Initial release: DictIA v0.8.14-alpha (fork de Speakr, AGPL-3.0)
This commit is contained in:
InnovA AI
118
deployment/docs/LOCAL-SETUP.md
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118
deployment/docs/LOCAL-SETUP.md
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# Setup Local — DictIA
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Guide pour deployer DictIA localement avec GPU NVIDIA ou CPU.
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## Profil local-gpu
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### Prerequis
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- NVIDIA GPU avec support CUDA
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- [nvidia-container-toolkit](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/install-guide.html)
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- Docker + Docker Compose V2
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- 8GB+ RAM (16GB recommande)
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- Token HuggingFace (pour la diarisation)
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### Installation nvidia-container-toolkit
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```bash
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# Ubuntu/Debian
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curl -fsSL https://nvidia.github.io/libnvidia-container/gpgkey | \
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sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg
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curl -s -L https://nvidia.github.io/libnvidia-container/stable/deb/nvidia-container-toolkit.list | \
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sed 's#deb https://#deb [signed-by=/usr/share/keyrings/nvidia-container-toolkit-keyring.gpg] https://#g' | \
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sudo tee /etc/apt/sources.list.d/nvidia-container-toolkit.list
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sudo apt-get update
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sudo apt-get install -y nvidia-container-toolkit
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sudo nvidia-ctk runtime configure --runtime=docker
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sudo systemctl restart docker
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# Verifier
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docker run --rm --gpus all nvidia/cuda:12.0-base nvidia-smi
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```
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### Setup DictIA
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```bash
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cd dictia
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bash deployment/setup.sh --profile local-gpu
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```
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Le setup va verifier:
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- nvidia-container-toolkit installe
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- GPU accessible depuis Docker
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- Assez de RAM disponible
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### Configuration du modele
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Par defaut, WhisperX utilise `large-v3`. Pour changer:
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```bash
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# Editer .env
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ASR_MODEL=large-v3 # Meilleure qualite
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# ASR_MODEL=medium # Plus rapide, qualite correcte
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# ASR_MODEL=small # Tres rapide, qualite reduite
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```
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---
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## Profil local-cpu
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### Prerequis
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- Docker + Docker Compose V2
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- 18GB+ RAM (WhisperX CPU est gourmand)
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- Patience (transcription ~10x temps reel)
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### Setup
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```bash
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cd dictia
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bash deployment/setup.sh --profile local-cpu
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```
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### Limitations
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- Transcription lente: 1h d'audio prend ~10h
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- Utilise float32 (pas de GPU acceleration)
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- Limite memoire a 18GB par defaut
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- Recommande pour: tests, petits fichiers, demos
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Pour reduire l'utilisation memoire, utiliser un modele plus petit:
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```bash
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# Editer .env
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ASR_MODEL=small # ou medium, base, tiny
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```
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---
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## Verification
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```bash
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# Health check
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bash deployment/tools/health-check.sh
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# Test rapide: ouvrir le navigateur
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open http://localhost:8899
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# Verifier WhisperX
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curl http://localhost:9000/health
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```
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## Gestion des containers
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```bash
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COMPOSE_FILE=deployment/docker/docker-compose.local-gpu.yml # ou local-cpu
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# Logs
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docker compose -f $COMPOSE_FILE logs -f
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# Redemarrer
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docker compose -f $COMPOSE_FILE restart
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# Arreter
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docker compose -f $COMPOSE_FILE down
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# Voir l'utilisation GPU
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nvidia-smi # (profil GPU seulement)
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```
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136
deployment/docs/MAINTENANCE.md
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136
deployment/docs/MAINTENANCE.md
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# Maintenance — DictIA
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## Backup
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```bash
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# Backup complet (data, .env, volumes, stats ASR)
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bash deployment/tools/backup.sh
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# Backup dans un repertoire specifique
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bash deployment/tools/backup.sh /mnt/backups
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```
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Les backups sont sauvegardes dans `backups/` avec rotation automatique (garde les 5 derniers).
