probleme dependances
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@ -1,9 +1,10 @@
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version: '3.8'
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version: '3.8'
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services:
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services:
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# --- LE PORTIER (Point d'entrée pour tes 20 étudiants) ---
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# --- LE PORTIER ---
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gateway:
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gateway:
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image: nginx:latest
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image: nginx:latest
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container_name: studio-gateway-1
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ports:
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ports:
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- "80:80"
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- "80:80"
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volumes:
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volumes:
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@ -12,12 +13,13 @@ services:
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- studio-net
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- studio-net
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depends_on:
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depends_on:
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- open-webui
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- open-webui
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- audio-api # Ajouté ici : Nginx attend que l'audio soit prêt
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restart: always
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# --- L'INTERFACE (Open WebUI) ---
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# --- L'INTERFACE ---
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open-webui:
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open-webui:
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image: ghcr.io/open-webui/open-webui:main
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image: ghcr.io/open-webui/open-webui:main
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container_name: open-webui
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container_name: open-webui
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# On ne publie plus le port 3000 vers l'extérieur, Nginx s'en charge en interne
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environment:
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environment:
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- OLLAMA_BASE_URL=http://ollama:11434
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- OLLAMA_BASE_URL=http://ollama:11434
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- WEBUI_SECRET_KEY=${WEBUI_SECRET_KEY:-supersecretkey}
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- WEBUI_SECRET_KEY=${WEBUI_SECRET_KEY:-supersecretkey}
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@ -27,7 +29,7 @@ services:
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- studio-net
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- studio-net
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restart: always
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restart: always
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# --- LE CERVEAU (Ollama) ---
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# --- LE CERVEAU ---
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ollama:
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ollama:
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image: ollama/ollama:latest
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image: ollama/ollama:latest
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container_name: ollama
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container_name: ollama
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@ -42,29 +44,33 @@ services:
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- ollama_data:/root/.ollama
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- ollama_data:/root/.ollama
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networks:
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networks:
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- studio-net
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- studio-net
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restart: always
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# --- LE SERVICE AUDIO (Ton API) ---
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# --- LE SERVICE AUDIO ---
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audio-api:
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audio-api:
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build:
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image: nvcr.io/nvidia/pytorch:23.10-py3 # On utilise une image robuste
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context: ./services/audio-api
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container_name: audio-api
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container_name: audio-api
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# On laisse le port 7860 ouvert au cas où tu voudrais tester en direct
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working_dir: /app
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# On monte le dossier local pour que le script server.py soit trouvé
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volumes:
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- ./services/audio-api:/app
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- ./models:/app/models
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- ./outputs:/app/outputs
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# L'astuce : On installe Gradio AVANT de lancer le script
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command: >
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sh -c "pip install --no-cache-dir gradio faster-whisper && python3 server.py"
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ports:
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ports:
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- "7860:7860"
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- "7860:7860"
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deploy:
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deploy:
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resources:
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resources:
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limits:
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memory: 32G # 64 Go de VRAM permet d'être large sur la RAM système aussi
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reservations:
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reservations:
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devices:
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devices:
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- driver: nvidia
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- driver: nvidia
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count: all
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count: all
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capabilities: [gpu]
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capabilities: [gpu]
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volumes:
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- ./models:/app/models
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- ./outputs:/app/outputs
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networks:
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networks:
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- studio-net
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- studio-net
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restart: always
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networks:
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networks:
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studio-net:
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studio-net:
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