llm-eval/docker-compose.local.yaml at main · codecentric/llm-eval · GitHub

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# Application services to run in combination with docker-compose.yaml
# to start the whole LLMEval system locally without any other dependency
services:
  backend:
    image: llm-eval-backend:compose
    build: # TODO use registry image
      context: backend
      dockerfile: Dockerfile
      args:
        REMOTE_UID: ${REMOTE_UID:-1000}
        REMOTE_GID: ${REMOTE_GID:-1000}
    ports:
      - "8070:8070"
    env_file:
      - .env.services
      - .env
    depends_on:
      - eval-db
      - keycloak
      - rabbit-mq
    environment:
      RUN_IN_CONTAINER: True
      DEEPEVAL_UPDATE_WARNING_OPT_OUT: YES
      FILE_UPLOAD_TEMP_LOCATION: /data/tmp
    networks:
      - keycloak
      - backend
    volumes:
      - ./data/uploaded_files:/data/tmp
    entrypoint: ["/venv/bin/uvicorn", "llm_eval.main:app", "--host", "0.0.0.0", "--port", "8070"]

  backend-worker:
    image: llm-eval-backend:compose
    env_file:
      - .env.services
      - .env
    depends_on:
      - eval-db
      - rabbit-mq
    environment:
      RUN_IN_CONTAINER: True
      DEEPEVAL_UPDATE_WARNING_OPT_OUT: YES
      FILE_UPLOAD_TEMP_LOCATION: /data/tmp
    networks:
      - backend
    volumes:
      - ./data/uploaded_files:/data/tmp
    entrypoint: ["/venv/bin/celery", "-A", "llm_eval.tasks", "worker", "--loglevel=INFO", "--concurrency=1"]

  frontend:
    image: llm-eval-frontend:compose # TODO use registry image
    build:
      context: frontend
    env_file:
      - .env.services
      - .env
    environment:
      AUTH_TRUST_HOST: true
    depends_on:
      - backend
    network_mode: "host"