Add 'percentile' (with a 'p' fraction in [0,1]) and 'distinctCount' to the
aggregation engine. Both are exact, computed from a per-metric value multiset
(MetricState.valueCounts) maintained incrementally and delete-safe; percentile
uses numpy-linear interpolation. The multiset is JSON-serializable so results
survive persistence. 35 aggregation unit tests pass.
- 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.
Three advanced-API correctness fixes, all reproducible on Node (not Bun-specific):
- Entity/concept extraction returned []. SmartExtractor combined agreeing signals
with a weighted sum compared against an absolute 0.60 gate, so a confident
low-weight signal lost selection to a mediocre high-weight one that then failed
the gate, dropping the whole result. Select and gate on a normalized weighted
average instead. The public `confidence` option now controls the threshold (was
a dead hardcoded 0.60), and the embedding-signal timeout is raised 100ms -> 2000ms
so the neural signal is not silently dropped on slower runtimes.
- Multi-hop find({ connected }) returned only the 1-hop neighbour. executeGraphSearch
ignored depth/via; it now delegates to the depth-aware neighbors() BFS.
- find({ aggregate }) hid groupKey/metrics/count under .metadata, so callers
expecting AggregateResult saw empty rows. Expose those fields at the top level.
Adds real-embedding regression tests in tests/integration/advanced-apis-regression.test.ts.
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.
The storage config type only exposed { type, options, branch } but plugin
storage factories (e.g. Cortex mmap) read rootDirectory from the top level
of the config object. This caused undefined storage paths when Cortex was
active. The underlying StorageOptions interface already declares
rootDirectory — this aligns BrainyConfig.storage to match.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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).
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
- Add native config option: `new Brainy({ integrations: true })`
- OData integration for Excel Power Query and Power BI
- Google Sheets integration with Apps Script
- Server-Sent Events (SSE) for real-time streaming
- Webhooks for push notifications
- Zero-config with sensible defaults
- Full tree-shaking when disabled
Cloud Run cold starts taking 139 seconds due to 90MB WASM file with
embedded 87MB model weights. WASM compilation scales with file size.
Solution: Split into 2.4MB WASM (code only) + external model files.
- WASM compile: 139,000ms → 6-8ms
- Model load: N/A → 30-115ms
- Total init: 139,000ms → 136-240ms
New modelLoader.ts handles all environments:
- Node.js: fs.readFile()
- Bun: Bun.file()
- Bun --compile: auto-embedded assets
- Browser: fetch()
Zero config - same API, npm package includes model files.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Remove unused model.type validation that caused Workshop error
- Remove model config from BrainyConfig type (never used)
- Simplify modelAutoConfig.ts (always Q8 WASM)
- Clean up zeroConfig.ts model references
This fixes the "Invalid model type: balanced" error and removes
unnecessary configuration options that did nothing.
CRITICAL BUG FIX: TypeAwareStorage metadata race condition
Problem:
- saveNoun() called before saveNounMetadata()
- TypeAwareStorage couldn't determine entity type (not cached yet)
- Defaulted to 'thing' and saved to wrong storage path
- Later saveNounMetadata() saved to correct path
- Noun and metadata in different locations = entity not found
Impact:
- Broke VFS file operations completely
- Broke brain.get(), brain.relate(), brain.find()
- All metadata-dependent features failed
- Workshop team completely blocked
Solution:
- Reversed save order: saveNounMetadata() FIRST, then saveNoun()
- Type now cached before saveNoun() needs it
- Both saved to correct type-aware paths
Additional Fixes:
- Make baseStorage.initializeCOW() public (was protected)
- Remove enableCOW config option (cleanup)
- COW auto-init temporarily disabled (deadlock issue)
Known Limitations (v5.0.1):
- Fork API exists but COW requires manual init
- Will be zero-config in v5.1.0
Fixes: Workshop Bug Report (VFS metadata missing)
CRITICAL FIX: VFS bug that persisted through v4.5.1-v4.7.4 is NOW FIXED.
Root Cause:
- Storage adapters were not properly extracting standard fields from metadata
- This caused getVerbsBySource_internal() to return 0 relationships despite relationships existing
- VFS PathResolver couldn't navigate directory structure
Solution - Metadata Architecture Refactoring:
1. Move standard fields to top-level of HNSWNounWithMetadata and HNSWVerbWithMetadata
- type, createdAt, updatedAt, confidence, weight, service, data, createdBy
2. Update all 9 storage adapters to extract standard fields from metadata on load
3. Maintain backward compatibility at storage layer (metadata files unchanged)
Changes:
- src/coreTypes.ts: Update HNSWNounWithMetadata and HNSWVerbWithMetadata interfaces
- Add top-level standard fields
- Change data type from unknown to Record<string, any>
- Add confidence field to GraphVerb
- src/storage/baseStorage.ts: Add type cast pattern for standard field extraction
- src/storage/adapters/*.ts: Fix all 9 adapters (memoryStorage, fileSystemStorage, gcsStorage,
s3CompatibleStorage, r2Storage, opfsStorage, azureBlobStorage, typeAwareStorageAdapter)
- Extract standard fields from metadata on load
- Place at top-level of returned entities
- src/api/DataAPI.ts: Read fields from top-level instead of metadata
- src/graph/graphAdjacencyIndex.ts: Convert HNSWVerbWithMetadata to GraphVerb format
- src/utils/metadataIndex.ts: Fix typo (metadata → entityOrMetadata)
- src/types/brainy.types.ts: Add createdBy field to AddParams
- src/types/graphTypes.ts: Add service field to GraphVerb
Test Results:
✅ VFS bug FIXED - vfs.readdir('/') now returns files (was returning empty array)
✅ getVerbsBySource_internal() now returns relationships correctly
✅ Build succeeds with ZERO compilation errors
✅ 95.7% of tests pass (954/997)
Breaking Changes:
- None - backward compatibility maintained at storage layer
Version: 4.8.0
🤖 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>
Add production-scale sorting support with orderBy/order parameters:
- Sort by any field including createdAt, updatedAt, timestamps
- Works in both metadata-only and vector+metadata query paths
- O(k) memory complexity where k = filtered results
Fix timestamp sorting precision issue:
- Load actual timestamp values from entity metadata for sorting
- Avoids 1-minute bucketing precision loss
- Maintains bucketing for efficient range queries
Fix range query operators:
- Normalize min/max bounds before comparison with bucketed index
- Ensures gte, lte, gt, lt work correctly with timestamps
Standardize operator syntax:
- Canonical: eq, ne, gt, gte, lt, lte, in, between, contains, exists
- Deprecate: is, isNot, greaterEqual, lessEqual (remove in v5.0.0)
- Maintain backward compatibility with aliases
Test results: All sorting and range query tests pass, no regressions
CRITICAL BUG FIX - VFS Files Were Completely Invisible
Workshop Team Issue:
- Import created 569 VFS files
- vfs.readdir('/') returned 0 items
- VFS was 100% unusable
Root Cause:
v4.4.0 added includeVFS to brain.find() but FORGOT brain.getRelations().
PathResolver.getChildren() calls getRelations() to find VFS relationships,
but those were being excluded by default - making ALL VFS files invisible!
Fix:
1. Add includeVFS parameter to GetRelationsParams interface
2. Wire includeVFS filtering in brain.getRelations()
- Excludes VFS relationships by default (metadata.isVFS != true)
- Include them when includeVFS: true
3. Update VFS to mark all relationships with metadata: { isVFS: true }
- 7 relate() calls updated in VirtualFileSystem.ts
4. Update PathResolver to use includeVFS: true
- resolveChild() line 200
- getChildren() line 229
Impact:
- VFS is now fully functional again
- Consistent with v4.4.0 architecture (VFS separate from knowledge graph)
- All APIs now have includeVFS where needed
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
Add real-time progress reporting throughout the entire import pipeline
with a standardized API that works across all supported formats.
Workshop Team Feature Request:
- Eliminates "0% complete" hangs during AI extraction
- Shows continuous progress with entities/sec, throughput, ETA
- Reports contextual messages ("Processing page 5 of 23")
- Standardized progress API for CSV, PDF, Excel, JSON, Markdown, YAML, DOCX
Core Changes:
- Add FormatHandlerProgressHooks interface for extensible progress
- Wire up all 3 binary format handlers (CSV, PDF, Excel) with 7+ progress points
- Wire up all 4 text format importers (JSON, Markdown, YAML, DOCX)
- Add ImportProgress interface with stage, message, counts, throughput, ETA
- ImportCoordinator normalizes all format progress to standard interface
CLI Improvements:
- Import command now uses brain.import() directly with full progress
- Add --include-vfs flag to find command (v4.4.0 compatibility)
- Add --confidence and --weight options to add command
Documentation:
- docs/guides/standard-import-progress.md - Universal API guide
- docs/guides/import-progress-implementation.md - Developer guide
- docs/guides/import-progress-examples.md - Practical examples
- JSDoc on brain.import() with universal handler examples
Result: ONE progress handler works for ALL 7 formats with zero format-specific code!
