationOptions", + "AnalyzeConversationAuthoringEvaluationSummary", + "AnalyzeConversationAuthoringExportProjectJobState", + "AnalyzeConversationAuthoringExportedConversationOrchestration", + "AnalyzeConversationAuthoringExportedConversationOrchestrationOptions", + "AnalyzeConversationAuthoringExportedEntityList", + "AnalyzeConversationAuthoringExportedEntityListSynonym", + "AnalyzeConversationAuthoringExportedEntityRegex", + "AnalyzeConversationAuthoringExportedEntityRegexExpression", + "AnalyzeConversationAuthoringExportedEntitySublist", + "AnalyzeConversationAuthoringExportedLuisOrchestration", + "AnalyzeConversationAuthoringExportedLuisOrchestrationOptions", + "AnalyzeConversationAuthoringExportedModelJobState", + "AnalyzeConversationAuthoringExportedOrchestrationOptions", + "AnalyzeConversationAuthoringExportedPrebuiltEntity", + "AnalyzeConversationAuthoringExportedProject", + "AnalyzeConversationAuthoringExportedProjectAssets", + "AnalyzeConversationAuthoringExportedQuestionAnsweringOrchestration", + "AnalyzeConversationAuthoringExportedQuestionAnsweringOrchestrationOptions", + "AnalyzeConversationAuthoringExportedTrainedModel", + "AnalyzeConversationAuthoringExportedUtteranceEntityLabel", + "AnalyzeConversationAuthoringImportProjectJobState", + "AnalyzeConversationAuthoringIntentEvaluationSummary", + "AnalyzeConversationAuthoringIntentsEvaluationSummary", + "AnalyzeConversationAuthoringLoadSnapshotJobState", + "AnalyzeConversationAuthoringOrchestrationExportedIntent", + "AnalyzeConversationAuthoringOrchestrationExportedProjectAssets", + "AnalyzeConversationAuthoringOrchestrationExportedUtterance", + "AnalyzeConversationAuthoringPrebuiltEntities", + "AnalyzeConversationAuthoringPrebuiltEntity", + "AnalyzeConversationAuthoringProjectDeletionJobState", + "AnalyzeConversationAuthoringProjectDeployment", + "AnalyzeConversationAuthoringProjectMetadata", + "AnalyzeConversationAuthoringProjectSettings", + "AnalyzeConversationAuthoringProjectTrainedModel", + "AnalyzeConversationAuthoringResourceMetadata", + "AnalyzeConversationAuthoringSubTrainingJobState", + "AnalyzeConversationAuthoringSupportedLanguage", + "AnalyzeConversationAuthoringSupportedLanguages", + "AnalyzeConversationAuthoringSwapDeploymentsJobState", + "AnalyzeConversationAuthoringSwapDeploymentsOptions", + "AnalyzeConversationAuthoringTrainingConfigVersion", + "AnalyzeConversationAuthoringTrainingConfigVersions", + "AnalyzeConversationAuthoringTrainingJobOptions", + "AnalyzeConversationAuthoringTrainingJobResult", + "AnalyzeConversationAuthoringTrainingJobState", + "AnalyzeConversationAuthoringUnassignDeploymentResourcesOptions", + "AnalyzeConversationAuthoringUtteranceEntitiesEvaluationResult", + "AnalyzeConversationAuthoringUtteranceEntityEvaluationResult", + "AnalyzeConversationAuthoringUtteranceEvaluationResult", + "AnalyzeConversationAuthoringUtteranceIntentsEvaluationResult", + "Error", + "ErrorResponse", + "ExportedModelOptions", + "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/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/models/_enums.py b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/models/_enums.py new file mode 100644 index 000000000000..7ee31a66baf3 --- /dev/null +++ b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/models/_enums.py @@ -0,0 +1,136 @@ +# 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/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/models/_models.py b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/models/_models.py new file mode 100644 index 000000000000..36f0cd7d10ec --- /dev/null +++ b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/models/_models.py @@ -0,0 +1,4006 @@ +# pylint: disable=line-too-long,useless-suppression,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. +# -------------------------------------------------------------------------- +# pylint: disable=useless-super-delegation + +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 AnalyzeConversationAuthoringAssignDeploymentResourcesOptions(_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.conversations.authoring.models.AnalyzeConversationAuthoringResourceMetadata] + """ + + resources_metadata: List["_models.AnalyzeConversationAuthoringResourceMetadata"] = rest_field( + name="resourcesMetadata", visibility=["read", "create", "update", "delete", "query"] + ) + """Represents the metadata for the resources to be assigned. Required.""" + + @overload + def __init__( + self, + *, + resources_metadata: List["_models.AnalyzeConversationAuthoringResourceMetadata"], + ) -> None: ... + + @overload + def __init__(self, mapping: Mapping[str, Any]) -> None: + """ + :param mapping: raw JSON to initialize the model. + :type mapping: Mapping[str, Any] + """ + + def __init__(self, *args: Any, **kwargs: Any) -> None: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringAssignedDeploymentResource(_model_base.Model): # pylint: disable=name-too-long + """Represents the assigned deployment resource. + + Readonly variables are only populated by the server, and will be ignored when sending a request. + + + :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", visibility=["read"]) + """The resource ID. Required.""" + region: str = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """The resource region. Required.""" + + @overload + def __init__( + self, + *, + 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: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringAssignedProjectDeploymentMetadata(_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", visibility=["read", "create", "update", "delete", "query"]) + """Represents the deployment name. Required.""" + last_deployed_date_time: datetime.datetime = rest_field( + name="lastDeployedDateTime", visibility=["read", "create", "update", "delete", "query"], format="rfc3339" + ) + """Represents deployment last deployed time. Required.""" + deployment_expiration_date: datetime.date = rest_field( + name="deploymentExpirationDate", visibility=["read", "create", "update", "delete", "query"] + ) + """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: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringAssignedProjectDeploymentsMetadata( + _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.conversations.authoring.models.AnalyzeConversationAuthoringAssignedProjectDeploymentMetadata] + """ + + project_name: str = rest_field(name="projectName", visibility=["read", "create", "update", "delete", "query"]) + """Represents the project name. Required.""" + deployments_metadata: List["_models.AnalyzeConversationAuthoringAssignedProjectDeploymentMetadata"] = rest_field( + name="deploymentsMetadata", visibility=["read", "create", "update", "delete", "query"] + ) + """Represents the resource region. Required.""" + + @overload + def __init__( + self, + *, + project_name: str, + deployments_metadata: List["_models.AnalyzeConversationAuthoringAssignedProjectDeploymentMetadata"], + ) -> None: ... + + @overload + def __init__(self, mapping: Mapping[str, Any]) -> None: + """ + :param mapping: raw JSON to initialize the model. + :type mapping: Mapping[str, Any] + """ + + def __init__(self, *args: Any, **kwargs: Any) -> None: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringAssignedResourceDeploymentsMetadata( + _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.conversations.authoring.models.AnalyzeConversationAuthoringAssignedProjectDeploymentsMetadata] + :ivar next_link: The next page link. + :vartype next_link: str + """ + + value: List["_models.AnalyzeConversationAuthoringAssignedProjectDeploymentsMetadata"] = rest_field( + visibility=["read", "create", "update", "delete", "query"] + ) + """The list of retrieved assigned project deployments. Required.""" + next_link: Optional[str] = rest_field(name="nextLink", visibility=["read", "create", "update", "delete", "query"]) + """The next page link.""" + + @overload + def __init__( + self, + *, + value: List["_models.AnalyzeConversationAuthoringAssignedProjectDeploymentsMetadata"], + 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: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringConfusionMatrix(_model_base.Model): # pylint: disable=name-too-long + """AnalyzeConversationAuthoringConfusionMatrix.""" + + +class AnalyzeConversationAuthoringConfusionMatrixCell(_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", visibility=["read", "create", "update", "delete", "query"] + ) + """Represents normalized value in percentages. Required.""" + raw_value: float = rest_field(name="rawValue", visibility=["read", "create", "update", "delete", "query"]) + """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: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringConfusionMatrixRow(_model_base.Model): # pylint: disable=name-too-long + """AnalyzeConversationAuthoringConfusionMatrixRow.""" + + +class AnalyzeConversationAuthoringConversationExportedEntity(_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.conversations.authoring.models.CompositionSetting + :ivar list: The list component of the entity. + :vartype list: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringExportedEntityList + :ivar prebuilts: The prebuilt entities components. + :vartype prebuilts: + list[~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringExportedPrebuiltEntity] + :ivar regex: The regex component of the entity. + :vartype regex: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringExportedEntityRegex + :ivar required_components: The required components. Allowed values are 'learned', 'list', + 'prebuilts' and 'regex'. + :vartype required_components: list[str] + """ + + category: str = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """The category of the entity. Required.""" + composition_setting: Optional[Union[str, "_models.CompositionSetting"]] = rest_field( + name="compositionSetting", visibility=["read", "create", "update", "delete", "query"] + ) + """The behavior to follow when the entity's components overlap with each other. Known values are: + \"returnLongestOverlap\", \"requireExactOverlap\", \"separateComponents\", and + \"combineComponents\".""" + list: Optional["_models.AnalyzeConversationAuthoringExportedEntityList"] = rest_field( + visibility=["read", "create", "update", "delete", "query"] + ) + """The list component of the entity.""" + prebuilts: Optional[List["_models.AnalyzeConversationAuthoringExportedPrebuiltEntity"]] = rest_field( + visibility=["read", "create", "update", "delete", "query"] + ) + """The prebuilt entities components.""" + regex: Optional["_models.AnalyzeConversationAuthoringExportedEntityRegex"] = rest_field( + visibility=["read", "create", "update", "delete", "query"] + ) + """The regex component of the entity.""" + required_components: Optional[List[str]] = rest_field( + name="requiredComponents", visibility=["read", "create", "update", "delete", "query"] + ) + """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.AnalyzeConversationAuthoringExportedEntityList"] = None, + prebuilts: Optional[List["_models.AnalyzeConversationAuthoringExportedPrebuiltEntity"]] = None, + regex: Optional["_models.AnalyzeConversationAuthoringExportedEntityRegex"] = 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: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringConversationExportedIntent(_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(visibility=["read", "create", "update", "delete", "query"]) + """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: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringExportedProjectAssets(_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: + AnalyzeConversationAuthoringConversationExportedProjectAssets, + AnalyzeConversationAuthoringOrchestrationExportedProjectAssets + + 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.conversations.authoring.models.ProjectKind + """ + + __mapping__: Dict[str, _model_base.Model] = {} + project_kind: str = rest_discriminator( + name="projectKind", visibility=["read", "create", "update", "delete", "query"] + ) + """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: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringConversationExportedProjectAssets( + AnalyzeConversationAuthoringExportedProjectAssets, 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.conversations.authoring.models.AnalyzeConversationAuthoringConversationExportedIntent] + :ivar entities: The entities defined in the project. + :vartype entities: + list[~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringConversationExportedEntity] + :ivar utterances: The utterances defined in the project. + :vartype utterances: + list[~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringConversationExportedUtterance] + :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.conversations.authoring.models.CONVERSATION + """ + + intents: Optional[List["_models.AnalyzeConversationAuthoringConversationExportedIntent"]] = rest_field( + visibility=["read", "create", "update", "delete", "query"] + ) + """The intents defined in the project.""" + entities: Optional[List["_models.AnalyzeConversationAuthoringConversationExportedEntity"]] = rest_field( + visibility=["read", "create", "update", "delete", "query"] + ) + """The entities defined in the project.""" + utterances: Optional[List["_models.AnalyzeConversationAuthoringConversationExportedUtterance"]] = rest_field( + visibility=["read", "create", "update", "delete", "query"] + ) + """The utterances defined in the project.""" + project_kind: Literal[ProjectKind.CONVERSATION] = rest_discriminator(name="projectKind", visibility=["read", "create", "update", "delete", "query"]) # 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.AnalyzeConversationAuthoringConversationExportedIntent"]] = None, + entities: Optional[List["_models.AnalyzeConversationAuthoringConversationExportedEntity"]] = None, + utterances: Optional[List["_models.AnalyzeConversationAuthoringConversationExportedUtterance"]] = None, + ) -> None: ... + + @overload + def __init__(self, mapping: Mapping[str, Any]) -> None: + """ + :param mapping: raw JSON to initialize the model. + :type mapping: Mapping[str, Any] + """ + + def __init__(self, *args: Any, **kwargs: Any) -> None: + super().__init__(*args, project_kind=ProjectKind.CONVERSATION, **kwargs) + + +class AnalyzeConversationAuthoringConversationExportedUtterance(_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.conversations.authoring.models.AnalyzeConversationAuthoringExportedUtteranceEntityLabel] + :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.AnalyzeConversationAuthoringExportedUtteranceEntityLabel"]] = rest_field( + visibility=["read", "create", "update", "delete", "query"] + ) + """Represents the entity labels of the utterance.""" + text: str = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """The utterance text. Required.""" + language: Optional[str] = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """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(visibility=["read", "create", "update", "delete", "query"]) + """The intent of the utterance. Required.""" + dataset: Optional[str] = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """The dataset for this utterance. Allowed values are 'Train' and 'Test'.""" + + @overload + def __init__( + self, + *, + text: str, + intent: str, + entities: Optional[List["_models.AnalyzeConversationAuthoringExportedUtteranceEntityLabel"]] = 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: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringCopyProjectJobState(_model_base.Model): # pylint: disable=name-too-long + """Represents the state of a copy job. + + Readonly variables are only populated by the server, and will be ignored when sending a request. + + + :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.conversations.authoring.models.JobStatus + :ivar warnings: The warnings that were encountered while executing the job. + :vartype warnings: list[~azure.ai.language.conversations.authoring.models.Warning] + :ivar errors: The errors encountered while executing the job. + :vartype errors: list[~azure.ai.language.conversations.authoring.models.Error] + """ + + job_id: str = rest_field(name="jobId", visibility=["read"]) + """The job ID. Required.""" + created_date_time: datetime.datetime = rest_field( + name="createdDateTime", visibility=["read", "create", "update", "delete", "query"], format="rfc3339" + ) + """The creation date time of the job. Required.""" + last_updated_date_time: datetime.datetime = rest_field( + name="lastUpdatedDateTime", visibility=["read", "create", "update", "delete", "query"], format="rfc3339" + ) + """The last date time the job was updated. Required.""" + expiration_date_time: Optional[datetime.datetime] = rest_field( + name="expirationDateTime", visibility=["read", "create", "update", "delete", "query"], format="rfc3339" + ) + """The expiration date time of the job.""" + status: Union[str, "_models.JobStatus"] = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """The job status. Required. Known values are: \"notStarted\", \"running\", \"succeeded\", + \"failed\", \"cancelled\", \"cancelling\", and \"partiallyCompleted\".""" + warnings: Optional[List["_models.Warning"]] = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """The warnings that were encountered while executing the job.""" + errors: Optional[List["_models.Error"]] = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """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: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringCopyProjectOptions(_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.conversations.authoring.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", visibility=["read", "create", "update", "delete", "query"] + ) + """Represents the project kind. Required. Known values are: \"Conversation\", \"Orchestration\", + and \"CustomConversationSummarization\".""" + target_project_name: str = rest_field( + name="targetProjectName", visibility=["read", "create", "update", "delete", "query"] + ) + """The project name to be copied-into. Required.""" + access_token: str = rest_field(name="accessToken", visibility=["read", "create", "update", "delete", "query"]) + """The access token. Required.""" + expires_at: datetime.datetime = rest_field( + name="expiresAt", visibility=["read", "create", "update", "delete", "query"], format="rfc3339" + ) + """The expiration of the access token. Required.""" + target_resource_id: str = rest_field( + name="targetResourceId", visibility=["read", "create", "update", "delete", "query"] + ) + """Represents the target Azure resource ID. Required.""" + target_resource_region: str = rest_field( + name="targetResourceRegion", visibility=["read", "create", "update", "delete", "query"] + ) + """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: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringCreateDeploymentOptions(_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", visibility=["read", "create", "update", "delete", "query"] + ) + """Represents the trained model label. Required.""" + assigned_resource_ids: Optional[List[str]] = rest_field( + name="assignedResourceIds", visibility=["read", "create", "update", "delete", "query"] + ) + """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: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringCreateProjectOptions(_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.conversations.authoring.models.ProjectKind + :ivar settings: The project settings. + :vartype settings: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringProjectSettings + :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", visibility=["read", "create", "update", "delete", "query"] + ) + """Represents the project kind. Required. Known values are: \"Conversation\", \"Orchestration\", + and \"CustomConversationSummarization\".""" + settings: Optional["_models.AnalyzeConversationAuthoringProjectSettings"] = rest_field( + visibility=["read", "create", "update", "delete", "query"] + ) + """The project settings.""" + storage_input_container_name: Optional[str] = rest_field( + name="storageInputContainerName", visibility=["read", "create", "update", "delete", "query"] + ) + """The storage container name in case of conversation summarization.""" + project_name: str = rest_field(name="projectName", visibility=["read", "create", "update", "delete", "query"]) + """The new project name. Required.""" + multilingual: Optional[bool] = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """Whether the project would be used for multiple languages or not.""" + description: Optional[str] = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """The project description.""" + language: str = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """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.AnalyzeConversationAuthoringProjectSettings"] = 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: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringDeleteDeploymentOptions(_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", visibility=["read", "create", "update", "delete", "query"] + ) + """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: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringDeploymentDeleteFromResourcesJobState( + _model_base.Model +): # pylint: disable=name-too-long + """Represents the state of an existing delete deployment from specific resources job. + + Readonly variables are only populated by the server, and will be ignored when sending a request. + + + :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.conversations.authoring.models.JobStatus + :ivar warnings: The warnings that were encountered while executing the job. + :vartype warnings: list[~azure.ai.language.conversations.authoring.models.Warning] + :ivar errors: The errors encountered while executing the job. + :vartype errors: list[~azure.ai.language.conversations.authoring.models.Error] + """ + + job_id: str = rest_field(name="jobId", visibility=["read"]) + """The job ID. Required.""" + created_date_time: datetime.datetime = rest_field( + name="createdDateTime", visibility=["read", "create", "update", "delete", "query"], format="rfc3339" + ) + """The creation date time of the job. Required.""" + last_updated_date_time: datetime.datetime = rest_field( + name="lastUpdatedDateTime", visibility=["read", "create", "update", "delete", "query"], format="rfc3339" + ) + """The last date time the job was updated. Required.""" + expiration_date_time: