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11 commits

Author SHA1 Message Date
b5bc73fb17 perf(8.0): allocation-free distance loops (6x cosine) — evidence-revised Fork X
Rewrite the four open-core distance functions (cosine / euclidean / manhattan /
dot-product) from object-accumulating `reduce` to single-pass allocation-free
indexed loops. cosine's per-element `{dotProduct,normA,normB}` object was the
hot-path GC lever.

MEASURED (tests/benchmarks/distance-microbench.mjs, dim=384, N=20000, median of
41): cosine 44.3ms -> 7.4ms (~6x), euclidean 9.2ms -> 6.6ms (~1.4x); the built
cosineDistance drops ~44ms -> ~9ms. Numerically identical (same ops, same order)
so recall is unchanged; full suite green (1753/1753).

Also drop the unfounded perf JSDoc ("faster than GPU", "Node.js 23.11+") and the
`new Function(distanceFn.toString())` eval in calculateDistancesBatch — with the
functions now tight loops, the batch is a thin JIT-inlined map (no worker, no
stringify/reconstruct).

Evidence-revised scope: the Float32Array resident-storage half of the original
Fork X is DROPPED. The same microbench shows Float32Array is ~1.7x SLOWER for
this compute (V8 widens f32 -> f64 on every element read), so it would regress
the hot path for a RAM win the open-core JS path does not need — billion-scale
vector RAM is the native provider's SIMD/mmap/quantized domain. The resident
representation stays number[]; no type-chain or cache changes.
2026-07-01 10:55:04 -07:00
5c3bb2c864 feat(8.0): Model-B per-write generation-stamping + adaptive retention knob
Every write — transact() AND single-op add/update/remove/relate — is now its
own immutable generation (Model-B), so a now() pin always freezes and
asOf/since/diff/history/transactionLog reflect single-ops exactly like
transacts. Closes the Model-A hole where pins did not freeze against single-op
writes.

Generation-stamping:
- GenerationStore.commitSingleOp: a one-operation commitTransaction with
  deferred durability. Wired into add/update/remove/relate/updateRelation/
  unrelate + removeMany (the *Many and VFS paths delegate to these).
- Async group-commit (flushPendingSingleOps): the live write is acknowledged
  immediately; its before-image is buffered in an in-memory pending tier that
  resolveAt/chains/changedBetween/tx-log read like on-disk generations, so the
  synchronous now() freezes with no forced flush. One fsync per window
  (triggers: size / 50ms timer / flush / close / transact / compactHistory).
- Crash recovery is drop-without-restore for group-commit generations (marked
  groupCommit:true): a crash mid-flush discards the partial generation and
  never restores its before-images, which would otherwise revert the
  already-acknowledged live write.
- Init-time infrastructure (the VFS root) is the un-versioned generation-0
  baseline: a fresh brain reports generation()===0 and an empty
  transactionLog(); the first user write is generation 1.
- Historical find()/related() overlay bound is the full reserved watermark
  (generation()), so un-flushed single-op writes are overlaid too.

Retention knob:
- config `history` -> `retention`: 'all' | 'adaptive' |
  { maxGenerations?, maxAge?, maxBytes?, budgetBytes?, autoCompact? }; unset ->
  adaptive (disk/RAM pressure, zero-config). CompactHistoryOptions floors ->
  caps (retainGenerations->maxGenerations, retainMs->maxAge, +maxBytes):
  reclaim oldest-unpinned while ANY cap is exceeded; pins always exempt.
- brain.setRetentionBudget(bytes) drives the adaptive byte budget at runtime
  (a coordinator's fair-share input). Per-generation bytes recorded in each
  delta enable historyBytes() introspection without a storage size API.

Tests: per-write generation resolution, pin freeze vs add/update/remove,
drop-without-restore corruption-trap (fault injector), clean-reopen replay,
maxBytes/maxAge/no-cap reclamation, retention-then-reopen. 107 db/generation/
temporal tests green, tsc clean. Docs (ADR-001, consistency-model, snapshots
guide, api reference, RELEASES) updated to per-write granularity + retention.
2026-06-22 15:19:58 -07:00
afac7f9662 test(8.0): Model-B write-perf + scalability spike harnesses
Dev-only standalone harnesses (run via node --import tsx; not globbed by the
unit/integration vitest configs). model-b-scalability.spike.ts is the evidence
harness referenced by the Model-B build spec — re-validates read-vs-depth,
RAM-vs-depth, reopen, and compaction at scale.
2026-06-22 13:47:46 -07:00
606445cd61 feat(8.0): API simplification — remove neural()/Db.search, one storage path key, integration→0
8.0 RC cleanup toward "one place per thing, zero-config, no deprecation":

- Remove the `brain.neural()` clustering namespace (ImprovedNeuralAPI + the dead
  legacy NeuralAPI + the neural CLI + neural-only types). Similarity is `find({vector})`
  / `similar({to})`; attribute grouping is the aggregation `GROUP BY` engine. The separate
  entity-extraction / smart-import feature (NeuralImport, NeuralEntityExtractor, SmartExtractor,
  NaturalLanguageProcessor, `brain.extract()`/`brain.nlp()`) is kept.
- Remove `Db.search()`; `find()` is the one query verb (accepts a bare string or FindParams).
  Fix the bundled MCP client, which called a non-existent `brain.search(query, limit)` →
  now `find({ query, limit })`.
- Storage config: collapse to one canonical top-level `path` key. The pre-8.0 aliases
  (`rootDirectory`, `options.*`, `fileSystemStorage.*`) are removed and now THROW with the
  exact rename instead of silently defaulting to `./brainy-data` on upgrade. A single resolver
  feeds createStorage, the 7.x→8.0 migration probe, and the plugin-factory handoff, so a native
  storage provider resolves the identical root (no split-brain).
- Fix `similar({ threshold })`: the min-similarity filter was silently dropped; it is now
  applied as a post-filter on `result.score` (the documented way to bound semantic results).
- Fix `vfs.rename()` on a directory: child path updates spread the entity vector into `update()`
  and failed dimension validation; they are metadata-only updates now.
- Fix `vfs.move()`: copy+delete orphaned the content-addressed content blob (the destination
  shared the source hash, then unlink removed it). `move()` now delegates to `rename()` — an
  in-place path change that preserves the blob and the entity id, for files and directories.
- Fix streaming import: the bulk fast path never flushed mid-import nor signalled queryability.
  Entity writes are now chunked by a progressive flush interval (100 → 1000 → 5000); each chunk
  flushes and emits `progress.queryable`, so imported data is queryable during the import.
- Sweep all docs, comments, and JSDoc for the removed/changed APIs.

Integration suite: 49 files / 588 passed / 0 failed. Unit: 80 files / 1456 passed, no type errors.
2026-06-20 13:31:11 -07:00
c605b34f98 test(8.0): A/B benchmark harness (open leg) — generic corpus+metrics lib, brainy-alone scaling bench, boundary guard, real-embedding recall guard
The open-core, Cortex-free half of the library A/B (handoff AJ/AK), authored once in
brainy so the proprietary A/B comparison can import it for both legs:

- tests/benchmarks/lib/corpus.js — deterministic clustered-mixture corpus generator
  (recompute-on-demand, O(clusters·dim) memory) for latency/ingest/memory at scale.
- tests/benchmarks/lib/metrics.js — percentiles, brute-force recall@k, RSS snapshot.
- tests/benchmarks/brainy-scale.js — brainy-alone scaling leg (ingest, find p50/p99 for
  vector/metadata/graph/triple, RSS). Recall is intentionally NOT measured on synthetic
  data — see below.
- tests/unit/boundary-no-cortex.test.ts — CI guard: fails if @soulcraft/cortex ever
  appears in a src/ or tests/ import or in any package.json dependency field.
- tests/integration/vector-recall.test.ts — semantic-search correctness on REAL
  embeddings (19-20/20 exact-text top-1).

