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[AutoPR azure-ai-projects] Create a structure for AzureFunction. #9505

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6 changes: 6 additions & 0 deletions sdk/ai/azure-ai-projects/_meta.json
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@@ -0,0 +1,6 @@
{
"commit": "4ec5f518e271dd69523ace2e83ecfe7bb8113d9c",
"repository_url": "https://github.com/Azure/azure-rest-api-specs",
"typespec_src": "specification/ai/Azure.AI.Projects",
"@azure-tools/typespec-python": "0.37.0"
}
4 changes: 2 additions & 2 deletions sdk/ai/azure-ai-projects/azure/ai/projects/_client.py
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Expand Up @@ -33,7 +33,7 @@ class AIProjectClient:
:vartype telemetry: azure.ai.projects.operations.TelemetryOperations
:ivar evaluations: EvaluationsOperations operations
:vartype evaluations: azure.ai.projects.operations.EvaluationsOperations
:param endpoint: The Azure AI Studio project endpoint, in the form
:param endpoint: The Azure AI Foundry project endpoint, in the form
``https://<azure-region>.api.azureml.ms`` or
``https://<private-link-guid>.<azure-region>.api.azureml.ms``\\\\ , where
:code:`<azure-region>` is the Azure region where the project is deployed (e.g. westus) and
Expand All @@ -43,7 +43,7 @@ class AIProjectClient:
:type subscription_id: str
:param resource_group_name: The name of the Azure Resource Group. Required.
:type resource_group_name: str
:param project_name: The Azure AI Studio project name. Required.
:param project_name: The Azure AI Foundry project name. Required.
:type project_name: str
:param credential: Credential used to authenticate requests to the service. Required.
:type credential: ~azure.core.credentials.TokenCredential
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4 changes: 2 additions & 2 deletions sdk/ai/azure-ai-projects/azure/ai/projects/_configuration.py
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Expand Up @@ -22,7 +22,7 @@ class AIProjectClientConfiguration: # pylint: disable=too-many-instance-attribu
Note that all parameters used to create this instance are saved as instance
attributes.

:param endpoint: The Azure AI Studio project endpoint, in the form
:param endpoint: The Azure AI Foundry project endpoint, in the form
``https://<azure-region>.api.azureml.ms`` or
``https://<private-link-guid>.<azure-region>.api.azureml.ms``\\ , where :code:`<azure-region>`
is the Azure region where the project is deployed (e.g. westus) and :code:`<private-link-guid>`
Expand All @@ -32,7 +32,7 @@ class AIProjectClientConfiguration: # pylint: disable=too-many-instance-attribu
:type subscription_id: str
:param resource_group_name: The name of the Azure Resource Group. Required.
:type resource_group_name: str
:param project_name: The Azure AI Studio project name. Required.
:param project_name: The Azure AI Foundry project name. Required.
:type project_name: str
:param credential: Credential used to authenticate requests to the service. Required.
:type credential: ~azure.core.credentials.TokenCredential
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18 changes: 17 additions & 1 deletion sdk/ai/azure-ai-projects/azure/ai/projects/_model_base.py
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Expand Up @@ -754,7 +754,7 @@ def _get_deserialize_callable_from_annotation( # pylint: disable=too-many-retur
except AttributeError:
model_name = annotation
if module is not None:
annotation = _get_model(module, model_name)
annotation = _get_model(module, model_name) # type: ignore

try:
if module and _is_model(annotation):
Expand Down Expand Up @@ -894,6 +894,22 @@ def _deserialize(
return _deserialize_with_callable(deserializer, value)


def _failsafe_deserialize(
deserializer: typing.Any,
value: typing.Any,
module: typing.Optional[str] = None,
rf: typing.Optional["_RestField"] = None,
format: typing.Optional[str] = None,
) -> typing.Any:
try:
return _deserialize(deserializer, value, module, rf, format)
except DeserializationError:
_LOGGER.warning(
"Ran into a deserialization error. Ignoring since this is failsafe deserialization", exc_info=True
)
return None


class _RestField:
def __init__(
self,
Expand Down
287 changes: 2 additions & 285 deletions sdk/ai/azure-ai-projects/azure/ai/projects/_patch.py
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Expand Up @@ -6,292 +6,9 @@

Follow our quickstart for examples: https://aka.ms/azsdk/python/dpcodegen/python/customize
"""
import uuid
from os import PathLike
from pathlib import Path
from typing import Any, Dict, List, Tuple, Union
from typing_extensions import Self
from typing import List

from azure.core import PipelineClient
from azure.core.credentials import TokenCredential
from azure.core.pipeline import policies

from ._client import AIProjectClient as ClientGenerated
from ._configuration import AIProjectClientConfiguration
from ._serialization import Deserializer, Serializer
from .operations import AgentsOperations, ConnectionsOperations, EvaluationsOperations, TelemetryOperations
from .operations._patch import InferenceOperations


