brainy

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Author	SHA1	Message	Date
David Snelling	da7d2ed29d	feat: migrate embeddings to Candle WASM + remove semantic type inference Major architectural changes: 1. EMBEDDINGS ENGINE (ONNX → Candle WASM): - Replace ONNX Runtime with Rust Candle compiled to WASM - Embedded model in WASM binary (no external downloads) - Quantized Q8 precision with <50MB memory footprint - Zero-download, offline-first operation - Same embedding quality (all-MiniLM-L6-v2) 2. REMOVE SEMANTIC TYPE INFERENCE: - Delete embeddedKeywordEmbeddings.ts (14MB of pre-computed embeddings) - Remove typeAwareQueryPlanner.ts and semanticTypeInference.ts - Remove VerbExactMatchSignal (uses keyword embeddings) - Update SmartRelationshipExtractor to 3 signals (55%/30%/15% weights) API CHANGES (requires v7.0.0): - Removed: inferTypes(), inferNouns(), inferVerbs(), inferIntent() - Removed: getSemanticTypeInference(), SemanticTypeInference class - Removed: TypeInference, SemanticTypeInferenceOptions types Users can still use natural language queries in find() - they just need to specify type explicitly for type-optimized searches. PACKAGE SIZE IMPACT: - Compressed: 90.1 MB → 86.2 MB (-4.3%) - Uncompressed: 114.4 MB → 100.3 MB (-12%) - ~448K lines of code removed 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>	2026-01-06 12:52:34 -08:00
David Snelling	759e7fabd0	docs: add production service architecture guide to public docs 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>	2025-11-14 16:21:27 -08:00

Author

SHA1

Message

Date

David Snelling

da7d2ed29d

feat: migrate embeddings to Candle WASM + remove semantic type inference

Major architectural changes:

1. EMBEDDINGS ENGINE (ONNX → Candle WASM):
   - Replace ONNX Runtime with Rust Candle compiled to WASM
   - Embedded model in WASM binary (no external downloads)
   - Quantized Q8 precision with <50MB memory footprint
   - Zero-download, offline-first operation
   - Same embedding quality (all-MiniLM-L6-v2)

2. REMOVE SEMANTIC TYPE INFERENCE:
   - Delete embeddedKeywordEmbeddings.ts (14MB of pre-computed embeddings)
   - Remove typeAwareQueryPlanner.ts and semanticTypeInference.ts
   - Remove VerbExactMatchSignal (uses keyword embeddings)
   - Update SmartRelationshipExtractor to 3 signals (55%/30%/15% weights)

API CHANGES (requires v7.0.0):
- Removed: inferTypes(), inferNouns(), inferVerbs(), inferIntent()
- Removed: getSemanticTypeInference(), SemanticTypeInference class
- Removed: TypeInference, SemanticTypeInferenceOptions types

Users can still use natural language queries in find() - they just
need to specify type explicitly for type-optimized searches.

PACKAGE SIZE IMPACT:
- Compressed: 90.1 MB → 86.2 MB (-4.3%)
- Uncompressed: 114.4 MB → 100.3 MB (-12%)
- ~448K lines of code removed

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

2026-01-06 12:52:34 -08:00

David Snelling

759e7fabd0

docs: add production service architecture guide to public docs

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>

2025-11-14 16:21:27 -08:00

2 commits