# ============================================================================= # DictIA 8 — Docker Compose # GPU : RTX 5060 (8 Go VRAM) # ============================================================================= # # Services : # - dictia : Application principale DictIA # - whisperx-asr : Service de transcription WhisperX Large-v3 # # Démarrage : # 1. cp config/env.dictia8.example .env # 2. Remplir TEXT_MODEL_API_KEY dans .env # 3. docker compose -f config/docker-compose.dictia8.yml up -d # ============================================================================= services: # --------------------------------------------------------------------------- # Application DictIA # --------------------------------------------------------------------------- dictia: image: dictia:latest container_name: dictia restart: unless-stopped ports: - "8899:8899" env_file: - ../.env environment: - LOG_LEVEL=ERROR volumes: - ../uploads:/data/uploads - ../instance:/data/instance # Décommenter pour l'export automatique : # - ../exports:/data/exports # Décommenter pour le traitement automatique : # - ../auto-process:/data/auto-process depends_on: - whisperx-asr networks: - dictia-net # --------------------------------------------------------------------------- # WhisperX ASR — Transcription locale (WhisperX Large-v3) # RTX 5060 : BATCH_SIZE=16, COMPUTE_TYPE=float16 # --------------------------------------------------------------------------- whisperx-asr: image: murtazanasir/whisperx-asr-service:latest container_name: whisperx-asr restart: unless-stopped environment: - HF_TOKEN=${HF_TOKEN} - DEVICE=cuda - COMPUTE_TYPE=float16 - BATCH_SIZE=16 - DEFAULT_MODEL=large-v3 volumes: - whisperx-models:/root/.cache deploy: resources: reservations: devices: - driver: nvidia count: 1 capabilities: [gpu] networks: - dictia-net networks: dictia-net: driver: bridge volumes: whisperx-models: driver: local