Claude/folder structure burmese 7apslx#202
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- Camera CRUD with go2rtc RTSP stream registration - Incident model with type/severity classification (traffic_accident, fight, etc.) - VLM analysis endpoint: snapshot capture → Celery job → VLM → incident record - LLM agent query endpoint with DB context injection - Shift/daily report generator via LLM agent - WebSocket real-time alert stream via Redis pub/sub - MinIO snapshot storage service - PostgreSQL + asyncpg async ORM (SQLAlchemy 2.0) - Celery worker for async VLM jobs - Docker Compose stack: backend, worker, db, redis, minio, go2rtc Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01DXvYppU6bAHzS9R8HbTHdN
- Dark-theme dashboard with stat cards, severity pie chart, incident type bar chart - Multi-camera live grid (2/3 col toggle) with per-cell VLM analysis trigger - Incident table with filter, resolve/false-alarm actions - AI Agent chat page with quick-suggestion prompts and DB context display - Shift report generator with time window + district filter and TXT download - Camera manager (CRUD, toggle active, delete) with go2rtc registration - Real-time alert ticker bar via WebSocket with auto-reconnect - Full TypeScript, Tailwind dark theme, Recharts for charts - Dockerfile (multi-stage) + docker-compose frontend service Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01DXvYppU6bAHzS9R8HbTHdN
7 analysis modes with tailored VLM prompt templates: - traffic_accident, crowd_anomaly, suspicious_behavior - wrong_way, road_obstruction, fire_smoke, full_scan Features: - Sensitivity levels (low/medium/high) adjusting VLM strictness - Language support: English, Burmese, or bilingual output - Camera location context injection into prompts - YOLO pre-filter: only sends frames to VLM when trigger objects detected - Frame throttle (configurable FPS) to manage VLM token cost - Full Aegis JSONL stdin/stdout protocol compliance - Zero extra Python dependencies (stdlib urllib only) - Standalone test script for prompt validation per mode - deploy.sh with prompt module sanity check Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01DXvYppU6bAHzS9R8HbTHdN
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Thanks for the contribution — this is a lot of ground covered! Before we do a full review, could you share a bit of background: what's this built for (a specific deployment, a demo, etc.), and is Asking because right now it runs as a fully standalone app — its own DB/camera registry/dashboard, no wiring to Aegis's skill runtime or existing camera data — while the new |
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