Promotes `subtype?: string` to a top-level standard field on every entity,
alongside `type` / `confidence` / `weight`. Flat string, no hierarchy — the
consumer-chosen vocabulary for sub-classifying entities within a NounType
(Person → employee/customer, Document → invoice/contract, etc.).
Layer 1 — subtype field + rollup
- HNSWNounWithMetadata.subtype + STANDARD_ENTITY_FIELDS entry
- Entity / Result / AddParams / UpdateParams / FindParams threading
- add()/update() persist subtype on storageMetadata + entityForIndexing
- get()/find() route through the standard-field fast path
- subtypeCountsByType (Map<NounTypeIdx, Map<subtype, count>>) on
BaseStorage, mirrored after nounCountsByType with the same self-heal
rebuild and persisted to _system/subtype-statistics.json
- brain.counts.bySubtype(type, subtype?) — O(1) point + breakdown
- brain.counts.topSubtypes(type, n) — top-N by count
- brain.subtypesOf(type) — distinct subtypes seen
- find({ type, subtype }) and find({ subtype: ['a','b'] }) on the fast path
Layer 2 — trackField for other facets
- brain.trackField(name, { perType?, values? }) registers a field for
cardinality + per-NounType breakdown stats. Backed by the aggregation
engine (auto-defines __fieldCounts__<name>), backfill-on-define applies.
- brain.counts.byField(name, { type? }) returns value frequencies
- Optional vocabulary whitelist rejects off-vocabulary writes at add/update
Layer 3 — generic migrateField
- brain.migrateField({ from, to, readBoth?, batchSize?, onProgress? })
streams every entity, copies the value from one path to another, and
(unless readBoth) clears the source. Supports top-level standard fields,
metadata.X, and data.X paths. Idempotent — safe to re-run.
Docs
- New guide: docs/guides/subtypes-and-facets.md (Layer 1 + 2 + 3)
- README, DATA_MODEL, QUERY_OPERATORS, api/README, finite-type-system,
quick-start all treat subtype as a core primitive with anonymous example
vocabularies (employee/customer/invoice/milestone).
Tests
- 26 new integration tests covering write/read/update/delete round-trips,
counts rollup decrement + re-route on mutation, trackField + byField
with and without perType, vocabulary whitelist enforcement, and
migrateField for metadata.X → subtype and data.X → subtype paths
including readBoth deprecation-window semantics.
Unit suite: 1468/1468 passing. Type-check + build clean.
- groupBy now supports { field, unnest: true }: an entity contributes once per
distinct element of an array field (tag frequency / faceted counts). Duplicate
elements on one entity count once; an empty/missing array joins no group. The
incremental add/update/delete paths fan out across the unnested groups.
- extractEntities/extractConcepts batch-embed the unique candidate spans in one
embedBatch call instead of one embed() per candidate (N sequential model calls);
falls back to per-candidate embedding if the batch fails. No behavior change.
New report APIs:
- brain.queryAggregate(name, params) returns the clean AggregateResult[] shape
({ groupKey, metrics, count }) directly, instead of the search-Result wrapper that
find({ aggregate }) returns.
- HAVING: find({ aggregate, having }) and queryAggregate filter groups by computed
metric values (e.g. revenue > 1000), complementing where (which filters group keys).
Evaluated per group: O(groups), independent of entity count.
Fixes (all reproducible on Node; surfaced under Cortex+Bun by Memory):
- Aggregate backfill-on-define: defining an aggregate over a store that already holds
matching entities returned []. It now backfills from existing entities on first query
(storage-agnostic via getNouns), so it works under durable backends that reopen
pre-populated. groupBy:['noun'] resolves to the entity type; find({ aggregate }) rows
expose groupKey/metrics/count at the top level.
- Multi-hop find({ connected: { depth, via } }) honors depth and via at every hop
(was 1-hop only, with verb filtering applied to hop 1 only); BFS bounded by limit.
- extractEntities no longer bleeds a neighbour's type indicator across candidates; each
candidate is typed by its own span. Also fixes the "Dr." title pattern.
Adds real-embedding regression tests; full unit suite green.
Per the Cortex team's audit, the BR-CX-INTERFACE-GAP boot crash was a
build/install artifact (stale node_modules, lockfile drift, Docker cache,
bundler quirks), not a plugin-bundles-brainy version-skew issue. Cortex's
MmapFileSystemStorage extends FileSystemStorage and inherits all 6
multi-process helpers via the prototype chain at runtime; the dynamic
ESM import to @soulcraft/brainy is preserved in cortex's dist.
- Rewrote the hasStorageMethod() doc comment to credit the real cause.
- Updated the init-time warning to point operators at the actual fix:
clean install or container rebuild to refresh node_modules.
