fix: RandomForestEstimator honors random_seed config

[immu4989]

Why are these changes needed?

Migrate RandomForestEstimator from a hardcoded random_state=12032022 in config2params to the random_seed-aware pattern used by the recently fixed estimators (#1364, #1374, #1376, #1541, #1546).

Before this change, callers passing AutoML(random_seed=N).fit(...) would get the same internal RandomForest/ExtraTrees random_state (always 12032022) regardless of N , inconsistent with how CatBoostEstimator, ElasticNetEstimator, SVCEstimator, SGDEstimator, and LRL1Classifier already behave. This brings RandomForestEstimator and the inheriting ExtraTreesEstimator in line with the rest of the audited estimator family.

The default value is preserved (12032022), so the existing reproducibility tests for rf and extra_tree in test/automl/test_classification.py and test/automl/test_regression.py continue to pass unchanged.

Related issue number

Tracking issue: #1540
Pattern reference: #1541 (SGD), #1546 (LRL1)

Test plan

• pytest test/automl/test_classification.py test/automl/test_regression.py -k "reproducibility and (rf or extra_tree)" — 8/8 pass
• pre-commit run --files flaml/automl/model.py — all hooks pass
• CI green on the PR

Checks

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• I've included any doc changes needed for https://microsoft.github.io/FLAML/. See https://microsoft.github.io/FLAML/docs/Contribute#documentation to build and test documentation locally.
• I've added tests (if relevant) corresponding to the changes introduced in this PR.
• I've made sure all auto checks have passed.