Project_Velocity/.Agent Context/Sprint 1/velocity_status_report.md

Project Velocity: Sentinel QD Engine Status Report

Generated: April 1, 2026

This artifact provides a comprehensive overview of the current status of the Sentinel Quantum Dynamics (QD) Engine. It maps the architectural decisions and milestones directly to the codebase, detailing what has been completed, deployed, and what remains to be done.

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1. Architectural Adjustments & Realities

During the NemoClaw deployment (Milestone 4 & 7), several key architectural realities emerged that forced an adjustment to the original design:

1. Inference Pipeline Switch (NVIDIA API vs. Ollama)

   • Original Plan: Route traffic through the OpenShell mTLS gateway locally holding qwen3.5:27b.
   • The Reality: The qwen3.5:27b model under Ollama currently runs in an extended "think mode" (chain-of-thought) which exhausts token limits before outputting JSON, causing timeouts. The OpenShell Gateway also expects internal sandbox client certificates (mTLS).
   • The Pivot: We have updated nemoclaw_client.py to use the NVIDIA API directly (llama-3.3-nemotron-super-49b-v1) as the primary inference engine since it is OpenAI-compatible, fast, and reliable. Ollama remains a fallback (with a known TODO to fix the think parameter parsing).

2. Storage Eviction Issues Resolved

   • The Reality: k3s and Docker were exhausting the root /dev/root volume, triggering disk pressure evictions and crashing OpenShell pods.
   • The Pivot: We migrated the 103GB model cache and the /var/lib/rancher k3s storage to the 3.4TB /opt/dlami/nvme partition, restoring disk health and allowing NemoClaw to successfully "onboard" and enter a "Ready" state.

3. Port Collisions

   • The Reality: Both the existing velocity-oracle and the OpenShell gateway wanted port 8080.
   • The Pivot: We migrated velocity-oracle to bind to port 8081.

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2. Codebase Map: What is Done

✅ Milestone 1: Database & Auth

• Types: app/src/types/index.ts (BiometricPacket, QDScore, Notifications)
• State: app/src/store/useStore.ts (Notification state management)
• Schema: backend/db/schema.sql, backend/db/schema_addendum.sql
• Pool Data: backend/db/pool.py, backend/auth/dependencies.py
• Entrypoint: backend/main.py (FastAPI lifecycle and router integration)

✅ Milestone 2: Velocity Link & Notifications

• Routers: backend/routers/vault.py
• Hooks: app/src/hooks/useVelocitySocket.ts
• UI: app/src/components/layout/NotificationCenter.tsx + App.tsx wiring.

✅ Milestone 3: Perception Pipeline (Frontend)

• WASM Encoders: app/src/utils/landmarkPacketEncoder.ts
• Vision Feed: app/src/hooks/useMediapipeFaceLandmarker.ts
• Live UI: app/src/components/modules/sentinel/PerceptionPlayer.tsx + SentinelLiveSession.tsx

✅ Milestone 4 & 7: NemoClaw Sandbox & AWS Env

• Client Logic: backend/services/nemoclaw_client.py (Now pointed to NVIDIA API)
• Prompts: Uploaded to NVMe (cctv_profiler.md, lead_tagger.md, qd_calculator.md)
• System Service: nemoclaw-velocity.service created and enabled.
• Environment: /opt/dlami/nvme/velocity/env written.
• NemoClaw Onboarding: Succeeded; the sandbox is completely ready (Phase: Ready).

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3. Pending Workflow: What is Left

⏳ Database Initialization (Finalizing Milestone 1/7)

While the backend code and schema files exist, the AWS database instance itself has not been booted.

• Action Required: Instantiate PostgreSQL on /opt/dlami/nvme/pgdata and execute schema.sql and schema_addendum.sql.
• Action Required: Point FastAPI to the PostgreSQL instance.

⏳ Milestone 5: CCTV & Auto Mode Integration

• Action Required: Build backend/routers/cctv.py to ingest frames.
• Action Required: Build OCR bridging logic to pass plates and cars to the NemoClaw prompt (cctv_profiler.md) and into the DB.
• Action Required: Build backend/services/auto_mode_matcher.py (matching CCTV feed data to post-session lead attribution).

⏳ Milestone 6: Video Scene CSV Upload

• Action Required: Implement backend/routers/scenes.py (/api/scenes/upload endpoint).
• Action Required: Integrate the scene context into the frontend PerceptionPlayer to correlate timestamped video annotations with real-time biometric feeds.

⏳ Milestone 8: End-to-End Integration Testing

• Action Required: E2E testing of the full pipeline (Frontend → FastAPI → PostgreSQL/NemoClaw → Frontend Notifications).