Metadata-Version: 2.4
Name: azure-ai-projects
Version: 2.2.0
Summary: Microsoft Corporation Azure AI Projects Client Library for Python
Author-email: Microsoft Corporation <azpysdkhelp@microsoft.com>
License-Expression: MIT
Project-URL: repository, https://aka.ms/azsdk/azure-ai-projects-v2/python/code
Keywords: azure,azure sdk
Classifier: Development Status :: 5 - Production/Stable
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Programming Language :: Python :: 3.14
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: isodate>=0.6.1
Requires-Dist: azure-core>=1.37.0
Requires-Dist: typing-extensions>=4.11
Requires-Dist: azure-identity>=1.15.0
Requires-Dist: openai>=2.8.0
Requires-Dist: azure-storage-blob>=12.15.0
Dynamic: license-file

# Azure AI Projects client library for Python

The AI Projects client library is part of the Microsoft Foundry SDK, and provides easy access to
resources in your [Microsoft Foundry](https://ai.azure.com/) Project. Use it to:

* **Create and run Agents** using methods on the `.agents` client property. This includes **Hosted Agents** (Preview), which let you run your own containerized agent runtime while using Microsoft Foundry for managed hosting and scaling.
* **Enhance Agents with specialized tools**:
  * Agent-to-Agent (A2A) (Preview)
  * Azure AI Search
  * Azure Functions
  * Bing Custom Search (Preview)
  * Bing Grounding
  * Browser Automation (Preview)
  * Code Interpreter
  * Computer Use (Preview)
  * Fabric IQ (Preview)
  * File Search
  * Function Tool
  * Image Generation
  * Memory Search (Preview)
  * Microsoft Fabric (Preview)
  * Microsoft SharePoint (Preview)
  * Model Context Protocol (MCP)
  * OpenAPI
  * Toolbox Search (Preview)
  * Web Search
  * Web Search (Preview)
  * Work IQ (Preview)
* **Get an OpenAI client** using `.get_openai_client()` method to run Responses, Conversations, Evaluations and Fine-Tuning operations with your Agent.
* **Fine-tune** AI Models on your data.
* **Enumerate AI Models** deployed to your Foundry Project using `.deployments` operations.
* **Enumerate connected Azure resources** in your Foundry project using `.connections` operations.
* **Upload documents and create Datasets** to reference them using `.datasets` operations.
* **Create and enumerate Search Indexes** using `.indexes` operations.
* **Explore additional evaluation tools (some in preview)** to assess the performance of your generative AI application, using `.evaluation_rules`,
`.beta.evaluation_taxonomies`, `.beta.evaluators`, `.beta.insights`, and `.beta.schedules` operations.
* **Manage memory stores (preview)** for Agent conversations, using `.beta.memory_stores` operations.
* **Register and manage local AI model weights (preview)** using `.beta.models` operations.
* **Run Red Team scans (preview)** to identify risks associated with your generative AI application, using `.beta.red_teams` operations.
* **Create and manage routines (preview)** that execute triggered actions based on configured conditions, using `.beta.routines` operations.
* **Manage skills (preview)** as reusable capabilities that can be included in toolboxes and agents, using `.beta.skills` operations.
* **Create and version toolboxes (preview)** that bundle collections of tools and skills for your agents, using `.beta.toolboxes` operations.

The client library uses version `v1` of the Microsoft Foundry [data plane REST APIs](https://aka.ms/azsdk/azure-ai-projects-v2/api-reference-v1).

[Microsoft Foundry](https://ai.azure.com/)
| [Documentation](https://aka.ms/azsdk/azure-ai-projects-v2/product-doc)
| [Samples][samples]
| [API reference](https://aka.ms/azsdk/azure-ai-projects-v2/python/api-reference)
| [Package (PyPI)](https://aka.ms/azsdk/azure-ai-projects-v2/python/package)
| [SDK source code](https://aka.ms/azsdk/azure-ai-projects-v2/python/code)
| [Release history](https://aka.ms/azsdk/azure-ai-projects-v2/python/release-history)

## Reporting issues

To report an issue with the client library, or request additional features, please open a [GitHub issue here](https://github.com/Azure/azure-sdk-for-python/issues). Mention the package name "azure-ai-projects" in the title or content.

## Getting started

### Prerequisite

* Python 3.9 or later.
* An [Azure subscription][azure_sub].
* A [project in Microsoft Foundry](https://learn.microsoft.com/azure/foundry/how-to/create-projects).
* A Foundry project endpoint URL of the form `https://your-ai-services-account-name.services.ai.azure.com/api/projects/your-project-name`. It can be found in your Microsoft Foundry Project home page. Below we will assume the environment variable `FOUNDRY_PROJECT_ENDPOINT` was defined to hold this value.
* Client authentication is done using Entra ID. To authenticate, your application needs an object that implements the [TokenCredential](https://learn.microsoft.com/python/api/azure-core/azure.core.credentials.tokencredential) interface. Code samples here use [DefaultAzureCredential](https://learn.microsoft.com/python/api/azure-identity/azure.identity.defaultazurecredential). To get that working, you will need:
  * An appropriate role assignment. See [Role-based access control in Microsoft Foundry portal](https://learn.microsoft.com/azure/foundry/concepts/rbac-foundry). Role assignment can be done via the "Access Control (IAM)" tab of your Azure AI Project resource in the Azure portal.
  * [Azure CLI](https://learn.microsoft.com/cli/azure/install-azure-cli) installed.
  * You are logged into your Azure account by running `az login`.

### Install the package

```bash
pip install azure-ai-projects
```

Verify that you have version 2.2.0 or above installed by running:

```bash
pip show azure-ai-projects
```

## Key concepts

### Create and authenticate the client with Entra ID

Entra ID is the only authentication method currently supported by the client.

To construct a synchronous client using a context manager:

```python
import os
from azure.ai.projects import AIProjectClient
from azure.identity import DefaultAzureCredential

with (
    DefaultAzureCredential() as credential,
    AIProjectClient(
        endpoint=os.environ["FOUNDRY_PROJECT_ENDPOINT"],
        credential=credential
    ) as project_client,
):
```

To construct an asynchronous client, install the additional package [aiohttp](https://pypi.org/project/aiohttp/):

```bash
pip install aiohttp
```

and run:

```python
import os
import asyncio
from azure.ai.projects.aio import AIProjectClient
from azure.identity.aio import DefaultAzureCredential

async with (
    DefaultAzureCredential() as credential,
    AIProjectClient(
        endpoint=os.environ["FOUNDRY_PROJECT_ENDPOINT"],
        credential=credential
    ) as project_client,
):
```
### Performing Responses operations using OpenAI client

Use the `.get_openai_client()` method to obtain an authenticated [OpenAI](https://github.com/openai/openai-python) client and run Responses, Conversations, Evaluations, Files, and Fine-Tuning operations. See the **responses**, **agents**, **evaluations**, **files**, and **finetuning** folders in the [samples][samples] for complete working examples.

The code below assumes the environment variable `FOUNDRY_MODEL_NAME` is defined. It's the deployment name of an AI model in your Foundry Project. See first column titled "Name" in the "Deployed models" table in your Foundry Project.

<!-- SNIPPET:sample_responses_basic.responses -->

```python
with project_client.get_openai_client() as openai_client:
    response = openai_client.responses.create(
        model=os.environ["FOUNDRY_MODEL_NAME"],
        input="What is the size of France in square miles?",
    )
    print(f"Response output: {response.output_text}")

    response = openai_client.responses.create(
        model=os.environ["FOUNDRY_MODEL_NAME"],
        input="And what is the capital city?",
        previous_response_id=response.id,
    )
    print(f"Response output: {response.output_text}")
```

<!-- END SNIPPET -->

See the **responses** folder in the [samples][samples] for additional samples including streaming responses.

### Agents

See Foundry documentation:
* **[Microsoft Foundry Agents overview](https://learn.microsoft.com/azure/foundry/agents/overview)** — concepts, setup, and quick-starts.
* **[Runtime components](https://learn.microsoft.com/azure/foundry/agents/concepts/runtime-components?tabs=python)** — deep-dive into agent architecture.
* **[Tool catalog](https://learn.microsoft.com/azure/foundry/agents/concepts/tool-catalog)** — all available tools and agent capabilities.
* **[SDK samples folder][samples]** — fully runnable Python code for synchronous and asynchronous clients covering all operations below.

## Examples

The table below lists the operation groups supported by the client library, with links to Foundry documentation and relevant [samples][samples] sub-folder. Additional documentation and samples may have been added after this package was released to cover the empty cells below.

| Topic | Foundry documentation | Samples folder |
|---|---|---|
| Agents (create, run, stream) | [Agents overview](https://learn.microsoft.com/azure/foundry/agents/overview) | `samples/agents/` |
| Hosted agents (preview) | [Hosted agents concepts](https://learn.microsoft.com/azure/foundry/agents/concepts/hosted-agents), [Deploy your first hosted agent](https://learn.microsoft.com/azure/foundry/agents/quickstarts/quickstart-hosted-agent) | `samples/hosted_agents/` |
| Agents tools | [Tool catalog](https://learn.microsoft.com/azure/foundry/agents/concepts/tool-catalog) | `samples/agents/tools/` |
| Connections | [Add a new connection to your project](https://learn.microsoft.com/azure/foundry/how-to/connections-add?tabs=foundry-portal)| `samples/connections/` |
| Datasets | | `samples/datasets/` |
| Deployments | [Deployment types](https://learn.microsoft.com/azure/foundry/foundry-models/concepts/deployment-types) | `samples/deployments/` |
| Evaluation | [Evaluate agents](https://learn.microsoft.com/azure/foundry/observability/how-to/evaluate-agent) | `samples/evaluations/` |
| Files (upload, retrieve, list, delete) | [OpenAI Files API](https://platform.openai.com/docs/api-reference/files) | `samples/files/` |
| Fine-tuning | [When to use fine-tuning](https://learn.microsoft.com/azure/foundry/openai/concepts/fine-tuning-considerations), [Fine-Tuning in AI Foundry (GitHub repo)](https://github.com/microsoft-foundry/fine-tuning) | `samples/finetuning/` |
| Indexes | [Azure AI Search](https://learn.microsoft.com/azure/search/search-what-is-azure-search) | `samples/indexes/` |
| Memory stores (preview) | | `samples/memories/` |
| Models (preview) | | `samples/models/` |
| Red teams (preview) | | `samples/red_team/` |
| Responses | [Responses API](https://platform.openai.com/docs/api-reference/responses) | `samples/responses/` |
| Routines (preview) | | |
| Skills (preview) | | `samples/hosted_agents/` |
| Toolboxes (preview) | [Curate intent-based toolbox in Foundry](https://learn.microsoft.com/azure/foundry/agents/how-to/tools/toolbox?pivots=python) | `samples/hosted_agents/` |


## Client-side tracing

See [Add client-side tracing to Foundry agents (preview)](https://learn.microsoft.com/azure/foundry/observability/how-to/trace-agent-client-side?tabs=python).

**Important:** GenAI tracing instrumentation is an experimental preview feature. Spans, attributes, and events may be modified in future versions. 

Samples can be found in the sub-folders `agents/telemetry` and `telemetry` in the [Samples][samples] folder.

## Troubleshooting

### Exceptions

Client methods that make service calls raise an [HttpResponseError](https://learn.microsoft.com/python/api/azure-core/azure.core.exceptions.httpresponseerror) exception for a non-success HTTP status code response from the service. The exception's `status_code` will hold the HTTP response status code (with `reason` showing the friendly name). The exception's `error.message` contains a detailed message that may be helpful in diagnosing the issue:

```python
from azure.core.exceptions import HttpResponseError

...

try:
    result = project_client.connections.list()
except HttpResponseError as e:
    print(f"Status code: {e.status_code} ({e.reason})")
    print(e.message)
```

For example, when you provide wrong credentials:

```text
Status code: 401 (Unauthorized)
Operation returned an invalid status 'Unauthorized'
```

### Logging

The client uses the standard [Python logging library](https://docs.python.org/3/library/logging.html). The logs include HTTP request and response headers and body, which are often useful when troubleshooting or reporting an issue to Microsoft.

#### Default console logging

To turn on client console logging define the environment variable `AZURE_AI_PROJECTS_CONSOLE_LOGGING=true` before running your Python script. Authentication bearer tokens are automatically redacted from the log. Your log may contain other sensitive information, so be sure to remove it before sharing the log with others.

#### Customizing your log

Instead of using the above-mentioned environment variable, you can configure logging yourself and control the log level, format and destination. To log to `stdout`, add the following at the top of your Python script:

```python
import sys
import logging

# Acquire the logger for this client library. Use 'azure' to affect both
# `azure.core` and `azure.ai.projects' libraries.
logger = logging.getLogger("azure")

# Set the desired logging level. logging.INFO or logging.DEBUG are good options.
logger.setLevel(logging.DEBUG)

# Direct logging output to stdout:
handler = logging.StreamHandler(stream=sys.stdout)
# Or direct logging output to a file:
# handler = logging.FileHandler(filename="sample.log")
logger.addHandler(handler)

# Optional: change the default logging format. Here we add a timestamp.
#formatter = logging.Formatter("%(asctime)s:%(levelname)s:%(name)s:%(message)s")
#handler.setFormatter(formatter)
```

By default logs redact the values of URL query strings, the values of some HTTP request and response headers (including `Authorization` which holds the key or token), and the request and response payloads. To create logs without redaction, add `logging_enable=True` to the client constructor:

```python
project_client = AIProjectClient(
    credential=DefaultAzureCredential(),
    endpoint=os.environ["FOUNDRY_PROJECT_ENDPOINT"],
    logging_enable=True
)
```

Note that the log level must be set to `logging.DEBUG` (see above code). Logs will be redacted with any other log level.

