GlyphRunner System
1a0b45df9c
New subsystem fully self-contained: Components: - LLMCompress/llm_adapter.py: LLMAdapter + LLMResponse (abstract over LLM backends) - LLMCompress/compression_report.py: CompressionReport (symbolic analysis results) - LLMCompress/llm_compressor.py: compress_interaction() and compress_session() - LLMCompress/tests/test_llm_compress.py: 5 comprehensive tests Integration: - Uses GlyphOS Cognitive Kernel for symbolic analysis - Integrates with GlyphOS Event System - Emits cognition.started and cognition.completed events - Supports in-memory GX execution via execute_symbolic() Test Coverage: - LLMCompress tests: 5/5 PASS - All existing tests still pass (52/52) - Total: 57 tests passing Bug fixes in cognitive_kernel.py: - Fixed execute_symbolic() method calls to use correct function signatures - normalize_segments(manifest, segments, payload) - map_lanes(segments) - build_envelope(manifest, lanes, payload, context) - execute_with_lain(envelope) Constraints: - No modifications to gx_compiler/* - No modifications to glyphs/super_registry.py - Self-contained subsystem with proper isolation - Full backward compatibility maintained
40 lines
1.3 KiB
Python
40 lines
1.3 KiB
Python
"""Compression report structures for LLMCompress."""
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from __future__ import annotations
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from dataclasses import dataclass, field
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from typing import Any, Dict, List, Optional
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@dataclass
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class CompressionReport:
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"""Symbolic compression report for a single LLM interaction or session."""
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# Raw interaction(s)
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interactions: List[Dict[str, Any]] = field(default_factory=list)
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# Symbolic outputs from LAIN / GlyphOS
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fused_symbol: Optional[Dict[str, Any]] = None
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diagnostics: Optional[Dict[str, Any]] = None
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cognition_trace: Optional[List[Dict[str, Any]]] = None
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# Glyph-related summaries
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glyph_ids: List[str] = field(default_factory=list)
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glyph_resonance: Optional[Dict[str, Any]] = None
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# Free-form notes / tags
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tags: List[str] = field(default_factory=list)
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metadata: Dict[str, Any] = field(default_factory=dict)
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def to_dict(self) -> Dict[str, Any]:
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return {
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"interactions": self.interactions,
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"fused_symbol": self.fused_symbol,
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"diagnostics": self.diagnostics,
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"cognition_trace": self.cognition_trace,
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"glyph_ids": self.glyph_ids,
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"glyph_resonance": self.glyph_resonance,
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"tags": self.tags,
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"metadata": self.metadata,
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}
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