Optional[datetime.datetime] = rest_field( + name="expirationDateTime", visibility=["read", "create", "update", "delete", "query"], format="rfc3339" + ) + """The expiration date time of the job.""" + status: Union[str, "_models.JobStatus"] = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """The job status. Required. Known values are: \"notStarted\", \"running\", \"succeeded\", + \"failed\", \"cancelled\", \"cancelling\", and \"partiallyCompleted\".""" + warnings: Optional[List["_models.Warning"]] = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """The warnings that were encountered while executing the job.""" + errors: Optional[List["_models.Error"]] = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """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: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringDeploymentJobState(_model_base.Model): # pylint: disable=name-too-long + """Represents the state of a deployment job. + + Readonly variables are only populated by the server, and will be ignored when sending a request. + + + :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.conversations.authoring.models.JobStatus + :ivar warnings: The warnings that were encountered while executing the job. + :vartype warnings: list[~azure.ai.language.conversations.authoring.models.Warning] + :ivar errors: The errors encountered while executing the job. + :vartype errors: list[~azure.ai.language.conversations.authoring.models.Error] + """ + + job_id: str = rest_field(name="jobId", visibility=["read"]) + """The job ID. Required.""" + created_date_time: datetime.datetime = rest_field( + name="createdDateTime", visibility=["read", "create", "update", "delete", "query"], format="rfc3339" + ) + """The creation date time of the job. Required.""" + last_updated_date_time: datetime.datetime = rest_field( + name="lastUpdatedDateTime", visibility=["read", "create", "update", "delete", "query"], format="rfc3339" + ) + """The last date time the job was updated. Required.""" + expiration_date_time: Optional[datetime.datetime] = rest_field( + name="expirationDateTime", visibility=["read", "create", "update", "delete", "query"], format="rfc3339" + ) + """The expiration date time of the job.""" + status: Union[str, "_models.JobStatus"] = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """The job status. Required. Known values are: \"notStarted\", \"running\", \"succeeded\", + \"failed\", \"cancelled\", \"cancelling\", and \"partiallyCompleted\".""" + warnings: Optional[List["_models.Warning"]] = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """The warnings that were encountered while executing the job.""" + errors: Optional[List["_models.Error"]] = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """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: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringDeploymentResource(_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", visibility=["read", "create", "update", "delete", "query"]) + """Represents the Azure resource Id. Required.""" + region: str = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """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: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringDeploymentResourcesJobState(_model_base.Model): # pylint: disable=name-too-long + """Represents the state of a deployment resources job. + + Readonly variables are only populated by the server, and will be ignored when sending a request. + + + :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.conversations.authoring.models.JobStatus + :ivar warnings: The warnings that were encountered while executing the job. + :vartype warnings: list[~azure.ai.language.conversations.authoring.models.Warning] + :ivar errors: The errors encountered while executing the job. + :vartype errors: list[~azure.ai.language.conversations.authoring.models.Error] + """ + + job_id: str = rest_field(name="jobId", visibility=["read"]) + """The job ID. Required.""" + created_date_time: datetime.datetime = rest_field( + name="createdDateTime", visibility=["read", "create", "update", "delete", "query"], format="rfc3339" + ) + """The creation date time of the job. Required.""" + last_updated_date_time: datetime.datetime = rest_field( + name="lastUpdatedDateTime", visibility=["read", "create", "update", "delete", "query"], format="rfc3339" + ) + """The last date time the job was updated. Required.""" + expiration_date_time: Optional[datetime.datetime] = rest_field( + name="expirationDateTime", visibility=["read", "create", "update", "delete", "query"], format="rfc3339" + ) + """The expiration date time of the job.""" + status: Union[str, "_models.JobStatus"] = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """The job status. Required. Known values are: \"notStarted\", \"running\", \"succeeded\", + \"failed\", \"cancelled\", \"cancelling\", and \"partiallyCompleted\".""" + warnings: Optional[List["_models.Warning"]] = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """The warnings that were encountered while executing the job.""" + errors: Optional[List["_models.Error"]] = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """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: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringEntitiesEvaluationSummary(_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.conversations.authoring.models.AnalyzeConversationAuthoringConfusionMatrix + :ivar entities: Represents the entities evaluation summary. Required. + :vartype entities: dict[str, + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringEntityEvaluationSummary] + :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.AnalyzeConversationAuthoringConfusionMatrix" = rest_field( + name="confusionMatrix", visibility=["read", "create", "update", "delete", "query"] + ) + """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.AnalyzeConversationAuthoringEntityEvaluationSummary"] = rest_field( + visibility=["read", "create", "update", "delete", "query"] + ) + """Represents the entities evaluation summary. Required.""" + micro_f1: float = rest_field(name="microF1", visibility=["read", "create", "update", "delete", "query"]) + """Represents the micro F1. Expected value is a float between 0 and 1 inclusive. Required.""" + micro_precision: float = rest_field( + name="microPrecision", visibility=["read", "create", "update", "delete", "query"] + ) + """Represents the micro precision. Expected value is a float between 0 and 1 inclusive. Required.""" + micro_recall: float = rest_field(name="microRecall", visibility=["read", "create", "update", "delete", "query"]) + """Represents the micro recall. Expected value is a float between 0 and 1 inclusive. Required.""" + macro_f1: float = rest_field(name="macroF1", visibility=["read", "create", "update", "delete", "query"]) + """Represents the macro F1. Expected value is a float between 0 and 1 inclusive. Required.""" + macro_precision: float = rest_field( + name="macroPrecision", visibility=["read", "create", "update", "delete", "query"] + ) + """Represents the macro precision. Expected value is a float between 0 and 1 inclusive. Required.""" + macro_recall: float = rest_field(name="macroRecall", visibility=["read", "create", "update", "delete", "query"]) + """Represents the macro recall. Expected value is a float between 0 and 1 inclusive. Required.""" + + @overload + def __init__( + self, + *, + confusion_matrix: "_models.AnalyzeConversationAuthoringConfusionMatrix", + entities: Dict[str, "_models.AnalyzeConversationAuthoringEntityEvaluationSummary"], + 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: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringEntityEvaluationSummary(_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(visibility=["read", "create", "update", "delete", "query"]) + """Represents the model precision. Required.""" + precision: float = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """Represents the model recall. Required.""" + recall: float = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """Represents the model F1 score. Required.""" + true_positive_count: int = rest_field( + name="truePositiveCount", visibility=["read", "create", "update", "delete", "query"] + ) + """Represents the count of true positive. Required.""" + true_negative_count: int = rest_field( + name="trueNegativeCount", visibility=["read", "create", "update", "delete", "query"] + ) + """Represents the count of true negative. Required.""" + false_positive_count: int = rest_field( + name="falsePositiveCount", visibility=["read", "create", "update", "delete", "query"] + ) + """Represents the count of false positive. Required.""" + false_negative_count: int = rest_field( + name="falseNegativeCount", visibility=["read", "create", "update", "delete", "query"] + ) + """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: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringEvaluationJobResult(_model_base.Model): # pylint: disable=name-too-long + """AnalyzeConversationAuthoringEvaluationJobResult. + + + :ivar evaluation_options: Represents the options used running the evaluation. Required. + :vartype evaluation_options: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringEvaluationOptions + :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.AnalyzeConversationAuthoringEvaluationOptions" = rest_field( + name="evaluationOptions", visibility=["read", "create", "update", "delete", "query"] + ) + """Represents the options used running the evaluation. Required.""" + model_label: str = rest_field(name="modelLabel", visibility=["read", "create", "update", "delete", "query"]) + """Represents trained model label. Required.""" + training_config_version: str = rest_field( + name="trainingConfigVersion", visibility=["read", "create", "update", "delete", "query"] + ) + """Represents training config version. Required.""" + percent_complete: int = rest_field( + name="percentComplete", visibility=["read", "create", "update", "delete", "query"] + ) + """Represents progress percentage. Required.""" + + @overload + def __init__( + self, + *, + evaluation_options: "_models.AnalyzeConversationAuthoringEvaluationOptions", + 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: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringEvaluationJobState(_model_base.Model): # pylint: disable=name-too-long + """Represents the state of a evaluation job. + + Readonly variables are only populated by the server, and will be ignored when sending a request. + + + :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.conversations.authoring.models.JobStatus + :ivar warnings: The warnings that were encountered while executing the job. + :vartype warnings: list[~azure.ai.language.conversations.authoring.models.Warning] + :ivar errors: The errors encountered while executing the job. + :vartype errors: list[~azure.ai.language.conversations.authoring.models.Error] + :ivar result: Represents evaluation task detailed result. Required. + :vartype result: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringEvaluationJobResult + """ + + job_id: str = rest_field(name="jobId", visibility=["read"]) + """The job ID. Required.""" + created_date_time: datetime.datetime = rest_field( + name="createdDateTime", visibility=["read", "create", "update", "delete", "query"], format="rfc3339" + ) + """The creation date time of the job. Required.""" + last_updated_date_time: datetime.datetime = rest_field( + name="lastUpdatedDateTime", visibility=["read", "create", "update", "delete", "query"], format="rfc3339" + ) + """The last date time the job was updated. Required.""" + expiration_date_time: Optional[datetime.datetime] = rest_field( + name="expirationDateTime", visibility=["read", "create", "update", "delete", "query"], format="rfc3339" + ) + """The expiration date time of the job.""" + status: Union[str, "_models.JobStatus"] = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """The job status. Required. Known values are: \"notStarted\", \"running\", \"succeeded\", + \"failed\", \"cancelled\", \"cancelling\", and \"partiallyCompleted\".""" + warnings: Optional[List["_models.Warning"]] = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """The warnings that were encountered while executing the job.""" + errors: Optional[List["_models.Error"]] = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """The errors encountered while executing the job.""" + result: "_models.AnalyzeConversationAuthoringEvaluationJobResult" = rest_field( + visibility=["read", "create", "update", "delete", "query"] + ) + """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.AnalyzeConversationAuthoringEvaluationJobResult", + 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: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringEvaluationOptions(_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.conversations.authoring.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( + visibility=["read", "create", "update", "delete", "query"] + ) + """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", visibility=["read", "create", "update", "delete", "query"] + ) + """Represents the training dataset split percentage. Only needed in case the evaluation kind is + percentage.""" + testing_split_percentage: Optional[int] = rest_field( + name="testingSplitPercentage", visibility=["read", "create", "update", "delete", "query"] + ) + """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: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringEvaluationSummary(_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.conversations.authoring.models.AnalyzeConversationAuthoringEntitiesEvaluationSummary + :ivar intents_evaluation: Contains the data related to intents evaluation. Required. + :vartype intents_evaluation: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringIntentsEvaluationSummary + :ivar evaluation_options: The options that were used while running the evaluation. + :vartype evaluation_options: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringEvaluationOptions + """ + + entities_evaluation: "_models.AnalyzeConversationAuthoringEntitiesEvaluationSummary" = rest_field( + name="entitiesEvaluation", visibility=["read", "create", "update", "delete", "query"] + ) + """Contains the data related to entities evaluation. Required.""" + intents_evaluation: "_models.AnalyzeConversationAuthoringIntentsEvaluationSummary" = rest_field( + name="intentsEvaluation", visibility=["read", "create", "update", "delete", "query"] + ) + """Contains the data related to intents evaluation. Required.""" + evaluation_options: Optional["_models.AnalyzeConversationAuthoringEvaluationOptions"] = rest_field( + name="evaluationOptions", visibility=["read", "create", "update", "delete", "query"] + ) + """The options that were used while running the evaluation.""" + + @overload + def __init__( + self, + *, + entities_evaluation: "_models.AnalyzeConversationAuthoringEntitiesEvaluationSummary", + intents_evaluation: "_models.AnalyzeConversationAuthoringIntentsEvaluationSummary", + evaluation_options: Optional["_models.AnalyzeConversationAuthoringEvaluationOptions"] = None, + ) -> None: ... + + @overload + def __init__(self, mapping: Mapping[str, Any]) -> None: + """ + :param mapping: raw JSON to initialize the model. + :type mapping: Mapping[str, Any] + """ + + def __init__(self, *args: Any, **kwargs: Any) -> None: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringExportedConversationOrchestration(_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", visibility=["read", "create", "update", "delete", "query"]) + """The name of the targeted project. Required.""" + deployment_name: str = rest_field(name="deploymentName", visibility=["read", "create", "update", "delete", "query"]) + """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: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringExportedOrchestrationOptions(_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: + AnalyzeConversationAuthoringExportedConversationOrchestrationOptions, + AnalyzeConversationAuthoringExportedLuisOrchestrationOptions, + AnalyzeConversationAuthoringExportedQuestionAnsweringOrchestrationOptions + + 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.conversations.authoring.models.OrchestrationTargetProjectKind + """ + + __mapping__: Dict[str, _model_base.Model] = {} + target_project_kind: str = rest_discriminator( + name="targetProjectKind", visibility=["read", "create", "update", "delete", "query"] + ) + """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: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringExportedConversationOrchestrationOptions( + AnalyzeConversationAuthoringExportedOrchestrationOptions, 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.conversations.authoring.models.AnalyzeConversationAuthoringExportedConversationOrchestration + :ivar target_project_kind: The kind of the target used in the orchestration flow. Required. + :vartype target_project_kind: str or + ~azure.ai.language.conversations.authoring.models.CONVERSATION + """ + + conversation_orchestration: "_models.AnalyzeConversationAuthoringExportedConversationOrchestration" = rest_field( + name="conversationOrchestration", visibility=["read", "create", "update", "delete", "query"] + ) + """The Conversational project target details. Required.""" + target_project_kind: Literal[OrchestrationTargetProjectKind.CONVERSATION] = rest_discriminator(name="targetProjectKind", visibility=["read", "create", "update", "delete", "query"]) # type: ignore + """The kind of the target used in the orchestration flow. Required.""" + + @overload + def __init__( + self, + *, + conversation_orchestration: "_models.AnalyzeConversationAuthoringExportedConversationOrchestration", + ) -> None: ... + + @overload + def __init__(self, mapping: Mapping[str, Any]) -> None: + """ + :param mapping: raw JSON to initialize the model. + :type mapping: Mapping[str, Any] + """ + + def __init__(self, *args: Any, **kwargs: Any) -> None: + super().__init__(*args, target_project_kind=OrchestrationTargetProjectKind.CONVERSATION, **kwargs) + + +class AnalyzeConversationAuthoringExportedEntityList(_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.conversations.authoring.models.AnalyzeConversationAuthoringExportedEntitySublist] + """ + + sublists: Optional[List["_models.AnalyzeConversationAuthoringExportedEntitySublist"]] = rest_field( + visibility=["read", "create", "update", "delete", "query"] + ) + """The sub-lists of the list component.""" + + @overload + def __init__( + self, + *, + sublists: Optional[List["_models.AnalyzeConversationAuthoringExportedEntitySublist"]] = None, + ) -> None: ... + + @overload + def __init__(self, mapping: Mapping[str, Any]) -> None: + """ + :param mapping: raw JSON to initialize the model. + :type mapping: Mapping[str, Any] + """ + + def __init__(self, *args: Any, **kwargs: Any) -> None: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringExportedEntityListSynonym(_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(visibility=["read", "create", "update", "delete", "query"]) + """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", visibility=["read", "create", "update", "delete", "query"] + ) + """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: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringExportedEntityRegex(_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.conversations.authoring.models.AnalyzeConversationAuthoringExportedEntityRegexExpression] + """ + + expressions: Optional[List["_models.AnalyzeConversationAuthoringExportedEntityRegexExpression"]] = rest_field( + visibility=["read", "create", "update", "delete", "query"] + ) + """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.AnalyzeConversationAuthoringExportedEntityRegexExpression"]] = None, + ) -> None: ... + + @overload + def __init__(self, mapping: Mapping[str, Any]) -> None: + """ + :param mapping: raw JSON to initialize the model. + :type mapping: Mapping[str, Any] + """ + + def __init__(self, *args: Any, **kwargs: Any) -> None: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringExportedEntityRegexExpression(_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", visibility=["read", "create", "update", "delete", "query"]) + """The key of the regex expression.""" + language: Optional[str] = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """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", visibility=["read", "create", "update", "delete", "query"] + ) + """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: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringExportedEntitySublist(_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.conversations.authoring.models.AnalyzeConversationAuthoringExportedEntityListSynonym] + """ + + list_key: Optional[str] = rest_field(name="listKey", visibility=["read", "create", "update", "delete", "query"]) + """The key of the sub-list.""" + synonyms: Optional[List["_models.AnalyzeConversationAuthoringExportedEntityListSynonym"]] = rest_field( + visibility=["read", "create", "update", "delete", "query"] + ) + """The phrases of that correspond to the sub-list.""" + + @overload + def __init__( + self, + *, + list_key: Optional[str] = None, + synonyms: Optional[List["_models.AnalyzeConversationAuthoringExportedEntityListSynonym"]] = None, + ) -> None: ... + + @overload + def __init__(self, mapping: Mapping[str, Any]) -> None: + """ + :param mapping: raw JSON to initialize the model. + :type mapping: Mapping[str, Any] + """ + + def __init__(self, *args: Any, **kwargs: Any) -> None: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringExportedLuisOrchestration(_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", visibility=["read", "create", "update", "delete", "query"]) + """The LUIS application ID. Required.""" + app_version: Optional[str] = rest_field( + name="appVersion", visibility=["read", "create", "update", "delete", "query"] + ) + """The targeted version Id.""" + slot_name: Optional[str] = rest_field(name="slotName", visibility=["read", "create", "update", "delete", "query"]) + """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: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringExportedLuisOrchestrationOptions( + AnalyzeConversationAuthoringExportedOrchestrationOptions, 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.conversations.authoring.models.AnalyzeConversationAuthoringExportedLuisOrchestration + :ivar target_project_kind: The kind of the target used in the orchestration flow. Required. + :vartype target_project_kind: str or ~azure.ai.language.conversations.authoring.models.LUIS + """ + + luis_orchestration: "_models.AnalyzeConversationAuthoringExportedLuisOrchestration" = rest_field( + name="luisOrchestration", visibility=["read", "create", "update", "delete", "query"] + ) + """The LUIS application target details. Required.""" + target_project_kind: Literal[OrchestrationTargetProjectKind.LUIS] = rest_discriminator(name="targetProjectKind", visibility=["read", "create", "update", "delete", "query"]) # type: ignore + """The kind of the target used in the orchestration flow. Required.""" + + @overload + def __init__( + self, + *, + luis_orchestration: "_models.AnalyzeConversationAuthoringExportedLuisOrchestration", + ) -> None: ... + + @overload + def __init__(self, mapping: Mapping[str, Any]) -> None: + """ + :param mapping: raw JSON to initialize the model. + :type mapping: Mapping[str, Any] + """ + + def __init__(self, *args: Any, **kwargs: Any) -> None: + super().