docker-compose.yaml

services:
  mlflow:
    build:
        context: .
        dockerfile: Dockerfile
    image: cogment_verse:local
    ports:
      - ${MLFLOW_PORT:-3000}:${MLFLOW_PORT:-3000}
    volumes:
      - type: bind
        source: .cogment_verse
        target: /cogment_verse_work_dir
        bind:
          create_host_path: true
    command: python -m simple_mlflow --port=${MLFLOW_PORT:-3000}

  cogment_verse:
    build:
        context: .
        dockerfile: Dockerfile
    image: cogment_verse:local
    ports:
      - ${WEB_PORT:-8080}:${WEB_PORT:-8080}
      - ${ORCHESTRATOR_WEB_PORT:-9000}:${ORCHESTRATOR_WEB_PORT:-9000}
    volumes:
      - type: bind
        source: .cogment_verse
        target: /cogment_verse_work_dir
        bind:
          create_host_path: true
    depends_on:
      - mlflow
    entrypoint: >
      python -m main
      run.experiment_tracker.mlflow_tracking_uri=http://mlflow:${MLFLOW_PORT:-3000}
      services.web.port=${WEB_PORT:-8080}
      services.orchestrator.web_port=${ORCHESTRATOR_WEB_PORT:-9000}
      services.orchestrator.web_endpoint=http://${WEB_HOST:-localhost}:${ORCHESTRATOR_WEB_PORT:-9000}