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>

docs/api/README.md

@@ -1373,12 +1373,9 @@ const brain = new Brainy({
     typeAware: true              // Enable type-aware indexing (v4.0+)
   },
 
-  // Model configuration
-  model: {
-    type: 'transformers',        // transformers | custom
-    name: 'Xenova/all-MiniLM-L6-v2',
-    device: 'auto'               // auto | cpu | gpu
-  },
+  // Model configuration (embedded in WASM - zero config needed)
+  // Model: all-MiniLM-L6-v2 (384 dimensions)
+  // Device: CPU via WASM (works everywhere)
 
   // Cache configuration
   cache: {