docker-compose.yml

version: '3'
#Make sure you have the nvida drivers installed on the host machine
#Download the models to use in the container in the 'command' section below - Exmples are provided
#Replace any special characters in the file names with the '_' character in the `-O` like `mdjrny-v4.ckpt` to `mdjrny_v4.ckpt`
#Separate models with `&& \`
#Keep your GPU memory in mind when adding/removing models.
#The number and size of models you add should be less than your available video RAM

services:
  gen-net:
    image: gennet/gen-net:latest
    container_name: gen-net
    environment:
      - WORKER_ID=<API_KEY>
    restart: unless-stopped
    volumes:
      - models:/stable-diffusion-webui/models/Stable-diffusion/
    ports: #Port per model - Starting at 12000
      - '12000:12000'
      - '12001:12001'
      - '12002:12002'
      - '12003:12003'
      - '12004:12004'
      - '12005:12005'
      - '12006:12006'
      - '12007:12007'
      - '12008:12008'
      - '12009:12009'
    command: bash -c "\
      test -f /stable-diffusion-webui/models/Stable-diffusion/<model1_name>.ckpt || \
      wget -N -O /stable-diffusion-webui/models/Stable-diffusion/<model1_name>.ckpt https://<url_to_model1>.ckpt && \
      test -f /stable-diffusion-webui/models/Stable-diffusion/<model2_name>.ckpt || \
      wget -N -O /stable-diffusion-webui/models/Stable-diffusion/<model2_name>.ckpt https://<url_to_model2>.ckpt && \
      cd /artgen_backend/ && git reset --hard HEAD && git checkout main && git pull && \
      /app/venv/bin/python /artgen_backend/api/worker_manager.py"
    deploy:
      resources:
        reservations:
          devices:
            - driver: nvidia
              count: 1 #all
              capabilities: [gpu]
volumes:
  models: