2 Commits

Author	SHA1	Message	Date
freemo	583e6b7ea2	feat(correcting-plans): implement Predictive Error Prevention (Layer 4) with Error Pattern Database ... Implement spec-mandated Layer 4 Predictive Error Prevention system: - ErrorPattern domain model with pattern text, historical failures, preventive checks, frequency tracking, and keyword-based matching. - ErrorPatternRepository with in-memory CRUD + context-matching query. - ErrorPatternService with record_failure(), match_patterns(), and get_statistics() methods. - Wire into plan execution via plan_lifecycle_service pre-execution hook. - Add error pattern statistics to CLI diagnostics output. Behave BDD: 11 scenarios covering recording, matching, formatting, stats. Robot Framework: 3 integration smoke tests. ASV benchmarks: pattern matching performance. ISSUES CLOSED: #571	2026-03-08 21:53:21 -04:00
freemo	4221582368	feat(acms): implement pipeline Phase 3 components ... Implemented the remaining ACMS pipeline components and advanced context strategies: Pipeline Phase 3: - FragmentOrdererProtocol + RelevanceCoherenceOrderer: orders fragments by relevance while maintaining narrative coherence via UKO node prefix grouping. Groups related fragments together, sorts groups by max relevance, and within groups orders by relevance desc / depth asc. - PreambleGeneratorProtocol + ProvenancePreambleGenerator: generates provenance preamble with strategy contributions (fragment counts and token percentages), confidence indicators (avg/min/max), tier and depth distribution, UKO node coverage, and coverage gap detection. Advanced Strategies: - ArceStrategy (quality 0.95): adaptive recursive context expansion with iterative multi-backend refinement and configurable iteration limit (default 5) to prevent unbounded refinement. Uses composite scoring (relevance + depth + diversity) with contextual boosting for fragments related to the current top-ranked anchor set. - TemporalArchaeologyStrategy (quality 0.5): historical context retrieval from graph+cold backends. Prioritises cold-tier fragments using a temporal scoring model (tier bonus + relevance + depth). - PlanDecisionContextStrategy (quality 0.7): decision history retrieval from warm/cold backends. Prioritises warm then cold tier fragments for correction and retry scenarios. All strategies registered in strategy registry with correct quality scores and backend requirements. All components implement their respective Protocol interfaces and can be injected into the ContextAssemblyPipeline via constructor dependency injection. Tests: - 33 BDD scenarios in features/acms_pipeline_phase3.feature - Robot Framework integration tests in robot/acms_pipeline_phase3.robot - ASV performance benchmarks in benchmarks/acms_pipeline_phase3_bench.py ISSUES CLOSED: #545	2026-03-07 14:53:18 +00:00