jx12n
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bb21e69ae6
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feat(m12): vector retrieval G1/G2 — recall harness, ANN in RETRIEVE, index tuning
m12p1 (measurement truth): TidalDb::vector_search_items pure k-NN probe +
POST /vector_search (standalone + region node, merge-by-distance) +
tidal-stress --verify-recall (deterministic id-keyed corpus, in-RAM brute-force
cosine oracle, open-loop ramp → recall@k + true p99 + read-knee + JSON/gate exit).
Repaired fabricated p99 columns (mean-as-p99) in social-scale.md / scale.rs.
Verified real: recall@10=0.9997 at 20k/1536-D vs brute-force.
m12p2 (G1 unblock): ANN candidate-gen wired into RETRIEVE — for_you=preference
vector, related=seed embedding (similar_to), graceful scan-fallback. Cached
per-signal-type top-K (signals/ledger/hot_top_k.rs, decay-order-invariant) so
trending serves O(K). related over HTTP (FeedQuery.similar_to). Harness gains
--feed-profile / --seed-preferences. Verified: trending retrieve p99 3.5-7.7ms.
m12p3 (G2): per-query ef_search now honored (RwLock epoch-guard with_expansion,
shared guard for same-ef concurrency) + dimension-aware brute→HNSW crossover
usearch_min_vectors(dim) + memory_usage() + examples/ann_grid_search.rs.
Measured 1536-D/100k clustered: default M=16/ef_c=400/F16/ef_s=200 clears
G1+G2 (recall 0.997, p99 1.4ms); F16 -0.25% vs F32; Int8 rejected (-28%).
Recall corpus is now clustered (Gaussian mixture) in grid + harness.
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2026-06-14 11:07:09 -06:00 |
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jx12n
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3bcfb3c576
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feat: Bazel build, crate docs/ai-lookup, docker images, and engine hardening
- Add BUILD.bazel across tidal, tidal-net, tidal-server, tidalctl for bzlmod build
- Add tidal/ crate docs (README, CHANGELOG, CONTRIBUTING, AGENTS, CLAUDE, API, ARCHITECTURE) and ai-lookup reference
- Add docker standalone/cluster/deploy images, compose, and prometheus config
- Harden WAL (batch format, writer, dedup, diagnostics), text syncer/collectors, and vector registry
- Expand tidalctl CLI and tests; restructure WAL/visibility integration test suites
- Refine tidal-net transport/client/server and tidal-server cluster/scatter-gather
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2026-06-07 18:29:38 -06:00 |
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jordan
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39ada28c6e
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feat: complete Milestones 2–4 — RETRIEVE query, vector index, ranking profiles, diversity, entity system, sessions
M2: RETRIEVE query pipeline with 5-stage execution (candidate → filter → score → diversify → limit),
usearch HNSW vector index, bitmap/range/universe filters, ranking profiles with signal scoring,
MMR diversity enforcement, and m2_uat integration tests.
M3: Entity system with typed metadata, relationship graph (follows/blocks/interactions),
creator entities, session tracking, and m3_uat integration tests.
M4: Advanced ranking with builtin functions (freshness, trending, controversy, wilson),
ranking executor with explain mode, query executor integration, benchmarks for
query/ranking/vector/filters/diversity, and m4_uat integration tests.
Includes: 9 new blog posts, marketing site updates, updated roadmap, and updated vision doc.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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2026-02-21 16:24:48 -07:00 |
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