Be sure to protect non-redacted logs to avoid compromising security.

For more information, see [Configure logging in the Azure libraries for Python](https://aka.ms/azsdk/python/logging)

### Reporting issues

To report an issue with the client library, or request additional features, please open a [GitHub issue here](https://github.com/Azure/azure-sdk-for-python/issues). Mention the package name "azure-ai-projects" in the title or content.

## Next steps

Have a look at the [Samples][samples] folder, containing fully runnable Python code for synchronous and asynchronous clients.

## 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.

<!-- LINKS -->
[samples]: https://aka.ms/azsdk/azure-ai-projects-v2/python/samples/
[code_of_conduct]: https://opensource.microsoft.com/codeofconduct/
[azure_sub]: https://azure.microsoft.com/free/

# Release History

## 2.2.0 (2026-05-29)

### Features Added

* Support integration of external Agents (in preview). See new `ExternalAgentDefinition` class.
* New Agent tool in preview `FabricIQPreviewTool`.
* New Agent tool in preview `ToolboxSearchPreviewTool`.
* New methods on `.beta.agents` for 
  * Code-based hosted agents: `create_version_from_code`, `download_code`.
  * Optimization jobs: `create_optimization_job`, `get_optimization_job`, `list_optimization_jobs`, `cancel_optimization_job`, `list_optimization_candidates`.
  * Optimization candidate management: `list_optimization_candidates`, `get_optimization_candidate`, `get_optimization_candidate_config`, `get_optimization_candidate_results`, `get_candidate_file`, `promote_candidate`.
  * `stop_session` to stop a running agent session.
* New `.beta.datasets` sub-client with data generation job operations: `create_generation_job`, `get_generation_job`, `list_generation_jobs`, `cancel_generation_job`, `delete_generation_job`.
* New `.beta.models` sub-client to handle AI model weights: `create`, `list_versions`, `list`, `get`, `delete`, `update`, `pending_create_version`, `pending_upload`, `get_credentials`.
* New `.beta.routines` sub-client with routine operations: `create_or_update`, `get`, `enable`, `disable`, `list`, `delete`, `list_runs`, `dispatch`.
* New methods on `.beta.evaluators` for evaluator generation jobs: `create_generation_job`, `get_generation_job`, `list_generation_jobs`, `cancel_generation_job`, `delete_generation_job`.
* New methods on `.beta.memory_stores` to handle individual memory items: `create_memory`, `update_memory`, `list_memories`, `get_memory`, `delete_memory`.
* New methods on `.beta.skills` for versioned skill management: `create`, `list_versions`, `get_version`, `download_version`, `delete_version`.
* New optional string properties `description` and `name` added to Agent tools classes which did not have them before.
* New optional `tool_configs` added to Agent tool classes.
* New read-only property `content_hash` on `CodeConfiguration`, returning the SHA-256 hex digest of the uploaded code zip.
* New optional `force` parameter on `agents.delete` and `agents.delete_version` methods.
* New optional `blueprint_reference` parameters on `agents.create_version` method.


### Breaking Changes

Breaking changes in beta methods:
* Required keyword `isolation_key` removed from `.beta.agents.create_session()` and `.beta.agents.delete_session()` methods.
* Argument `body` in methods `.beta.evaluation_taxonomies.create()` and `.beta.evaluation_taxonomies.update()` renamed to `taxonomy`.
* Argument `body` in method `.beta.skills.create_from_files()` renamed to `content`.
* Method `.beta.agents.get_session_files` renamed to `.beta.agents.list_session_files`.
* Method `.beta.skills.create` signature changed — now takes `name` and keyword `inline_content: SkillInlineContent`; returns `SkillVersion`.
* Method `.beta.skills.create_from_package` renamed to `.beta.skills.create_from_files`.
* Method `.beta.skills.create_from_files` signature changed — now takes `name` and `content: CreateSkillVersionFromFilesBody`; returns `SkillVersion`.
* Method `.beta.skills.update` signature changed — now only accepts keyword `default_version`; returns `SkillDetails`.

Breaking changes in beta classes:
* Required property `isolation_key_source` removed from class `EntraAuthorizationScheme`.
* Renamed class `AgentEndpoint` to `AgentEndpointConfig`.
* Renamed class `DeleteSkillResponse` to `DeleteSkillResult`.
* Renamed class `SessionDirectoryListResponse` to `SessionDirectoryListResult`.
* Renamed class `SessionFileWriteResponse` to `SessionFileWriteResult`.
* Renamed class `SkillObject` to `SkillDetails`. Property `skill_id` renamed to `id`. Properties `has_blob` and `metadata` were removed.
* Renamed class `Target` to `EvaluationTarget`.
* Renamed class `TargetConfig` to `RedTeamTargetConfig`.

### Bugs Fixed

* Fixed telemetry instrumentor to correctly call is_recording() as a method on spans, ensuring non-recording spans are properly skipped (e.g., when sampling is configured) ([GitHub issue 46544](https://github.com/Azure/azure-sdk-for-python/issues/46544)).

