 Dragan Spiridonov
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6b249c034f
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feat: RuVector integration phases 1-4 — native HNSW, neural routing, safety gates, differentiation
Implements 23 tasks across 4 phases per docs/implementation/ruvector-integration-plan.md:
Phase 1 — Foundation (make what we have faster):
- Native HNSW backend via @ruvector/router (150x search speedup, ADR-081)
- Metadata filtering layer with composable AND/OR/NOT/FIELD expressions
- Temporal tensor compression (Int8Array quantization, 4x memory reduction)
- Deterministic golden-ratio dithering for cross-platform reproducibility
- 15 feature flags (all default false) with CLI profiles
Phase 2 — Intelligence (make agents smarter):
- Neural TinyDancer router with REINFORCE policy gradient (ADR-082)
- SONA three-loop enhancement (MicroLoRA 0.18μs/adapt via WASM)
- Cross-domain transfer learning with Thompson Sampling (ADR-084)
- Regret tracking with log-log regression growth classification
Phase 3 — Safety (make agents trustworthy):
- Sheaf-gated test validation via prime-radiant CohomologyEngine
- Coherence-gated agent actions (3-filter pipeline, ADR-083)
- Witness chain audit trail with SHA-256 hash linking
- HNSW health monitoring with spectral analysis
Phase 4 — Differentiation (make AQE unique):
- Cognitive container export/import (RVF v2)
- DAG attention scheduler for dependency-aware test ordering
- CNN visual regression with spatial pooling embeddings
- Behavior tree orchestration (Sequence/Selector/Parallel)
- Reasoning QEC with majority-vote consensus
- Browser QE dashboard scaffolding
Also: remove obsolete v2-to-v3-migration test (source already removed),
add ADR-081 through ADR-085, research docs, benchmarks, and integration
test suites for all 4 phases.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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2026-03-16 17:37:43 +00:00 |
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