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Peridot v1.5.1

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@uncoalesced uncoalesced released this 07 Jun 19:17
· 115 commits to main since this release
v1.5.1
d2b7ee0

Peridot - Changelog

Engineered by uncoalesced

Peridot v1.5.1 is the biggest update yet! A major step forward in Peridot’s security posture, hardware adaptability and long term usability. This release hardens the local perimeter (removing high risk deserialization and injection paths), introduces intelligent VRAM aware auto-scaling for smoother performance across GPUs, and delivers persistent multi-session conversational memory so Peridot can support real workflows without losing context between runs. Really delighted with how this update has come together and the stability achieved across this version.

[v1.5.1-STABLE] - 2026-06-08

Name: Peridot v1.5.1 STABLE - Security Hardening, Hardware Auto-Scaling & Multi-Session Memory

Security & Compliance (Phase 1: Critical Hotfixes)

  • API Key Rotation: Eliminated hardcoded default key (08101954). config.py now generates a cryptographically secure secrets.token_hex(32) on first boot and persists to .env via python-dotenv. Each deployment receives a unique 256-bit key.
  • Pickle RCE Remediation: core_system/memory/vault.py - Replaced pickle.load()/dump() with json.load()/dump() for metadata serialization (.meta file). Removes arbitrary code execution vector via malicious serialized metadata.
  • Shell Injection Hardening: ui.py - Removed shell=True from all subprocess.check_output() calls to nvidia-smi. Arguments now passed as safe arrays (creationflags=0x08000000 preserved for window suppression).
  • CORS Restriction: server.py - Restricted CORS(app) to exclusively allow http://127.0.0.1:5000 and http://localhost:5000. Blocks cross-origin requests from external origins.
  • Multi-Session Conversational Memory: New core_system/chat_ledger.py - SQLite-backed chat ledger with session CRUD, message logging, and sliding-window history retrieval (get_history(session_id, limit=6)). Integrated into /ask route: accepts optional session_id, auto-creates titled sessions, persists user/assistant turns, injects last 6 turns into prompt context, returns session_id for client continuity.

Hardware Auto-Scaling (Phase 2: VRAM Detection)

  • Dynamic VRAM Detection: config.py - Added _detect_total_vram_mb() using nvidia-smi --query-gpu=memory.total (safe subprocess, no shell). Detects total GPU VRAM at module load.
  • Auto GPU_LAYERS Calculation: If model size < 75% of total VRAM -> GPU_LAYERS=99 (full offload). Else -> GPU_LAYERS=20 (partial). CPU-only fallback: GPU_LAYERS=0.
  • Auto CONTEXT_LENGTH Calculation: >10GB VRAM -> 8192 tokens. <=10GB VRAM -> 4096 tokens. CPU-only -> 2048 tokens.
  • UI Integration: ui.py now imports TOTAL_VRAM_GB from config instead of hardcoded 8.0 or duplicate nvidia-smi call. Model compatibility ratings in dropdown use dynamic VRAM envelope.

RAG Ingestion Overhaul (Phase 3: PyMuPDF & Metadata Tagging)

  • Layout-Preserving PDF Extraction: core_system/memory/vault.py - Replaced fitz.get_text("text") with fitz.get_text("text", sort=True) to preserve visual layout geometry of multi-column tables (e.g., Balance Sheets).
  • Provenance Tagging: core_system/memory/vault.py Every text chunk now strictly prepends [SOURCE DOC: {filename}] before embedding, enabling the LLM to cite exact documentary sources during generation.
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