- Remove @huggingface/transformers dependency (539MB native binaries)
- Add direct ONNX Runtime Web embedding engine
- Bundle all-MiniLM-L6-v2-q8 model (24MB, no runtime downloads)
- Works with Node.js, Bun, and bun build --compile
- Air-gap compatible: fully self-contained, no internet required
New WASM embedding components:
- WASMEmbeddingEngine: Main integration class
- WordPieceTokenizer: Pure TypeScript tokenizer
- EmbeddingPostProcessor: Mean pooling + L2 normalization
- ONNXInferenceEngine: Direct ONNX Runtime Web wrapper
- AssetLoader: Model file loading
Tests added:
- 11 WASM embedding integration tests
- 8 Bun compatibility tests
New npm scripts:
- test:wasm - Run WASM embedding tests
- test:bun - Run tests with Bun
- test:bun:compile - Build and run compiled binary
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>
Major optimization - all type embeddings now built into package:
Build-time generation:
- Created scripts/buildTypeEmbeddings.ts to generate all type embeddings
- Generates embeddings for 31 NounTypes + 40 VerbTypes at build time
- Stores as base64-encoded binary data in embeddedTypeEmbeddings.ts
- Added check script to rebuild only when needed
Updated all consumers:
- NeuralEntityExtractor: loads pre-computed embeddings (instant)
- BrainyTypes: loads pre-computed embeddings (instant init)
- NaturalLanguageProcessor: loads pre-computed embeddings (instant init)
Build process:
- Added npm run build:types to generate embeddings
- Added npm run build:types:if-needed for conditional rebuild
- Integrated into main build pipeline
- Auto-rebuilds only when types or build script change
Benefits:
- Zero runtime cost - embeddings loaded instantly
- Survives all container restarts
- All 71 types always available (31 nouns + 40 verbs)
- ~100KB memory overhead for permanent performance gain
- Eliminates 5-10 second initialization delay
This completes the type embedding optimization started in v3.32.5
- Add scripts/release.sh for automated build → test → commit → push → publish → release
- Fix .versionrc.json types configuration (was causing 'types.find is not a function' error)
- Remove problematic precommit/postcommit hooks that ran full test suite during release
- Keep standard-version as fallback option (npm run release:standard-version:*)
- New workflow is faster, more reliable, and easier to debug
Usage:
npm run release # patch release (3.20.4 → 3.20.5)
npm run release:minor # minor release (3.20.4 → 3.21.0)
npm run release:major # major release (3.20.4 → 4.0.0)
npm run release:dry # dry-run mode (no changes)
- Replace Brainy with TransformerEmbedding for embedding patterns
- Update initialization logic to support TransformerEmbedding features like `localFilesOnly`
- Adjust embedding logic to use TransformerEmbedding's embed method
- Remove unused Brainy-related code (e.g., close method)
- 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.
- Implements automatic fallback chain: CDN → GitHub → Hugging Face
- Adds Soulcraft CDN as primary model source (models.soulcraft.com)
- GitHub release tar.gz extraction as reliable backup
- Zero configuration required - fully automatic
- Guarantees same model (all-MiniLM-L6-v2) across all sources
- 384-dimensional embeddings for data compatibility
- Local caching after first download
- Production-ready with multiple redundancy layers
BREAKING CHANGE: Removed tar-stream dependency, now uses native tar command
BREAKING CHANGE: Remove hard delete option from deleteVerb() for consistent API
- Add complete metadata namespace architecture with O(1) soft delete performance
- Implement periodic cleanup system for old soft-deleted items
- Add restore methods for both nouns and verbs
- Require metadata contracts for all augmentations
- Eliminate namespace collisions with clean separation (_brainy, _augmentations, _audit)
- Optimize index performance using flattened dot-notation for O(1) lookups
- Add comprehensive augmentation safety system with type-safe access control
- Maintain full backward compatibility for existing data
- Add enterprise-grade cleanup with configurable age thresholds and batch processing
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
- Rename check-patterns.js to check-patterns.cjs for CommonJS compatibility
- Update package.json to reference .cjs file
- This fixes ES module errors when checking if patterns need rebuild
- Add embeddedPatterns.ts to version control (544KB file)
- Add check-patterns.js script to detect when rebuild is needed
- Modify build scripts to only rebuild patterns when changed
- This avoids memory-intensive pattern embedding on every npm publish
- Patterns rarely change, so this significantly speeds up releases