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
Add confidence and weight properties to Entity interface and flatten Result fields to top level for improved developer experience and API consistency.
Breaking Changes: None (all changes are backward compatible)
Phase 2 - Entity Confidence & Weight:
- Add confidence (type classification certainty) and weight (entity importance) to Entity interface
- Add confidence/weight parameters to AddParams and UpdateParams
- Update convertNounToEntity() to extract confidence/weight from storage
- Update add() and update() methods to preserve confidence/weight in metadata
- Enable developers to specify and access entity confidence/weight scores
Phase 3 - Result Field Flattening:
- Flatten commonly-used entity fields (type, metadata, data, confidence, weight) to Result top level
- Add createResult() helper for consistent Result construction
- Update all find() code paths to use createResult()
- Enable direct access: result.metadata instead of result.entity.metadata
- Preserve full entity in result.entity for backward compatibility
VFS Fix (from previous work):
- Fix VFSStructureGenerator to use brain.vfs() cached instance instead of creating separate instance
- Improve VFS error messages with step-by-step guidance
- Update examples to show correct vfs.init() usage
- Add comprehensive VFS import verification tests
Documentation Updates:
- Update API_REFERENCE.md with confidence/weight examples and flattened Result documentation
- Enhance JSDoc for add(), get(), find(), similar() with v4.3.0 examples
- Document Result structure changes and backward compatibility
- Add migration examples showing both old and new access patterns
Tests:
- Add 16 comprehensive tests for Entity confidence/weight exposure
- Add tests for Result field flattening
- Add tests for backward compatibility
- All tests passing (16/16)
API Consistency:
- Entity: direct access to confidence/weight
- Result: flattened fields + nested entity (both work)
- Relation: already had confidence/weight (consistent)
- VFS: inherits from Entity (automatic)
Files Changed:
- src/types/brainy.types.ts - Updated Entity, AddParams, UpdateParams, Result interfaces
- src/brainy.ts - Updated implementation and JSDoc for all affected methods
- tests/integration/entity-confidence-weight.test.ts - 16 comprehensive tests
- docs/API_REFERENCE.md - Updated with v4.3.0 examples
- src/importers/VFSStructureGenerator.ts - VFS fix
- src/vfs/VirtualFileSystem.ts - Improved error messages
- examples/unified-import-example.ts - Added vfs.init() example
- tests/integration/vfs-*-verification.test.ts - VFS verification tests
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
**Problem**: brain.getRelations() returned empty array when called without
parameters, making 524 imported relationships inaccessible for Workshop team.
**Root Cause**: Method only queried storage when `from` or `to` parameters
were provided. Without params, it returned empty array.
**Solution**:
- Add support for "get all" via storage.getVerbs() when no from/to provided
- Add string ID shorthand: getRelations(id) → getRelations({ from: id })
- Default limit: 100 (matching storage layer pattern)
- Production safety: warn for >10k queries without filters
- Fix broken improvedNeuralAPI.ts calls (getVerbsForNoun → getRelations)
- Fix property bugs: verb.target → verb.to, verb.verb → verb.type
**Testing**:
- 14 new integration tests covering all query patterns
- All critical tests passing (25/25)
- Backward compatible - no breaking changes
**Impact**: Resolves Workshop bug where imported relationships were invisible
- Change default storage from 'memory' to 'auto' for smart environment detection
- Add 'auto' support to storage type validation and TypeScript types
- Browser: auto-selects OPFS → memory fallback
- Node.js: auto-selects filesystem → memory fallback
- Cloud: auto-detects S3/GCS/R2 → disk → memory fallback
- Eliminates need for manual storage configuration in most cases
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
- Fix FileSystemStorage counting non-existent files in totalCount
- Add safety check in BaseStorage to prevent hasMore:true with empty items
- Ensure pagination terminates correctly even with corrupted storage state
- Add incremental sorted index updates during CRUD operations for consistent <5ms range queries
- Implement parallel search optimization with vector, metadata, and graph intelligence fusion
- Fix metadata-only query handling to properly return results without vector search
- Fix NLP recursive call issue by using embed() instead of add()
- Add cardinality tracking for smart index optimization
- Store entity data in metadata for proper retrieval
- Add comprehensive performance documentation
This improves query performance from O(n) to O(log n) for range queries
and ensures consistent fast performance without lazy loading delays.
