Python 3.14: compatibility issue with default lazy annotations

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Highlighting the Python 3.14 compatibility requirements:

* base any data model classes passed to the SDK on Pydantic rather than `lmstudio.BaseModel`; or
* specify `from __future__ import annotations` to use string annotations instead of lazy ones (since `msgspec` handles those)

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`lmstudio-python` is affected by https://github.com/jcrist/msgspec/issues/847, so running on Python 3.14+ currently requires the use of `from __future__ import annotations` when defining structured response formats based on `lmstudio.BaseModel`.

The main SDK schema export classes already used string annotations to avoid forward referencing problems, so the PR adding 3.14 to CI (https://github.com/lmstudio-ai/lmstudio-python/pull/154) works around the issue by also adding `from __future__ import annotations` to the affected test modules.

Client applications relying on Pydantic for their data model classes won't be affected (beyond needing to update to Pydantic 2.12.0a1 or later), but those relying on `lmstudio.BaseModel` to define their structured response formats will currently also need to use `from __future__ import annotations` for their struct fields to actually get defined.

Begin with PR #154 and the affected test modules, then inspect the main SDK schema export classes mentioned in the issue. Check how structured response formats behave on Python 3.14 and compare the existing string-annotation workaround. Done means the compatibility requirement is covered consistently for these formats.

Written by the indexing model from the issue text.