__init__(*args, target_project_kind=OrchestrationTargetProjectKind.LUIS, **kwargs) + + +class AnalyzeConversationAuthoringExportedModelJobState(_model_base.Model): # pylint: disable=name-too-long + """Represents the state of a job to create or updated an exported model. + + Readonly variables are only populated by the server, and will be ignored when sending a request. + + + :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.conversations.authoring.models.JobStatus + :ivar warnings: The warnings that were encountered while executing the job. + :vartype warnings: list[~azure.ai.language.conversations.authoring.models.Warning] + :ivar errors: The errors encountered while executing the job. + :vartype errors: list[~azure.ai.language.conversations.authoring.models.Error] + """ + + job_id: str = rest_field(name="jobId", visibility=["read"]) + """The job ID. Required.""" + created_date_time: datetime.datetime = rest_field( + name="createdDateTime", visibility=["read", "create", "update", "delete", "query"], format="rfc3339" + ) + """The creation date time of the job. Required.""" + last_updated_date_time: datetime.datetime = rest_field( + name="lastUpdatedDateTime", visibility=["read", "create", "update", "delete", "query"], format="rfc3339" + ) + """The last date time the job was updated. Required.""" + expiration_date_time: Optional[datetime.datetime] = rest_field( + name="expirationDateTime", visibility=["read", "create", "update", "delete", "query"], format="rfc3339" + ) + """The expiration date time of the job.""" + status: Union[str, "_models.JobStatus"] = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """The job status. Required. Known values are: \"notStarted\", \"running\", \"succeeded\", + \"failed\", \"cancelled\", \"cancelling\", and \"partiallyCompleted\".""" + warnings: Optional[List["_models.Warning"]] = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """The warnings that were encountered while executing the job.""" + errors: Optional[List["_models.Error"]] = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """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: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringExportedPrebuiltEntity(_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(visibility=["read", "create", "update", "delete", "query"]) + """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: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringExportedProject(_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.conversations.authoring.models.StringIndexType + :ivar metadata: Represents the project metadata. Required. + :vartype metadata: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringCreateProjectOptions + :ivar assets: Represents the project assets. + :vartype assets: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringExportedProjectAssets + """ + + project_file_version: str = rest_field( + name="projectFileVersion", visibility=["read", "create", "update", "delete", "query"] + ) + """The version of the exported file. Required.""" + string_index_type: Union[str, "_models.StringIndexType"] = rest_field( + name="stringIndexType", visibility=["read", "create", "update", "delete", "query"] + ) + """Specifies the method used to interpret string offsets. For additional information see + https://aka.ms/text-analytics-offsets. Required. \"Utf16CodeUnit\"""" + metadata: "_models.AnalyzeConversationAuthoringCreateProjectOptions" = rest_field( + visibility=["read", "create", "update", "delete", "query"] + ) + """Represents the project metadata. Required.""" + assets: Optional["_models.AnalyzeConversationAuthoringExportedProjectAssets"] = rest_field( + visibility=["read", "create", "update", "delete", "query"] + ) + """Represents the project assets.""" + + @overload + def __init__( + self, + *, + project_file_version: str, + string_index_type: Union[str, "_models.StringIndexType"], + metadata: "_models.AnalyzeConversationAuthoringCreateProjectOptions", + assets: Optional["_models.AnalyzeConversationAuthoringExportedProjectAssets"] = None, + ) -> None: ... + + @overload + def __init__(self, mapping: Mapping[str, Any]) -> None: + """ + :param mapping: raw JSON to initialize the model. + :type mapping: Mapping[str, Any] + """ + + def __init__(self, *args: Any, **kwargs: Any) -> None: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringExportedQuestionAnsweringOrchestration( + _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", visibility=["read", "create", "update", "delete", "query"]) + """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: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringExportedQuestionAnsweringOrchestrationOptions( + AnalyzeConversationAuthoringExportedOrchestrationOptions, 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.conversations.authoring.models.AnalyzeConversationAuthoringExportedQuestionAnsweringOrchestration + :ivar target_project_kind: The kind of the target used in the orchestration flow. Required. + :vartype target_project_kind: str or + ~azure.ai.language.conversations.authoring.models.QUESTION_ANSWERING + """ + + question_answering_orchestration: "_models.AnalyzeConversationAuthoringExportedQuestionAnsweringOrchestration" = ( + rest_field(name="questionAnsweringOrchestration", visibility=["read", "create", "update", "delete", "query"]) + ) + """The Question Answering project details. Required.""" + target_project_kind: Literal[OrchestrationTargetProjectKind.QUESTION_ANSWERING] = rest_discriminator(name="targetProjectKind", visibility=["read", "create", "update", "delete", "query"]) # type: ignore + """The kind of the target used in the orchestration flow. Required.""" + + @overload + def __init__( + self, + *, + question_answering_orchestration: "_models.AnalyzeConversationAuthoringExportedQuestionAnsweringOrchestration", + ) -> None: ... + + @overload + def __init__(self, mapping: Mapping[str, Any]) -> None: + """ + :param mapping: raw JSON to initialize the model. + :type mapping: Mapping[str, Any] + """ + + def __init__(self, *args: Any, **kwargs: Any) -> None: + super().__init__(*args, target_project_kind=OrchestrationTargetProjectKind.QUESTION_ANSWERING, **kwargs) + + +class AnalyzeConversationAuthoringExportedTrainedModel(_model_base.Model): # pylint: disable=name-too-long + """Represents an exported trained model. + + Readonly variables are only populated by the server, and will be ignored when sending a request. + + + :ivar exported_model_name: The exported model name. Required. + :vartype exported_model_name: 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_exported_model_date_time: The last exported date time of the model. Required. + :vartype last_exported_model_date_time: ~datetime.datetime + :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 + """ + + exported_model_name: str = rest_field(name="exportedModelName", visibility=["read"]) + """The exported model name. Required.""" + model_id: str = rest_field(name="modelId", visibility=["read", "create", "update", "delete", "query"]) + """The model ID. Required.""" + last_trained_date_time: datetime.datetime = rest_field( + name="lastTrainedDateTime", visibility=["read", "create", "update", "delete", "query"], format="rfc3339" + ) + """The last trained date time of the model. Required.""" + last_exported_model_date_time: datetime.datetime = rest_field( + name="lastExportedModelDateTime", visibility=["read", "create", "update", "delete", "query"], format="rfc3339" + ) + """The last exported date time of the model. Required.""" + model_expiration_date: datetime.date = rest_field( + name="modelExpirationDate", visibility=["read", "create", "update", "delete", "query"] + ) + """The model expiration date. Required.""" + model_training_config_version: str = rest_field( + name="modelTrainingConfigVersion", visibility=["read", "create", "update", "delete", "query"] + ) + """The model training config version. Required.""" + + @overload + def __init__( + self, + *, + model_id: str, + last_trained_date_time: datetime.datetime, + last_exported_model_date_time: datetime.datetime, + model_expiration_date: datetime.date, + model_training_config_version: 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: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringExportedUtteranceEntityLabel(_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(visibility=["read", "create", "update", "delete", "query"]) + """The category of the entity label. Required.""" + offset: int = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """Start position for the entity text. Required.""" + length: int = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """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: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringExportProjectJobState(_model_base.Model): # pylint: disable=name-too-long + """Represents the state of an export job. + + Readonly variables are only populated by the server, and will be ignored when sending a request. + + + :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.conversations.authoring.models.JobStatus + :ivar warnings: The warnings that were encountered while executing the job. + :vartype warnings: list[~azure.ai.language.conversations.authoring.models.Warning] + :ivar errors: The errors encountered while executing the job. + :vartype errors: list[~azure.ai.language.conversations.authoring.models.Error] + :ivar result_url: The URL to use in order to download the exported project. + :vartype result_url: str + """ + + job_id: str = rest_field(name="jobId", visibility=["read"]) + """The job ID. Required.""" + created_date_time: datetime.datetime = rest_field( + name="createdDateTime", visibility=["read", "create", "update", "delete", "query"], format="rfc3339" + ) + """The creation date time of the job. Required.""" + last_updated_date_time: datetime.datetime = rest_field( + name="lastUpdatedDateTime", visibility=["read", "create", "update", "delete", "query"], format="rfc3339" + ) + """The last date time the job was updated. Required.""" + expiration_date_time: Optional[datetime.datetime] = rest_field( + name="expirationDateTime", visibility=["read", "create", "update", "delete", "query"], format="rfc3339" + ) + """The expiration date time of the job.""" + status: Union[str, "_models.JobStatus"] = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """The job status. Required. Known values are: \"notStarted\", \"running\", \"succeeded\", + \"failed\", \"cancelled\", \"cancelling\", and \"partiallyCompleted\".""" + warnings: Optional[List["_models.Warning"]] = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """The warnings that were encountered while executing the job.""" + errors: Optional[List["_models.Error"]] = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """The errors encountered while executing the job.""" + result_url: Optional[str] = rest_field(name="resultUrl", visibility=["read", "create", "update", "delete", "query"]) + """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: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringImportProjectJobState(_model_base.Model): # pylint: disable=name-too-long + """Represents the state of an import job. + + Readonly variables are only populated by the server, and will be ignored when sending a request. + + + :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.conversations.authoring.models.JobStatus + :ivar warnings: The warnings that were encountered while executing the job. + :vartype warnings: list[~azure.ai.language.conversations.authoring.models.Warning] + :ivar errors: The errors encountered while executing the job. + :vartype errors: list[~azure.ai.language.conversations.authoring.models.Error] + """ + + job_id: str = rest_field(name="jobId", visibility=["read"]) + """The job ID. Required.""" + created_date_time: datetime.datetime = rest_field( + name="createdDateTime", visibility=["read", "create", "update", "delete", "query"], format="rfc3339" + ) + """The creation date time of the job. Required.""" + last_updated_date_time: datetime.datetime = rest_field( + name="lastUpdatedDateTime", visibility=["read", "create", "update", "delete", "query"], format="rfc3339" + ) + """The last date time the job was updated. Required.""" + expiration_date_time: Optional[datetime.datetime] = rest_field( + name="expirationDateTime", visibility=["read", "create", "update", "delete", "query"], format="rfc3339" + ) + """The expiration date time of the job.""" + status: Union[str, "_models.JobStatus"] = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """The job status. Required. Known values are: \"notStarted\", \"running\", \"succeeded\", + \"failed\", \"cancelled\", \"cancelling\", and \"partiallyCompleted\".""" + warnings: Optional[List["_models.Warning"]] = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """The warnings that were encountered while executing the job.""" + errors: Optional[List["_models.Error"]] = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """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: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringIntentEvaluationSummary(_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(visibility=["read", "create", "update", "delete", "query"]) + """Represents the model precision. Required.""" + precision: float = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """Represents the model recall. Required.""" + recall: float = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """Represents the model F1 score. Required.""" + true_positive_count: int = rest_field( + name="truePositiveCount", visibility=["read", "create", "update", "delete", "query"] + ) + """Represents the count of true positive. Required.""" + true_negative_count: int = rest_field( + name="trueNegativeCount", visibility=["read", "create", "update", "delete", "query"] + ) + """Represents the count of true negative. Required.""" + false_positive_count: int = rest_field( + name="falsePositiveCount", visibility=["read", "create", "update", "delete", "query"] + ) + """Represents the count of false positive. Required.""" + false_negative_count: int = rest_field( + name="falseNegativeCount", visibility=["read", "create", "update", "delete", "query"] + ) + """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: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringIntentsEvaluationSummary(_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.conversations.authoring.models.AnalyzeConversationAuthoringConfusionMatrix + :ivar intents: Represents the intents evaluation summary. Required. + :vartype intents: dict[str, + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringIntentEvaluationSummary] + :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.AnalyzeConversationAuthoringConfusionMatrix" = rest_field( + name="confusionMatrix", visibility=["read", "create", "update", "delete", "query"] + ) + """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.AnalyzeConversationAuthoringIntentEvaluationSummary"] = rest_field( + visibility=["read", "create", "update", "delete", "query"] + ) + """Represents the intents evaluation summary. Required.""" + micro_f1: float = rest_field(name="microF1", visibility=["read", "create", "update", "delete", "query"]) + """Represents the micro F1. Expected value is a float between 0 and 1 inclusive. Required.""" + micro_precision: float = rest_field( + name="microPrecision", visibility=["read", "create", "update", "delete", "query"] + ) + """Represents the micro precision. Expected value is a float between 0 and 1 inclusive. Required.""" + micro_recall: float = rest_field(name="microRecall", visibility=["read", "create", "update", "delete", "query"]) + """Represents the micro recall. Expected value is a float between 0 and 1 inclusive. Required.""" + macro_f1: float = rest_field(name="macroF1", visibility=["read", "create", "update", "delete", "query"]) + """Represents the macro F1. Expected value is a float between 0 and 1 inclusive. Required.""" + macro_precision: float = rest_field( + name="macroPrecision", visibility=["read", "create", "update", "delete", "query"] + ) + """Represents the macro precision. Expected value is a float between 0 and 1 inclusive. Required.""" + macro_recall: float = rest_field(name="macroRecall", visibility=["read", "create", "update", "delete", "query"]) + """Represents the macro recall. Expected value is a float between 0 and 1 inclusive. Required.""" + + @overload + def __init__( + self, + *, + confusion_matrix: "_models.AnalyzeConversationAuthoringConfusionMatrix", + intents: Dict[str, "_models.AnalyzeConversationAuthoringIntentEvaluationSummary"], + 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: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringLoadSnapshotJobState(_model_base.Model): # pylint: disable=name-too-long + """Represents the state of loading a snapshot job. + + Readonly variables are only populated by the server, and will be ignored when sending a request. + + + :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.conversations.authoring.models.JobStatus + :ivar warnings: The warnings that were encountered while executing the job. + :vartype warnings: list[~azure.ai.language.conversations.authoring.models.Warning] + :ivar errors: The errors encountered while executing the job. + :vartype errors: list[~azure.ai.language.conversations.authoring.models.Error] + """ + + job_id: str = rest_field(name="jobId", visibility=["read"]) + """The job ID. Required.""" + created_date_time: datetime.datetime = rest_field( + name="createdDateTime", visibility=["read", "create", "update", "delete", "query"], format="rfc3339" + ) + """The creation date time of the job. Required.""" + last_updated_date_time: datetime.datetime = rest_field( + name="lastUpdatedDateTime", visibility=["read", "create", "update", "delete", "query"], format="rfc3339" + ) + """The last date time the job was updated. Required.""" + expiration_date_time: Optional[datetime.datetime] = rest_field( + name="expirationDateTime", visibility=["read", "create", "update", "delete", "query"], format="rfc3339" + ) + """The expiration date time of the job.""" + status: Union[str, "_models.JobStatus"] = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """The job status. Required. Known values are: \"notStarted\", \"running\", \"succeeded\", + \"failed\", \"cancelled\", \"cancelling\", and \"partiallyCompleted\".""" + warnings: Optional[List["_models.Warning"]] = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """The warnings that were encountered while executing the job.""" + errors: Optional[List["_models.Error"]] = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """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: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringOrchestrationExportedIntent(_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.conversations.authoring.models.AnalyzeConversationAuthoringExportedOrchestrationOptions + :ivar category: The intent category. Required. + :vartype category: str + """ + + orchestration: Optional["_models.AnalyzeConversationAuthoringExportedOrchestrationOptions"] = rest_field( + visibility=["read", "create", "update", "delete", "query"] + ) + """Specifies the behavior of this intent in the orchestration flow.""" + category: str = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """The intent category. Required.""" + + @overload + def __init__( + self, + *, + category: str, + orchestration: Optional["_models.AnalyzeConversationAuthoringExportedOrchestrationOptions"] = None, + ) -> None: ... + + @overload + def __init__(self, mapping: Mapping[str, Any]) -> None: + """ + :param mapping: raw JSON to initialize the model. + :type mapping: Mapping[str, Any] + """ + + def __init__(self, *args: Any, **kwargs: Any) -> None: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringOrchestrationExportedProjectAssets( + AnalyzeConversationAuthoringExportedProjectAssets, 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.conversations.authoring.models.AnalyzeConversationAuthoringOrchestrationExportedIntent] + :ivar utterances: Represents the utterances of the project. + :vartype utterances: + list[~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringOrchestrationExportedUtterance] + :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.conversations.authoring.models.ORCHESTRATION + """ + + intents: Optional[List["_models.AnalyzeConversationAuthoringOrchestrationExportedIntent"]] = rest_field( + visibility=["read", "create", "update", "delete", "query"] + ) + """Represents the intents of the project.""" + utterances: Optional[List["_models.AnalyzeConversationAuthoringOrchestrationExportedUtterance"]] = rest_field( + visibility=["read", "create", "update", "delete", "query"] + ) + """Represents the utterances of the project.""" + project_kind: Literal[ProjectKind.ORCHESTRATION] = rest_discriminator(name="projectKind", visibility=["read", "create", "update", "delete", "query"]) # 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.AnalyzeConversationAuthoringOrchestrationExportedIntent"]] = None, + utterances: Optional[List["_models.AnalyzeConversationAuthoringOrchestrationExportedUtterance"]] = None, + ) -> None: ... + + @overload + def __init__(self, mapping: Mapping[str, Any]) -> None: + """ + :param mapping: raw JSON to initialize the model. + :type mapping: Mapping[str, Any] + """ + + def __init__(self, *args: Any, **kwargs: Any) -> None: + super().