### Sample updates

* Added new Agent tool samples `sample_agent_work_iq.py` and `sample_agent_work_iq_async.py` demonstrating use of `WorkIQPreviewTool`.
* Added new Agent tool samples `sample_agent_fabric_iq.py` and `sample_agent_fabric_iq_async.py` demonstrating use of `FabricIQPreviewTool`.
* Hosted Agents:
  * Added Hosted Agent creation samples `sample_create_hosted_agent.py` and `sample_create_hosted_agent_async.py`, demonstrating hosted agent version creation and retrieval with `AIProjectClient`.
  * Added Hosted Agent code-upload samples `sample_create_hosted_agent_from_code.py` and `sample_create_hosted_agent_from_code_async.py`, demonstrating uploading a code package (zip) as a new hosted agent version.
  * The Hosted Agent creation sample also demonstrates assigning the hosted agent managed identity the Azure AI User RBAC role on the backing Azure AI account.
  * Updated the other Hosted Agent samples to reuse an existing Hosted Agent as a prerequisite, instead of creating a new hosted agent version in each sample.
* Added Toolbox tool-search sample `sample_toolboxes_with_search_preview.py` and `sample_toolboxes_with_search_preview_async.py`, demonstrating creating a Toolbox version with `ToolboxSearchPreviewTool` and invoking `MCPTool`.
* Added `.beta.models` samples under `samples/models/`:
  * `sample_models_basic.py` — synchronous end-to-end registration via the `create` helper (uses `azcopy`), followed by `get`, `list_versions`, `list`, `get_credentials`, `update`, and `delete`.
  * `sample_models_create_and_poll.py` — alternative synchronous registration that hand-rolls the spec's three-step flow (`pending_upload` → upload via `azure-storage-blob` → `pending_create_version` + poll), without taking a dependency on `azcopy`.
  * `sample_models_basic_async.py` — asynchronous version of the same three-step flow using `azure.ai.projects.aio.AIProjectClient` and `azure.storage.blob.aio.ContainerClient`.
* Added new evaluation sample `sample_model_evaluation_instant_model.py` demonstrating model evaluation with an instant model.
* Refreshed evaluation samples under `samples/evaluations/` and `samples/evaluations/agentic_evaluators/` (including `sample_agent_evaluation`, `sample_agent_response_evaluation`, `sample_eval_catalog_prompt_based_evaluators`, `sample_evaluations_ai_assisted`, `sample_evaluations_builtin_with_csv`, `sample_evaluations_builtin_with_dataset_id`, `sample_evaluations_builtin_with_inline_data`, `sample_evaluations_builtin_with_inline_data_oai`, `sample_scheduled_evaluations`, `sample_coherence`, `sample_fluency`, `sample_intent_resolution`, `sample_relevance`, `sample_response_completeness`, `sample_tool_call_accuracy`, `sample_tool_call_success`, `sample_tool_input_accuracy`, `sample_tool_output_utilization`, `sample_tool_selection`, and `sample_generic_agentic_evaluator`).
* New sample `sample_dataset_generation_job_simpleqna_with_prompt_source.py` showing an end-to-end flow that generates a QnA dataset via `.beta.datasets.create_generation_job` and runs an OpenAI evaluation.

## 2.1.0 (2026-04-20)

### Features Added

* New `WorkIQPreviewTool`.
* `get_openai_client()` on `AIProjectClient` now takes an optional input argument `agent_name`. If provided, the returned OpenAI
client will use a base URL of Agent endpoint instead of Foundry Project endpoint. As Agent endpoints are a preview feature, you
need to set `allow_preview=True` on the `AIProjectClient` constructor.
* New `.beta.agents` sub-client added, with Session operations (those only work with Hosted Agents)
  * `create_session()`
  * `delete_session()`
  * `delete_session_file()`
  * `download_session_file()`
  * `get_session()`
  * `get_session_files()`
  * `list_sessions()`
  * `upload_session_file()`
* Also on `.beta.agents` sub-client, a new method `patch_agent_details()`.
* New `beta.skills` sub-client added, with Skills operations:
  * `create()`
  * `create_from_package()`
  * `delete()`
  * `download()`
  * `get()`
  * `list()`
  * `update()`
* New `beta.toolboxes` sub-client added, with Toolboxes operations:
  * `create_version()`
  * `delete()`
  * `delete_version()`
  * `get()`
  * `get_version()`
  * `list()`
  * `list_versions()`
  * `update()`
* Type hinting support for OpenAI client operations `.evals.create()` and `.evals.runs.create()`, when you
get the OpenAI client using `get_openai_client()` method of `AIProjectClient`. This includes new TypedDicts
classes to help you author the input to these methods. See new TypedDict classes `ModelSamplingConfigParam`, 
`ToolDescriptionParam`, `AzureAIAgentTargetParam`, `AzureAIModelTargetParam`,
`ResponseRetrievalItemGenerationParams`, `AzureAIResponsesEvalRunDataSource`, `AzureAIDataSourceConfig`,
`TargetCompletionEvalRunDataSource`, `TestingCriterionAzureAIEvaluator`, `AzureAIBenchmarkPreviewEvalRunDataSource`,
`EvalCsvFileIdSource`, `EvalCsvRunDataSource`, `RedTeamEvalRunDataSource`, `TracesPreviewEvalRunDataSource`.


### Breaking Changes

* Tracing: trace context propagation is enabled by default when tracing is enabled.

### Bugs Fixed

* Fix missing type hinting on the returned OpenAI client from method 'get_openai_client()`.

### Sample updates

* Evaluation samples updated to use TypedDicts to specify inputs to `.evals.create()` and `.evals.runs.create()` methods.
* Renamed environment variable `AZURE_AI_PROJECT_ENDPOINT` to `FOUNDRY_PROJECT_ENDPOINT` in all samples.
* Renamed environment variable `AZURE_AI_MODEL_DEPLOYMENT_NAME` to `FOUNDRY_MODEL_NAME` in all samples.
* Renamed environment variable `AZURE_AI_MODEL_AGENT_NAME` to `FOUNDRY_AGENT_NAME` in all samples.
* Added Hosted Agents related samples: `sample_agent_endpoint.py`, `sample_agent_endpoint_async.py`, `sample_sessions_crud.py`, `sample_sessions_crud_async.py`, `sample_sessions_files_upload_download.py`, `sample_sessions_files_upload_download_async.py`, `sample_skills_crud.py`, `sample_skills_crud_async.py`, `sample_skills_upload_and_download.py`, `sample_skills_upload_and_download_async.py`, `sample_toolboxes_crud.py`, and `sample_toolboxes_crud_async.py`.
* Added structured inputs + file upload sample (`sample_agent_structured_inputs_file_upload.py`) demonstrating passing an uploaded file ID to an agent at runtime.
* Added structured inputs + File Search sample (`sample_agent_file_search_structured_inputs.py`) demonstrating configuring File Search tool resources via structured inputs.
* Added structured inputs + Code Interpreter sample (`sample_agent_code_interpreter_structured_inputs.py`) demonstrating passing an uploaded file ID to Code Interpreter via structured inputs.
* Added CSV evaluation sample (`sample_evaluations_builtin_with_csv.py`) demonstrating evaluation with an uploaded CSV dataset.
* Added synthetic data evaluation samples (`sample_synthetic_data_agent_evaluation.py`) and (`sample_synthetic_data_model_evaluation.py`).
* Added Chat Completions basic samples (`sample_chat_completions_basic.py`, `sample_chat_completions_basic_async.py`) demonstrating chat completions calls using `AIProjectClient` + the OpenAI-compatible client.
* Added Toolboxes CRUD samples (`sample_toolboxes_crud.py`, `sample_toolboxes_crud_async.py`) demonstrating `project_client.beta.toolboxes` create/get/update/list/delete.
* Simplified `sample_memory_basic.py` and `sample_agent_memory_search.py` (and their async equivalent) by removing 
`options=MemoryStoreDefaultOptions(user_profile_enabled=True, chat_summary_enabled=True)` when constructing `MemoryStoreDefaultDefinition`,
since this is now redundant (it's the service default).


## 2.0.1 (2026-03-12)

### Bugs Fixed

* Fix custom Memory Stores LRO poller operation to add the missing
  required `"Foundry-Features": "MemoryStores=V1Preview"` HTTP request header.

## 2.0.0 (2026-03-06)

First stable release of the client library that uses the Generally Available (GA) version "v1" of the Foundry REST APIs.

### Features Added

* To enable preview (beta) operations, a new optional boolean input argument named `allow_preview` was added
to the constructor of `AIProjectClient`. Caller must set it to True to opt-in to preview features.
This includes creating an Hosted Agent or Workflow Agent. Methods on the `.beta` sub-client (for example
`.beta.memory_stores.create()`) do not require setting `allow_preview=True` since it's implied by the sub-client name.
When preview features are enabled, the client libraries sends the HTTP request header `Foundry-Features`
with the appropriate value in all relevant calls to the service.

### Breaking Changes

* Input argument `foundry_features` was removed from all methods that supported it. Use the new `allow_preview`
instead on client constructor (see above).
* Class `TextResponseFormatConfiguration` renamed to `TextResponseFormat`.
* Class `TextResponseFormatConfigurationResponseFormatText` renamed to `TextResponseFormatTest`.
* Class `TextResponseFormatConfigurationResponseFormatJsonObject` renamed to `TextResponseFormatJsonObject`.
* Class `CodeInterpreterContainerAuto` was renamed to `AutoCodeInterpreterToolParam`,
  and has a new optional property `network_policy` of type `ContainerNetworkPolicyParam`.
* class `ImageGenActionEnum` was renamed to `ImageGenAction`.
* Rename `ToolChoiceParamType.WEB_SEARCH_PREVIEW2025_03_11` to `ToolChoiceParamType.WEB_SEARCH_PREVIEW_2025_03_11`.
* Rename `RankerVersionType.DEFAULT2024_11_15` to `RankerVersionType.DEFAULT_2024_11_15`.
* Rename method `.beta.evaluators.list_latest_versions()` to `.beta.evaluators.list()`.
* Rename property `id` on class `Insight` to `insight_id`.
* Rename property `id` on class `Schedule` to `schedule_id`.
* Rename input argument `id` to `insight_id` in `.beta.insights.get()` method.
* Rename input argument `id` to `schedule_id` in `.beta.schedules` methods.
* Updated datetime-typed fields (`start_time`, `end_time`, `trigger_at`, `trigger_time`, `created_at`, `modified_at`) 
across `CronTrigger`, `RecurrenceTrigger`, `OneTimeTrigger`, `ScheduleRun`, and `EvaluatorVersion` classes from `str`
to `datetime.datetime` with format="rfc3339".

### Other Changes

* The input `items` argument in the methods `.beta.memory_stores.begin_update_memories()` and `.beta.memory_stores.search_memories`
was changed from type `Optional[List[dict[str, Any]]]` to `Optional[Union[str, ResponseInputParam]]`, where `ResponseInputParam`
is defined in the openai package. This allows passing in, for example, a list of `EasyInputMessageParam`. Import it using
`from openai.types.responses import EasyInputMessageParam`. This is not a breaking change, since the caller
can still pass in `List[dict[str, Any]`.

## 2.0.0b4 (2026-02-24)

This is the first release that uses the Generally Available (GA) version "v1" of the Foundry REST APIs.

### Features Added

* Tracing: included agent ID in response generation traces when available.
* Tracing: Added support for opt-in trace context propagation.

### Breaking changes

* A Responses call on OpenAPI client (`openai_client.responses.create()`) that uses an Agent reference, now needs to specify
`extra_body={"agent_reference": {"name": agent_name, "type": "agent_reference"}}` instead of `extra_body={"agent": {"name": agent_name, "type": "agent_reference"}}`.
* Agent methods `.agents.create()`, `.agents.create_from_manifest()`, `.agents.update()` and `.agents.update_from_manifest()` were removed. Use
the remaining methods `.agents.create_version()` and `.agents.create_version_from_manifest()` instead.
* To align with OpenAI naming conventions, use "Tool" suffix for class names describing Azure tools that are generally available (stable release):
  * Rename class `AzureAISearchAgentTool` to `AzureAISearchTool`.
  * Rename class `AzureFunctionAgentTool` to `AzureFunctionTool`.
  * Rename class `BingGroundingAgentTool` to `BingGroundingTool`.
  * Rename class `OpenApiAgentTool` to `OpenApiTool`.
* To align with OpenAI naming conventions, use "PreviewTool" suffix for class names describing Azure tools in preview:
  * Rename class `A2ATool` to `A2APreviewTool`.
  * Rename class `BingCustomSearchAgentTool` to `BingCustomSearchPreviewTool`.
  * Rename class `BrowserAutomationAgentTool` to `BrowserAutomationPreviewTool`.
  * Rename class `MemorySearchTool` to `MemorySearchPreviewTool`.
  * Rename class `MicrosoftFabricAgentTool` to `MicrosoftFabricPreviewTool`.
  * Rename class `SharepointAgentTool` to `SharepointPreviewTool`.
* Other class renames:
  * Rename class `PromptAgentDefinitionText` to `PromptAgentDefinitionTextOptions`
  * Rename class `EvaluationComparisonRequest` to `InsightRequest`
* To use Workflow Agents, which are still in preview, you now need to set an additional input
argument `foundry_features=FoundryFeaturesOptInKeys.WORKFLOW_AGENTS_V1_PREVIEW` when calling
`.agents.create_version()`.
* To use Hosted Agents, which are still in preview, you now need to set an additional input
argument `foundry_features=FoundryFeaturesOptInKeys.HOSTED_AGENTS_V1_PREVIEW` when calling
`.agents.create_version()`.
* To use `.evaluation_rules.create_or_update()` with `HumanEvaluationPreviewRuleAction`, you now
need to set an additional input argument `foundry_features=FoundryFeaturesOptInKeys.EVALUATIONS_V1_PREVIEW`.
* Operation sets that are still in preview now have the ".beta" subclient in their call path. So for example
`project_client.memory_stores.create()` has changed to `project_client.beta.memory_stores.create()`.
Similarly for the operation sets: `evaluators`, `insights`, `evaluation_taxonomies`, `schedules` and `red_teams`.
* The method `begin_update_memories()` in Memory Stores operation now accept optional `items` of type `List[dict[str, Any]]`
instead of `List[ItemParam]`. Similarly for `items` in method `search_memories()`. As a result around 100 classes
that are derived from `ItemParam` were removed as they are no longer used by the client library.
* Tracing instrumentation, is an experimental preview feature, now requires explicitly opt in by setting the environment variable:
`AZURE_EXPERIMENTAL_ENABLE_GENAI_TRACING=true`
* Tracing: workflow actions in conversation item listings are now emitted as "gen_ai.conversation.item" events
(with role="workflow") instead of "gen_ai.workflow.action" events in the list_conversation_items span.
* Tracing: response generation span names changed from "responses {model_name}" to "chat {model_name}" for model
calls and from "responses {agent_name}" to "invoke_agent {agent_name}" for agent calls.
* Tracing: response generation operation names changed from "responses" to "chat" for model calls and from "responses"
to "invoke_agent" for agent calls.
* Tracing: response generation uses gen_ai.input.messages and gen_ai.output.messages attributes directly under the
span instead of events.
* Tracing: agent creation uses gen_ai.system_instructions attribute directly under the span instead of an event.
Note that the attribute name is gen_ai.system_instructions not gen_ai.system.instructions.
* Tracing: "gen_ai.provider.name" attribute value changed to "microsoft.foundry".
* Tracing: the format of the function tool call related traces in input and output messages changed to
{"type": "tool_call", "id": "...", "name": "...", "arguments": {...}} and {"type": "tool_call_response", "id": "...", "result": "..."}

### Sample updates

* Add and update samples for `AzureFunctionTool`, `WebSearchTool`, and `WebSearchPreviewTool`
* All samples for agent tools call `responses.create` API with `agent_reference` instead of `agent`

## 2.0.0b3 (2026-01-06)

### Features Added

* The package now takes dependency on openai and azure-identity packages. No need to install them separately.
* Tracing: support for tracing the schema when an Agent is created with structured output definition.

### Breaking changes

* Rename class `AgentObject` to `AgentDetails`
* Rename class `AgentVersionObject` to `AgentVersionDetails`
* Rename class `MemoryStoreObject` to `MemoryStoreDetails`
* Tracing: removed outer "content" from event content format wrapper and unified type-specific keys (e.g., "text", "image_url") to generic "content" key.
* Tracing: replaced "gen_ai.request.assistant_name" attribute with gen_ai.agent.name.
* Tracing: removed "gen_ai.system" - the "gen_ai.provider.name" provides same information.
* Tracing: changed "gen_ai.user.message" and "gen_ai.tool.message" to "gen_ai.input.messages". Changed "gen_ai.assistant.message" to "gen_ai.output.messages".
* Tracing: changed "gen_ai.system.instruction" to "gen_ai.system.instructions".
* Tracing: added the "parts" array to "gen_ai.input.messages" and "gen_ai.output.messages".
* Tracing: removed "role" as a separate attribute and added "role" to "gen_ai.input.messages" and "gen_ai.output.messages" content.
* Tracing: added "finish_reason" as part of "gen_ai.output.messages" content.
* Tracing: changed the tool calls to use the api definitions as the types in traces. For example "function_call" instead of "function" and "function_call_output" instead of "function"

### Bugs Fixed

* Tracing: fixed a bug with computer use tool call output including screenshot binary data even when binary data tracing is off.

### Sample updates

* Added OpenAPI tool sample. See `sample_agent_openapi.py`.
* Added OpenAPI with Project Connection sample. See `sample_agent_openapi_with_project_connection.py`.
* Added SharePoint grounding tool sample. See `sample_agent_sharepoint.py`.
* Improved MCP client sample showing direct MCP tool invocation. See `samples/mcp_client/sample_mcp_tool_async.py`.
* Samples that download generated files (code interpreter and image generation) now save files to the system temp directory instead of the current working directory. See `sample_agent_code_interpreter.py`, `sample_agent_code_interpreter_async.py`, `sample_agent_image_generation.py`, and `sample_agent_image_generation_async.py`.
* The Agent to Agent sample was updated to allow "Custom keys" connection type.
* Update Fine-Tuning supervised job samples to show waiting for model result instead of polling
* Add evaluations sample `samples/evaluations/sample_evaluations_score_model_grader_with_image.py`.
* Add basic steam event samples `samples/agents/sample_agent_stream_events.py` and `samples/responses/sample_responses_stream_events.py`

## 2.0.0b2 (2025-11-14)

### Features Added

* Tracing: support for workflow agent tracing.
* Agent Memory operations, including code for custom LRO poller. See methods on the ".memory_store"
property of `AIProjectClient`.

### Breaking changes

* `get_openai_client()` method on the asynchronous AIProjectClient is no longer an "async" method.
* Tracing: tool call output event content format updated to be in line with other events.

### Bugs Fixed

* Tracing: operation name attribute added to create agent span, token usage added to streaming response generation span.

### Sample updates

* Added samples to show usage of the Memory Search Tool (see sample_agent_memory_search.py) and its async equivalent.
* Added samples to show Memory management. See samples in the folder `samples\memories`.
* Added `finetuning` samples for operations create, retrieve, list, list_events, list_checkpoints, cancel, pause and resume. Also, these samples includes various finetuning techniques like Supervised (SFT), Reinforcement (RFT) and Direct performance optimization (DPO).
* In all most samples, credential, project client, and openai client are combined into one context manager.
* Remove `await` while calling `get_openai_client()` for samples using asynchronous clients. 

## 2.0.0b1 (2025-11-11)

### Features added

* The client library now uses version `2025-11-15-preview` of the Microsoft Foundry [data plane REST APIs](https://aka.ms/azsdk/azure-ai-projects-v2/api-reference-2025-11-15-preview).
* New Agent operations (now built on top of OpenAI's `Responses` protocol) were added to the `AIProjectClient`.
This package no longer depends on `azure-ai-agents` package. See `samples\agents` folder.
* New Evaluation operations. See methods on properties `.evaluation_rules`, `.evaluation_taxonomies`, `.evaluators`, `.insights`, and `.schedules`.
* New Memory Store operations. See methods on the property `.memory_store`.

### Breaking changes

* The implementation of `.get_openai_client()` method was updated to return an authenticated
OpenAI client from the openai package, configure to run Responses operations on your Foundry Project endpoint.

### Sample updates

* Added new Agent samples. See `samples\agents` folder.
* Added new Evaluation samples. See `samples\evaluations` folder.
* Added `files` samples for operations create, delete, list, retrieve and content. See `samples\files` folder.

## 1.1.0b4 (2025-09-12)

### Bugs Fixed

* Fix getting secret keys for connections of type "Custom Keys" ([GitHub issue 52355](https://github.com/Azure/azure-sdk-for-net/issues/52355))

## 1.1.0b3 (2025-08-26)

### Features added

* File `setup.py` was updated to indicate the dependency `azure-ai-agents>=1.2.0b3`
instead of `azure-ai-agents>=1.0.0`. This means that in a clean environment, installing
via `pip install --pre azure-ai-projects` will install latest beta version of `azure-ai-agents`
(which has features in preview) instead of latest stable version (which does
not include preview features).

