Initial release: DictIA v0.8.14-alpha (fork de Speakr, AGPL-3.0)

deployment/docs/LOCAL-SETUP.md

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+# Setup Local — DictIA
+
+Guide pour deployer DictIA localement avec GPU NVIDIA ou CPU.
+
+## Profil local-gpu
+
+### Prerequis
+
+- NVIDIA GPU avec support CUDA
+- [nvidia-container-toolkit](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/install-guide.html)
+- Docker + Docker Compose V2
+- 8GB+ RAM (16GB recommande)
+- Token HuggingFace (pour la diarisation)
+
+### Installation nvidia-container-toolkit
+
+```bash
+# Ubuntu/Debian
+curl -fsSL https://nvidia.github.io/libnvidia-container/gpgkey | \
+    sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg
+curl -s -L https://nvidia.github.io/libnvidia-container/stable/deb/nvidia-container-toolkit.list | \
+    sed 's#deb https://#deb [signed-by=/usr/share/keyrings/nvidia-container-toolkit-keyring.gpg] https://#g' | \
+    sudo tee /etc/apt/sources.list.d/nvidia-container-toolkit.list
+sudo apt-get update
+sudo apt-get install -y nvidia-container-toolkit
+sudo nvidia-ctk runtime configure --runtime=docker
+sudo systemctl restart docker
+
+# Verifier
+docker run --rm --gpus all nvidia/cuda:12.0-base nvidia-smi
+```
+
+### Setup DictIA
+
+```bash
+cd dictia
+bash deployment/setup.sh --profile local-gpu
+```
+
+Le setup va verifier:
+- nvidia-container-toolkit installe
+- GPU accessible depuis Docker
+- Assez de RAM disponible
+
+### Configuration du modele
+
+Par defaut, WhisperX utilise `large-v3`. Pour changer:
+
+```bash
+# Editer .env
+ASR_MODEL=large-v3      # Meilleure qualite
+# ASR_MODEL=medium       # Plus rapide, qualite correcte
+# ASR_MODEL=small        # Tres rapide, qualite reduite
+```
+
+---
+
+## Profil local-cpu
+
+### Prerequis
+
+- Docker + Docker Compose V2
+- 18GB+ RAM (WhisperX CPU est gourmand)
+- Patience (transcription ~10x temps reel)
+
+### Setup
+
+```bash
+cd dictia
+bash deployment/setup.sh --profile local-cpu
+```
+
+### Limitations
+
+- Transcription lente: 1h d'audio prend ~10h
+- Utilise float32 (pas de GPU acceleration)
+- Limite memoire a 18GB par defaut
+- Recommande pour: tests, petits fichiers, demos
+
+Pour reduire l'utilisation memoire, utiliser un modele plus petit:
+
+```bash
+# Editer .env
+ASR_MODEL=small    # ou medium, base, tiny
+```
+
+---
+
+## Verification
+
+```bash
+# Health check
+bash deployment/tools/health-check.sh
+
+# Test rapide: ouvrir le navigateur
+open http://localhost:8899
+
+# Verifier WhisperX
+curl http://localhost:9000/health
+```
+
+## Gestion des containers
+
+```bash
+COMPOSE_FILE=deployment/docker/docker-compose.local-gpu.yml  # ou local-cpu
+
+# Logs
+docker compose -f $COMPOSE_FILE logs -f
+
+# Redemarrer
+docker compose -f $COMPOSE_FILE restart
+
+# Arreter
+docker compose -f $COMPOSE_FILE down
+
+# Voir l'utilisation GPU
+nvidia-smi  # (profil GPU seulement)
+```