__init__(*args, project_kind=ProjectKind.ORCHESTRATION, **kwargs) + + +class AnalyzeConversationAuthoringOrchestrationExportedUtterance(_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(visibility=["read", "create", "update", "delete", "query"]) + """The utterance text. Required.""" + language: Optional[str] = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """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(visibility=["read", "create", "update", "delete", "query"]) + """The intent of the utterance. Required.""" + dataset: Optional[str] = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """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: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringPrebuiltEntities(_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.conversations.authoring.models.AnalyzeConversationAuthoringPrebuiltEntity] + :ivar next_link: The next page link. + :vartype next_link: str + """ + + value: List["_models.AnalyzeConversationAuthoringPrebuiltEntity"] = rest_field( + visibility=["read", "create", "update", "delete", "query"] + ) + """The supported prebuilt entities. Required.""" + next_link: Optional[str] = rest_field(name="nextLink", visibility=["read", "create", "update", "delete", "query"]) + """The next page link.""" + + @overload + def __init__( + self, + *, + value: List["_models.AnalyzeConversationAuthoringPrebuiltEntity"], + 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: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringPrebuiltEntity(_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(visibility=["read", "create", "update", "delete", "query"]) + """The prebuilt entity category. Required.""" + description: str = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """The description. Required.""" + examples: str = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """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: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringProjectDeletionJobState(_model_base.Model): # pylint: disable=name-too-long + """Represents the state of a project deletion job. + + Readonly variables are only populated by the server, and will be ignored when sending a request. + + + :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.conversations.authoring.models.JobStatus + :ivar warnings: The warnings that were encountered while executing the job. + :vartype warnings: list[~azure.ai.language.conversations.authoring.models.Warning] + :ivar errors: The errors encountered while executing the job. + :vartype errors: list[~azure.ai.language.conversations.authoring.models.Error] + """ + + job_id: str = rest_field(name="jobId", visibility=["read"]) + """The job ID. Required.""" + created_date_time: datetime.datetime = rest_field( + name="createdDateTime", visibility=["read", "create", "update", "delete", "query"], format="rfc3339" + ) + """The creation date time of the job. Required.""" + last_updated_date_time: datetime.datetime = rest_field( + name="lastUpdatedDateTime", visibility=["read", "create", "update", "delete", "query"], format="rfc3339" + ) + """The last date time the job was updated. Required.""" + expiration_date_time: Optional[datetime.datetime] = rest_field( + name="expirationDateTime", visibility=["read", "create", "update", "delete", "query"], format="rfc3339" + ) + """The expiration date time of the job.""" + status: Union[str, "_models.JobStatus"] = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """The job status. Required. Known values are: \"notStarted\", \"running\", \"succeeded\", + \"failed\", \"cancelled\", \"cancelling\", and \"partiallyCompleted\".""" + warnings: Optional[List["_models.Warning"]] = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """The warnings that were encountered while executing the job.""" + errors: Optional[List["_models.Error"]] = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """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: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringProjectDeployment(_model_base.Model): # pylint: disable=name-too-long + """Represents a project deployment. + + Readonly variables are only populated by the server, and will be ignored when sending a request. + + + :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.conversations.authoring.models.AnalyzeConversationAuthoringDeploymentResource] + """ + + deployment_name: str = rest_field(name="deploymentName", visibility=["read"]) + """Represents deployment name. Required.""" + model_id: str = rest_field(name="modelId", visibility=["read", "create", "update", "delete", "query"]) + """Represents deployment modelId. Required.""" + last_trained_date_time: datetime.datetime = rest_field( + name="lastTrainedDateTime", visibility=["read", "create", "update", "delete", "query"], format="rfc3339" + ) + """Represents deployment last trained time. Required.""" + last_deployed_date_time: datetime.datetime = rest_field( + name="lastDeployedDateTime", visibility=["read", "create", "update", "delete", "query"], format="rfc3339" + ) + """Represents deployment last deployed time. Required.""" + deployment_expiration_date: datetime.date = rest_field( + name="deploymentExpirationDate", visibility=["read", "create", "update", "delete", "query"] + ) + """Represents deployment expiration date in the runtime. Required.""" + model_training_config_version: str = rest_field( + name="modelTrainingConfigVersion", visibility=["read", "create", "update", "delete", "query"] + ) + """Represents model training config version. Required.""" + assigned_resources: List["_models.AnalyzeConversationAuthoringDeploymentResource"] = rest_field( + name="assignedResources", visibility=["read", "create", "update", "delete", "query"] + ) + """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.AnalyzeConversationAuthoringDeploymentResource"], + ) -> None: ... + + @overload + def __init__(self, mapping: Mapping[str, Any]) -> None: + """ + :param mapping: raw JSON to initialize the model. + :type mapping: Mapping[str, Any] + """ + + def __init__(self, *args: Any, **kwargs: Any) -> None: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringProjectMetadata(_model_base.Model): # pylint: disable=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.conversations.authoring.models.ProjectKind + :ivar settings: The project settings. + :vartype settings: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringProjectSettings + :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", visibility=["read", "create", "update", "delete", "query"], format="rfc3339" + ) + """Represents the project creation datetime. Required.""" + last_modified_date_time: datetime.datetime = rest_field( + name="lastModifiedDateTime", visibility=["read", "create", "update", "delete", "query"], format="rfc3339" + ) + """Represents the project creation datetime. Required.""" + last_trained_date_time: Optional[datetime.datetime] = rest_field( + name="lastTrainedDateTime", visibility=["read", "create", "update", "delete", "query"], format="rfc3339" + ) + """Represents the project last trained datetime.""" + last_deployed_date_time: Optional[datetime.datetime] = rest_field( + name="lastDeployedDateTime", visibility=["read", "create", "update", "delete", "query"], 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.AnalyzeConversationAuthoringProjectSettings"] = 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.AnalyzeConversationAuthoringProjectSettings"] = 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: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringProjectSettings(_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", visibility=["read", "create", "update", "delete", "query"] + ) + """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: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringProjectTrainedModel(_model_base.Model): # pylint: disable=name-too-long + """Represents a trained model. + + Readonly variables are only populated by the server, and will be ignored when sending a request. + + + :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(visibility=["read"]) + """The trained model label. Required.""" + model_id: str = rest_field(name="modelId", visibility=["read", "create", "update", "delete", "query"]) + """The model ID. Required.""" + last_trained_date_time: datetime.datetime = rest_field( + name="lastTrainedDateTime", visibility=["read", "create", "update", "delete", "query"], format="rfc3339" + ) + """The last trained date time of the model. Required.""" + last_training_duration_in_seconds: int = rest_field( + name="lastTrainingDurationInSeconds", visibility=["read", "create", "update", "delete", "query"] + ) + """The duration of the model's last training request in seconds. Required.""" + model_expiration_date: datetime.date = rest_field( + name="modelExpirationDate", visibility=["read", "create", "update", "delete", "query"] + ) + """The model expiration date. Required.""" + model_training_config_version: str = rest_field( + name="modelTrainingConfigVersion", visibility=["read", "create", "update", "delete", "query"] + ) + """The model training config version. Required.""" + has_snapshot: bool = rest_field(name="hasSnapshot", visibility=["read", "create", "update", "delete", "query"]) + """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: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringResourceMetadata(_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", visibility=["read", "create", "update", "delete", "query"] + ) + """Represents the Azure resource ID. Required.""" + custom_domain: str = rest_field(name="customDomain", visibility=["read", "create", "update", "delete", "query"]) + """Represents the Azure resource custom domain. Required.""" + region: str = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """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: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringSubTrainingJobState(_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.conversations.authoring.models.JobStatus + """ + + percent_complete: int = rest_field( + name="percentComplete", visibility=["read", "create", "update", "delete", "query"] + ) + """Represents progress percentage. Required.""" + start_date_time: Optional[datetime.datetime] = rest_field( + name="startDateTime", visibility=["read", "create", "update", "delete", "query"], format="rfc3339" + ) + """Represents the start date time.""" + end_date_time: Optional[datetime.datetime] = rest_field( + name="endDateTime", visibility=["read", "create", "update", "delete", "query"], format="rfc3339" + ) + """Represents the end date time.""" + status: Union[str, "_models.JobStatus"] = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """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: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringSupportedLanguage(_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", visibility=["read", "create", "update", "delete", "query"]) + """The language name. Required.""" + language_code: str = rest_field(name="languageCode", visibility=["read", "create", "update", "delete", "query"]) + """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: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringSupportedLanguages(_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.conversations.authoring.models.AnalyzeConversationAuthoringSupportedLanguage] + :ivar next_link: The next page link. + :vartype next_link: str + """ + + value: List["_models.AnalyzeConversationAuthoringSupportedLanguage"] = rest_field( + visibility=["read", "create", "update", "delete", "query"] + ) + """The list of the languages. Required.""" + next_link: Optional[str] = rest_field(name="nextLink", visibility=["read", "create", "update", "delete", "query"]) + """The next page link.""" + + @overload + def __init__( + self, + *, + value: List["_models.AnalyzeConversationAuthoringSupportedLanguage"], + 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: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringSwapDeploymentsJobState(_model_base.Model): # pylint: disable=name-too-long + """Represents the state of a deployment job. + + Readonly variables are only populated by the server, and will be ignored when sending a request. + + + :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.conversations.authoring.models.JobStatus + :ivar warnings: The warnings that were encountered while executing the job. + :vartype warnings: list[~azure.ai.language.conversations.authoring.models.Warning] + :ivar errors: The errors encountered while executing the job. + :vartype errors: list[~azure.ai.language.conversations.authoring.models.Error] + """ + + job_id: str = rest_field(name="jobId", visibility=["read"]) + """The job ID. Required.""" + created_date_time: datetime.datetime = rest_field( + name="createdDateTime", visibility=["read", "create", "update", "delete", "query"], format="rfc3339" + ) + """The creation date time of the job. Required.""" + last_updated_date_time: datetime.datetime = rest_field( + name="lastUpdatedDateTime", visibility=["read", "create", "update", "delete", "query"], format="rfc3339" + ) + """The last date time the job was updated. Required.""" + expiration_date_time: Optional[datetime.datetime] = rest_field( + name="expirationDateTime", visibility=["read", "create", "update", "delete", "query"], format="rfc3339" + ) + """The expiration date time of the job.""" + status: Union[str, "_models.JobStatus"] = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """The job status. Required. Known values are: \"notStarted\", \"running\", \"succeeded\", + \"failed\", \"cancelled\", \"cancelling\", and \"partiallyCompleted\".""" + warnings: Optional[List["_models.Warning"]] = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """The warnings that were encountered while executing the job.""" + errors: Optional[List["_models.Error"]] = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """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: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringSwapDeploymentsOptions(_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", visibility=["read", "create", "update", "delete", "query"] + ) + """Represents the first deployment name. Required.""" + second_deployment_name: str = rest_field( + name="secondDeploymentName", visibility=["read", "create", "update", "delete", "query"] + ) + """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: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringTrainingConfigVersion(_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", visibility=["read", "create", "update", "delete", "query"] + ) + """Represents the version of the config. Required.""" + model_expiration_date: datetime.date = rest_field( + name="modelExpirationDate", visibility=["read", "create", "update", "delete", "query"] + ) + """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: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringTrainingConfigVersions(_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.conversations.authoring.models.AnalyzeConversationAuthoringTrainingConfigVersion] + :ivar next_link: The next page link. + :vartype next_link: str + """ + + value: List["_models.AnalyzeConversationAuthoringTrainingConfigVersion"] = rest_field( + visibility=["read", "create", "update", "delete", "query"] + ) + """The list of the training config versions. Required.""" + next_link: Optional[str] = rest_field(name="nextLink", visibility=["read", "create", "update", "delete", "query"]) + """The next page link.""" + + @overload + def __init__( + self, + *, + value: List["_models.AnalyzeConversationAuthoringTrainingConfigVersion"], + 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: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringTrainingJobOptions(_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.conversations.authoring.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.conversations.authoring.models.AnalyzeConversationAuthoringEvaluationOptions + """ + + model_label: str = rest_field(name="modelLabel", visibility=["read", "create", "update", "delete", "query"]) + """Represents the output model label. Required.""" + training_config_version: Optional[str] = rest_field( + name="trainingConfigVersion", visibility=["read", "create", "update", "delete", "query"] + ) + """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", visibility=["read", "create", "update", "delete", "query"] + ) + """Represents the mode of the training operation. Required. Known values are: \"advanced\" and + \"standard\".""" + evaluation_options: Optional["_models.AnalyzeConversationAuthoringEvaluationOptions"] = rest_field( + name="evaluationOptions", visibility=["read", "create", "update", "delete", "query"] + ) + """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.AnalyzeConversationAuthoringEvaluationOptions"] = None, + ) -> None: ... + + @overload + def __init__(self, mapping: Mapping[str, Any]) -> None: + """ + :param mapping: raw JSON to initialize the model. + :type mapping: Mapping[str, Any] + """ + + def __init__(self, *args: Any, **kwargs: Any) -> None: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringTrainingJobResult(_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.conversations.authoring.models.TrainingMode + :ivar training_status: Represents the model training status. Required. + :vartype training_status: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringSubTrainingJobState + :ivar evaluation_status: Represents model evaluation status. + :vartype evaluation_status: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringSubTrainingJobState + :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", visibility=["read", "create", "update", "delete", "query"]) + """Represents trained model label. Required.""" + training_config_version: str = rest_field( + name="trainingConfigVersion", visibility=["read", "create", "update", "delete", "query"] + ) + """Represents training config version. Required.""" + training_mode: Optional[Union[str, "_models.TrainingMode"]] = rest_field( + name="trainingMode", visibility=["read", "create", "update", "delete", "query"] + ) + """Represents the mode of the training operation. Known values are: \"advanced\" and \"standard\".""" + training_status: "_models.AnalyzeConversationAuthoringSubTrainingJobState" = rest_field( + name="trainingStatus", visibility=["read", "create", "update", "delete", "query"] + ) + """Represents the model training status. Required.""" + evaluation_status: Optional["_models.AnalyzeConversationAuthoringSubTrainingJobState"] = rest_field( + name="evaluationStatus", visibility=["read", "create", "update", "delete", "query"] + ) + """Represents model evaluation status.""" + estimated_end_date_time: Optional[datetime.datetime] = rest_field( + name="estimatedEndDateTime", visibility=["read", "create", "update", "delete", "query"], 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.AnalyzeConversationAuthoringSubTrainingJobState", + training_mode: Optional[Union[str, "_models.TrainingMode"]] = None, + evaluation_status: Optional["_models.AnalyzeConversationAuthoringSubTrainingJobState"] = 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: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringTrainingJobState(_model_base.Model): # pylint: disable=name-too-long + """Represents the state of a training job. + + Readonly variables are only populated by the server, and will be ignored when sending a request. + + + :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.conversations.authoring.models.JobStatus + :ivar warnings: The warnings that were encountered while executing the job. + :vartype warnings: list[~azure.ai.language.conversations.authoring.models.Warning] + :ivar errors: The errors encountered while executing the job. + :vartype errors: list[~azure.ai.language.conversations.authoring.models.Error] + :ivar result: Represents training tasks detailed result. Required. + :vartype result: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringTrainingJobResult + """ + + job_id: str = rest_field(name="jobId", visibility=["read"]) + """The job ID. Required.""" + created_date_time: datetime.datetime = rest_field( + name="createdDateTime", visibility=["read", "create", "update", "delete", "query"], format="rfc3339" + ) + """The creation date time of the job. Required.""" + last_updated_date_time: datetime.datetime = rest_field( + name="lastUpdatedDateTime", visibility=["read", "create", "update", "delete", "query"], format="rfc3339" + ) + """The last date time the job was updated. Required.""" + expiration_date_time: Optional[datetime.datetime] = rest_field( + name="expirationDateTime", visibility=["read", "create", "update", "delete", "query"], format="rfc3339" + ) + """The expiration date time of the job.""" + status: Union[str, "_models.JobStatus"] = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """The job status. Required. Known values are: \"notStarted\", \"running\", \"succeeded\", + \"failed\", \"cancelled\", \"cancelling\", and \"partiallyCompleted\".""" + warnings: Optional[List["_models.Warning"]] = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """The warnings that were encountered while executing the job.""" + errors: Optional[List["_models.Error"]] = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """The errors encountered while executing the job.""" + result: "_models.AnalyzeConversationAuthoringTrainingJobResult" = rest_field( + visibility=["read", "create", "update", "delete", "query"] + ) + """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.AnalyzeConversationAuthoringTrainingJobResult", + 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: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringUnassignDeploymentResourcesOptions( + _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", visibility=["read", "create", "update", "delete", "query"] + ) + """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: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringUtteranceEntitiesEvaluationResult(_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.conversations.authoring.models.AnalyzeConversationAuthoringUtteranceEntityEvaluationResult] + :ivar predicted_entities: Represents the predicted entity labels. Required. + :vartype predicted_entities: + list[~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringUtteranceEntityEvaluationResult] + """ + + expected_entities: List["_models.AnalyzeConversationAuthoringUtteranceEntityEvaluationResult"] = rest_field( + name="expectedEntities", visibility=["read", "create", "update", "delete", "query"] + ) + """Represents the expected entity labels. Required.""" + predicted_entities: List["_models.AnalyzeConversationAuthoringUtteranceEntityEvaluationResult"] = rest_field( + name="predictedEntities", visibility=["read", "create", "update", "delete", "query"] + ) + """Represents the predicted entity labels. Required.""" + + @overload + def __init__( + self, + *, + expected_entities: List["_models.AnalyzeConversationAuthoringUtteranceEntityEvaluationResult"], + predicted_entities: List["_models.AnalyzeConversationAuthoringUtteranceEntityEvaluationResult"], + ) -> None: ... + + @overload + def __init__(self, mapping: Mapping[str, Any]) -> None: + """ + :param mapping: raw JSON to initialize the model. + :type mapping: Mapping[str, Any] + """ + + def __init__(self, *args: Any, **kwargs: Any) -> None: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringUtteranceEntityEvaluationResult(_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(visibility=["read", "create", "update", "delete", "query"]) + """Represents the entity category. Required.""" + offset: int = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """Represents the entity offset index relative to the original text. Required.""" + length: int = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """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: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringUtteranceEvaluationResult(_model_base.Model): # pylint: disable=name-too-long + """Represents the evaluation result for an utterance. + + Readonly variables are only populated by the server, and will be ignored when sending a request. + + + :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.conversations.authoring.models.AnalyzeConversationAuthoringUtteranceEntitiesEvaluationResult + :ivar intents_result: Represents the intents results for the utterance. Required. + :vartype intents_result: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringUtteranceIntentsEvaluationResult + """ + + text: str = rest_field(visibility=["read"]) + """Represents the utterance text. Required.""" + language: str = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """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.AnalyzeConversationAuthoringUtteranceEntitiesEvaluationResult" = rest_field( + name="entitiesResult", visibility=["read", "create", "update", "delete", "query"] + ) + """Represents the entities results for the utterance. Required.""" + intents_result: "_models.AnalyzeConversationAuthoringUtteranceIntentsEvaluationResult" = rest_field( + name="intentsResult", visibility=["read", "create", "update", "delete", "query"] + ) + """Represents the intents results for the utterance. Required.""" + + @overload + def __init__( + self, + *, + language: str, + entities_result: "_models.AnalyzeConversationAuthoringUtteranceEntitiesEvaluationResult", + intents_result: "_models.AnalyzeConversationAuthoringUtteranceIntentsEvaluationResult", + ) -> None: ... + + @overload + def __init__(self, mapping: Mapping[str, Any]) -> None: + """ + :param mapping: raw JSON to initialize the model. + :type mapping: Mapping[str, Any] + """ + + def __init__(self, *args: Any, **kwargs: Any) -> None: + super().