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Sam Valladares 495a88331f feat: Vestige v1.6.0 — 6x storage reduction, neural reranking, instant startup 
Four internal optimizations for dramatically better performance:

1. F16 vector quantization (ScalarKind::F16 in USearch) — 2x storage savings
2. Matryoshka 256-dim truncation (768→256) — 3x embedding storage savings
3. Convex Combination fusion (0.3 keyword / 0.7 semantic) replacing RRF
4. Cross-encoder reranker (Jina Reranker v1 Turbo via fastembed TextRerank)

Combined: 6x vector storage reduction, ~20% better retrieval quality.
Cross-encoder loads in background — server starts instantly.
Old 768-dim embeddings auto-migrated on load.

614 tests pass, zero warnings.
2026-02-19 01:09:39 -06:00
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vestige-core feat: Vestige v1.6.0 — 6x storage reduction, neural reranking, instant startup 2026-02-19 01:09:39 -06:00
vestige-mcp feat: Vestige v1.6.0 — 6x storage reduction, neural reranking, instant startup 2026-02-19 01:09:39 -06:00