rss/docker-compose.yml

services:
  db:
    image: postgres:18
    container_name: rss_db
    environment:
      POSTGRES_DB: ${DB_NAME}
      POSTGRES_USER: ${DB_USER}
      POSTGRES_PASSWORD: ${DB_PASS}
      POSTGRES_INITDB_ARGS: "--encoding=UTF8 --locale=C.UTF-8"
      LANG: C.UTF-8
      LC_ALL: C.UTF-8
      TZ: Europe/Madrid
      PGDATA: /var/lib/postgresql/data/18/main
    command: ["postgres", "-c", "max_connections=400"]
    volumes:
      # Datos de Postgres dentro del proyecto
      - ./pgdata:/var/lib/postgresql/data
      # Scripts de inicialización
      - ./init-db:/docker-entrypoint-initdb.d:ro
    restart: always
    healthcheck:
      test: ["CMD-SHELL", "pg_isready -h 127.0.0.1 -p 5432 -U $$POSTGRES_USER -d $$POSTGRES_DB || exit 1"]
      interval: 5s
      timeout: 5s
      retries: 30
      start_period: 20s

  web:
    build:
      context: .
      args:
        TORCH_CUDA: cu121
    container_name: rss_web
    command: bash -lc "gunicorn --bind 0.0.0.0:8000 --workers 3 --timeout 120 app:app"
    ports:
      - "8001:8000"
    environment:
      - DB_HOST=db
      - DB_PORT=5432
      - DB_NAME=${DB_NAME}
      - DB_USER=${DB_USER}
      - DB_PASS=${DB_PASS}
      - SECRET_KEY=${SECRET_KEY}
      - WEB_TRANSLATED_DEFAULT=1
      - DEFAULT_LANG=es
      - TRANSLATION_PREFERRED_LANGS=es
    depends_on:
      db:
        condition: service_healthy
    restart: always

  scheduler:
    build:
      context: .
      args:
        TORCH_CUDA: cu121
    container_name: rss_scheduler
    command: bash -lc "python scheduler.py"
    environment:
      - DB_HOST=db
      - DB_PORT=5432
      - DB_NAME=${DB_NAME}
      - DB_USER=${DB_USER}
      - DB_PASS=${DB_PASS}
      - SECRET_KEY=${SECRET_KEY}
      - RSS_MAX_WORKERS=16
    depends_on:
      db:
        condition: service_healthy
    restart: always

  # --- Worker de traducción en GPU: encola + traduce ---
  translator_gpu:
    build:
      context: .
      args:
        TORCH_CUDA: cu121
    container_name: rss_translator_gpu
    command: bash -lc "python translation_worker.py"
    environment:
      - DB_HOST=db
      - DB_PORT=5432
      - DB_NAME=${DB_NAME}
      - DB_USER=${DB_USER}
      - DB_PASS=${DB_PASS}
      - TARGET_LANGS=es
      - TRANSLATOR_BATCH=16
      - ENQUEUE=200            # ESTE encola traducciones nuevas
      - TRANSLATOR_SLEEP_IDLE=5
      - MAX_SRC_TOKENS=680
      - MAX_NEW_TOKENS=400
      - NUM_BEAMS_TITLE=1
      - NUM_BEAMS_BODY=1
      - UNIVERSAL_MODEL=facebook/nllb-200-distilled-600M
      - CHUNK_BY_SENTENCES=True
      - CHUNK_MAX_TOKENS=400
      - CHUNK_OVERLAP_SENTS=1
      - CLEAN_ARTICLE=1
      - DEVICE=cuda            # GPU
      - PYTHONUNBUFFERED=1
      - HF_HOME=/root/.cache/huggingface
      - TOKENIZERS_PARALLELISM=false
      - PYTORCH_CUDA_ALLOC_CONF=max_split_size_mb:64,garbage_collection_threshold:0.9
      - NVIDIA_VISIBLE_DEVICES=all
      - NVIDIA_DRIVER_CAPABILITIES=compute,utility
    volumes:
      # Cache de modelos HF dentro del proyecto
      - ./hf_cache:/root/.cache/huggingface
    depends_on:
      db:
        condition: service_healthy
    restart: always
    gpus: all