__init__(*args, **kwargs) + + +class AnalyzeConversationAuthoringUtteranceIntentsEvaluationResult(_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", visibility=["read", "create", "update", "delete", "query"]) + """Represents the utterance's expected intent. Required.""" + predicted_intent: str = rest_field( + name="predictedIntent", visibility=["read", "create", "update", "delete", "query"] + ) + """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: + 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.conversations.authoring.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.conversations.authoring.models.Error] + :ivar innererror: An object containing more specific information than the current object about + the error. + :vartype innererror: ~azure.ai.language.conversations.authoring.models.InnerErrorModel + """ + + code: Union[str, "_models.ErrorCode"] = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """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(visibility=["read", "create", "update", "delete", "query"]) + """A human-readable representation of the error. Required.""" + target: Optional[str] = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """The target of the error.""" + details: Optional[List["_models.Error"]] = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """An array of details about specific errors that led to this reported error.""" + innererror: Optional["_models.InnerErrorModel"] = rest_field( + visibility=["read", "create", "update", "delete", "query"] + ) + """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: + super().__init__(*args, **kwargs) + + +class ErrorResponse(_model_base.Model): + """Error response. + + All required parameters must be populated in order to send to server. + + :ivar error: The error object. Required. + :vartype error: ~azure.ai.language.conversations.authoring.models.Error + """ + + error: "_models.Error" = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """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: + super().__init__(*args, **kwargs) + + +class ExportedModelOptions(_model_base.Model): + """Represents the options for creating or replacing an exported model. + + All required parameters must be populated in order to send to server. + + :ivar trained_model_label: The trained model label. Required. + :vartype trained_model_label: str + """ + + trained_model_label: str = rest_field( + name="trainedModelLabel", visibility=["read", "create", "update", "delete", "query"] + ) + """The trained model label. Required.""" + + @overload + def __init__( + self, + *, + trained_model_label: 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: + 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.conversations.authoring.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.conversations.authoring.models.InnerErrorModel + """ + + code: Union[str, "_models.InnerErrorCode"] = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """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(visibility=["read", "create", "update", "delete", "query"]) + """Error message. Required.""" + details: Optional[Dict[str, str]] = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """Error details.""" + target: Optional[str] = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """Error target.""" + innererror: Optional["_models.InnerErrorModel"] = rest_field( + visibility=["read", "create", "update", "delete", "query"] + ) + """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: + 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(visibility=["read", "create", "update", "delete", "query"]) + """The warning code. Required.""" + message: str = rest_field(visibility=["read", "create", "update", "delete", "query"]) + """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: + super().__init__(*args, **kwargs) diff --git a/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/models/_patch.py b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/models/_patch.py new file mode 100644 index 000000000000..f7dd32510333 --- /dev/null +++ b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/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/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/operations/__init__.py b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/operations/__init__.py new file mode 100644 index 000000000000..b1edaad8b818 --- /dev/null +++ b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/operations/__init__.py @@ -0,0 +1,25 @@ +# 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. +# -------------------------------------------------------------------------- +# pylint: disable=wrong-import-position + +from typing import TYPE_CHECKING + +if TYPE_CHECKING: + from ._patch import * # pylint: disable=unused-wildcard-import + +from ._operations import AnalyzeConversationAuthoringOperations # type: ignore + +from ._patch import __all__ as _patch_all +from ._patch import * +from ._patch import patch_sdk as _patch_sdk + +__all__ = [ + "AnalyzeConversationAuthoringOperations", +] +__all__.extend([p for p in _patch_all if p not in __all__]) # pyright: ignore +_patch_sdk() diff --git a/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/operations/_operations.py b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/operations/_operations.py new file mode 100644 index 000000000000..445f19a7574f --- /dev/null +++ b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/operations/_operations.py @@ -0,0 +1,7078 @@ +# pylint: disable=line-too-long,useless-suppression,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 import PipelineClient +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 .._configuration import AuthoringClientConfiguration +from .._model_base import SdkJSONEncoder, _deserialize, _failsafe_deserialize +from .._serialization import Deserializer, 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_analyze_conversation_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", "2024-11-15-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_analyze_conversation_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", "2024-11-15-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_analyze_conversation_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", "2024-11-15-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_analyze_conversation_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", "2024-11-15-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_analyze_conversation_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", "2024-11-15-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_analyze_conversation_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", "2024-11-15-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_analyze_conversation_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", "2024-11-15-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_analyze_conversation_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", "2024-11-15-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_analyze_conversation_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", "2024-11-15-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_analyze_conversation_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", "2024-11-15-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_analyze_conversation_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", "2024-11-15-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_analyze_conversation_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", "2024-11-15-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_analyze_conversation_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", "2024-11-15-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_analyze_conversation_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", "2024-11-15-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_analyze_conversation_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", "2024-11-15-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_analyze_conversation_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", "2024-11-15-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_analyze_conversation_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", "2024-11-15-preview")) + accept = _headers.pop("Accept", "application/json") + + # Construct URL + _url = "/authoring/analyze-conversations/projects/{projectName}/deployments/{deploymentName}/delete-from-resources/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_analyze_conversation_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", "2024-11-15-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_analyze_conversation_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", "2024-11-15-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_analyze_conversation_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", "2024-11-15-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_analyze_conversation_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", "2024-11-15-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_analyze_conversation_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", "2024-11-15-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_analyze_conversation_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", "2024-11-15-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_analyze_conversation_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", "2024-11-15-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_analyze_conversation_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", "2024-11-15-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_analyze_conversation_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", "2024-11-15-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_analyze_conversation_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", "2024-11-15-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_analyze_conversation_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", "2024-11-15-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_analyze_conversation_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", "2024-11-15-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_analyze_conversation_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", "2024-11-15-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_analyze_conversation_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", "2024-11-15-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_analyze_conversation_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", "2024-11-15-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_analyze_conversation_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", "2024-11-15-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_analyze_conversation_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", "2024-11-15-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_analyze_conversation_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", "2024-11-15-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_analyze_conversation_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", "2024-11-15-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_analyze_conversation_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", "2024-11-15-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_analyze_conversation_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", "2024-11-15-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_analyze_conversation_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", "2024-11-15-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_analyze_conversation_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", "2024-11-15-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_analyze_conversation_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", "2024-11-15-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_analyze_conversation_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", "2024-11-15-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_analyze_conversation_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", "2024-11-15-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) + + +def build_analyze_conversation_authoring_get_exported_model_request( # pylint: disable=name-too-long + project_name: str, exported_model_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", "2024-11-15-preview")) + accept = _headers.pop("Accept", "application/json") + + # Construct URL + _url = "/authoring/analyze-conversations/projects/{projectName}/exported-models/{exportedModelName}" + path_format_arguments = { + "projectName": _SERIALIZER.url("project_name", project_name, "str"), + "exportedModelName": _SERIALIZER.url("exported_model_name", exported_model_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_analyze_conversation_authoring_list_exported_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", "2024-11-15-preview")) + accept = _headers.pop("Accept", "application/json") + + # Construct URL + _url = "/authoring/analyze-conversations/projects/{projectName}/exported-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_analyze_conversation_authoring_delete_exported_model_request( # pylint: disable=name-too-long + project_name: str, exported_model_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", "2024-11-15-preview")) + accept = _headers.pop("Accept", "application/json") + + # Construct URL + _url = "/authoring/analyze-conversations/projects/{projectName}/exported-models/{exportedModelName}" + path_format_arguments = { + "projectName": _SERIALIZER.url("project_name", project_name, "str"), + "exportedModelName": _SERIALIZER.url("exported_model_name", exported_model_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_analyze_conversation_authoring_create_or_update_exported_model_request( # pylint: disable=name-too-long + project_name: str, exported_model_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", "2024-11-15-preview")) + accept = _headers.pop("Accept", "application/json") + + # Construct URL + _url = "/authoring/analyze-conversations/projects/{projectName}/exported-models/{exportedModelName}" + path_format_arguments = { + "projectName": _SERIALIZER.url("project_name", project_name, "str"), + "exportedModelName": _SERIALIZER.url("exported_model_name", exported_model_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_analyze_conversation_authoring_get_exported_model_job_status_request( # pylint: disable=name-too-long + project_name: str, exported_model_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", "2024-11-15-preview")) + accept = _headers.pop("Accept", "application/json") + + # Construct URL + _url = "/authoring/analyze-conversations/projects/{projectName}/exported-models/{exportedModelName}/jobs/{jobId}" + path_format_arguments = { + "projectName": _SERIALIZER.url("project_name", project_name, "str"), + "exportedModelName": _SERIALIZER.url("exported_model_name", exported_model_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) + + +class AnalyzeConversationAuthoringOperations: # pylint: disable=too-many-public-methods + """ + .. warning:: + **DO NOT** instantiate this class directly. + + Instead, you should access the following operations through + :class:`~azure.ai.language.conversations.authoring.AuthoringClient`'s + :attr:`analyze_conversation_authoring` attribute. + """ + + def __init__(self, *args, **kwargs): + input_args = list(args) + self._client: PipelineClient = input_args.pop(0) if input_args else kwargs.pop("client") + self._config: AuthoringClientConfiguration = input_args.pop(0) if input_args else kwargs.pop("config") + self._serialize: Serializer = input_args.pop(0) if input_args else kwargs.pop("serializer") + self._deserialize: Deserializer = 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.AnalyzeConversationAuthoringProjectMetadata"]: + """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 AnalyzeConversationAuthoringProjectMetadata + :rtype: + ~azure.core.paging.ItemPaged[~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringProjectMetadata] + :raises ~azure.core.exceptions.HttpResponseError: + """ + _headers = kwargs.pop("headers", {}) or {} + _params = kwargs.pop("params", {}) or {} + + maxpagesize = kwargs.pop("maxpagesize", None) + cls: ClsType[List[_models.AnalyzeConversationAuthoringProjectMetadata]] = 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_analyze_conversation_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", skip_quote=True + ), + } + _request.url = self._client.format_url(_request.url, **path_format_arguments) + + else: + # make call to next link with the client's api-version + _parsed_next_link = urllib.parse.urlparse(next_link) + _next_request_params = case_insensitive_dict( + { + key: [urllib.parse.quote(v) for v in value] + for key, value in urllib.parse.parse_qs(_parsed_next_link.query).items() + } + ) + _next_request_params["api-version"] = self._config.api_version + _request = HttpRequest( + "GET", urllib.parse.urljoin(next_link, _parsed_next_link.path), params=_next_request_params + ) + path_format_arguments = { + "Endpoint": self._serialize.url( + "self._config.endpoint", self._config.endpoint, "str", skip_quote=True + ), + } + _request.url = self._client.format_url(_request.url, **path_format_arguments) + + return _request + + def extract_data(pipeline_response): + deserialized = pipeline_response.http_response.json() + list_of_elem = _deserialize( + List[_models.AnalyzeConversationAuthoringProjectMetadata], deserialized["value"] + ) + if cls: + list_of_elem = cls(list_of_elem) # type: ignore + return deserialized.get("nextLink") or None, iter(list_of_elem) + + def get_next(next_link=None): + _request = prepare_request(next_link) + + _stream = False + pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access + _request, stream=_stream, **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = _failsafe_deserialize(_models.