70 lines
1.6 KiB
YAML
70 lines
1.6 KiB
YAML
# DictIA — Local GPU deployment (WhisperX on NVIDIA GPU + DictIA)
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#
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# Usage:
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# docker compose -f deployment/docker/docker-compose.local-gpu.yml up -d
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#
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# Prerequisites:
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# - NVIDIA GPU with CUDA support
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# - nvidia-container-toolkit installed
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# - Docker configured with nvidia runtime
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services:
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whisperx-asr:
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image: ghcr.io/jim60105/whisperx-asr:latest-cuda
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container_name: whisperx-asr
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restart: unless-stopped
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ports:
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- "9000:9000"
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environment:
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- ASR_MODEL=${ASR_MODEL:-large-v3}
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- ASR_ENGINE=whisperx
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- DEVICE=cuda
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- COMPUTE_TYPE=float16
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- HF_TOKEN=${HF_TOKEN:-}
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volumes:
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- whisperx-cache:/root/.cache
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deploy:
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resources:
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reservations:
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devices:
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- driver: nvidia
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count: 1
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capabilities: [gpu]
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networks:
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- dictia-network
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dictia:
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build:
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context: ../..
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dockerfile: Dockerfile
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image: innova-ai/dictia:latest
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container_name: dictia
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restart: unless-stopped
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ports:
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- "8899:8899"
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env_file:
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- ../../.env
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environment:
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- LOG_LEVEL=${LOG_LEVEL:-ERROR}
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- ASR_BASE_URL=http://whisperx-asr:9000
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volumes:
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- ../../data/uploads:/data/uploads
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- ../../data/instance:/data/instance
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depends_on:
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- whisperx-asr
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healthcheck:
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test: ["CMD", "python3", "-c", "import urllib.request; urllib.request.urlopen('http://localhost:8899/health')"]
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interval: 30s
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timeout: 10s
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retries: 3
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start_period: 30s
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networks:
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- dictia-network
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volumes:
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whisperx-cache:
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networks:
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dictia-network:
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driver: bridge
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