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Author SHA1 Message Date
GlyphRunner System 150a036604 Implement multi-glyph resonance system for XIC v1.5 (6 phases) 
Complete end-to-end multi-glyph resonance enabling simultaneous analysis
of multiple glyphs with cross-glyph resonance metrics, guardrails, and
comprehensive telemetry.

## Phase 1: XIC Layer - Context Accumulation

### XICContext Enhancement
- Added glyph_contexts: list field for accumulating glyph IDs

### New Operations
- PUSH_GLYPH_CONTEXT: accumulate glyph with guardrail enforcement
- CLEAR_GLYPH_CONTEXT: reset context for new analysis chains

### Enhanced Existing Operations
- CALL_GLYPH: detects populated glyph_contexts, passes glyph_ids to pipeline
- RUN_PROMPT: supports multi-glyph context via glyph_ids parameter
- STREAM: supports multi-glyph context via glyph_ids parameter

### Guardrail Integration
- max_resonance_glyphs (default 10, configurable)
- enable_resonance_guardrails (default True)
- Enforced at PUSH_GLYPH_CONTEXT to prevent exceeding limit

## Phase 2: Symbolic Pipeline - Multi-Glyph Support

### Extended Signature
- run_symbolic_pipeline now accepts glyph_ids parameter
- Multi-glyph mode detection and routing
- glyph_ids takes precedence over glyph_id if both provided

### Multi-Glyph Processing
- SymbolicStep(kind="multi_glyph_resonance") for glyph_ids
- SymbolicStep(kind="guardrail") when truncation needed
- Guardrail enforcement with pipeline-level truncation to max_resonance_glyphs

### Null-Safety Fixes
- extract_glyph_resonances: handles None resonance_map
- get_dominant_glyphs: handles None resonance_map
- format_glyph_resonance_report: handles None resonance_map

## Phase 3: LAIN Cognitive Kernel - Resonance Computation

### New Method: compute_multi_glyph_resonance
- Takes glyph_ids list and execution result
- Computes 5-dimensional metrics per glyph:
  - weight: relative importance [0.0, 1.0]
  - lineage_score: symbolic ancestry [0.0, 1.0]
  - contributor_score: contribution to fusion [0.0, 1.0]
  - frequency_score: occurrence frequency [0.0, 1.0]
  - grammar_score: structural alignment [0.0, 1.0]
- Returns global_resonance_score as weighted average

### Enhanced execute_symbolic
- Detects context["glyph_ids"] for multi-glyph mode
- Post-processes LAIN result via compute_multi_glyph_resonance
- Merges multi-glyph metrics into fused_symbol
- Maintains backward compatibility (single-glyph unaffected)

## Phase 4: Guardrails & Telemetry

### Guardrail Enforcement
- PUSH_GLYPH_CONTEXT rejects pushes exceeding max_resonance_glyphs
- run_symbolic_pipeline truncates glyph_ids if needed
- Guardrail step recorded in pipeline with reason message

### Telemetry Collection
- ctx._state["last_resonance_stats"] stores:
  - glyph_count: number of glyphs processed
  - global_resonance_score: weighted average [0.0, 1.0]
  - guardrails_triggered: list of guardrail messages
  - timestamp: execution time

## Phase 5: Validation Suite

### 12 Comprehensive Tests (all passing)
1. New operations in OP_TABLE
2. XICContext.glyph_contexts field
3. PUSH_GLYPH_CONTEXT accumulation
4. CLEAR_GLYPH_CONTEXT reset
5. Guardrail enforcement on PUSH
6. run_symbolic_pipeline signature
7. compute_multi_glyph_resonance method
8. Multi-glyph resonance structure
9. execute_symbolic multi-glyph processing
10. Single-glyph backward compatibility
11. Demo programs validity
12. Multi-glyph demo structure

### Test File: test_multi_glyph_resonance.py
- Unit tests for all components
- Integration tests for data flow
- Backward compatibility validation
- Mock-based testing for isolated units

## Phase 6: Documentation

### Updated XIC_SEMANTICS_v1_5.md
- Added PUSH_GLYPH_CONTEXT instruction semantics
- Added CLEAR_GLYPH_CONTEXT instruction semantics
- Added comprehensive Multi-Glyph Resonance section with:
  - Context accumulation model diagram
  - Complete workflow documentation
  - Guardrail specifications
  - Telemetry format definition
  - Three-glyph analysis example with JSON/Python output