  # --- Worker de traducción en CPU: SOLO procesa pendientes ---
  translator_cpu:
    build:
      context: .
      args:
        TORCH_CUDA: cu121
    container_name: rss_translator_cpu
    command: bash -lc "python translation_worker.py"
    environment:
      - DB_HOST=db
      - DB_PORT=5432
      - DB_NAME=${DB_NAME}
      - DB_USER=${DB_USER}
      - DB_PASS=${DB_PASS}
      - TARGET_LANGS=es
      - TRANSLATOR_BATCH=8      # batch más pequeño para CPU
      - ENQUEUE=0               # NO encola nuevas traducciones
      - TRANSLATOR_SLEEP_IDLE=5
      - MAX_SRC_TOKENS=680
      - MAX_NEW_TOKENS=400
      - NUM_BEAMS_TITLE=1
      - NUM_BEAMS_BODY=1
      - UNIVERSAL_MODEL=facebook/nllb-200-distilled-600M
      - CHUNK_BY_SENTENCES=True
      - CHUNK_MAX_TOKENS=400
      - CHUNK_OVERLAP_SENTS=1
      - CLEAN_ARTICLE=1
      - DEVICE=cpu              # Fuerza CPU
      - PYTHONUNBUFFERED=1
      - HF_HOME=/root/.cache/huggingface
      - TOKENIZERS_PARALLELISM=false
    volumes:
      - ./hf_cache:/root/.cache/huggingface
    depends_on:
      db:
        condition: service_healthy
    restart: always

  ner:
    build:
      context: .
      args:
        TORCH_CUDA: cu121
    container_name: rss_ner
    command: bash -lc "python ner_worker.py"
    environment:
      - DB_HOST=db
      - DB_PORT=5432
      - DB_NAME=${DB_NAME}
      - DB_USER=${DB_USER}
      - DB_PASS=${DB_PASS}
      - NER_LANG=es
      - NER_BATCH=64
    depends_on:
      db:
        condition: service_healthy
    restart: always

  embeddings:
    build:
      context: .
      args:
        TORCH_CUDA: cu121
    container_name: rss_embeddings
    command: bash -lc "python embeddings_worker.py"
    environment:
      - DB_HOST=db
      - DB_PORT=5432
      - DB_NAME=${DB_NAME}
      - DB_USER=${DB_USER}
      - DB_PASS=${DB_PASS}
      - EMB_MODEL=sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2
      - EMB_BATCH=256
      - EMB_SLEEP_IDLE=5
      - EMB_LANGS=es
      - EMB_LIMIT=5000
      - DEVICE=cuda
      - PYTHONUNBUFFERED=1
      - HF_HOME=/root/.cache/huggingface
      - TOKENIZERS_PARALLELISM=false
    volumes:
      # Reutiliza el mismo cache HF
      - ./hf_cache:/root/.cache/huggingface
    depends_on:
      db:
        condition: service_healthy
    restart: always
    gpus: all

  related:
    build:
      context: .
      args:
        TORCH_CUDA: cu121
    container_name: rss_related
    command: bash -lc "python related_worker.py"
    environment:
      - DB_HOST=db
      - DB_PORT=5432
      - DB_NAME=${DB_NAME}
      - DB_USER=${DB_USER}
      - DB_PASS=${DB_PASS}
      - RELATED_TOPK=10
      - RELATED_BATCH_IDS=200
      - RELATED_BATCH_SIM=2000
      - RELATED_SLEEP=10
      - RELATED_MIN_SCORE=0.0
      - RELATED_WINDOW_H=0
    depends_on:
      db:
        condition: service_healthy
    restart: always

  cluster:
    build:
      context: .
      args:
        TORCH_CUDA: cu121
    container_name: rss_cluster
    command: bash -lc "python cluster_worker.py"
    environment:
      - DB_HOST=db
      - DB_PORT=5432
      - DB_NAME=${DB_NAME}
      - DB_USER=${DB_USER}
      - DB_PASS=${DB_PASS}
    depends_on:
      db:
        condition: service_healthy
    restart: always

networks:
  default:
    name: rss_default