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.AnalyzeConversationAuthoringProjectMetadata: + """Gets the details of a project. + + :param project_name: The new project name. Required. + :type project_name: str + :return: AnalyzeConversationAuthoringProjectMetadata. The + AnalyzeConversationAuthoringProjectMetadata is compatible with MutableMapping + :rtype: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringProjectMetadata + :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.AnalyzeConversationAuthoringProjectMetadata] = kwargs.pop("cls", None) + + _request = build_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_deserialize(_models.ErrorResponse, response.json()) + raise HttpResponseError(response=response, model=error) + + if _stream: + deserialized = response.iter_bytes() + else: + deserialized = _deserialize(_models.AnalyzeConversationAuthoringProjectMetadata, 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.AnalyzeConversationAuthoringCreateProjectOptions, + *, + content_type: str = "application/merge-patch+json", + **kwargs: Any + ) -> _models.AnalyzeConversationAuthoringProjectMetadata: + """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.conversations.authoring.models.AnalyzeConversationAuthoringCreateProjectOptions + :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: AnalyzeConversationAuthoringProjectMetadata. The + AnalyzeConversationAuthoringProjectMetadata is compatible with MutableMapping + :rtype: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringProjectMetadata + :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.AnalyzeConversationAuthoringProjectMetadata: + """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: AnalyzeConversationAuthoringProjectMetadata. The + AnalyzeConversationAuthoringProjectMetadata is compatible with MutableMapping + :rtype: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringProjectMetadata + :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.AnalyzeConversationAuthoringProjectMetadata: + """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: AnalyzeConversationAuthoringProjectMetadata. The + AnalyzeConversationAuthoringProjectMetadata is compatible with MutableMapping + :rtype: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringProjectMetadata + :raises ~azure.core.exceptions.HttpResponseError: + """ + + @distributed_trace + def create_project( + self, + project_name: str, + body: Union[_models.AnalyzeConversationAuthoringCreateProjectOptions, JSON, IO[bytes]], + **kwargs: Any + ) -> _models.AnalyzeConversationAuthoringProjectMetadata: + """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: + AnalyzeConversationAuthoringCreateProjectOptions, JSON, IO[bytes] Required. + :type body: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringCreateProjectOptions + or JSON or IO[bytes] + :return: AnalyzeConversationAuthoringProjectMetadata. The + AnalyzeConversationAuthoringProjectMetadata is compatible with MutableMapping + :rtype: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringProjectMetadata + :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.AnalyzeConversationAuthoringProjectMetadata] = 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_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_deserialize(_models.ErrorResponse, response.json()) + raise HttpResponseError(response=response, model=error) + + if _stream: + deserialized = response.iter_bytes() + else: + deserialized = _deserialize(_models.AnalyzeConversationAuthoringProjectMetadata, 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_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_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", skip_quote=True), + } + + if polling is True: + polling_method: PollingMethod = cast( + PollingMethod, LROBasePolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs) + ) + elif polling is False: + polling_method = cast(PollingMethod, NoPolling()) + else: + polling_method = polling + if cont_token: + return LROPoller[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, + *, + 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.AnalyzeConversationAuthoringCopyProjectOptions: + """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.conversations.authoring.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: AnalyzeConversationAuthoringCopyProjectOptions. The + AnalyzeConversationAuthoringCopyProjectOptions is compatible with MutableMapping + :rtype: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringCopyProjectOptions + :raises ~azure.core.exceptions.HttpResponseError: + """ + + @overload + def copy_project_authorization( + self, project_name: str, body: JSON, *, content_type: str = "application/json", **kwargs: Any + ) -> _models.AnalyzeConversationAuthoringCopyProjectOptions: + """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: AnalyzeConversationAuthoringCopyProjectOptions. The + AnalyzeConversationAuthoringCopyProjectOptions is compatible with MutableMapping + :rtype: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringCopyProjectOptions + :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.AnalyzeConversationAuthoringCopyProjectOptions: + """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: AnalyzeConversationAuthoringCopyProjectOptions. The + AnalyzeConversationAuthoringCopyProjectOptions is compatible with MutableMapping + :rtype: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringCopyProjectOptions + :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.AnalyzeConversationAuthoringCopyProjectOptions: + """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.conversations.authoring.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: AnalyzeConversationAuthoringCopyProjectOptions. The + AnalyzeConversationAuthoringCopyProjectOptions is compatible with MutableMapping + :rtype: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringCopyProjectOptions + :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.AnalyzeConversationAuthoringCopyProjectOptions] = 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_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_deserialize(_models.ErrorResponse, response.json()) + raise HttpResponseError(response=response, model=error) + + if _stream: + deserialized = response.iter_bytes() + else: + deserialized = _deserialize(_models.AnalyzeConversationAuthoringCopyProjectOptions, 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.AnalyzeConversationAuthoringCopyProjectOptions, 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_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_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.AnalyzeConversationAuthoringCopyProjectOptions, + *, + 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.conversations.authoring.models.AnalyzeConversationAuthoringCopyProjectOptions + :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.AnalyzeConversationAuthoringCopyProjectOptions, 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: + AnalyzeConversationAuthoringCopyProjectOptions, JSON, IO[bytes] Required. + :type body: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringCopyProjectOptions + 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", skip_quote=True), + } + + if polling is True: + polling_method: PollingMethod = cast( + PollingMethod, LROBasePolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs) + ) + elif polling is False: + polling_method = cast(PollingMethod, NoPolling()) + else: + polling_method = polling + if cont_token: + return LROPoller[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_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_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.conversations.authoring.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.conversations.authoring.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", skip_quote=True), + } + + if polling is True: + polling_method: PollingMethod = cast( + PollingMethod, LROBasePolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs) + ) + elif polling is False: + polling_method = cast(PollingMethod, NoPolling()) + else: + polling_method = polling + if cont_token: + return LROPoller[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.AnalyzeConversationAuthoringExportedProject, 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_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_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.AnalyzeConversationAuthoringExportedProject, + *, + 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.conversations.authoring.models.AnalyzeConversationAuthoringExportedProject + :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.conversations.authoring.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.conversations.authoring.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.conversations.authoring.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.AnalyzeConversationAuthoringExportedProject, 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: + AnalyzeConversationAuthoringExportedProject, JSON, IO[bytes] Required. + :type body: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringExportedProject + 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.conversations.authoring.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", skip_quote=True), + } + + if polling is True: + polling_method: PollingMethod = cast( + PollingMethod, LROBasePolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs) + ) + elif polling is False: + polling_method = cast(PollingMethod, NoPolling()) + else: + polling_method = polling + if cont_token: + return LROPoller[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.AnalyzeConversationAuthoringTrainingJobOptions, 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_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_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.AnalyzeConversationAuthoringTrainingJobOptions, + *, + content_type: str = "application/json", + **kwargs: Any + ) -> LROPoller[_models.AnalyzeConversationAuthoringTrainingJobResult]: + """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.conversations.authoring.models.AnalyzeConversationAuthoringTrainingJobOptions + :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 AnalyzeConversationAuthoringTrainingJobResult. + The AnalyzeConversationAuthoringTrainingJobResult is compatible with MutableMapping + :rtype: + ~azure.core.polling.LROPoller[~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringTrainingJobResult] + :raises ~azure.core.exceptions.HttpResponseError: + """ + + @overload + def begin_train( + self, project_name: str, body: JSON, *, content_type: str = "application/json", **kwargs: Any + ) -> LROPoller[_models.AnalyzeConversationAuthoringTrainingJobResult]: + """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 AnalyzeConversationAuthoringTrainingJobResult. + The AnalyzeConversationAuthoringTrainingJobResult is compatible with MutableMapping + :rtype: + ~azure.core.polling.LROPoller[~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringTrainingJobResult] + :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.AnalyzeConversationAuthoringTrainingJobResult]: + """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 AnalyzeConversationAuthoringTrainingJobResult. + The AnalyzeConversationAuthoringTrainingJobResult is compatible with MutableMapping + :rtype: + ~azure.core.polling.LROPoller[~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringTrainingJobResult] + :raises ~azure.core.exceptions.HttpResponseError: + """ + + @distributed_trace + def begin_train( + self, + project_name: str, + body: Union[_models.AnalyzeConversationAuthoringTrainingJobOptions, JSON, IO[bytes]], + **kwargs: Any + ) -> LROPoller[_models.AnalyzeConversationAuthoringTrainingJobResult]: + """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: + AnalyzeConversationAuthoringTrainingJobOptions, JSON, IO[bytes] Required. + :type body: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringTrainingJobOptions + or JSON or IO[bytes] + :return: An instance of LROPoller that returns AnalyzeConversationAuthoringTrainingJobResult. + The AnalyzeConversationAuthoringTrainingJobResult is compatible with MutableMapping + :rtype: + ~azure.core.polling.LROPoller[~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringTrainingJobResult] + :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.AnalyzeConversationAuthoringTrainingJobResult] = 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.AnalyzeConversationAuthoringTrainingJobResult, 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", skip_quote=True), + } + + if polling is True: + polling_method: PollingMethod = cast( + PollingMethod, LROBasePolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs) + ) + elif polling is False: + polling_method = cast(PollingMethod, NoPolling()) + else: + polling_method = polling + if cont_token: + return LROPoller[_models.AnalyzeConversationAuthoringTrainingJobResult].from_continuation_token( + polling_method=polling_method, + continuation_token=cont_token, + client=self._client, + deserialization_callback=get_long_running_output, + ) + return LROPoller[_models.AnalyzeConversationAuthoringTrainingJobResult]( + 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.AnalyzeConversationAuthoringCopyProjectJobState: + """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: AnalyzeConversationAuthoringCopyProjectJobState. The + AnalyzeConversationAuthoringCopyProjectJobState is compatible with MutableMapping + :rtype: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringCopyProjectJobState + :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.AnalyzeConversationAuthoringCopyProjectJobState] = kwargs.pop("cls", None) + + _request = build_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_deserialize(_models.ErrorResponse, response.json()) + raise HttpResponseError(response=response, model=error) + + if _stream: + deserialized = response.iter_bytes() + else: + deserialized = _deserialize(_models.AnalyzeConversationAuthoringCopyProjectJobState, 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.AnalyzeConversationAuthoringProjectDeployment"]: + """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 AnalyzeConversationAuthoringProjectDeployment + :rtype: + ~azure.core.paging.ItemPaged[~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringProjectDeployment] + :raises ~azure.core.exceptions.HttpResponseError: + """ + _headers = kwargs.pop("headers", {}) or {} + _params = kwargs.pop("params", {}) or {} + + maxpagesize = kwargs.pop("maxpagesize", None) + cls: ClsType[List[_models.AnalyzeConversationAuthoringProjectDeployment]] = 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_analyze_conversation_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", skip_quote=True + ), + } + _request.url = self._client.format_url(_request.url, **path_format_arguments) + + else: + # make call to next link with the client's api-version + _parsed_next_link = urllib.parse.urlparse(next_link) + _next_request_params = case_insensitive_dict( + { + key: [urllib.parse.quote(v) for v in value] + for key, value in urllib.parse.parse_qs(_parsed_next_link.query).items() + } + ) + _next_request_params["api-version"] = self._config.api_version + _request = HttpRequest( + "GET", urllib.parse.urljoin(next_link, _parsed_next_link.path), params=_next_request_params + ) + path_format_arguments = { + "Endpoint": self._serialize.url( + "self._config.endpoint", self._config.endpoint, "str", skip_quote=True + ), + } + _request.url = self._client.format_url(_request.url, **path_format_arguments) + + return _request + + def extract_data(pipeline_response): + deserialized = pipeline_response.http_response.json() + list_of_elem = _deserialize( + List[_models.AnalyzeConversationAuthoringProjectDeployment], deserialized["value"] + ) + if cls: + list_of_elem = cls(list_of_elem) # type: ignore + return deserialized.get("nextLink") or None, iter(list_of_elem) + + def get_next(next_link=None): + _request = prepare_request(next_link) + + _stream = False + pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access + _request, stream=_stream, **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = _failsafe_deserialize(_models.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.AnalyzeConversationAuthoringSwapDeploymentsOptions, 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_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_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.AnalyzeConversationAuthoringSwapDeploymentsOptions, + *, + 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.conversations.authoring.models.AnalyzeConversationAuthoringSwapDeploymentsOptions + :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.AnalyzeConversationAuthoringSwapDeploymentsOptions, 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: + AnalyzeConversationAuthoringSwapDeploymentsOptions, JSON, IO[bytes] Required. + :type body: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringSwapDeploymentsOptions + 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", skip_quote=True), + } + + if polling is True: + polling_method: PollingMethod = cast( + PollingMethod, LROBasePolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs) + ) + elif polling is False: + polling_method = cast(PollingMethod, NoPolling()) + else: + polling_method = polling + if cont_token: + return LROPoller[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.AnalyzeConversationAuthoringProjectDeployment: + """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: AnalyzeConversationAuthoringProjectDeployment. The + AnalyzeConversationAuthoringProjectDeployment is compatible with MutableMapping + :rtype: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringProjectDeployment + :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.AnalyzeConversationAuthoringProjectDeployment] = kwargs.pop("cls", None) + + _request = build_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_deserialize(_models.ErrorResponse, response.json()) + raise HttpResponseError(response=response, model=error) + + if _stream: + deserialized = response.iter_bytes() + else: + deserialized = _deserialize(_models.AnalyzeConversationAuthoringProjectDeployment, 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.AnalyzeConversationAuthoringCreateDeploymentOptions, 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_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_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.AnalyzeConversationAuthoringCreateDeploymentOptions, + *, + 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.conversations.authoring.models.AnalyzeConversationAuthoringCreateDeploymentOptions + :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.AnalyzeConversationAuthoringCreateDeploymentOptions, 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: + AnalyzeConversationAuthoringCreateDeploymentOptions, JSON, IO[bytes] Required. + :type body: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringCreateDeploymentOptions + 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", skip_quote=True), + } + + if polling is True: + polling_method: PollingMethod = cast( + PollingMethod, LROBasePolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs) + ) + elif polling is False: + polling_method = cast(PollingMethod, NoPolling()) + else: + polling_method = polling + if cont_token: + return LROPoller[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_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_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", skip_quote=True), + } + + if polling is True: + polling_method: PollingMethod = cast( + PollingMethod, LROBasePolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs) + ) + elif polling is False: + polling_method = cast(PollingMethod, NoPolling()) + else: + polling_method = polling + if cont_token: + return LROPoller[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"] + }, + ) + def _delete_deployment_from_resources_initial( # pylint: disable=name-too-long + self, + project_name: str, + deployment_name: str, + body: Union[_models.AnalyzeConversationAuthoringDeleteDeploymentOptions, 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_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_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.AnalyzeConversationAuthoringDeleteDeploymentOptions, + *, + 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.conversations.authoring.models.AnalyzeConversationAuthoringDeleteDeploymentOptions + :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.AnalyzeConversationAuthoringDeleteDeploymentOptions, 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: + AnalyzeConversationAuthoringDeleteDeploymentOptions, JSON, IO[bytes] Required. + :type body: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringDeleteDeploymentOptions + 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", skip_quote=True), + } + + if polling is True: + polling_method: PollingMethod = cast( + PollingMethod, LROBasePolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs) + ) + elif polling is False: + polling_method = cast(PollingMethod, NoPolling()) + else: + polling_method = polling + if cont_token: + return LROPoller[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"]}, + ) + 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.AnalyzeConversationAuthoringDeploymentDeleteFromResourcesJobState: + """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: AnalyzeConversationAuthoringDeploymentDeleteFromResourcesJobState. The + AnalyzeConversationAuthoringDeploymentDeleteFromResourcesJobState is compatible with + MutableMapping + :rtype: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringDeploymentDeleteFromResourcesJobState + :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.AnalyzeConversationAuthoringDeploymentDeleteFromResourcesJobState] = kwargs.pop( + "cls", None + ) + + _request = build_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_deserialize(_models.ErrorResponse, response.json()) + raise HttpResponseError(response=response, model=error) + + if _stream: + deserialized = response.iter_bytes() + else: + deserialized = _deserialize( + _models.AnalyzeConversationAuthoringDeploymentDeleteFromResourcesJobState, 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.AnalyzeConversationAuthoringDeploymentJobState: + """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: AnalyzeConversationAuthoringDeploymentJobState. The + AnalyzeConversationAuthoringDeploymentJobState is compatible with MutableMapping + :rtype: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringDeploymentJobState + :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.AnalyzeConversationAuthoringDeploymentJobState] = kwargs.pop("cls", None) + + _request = build_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_deserialize(_models.ErrorResponse, response.json()) + raise HttpResponseError(response=response, model=error) + + if _stream: + deserialized = response.iter_bytes() + else: + deserialized = _deserialize(_models.AnalyzeConversationAuthoringDeploymentJobState, 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.AnalyzeConversationAuthoringSwapDeploymentsJobState: + """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: AnalyzeConversationAuthoringSwapDeploymentsJobState. The + AnalyzeConversationAuthoringSwapDeploymentsJobState is compatible with MutableMapping + :rtype: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringSwapDeploymentsJobState + :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.AnalyzeConversationAuthoringSwapDeploymentsJobState] = kwargs.pop("cls", None) + + _request = build_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_deserialize(_models.ErrorResponse, response.json()) + raise HttpResponseError(response=response, model=error) + + if _stream: + deserialized = response.iter_bytes() + else: + deserialized = _deserialize(_models.AnalyzeConversationAuthoringSwapDeploymentsJobState, 