class AIProjectClient(
ClientGenerated
): # pylint: disable=client-accepts-api-version-keyword,too-many-instance-attributes
def __init__( # pylint: disable=super-init-not-called,too-many-statements
self,
endpoint: str,
subscription_id: str,
resource_group_name: str,
project_name: str,
credential: "TokenCredential",
**kwargs: Any,
) -> None:
# TODO: Validate input formats with regex match (e.g. subscription ID)
if not endpoint:
raise ValueError("endpoint is required")
if not subscription_id:
raise ValueError("subscription_id ID is required")
if not resource_group_name:
raise ValueError("resource_group_name is required")
if not project_name:
raise ValueError("project_name is required")
if not credential:
raise ValueError("credential is required")
if "api_version" in kwargs:
raise ValueError("No support for overriding the API version")
if "credential_scopes" in kwargs:
raise ValueError("No support for overriding the credential scopes")

kwargs0 = kwargs.copy()
kwargs1 = kwargs.copy()
kwargs2 = kwargs.copy()
kwargs3 = kwargs.copy()

# For getting AppInsights connection string from the AppInsights resource.
# The AppInsights resource URL is not known at this point. We need to get it from the
# AzureML "Workspace - Get" REST API call. It will have the form:
# https://management.azure.com/subscriptions/{appinsights_subscription_id}/resourceGroups/{appinsights_resource_group_name}/providers/microsoft.insights/components/{appinsights_resource_name}
_endpoint0 = "https://management.azure.com"
self._config0: AIProjectClientConfiguration = AIProjectClientConfiguration(
endpoint=endpoint,
subscription_id=subscription_id,
resource_group_name=resource_group_name,
project_name=project_name,
credential=credential,
api_version="2020-02-02",
credential_scopes=["https://management.azure.com/.default"],
**kwargs0,
)

_policies0 = kwargs0.pop("policies", None)
if _policies0 is None:
_policies0 = [
policies.RequestIdPolicy(**kwargs0),
self._config0.headers_policy,
self._config0.user_agent_policy,
self._config0.proxy_policy,
policies.ContentDecodePolicy(**kwargs0),
self._config0.redirect_policy,
self._config0.retry_policy,
self._config0.authentication_policy,
self._config0.custom_hook_policy,
self._config0.logging_policy,
policies.DistributedTracingPolicy(**kwargs0),
policies.SensitiveHeaderCleanupPolicy(**kwargs0) if self._config0.redirect_policy else None,
self._config0.http_logging_policy,
]
self._client0: PipelineClient = PipelineClient(base_url=_endpoint0, policies=_policies0, **kwargs0)

# For Endpoints operations (listing connections, getting connection properties, getting project properties)
_endpoint1 = (
"https://management.azure.com/"
+ f"subscriptions/{subscription_id}/"
+ f"resourceGroups/{resource_group_name}/"
+ "providers/Microsoft.MachineLearningServices/"
+ f"workspaces/{project_name}"
)
self._config1: AIProjectClientConfiguration = AIProjectClientConfiguration(
endpoint=endpoint,
subscription_id=subscription_id,
resource_group_name=resource_group_name,
project_name=project_name,
credential=credential,
api_version="2024-07-01-preview",
credential_scopes=["https://management.azure.com/.default"],
**kwargs1,
)
_policies1 = kwargs1.pop("policies", None)
if _policies1 is None:
_policies1 = [
policies.RequestIdPolicy(**kwargs1),
self._config1.headers_policy,
self._config1.user_agent_policy,
self._config1.proxy_policy,
policies.ContentDecodePolicy(**kwargs1),
self._config1.redirect_policy,
self._config1.retry_policy,
self._config1.authentication_policy,
self._config1.custom_hook_policy,
self._config1.logging_policy,
policies.DistributedTracingPolicy(**kwargs1),
policies.SensitiveHeaderCleanupPolicy(**kwargs1) if self._config1.redirect_policy else None,
self._config1.http_logging_policy,
]
self._client1: PipelineClient = PipelineClient(base_url=_endpoint1, policies=_policies1, **kwargs1)

# For Agents operations
_endpoint2 = f"{endpoint}/agents/v1.0/subscriptions/{subscription_id}/resourceGroups/{resource_group_name}/providers/Microsoft.MachineLearningServices/workspaces/{project_name}" # pylint: disable=line-too-long
self._config2 = AIProjectClientConfiguration(
endpoint=endpoint,
subscription_id=subscription_id,
resource_group_name=resource_group_name,
project_name=project_name,
credential=credential,
api_version="2024-07-01-preview", # TODO: Update me
credential_scopes=["https://ml.azure.com/.default"],
**kwargs2,
)
_policies2 = kwargs2.pop("policies", None)
if _policies2 is None:
_policies2 = [
policies.RequestIdPolicy(**kwargs2),
self._config2.headers_policy,
self._config2.user_agent_policy,
self._config2.proxy_policy,
policies.ContentDecodePolicy(**kwargs2),
self._config2.redirect_policy,
self._config2.retry_policy,
self._config2.authentication_policy,
self._config2.custom_hook_policy,
self._config2.logging_policy,
policies.DistributedTracingPolicy(**kwargs2),
policies.SensitiveHeaderCleanupPolicy(**kwargs2) if self._config2.redirect_policy else None,
self._config2.http_logging_policy,
]
self._client2: PipelineClient = PipelineClient(base_url=_endpoint2, policies=_policies2, **kwargs2)

