docker-compose.yml

services:
  mlflow:
    image: ghcr.io/mlflow/mlflow:v2.19.0
    container_name: mlflow-server
    ports:
      - "5000:5000"
    volumes:
      - ./logdir/mlflow/:/mlflow
    command: ["mlflow", "server" ,"--host", "0.0.0.0", "--port", "5000", "--backend-store-uri",
               "sqlite:////mlflow/mlflow.db", "--default-artifact-root", "/mlflow/mlflow-artifacts"]

  model-training:
    build:
      context: ./taxfix-training
      dockerfile: Dockerfile
    container_name: model-training
    environment:
      - MLFLOW_TRACKING_URI=http://mlflow:5000
      - GIT_PYTHON_REFRESH=quiet
    volumes:
      - ./logdir/mlflow/:/mlflow
      - ./logdir/validation-data:/validation-data
    depends_on:
      - mlflow
    command: ["python", "-m", "taxfix_training.main"]

  model-inference:
    build:
      context: ./taxfix-inference
      dockerfile: Dockerfile
    container_name: taxfix-inference
    ports:
      - "8000:8000"
    environment:
      - MLFLOW_TRACKING_URI=http://mlflow:5000
    depends_on:
      model-training:
        condition: service_completed_successfully
    volumes:
      - ./logdir/mlflow/:/mlflow
    command: ["/app/.venv/bin/uvicorn", "taxfix_inference.main:app", "--host", "0.0.0.0", "--port", "8000"]