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.AnalyzeConversationAuthoringExportProjectJobState: + """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: AnalyzeConversationAuthoringExportProjectJobState. The + AnalyzeConversationAuthoringExportProjectJobState is compatible with MutableMapping + :rtype: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringExportProjectJobState + :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.AnalyzeConversationAuthoringExportProjectJobState] = kwargs.pop("cls", None) + + _request = build_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_deserialize(_models.ErrorResponse, response.json()) + raise HttpResponseError(response=response, model=error) + + if _stream: + deserialized = response.iter_bytes() + else: + deserialized = _deserialize(_models.AnalyzeConversationAuthoringExportProjectJobState, 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.AnalyzeConversationAuthoringImportProjectJobState: + """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: AnalyzeConversationAuthoringImportProjectJobState. The + AnalyzeConversationAuthoringImportProjectJobState is compatible with MutableMapping + :rtype: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringImportProjectJobState + :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.AnalyzeConversationAuthoringImportProjectJobState] = kwargs.pop("cls", None) + + _request = build_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_deserialize(_models.ErrorResponse, response.json()) + raise HttpResponseError(response=response, model=error) + + if _stream: + deserialized = response.iter_bytes() + else: + deserialized = _deserialize(_models.AnalyzeConversationAuthoringImportProjectJobState, 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.AnalyzeConversationAuthoringProjectTrainedModel"]: + """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 AnalyzeConversationAuthoringProjectTrainedModel + :rtype: + ~azure.core.paging.ItemPaged[~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringProjectTrainedModel] + :raises ~azure.core.exceptions.HttpResponseError: + """ + _headers = kwargs.pop("headers", {}) or {} + _params = kwargs.pop("params", {}) or {} + + maxpagesize = kwargs.pop("maxpagesize", None) + cls: ClsType[List[_models.AnalyzeConversationAuthoringProjectTrainedModel]] = 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_analyze_conversation_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", skip_quote=True + ), + } + _request.url = self._client.format_url(_request.url, **path_format_arguments) + + else: + # make call to next link with the client's api-version + _parsed_next_link = urllib.parse.urlparse(next_link) + _next_request_params = case_insensitive_dict( + { + key: [urllib.parse.quote(v) for v in value] + for key, value in urllib.parse.parse_qs(_parsed_next_link.query).items() + } + ) + _next_request_params["api-version"] = self._config.api_version + _request = HttpRequest( + "GET", urllib.parse.urljoin(next_link, _parsed_next_link.path), params=_next_request_params + ) + path_format_arguments = { + "Endpoint": self._serialize.url( + "self._config.endpoint", self._config.endpoint, "str", skip_quote=True + ), + } + _request.url = self._client.format_url(_request.url, **path_format_arguments) + + return _request + + def extract_data(pipeline_response): + deserialized = pipeline_response.http_response.json() + list_of_elem = _deserialize( + List[_models.AnalyzeConversationAuthoringProjectTrainedModel], deserialized["value"] + ) + if cls: + list_of_elem = cls(list_of_elem) # type: ignore + return deserialized.get("nextLink") or None, iter(list_of_elem) + + def get_next(next_link=None): + _request = prepare_request(next_link) + + _stream = False + pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access + _request, stream=_stream, **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = _failsafe_deserialize(_models.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.AnalyzeConversationAuthoringProjectTrainedModel: + """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: AnalyzeConversationAuthoringProjectTrainedModel. The + AnalyzeConversationAuthoringProjectTrainedModel is compatible with MutableMapping + :rtype: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringProjectTrainedModel + :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.AnalyzeConversationAuthoringProjectTrainedModel] = kwargs.pop("cls", None) + + _request = build_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_deserialize(_models.ErrorResponse, response.json()) + raise HttpResponseError(response=response, model=error) + + if _stream: + deserialized = response.iter_bytes() + else: + deserialized = _deserialize(_models.AnalyzeConversationAuthoringProjectTrainedModel, 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_analyze_conversation_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", skip_quote=True), + } + _request.url = self._client.format_url(_request.url, **path_format_arguments) + + _stream = False + pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access + _request, stream=_stream, **kwargs + ) + + response = pipeline_response.http_response + + if response.status_code not in [204]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = _failsafe_deserialize(_models.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.AnalyzeConversationAuthoringEvaluationOptions, 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_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_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.AnalyzeConversationAuthoringEvaluationOptions, + *, + content_type: str = "application/json", + **kwargs: Any + ) -> LROPoller[_models.AnalyzeConversationAuthoringEvaluationJobResult]: + """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.conversations.authoring.models.AnalyzeConversationAuthoringEvaluationOptions + :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 AnalyzeConversationAuthoringEvaluationJobResult. + The AnalyzeConversationAuthoringEvaluationJobResult is compatible with MutableMapping + :rtype: + ~azure.core.polling.LROPoller[~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringEvaluationJobResult] + :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.AnalyzeConversationAuthoringEvaluationJobResult]: + """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 AnalyzeConversationAuthoringEvaluationJobResult. + The AnalyzeConversationAuthoringEvaluationJobResult is compatible with MutableMapping + :rtype: + ~azure.core.polling.LROPoller[~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringEvaluationJobResult] + :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.AnalyzeConversationAuthoringEvaluationJobResult]: + """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 AnalyzeConversationAuthoringEvaluationJobResult. + The AnalyzeConversationAuthoringEvaluationJobResult is compatible with MutableMapping + :rtype: + ~azure.core.polling.LROPoller[~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringEvaluationJobResult] + :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.AnalyzeConversationAuthoringEvaluationOptions, JSON, IO[bytes]], + **kwargs: Any + ) -> LROPoller[_models.AnalyzeConversationAuthoringEvaluationJobResult]: + """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: + AnalyzeConversationAuthoringEvaluationOptions, JSON, IO[bytes] Required. + :type body: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringEvaluationOptions + or JSON or IO[bytes] + :return: An instance of LROPoller that returns AnalyzeConversationAuthoringEvaluationJobResult. + The AnalyzeConversationAuthoringEvaluationJobResult is compatible with MutableMapping + :rtype: + ~azure.core.polling.LROPoller[~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringEvaluationJobResult] + :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.AnalyzeConversationAuthoringEvaluationJobResult] = 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.AnalyzeConversationAuthoringEvaluationJobResult, 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", skip_quote=True), + } + + if polling is True: + polling_method: PollingMethod = cast( + PollingMethod, LROBasePolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs) + ) + elif polling is False: + polling_method = cast(PollingMethod, NoPolling()) + else: + polling_method = polling + if cont_token: + return LROPoller[_models.AnalyzeConversationAuthoringEvaluationJobResult].from_continuation_token( + polling_method=polling_method, + continuation_token=cont_token, + client=self._client, + deserialization_callback=get_long_running_output, + ) + return LROPoller[_models.AnalyzeConversationAuthoringEvaluationJobResult]( + 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_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_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", skip_quote=True), + } + + if polling is True: + polling_method: PollingMethod = cast( + PollingMethod, LROBasePolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs) + ) + elif polling is False: + polling_method = cast(PollingMethod, NoPolling()) + else: + polling_method = polling + if cont_token: + return LROPoller[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.AnalyzeConversationAuthoringEvaluationJobState: + """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: AnalyzeConversationAuthoringEvaluationJobState. The + AnalyzeConversationAuthoringEvaluationJobState is compatible with MutableMapping + :rtype: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringEvaluationJobState + :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.AnalyzeConversationAuthoringEvaluationJobState] = kwargs.pop("cls", None) + + _request = build_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_deserialize(_models.ErrorResponse, response.json()) + raise HttpResponseError(response=response, model=error) + + if _stream: + deserialized = response.iter_bytes() + else: + deserialized = _deserialize(_models.AnalyzeConversationAuthoringEvaluationJobState, 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.AnalyzeConversationAuthoringUtteranceEvaluationResult"]: + """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.conversations.authoring.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 AnalyzeConversationAuthoringUtteranceEvaluationResult + :rtype: + ~azure.core.paging.ItemPaged[~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringUtteranceEvaluationResult] + :raises ~azure.core.exceptions.HttpResponseError: + """ + _headers = kwargs.pop("headers", {}) or {} + _params = kwargs.pop("params", {}) or {} + + maxpagesize = kwargs.pop("maxpagesize", None) + cls: ClsType[List[_models.AnalyzeConversationAuthoringUtteranceEvaluationResult]] = 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_analyze_conversation_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", skip_quote=True + ), + } + _request.url = self._client.format_url(_request.url, **path_format_arguments) + + else: + # make call to next link with the client's api-version + _parsed_next_link = urllib.parse.urlparse(next_link) + _next_request_params = case_insensitive_dict( + { + key: [urllib.parse.quote(v) for v in value] + for key, value in urllib.parse.parse_qs(_parsed_next_link.query).items() + } + ) + _next_request_params["api-version"] = self._config.api_version + _request = HttpRequest( + "GET", urllib.parse.urljoin(next_link, _parsed_next_link.path), params=_next_request_params + ) + path_format_arguments = { + "Endpoint": self._serialize.url( + "self._config.endpoint", self._config.endpoint, "str", skip_quote=True + ), + } + _request.url = self._client.format_url(_request.url, **path_format_arguments) + + return _request + + def extract_data(pipeline_response): + deserialized = pipeline_response.http_response.json() + list_of_elem = _deserialize( + List[_models.AnalyzeConversationAuthoringUtteranceEvaluationResult], deserialized["value"] + ) + if cls: + list_of_elem = cls(list_of_elem) # type: ignore + return deserialized.get("nextLink") or None, iter(list_of_elem) + + def get_next(next_link=None): + _request = prepare_request(next_link) + + _stream = False + pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access + _request, stream=_stream, **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = _failsafe_deserialize(_models.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.AnalyzeConversationAuthoringEvaluationSummary: + """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: AnalyzeConversationAuthoringEvaluationSummary. The + AnalyzeConversationAuthoringEvaluationSummary is compatible with MutableMapping + :rtype: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringEvaluationSummary + :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.AnalyzeConversationAuthoringEvaluationSummary] = kwargs.pop("cls", None) + + _request = build_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_deserialize(_models.ErrorResponse, response.json()) + raise HttpResponseError(response=response, model=error) + + if _stream: + deserialized = response.iter_bytes() + else: + deserialized = _deserialize(_models.AnalyzeConversationAuthoringEvaluationSummary, 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.AnalyzeConversationAuthoringLoadSnapshotJobState: + """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: AnalyzeConversationAuthoringLoadSnapshotJobState. The + AnalyzeConversationAuthoringLoadSnapshotJobState is compatible with MutableMapping + :rtype: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringLoadSnapshotJobState + :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.AnalyzeConversationAuthoringLoadSnapshotJobState] = kwargs.pop("cls", None) + + _request = build_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_deserialize(_models.ErrorResponse, response.json()) + raise HttpResponseError(response=response, model=error) + + if _stream: + deserialized = response.iter_bytes() + else: + deserialized = _deserialize(_models.AnalyzeConversationAuthoringLoadSnapshotJobState, 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.AnalyzeConversationAuthoringAssignedDeploymentResource"]: + """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 AnalyzeConversationAuthoringAssignedDeploymentResource + :rtype: + ~azure.core.paging.ItemPaged[~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringAssignedDeploymentResource] + :raises ~azure.core.exceptions.HttpResponseError: + """ + _headers = kwargs.pop("headers", {}) or {} + _params = kwargs.pop("params", {}) or {} + + maxpagesize = kwargs.pop("maxpagesize", None) + cls: ClsType[List[_models.AnalyzeConversationAuthoringAssignedDeploymentResource]] = 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_analyze_conversation_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", skip_quote=True + ), + } + _request.url = self._client.format_url(_request.url, **path_format_arguments) + + else: + # make call to next link with the client's api-version + _parsed_next_link = urllib.parse.urlparse(next_link) + _next_request_params = case_insensitive_dict( + { + key: [urllib.parse.quote(v) for v in value] + for key, value in urllib.parse.parse_qs(_parsed_next_link.query).items() + } + ) + _next_request_params["api-version"] = self._config.api_version + _request = HttpRequest( + "GET", urllib.parse.urljoin(next_link, _parsed_next_link.path), params=_next_request_params + ) + path_format_arguments = { + "Endpoint": self._serialize.url( + "self._config.endpoint", self._config.endpoint, "str", skip_quote=True + ), + } + _request.url = self._client.format_url(_request.url, **path_format_arguments) + + return _request + + def extract_data(pipeline_response): + deserialized = pipeline_response.http_response.json() + list_of_elem = _deserialize( + List[_models.AnalyzeConversationAuthoringAssignedDeploymentResource], deserialized["value"] + ) + if cls: + list_of_elem = cls(list_of_elem) # type: ignore + return deserialized.get("nextLink") or None, iter(list_of_elem) + + def get_next(next_link=None): + _request = prepare_request(next_link) + + _stream = False + pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access + _request, stream=_stream, **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = _failsafe_deserialize(_models.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.AnalyzeConversationAuthoringAssignDeploymentResourcesOptions, 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_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_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.AnalyzeConversationAuthoringAssignDeploymentResourcesOptions, + *, + 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: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringAssignDeploymentResourcesOptions + :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.AnalyzeConversationAuthoringAssignDeploymentResourcesOptions, JSON, IO[bytes]], + **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. Is one of the following types: + AnalyzeConversationAuthoringAssignDeploymentResourcesOptions, JSON, IO[bytes] Required. + :type body: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringAssignDeploymentResourcesOptions + 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", skip_quote=True), + } + + if polling is True: + polling_method: PollingMethod = cast( + PollingMethod, LROBasePolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs) + ) + elif polling is False: + polling_method = cast(PollingMethod, NoPolling()) + else: + polling_method = polling + if cont_token: + return LROPoller[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.AnalyzeConversationAuthoringUnassignDeploymentResourcesOptions, 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_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_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.AnalyzeConversationAuthoringUnassignDeploymentResourcesOptions, + *, + 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: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringUnassignDeploymentResourcesOptions + :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.AnalyzeConversationAuthoringUnassignDeploymentResourcesOptions, JSON, IO[bytes]], + **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. Is one of the following + types: AnalyzeConversationAuthoringUnassignDeploymentResourcesOptions, JSON, IO[bytes] + Required. + :type body: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringUnassignDeploymentResourcesOptions + 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", skip_quote=True), + } + + if polling is True: + polling_method: PollingMethod = cast( + PollingMethod, LROBasePolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs) + ) + elif polling is False: + polling_method = cast(PollingMethod, NoPolling()) + else: + polling_method = polling + if cont_token: + return LROPoller[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.AnalyzeConversationAuthoringDeploymentResourcesJobState: + """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: AnalyzeConversationAuthoringDeploymentResourcesJobState. The + AnalyzeConversationAuthoringDeploymentResourcesJobState is compatible with MutableMapping + :rtype: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringDeploymentResourcesJobState + :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.AnalyzeConversationAuthoringDeploymentResourcesJobState] = kwargs.pop("cls", None) + + _request = build_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_deserialize(_models.ErrorResponse, response.json()) + raise HttpResponseError(response=response, model=error) + + if _stream: + deserialized = response.iter_bytes() + else: + deserialized = _deserialize( + _models.AnalyzeConversationAuthoringDeploymentResourcesJobState, 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.AnalyzeConversationAuthoringDeploymentResourcesJobState: + """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: AnalyzeConversationAuthoringDeploymentResourcesJobState. The + AnalyzeConversationAuthoringDeploymentResourcesJobState is compatible with MutableMapping + :rtype: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringDeploymentResourcesJobState + :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.AnalyzeConversationAuthoringDeploymentResourcesJobState] = kwargs.pop("cls", None) + + _request = build_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_deserialize(_models.ErrorResponse, response.json()) + raise HttpResponseError(response=response, model=error) + + if _stream: + deserialized = response.iter_bytes() + else: + deserialized = _deserialize( + _models.AnalyzeConversationAuthoringDeploymentResourcesJobState, 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.AnalyzeConversationAuthoringTrainingJobState"]: + """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 AnalyzeConversationAuthoringTrainingJobState + :rtype: + ~azure.core.paging.ItemPaged[~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringTrainingJobState] + :raises ~azure.core.exceptions.HttpResponseError: + """ + _headers = kwargs.pop("headers", {}) or {} + _params = kwargs.pop("params", {}) or {} + + maxpagesize = kwargs.pop("maxpagesize", None) + cls: ClsType[List[_models.AnalyzeConversationAuthoringTrainingJobState]] = 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_analyze_conversation_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", skip_quote=True + ), + } + _request.url = self._client.format_url(_request.url, **path_format_arguments) + + else: + # make call to next link with the client's api-version + _parsed_next_link = urllib.parse.urlparse(next_link) + _next_request_params = case_insensitive_dict( + { + key: [urllib.parse.quote(v) for v in value] + for key, value in urllib.parse.parse_qs(_parsed_next_link.query).items() + } + ) + _next_request_params["api-version"] = self._config.api_version + _request = HttpRequest( + "GET", urllib.parse.urljoin(next_link, _parsed_next_link.path), params=_next_request_params + ) + path_format_arguments = { + "Endpoint": self._serialize.url( + "self._config.endpoint", self._config.endpoint, "str", skip_quote=True + ), + } + _request.url = self._client.format_url(_request.url, **path_format_arguments) + + return _request + + def extract_data(pipeline_response): + deserialized = pipeline_response.http_response.json() + list_of_elem = _deserialize( + List[_models.AnalyzeConversationAuthoringTrainingJobState], deserialized["value"] + ) + if cls: + list_of_elem = cls(list_of_elem) # type: ignore + return deserialized.get("nextLink") or None, iter(list_of_elem) + + def get_next(next_link=None): + _request = prepare_request(next_link) + + _stream = False + pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access + _request, stream=_stream, **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = _failsafe_deserialize(_models.