- New docs/concepts/storage-adapters.md documenting the inheritance
contract: extend FileSystemStorage to inherit the multi-process
helpers, override supportsMultiProcessLocking() -> true to activate.
Includes a minimum checklist for adapter authors.
- New docs/architecture/multiprocess-storage-mixin.md as a future-
direction note: extracting the 7 methods into a
MultiProcessSafeStorage interface/mixin is the architecturally clean
next step, deferred to v8 or until a second multi-process capability
lands.
No behavior changes. Ships with the next release.
Filesystem storage now enforces single-writer, many-reader semantics.
A second writer on the same data directory throws at init time with the
holder's PID, hostname, and heartbeat — replacing the previous silent
stale-reads failure mode.
- New: `Brainy.openReadOnly()` — coexists with a live writer, every
mutation throws clearly.
- New: writer lock at `<rootDir>/locks/_writer.lock` with 10s heartbeat
and stale-detection (PID liveness + heartbeat freshness).
- New: cross-process flush-request RPC (filesystem-based, no signals)
so inspectors can force fresh state on demand.
- New: `brain.stats()`, `brain.explain(findParams)`, `brain.health()`
for operator-facing introspection.
- New: `brainy inspect` CLI with 13 subcommands (stats, find, get,
relations, explain, health, sample, fields, dump, watch, backup,
repair, diff), all read-only by default.
- Same-PID re-opens allowed with a warning (preserves test "simulate
restart" patterns).
- Storage instances passed directly via `storage: new MemoryStorage()`
are now honoured instead of silently falling through to the
filesystem auto-detect path.
Brainy + Cortex compose under this model — the lock covers both because
they share `rootDir`, Cortex segments are immutable mmap files, and
MANIFEST updates use atomic-rename.
Code blocks with Unicode box-drawing characters render poorly in web
doc viewers — font alignment breaks and the styled container creates
a visual box-in-a-box. Replaced with a bullet list (before) and a
bold statement (after) that render cleanly at any size and theme.
Replace flat 15-row table with a Before/After ASCII diagram plus a
capability grid (Search/Graph/Filter/VFS/Branch/Import) with competitors
grouped by category. Add new What Can You Build? section with generic
use cases and Built with Brainy showcase. Tighten header copy.
Adds docs/eli5.md — a jargon-free explanation of Brainy and Cortex
using everyday analogies (smart librarian, turbocharger). Targets
non-technical readers who want to understand the project before diving
into the API. Links added at the top of README and in the Documentation
section index.
All code examples in installation.md and quick-start.md were tagged
as javascript — converted to typescript throughout.
quick-start.md also gets explicit type annotations:
- reactId/nextId declared as string (return type of brain.add)
- results declared as FindResult[]
- results[0].data and results[0].score shown in console.log example
Add YAML frontmatter (slug, public, category, template, order) to 8
existing docs and 2 new getting-started guides (installation, quick-start).
Include docs/**/*.md in npm package files so the portal sync-docs script
can read them from node_modules after publish.
Update CLAUDE.md with docs pipeline trigger phrases and release checklist.
Add a write-time incremental aggregation engine that maintains running
totals on every add/update/delete for O(1) read performance. Integrates
into brain.find({ aggregate }) for a unified query API.
Core features:
- AggregationIndex with defineAggregate()/removeAggregate() API
- Five aggregation operations: SUM, COUNT, AVG, MIN, MAX
- GROUP BY with multiple dimensions including time windows
- Time window bucketing: hour, day, week, month, quarter, year, custom
- Materialization of results as NounType.Measurement entities
- Debounced persistence of definitions and state to storage
- Definition change detection via FNV-1a hashing with auto-rebuild
- Infinite loop prevention for materialized entities
- 'aggregation' plugin provider key for native acceleration
- Lazy initialization (created on first defineAggregate() call)
- 73 tests (unit + integration) covering all functionality
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Store data opaquely in add() and update() instead of spreading object
properties into top-level metadata. data is for semantic search (HNSW),
metadata is for structured where-filter queries (MetadataIndex).
- Fix numeric range queries in MetadataIndex — use numeric-aware comparison
instead of lexicographic string comparison for normalized values.
- Add data field to RelateParams and Relation types for relationship content.
- Add where.type → where.noun alias in metadata-only find() path.
- Rewrite README: focused ~350 lines from 791, quick start first, feature
showcase with mini-snippets, organized doc links, no version callouts.
- Add DATA_MODEL.md and QUERY_OPERATORS.md reference docs.
- Remove 10 outdated/redundant doc files consolidated into API reference.
- Improve JSDoc on Entity, Relation, AddParams, FindParams, and core methods.
- Fix tests asserting data properties appear in metadata (data model violation).
- Deprecate verb.source/target in favor of from/to (public) and sourceId/targetId (storage).
Plugins are no longer auto-detected. Updated README and PLUGINS.md
to show explicit plugins config, document all config values, and
fix manual registration example to use brain.use() API.
Fix critical wiring bugs that prevented plugin-provided implementations
from being used at runtime. All CRUD operations, fork/checkout/clear,
batch embedding, neural APIs, and VFS path resolution now properly
dispatch through the plugin registry.
Changes:
- Wire graphIndex to storage for getVerbsBySource() fast path
- Replace instanceof checks with duck-typing (indexIsTypeAware flag)
so plugin HNSW indexes work in add/update/delete/search
- Add createIndex() shared helper for plugin HNSW factory
- Fix fork/checkout/clear to use plugin factories for metadataIndex,
graphIndex, and HNSW instead of hardcoding JS constructors
- Add three-tier embedBatch priority: embedBatch > embeddings > WASM
- Skip WASM warmup/eagerEmbeddings when plugin provides embeddings
- Fix PathResolver metadataIndex access (was looking on storage)
- Use global UnifiedCache in SemanticPathResolver
- Wire plugin distance function through neural APIs
- Add diagnostics() method and CLI command for provider inspection
- Add requireProviders() for production fail-fast assertions
- Add init-time provider summary log
- Add plugin developer documentation (docs/PLUGINS.md)
- Export DiagnosticsResult type
- Switch vitest pool from threads to forks for process isolation
- Disable v8 coverage by default (causes vitest worker RPC timeout)
- Increase hookTimeout 30s to 60s for MetadataIndexManager init under load
- Reduce O(1) space test entity count, replace brittle timing assertions
- Add docs/guides/storage-adapters.md with verified batch config values
brain.add() was generating 26-40 immediate cloud writes per call, causing
HTTP 429 rate limit errors and high latency on GCS/S3/R2/Azure. Three-layer
fix: (1) deferred metadata writes with dirty-marking, (2) MetadataWriteBuffer
for write coalescing, (3) retry/backoff on all cloud storage adapters.
The __words__ keyword index stores 50-5000 entries per entity (one per
word), which inflated avg entries/entity well above the corruption
threshold of 100. This caused:
1. validateConsistency() to falsely detect corruption on every startup,
triggering unnecessary clearAllIndexData() + rebuild() cycles
2. getStats() to log false "Metadata index may be corrupted" warnings
and report inflated totalEntries/totalIds stats
Both methods now skip __words__ when counting, so stats and health
checks reflect metadata fields only (noun, type, createdAt, etc.).
Keyword search is unaffected since the __words__ field index itself
is not modified.
Replace document-centric categories (prose/heading/code/label) with a
universal set that works across documents, code, and UI:
- title: headings, identifiers, labels, JSON keys
- annotation: comments, docstrings, captions, alt text
- content: paragraphs, list items, flowing text
- value: string literals, numbers, form values
- code: unparsed code blocks
- structural: keywords, operators, punctuation
Built-in extractors now produce title/content/code. All 6 categories
are available for custom parsers (e.g. tree-sitter).
Also adds inline code detection in Markdown: backtick spans within
prose lines are split into separate code/content segments.
Fix highlight() hanging on structured text input by addressing 3 root causes:
1. embedBatch() now uses native WASM batch API (single forward pass instead
of N individual embed() calls via Promise.all)
2. highlight() auto-detects content type (plain text, rich-text JSON, HTML,
Markdown) and extracts meaningful text segments. Supports TipTap, Slate.js,
Lexical, Draft.js, and Quill Delta formats. New contentType hint and
contentExtractor callback for custom parsers.
3. Semantic matching phase has 10s timeout - falls back to text-only matches
instead of hanging indefinitely.
Also fixes extractTextContent() array check: uses type-based detection
(typeof data[0] === 'number') instead of length-based (data.length > 10)
so arrays of objects are properly indexed for text search.
New types: ContentType, ContentCategory, ExtractedSegment
New fields: HighlightParams.contentType, HighlightParams.contentExtractor,
Highlight.contentCategory
- Add textMatches, textScore, semanticScore, matchSource to search results
- Add highlight() method for zero-config text + semantic highlighting
- Increase word indexing limit to 5000 (handles articles/chapters)
- Optimize findMatchingWords() with O(1) fast path for semantic-only results
- Add production safety limits (500 chunks for highlight)
- Add comprehensive tests for new features (35 tests)
- Update docs with match visibility and highlight() API
New public APIs:
- embedBatch(texts): Batch embed multiple texts efficiently
- similarity(textA, textB): Calculate semantic similarity (0-1 score)
- indexStats(): Get comprehensive index statistics with memory usage
- neighbors(entityId, options): Get graph neighbors with direction/depth/filter
- findDuplicates(options): Find semantic duplicates by embedding similarity
- cluster(options): Cluster entities by semantic similarity with centroids
All APIs:
- Added to BrainyInterface for type safety
- Documented in docs/API_REFERENCE.md and docs/api/README.md
- Include JSDoc examples and parameter descriptions
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Process mkdir operations sequentially first (sorted by path depth)
- Then process write/delete/update operations in parallel batches
- Prevents duplicate directory entities when mkdir and write for
related paths are in the same batch
- Add comprehensive tests for bulkWrite race condition scenarios
- Update API documentation for accuracy
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
VFS files store content in BlobStorage, but versioning was capturing
stale embedding text from entity.data instead of actual file content.
