ops/compose/compose_dev.yaml

# Podman / Docker compose for the full mindxtrain demo stack.
# Wires the operator FastAPI app -> vLLM-ROCm on the MI300X droplet.

services:
  vllm:
    image: docker.io/rocm/vllm-dev:rocm7.2.1
    container_name: mindxtrain-vllm
    ipc: host
    devices:
      - /dev/kfd
      - /dev/dri
    group_add:
      - video
    cap_add:
      - SYS_PTRACE
    security_opt:
      - seccomp=unconfined
    environment:
      PYTORCH_ROCM_ARCH: gfx942
      HSA_NO_SCRATCH_RECLAIM: "1"
      HIP_FORCE_DEV_KERNARG: "1"
      GPU_MAX_HW_QUEUES: "1"
    volumes:
      - ../../runs:/workspace/runs:ro
    command: >
      vllm serve /workspace/runs/latest/quantized
      --tensor-parallel-size 1
      --max-model-len 8192
      --port 8000
    ports:
      - "8000:8000"

  operator:
    build:
      context: ../..
      dockerfile: ops/containerfiles/containerfile_train
    container_name: mindxtrain-operator
    depends_on:
      - vllm
    environment:
      MINDXTRAIN_BACKEND: vllm
      MINDXTRAIN_VLLM_BASE_URL: http://vllm:8000/v1
      MINDXTRAIN_PERSONA_PATH: /home/hacker/mindX/personas/codephreak.json
    command: >
      uvicorn mindxtrain.operator.app:app --host 0.0.0.0 --port 8080
    ports:
      - "8080:8080"