Implement XIC v1.5 glyph resonance awareness upgrade (Phase 3-4)
This commit completes the comprehensive glyph resonance awareness upgrade
with queryable resonance metrics, new instruction, and formal specification.
## Changes
### Phase 3: New GET_GLYPH_RESONANCE Instruction
- Added op_GET_GLYPH_RESONANCE to xic_ops.py for querying glyph resonance data
- Supports metrics: report, global, dominant, weight, lineage, contributor, frequency, grammar
- Results printed with [XIC-RESONANCE] prefix and stored in ctx._state
- Handles both full pipeline result (preferred) and fallback to resonance_metrics dict
- Updated OP_TABLE to include 10th operation
### Phase 4: Formal Specification & Demo
#### XIC_SEMANTICS_v1_5.md Updates
- Added comprehensive "Glyph Resonance Structure" section documenting:
- FusedSymbol dataclass with summary, glyph_ids, resonance_map
- GlyphResonanceMap with resonances dict and utility methods
- GlyphResonanceMetrics (weight, lineage_score, contributor_score, frequency_score, grammar_score)
- Example JSON structure from LAIN cognition
- Added "GET_GLYPH_RESONANCE" instruction semantics with:
- Signature and preconditions/postconditions
- Metric table describing all query types
- Detailed side effects and remarks
- Data access patterns
#### New Demo Program
- Created programs/demo_glyph_resonance.gx.json
- Two-chain demonstration:
- Chain 1: compression_theory glyph with report, global, dominant, weight queries
- Chain 2: neural_dynamics glyph with individual metric queries (lineage, contributor, frequency, grammar)
- Full instrumentation with CHAIN markers and LOG statements
#### Comprehensive Report
- Created XIC_GLYPH_RESONANCE_REPORT.md documenting:
- Executive summary of resonance awareness upgrade
- Detailed explanation of all components
- Architecture and data flow diagrams
- All 10 validation test results
- Usage examples and design decisions
- Backward compatibility guarantees
- Future extensibility notes
## Implementation Details
### Enhanced Data Structures (glyphos/symbolic_pipeline.py)
- GlyphResonanceMetrics: 5-dimensional resonance scoring
- GlyphResonanceMap: with get_glyph_resonance(), get_top_glyphs(), get_average_resonance()
- FusedSymbol.from_lain_result(): parses LAIN output structure
### Glyph Resonance Utilities
- extract_glyph_resonances(): extract per-glyph metrics from pipeline result
- get_dominant_glyphs(n): rank glyphs by weight
- format_glyph_resonance_report(): human-readable resonance output
### Enhanced CALL_GLYPH
- Now stores comprehensive resonance data in ctx._state["glyph_{glyph_id}"]
- Captures output_text, fused_symbol, resonance_metrics, global_resonance_score, steps
- Also stores full SymbolicPipelineResult for direct access
### New op_GET_GLYPH_RESONANCE
- Query stored resonance metrics with flexible metric selection
- Integrates with symbolic_pipeline utilities for full introspection
- Prints results and stores in ctx._state for programmatic access
## Exports (glyphos/__init__.py)
- GlyphResonanceMetrics
- GlyphResonanceMap
- extract_glyph_resonances
- get_dominant_glyphs
- format_glyph_resonance_report
## Testing
All 10 validation tests pass:
✅ GlyphResonanceMetrics instantiation
✅ GlyphResonanceMap methods (get_glyph_resonance, get_top_glyphs, get_average_resonance)
✅ FusedSymbol.from_lain_result() parsing
✅ extract_glyph_resonances() functionality
✅ get_dominant_glyphs() ranking
✅ format_glyph_resonance_report() generation
✅ OP_TABLE has GET_GLYPH_RESONANCE
✅ op_GET_GLYPH_RESONANCE callable
✅ demo_glyph_resonance.gx.json valid
✅ All exports available from glyphos
## Backward Compatibility
- Zero breaking changes
- All XIC v1 and v1.5 programs work unchanged
- New resonance features are additive
- Existing instruction signatures preserved
- Compressed mode execution unaffected
Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>
This commit is contained in:
GlyphRunner System
@@ -284,6 +284,128 @@ Dual paths:
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---
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### 10. GET_GLYPH_RESONANCE
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**Signature**
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```json
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{ "op": "GET_GLYPH_RESONANCE", "args": ["<glyph_id>", "<metric>"] }
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```
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**Preconditions**
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- `glyph_id` must have been previously used in a CALL_GLYPH operation.
