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Author SHA1 Message Date
GlyphRunner System ae13f78c22 Initial commit: 2125_GCE project 2026-07-09 12:54:44 -04:00
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 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 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 9792449157 Implement GlyphOS Event System 
Add lightweight, in-process event bus with Cognitive Kernel integration:

New Components:
- glyphos/events.py: EventBus class + functional API
  * EventBus: publish/subscribe pattern with history
  * Event type definitions (EventType literal)
  * Singleton: get_event_bus(), emit(), on()
  * History filtering and limits
  * Graceful handler error handling

- tests/test_events.py: Comprehensive test suite (16 tests, 100% pass)
  * EventBus subscription/publishing/history
  * Global singleton behavior
  * Functional API (on, emit, get_event_bus)
  * Kernel integration tests
  * Cognition event emission tests

Modified:
- glyphos/cognitive_kernel.py: Event emissions at key points
  * kernel.warmup.completed: After warmup() completes
  * cognition.started: At start of execute_gx()
  * cognition.completed: After execute_gx() completes
  * glyph.resonance.updated: When glyph resonance present

- glyphos/__init__.py: Export events module

Test Results:
- Registry tests:          12/12 ✅
- Bridge tests:            10/10 ✅
- Kernel tests:             8/8  ✅
- Event system tests:      16/16 ✅ (NEW)
- Integration tests:        6/6  ✅
- Total:                   52/52 ✅

No breaking changes - all 36 existing tests still pass.
 2026-05-20 18:11:25 -04:00
GlyphRunner System 5c4bfb2dc1 Implement GlyphOS Cognitive Kernel 
Add a system service layer on top of LAIN cognition and Supercharged Glyph Registry:

Components:
- glyphos/cognitive_kernel.py: CognitiveKernel class + functional API
  * CognitiveKernel: Main orchestrator with execute_gx(), execute_symbolic()
  * Result accessors: get_last_result(), get_last_trace(), get_last_fused_symbol()
  * get_kernel(): Singleton kernel instance
  * run_gx(): Convenience function for global kernel
  * kernel_status(): Status introspection

- glyphos/__init__.py: Package initialization

- tests/test_cognitive_kernel.py: Comprehensive test suite (8 tests, 100% pass)
  * Kernel initialization and warmup
  * GX execution and result validation
  * Result accessor methods
  * Singleton pattern
  * Functional API

- COGNITIVE_KERNEL.md: Complete documentation

Test Results:
- 12 registry tests ✅
- 10 glyph bridge tests ✅
- 6 integration suites ✅
- 8 cognitive kernel tests ✅
- Total: 36 tests, 0 failures

No breaking changes - all existing tests pass.
 2026-05-20 18:03:25 -04:00