 GlyphRunner System
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4bc49c90b3
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Implement LAIN ↔ Supercharged Glyph Bridge
New module:
- gx_lain/lain_glyph_bridge.py: Bridge connecting LedoGlyph600 to LAIN cognition
Functions:
- load_glyph_context(manifest, context): Load relevant glyph from registry
- inject_glyph_metadata_into_lane(lane_result, glyph_context): Add glyph fields to lane
- compute_glyph_resonance(glyph_context): Calculate glyph resonance metrics
- augment_fused_symbol_with_glyphs(fused_symbol, glyph_context): Add glyph to final output
Modified:
- gx_lain/runtime.py: Integrate glyph bridge into execute_with_lain()
* Load glyph context as step 1 of cognition
* Inject glyph metadata into each lane result
* Augment fused symbol with glyph context
* Add glyph_resonance to diagnostics
* Track glyph loading in cognition_trace
Tests:
- tests/test_lain_glyph_bridge.py: 10 comprehensive tests
* Context loading (with/without glyph)
* Metadata injection (preserves existing fields)
* Resonance computation (4-component metric)
* Symbol augmentation
* Full integration test
Features:
- Glyph metadata: id, name, category, score, period, band
- Frequency signatures: praw (P, R, A, W)
- Activation envelopes: mode, score
- Lineage: signature, inheritance weight
- Symbolic anatomy: power, complexity, resonance, stability, connectivity, affinity
- Resonance profile: activation + frequency + symbolic metrics (0.0-1.0)
All 18 integration tests still passing (no regressions).
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2026-05-20 17:41:47 -04:00 |
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