# Local GPU serving via vLLM + agent-bench API.
# Requires: nvidia-container-toolkit
# See modal/serve_vllm.py for serverless alternative.
#
# Usage:
#   docker compose -f docker/docker-compose.vllm.yml up --build

services:
  vllm:
    image: vllm/vllm-openai:latest
    command:
      - --model=mistralai/Mistral-7B-Instruct-v0.3
      - --max-model-len=4096
      - --dtype=half
      - --gpu-memory-utilization=0.85
      - --host=0.0.0.0
      - --port=8000
    ports:
      - "8001:8000"
    deploy:
      resources:
        reservations:
          devices:
            - driver: nvidia
              count: 1
              capabilities: [gpu]
    volumes:
      - vllm-cache:/root/.cache/huggingface
    healthcheck:
      test: ["CMD", "curl", "-f", "http://localhost:8000/health"]
      interval: 30s
      timeout: 10s
      retries: 5
      start_period: 120s

  app:
    build:
      context: ..
      dockerfile: docker/Dockerfile
    environment:
      - MODAL_VLLM_URL=http://vllm:8000/v1
      - AGENT_BENCH_ENV=selfhosted_local
    depends_on:
      vllm:
        condition: service_healthy
    ports:
      - "8080:7860"

volumes:
  vllm-cache: