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Evan Mattson c084b067de Python: Support structured outputs with Azure AI inference chat completion. (#12183 )

### Motivation and Context

The Azure AI inference SDK released support for structured outputs for
chat completions (for models that support it). We had not brought this
into SK. This PR adds functionality and the ability to run the
structured output samples that exist today.

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### Description

Adds functionality to handle structured outputs for the Azure AI
Inference Chat Completion calls.
- Fixes a bug within AzureAIInferenceChatCompletion where the wrong
isinstance check type is used. This prevented adding tool calls during
streaming invocation. Also properly add the `ai_model_id` from the
connector during message construction during streaming invocation,
- Adds unit tests for AzureAIInferenceChatCompletion structured outputs
- Closes #11952

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### Contribution Checklist

<!-- Before submitting this PR, please make sure: -->

- [X] The code builds clean without any errors or warnings
- [X] The PR follows the [SK Contribution
Guidelines](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md)
and the [pre-submission formatting
script](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md#development-scripts)
raises no violations
- [X] All unit tests pass, and I have added new tests where possible
- [X] I didn't break anyone 😄

2025-05-21 09:29:03 +00:00

concepts

Python: Support structured outputs with Azure AI inference chat completion. (#12183 )

2025-05-21 09:29:03 +00:00

demos

Python: Update README.md (#11890 )

2025-05-06 18:02:41 +00:00

getting_started

Python: marked planners deprecated and removed all related items (#12058 )

2025-05-19 02:47:36 +00:00

getting_started_with_agents

Python: Update the AzureAIAgent packages, types, and APIs based on Azure SDK's new code (#12084 )

2025-05-19 23:43:40 +00:00

getting_started_with_processes

Python: Support callers passing in max supersteps for processes (#11798 )

2025-04-30 09:25:47 +00:00

learn_resources

Python: marked planners deprecated and removed all related items (#12058 )

2025-05-19 02:47:36 +00:00

__init__.py

Python: Adjust the learn file imports based on a previous refactor. (#6545 )

2024-06-04 19:40:12 +00:00

README.md

Python: Agent get_response API (#10701 )

2025-02-27 20:22:05 +09:00

SAMPLE_GUIDELINES.md

Python: improved chat history samples (#10737 )

2025-03-04 06:58:32 +00:00

service_settings.py

Python: allow settings to be created directly (#11468 )

2025-04-11 06:26:22 +00:00

sk_service_configurator.py

Python: allow settings to be created directly (#11468 )

2025-04-11 06:26:22 +00:00

README.md

Semantic Kernel Samples

Type	Description
`getting_started`	Take this step by step tutorial to get started with Semantic Kernel and get introduced to the key concepts.
`getting_started_with_agents`	Take this step by step tutorial to get started with Semantic Kernel Agents and get introduced to the key concepts.
`getting_started_with_processes`	Take this step by step tutorial to get started with Semantic Kernel Processes and get introduced to the key concepts.
`concepts`	This section contains focused samples which illustrate all of the concepts included in Semantic Kernel.
`demos`	Look here to find a sample which demonstrate how to use many of Semantic Kernel features.
`learn_resources`	Code snippets that are related to online documentation sources like Microsoft Learn, DevBlogs and others