c3a826b65c927ec096247e5d1762d6c3f96e88fd
5 Commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
|
|
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> |
||
|
|
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 |
||
|
|
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 |
||
|
|
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. |
||
|
|
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. |