arcisvlm / deploy /docker-compose.yml
Hardik Sanghvi
feat: integrate Gemma 4 E2B backbone for production-quality VLM inference
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version: "3.8"
services:
api:
build:
context: ..
dockerfile: deploy/Dockerfile.api
volumes:
- checkpoints:/app/checkpoints
environment:
- ARCISVLM_CONFIG=configs/scale_1.3b.yaml
- ARCISVLM_CHECKPOINT=${ARCISVLM_CHECKPOINT:-checkpoints/v3_stage1_final.pt}
- ARCISVLM_DEVICE=cuda
- HF_TOKEN=${HF_TOKEN:-}
deploy:
resources:
reservations:
devices:
- driver: nvidia
count: 1
capabilities: [gpu]
restart: unless-stopped
healthcheck:
test: ["CMD", "curl", "-f", "http://localhost:8000/health"]
interval: 30s
timeout: 10s
retries: 3
dashboard:
build:
context: ..
dockerfile: deploy/Dockerfile.dashboard
environment:
- NEXT_PUBLIC_API_URL=
- NEXT_PUBLIC_WS_URL=
depends_on:
- api
restart: unless-stopped
nginx:
image: nginx:alpine
ports:
- "80:80"
volumes:
- ./nginx.conf:/etc/nginx/conf.d/default.conf:ro
depends_on:
- api
- dashboard
restart: unless-stopped
volumes:
checkpoints: