documentation and system diagrams
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buenosairesam
153
def/architecture/asciidiagram.md
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153
def/architecture/asciidiagram.md
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+-------+
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| OBS | RTMP stream
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+---+---+ --------------+
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| |
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v |
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+-----+------+ |
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| nginx-rtmp |-- HLS ───+ |
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| (RTMP/HLS) | | |
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+-----+------+ | |
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| | |
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HLS on /media | |
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| | |
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v | |
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+----------+-----------+ | |
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| Host “media/” dir |<----+ |
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+----------+-----------+ |
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| File watcher |
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v |
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+----------+-----------+ |
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| Django Backend | |
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| (REST + ASGI + WS) +<--WebSocket--+
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+---+------------------+ |
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| | |
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| +-------+ HTTP/API |
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| v |
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| +-------+------+ |
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| | PostgreSQL | |
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| +-------+------+ |
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| |
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| Celery tasks |
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v |
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+------+--------+ queue +------+--------+
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| celery-logo |<-----------| celery-default |
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+---------------+ +---------------+
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| ^
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| |
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+----> Redis (broker) <------+
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Frontend:
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+-----------+
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| Angular |
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| (4200) |
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+-----+-----+
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| HTTP/API (/api/…)
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+-----v-----+
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| Nginx |
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| (SSP) |
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+-----------+
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Legend:
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• OBS pushes RTMP into nginx-rtmp, which writes HLS (.m3u8/.ts) into the shared media/ folder.
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• Django’s file-watcher polls media/ for new segments and enqueues Celery tasks.
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• Django Backend serves REST API, WebSockets (via Channels → Redis), and hosts analysis logic.
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• Celery Workers consume tasks from Redis:
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– celery-logo for logo detection
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– celery-default (or others) for visual analysis, etc.
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• PostgreSQL holds application & analysis metadata.
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• Angular (dev or static via Nginx) calls the Django API and listens on WebSockets.
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• Nginx (frontend) proxies /api and /ws to Django and serves the Angular SPA.
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This layout keeps streaming, AI-processing, data storage, and UI layers cleanly separated.
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codex
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Below is an updated architecture sketch—with the local webcam path and AI execution‐strategy layer added. Each box is a service or component, and arrows show the main flows:
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+--------+
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| OBS | RTMP stream
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+---+----+ --------+
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| |
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v |
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+-------+------+ |
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| nginx-rtmp |-- HLS →| (writes .m3u8/.ts to host media/)
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| (RTMP/HLS) | |
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+-------+------+ |
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| |
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+------------+---------------+-------------+
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| HLS |
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v |
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+------+-------+ |
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| Host “media/”|<-----------------------------------+
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| directory | (mount in backend & nginx-rtmp)
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+------+-------+
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| (poll .ts files)
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v
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+------+-------+
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| File Watcher | → enqueues Celery tasks
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+------+-------+
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v
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+------+-------+
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| Django | REST API & WebSocket (ASGI)
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| Backend |
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| - RTMP/Webcam|
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| Adapters |
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+------+-------+
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| +--------------------------------+
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| WebSocket | |
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+---------->+ Frontend Nginx (SPA + proxy) |
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| | – Serves Angular app on 80 |
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| | – Proxies /api → Django |
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v | – Proxies /ws → Django |
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+------+-------+ | – Proxies /streaming → nginx-rtmp
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| PostgreSQL | +--------------------------------+
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+------+-------+
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v
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+------+-------+ +------------------------+
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| Redis |<-----------+ Celery Workers |
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| (broker) | tasks | – Worker queues: |
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+------+-------+ | logo_detection, |
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| | visual_analysis, |
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| | default… |
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+------------------→ | – Uses AnalysisEngine |
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| with Execution |
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| Strategies: |
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| • local (in-worker) |
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| • remote LAN (via |
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| worker_host) |
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| • cloud (via API) |
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+------------------------+
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+--------+
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| Webcam | local device
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+---+----+
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| via Django’s Webcam
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|SourceAdapter (ffmpeg)
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v
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[ Django Backend ]
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v
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+------+-------+
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| Host “media/”|
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+--------------+
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Key points:
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• OBS → nginx-rtmp → host “media/” → Django file-watcher → Celery tasks
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• Local Webcam → Django backend (WebcamSourceAdapter with ffmpeg) → host “media/” → same pipeline
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• Django Backend (REST + ASGI/WebSocket) ↔ Angular (served by Frontend Nginx)
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• Celery Workers pick up tasks from Redis, run AnalysisEngine → can execute locally, offload to remote LAN workers, or call cloud APIs
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• PostgreSQL stores streams, queue, and analysis results
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This should give a clear bird’s-eye of how data and control flow through your streaming+AI stack.
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