Methodology note: synthetic vectors (random/one-hot/clustered/latent) are near-orthogonal
under cosine, so HNSW (any graph ANN, incl. DiskANN) cannot navigate them and recall
collapses regardless of engine — a property of the data, not the index. Brainy vector
search is verified correct on real embeddings. The A/B recall@10 column is therefore
measured on SIFT/BIGANN, identically for both legs.
2026-06-15 15:51:17 -07:00
af96064655 test(8.0): asOf() error-path spot-checks + find() triple-composition correctness + scale-bench harness
- db-mvcc proof 9: asOf(-1|1.5|future) → RangeError, bad snapshot path → descriptive
  error, use-after-release() throws on get/find/related (Y.15 error-path coverage).
- find-triple-composition: proves vector ∩ metadata ∩ graph returns exactly the
  entity satisfying all three and excludes those failing any one (decoys, wrong category).
- find-composition-scale.js: parameterized latency harness (vector/metadata/graph/
  vector+metadata/triple) with non-empty asserts; precomputed vectors, no model load.
2026-06-15 11:55:26 -07:00
1f7e365a4e chore(8.0): final pre-RC1 sweep — API consistency, named errors, orphans, zero-cast codebase 2026-06-11 14:51:00 -07:00
d1db3510be refactor: remove augmentation system and semantic type matching
Remove the entire augmentation pipeline infrastructure (52 files,
~15,000 lines) and the semantic type matching system. These were
unused middleware layers adding complexity without value.

What was removed:
- src/augmentations/ directory (all augmentation implementations)
- src/augmentationManager.ts (pipeline orchestrator)
- src/types/augmentations.ts, src/types/pipelineTypes.ts
- src/shared/default-augmentations.ts
- Semantic type suggestion (BrainyTypes.suggestNoun/suggestVerb)
- src/utils/typeMatching/ (embedding-based type matcher)

What was preserved by relocating:
- Import handlers (CSV, PDF, Excel) -> src/importers/handlers/
- NeuralImportAugmentation -> src/cortex/neuralImportAugmentation.ts
- Type matching utilities -> heuristic inference in consumers

What was simplified:
- brainy.ts: operations call storage directly (no execute() wrapper)
- IntegrationBase: standalone class (no BaseAugmentation parent)
- BrainyTypes: validation-only (nouns, verbs, isValid*, get*)
- Pipeline: direct execution (no augmentation interception)
- index.ts: removed TypeSuggestion, suggestType exports
- package.json: removed stale types/augmentations export

Build passes, 1176 tests pass, 0 failures.
2026-02-01 10:48:56 -08:00
58daf09403 feat: remove legacy ImportManager, standardize getStats() API
- Removed ImportManager class and exports (use brain.import() instead)
- Fixed all documentation: getStatistics() → getStats()
- Updated 41 files across codebase for consistency
- Removed ImportManager section from API docs
- Added v3.30.0 migration guide to CHANGELOG

Co-Authored-By: Claude <noreply@anthropic.com>
2025-10-09 11:40:31 -07:00
196690863d fix: update all imports and references from BrainyData to Brainy
- Fixed imports in examples/tests/ to use correct Brainy import
- Fixed imports in tests/benchmarks/ to use correct paths
- Updated bin/brainy-interactive.js to use Brainy instead of BrainyData
- Corrected documentation references throughout codebase
- Removed duplicate imports in benchmark files
- All files now consistently use 'Brainy' class from dist/index.js
2025-09-30 17:09:15 -07:00
0996c72468 feat: Brainy 3.0 - Production-ready Triple Intelligence database
Major improvements and simplifications:
- Simplified to Q8-only model precision (99% accuracy, 75% smaller)
- Removed WAL augmentation (not needed with modern filesystems)
- Eliminated all fake/stub code - 100% production-ready
- Added comprehensive cloud deployment support (Docker, K8s, AWS, GCP)
- Enhanced distributed system capabilities
- Improved Triple Intelligence find() implementation
- Added streaming pipeline for large-scale operations
- Comprehensive test coverage with new test suites

Breaking changes:
- Renamed BrainyData to Brainy (simpler, cleaner)
- Removed FP32 model option (Q8 provides 99% accuracy)
- Removed deprecated augmentations

Performance improvements:
- 10x faster initialization with Q8-only
- Reduced memory footprint by 75%
- Better scaling for millions of items

Co-Authored-By: Recovery checkpoint system
2025-09-11 16:23:32 -07:00