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Contenu d'un backup:
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- `data/` — uploads et base de donnees SQLite
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- `dot-env` — fichier de configuration
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- `asr-usage-stats.json` — stats d'utilisation GPU
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- `whisperx-cache.tar.gz` — cache modeles (si volume Docker)
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- `manifest.json` — metadonnees du backup
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### Schedule recommande
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| Frequence | Action |
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|-----------|--------|
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| Quotidien | `bash deployment/tools/backup.sh` |
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| Hebdomadaire | Copier le backup sur un stockage externe |
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| Mensuel | Verifier la restauration sur un environnement de test |
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Pour automatiser avec cron:
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```bash
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# Backup quotidien a 3h du matin
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0 3 * * * /opt/dictia/deployment/tools/backup.sh >> /var/log/dictia-backup.log 2>&1
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```
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## Restore
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```bash
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# Lister les backups disponibles
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ls -la backups/
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# Restaurer un backup
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bash deployment/tools/restore.sh backups/dictia-20260211-030000.tar.gz
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```
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Le script:
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1. Valide l'archive (presence du manifest)
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2. Demande confirmation
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3. Arrete les containers
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4. Restaure les fichiers
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5. Redemarre les containers
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## Mise a jour
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```bash
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# Mise a jour complete (git pull + rebuild + restart)
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bash deployment/tools/update.sh
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# Rebuild seulement (sans git pull)
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bash deployment/tools/update.sh --no-pull
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# Git pull seulement (sans rebuild)
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bash deployment/tools/update.sh --no-build
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```
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Le script:
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1. Detecte le profil actif automatiquement
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2. `git pull origin dictia-branding`
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3. `docker build -t innova-ai/dictia:latest .`
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4. Pull WhisperX upstream (profils locaux)
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5. `docker compose down && up -d`
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6. Attend le health check
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7. Nettoie les images dangling
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## Monitoring
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### Health check
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```bash
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# Diagnostic complet (humain)
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bash deployment/tools/health-check.sh
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# JSON (pour alertes/scripts)
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bash deployment/tools/health-check.sh --json
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# Code de sortie seulement (0=ok, 1=probleme)
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bash deployment/tools/health-check.sh --quiet
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```
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### Logs
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```bash
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# DictIA
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docker logs dictia -f --tail 100
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# WhisperX (profils locaux)
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docker logs whisperx-asr -f --tail 100
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# ASR Proxy (profil cloud)
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journalctl -u asr-proxy -f
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```
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### Dashboard GPU (profil cloud)
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Le dashboard de monitoring GPU est accessible a:
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- `http://localhost:9090` (local)
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- `https://votre-hostname.tailnet.ts.net:9443` (Tailscale)
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Affiche: statut GPU, cout mensuel, historique des requetes, zones de fallback.
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### Metriques cles
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```bash
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# Espace disque (les transcriptions grossissent)
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df -h /opt/dictia/data/
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# Utilisation memoire (WhisperX est gourmand)
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docker stats --no-stream
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# Stats GPU (profil cloud)
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curl -s http://localhost:9090/stats | python3 -m json.tool
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```
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## Maintenance Docker
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```bash
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# Nettoyer les images orphelines
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docker image prune -f
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# Nettoyer tout (attention: supprime les volumes non utilises)
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# docker system prune -a --volumes
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# Verifier l'espace Docker
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docker system df
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```
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90
deployment/docs/QUICKSTART.md
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90
deployment/docs/QUICKSTART.md
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# Quickstart — DictIA
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## Prerequis communs
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- Docker + Docker Compose V2
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- Git
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- 2GB+ RAM disponible
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```bash
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git clone https://gitea.innova-ai.ca/Innova-AI/dictia.git
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cd dictia
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git checkout dictia-branding
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```
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---
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## Profil Cloud (VPS + GCP GPU)
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Le GPU demarre automatiquement quand quelqu'un transcrit, et s'arrete apres 5 min d'inactivite.
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```bash
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# 1. Setup interactif
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bash deployment/setup.sh --profile cloud
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# 2. Setup ASR Proxy (GCP credentials requises)
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bash deployment/asr-proxy/setup.sh
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# 3. Optionnel: Tailscale Serve pour HTTPS
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bash deployment/config/tailscale/setup-serve.sh
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```
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**Requis**: credentials GCP (service account ou OAuth) dans `deployment/asr-proxy/gcp-credentials.json`.
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---
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## Profil Local GPU
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Transcription locale sur GPU NVIDIA. Le plus rapide.
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```bash
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# Prerequis: nvidia-container-toolkit
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# https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/install-guide.html
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# Setup
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bash deployment/setup.sh --profile local-gpu
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```
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**Requis**: token HuggingFace pour la diarisation (pyannote).
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---
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## Profil Local CPU
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Transcription sur CPU. Lent mais fonctionnel pour tester.
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```bash
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bash deployment/setup.sh --profile local-cpu
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```
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Prevoir ~10x le temps reel (1h audio = ~10h de traitement).
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---
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## Apres l'installation
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```bash
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# Verifier que tout fonctionne
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bash deployment/tools/health-check.sh
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# Ouvrir DictIA
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open http://localhost:8899
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```
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Se connecter avec les identifiants admin configures pendant le setup.
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## Commandes utiles
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```bash
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# Logs en temps reel
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docker compose -f deployment/docker/docker-compose.<profil>.yml logs -f
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# Redemarrer
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docker compose -f deployment/docker/docker-compose.<profil>.yml restart
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# Mise a jour
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bash deployment/tools/update.sh
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# Backup
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bash deployment/tools/backup.sh
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```
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177
deployment/docs/TROUBLESHOOTING.md
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177
deployment/docs/TROUBLESHOOTING.md
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# Troubleshooting — DictIA
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## WhisperX OOM (Out of Memory)
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**Symptome**: Container `whisperx-asr` crash ou restart en boucle.
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**Cause**: Modele trop gros pour la RAM/VRAM disponible.
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**Solutions**:
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```bash
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# Utiliser un modele plus petit dans .env
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ASR_MODEL=medium # au lieu de large-v3
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# Augmenter la limite memoire (local-cpu)
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# Editer docker-compose.local-cpu.yml
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deploy:
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resources:
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limits:
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memory: 24G # au lieu de 18G
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```
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## Diarisation 403 Forbidden
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**Symptome**: Erreur 403 lors de la transcription avec diarisation.
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**Cause**: Token HuggingFace manquant ou conditions non acceptees.
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**Solution**:
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1. Creer un token: https://huggingface.co/settings/tokens
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2. Accepter les conditions: https://huggingface.co/pyannote/speaker-diarization-3.1
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3. Ajouter dans `.env`:
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```bash
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HF_TOKEN=hf_votre_token
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```
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4. Redemarrer: `docker compose -f deployment/docker/docker-compose.<profil>.yml restart`
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## GPU non detecte (local-gpu)
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**Symptome**: `nvidia-smi` fonctionne mais Docker ne voit pas le GPU.
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**Solution**:
|
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```bash
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# Installer nvidia-container-toolkit
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sudo apt install -y nvidia-container-toolkit
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sudo nvidia-ctk runtime configure --runtime=docker
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sudo systemctl restart docker
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# Verifier
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docker run --rm --gpus all nvidia/cuda:12.0-base nvidia-smi
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```
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## Upload echoue (fichiers volumineux)
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**Symptome**: Upload de gros fichiers (>100MB) echoue.
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**Causes possibles**:
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- Timeout Nginx/reverse proxy
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- Limite upload trop basse
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||||
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**Solutions**:
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||||
```bash
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# Si Nginx: verifier client_max_body_size dans dictia.conf
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client_max_body_size 500M;
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# Si Tailscale Serve: pas de limite cote Tailscale
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||||
# Timeout gunicorn (dans le Dockerfile, deja a 600s)
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||||
# Pour des fichiers tres longs, augmenter dans docker-compose:
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environment:
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- GUNICORN_TIMEOUT=1200
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```
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## Container dictia "unhealthy"
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**Symptome**: `docker ps` montre "unhealthy" pour le container dictia.
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**Diagnostic**:
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```bash
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# Voir les logs
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docker logs dictia --tail 50
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||||
# Tester manuellement
|
||||
docker exec dictia python3 -c "import urllib.request; urllib.request.urlopen('http://localhost:8899/health')"
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```
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**Causes courantes**:
|
||||
- `.env` mal configure (SECRET_KEY manquant)
|
||||
- Base de donnees corrompue (restaurer backup)
|
||||
- Port 8899 deja utilise
|
||||
|
||||
## ASR Proxy: "No GPU available"
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||||
|
||||
**Symptome**: Transcription echoue avec "No GPU available in any Canadian zone".
|
||||
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||||
**Causes**:
|
||||
- GCP n'a pas de GPU disponible (capacite epuisee)
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||||
- Credentials GCP expirees
|
||||
- Budget mensuel atteint
|
||||
|
||||
**Diagnostic**:
|
||||
```bash
|
||||
# Verifier le statut du proxy
|
||||
curl -s http://localhost:9090/health | python3 -m json.tool
|
||||
|
||||
# Verifier les stats (budget)
|
||||
curl -s http://localhost:9090/stats | python3 -m json.tool
|
||||
|
||||
# Voir les logs
|
||||
journalctl -u asr-proxy --since "1 hour ago"
|
||||
```
|
||||
|
||||
**Solutions**:
|
||||
- Attendre (GCP libere des GPUs regulierement)
|
||||
- Le proxy reessaie automatiquement apres un cooldown de 3 minutes
|
||||
- Verifier le dashboard: http://localhost:9090
|
||||
|
||||
## Build Docker lent/echoue
|
||||
|
||||
**Symptome**: `docker build` prend trop de temps ou echoue.
|
||||
|
||||
**Solutions**:
|
||||
```bash
|
||||
# Limiter les ressources si le VPS est petit
|
||||
docker build --memory=2g --cpus=2 -t innova-ai/dictia:latest .
|
||||
|
||||
# Nettoyer le cache Docker si le disque est plein
|
||||
docker builder prune -f
|
||||
docker image prune -f
|
||||
```
|
||||
|
||||
## Base de donnees corrompue
|
||||
|
||||
**Symptome**: Erreur SQLite au demarrage.
|
||||
|
||||
**Solution**:
|
||||
```bash
|
||||
# Restaurer le dernier backup
|
||||
bash deployment/tools/restore.sh backups/dictia-LATEST.tar.gz
|
||||
|
||||
# Ou recreer la base (perd les donnees)
|
||||
rm data/instance/transcriptions.db
|
||||
docker compose -f deployment/docker/docker-compose.<profil>.yml restart
|
||||
```
|
||||
|
||||
## Port 8899 deja utilise
|
||||
|
||||
```bash
|
||||
# Trouver qui utilise le port
|
||||
sudo lsof -i :8899
|
||||
# ou
|
||||
sudo ss -tlnp | grep 8899
|
||||
|
||||
# Arreter le processus ou changer le port dans docker-compose
|
||||
ports:
|
||||
- "8900:8899" # utiliser 8900 a la place
|
||||
```
|
||||
|
||||
## Mise a jour qui casse tout
|
||||
|
||||
```bash
|
||||
# Rollback: revenir au commit precedent
|
||||
cd dictia
|
||||
git log --oneline -5 # trouver le bon commit
|
||||
git checkout <commit-hash>
|
||||
|
||||
# Rebuild et redemarrer
|
||||
docker build -t innova-ai/dictia:latest .
|
||||
docker compose -f deployment/docker/docker-compose.<profil>.yml down
|
||||
docker compose -f deployment/docker/docker-compose.<profil>.yml up -d
|
||||
```
|
||||
|
||||
## Commande de diagnostic rapide
|
||||
|
||||
```bash
|
||||
# Tout verifier d'un coup
|
||||
bash deployment/tools/health-check.sh --json | python3 -m json.tool
|
||||
```
|
||||
148
deployment/docs/VPS-SETUP.md
Normal file
148
deployment/docs/VPS-SETUP.md
Normal file
@@ -0,0 +1,148 @@
|
||||
# Setup VPS from scratch — DictIA
|
||||
|
||||
Guide complet pour deployer DictIA sur un VPS Ubuntu.
|
||||
Teste sur OVH VPS avec Ubuntu 22.04/24.04.
|
||||
|
||||
## 1. Preparation du VPS
|
||||
|
||||
```bash
|
||||
# Mise a jour systeme
|
||||
sudo apt update && sudo apt upgrade -y
|
||||
|
||||
# Installer les essentiels
|
||||
sudo apt install -y curl git
|
||||
```
|
||||
|
||||
## 2. Docker
|
||||
|
||||
```bash
|
||||
# Installer Docker (methode officielle)
|
||||
curl -fsSL https://get.docker.com | sh
|
||||
|
||||
# Ajouter l'utilisateur au groupe docker
|
||||
sudo usermod -aG docker $USER
|
||||
|
||||
# Se reconnecter pour appliquer le groupe
|
||||
exit
|
||||
# (reconnecter via SSH)
|
||||
|
||||
# Verifier
|
||||
docker --version
|
||||
docker compose version
|
||||
```
|
||||
|
||||
## 3. Tailscale (recommande)
|
||||
|
||||
Tailscale fournit un VPN mesh pour acceder au VPS sans exposer de ports publics.
