docker-compose.yml

version: "3.9"

services:
  fastapi:
    container_name: api
    build:
      dockerfile: app/Dockerfile
    env_file:
      - .env.dev
    ports:
      - "8989:8989"
#    user: root
    volumes:
      - ./app:/app
      - /var/run/docker.sock:/var/run/docker.sock
      - ./vector/chroma:/vector/chroma/
    command: python main.py --host 0.0.0.0 --port 8989 --env dev --reload

  elasticsearch:
    container_name: vector_db
#    image: elasticsearch:7.10.1
    image: elasticsearch:8.8.0
    env_file:
      - .env.dev
    ports:
      - ${ES_PORT1}:${ES_PORT1}
      - ${ES_PORT2}:${ES_PORT2}
    environment:
      - node.name=es
      - discovery.type=single-node
      - discovery.seed_hosts=elasticsearch
      - ELASTIC_PASSWORD=movie
      - bootstrap.memory_lock=true
      - xpack.security.enabled=false
      - xpack.security.http.ssl.enabled=false
      - xpack.security.http.ssl.verification_mode=certificate
      - xpack.security.transport.ssl.enabled=false
      - xpack.security.transport.ssl.verification_mode=certificate
      - xpack.license.self_generated.type=basic
    healthcheck:
      test:
        [
          "CMD-SHELL",
          "curl -s --cacert config/certs/ca/ca.crt http://localhost:9200 | grep -q 'missing authentication credentials'",
        ]
      interval: 10s
      timeout: 10s
      retries: 120
    volumes:
      #TODO 볼륨 권한이 root로 설정되어 chown으로 해결하였으나 자동으로 권한을 변경하도록 수정 필요
      - ./es-data:/usr/share/elasticsearch/data
      - ./certs:/usr/share/elasticsearch/config/certs

#  mlflow-deployment:
#    container_name: mlflow-deployment
#    build:
#      dockerfile: ops/deployment/Dockerfile
#    env_file:
#      - .env.dev
#    ports:
#      - "7001:7001"
##    networks:
##      - ops
##    environment:
##      OPENAI_API_KEY: ${OPENAI_API_KEY}
#    command: mlflow deployments start-server --config-path /mlflow_deployment/config.yaml --host 0.0.0.0 --port 7001

  mlflow-tracking:
    container_name: mlflow-tracking
    build:
      dockerfile: ops/tracking/Dockerfile
    env_file:
      - .env.dev
    ports:
      - "5001:5001"
#    networks:
#      - ops
#    links:
#      - ops-deployment
    volumes:
      - ./mlruns:/mlruns
#    environment:
#      MLFLOW_DEPLOYMENTS_TARGET: ${MLFLOW_DEPLOYMENTS_TARGET}
    command: mlflow server --host 0.0.0.0 --port 5001
#networks:
#  ops: