#!/usr/bin/env bash
# NVIDIA GPU + CUDA 환경 점검
set -euo pipefail

ROOT="$(cd "$(dirname "${BASH_SOURCE[0]}")/.." && pwd)"
cd "$ROOT"

echo "=== TTS 환경 점검 ==="
echo "프로젝트: $ROOT"
echo

echo "--- OS / CPU ---"
uname -a
echo

echo "--- Python ---"
if command -v python3 &>/dev/null; then
  python3 --version
  which python3
else
  echo "python3: 없음"
fi
echo

echo "--- NVIDIA GPU ---"
if command -v nvidia-smi &>/dev/null; then
  nvidia-smi
  echo
  nvidia-smi --query-gpu=name,memory.total,driver_version --format=csv
else
  echo "nvidia-smi: 사용 불가 (NVIDIA GPU 서버에서 실행하세요)"
fi
echo

echo "--- CUDA (nvcc) ---"
if command -v nvcc &>/dev/null; then
  nvcc --version | head -4
else
  echo "nvcc: 없음 (PyTorch CUDA 빌드로도 동작 가능)"
fi
echo

echo "--- PyTorch (API venv) ---"
API_VENV="$ROOT/.venvs/api"
if [[ -x "$API_VENV/bin/python" ]]; then
  "$API_VENV/bin/python" -c "
import sys
try:
    import torch
    print('torch:', torch.__version__)
    print('cuda available:', torch.cuda.is_available())
    if torch.cuda.is_available():
        print('device:', torch.cuda.get_device_name(0))
except ImportError:
    print('torch: 미설치 (API만 사용 시 정상)')
" 2>/dev/null || true
else
  echo "API venv 없음 → ./scripts/setup_api.sh 실행"
fi
echo

echo "--- 모델 venv ---"
for name in f5tts cosyvoice; do
  V="$ROOT/.venvs/$name"
  if [[ -x "$V/bin/python" ]]; then
    echo "[$name] OK: $V"
  else
    echo "[$name] 없음 → setup_${name}.sh (f5tts는 setup_f5tts.sh)"
  fi
done
echo

echo "--- 디렉터리 ---"
for d in samples outputs models config backend web; do
  [[ -d "$ROOT/$d" ]] && echo "  $d: OK" || echo "  $d: MISSING"
done
echo "점검 완료."