feat: docs Sphinx pipeline + lien dashboard header
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docs/_build/html/_sources/infrastructure.rst.txt
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docs/_build/html/_sources/infrastructure.rst.txt
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Infrastructure
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==============
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Réseau LAN — 192.168.0.0/24
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-----------------------------
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.. code-block:: text
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┌─────────────────────────────────────────────────────────┐
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│ LAN 192.168.0.0/24 │
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│ │
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│ .82 CORE Dispatcher (systemd) + FastAPI :3849 │
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│ Gitea + Grafana + InfluxDB + Caddy │
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│ │
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│ .84 ml-stack GPU worker RTX 3090 24GB │
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│ .87 gpu GPU worker RTX 3060 12GB │
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│ │
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│ .168 z620 Proxmox host HP Z620 │
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│ SSD → /mnt/portablessd (MP4 bruts) │
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└─────────────────────────────────────────────────────────┘
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Nœud core (.82)
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----------------
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**Rôle :** orchestrateur central du pipeline.
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Services actifs :
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- **Dispatcher** — service systemd cosma-qc-dispatcher.
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Boucle principale qui dispatch les jobs aux workers GPU.
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- **Dashboard FastAPI** — conteneur Docker exposé sur le port **3849**.
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Interface web de monitoring des jobs.
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- **Gitea** — dépôt source floppyrj45/cosma-qc.
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- **Grafana / InfluxDB** — monitoring infrastructure.
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Commandes utiles :
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.. code-block:: bash
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# Statut dispatcher
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sudo systemctl status cosma-qc-dispatcher
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# Logs dispatcher temps réel
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sudo journalctl -u cosma-qc-dispatcher -f
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# Dashboard
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http://192.168.0.82:3849
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Nœuds GPU workers (.84 et .87)
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--------------------------------
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.. list-table::
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:header-rows: 1
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:widths: 15 25 20 40
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* - IP
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- Nom
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- GPU
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- VRAM
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* - .84
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- ml-stack
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- RTX 3090
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- 24 GB
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* - .87
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- gpu
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- RTX 3060
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- 12 GB
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**Rôle :** exécution de ffmpeg (extraction frames) et lingbot-map (reconstruction 3D).
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Répertoire de travail sur chaque worker :
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.. code-block:: text
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/cosma-qc-frames/
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├── job_1/
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│ ├── frame_000001.jpg … frame_NNNNNN.jpg
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│ ├── .video_0.done
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│ ├── reconstruction.ply
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│ └── reconstruction.glb (généré à la demande)
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├── job_2/
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│ └── …
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└── stitch_1.ply
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Nœud z620 (.168)
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-----------------
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**Rôle :** stockage des MP4 bruts GoPro.
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- Proxmox host HP Z620.
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- SSD monté sur /mnt/portablessd.
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- Les MP4 **ne quittent jamais** z620 — ffmpeg s'y exécute via SSH.
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Accès SSH depuis core :
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.. code-block:: bash
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ssh floppyrj45@192.168.0.168
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Service systemd dispatcher
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---------------------------
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Fichier de service : /etc/systemd/system/cosma-qc-dispatcher.service
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.. code-block:: ini
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[Unit]
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Description=COSMA QC Dispatcher
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After=network.target
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[Service]
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User=floppyrj45
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WorkingDirectory=/home/floppyrj45/docker/cosma-qc
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ExecStart=/usr/bin/python3 app/dispatcher.py
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Restart=on-failure
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RestartSec=10
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[Install]
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WantedBy=multi-user.target
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Commandes de gestion :
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.. code-block:: bash
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sudo systemctl start cosma-qc-dispatcher
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sudo systemctl stop cosma-qc-dispatcher
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sudo systemctl restart cosma-qc-dispatcher
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sudo systemctl enable cosma-qc-dispatcher # démarrage auto
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Conteneur Docker dashboard
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---------------------------
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Le dashboard FastAPI tourne dans un conteneur Docker.
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.. code-block:: bash
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cd /home/floppyrj45/docker/cosma-qc
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docker compose up -d # démarrer
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docker compose down # arrêter
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docker compose logs -f # logs
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Accès : http://192.168.0.82:3849
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Ports réseau récapitulatifs
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----------------------------
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.. list-table::
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:header-rows: 1
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:widths: 15 15 70
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* - Host
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- Port
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- Service
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* - .82
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- 3849
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- Dashboard FastAPI cosma-qc
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* - .84 / .87
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- 8100+N
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- Viser viewer (reconstruction job N)
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* - .84 / .87
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- 8300
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- HTTP server GLB export
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