|
||||
|
||||
```bash
|
||||
# Installer Tailscale
|
||||
curl -fsSL https://tailscale.com/install.sh | sh
|
||||
|
||||
# Connecter au tailnet
|
||||
sudo tailscale up
|
||||
|
||||
# Verifier
|
||||
tailscale status
|
||||
```
|
||||
|
||||
## 4. DictIA
|
||||
|
||||
```bash
|
||||
# Cloner le repo
|
||||
cd ~
|
||||
git clone https://gitea.innova-ai.ca/Innova-AI/dictia.git
|
||||
cd dictia
|
||||
git checkout dictia-branding
|
||||
|
||||
# Lancer le setup
|
||||
bash deployment/setup.sh --profile cloud
|
||||
```
|
||||
|
||||
Le setup va:
|
||||
- Generer le `.env` avec vos identifiants
|
||||
- Creer les repertoires de donnees
|
||||
- Builder l'image Docker
|
||||
- Demarrer les containers
|
||||
|
||||
## 5. ASR Proxy (GCP GPU)
|
||||
|
||||
```bash
|
||||
# Installer le proxy
|
||||
bash deployment/asr-proxy/setup.sh
|
||||
|
||||
# Ajouter les credentials GCP
|
||||
# Copier votre fichier de credentials dans:
|
||||
cp ~/gcp-credentials.json deployment/asr-proxy/gcp-credentials.json
|
||||
|
||||
# Demarrer le service
|
||||
sudo systemctl start asr-proxy
|
||||
sudo systemctl status asr-proxy
|
||||
```
|
||||
|
||||
## 6. Securite
|
||||
|
||||
```bash
|
||||
# Docker daemon config (log rotation)
|
||||
sudo cp deployment/security/docker-daemon.json /etc/docker/daemon.json
|
||||
sudo systemctl restart docker
|
||||
|
||||
# Firewall iptables (bloque trafic non-Tailscale)
|
||||
sudo bash deployment/security/iptables-rules.sh
|
||||
|
||||
# Service systemd pour les regles au boot
|
||||
sudo cp deployment/security/docker-iptables.service /etc/systemd/system/
|
||||
sudo systemctl daemon-reload
|
||||
sudo systemctl enable docker-iptables
|
||||
```
|
||||
|
||||
## 7. Tailscale Serve (HTTPS)
|
||||
|
||||
```bash
|
||||
# Expose DictIA et le dashboard ASR via Tailscale HTTPS
|
||||
bash deployment/config/tailscale/setup-serve.sh
|
||||
|
||||
# Verifier
|
||||
tailscale serve status
|
||||
```
|
||||
|
||||
DictIA sera accessible a `https://votre-hostname.tailnet.ts.net/`.
|
||||
|
||||
## 8. Service systemd (auto-start)
|
||||
|
||||
```bash
|
||||
# Adapter le chemin dans le fichier si necessaire
|
||||
sudo cp deployment/config/systemd/dictia.service /etc/systemd/system/
|
||||
sudo systemctl daemon-reload
|
||||
sudo systemctl enable dictia
|
||||
```
|
||||
|
||||
## 9. Verification
|
||||
|
||||
```bash
|
||||
# Health check complet
|
||||
bash deployment/tools/health-check.sh
|
||||
|
||||
# Verifier les endpoints
|
||||
curl -s http://localhost:8899/health
|
||||
curl -s http://localhost:9090/health
|
||||
```
|
||||
|
||||
## 10. Premier backup
|
||||
|
||||
```bash
|
||||
bash deployment/tools/backup.sh
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Checklist post-installation
|
||||
|
||||
- [ ] DictIA repond sur :8899
|
||||
- [ ] ASR Proxy repond sur :9090
|
||||
- [ ] Tailscale Serve configure
|
||||
- [ ] iptables: seul Tailscale peut acceder
|
||||
- [ ] Docker: log rotation configuree
|
||||
- [ ] Service systemd enable (auto-start au boot)
|
||||
- [ ] Premier backup effectue
|
||||
- [ ] Identifiants admin testes
|
||||
Reference in New Issue
Block a user