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- `metric` is optional. Valid values: "report", "global", "dominant", "weight", "lineage", "contributor", "frequency", "grammar".
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**Postconditions**
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- Prints formatted resonance data based on requested metric.
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- Stores result in `ctx._state[f"resonance_query_{glyph_id}_{metric}"]`.
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**Behavior by metric**:
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| Metric | Output | Description |
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|--------|--------|-------------|
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| `<none>` or `"report"` | Human-readable resonance report | Formatted report with global score and top 5 glyphs by weight |
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| `"global"` | Global resonance score (float) | Single float value representing overall resonance |
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| `"dominant"` | List of top 5 glyphs by weight | List of (glyph_id, weight) tuples sorted descending |
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| `"weight"` | Weight metric (float) | Weight component of resonance (relative importance) |
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| `"lineage"` | Lineage score (float) | Score representing symbolic lineage and ancestry |
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| `"contributor"` | Contributor score (float) | Score representing contribution to fusion |
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| `"frequency"` | Frequency score (float) | Score representing occurrence frequency in cognition |
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| `"grammar"` | Grammar score (float) | Score representing grammatical/structural alignment |
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**Side effects**
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- Prints `[XIC-RESONANCE] ...` with requested data.
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- Stores result in `ctx._state` for programmatic access.
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**Remarks**
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- GET_GLYPH_RESONANCE requires prior CALL_GLYPH execution to populate glyph resonance data.
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- If glyph_id not found, prints error and stores None.
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- Queries access the full SymbolicPipelineResult stored by CALL_GLYPH.
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---
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## Glyph Resonance Structure
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### FusedSymbol Data Structure
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The `fused_symbol` in SymbolicPipelineResult contains:
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```python
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@dataclass
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class FusedSymbol:
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summary: str # Text summary of fused cognition
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glyph_ids: List[str] # List of glyph IDs engaged in fusion
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resonance_map: GlyphResonanceMap # Resonance metrics for each glyph
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```
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### GlyphResonanceMap
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Maps glyph IDs to their resonance metrics:
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```python
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@dataclass
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class GlyphResonanceMap:
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resonances: Dict[str, GlyphResonanceMetrics] # glyph_id → metrics
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global_resonance_score: float # Overall fusion quality score [0.0, 1.0]
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```
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Methods:
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- `get_glyph_resonance(glyph_id: str) → Optional[GlyphResonanceMetrics]`: Retrieve metrics for a specific glyph.
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- `get_top_glyphs(n: int = 5) → List[tuple[str, GlyphResonanceMetrics]]`: Get top N glyphs by weight.
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- `get_average_resonance() → float`: Get average resonance across all glyphs.
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### GlyphResonanceMetrics
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Per-glyph resonance metrics capturing multiple dimensions of symbolic activity:
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```python
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@dataclass
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class GlyphResonanceMetrics:
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weight: float # Relative importance of glyph in fusion [0.0, 1.0]
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lineage_score: float # Symbolic lineage and ancestry score [0.0, 1.0]
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contributor_score: float # Contribution to overall fusion [0.0, 1.0]
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frequency_score: float # Occurrence frequency in cognition [0.0, 1.0]
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grammar_score: float # Grammatical/structural alignment [0.0, 1.0]
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```
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### Example Structure
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```json
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{
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"fused_symbol": {
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"summary": "Compression and information theory are foundational to cognition...",
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"glyph_ids": ["glyph://compression_theory", "glyph://entropy", "glyph://coding"],
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"resonance_map": {
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"global_resonance_score": 0.847,
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"resonances": {
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"glyph://compression_theory": {
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"weight": 0.95,
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"lineage_score": 0.82,
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"contributor_score": 0.89,
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"frequency_score": 0.76,
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"grammar_score": 0.88
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},
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"glyph://entropy": {
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"weight": 0.73,
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"lineage_score": 0.68,
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"contributor_score": 0.71,
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"frequency_score": 0.65,
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"grammar_score": 0.75
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}
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}
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}
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}
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}
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```
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### Accessing Resonance Data
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From XIC programs:
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1. CALL_GLYPH stores result in `ctx._state[f"glyph_{glyph_id}"]` including resonance_metrics and global_resonance_score.
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2. GET_GLYPH_RESONANCE queries the stored data with various metric filters.
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3. Access pipeline result object via `ctx._state[f"glyph_{glyph_id}_pipeline_result"]` for direct FusedSymbol manipulation.
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---
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## Symbolic Pipeline Semantics
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### run_symbolic_pipeline() Entrypoint
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