### Created demo_multi_glyph_resonance.gx.json
- Two-chain demonstration program
- Chain 1: 3-glyph analysis (compression, entropy, information)
- Chain 2: 4-glyph analysis (cognition, language, symbol, meaning)
- Shows complete resonance query pipeline
- Demonstrates context clearing and reset

### Created XIC_MULTI_GLYPH_RESONANCE_REPORT.md
- Comprehensive implementation documentation
- All 6 phases detailed with code examples
- Architecture overview and data flow diagrams
- Design decisions with rationale
- Backward compatibility guarantees
- Usage examples (CLI, JSON, programmatic)
- Future enhancement suggestions

## Key Features

✅ Explicit context accumulation (PUSH_GLYPH_CONTEXT)
✅ Automatic multi-glyph detection in CALL_GLYPH/RUN_PROMPT/STREAM
✅ Guardrails prevent exceeding max_resonance_glyphs
✅ Telemetry tracking for analytics
✅ Full backward compatibility maintained
✅ Single-glyph mode unaffected
✅ Comprehensive validation suite (12/12 tests passing)
✅ Complete formal specification updates
✅ Demo program showcase

## Backward Compatibility

- All XIC v1 programs work unchanged
- Single-glyph CALL_GLYPH still works identically
- Empty glyph_contexts → single-glyph behavior
- .gx binary format unchanged
- No breaking changes to APIs

Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>
 2026-05-21 02:29:22 -04:00
GlyphRunner System bce6b6fa37 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>
 2026-05-21 02:21:44 -04:00
GlyphRunner System 6e0a586f51 Implement XIC v1.5: Symbolic Pipeline Abstraction with Glyph-Aware Transformations 
Implements all phases of the symbolic pipeline extension:

**Phase 1: Symbolic Pipeline Abstraction**
- Created glyphos/symbolic_pipeline.py with:
  - SymbolicStep: tracks individual pipeline steps (name, kind, payload, context)
  - SymbolicPipelineResult: complete pipeline execution result (steps, output_text, fused_symbol)
  - run_symbolic_pipeline(prompt, context, glyph_id): high-level pipeline entrypoint
- Integrated with glyphos/__init__.py exports

**Phase 2: Glyph-Aware Transformations**
- Updated glyphos/cognitive_kernel.py:
  - run_symbolic_prompt() now thin wrapper around pipeline
  - Maintains backward compatibility
- Updated xic_ops.py operations:
  - op_RUN_PROMPT: uses pipeline in symbolic mode
  - op_STREAM: uses pipeline with line-by-line output
  - op_CALL_GLYPH: routes through pipeline with explicit glyph_id parameter
- Context propagation: glyph_id automatically injected into LAIN context

**Phase 3: XIC Instruction Semantics v1.5**
- Created XIC_SEMANTICS_v1_5.md:
  - Formal specification of all 9 XIC instructions
  - Complete semantics: preconditions, postconditions, side effects
  - Symbolic vs compressed behavior for each op
  - Context model and pipeline semantics
  - Execution paths (compressed vs symbolic)
  - Backward compatibility guarantees

**Phase 4: Demo Program & Validation**
- Created programs/demo_symbolic_pipeline.gx.json
  - Demonstrates symbolic pipeline with glyph-aware cognition
  - Uses CALL_GLYPH, RUN_PROMPT, SET_CONTEXT, CHAIN, LOG
- All 7 validation tests pass:
  ✅ Pipeline module imports
  ✅ Pipeline execution
  ✅ Glyph-aware transformations
  ✅ Demo program
  ✅ CALL_GLYPH result storage
  ✅ Backward compatibility
  ✅ run_symbolic_prompt() wrapper

**Phase 5: Final Report**
- Created XIC_SYMBOLIC_PIPELINE_REPORT.md
  - Architecture and module hierarchy
  - Integration points and data flow
  - Design decisions and rationale
  - Usage examples

Key Features:
- Step-level introspection: full SymbolicPipelineResult with step history
- Glyph-aware: explicit glyph_id routing through LAIN kernel
- Formal semantics: complete specification for tool builders
- Backward compatible: all v1 programs work unchanged
- No breaking changes: compressed execution path untouched

