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Python: [BREAKING] Remove deprecated Python OpenAI/Azure AI surfaces (#4990)
* [BREAKING] Remove deprecated Python OpenAI/Azure AI surfaces Also clean up follow-on docs, environment guidance, package metadata, and lab test stability. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix deleted semantic-kernel sample links Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address PR review feedback Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * improve foundry language * Fix A2A Foundry sample regression Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
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@@ -1,3 +1,3 @@
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AZURE_AI_PROJECT_ENDPOINT="<your-project-endpoint>"
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AZURE_AI_MODEL_DEPLOYMENT_NAME_WORKFLOW="<your-model-deployment>"
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AZURE_AI_MODEL_DEPLOYMENT_NAME_EVAL="<your-model-deployment>"
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FOUNDRY_PROJECT_ENDPOINT="<your-project-endpoint>"
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FOUNDRY_MODEL_WORKFLOW="<your-model-deployment>"
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FOUNDRY_MODEL_EVAL="<your-model-deployment>"
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@@ -99,7 +99,7 @@ def fetch_agent_responses(openai_client: OpenAI, workflow_data: dict[str, Any],
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def create_evaluation(openai_client: OpenAI, deployment_name: str | None = "gpt-5.2") -> EvalCreateResponse:
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"""Create evaluation with multiple evaluators."""
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deployment_name = os.environ.get("AZURE_AI_MODEL_DEPLOYMENT_NAME", deployment_name)
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deployment_name = os.environ.get("FOUNDRY_MODEL", deployment_name)
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data_source_config = {"type": "azure_ai_source", "scenario": "responses"}
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testing_criteria = [
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@@ -199,8 +199,8 @@ async def main():
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openai_client = create_openai_client()
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# Model configuration
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workflow_agent_model = os.environ.get("AZURE_AI_MODEL_DEPLOYMENT_NAME_WORKFLOW", "gpt-4.1-nano")
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eval_model = os.environ.get("AZURE_AI_MODEL_DEPLOYMENT_NAME_EVAL", "gpt-5.2")
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workflow_agent_model = os.environ.get("FOUNDRY_MODEL_WORKFLOW", "gpt-4.1-nano")
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eval_model = os.environ.get("FOUNDRY_MODEL_EVAL", "gpt-5.2")
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# Focus on these agents, uncomment other ones you want to have evals run on
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agents_to_evaluate = [
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