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.AnalyzeConversationAuthoringTrainingJobState: + """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: AnalyzeConversationAuthoringTrainingJobState. The + AnalyzeConversationAuthoringTrainingJobState is compatible with MutableMapping + :rtype: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringTrainingJobState + :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.AnalyzeConversationAuthoringTrainingJobState] = kwargs.pop("cls", None) + + _request = build_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_deserialize(_models.ErrorResponse, response.json()) + raise HttpResponseError(response=response, model=error) + + if _stream: + deserialized = response.iter_bytes() + else: + deserialized = _deserialize(_models.AnalyzeConversationAuthoringTrainingJobState, 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_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_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.AnalyzeConversationAuthoringTrainingJobResult]: + """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 AnalyzeConversationAuthoringTrainingJobResult. + The AnalyzeConversationAuthoringTrainingJobResult is compatible with MutableMapping + :rtype: + ~azure.core.polling.LROPoller[~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringTrainingJobResult] + :raises ~azure.core.exceptions.HttpResponseError: + """ + _headers = kwargs.pop("headers", {}) or {} + _params = kwargs.pop("params", {}) or {} + + cls: ClsType[_models.AnalyzeConversationAuthoringTrainingJobResult] = 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.AnalyzeConversationAuthoringTrainingJobResult, 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", skip_quote=True), + } + + if polling is True: + polling_method: PollingMethod = cast( + PollingMethod, LROBasePolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs) + ) + elif polling is False: + polling_method = cast(PollingMethod, NoPolling()) + else: + polling_method = polling + if cont_token: + return LROPoller[_models.AnalyzeConversationAuthoringTrainingJobResult].from_continuation_token( + polling_method=polling_method, + continuation_token=cont_token, + client=self._client, + deserialization_callback=get_long_running_output, + ) + return LROPoller[_models.AnalyzeConversationAuthoringTrainingJobResult]( + 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.AnalyzeConversationAuthoringProjectDeletionJobState: + """Gets the status for a project deletion job. + + :param job_id: The job ID. Required. + :type job_id: str + :return: AnalyzeConversationAuthoringProjectDeletionJobState. The + AnalyzeConversationAuthoringProjectDeletionJobState is compatible with MutableMapping + :rtype: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringProjectDeletionJobState + :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.AnalyzeConversationAuthoringProjectDeletionJobState] = kwargs.pop("cls", None) + + _request = build_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_deserialize(_models.ErrorResponse, response.json()) + raise HttpResponseError(response=response, model=error) + + if _stream: + deserialized = response.iter_bytes() + else: + deserialized = _deserialize(_models.AnalyzeConversationAuthoringProjectDeletionJobState, 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.AnalyzeConversationAuthoringAssignedResourceDeploymentsMetadata: + """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: AnalyzeConversationAuthoringAssignedResourceDeploymentsMetadata. The + AnalyzeConversationAuthoringAssignedResourceDeploymentsMetadata is compatible with + MutableMapping + :rtype: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringAssignedResourceDeploymentsMetadata + :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.AnalyzeConversationAuthoringAssignedResourceDeploymentsMetadata] = kwargs.pop("cls", None) + + _request = build_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_deserialize(_models.ErrorResponse, response.json()) + raise HttpResponseError(response=response, model=error) + + if _stream: + deserialized = response.iter_bytes() + else: + deserialized = _deserialize( + _models.AnalyzeConversationAuthoringAssignedResourceDeploymentsMetadata, 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.AnalyzeConversationAuthoringSupportedLanguages: + """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.conversations.authoring.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: AnalyzeConversationAuthoringSupportedLanguages. The + AnalyzeConversationAuthoringSupportedLanguages is compatible with MutableMapping + :rtype: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringSupportedLanguages + :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.AnalyzeConversationAuthoringSupportedLanguages] = kwargs.pop("cls", None) + + _request = build_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_deserialize(_models.ErrorResponse, response.json()) + raise HttpResponseError(response=response, model=error) + + if _stream: + deserialized = response.iter_bytes() + else: + deserialized = _deserialize(_models.AnalyzeConversationAuthoringSupportedLanguages, 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.AnalyzeConversationAuthoringPrebuiltEntities: + """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: AnalyzeConversationAuthoringPrebuiltEntities. The + AnalyzeConversationAuthoringPrebuiltEntities is compatible with MutableMapping + :rtype: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringPrebuiltEntities + :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.AnalyzeConversationAuthoringPrebuiltEntities] = kwargs.pop("cls", None) + + _request = build_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_deserialize(_models.ErrorResponse, response.json()) + raise HttpResponseError(response=response, model=error) + + if _stream: + deserialized = response.iter_bytes() + else: + deserialized = _deserialize(_models.AnalyzeConversationAuthoringPrebuiltEntities, 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.AnalyzeConversationAuthoringTrainingConfigVersions: + """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.conversations.authoring.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: AnalyzeConversationAuthoringTrainingConfigVersions. The + AnalyzeConversationAuthoringTrainingConfigVersions is compatible with MutableMapping + :rtype: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringTrainingConfigVersions + :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.AnalyzeConversationAuthoringTrainingConfigVersions] = kwargs.pop("cls", None) + + _request = build_analyze_conversation_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", skip_quote=True), + } + _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 = _failsafe_deserialize(_models.ErrorResponse, response.json()) + raise HttpResponseError(response=response, model=error) + + if _stream: + deserialized = response.iter_bytes() + else: + deserialized = _deserialize(_models.AnalyzeConversationAuthoringTrainingConfigVersions, response.json()) + + if cls: + return cls(pipeline_response, deserialized, {}) # type: ignore + + return deserialized # type: ignore + + @distributed_trace + @api_version_validation( + method_added_on="2024-11-15-preview", + params_added_on={"2024-11-15-preview": ["api_version", "project_name", "exported_model_name", "accept"]}, + ) + def get_exported_model( + self, project_name: str, exported_model_name: str, **kwargs: Any + ) -> _models.AnalyzeConversationAuthoringExportedTrainedModel: + """Gets the details of an exported model. + + :param project_name: The new project name. Required. + :type project_name: str + :param exported_model_name: The exported model name. Required. + :type exported_model_name: str + :return: AnalyzeConversationAuthoringExportedTrainedModel. The + AnalyzeConversationAuthoringExportedTrainedModel is compatible with MutableMapping + :rtype: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringExportedTrainedModel + :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.AnalyzeConversationAuthoringExportedTrainedModel] = kwargs.pop("cls", None) + + _request = build_analyze_conversation_authoring_get_exported_model_request( + project_name=project_name, + exported_model_name=exported_model_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", skip_quote=True), + } + _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 = _failsafe_deserialize(_models.ErrorResponse, response.json()) + raise HttpResponseError(response=response, model=error) + + if _stream: + deserialized = response.iter_bytes() + else: + deserialized = _deserialize(_models.AnalyzeConversationAuthoringExportedTrainedModel, response.json()) + + if cls: + return cls(pipeline_response, deserialized, {}) # type: ignore + + return deserialized # type: ignore + + @distributed_trace + @api_version_validation( + method_added_on="2024-11-15-preview", + params_added_on={"2024-11-15-preview": ["api_version", "project_name", "top", "skip", "maxpagesize", "accept"]}, + ) + def list_exported_models( + self, project_name: str, *, top: Optional[int] = None, skip: Optional[int] = None, **kwargs: Any + ) -> Iterable["_models.AnalyzeConversationAuthoringExportedTrainedModel"]: + """Lists the exported 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 AnalyzeConversationAuthoringExportedTrainedModel + :rtype: + ~azure.core.paging.ItemPaged[~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringExportedTrainedModel] + :raises ~azure.core.exceptions.HttpResponseError: + """ + _headers = kwargs.pop("headers", {}) or {} + _params = kwargs.pop("params", {}) or {} + + maxpagesize = kwargs.pop("maxpagesize", None) + cls: ClsType[List[_models.AnalyzeConversationAuthoringExportedTrainedModel]] = 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_analyze_conversation_authoring_list_exported_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", skip_quote=True + ), + } + _request.url = self._client.format_url(_request.url, **path_format_arguments) + + else: + # make call to next link with the client's api-version + _parsed_next_link = urllib.parse.urlparse(next_link) + _next_request_params = case_insensitive_dict( + { + key: [urllib.parse.quote(v) for v in value] + for key, value in urllib.parse.parse_qs(_parsed_next_link.query).items() + } + ) + _next_request_params["api-version"] = self._config.api_version + _request = HttpRequest( + "GET", urllib.parse.urljoin(next_link, _parsed_next_link.path), params=_next_request_params + ) + path_format_arguments = { + "Endpoint": self._serialize.url( + "self._config.endpoint", self._config.endpoint, "str", skip_quote=True + ), + } + _request.url = self._client.format_url(_request.url, **path_format_arguments) + + return _request + + def extract_data(pipeline_response): + deserialized = pipeline_response.http_response.json() + list_of_elem = _deserialize( + List[_models.AnalyzeConversationAuthoringExportedTrainedModel], deserialized["value"] + ) + if cls: + list_of_elem = cls(list_of_elem) # type: ignore + return deserialized.get("nextLink") or None, iter(list_of_elem) + + def get_next(next_link=None): + _request = prepare_request(next_link) + + _stream = False + pipeline_response: PipelineResponse = self._client._pipeline.run( # pylint: disable=protected-access + _request, stream=_stream, **kwargs + ) + response = pipeline_response.http_response + + if response.status_code not in [200]: + map_error(status_code=response.status_code, response=response, error_map=error_map) + error = _failsafe_deserialize(_models.ErrorResponse, response.json()) + raise HttpResponseError(response=response, model=error) + + return pipeline_response + + return ItemPaged(get_next, extract_data) + + @api_version_validation( + method_added_on="2024-11-15-preview", + params_added_on={"2024-11-15-preview": ["api_version", "project_name", "exported_model_name", "accept"]}, + ) + def _delete_exported_model_initial( + self, project_name: str, exported_model_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_analyze_conversation_authoring_delete_exported_model_request( + project_name=project_name, + exported_model_name=exported_model_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", skip_quote=True), + } + _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 = _failsafe_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 + @api_version_validation( + method_added_on="2024-11-15-preview", + params_added_on={"2024-11-15-preview": ["api_version", "project_name", "exported_model_name", "accept"]}, + ) + def begin_delete_exported_model( + self, project_name: str, exported_model_name: str, **kwargs: Any + ) -> LROPoller[None]: + """Deletes an existing exported model. + + :param project_name: The name of the project to use. Required. + :type project_name: str + :param exported_model_name: The exported model name. Required. + :type exported_model_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_exported_model_initial( + project_name=project_name, + exported_model_name=exported_model_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", skip_quote=True), + } + + if polling is True: + polling_method: PollingMethod = cast( + PollingMethod, LROBasePolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs) + ) + elif polling is False: + polling_method = cast(PollingMethod, NoPolling()) + else: + polling_method = polling + if cont_token: + return LROPoller[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="2024-11-15-preview", + params_added_on={ + "2024-11-15-preview": ["api_version", "project_name", "exported_model_name", "content_type", "accept"] + }, + ) + def _create_or_update_exported_model_initial( + self, + project_name: str, + exported_model_name: str, + body: Union[_models.ExportedModelOptions, 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_analyze_conversation_authoring_create_or_update_exported_model_request( + project_name=project_name, + exported_model_name=exported_model_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", skip_quote=True), + } + _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 = _failsafe_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_create_or_update_exported_model( + self, + project_name: str, + exported_model_name: str, + body: _models.ExportedModelOptions, + *, + content_type: str = "application/json", + **kwargs: Any + ) -> LROPoller[None]: + """Creates a new exported model or replaces an existing one. + + :param project_name: The name of the project to use. Required. + :type project_name: str + :param exported_model_name: The exported model name. Required. + :type exported_model_name: str + :param body: The exported model info. Required. + :type body: ~azure.ai.language.conversations.authoring.models.ExportedModelOptions + :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_create_or_update_exported_model( + self, + project_name: str, + exported_model_name: str, + body: JSON, + *, + content_type: str = "application/json", + **kwargs: Any + ) -> LROPoller[None]: + """Creates a new exported model or replaces an existing one. + + :param project_name: The name of the project to use. Required. + :type project_name: str + :param exported_model_name: The exported model name. Required. + :type exported_model_name: str + :param body: The exported model 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_create_or_update_exported_model( + self, + project_name: str, + exported_model_name: str, + body: IO[bytes], + *, + content_type: str = "application/json", + **kwargs: Any + ) -> LROPoller[None]: + """Creates a new exported model or replaces an existing one. + + :param project_name: The name of the project to use. Required. + :type project_name: str + :param exported_model_name: The exported model name. Required. + :type exported_model_name: str + :param body: The exported model 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="2024-11-15-preview", + params_added_on={ + "2024-11-15-preview": ["api_version", "project_name", "exported_model_name", "content_type", "accept"] + }, + ) + def begin_create_or_update_exported_model( + self, + project_name: str, + exported_model_name: str, + body: Union[_models.ExportedModelOptions, JSON, IO[bytes]], + **kwargs: Any + ) -> LROPoller[None]: + """Creates a new exported model or replaces an existing one. + + :param project_name: The name of the project to use. Required. + :type project_name: str + :param exported_model_name: The exported model name. Required. + :type exported_model_name: str + :param body: The exported model info. Is one of the following types: ExportedModelOptions, + JSON, IO[bytes] Required. + :type body: ~azure.ai.language.conversations.authoring.models.ExportedModelOptions 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._create_or_update_exported_model_initial( + project_name=project_name, + exported_model_name=exported_model_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", skip_quote=True), + } + + if polling is True: + polling_method: PollingMethod = cast( + PollingMethod, LROBasePolling(lro_delay, path_format_arguments=path_format_arguments, **kwargs) + ) + elif polling is False: + polling_method = cast(PollingMethod, NoPolling()) + else: + polling_method = polling + if cont_token: + return LROPoller[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="2024-11-15-preview", + params_added_on={ + "2024-11-15-preview": ["api_version", "project_name", "exported_model_name", "job_id", "accept"] + }, + ) + def get_exported_model_job_status( + self, project_name: str, exported_model_name: str, job_id: str, **kwargs: Any + ) -> _models.AnalyzeConversationAuthoringExportedModelJobState: + """Gets the status for an existing job to create or update an exported model. + + :param project_name: The new project name. Required. + :type project_name: str + :param exported_model_name: The exported model name. Required. + :type exported_model_name: str + :param job_id: The job ID. Required. + :type job_id: str + :return: AnalyzeConversationAuthoringExportedModelJobState. The + AnalyzeConversationAuthoringExportedModelJobState is compatible with MutableMapping + :rtype: + ~azure.ai.language.conversations.authoring.models.AnalyzeConversationAuthoringExportedModelJobState + :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.AnalyzeConversationAuthoringExportedModelJobState] = kwargs.pop("cls", None) + + _request = build_analyze_conversation_authoring_get_exported_model_job_status_request( + project_name=project_name, + exported_model_name=exported_model_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", skip_quote=True), + } + _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 = _failsafe_deserialize(_models.ErrorResponse, response.json()) + raise HttpResponseError(response=response, model=error) + + if _stream: + deserialized = response.iter_bytes() + else: + deserialized = _deserialize(_models.AnalyzeConversationAuthoringExportedModelJobState, response.json()) + + if cls: + return cls(pipeline_response, deserialized, {}) # type: ignore + + return deserialized # type: ignore diff --git a/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/operations/_patch.py b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/operations/_patch.py new file mode 100644 index 000000000000..f7dd32510333 --- /dev/null +++ b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/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/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/py.typed b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/py.typed new file mode 100644 index 000000000000..e5aff4f83af8 --- /dev/null +++ b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/azure/ai/language/conversations/authoring/py.typed @@ -0,0 +1 @@ +# Marker file for PEP 561. \ No newline at end of file diff --git a/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/dev_requirements.txt b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/dev_requirements.txt new file mode 100644 index 000000000000..105486471444 --- /dev/null +++ b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/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/azure-ai-language-conversations-authoring/sdk_packaging.toml b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/sdk_packaging.toml new file mode 100644 index 000000000000..e7687fdae93b --- /dev/null +++ b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/sdk_packaging.toml @@ -0,0 +1,2 @@ +[packaging] +auto_update = false \ No newline at end of file diff --git a/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/setup.py b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/setup.py new file mode 100644 index 000000000000..3f4692a2c73b --- /dev/null +++ b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/setup.py @@ -0,0 +1,73 @@ +# 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-conversations-authoring" +PACKAGE_PPRINT_NAME = "Azure Ai Language Conversations Authoring" + +# 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 :: 4 - Beta", + "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", + # Exclude packages that will be covered by PEP420 or nspkg + "azure", + "azure.ai", + "azure.ai.language", + "azure.ai.language.conversations", + ] + ), + include_package_data=True, + package_data={ + "azure.ai.language.conversations.authoring": ["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/azure-ai-language-conversations-authoring/tsp-location.yaml b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/tsp-location.yaml new file mode 100644 index 000000000000..23c2de0edbf4 --- /dev/null +++ b/sdk/cognitivelanguage/azure-ai-language-conversations-authoring/tsp-location.yaml @@ -0,0 +1,4 @@ +directory: specification/cognitiveservices/Language.AnalyzeConversations-authoring +commit: 9bc056657f7b73ede802cee645b0aeb98c6d33cd +repo: Azure/azure-rest-api-specs +additionalDirectories: diff --git a/sdk/cognitivelanguage/ci.yml b/sdk/cognitivelanguage/ci.yml index 10f8866342d6..16c6ce340704 100644 --- a/sdk/cognitivelanguage/ci.yml +++ b/sdk/cognitivelanguage/ci.yml @@ -35,3 +35,5 @@ extends: safeName: azureailanguagequestionanswering - name: azure-ai-language-conversations safeName: azureailanguageconversations + - name: azure-ai-language-conversations-authoring + safeName: azureailanguageconversationsauthoring