# For Cloud Evaluations operations
# cSpell:disable-next-line
_endpoint3 = f"{endpoint}/raisvc/v1.0/subscriptions/{subscription_id}/resourceGroups/{resource_group_name}/providers/Microsoft.MachineLearningServices/workspaces/{project_name}" # pylint: disable=line-too-long
self._config3 = AIProjectClientConfiguration(
endpoint=endpoint,
subscription_id=subscription_id,
resource_group_name=resource_group_name,
project_name=project_name,
credential=credential,
api_version="2024-07-01-preview", # TODO: Update me
credential_scopes=["https://ml.azure.com/.default"], # TODO: Update once service changes are ready
**kwargs3,
)
_policies3 = kwargs3.pop("policies", None)
if _policies3 is None:
_policies3 = [
policies.RequestIdPolicy(**kwargs3),
self._config3.headers_policy,
self._config3.user_agent_policy,
self._config3.proxy_policy,
policies.ContentDecodePolicy(**kwargs3),
self._config3.redirect_policy,
self._config3.retry_policy,
self._config3.authentication_policy,
self._config3.custom_hook_policy,
self._config3.logging_policy,
policies.DistributedTracingPolicy(**kwargs3),
policies.SensitiveHeaderCleanupPolicy(**kwargs3) if self._config3.redirect_policy else None,
self._config3.http_logging_policy,
]
self._client3: PipelineClient = PipelineClient(base_url=_endpoint3, policies=_policies3, **kwargs3)

self._serialize = Serializer()
self._deserialize = Deserializer()
self._serialize.client_side_validation = False

self.telemetry = TelemetryOperations(
self._client0, self._config0, self._serialize, self._deserialize, outer_instance=self
)
self.connections = ConnectionsOperations(self._client1, self._config1, self._serialize, self._deserialize)
self.agents = AgentsOperations(self._client2, self._config2, self._serialize, self._deserialize)
self.evaluations = EvaluationsOperations(self._client3, self._config3, self._serialize, self._deserialize)
self.inference = InferenceOperations(self)

def close(self) -> None:
self._client0.close()
self._client1.close()
self._client2.close()
self._client3.close()

def __enter__(self) -> Self:
self._client0.__enter__()
self._client1.__enter__()
self._client2.__enter__()
self._client3.__enter__()
return self

def __exit__(self, *exc_details: Any) -> None:
self._client0.__exit__(*exc_details)
self._client1.__exit__(*exc_details)
self._client2.__exit__(*exc_details)
self._client3.__exit__(*exc_details)

@classmethod
def from_connection_string(cls, conn_str: str, credential: "TokenCredential", **kwargs) -> Self:
"""
Create an AIProjectClient from a connection string.

:param str conn_str: The connection string, copied from your AI Studio project.
:param TokenCredential credential: Credential used to authenticate requests to the service.
:return: An AIProjectClient instance.
:rtype: AIProjectClient
"""
if not conn_str:
raise ValueError("Connection string is required")
parts = conn_str.split(";")
if len(parts) != 4:
raise ValueError("Invalid connection string format")
endpoint = "https://" + parts[0]
subscription_id = parts[1]
resource_group_name = parts[2]
project_name = parts[3]
return cls(endpoint, subscription_id, resource_group_name, project_name, credential, **kwargs)

def upload_file(self, file_path: Union[Path, str, PathLike]) -> Tuple[str, str]:
"""Upload a file to the Azure AI Studio project.
This method required *azure-ai-ml* to be installed.

:param file_path: The path to the file to upload.
:type file_path: Union[str, Path, PathLike]
:return: The tuple, containing asset id and asset URI of uploaded file.
:rtype: Tuple[str]
"""
try:
from azure.ai.ml import MLClient # type: ignore
from azure.ai.ml.constants import AssetTypes # type: ignore
from azure.ai.ml.entities import Data # type: ignore
except ImportError as e:
raise ImportError(
"azure-ai-ml must be installed to use this function. Please install it using `pip install azure-ai-ml`"
) from e

data = Data(
path=str(file_path),
type=AssetTypes.URI_FILE,
name=str(uuid.uuid4()), # generating random name
is_anonymous=True,
version="1",
)

ml_client = MLClient(
self._config3.credential,
self._config3.subscription_id,
self._config3.resource_group_name,
self._config3.project_name,
)

data_asset = ml_client.data.create_or_update(data)

return data_asset.id, data_asset.path

@property
def scope(self) -> Dict[str, str]:
return {
"subscription_id": self._config3.subscription_id,
"resource_group_name": self._config3.resource_group_name,
"project_name": self._config3.project_name,
}


__all__: List[str] = [
"AIProjectClient",
] # Add all objects you want publicly available to users at this package level
__all__: List[str] = [] # Add all objects you want publicly available to users at this package level


def patch_sdk():
Expand Down
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