Changes:
- VersionManager.save() now reads fresh content via vfs.readFile()
- VersionManager.restore() writes content back via vfs.writeFile()
- Text files stored as UTF-8, binary as base64 with encoding flag
- Added comprehensive VFS versioning test suite (10 tests)
- Updated API docs with VFS file versioning example
Fixes: Workshop team bug report where all VFS file versions had
identical data despite different metadata.size values.
Implements comprehensive batching infrastructure (brain.batchGet, storage.getNounMetadataBatch, storage.getVerbsBySourceBatch) with native cloud adapter APIs for GCS, S3, R2, and Azure. VFS operations now use parallel breadth-first traversal with batching, reducing directory reads from 22 sequential calls to 2-3 batched calls. Improves cloud storage performance by 90%+ (12.7s → <1s for 12 files). Fully compatible with type-aware storage, sharding, COW, fork(), and all indexes.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
Added comprehensive production service architecture guide with singleton patterns, caching strategies, and performance optimization for Express/Node.js services.
Changes:
- NEW: docs/PRODUCTION_SERVICE_ARCHITECTURE.md - Complete guide for using Brainy in production services
- CHANGED: .gitignore - Removed PRODUCTION_*.md pattern to allow public documentation
- CHANGED: README.md - Added subtle link to production architecture guide in "Production MVP" section
Guide covers:
- Instance-per-request anti-pattern (40x memory waste)
- Singleton pattern implementation (40x memory reduction, 30x faster)
- Three implementation patterns (simple, service class, middleware)
- Optimization strategies (cache sizing, lazy loading, warm-up)
- Concurrency and thread safety
- Production checklist and monitoring
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
Cleaned up public documentation to remove references to external projects (Workshop). Documentation should be project-agnostic and professional.
Changes:
- docs/guides/import-progress-examples.md: Changed "Workshop team problem SOLVED" to "Problem SOLVED"
- docs/guides/standard-import-progress.md: Changed "Workshop team (and any developer)" to "Developers"
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
Implements Phase 1.5 (Comprehensive MIME Type Detection) and adds built-in image processing support to IntelligentImportAugmentation.
**New Features:**
- ImageHandler: Extracts image metadata (dimensions, format, color space) using sharp
- EXIF extraction: Camera data, GPS, timestamps using exifr library
- Support for JPEG, PNG, WebP, GIF, TIFF, BMP, SVG, HEIC, AVIF formats
- MimeTypeDetector: Unified MIME type detection with magic byte support
- FormatDetector: Enhanced with image format detection via MIME + magic bytes
**Architecture Fixes:**
- Fixed brain.import() augmentation pipeline integration (src/brainy.ts:3140-3154)
- Added parameter spreading for ImportSource objects to enable augmentation access
- Fixed metadata propagation through ImportCoordinator to final results
- Added augmentation data check in ImportCoordinator.extract()
**Integration:**
- ImageHandler registered as built-in handler alongside CSV, Excel, PDF
- Images import as 'media' entities with 'image' subtype
- Full metadata preserved in knowledge graph entities
- Configuration options: enableImage, extractEXIF, imageDefaults
**Test Coverage:**
- 15 integration tests (image-import.test.ts) - 100% passing
- 27 unit tests (image-handler.test.ts) - 100% passing
- Format detection tests for all supported image types
- Error handling and resilience tests
**Breaking Changes:** None - backward compatible
Generated with Claude Code
Co-Authored-By: Claude <noreply@anthropic.com>
Removed 9 undocumented feature sections from VFS docs (version history, distributed filesystem, AI auto-organization, etc.). Added status labels (Production/Beta/Experimental) to all features, updated performance claims with MEASURED vs PROJECTED labels, and created ROADMAP.md for planned features. Fixed storage adapter list to show only built-in adapters.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
- Remove includeVFS parameter and broken isVFS filtering logic
- Add excludeVFS parameter for optional VFS entity filtering
- VFS entities now part of knowledge graph by default
- Enable O(1) graph adjacency optimizations for VFS operations
- Update all VFS projections and PathResolver
- Add comprehensive VFS visibility documentation
This fixes the bug where VFS operations returned empty results due to
operator object mismatch in storage adapters. VFS relationships now use
proper graph traversal without metadata filtering.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
