LLMeQueue/docker-compose.nvidia.yml at main · gszecsenyi/LLMeQueue · GitHub

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# For NVIDIA GPU: Run everything in containers with GPU acceleration
#
# Then run (3 workers recommended for parallel processing):
#   docker compose -f docker-compose.nvidia.yml up --scale worker=3 --build
#
# Or for single worker:
#   docker compose -f docker-compose.nvidia.yml up --build

services:
  server:
    build: ./server
    ports:
      - "${SERVER_PORT:-8000}:8000"
    volumes:
      - ./data:/app/data
    environment:
      - AUTH_TOKEN=${AUTH_TOKEN:-your-secret-token}
      - DB_PATH=${DB_PATH:-data/llmequeue.db}
      - EMBEDDING_MODEL=${EMBEDDING_MODEL:-nomic-embed-text}
      - CHAT_MODEL=${CHAT_MODEL:-llama3.2}
    healthcheck:
      test: ["CMD", "curl", "-f", "http://localhost:8000/health"]
      interval: 10s
      timeout: 5s
      retries: 3

  worker:
    build: ./worker
    environment:
      - SERVER_URL=http://server:8000
      - OLLAMA_URL=http://ollama:11434
      - AUTH_TOKEN=${AUTH_TOKEN:-your-secret-token}
      - EMBEDDING_MODEL=${EMBEDDING_MODEL:-nomic-embed-text}
      - CHAT_MODEL=${CHAT_MODEL:-llama3.2}
      - POLL_INTERVAL=${POLL_INTERVAL:-2}
    depends_on:
      server:
        condition: service_healthy
      ollama:
        condition: service_started

  ollama:
    image: ollama/ollama
    volumes:
      - ollama_data:/root/.ollama
    deploy:
      resources:
        reservations:
          devices:
            - driver: nvidia
              count: all
              capabilities: [gpu]

volumes:
  ollama_data: