Add LLMCompress subsystem - sandbox for symbolic compression of LLM behavior

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

LLMCompress/compression_report.py

@@ -0,0 +1,39 @@
+"""Compression report structures for LLMCompress."""
+
+from __future__ import annotations
+
+from dataclasses import dataclass, field
+from typing import Any, Dict, List, Optional
+
+
+@dataclass
+class CompressionReport:
+    """Symbolic compression report for a single LLM interaction or session."""
+
+    # Raw interaction(s)
+    interactions: List[Dict[str, Any]] = field(default_factory=list)
+
+    # Symbolic outputs from LAIN / GlyphOS
+    fused_symbol: Optional[Dict[str, Any]] = None
+    diagnostics: Optional[Dict[str, Any]] = None
+    cognition_trace: Optional[List[Dict[str, Any]]] = None
+
+    # Glyph-related summaries
+    glyph_ids: List[str] = field(default_factory=list)
+    glyph_resonance: Optional[Dict[str, Any]] = None
+
+    # Free-form notes / tags
+    tags: List[str] = field(default_factory=list)
+    metadata: Dict[str, Any] = field(default_factory=dict)
+
+    def to_dict(self) -> Dict[str, Any]:
+        return {
+            "interactions": self.interactions,
+            "fused_symbol": self.fused_symbol,
+            "diagnostics": self.diagnostics,
+            "cognition_trace": self.cognition_trace,
+            "glyph_ids": self.glyph_ids,
+            "glyph_resonance": self.glyph_resonance,
+            "tags": self.tags,
+            "metadata": self.metadata,
+        }