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v0.2.0
Highlights
Learning that generalizes
- Dev-holdout refinement: patches are accepted only if they improve quality on a held-out split (
learn_rules(holdout_fraction=0.2)), with stratified splitting and failure-mode-clustered patch prompts. - Per-rule validated precision & support, Wilson-bounded ranking (
rank_rules()), and precision-based conflict resolution in the executor.
Robustness
- Catch-all regex ban, truncated-JSON rule recovery, and per-rule execution timeouts — an LLM-written rule can no longer hang the loop.
regexis now a core dependency (matching timeout guard).
Load & inspect rulesets
Rule.from_dictandRuleChef.load_rules(...): load a saved ruleset from a file/dict/list and immediately extract or evaluate with it.benchmarks/rule_report.py: browsable HTML report of a ruleset against gold data — per rule TP/FP with the matched span highlighted in context. Seebenchmarks/INSPECTING_RULES.md.
Evaluation
- Benchmark harnesses + committed results in
benchmarks/results/(TAB anonymization, ablation, HITL feedback repair, observation mode, and more).
Contributor infrastructure
- Issue forms with native types, PR rights-attestation checkbox enforced by CI, advisory DCO sign-off warning, Code of Conduct.
Install: pip install rulechef==0.2.0 · PyPI: https://pypi.org/project/rulechef/0.2.0/