David Snelling
da7d2ed29d
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>
31 lines
1.1 KiB
TypeScript
31 lines
1.1 KiB
TypeScript
/**
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* Brainy Setup - Minimal Polyfills
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*
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* ARCHITECTURE (v7.0.0):
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* Brainy uses Candle WASM (Rust-based) for embeddings.
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* No transformers.js or ONNX Runtime dependency, no hacks required.
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*
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* This file provides minimal polyfills for cross-environment compatibility:
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* - TextEncoder/TextDecoder for older environments
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*
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* BENEFITS:
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* - Clean codebase with no workarounds
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* - Works everywhere: Node.js, Bun, Bun --compile, browsers, Deno
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* - No platform-specific binaries
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* - Model bundled in package (no runtime downloads)
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*/
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// ============================================================================
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// TextEncoder/TextDecoder Polyfills
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// ============================================================================
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const globalObj = globalThis ?? global ?? self
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if (globalObj) {
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if (!globalObj.TextEncoder) globalObj.TextEncoder = TextEncoder
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if (!globalObj.TextDecoder) globalObj.TextDecoder = TextDecoder
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;(globalObj as any).__TextEncoder__ = TextEncoder
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;(globalObj as any).__TextDecoder__ = TextDecoder
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}
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import { applyTensorFlowPatch } from './utils/textEncoding.js'
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applyTensorFlowPatch()
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