docker-compose.yml

version: "3.7"

volumes:
    pgdata:
    m2home:
    solr9data:
    fswebhome:

services:

    # Database server
    db:
        image: postgres:12.1
        volumes:
            - pgdata:/var/lib/postgresql/data
            - ./freesound-data/db_dev_dump:/freesound-data/db_dev_dump
        env_file:
            - environment
        ports:
            - "${FS_BIND_HOST:-127.0.0.1}:${LOCAL_PORT_PREFIX}5432:5432"
        environment:
            - POSTGRES_USER=freesound
            - POSTGRES_DB=freesound
            - FS_USER_ID

    # Web worker
    web:
        build:
            context: ./
            dockerfile: ./docker/Dockerfile.workers_web
        init: true
        command: python manage.py runserver 0.0.0.0:8000
        volumes:
            - .:/code
            - ./freesound-data/:/freesound-data
            - fswebhome:/home/fsweb
        ports:
            - "0.0.0.0:${LOCAL_PORT_PREFIX}8000:8000"  # web does not use FS_BIND_HOST because it should be always 0.0.0.0
            - "${FS_BIND_HOST:-127.0.0.1}:${LOCAL_PORT_PREFIX}3000:3000"  # needed for debugpy debugger (to connect with vscode)
        env_file:
            - environment
        environment:
            - FS_USER_ID
        depends_on:
            - db
            - rabbitmq
            - redis
            - search

    # Search server
    search:
        build:
            context: ./
            dockerfile: ./docker/Dockerfile.solr
        volumes:
            - ./utils/search/solr9/cores:/var/solr/data/configsets
            - solr9data:/var/solr
            - ./utils/search/solr9/docker-entrypoint:/docker-entrypoint-initdb.d
        ports:
            - "${FS_BIND_HOST:-127.0.0.1}:${LOCAL_PORT_PREFIX}8983:8983"

    # Redis (caches)
    redis:
        image: redis:alpine
        command: redis-server --port 6379

    # Celery broker (queue manager)
    rabbitmq:
        hostname: rabbit
        image: rabbitmq:3.9.1-management
        ports:
            - "${FS_BIND_HOST:-127.0.0.1}:${LOCAL_PORT_PREFIX}5673:5673"
        volumes:
            - ./docker/rabbitmq.conf:/etc/rabbitmq/rabbitmq.conf
            - ./freesound-data/rabbitmq:/var/lib/rabbitmq/mnesia/

    # Worker for async tasks and sound processing
    worker_celery:
        build:
            context: ./
            dockerfile: ./docker/Dockerfile.workers_web
        init: true
        command: celery -A freesound worker --concurrency=2 -l info -Q async_tasks_queue,sound_processing_queue,sound_analysis_old_queue,clustering_queue
        volumes:
            - .:/code
            - ./freesound-data/:/freesound-data
        env_file:
            - environment
        environment:
            - FS_USER_ID
        depends_on:
            - db
            - rabbitmq

    # Audio Commons extractor - needs image to be built from freesound-audio-analyzers repository
    worker_analyzer1:
        profiles: ["analyzers", "all"]
        image: ac-extractor_v3
        volumes:
            - ./freesound-data/:/freesound-data
        init: true
        command: celery -A main worker --concurrency=1 -l info -Q ac-extractor_v3
        depends_on:
            - rabbitmq

    # Essentia extractor - needs image to be built from freesound-audio-analyzers repository
    worker_analyzer2:
        profiles: ["analyzers", "all"]
        image: fs-essentia-extractor_legacy
        volumes:
            - ./freesound-data/:/freesound-data
        init: true
        command: celery -A main worker --concurrency=1 -l info -Q fs-essentia-extractor_legacy
        depends_on:
            - rabbitmq

    # Audioset-YAMNet extractor - needs image to be built from freesound-audio-analyzers repository
    # Note this worker must be run with --pool=threads in order for tensorflow predictions to work inside celery
    worker_analyzer3:
        profiles: ["analyzers", "all"]
        image: audioset-yamnet_v1
        volumes:
            - ./freesound-data/:/freesound-data
        init: true
        command: celery -A main worker --pool=threads --concurrency=1 -l info -Q audioset-yamnet_v1
        depends_on:
            - rabbitmq

    # BirdNET analyzer - needs image to be built from freesound-audio-analyzers repository
    worker_analyzer4:
        profiles: ["analyzers", "all"]
        image: birdnet_v1
        volumes:
            - ./freesound-data/:/freesound-data
        init: true
        command: celery -A main worker --concurrency=1 -l info -Q birdnet_v1
        depends_on:
            - rabbitmq

    # FSD-Sinet analyzer - needs image to be built from freesound-audio-analyzers repository
    # Note this worker must be run with --pool=threads in order for tensorflow predictions to work inside celery
    worker_analyzer5:
        profiles: ["analyzers", "all"]
        image: fsd-sinet_v1
        volumes:
            - ./freesound-data/:/freesound-data
        init: true
        command: celery -A main worker --pool=threads --concurrency=1 -l info -Q fsd-sinet_v1
        depends_on:
            - rabbitmq

    # Similarity http server
    similarity:
        profiles: ["all"]
        build:
            context: ./similarity
            dockerfile: ../docker/Dockerfile.similarity
        init: true
        command: python similarity_server.py
        volumes:
            - ./similarity:/code
            - ./freesound-data/similarity_index:/freesound-data/similarity_index
            - ./freesound-data/analysis:/freesound-data/analysis
        ports:
            - "${FS_BIND_HOST:-127.0.0.1}:${LOCAL_PORT_PREFIX}8008:8008"
        environment:
            - FS_USER_ID

    # Tag recommendation http server
    tagrecommendation:
        profiles: ["all"]
        build:
            context: ./tagrecommendation
            dockerfile: ../docker/Dockerfile.tagrecommendation
        init: true
        command: python tagrecommendation_server.py
        volumes:
            - ./tagrecommendation:/code
            - ./freesound-data/tag_recommendation_models:/freesound-data/tag_recommendation_models
        ports:
            - "${FS_BIND_HOST:-127.0.0.1}:${LOCAL_PORT_PREFIX}8010:8010"
        environment:
            - FS_USER_ID