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Description:

azureairesources 1.0.0b8

Azure AI Resources Package client library for Python
The Azure AI Resources package is part of the Azure AI SDK for Python and contains functionality for connecting to and managing your Azure AI resources and projects. Within your Azure AI projects it provides control plane operations for creating and managing data, indexes, models and deployments.
Source code
| Package (PyPI)
| API reference documentation
| Product documentation
| Samples
This package has been tested with Python 3.8, 3.9, 3.10, 3.11 and 3.12.
For a more complete set of Azure libraries, see https://aka.ms/azsdk/python/all.
Getting started
Prerequisites

Python 3.7 or later is required to use this package.
You must have an Azure subscription.
An Azure Machine Learning Workspace.
An Azure AI Studio project.

Install the package
Install the Azure AI generative package for Python with pip:
pip install azure-ai-resources
pip install azure-identity

Authenticate the client
from azure.ai.resources.client import AIClient
from azure.identity import DefaultAzureCredential

ai_client = AIClient(credential=DefaultAzureCredential(), subscription_id='subscription_id',
resource_group_name='resource_group', project_name='project_name')

Key concepts
Use this library within your Azure AI projects to provide control plane operations for creating and managing data, indexes, models and deployments.
Examples
View our samples repository on GitHub for examples demonstrating how to use the Azure AI Generative Python SDK.
Troubleshooting
General
Azure AI clients raise exceptions defined in Azure Core.
from azure.core.exceptions import HttpResponseError

try:
ai_client.compute.get("cpu-cluster")
except HttpResponseError as error:
print("Request failed: {}".format(error.message))

Logging
This library uses the standard logging library for logging. Basic information about HTTP sessions (URLs, headers, etc.) is logged at INFO level.
Detailed DEBUG level logging, including request/response bodies and unredacted headers, can be enabled on a client with the logging_enable argument.
See full SDK logging documentation with examples here.
Telemetry
The Azure AI Generative Python SDK includes a telemetry feature that collects usage and failure data about the SDK and sends it to Microsoft when you use the SDK in a Jupyter Notebook only. Telemetry will not be collected for any use of the Python SDK outside of a Jupyter Notebook.
Telemetry data helps the SDK team understand how the SDK is used so it can be improved and the information about failures helps the team resolve problems and fix bugs. The SDK telemetry feature is enabled by default for Jupyter Notebook usage and cannot be enabled for non-Jupyter scenarios. To opt out of the telemetry feature in a Jupyter scenario, set the environment variable "AZURE_AI_RESOURCES_ENABLE_LOGGING" to "False".
Next steps
View our samples repository on GitHub for examples demonstrating how to use the Azure AI Generative Python SDK.
Contributing
If you encounter any bugs or have suggestions, please file an issue in the Issues section of the project.

Release History
1.0.0b8 (2024-03-27)
Features Added

Connections LIST operation now supports returning data connections via new optional flag: include_data_connections.
Connections have read-only support for 3 new connection types: gen 2, data lake, and azure blob.

Bugs Fixed

Connections docstrings now discuss scope field.

Other Changes

Bug fixes

1.0.0b7 (2024-02-07)
Other Changes

Bug fixes

1.0.0b6 (2024-02-06)
Other Changes

Bug fixes

1.0.0b5 (2024-02-01)
Other Changes

Duplicate cleanup

1.0.0b4 (2024-02-01)
Other Changes

Use openai v1 environment variable

1.0.0b3 (2024-01-30)
Features Added

AzureOpenAIConnection.set_current_environment supports openai 1.0 and above.

Other Changes

Support for Python 3.12

1.0.0b2 (2023-11-30)
Other Changes

Dependency improvements.

1.0.0b1 (2023-11-10)
Features Added

First preview.