SME v2.1.0: The Rhetorical Fingerprint (Lawnmower Man)

🌿 SME v2.1.0: The Rhetorical Fingerprint (Lawnmower Man)
This release shifts the Semantic-Memory-Engine from simple data ingestion to Forensic Stylometry. By integrating Microsoft's MarkItDown and formalizing archival diffs, SME can now track not just what was said, but how it was said and how it changed over time.

🧬 New Forensic Capabilities
Rhetorical Fingerprinting: Introduced active_persona.json mapping. The engine now identifies stylistic markers in ingested text using the vendored faststylometry suite, bypassing PyPI dependency issues.

Archival Diff Specification: Formalized the logic for tracking "Semantic Drift." This allows the engine to compare two versions of a document and highlight changes in intent or sentiment, not just text.

MarkItDown Integration: Switched to a more robust markdown conversion for web ingestion, ensuring high-fidelity "atomic facts" for the Knowledge Graph.

⚡ Hardware Optimizations (GTX 1660 Ti / 6GB VRAM)
Memory Footprint Audit: Verified that the auditor.py (Isolation Forest) maintains a <5MB RAM footprint.

VRAM Safeguards: The gephi_bridge.py now strictly enforces the 2000-node limit to prevent OOM crashes during large codebase visualizations.

Sidecar Isolation: The Dual-Python architecture is now standard, allowing the Logic Layer (Operator) to run on Python 3.10 while the Inference Layer (Sidecar) handles heavier ML tasks.

🧪 Validation Results
Master Forensic Test Suite: 100% Pass rate on all forensic utilities.

Container Health: Unified docker-compose now successfully orchestrates the Operator, Sidecar, and the Vite-based Control Room.