Constraints Met:
✅ No GPU code
✅ No XIC v2 binary container
✅ No .gx format changes
✅ Full backward compatibility
 2026-05-21 01:27:49 -04:00
GlyphRunner System b4ba84c1d2 Refine XIC v1 to Symbolic Extension Only (No GPU Code) 
Removed GPU-related code per specification:
- Deleted xic_extensions/gpu_runtime.py
- Removed GPU logic from op_RUN_PROMPT and op_STREAM
- Removed demo_gpu.gx.json

Kept pure symbolic extension:
- 5 new instructions: STREAM, CHAIN, CALL_GLYPH, SET_CONTEXT, LOG
- Symbolic execution mode via SET_MODE "symbolic"
- run_symbolic_prompt() integration with LAIN cognition layer
- demo_symbolic.gx.json for testing

Implementation now focuses exclusively on:
- Extending instruction set (9 total ops)
- Adding symbolic routing to cognition layer
- Preserving backward compatibility (zero breaking changes)
- No external GPU dependencies

All validation tests pass:
✅ OP_TABLE coverage (9 operations)
✅ XICContext.symbolic_mode field
✅ run_symbolic_prompt() callable
✅ Backward compatibility (demo_chat unchanged)
✅ Symbolic mode execution (LAIN pipeline)
✅ SET_CONTEXT, CHAIN, RUN_PROMPT routing

Constraints met:
✅ No breaking changes
✅ No XIC v2 binary format
✅ No GPU-related code
✅ Strict v1 JSON + .gx architecture
 2026-05-21 01:23:48 -04:00
GlyphRunner System 69c97e125a Extend XIC v1 Engine with Symbolic Mode, 5 New Ops, GPU Path, Cognition Integration 
New instructions:
- STREAM: Line-by-line execution and output
- CHAIN: Named execution boundaries
- CALL_GLYPH: Invoke glyph-aware cognition
- SET_CONTEXT: Set symbolic/cognitive context metadata
- LOG: Structured logging

Symbolic execution mode:
- SET_MODE "symbolic" routes prompts through LAIN 8-lane cognition pipeline
- run_symbolic_prompt() compresses prompt, builds manifest, executes via execute_symbolic()
- Full integration with glyphos/cognitive_kernel.py

GPU-accelerated path:
- xic_extensions/gpu_runtime.py: has_gpu() probes torch.cuda, run_on_gpu() executes
- SET_PARAM "use_gpu" true enables GPU (auto-fallback to CPU if unavailable)
- No required GPU dependencies; system works equally on CPU

Demo programs:
- demo_symbolic.gx.json: Shows symbolic mode through LAIN pipeline
- demo_gpu.gx.json: Shows GPU mode with CPU fallback

Backward compatibility:
- All 4 original ops unchanged; 5 new ops added to OP_TABLE
- xic_vm.py, xic_executor.py: No changes (pure dispatcher pattern holds)
- demo_chat.gx.json: Still executes identically
- All existing GlyphRunner commands: Unchanged behavior

Architecture:
- Lazy imports prevent circular dependencies (xic_ops, glyphos, xic_extensions)
- Clean separation: XIC is client of cognition layer
- Zero breaking changes; additive extension only
- No XIC v2 binary format; all within v1 JSON+.gx architecture

Validation:
- 10 integration tests: all passing
- Backward compat verified with original demo
- Symbolic and GPU modes tested end-to-end
- No external dependencies required (GPU optional)

Co-contributors: LAIN cognition engine, gx_compiler GSZ3, glyphos event system
 2026-05-21 01:19:40 -04:00
GlyphRunner System df19777505 Add XIC v1 Engine — Execute-In-Compressed Runtime Integration 
- Implemented XIC loader, VM, ops, and executor
- Wired RUN_PROMPT directly to execute_gx() (no stubs)
- Added demo compressed model and demo XIC program
- Integrated XIC into glyph_runner.py with --xic flag and shell support
- Added full validation suite and XIC_INTEGRATION_REPORT.md
- Verified real GSZ3 decompression and execution pipeline

This commit introduces a complete compressed-space execution engine
with zero breaking changes and full backward compatibility.
 2026-05-21 01:01:10 -04:00