✨ Add configurable RL pass timeouts

[flowerthrower]

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Description

Adds an opt-in timeout for individual RL compilation passes during training and inference.

• Add pass_timeout to Predictor.train_model for training.
• Add a separate pass_timeout to Predictor.compile_as_predicted, rl_compile, and qcompile for inference.
• Keep pass execution unbounded by default.
• Truncate the current episode through the existing action-error path when a pass times out.
• Restore per-call timeout settings so singleton predictors do not leak them between training and inference calls.

The lightweight implementation uses POSIX real-time signals on the main thread. Unsupported platforms or worker threads emit a warning and continue without a timeout.

This PR is stacked on #782.

Codex materially assisted with implementation, tests, validation, and drafting this description. Human review remains required.

Validation

• uvx nox -s lint
• focused pass-timeout tests (6 passed)
• existing non-training RL predictor tests (29 passed, 2 deselected)

The broader local suite reached an existing BQSKit worker startup failure (ConnectionRefusedError) and was stopped after making no progress. CI remains the authoritative integration run.

Checklist

• The pull request only contains commits that are focused and relevant to this change.
• I have added appropriate tests that cover the new/changed functionality.
• I have updated the documentation to reflect these changes.
• I have added entries to the changelog for any noteworthy additions, changes, fixes, or removals.
• I have added migration instructions to the upgrade guide (if needed).
• The changes follow the project's style guidelines and introduce no new warnings.
• The changes are fully tested and pass the CI checks.
• I have reviewed my own code changes.

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[codecov]

Codecov Report

❌ Patch coverage is 78.33333% with 13 lines in your changes missing coverage. Please review.

Files with missing lines	Patch %	Lines
src/mqt/predictor/rl/predictorenv.py	77.7%	10 Missing ⚠️
src/mqt/predictor/rl/predictor.py	80.0%	3 Missing ⚠️

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