Fix #4478: Detect Azure OpenAI models by endpoint, not just deployment name

[devin-ai-integration]

Fix #4478: Detect Azure OpenAI models by endpoint, not just deployment name

Summary

AzureCompletion.is_openai_model was determined solely by checking model name prefixes (gpt-, o1-, text-). Since Azure deployment names can be arbitrary (e.g. gpt5nano), this caused is_openai_model to be False for custom-named deployments, which silently broke:

• response_model / structured output (JSON schema not sent to API, validation skipped)
• Tool/function calling (tools not included in request params)
• supports_function_calling() returning False

Fix: Compute is_azure_openai_endpoint first, then use it as an additional signal — if the endpoint matches openai.azure.com + /openai/deployments/, it's an OpenAI model regardless of deployment name. Non-OpenAI models on Azure AI Inference endpoints (e.g. models.inference.ai.azure.com) are unaffected.

The production code change is 6 lines in AzureCompletion.__init__(). 7 new regression tests added covering detection, response_model parsing, params preparation, tool inclusion, streaming, and negative cases.

Review & Testing Checklist for Human

• Verify the assumption that openai.azure.com/openai/deployments/ always implies an OpenAI model — could a non-OpenAI model ever be deployed at this endpoint pattern?
• Ideally test end-to-end with an actual Azure OpenAI deployment using a custom name (e.g. gpt5nano) and a response_model to confirm structured output works
• Confirm existing test_azure_deepseek_model_support and test_azure_mistral_and_other_models still correctly identify non-OpenAI models as is_openai_model=False (they pass in CI, but worth a glance)

Notes

• All 60 existing Azure tests pass, plus 7 new tests
• Requested by: João
• Link to Devin run

[devin-ai-integration]

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