Memory leak in parse_response usage of pydantic

[avilaton]

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Changes being requested

Address a memory leak in parse_response detected using the OpenAI client in a webserver context (gunicorn, gevent)

Additional context & links

Problem

client.responses.parse() can trigger sustained memory growth on pydantic >= 2.11 (see #1181).

The issue is that parse_response() used subscripted runtime generic aliases (for example ParsedResponse[T]) when calling construct_type_unchecked(). In pydantic v2, this can cause repeated runtime generic specialization/schema work in a hot path.

Fix

Use the non-subscripted runtime classes in parse_response() when calling construct_type_unchecked():

• ParsedResponseOutputText[TextFormatT] → ParsedResponseOutputText
• ParsedResponseOutputMessage[TextFormatT] → ParsedResponseOutputMessage
• ParsedResponse[TextFormatT] → ParsedResponse

Why this is safe

construct_type_unchecked() constructs models loosely and does not require runtime generic specialization for correctness here. parse_text() still produces the typed parsed payload, and the return type for callers remains ParsedResponse[TextFormatT].

Tests

• Added a regression test in tests/lib/responses/test_parsing.py that fails if parse_response() routes through _validate_non_model_type.
• Added an opt-in memory characterization test (OPENAI_RUN_MEMORY_TESTS=1) in tests/lib/responses/test_parsing.py.
• Ran responses suites against the mock server: 158 passed.