fix: resolve PydanticUserError with defer_build=True in multiprocess forkserver workers (pydantic >= 2.12)

[SanskaarUndale21]

Summary

Fixes #3079

When defer_build=True (the default via DEFER_PYDANTIC_BUILD), pydantic wraps
__pydantic_core_schema__ in a MockCoreSchema. Accessing schema["type"] inside
_get_extra_fields_type triggers a lazy rebuild that uses a hardcoded stack depth
(5 frames) to locate forward-reference namespaces. In multiprocess forkserver
workers the call stack is shallower/different, so the heuristic cannot find the
openai types namespace. Before pydantic 2.12 this silent failure was mostly harmless;
starting in 2.12 MockCoreSchema._get_built() raises PydanticUserError when the
rebuild fails, causing ~0.6 % of requests to crash in large forkserver deployments.

Changes

• src/openai/_models.py — _get_extra_fields_type:
  • Checks cls.__pydantic_complete__ before touching the schema; if the model is
    still deferred, calls cls.model_rebuild(_types_namespace=vars(module)) using the
    class's own module from sys.modules. This bypasses the fragile stack-depth
    heuristic and resolves forward references correctly regardless of call-stack depth.
  • Wraps the subsequent schema access in a try/except so that any residual failure
    degrades gracefully (returning None) instead of propagating an unhandled exception.

Test plan

• Verify existing test suite passes (pytest tests/)
• Manually reproduce with multiprocess forkserver + pydantic 2.12: create a pool
  with forkserver start method, import openai inside workers, deserialize a
  ChatCompletion response — confirm no PydanticUserError raised
• Run with DEFER_PYDANTIC_BUILD=true (default) and DEFER_PYDANTIC_BUILD=false

[Copilot]

Pull request overview

Fixes an intermittent PydanticUserError triggered by Pydantic v2.12’s deferred schema rebuild (defer_build=True) in multiprocess forkserver workers by proactively rebuilding models using the model’s module namespace and by guarding schema access.

Changes:

• Add proactive model_rebuild() when __pydantic_complete__ is false, using the class’s module namespace from sys.modules.
• Wrap __pydantic_core_schema__ access in error handling to avoid propagating rebuild failures during construction.

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[Copilot]

This change targets a forkserver + deferred-build regression in pydantic >=2.12, but there doesn’t appear to be test coverage that exercises the deferred rebuild (MockCoreSchema) path in a forkserver worker. Adding a regression test (skipping platforms without forkserver) would help prevent reintroducing this crash.

[Copilot]

cls.model_rebuild(_types_namespace=...) relies on a private Pydantic kwarg; if that kwarg is absent/renamed in some supported pydantic v2 versions, this will raise (e.g. TypeError). Returning None immediately in that case skips the later schema-based path that might still succeed. Consider detecting whether _types_namespace is supported (e.g. via inspect.signature) and/or falling back to calling model_rebuild() without it, and avoid returning early so behavior degrades minimally across versions.

Suggested change

	try:
	cls.model_rebuild(_types_namespace=vars(module) if module is not None else None)
	except Exception:
	return None
	model_rebuild = cls.model_rebuild
	try:
	supports_types_namespace = "_types_namespace" in inspect.signature(model_rebuild).parameters
	except (TypeError, ValueError):
	supports_types_namespace = False
	try:
	if supports_types_namespace:
	model_rebuild(_types_namespace=vars(module) if module is not None else None)
	else:
	model_rebuild()
	except TypeError:
	try:
	model_rebuild()
	except Exception:
	pass
	except Exception:
	pass

[Copilot]

The broad except Exception around schema access will swallow unexpected errors (e.g. schema shape changes causing KeyError, or accidental AttributeError) and silently treat extras as untyped. To avoid masking real bugs, consider narrowing this to the specific failure you’re targeting (notably pydantic.errors.PydanticUserError from deferred rebuild) and letting truly unexpected exceptions surface.