## 1.1.0b2 (2025-08-05)

### Bugs Fixed

Fix regression in Red-Team operations, in the definition of the class `AzureOpenAIModelConfiguration`.

## 1.1.0b1 (2025-08-01)

First beta version following the 1.0.0 stable release. It brings back the Evaluation and Red-Team operations which are still in preview.

### Features added

* Evaluation and Red-Team operations (in preview) were restored.

## 1.0.0 (2025-07-31)

First stable version of the client library. The client library now uses version `v1` of the
AI Foundry [data plane REST APIs](https://aka.ms/azsdk/azure-ai-projects/ga-rest-api-reference).

### Breaking changes

* Features that are still in preview were removed from this stable release. This includes:
  * Evaluation operations (property `.evaluations`)
  * Red-Team operations (property `.red_teams`)
  * Class `PromptTemplate`.
  * Package function `enable_telemetry()`
* Classes were renamed:
  * Class `Sku` was renamed `ModelDeploymentSku`
  * Class `SasCredential` was renamed `BlobReferenceSasCredential`
  * Class `AssetCredentialResponse` was renamed `DatasetCredential`
* Method `.inference.get_azure_openai_client()` was renamed `.get_openai_client()`. The `.inference` property was removed.
  The method is documented as returning an object of type `OpenAI`, but it still returns an object of the derived type `AzureOpenAI`.
  The function implementation has not changed.
* Method `.telemetry.get_connection_string()` was renamed `.telemetry.get_application_insights_connection_string()`

### Sample updates

* Added a new Dataset sample named `sample_datasets_download.py` to show how you can download all files referenced by a certain Dataset (following a question in [this GitHub issue](https://github.com/Azure/azure-sdk-for-python/issues/41960))
* Two samples added showing how to do a `responses` operation using an authenticated Azure OpenAI client created
using `get_openai_client()`.
* Existing inference samples that used the package function `enable_telemetry()` were updated to remove this call,
and instead add the necessary tracing configuration calls to the sample.

## 1.0.0b12 (2025-06-23)

### Breaking changes

* These 3 methods on `AIProjectClient` were removed: `.inference.get_chat_completions_client()`,
`.inference.get_embeddings_client()` and `.inference.get_image_embeddings_client()`.
For guidance on obtaining an authenticated `azure-ai-inference` client for your AI Foundry Project,
refer to the updated samples in the `samples\inference` directory. For example,
`sample_chat_completions_with_azure_ai_inference_client.py`. Alternatively, use the `.inference.get_azure_openai_client()` method to perform chat completions with an Azure OpenAI client.
* Method argument name changes:
  * In method `.indexes.create_or_update()` argument `body` was renamed `index`.
  * In method `.datasets.create_or_update()` argument `body` was renamed `dataset_version`.
  * In method `.datasets.pending_upload()` argument `body` was renamed `pending_upload_request`.

### Bugs Fixed

* Fix to package function `enable_telemetry()` to correctly instrument `azure-ai-agents`.
* Updated RedTeam target type visibility to allow for type being sent in the JSON for redteam run creation.

### Other

* Set dependency on `azure-ai-agents` version `1.0.0` or above,
now that we have a stable release of the Agents package.

## 1.0.0b11 (2025-05-15)

There have been significant updates with the release of version 1.0.0b11, including breaking changes.
Please see new samples and package README.md file.

### Features added

* `.deployments` methods to enumerate AI models deployed to your AI Foundry Project.
* `.datasets` methods to upload documents and reference them. To be used with Evaluations.
* `.indexes` methods to handle your Search Indexes.

### Breaking changes

* Azure AI Foundry Project endpoint is now required to construct the `AIProjectClient`. It has the form
`https://<your-ai-services-account-name>.services.ai.azure.com/api/projects/<your-project-name>`. Find it in your AI Foundry Project
Overview page. The factory method `from_connection_string` was removed. Support for project connection string and hub-based projects has been discontinued. We recommend creating a new Azure AI Foundry resource utilizing project endpoint. If this is not possible, please pin the version of or pin the version of `azure-ai-projects` to `1.0.0b10` or earlier.
* Agents are now implemented in a separate package `azure-ai-agents`. Continue using the ".agents" operations on the
`AIProjectsClient` to create, run and delete agents, as before. However there have been some breaking changes in these operations.
See [Agents package document and samples](https://github.com/Azure/azure-sdk-for-python/tree/azure-ai-projects_1.0.0b11/sdk/ai/azure-ai-agents) for more details.
* Several changes to the `.connections` methods, including the response object (now simply called `Connection`)
* The method `.inference.get_azure_openai_client()` now supports returning an authenticated `AzureOpenAI` client to be used with
AI models deployed to the Project's AI Services. This is in addition to the existing option to get an `AzureOpenAI` client for one of the connected Azure OpenAI services.
* Import `PromptTemplate` from `azure.ai.projects` instead of `azure.ai.projects.prompts`.
* The class ConnectionProperties was renamed to Connection, and its properties have changed.
* The method `.to_evaluator_model_config` on `ConnectionProperties` is no longer required and does not have an equivalent method on `Connection`. When constructing the EvaluatorConfiguration class, the `init_params` element now requires `deployment_name` instead of `model_config`.
* The method `upload_file` on `AIProjectClient` had been removed, use `datasets.upload_file` instead.
* Evaluator Ids are available using the Enum `EvaluatorIds` and no longer require `azure-ai-evaluation` package to be installed.
* Property `scope` on `AIProjectClient` is removed, use AI Foundry Project endpoint instead.
* Property `id` on Evaluation is replaced with `name`.
* Please see the [agents migration guide](https://github.com/Azure/azure-sdk-for-python/blob/azure-ai-projects_1.0.0/sdk/ai/azure-ai-projects/AGENTS_MIGRATION_GUIDE.md) on how to use the new `azure-ai-projects` with `azure-ai-agents` package.

### Sample updates

* All samples have been updated. New ones added for Deployments, Datasets and Indexes.

## 1.0.0b10 (2025-04-23)

### Features added

* Added `ConnectedAgentTool` class for better connected Agent support.
* Added Agent tool call tracing for all tool call types when streaming with `AgentEventHandler` based event handler.
* Added tracing for listing Agent run steps.
* Add a `max_retry` argument to the Agent's `enable_auto_function_calls` function to cancel the run if the maximum number of retries for auto function calls is reached.

### Sample updates

* Added connected Agent tool sample.

### Bugs Fixed

* Fix for filtering of Agent messages by run ID (see [GitHub issue 49513](https://github.com/Azure/azure-sdk-for-net/issues/49513)).

## 1.0.0b9 (2025-04-16)

### Features added

* Utilities to load prompt template strings and Prompty file content
* Added BingCustomSearchTool class with sample
* Added list_threads API to agents namespace
* Added image input support for agents create_message

### Sample updates

* Added `project_client.agents.enable_auto_function_calls(toolset=toolset)` to all samples that has `toolcalls` executed by `azure-ai-project` SDK
* New BingCustomSearchTool sample
* New samples added for image input from url, file and base64

### Breaking Changes

Redesigned automatic function calls because agents retrieved by `update_agent` and `get_agent` do not support them.  With the new design, the toolset parameter in `create_agent` no longer executes toolcalls automatically during `create_and_process_run` or `create_stream`. To retain this behavior, call `enable_auto_function_calls` without additional changes.

## 1.0.0b8 (2025-03-28)

### Features added

* New parameters added for Azure AI Search tool, with corresponding sample update.
* Fabric tool REST name updated, along with convenience code.

### Sample updates

* Sample update demonstrating new parameters added for Azure AI Search tool.
* Sample added using OpenAPI tool against authenticated TripAdvisor API spec.

### Bugs Fixed

* Fix for a bug in Agent tracing causing event handler return values to not be returned when tracing is enabled.
* Fix for a bug in Agent tracing causing tool calls not to be recorded in traces.
* Fix for a bug in Agent tracing causing function tool calls to not work properly when tracing is enabled.
* Fix for a bug in Agent streaming, where `agent_id` was not included in the response. This caused the SDK not to make function calls when the thread run status is `requires_action`.

## 1.0.0b7 (2025-03-06)

### Features added

* Add support for parsing URL citations in Agent text messages. See new classes `MessageTextUrlCitationAnnotation` and `MessageDeltaTextUrlCitationAnnotation`.
* Add enum value `ConnectionType.API_KEY` to support enumeration of generic connections that uses API Key authentication.

### Sample updates

* Update sample `sample_agents_bing_grounding.py` with printout of URL citation.
* Add new samples `sample_agents_stream_eventhandler_with_bing_grounding.py` and `sample_agents_stream_iteration_with_bing_grounding.py` with printout of URL citation.

### Bugs Fixed

* Fix a bug in deserialization of `RunStepDeltaFileSearchToolCall` returned during Agent streaming (see [GitHub issue 48333](https://github.com/Azure/azure-sdk-for-net/issues/48333)).
* Fix for Exception raised while parsing Agent streaming response, in some rare cases, for multibyte UTF-8 languages like Chinese.

### Breaking Changes

* Rename input argument `assistant_id` to `agent_id` in all Agent methods to align with the "Agent" terminology. Similarly, rename all `assistant_id` properties on classes.

## 1.0.0b6 (2025-02-14)

### Features added

* Added `trace_function` decorator for conveniently tracing function calls in Agents using OpenTelemetry. Please see the README.md for updated documentation.

### Sample updates

* Added AzureLogicAppTool utility and Logic App sample under `samples/agents`, folder to make Azure Logic App integration with Agents easier.
* Added better observability for Azure AI Search sample for Agents via improved run steps information from the service.
* Added sample to demonstrate how to add custom attributes to telemetry span.

### Bugs Fixed

* Lowered the logging level of "Toolset is not available in the client" from `warning` to `debug` to prevent unnecessary log entries in agent application runs.

## 1.0.0b5 (2025-01-17)

### Features added

* Add method `.inference.get_image_embeddings_client` on `AIProjectClient` to get an authenticated
`ImageEmbeddingsClient` (from the package azure-ai-inference). You need to have azure-ai-inference package
version 1.0.0b7 or above installed for this method to work.

### Bugs Fixed

* Fix for events dropped in streamed Agent response (see [GitHub issue 39028](https://github.com/Azure/azure-sdk-for-python/issues/39028)).
* In Agents, incomplete status thread run event is now deserialized into a ThreadRun object, during stream iteration, and invokes the correct function `on_thread_run` (instead of the wrong function `on_unhandled_event`).
* Fix an error when calling the `to_evaluator_model_config` method of class `ConnectionProperties`. See new input
argument `include_credentials`.

### Breaking Changes

* `submit_tool_outputs_to_run` returns `None` instead of `ThreadRun` (see [GitHub issue 39028](https://github.com/Azure/azure-sdk-for-python/issues/39028)).

## 1.0.0b4 (2024-12-20)

### Bugs Fixed

* Fix for Agent streaming issue (see [GitHub issue 38918](https://github.com/Azure/azure-sdk-for-python/issues/38918))
* Fix for Agent async function `send_email_async` is not called (see [GitHub issue 38898](https://github.com/Azure/azure-sdk-for-python/issues/38898))
* Fix for Agent streaming with event handler fails with "AttributeError: 'MyEventHandler' object has no attribute 'buffer'" (see [GitHub issue 38897](https://github.com/Azure/azure-sdk-for-python/issues/38897))

### Features Added

* Add optional input argument `connection_name` to methods `.inference.get_chat_completions_client`,
 `.inference.get_embeddings_client` and `.inference.get_azure_openai_client`.

## 1.0.0b3 (2024-12-13)

### Features Added

* Add support for Structured Outputs for Agents.
* Add option to include file contents, when index search is used for Agents.
* Added objects to inform Agents about Azure Functions.
* Redesigned streaming and event handlers for agents.
* Add `parallel_tool_calls` parameter to allow parallel tool execution for Agents.
* Added `BingGroundingTool` for Agents to use against a Bing API Key connection.
* Added `AzureAiSearchTool` for Agents to use against an Azure AI Search resource.
* Added `OpenApiTool` for Agents, which creates and executes a REST function defined by an OpenAPI spec.
* Added new helper properties in `OpenAIPageableListOfThreadMessage`, `MessageDeltaChunk`, and `ThreadMessage`.
* Rename "AI Studio" to "AI Foundry" in package documents and samples, following recent rebranding.

### Breaking Changes

* The method `.agents.get_messages` was removed. Please use `.agents.list_messages` instead.

## 1.0.0b2 (2024-12-03)

### Bugs Fixed

* Fix a bug in the `.inference` operations when Entra ID authentication is used by the default connection.
* Fixed bugs occurring during streaming in function tool calls by asynchronous agents.
* Fixed bugs that were causing issues with tracing agent asynchronous functionality.
* Fix a bug causing warning about unclosed session, shown when using asynchronous credentials to create agent.
* Fix a bug that would cause agent function tool related function names and parameters to be included in traces even when content recording is not enabled.

## 1.0.0b1 (2024-11-15)

### Features Added

First beta version
