- .github/workflows/verify-pipeline.yml: CI that verifies pipeline
determinism and checks for np.random in production code
- ui/components/body-model.js: Three.js 3D human body model with
24 DensePose body parts mapped to 3D geometry
- v1/requirements-lock.txt: Minimal pinned dependencies for verification
- v1/src/api/dependencies.py: Fix mock auth returns with proper errors
- v1/src/core/router_interface.py: Additional mock mode cleanup
- v1/src/services/pose_service.py: Further mock elimination in service
https://claude.ai/code/session_01Ki7pvEZtJDvqJkmyn6B714
Commodity Sensing Module (ADR-013):
- sensing/rssi_collector.py: Real Linux WiFi RSSI collection from
/proc/net/wireless and iw commands, with SimulatedCollector for testing
- sensing/feature_extractor.py: FFT-based spectral analysis, CUSUM
change-point detection, breathing/motion band power extraction
- sensing/classifier.py: Rule-based presence/motion classification
with confidence scoring and multi-receiver agreement
- sensing/backend.py: Common SensingBackend protocol with honest
capability reporting (PRESENCE + MOTION only for commodity)
Proof of Reality Bundle (ADR-011):
- data/proof/generate_reference_signal.py: Deterministic synthetic CSI
with known breathing (0.3 Hz) and walking (1.2 Hz) signals
- data/proof/sample_csi_data.json: Generated reference signal
- data/proof/verify.py: One-command pipeline verification with SHA-256
- data/proof/expected_features.sha256: Expected output hash
Three.js Visualization:
- ui/components/scene.js: 3D scene setup with OrbitControls
Mock Isolation:
- testing/mock_pose_generator.py: Mock pose generation moved out of
production pose_service.py
- services/pose_service.py: Cleaned mock paths
https://claude.ai/code/session_01Ki7pvEZtJDvqJkmyn6B714
- Created comprehensive API reference documentation covering authentication, request/response formats, error handling, and various API endpoints for pose estimation, system management, health checks, and WebSocket interactions.
- Developed a detailed deployment guide outlining prerequisites, Docker and Kubernetes deployment steps, cloud deployment options for AWS, GCP, and Azure, and configuration for production environments.
