app_backup.py

import os, subprocess, requests
from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()

class RigIn(BaseModel):
    mesh_url: str  # 입력 파일 URL (obj, glb, fbx 등)

@app.get("/")
def root():
    return {"message": "Puppeteer API (GPU) ready"}

@app.get("/health")
def health():
    try:
        import torch
        gpu = torch.cuda.is_available()
        name = torch.cuda.get_device_name(0) if gpu else None
        return {"status": "ok", "cuda": gpu, "gpu": name}
    except Exception as e:
        return {"status": "ok", "cuda": False, "detail": str(e)}

@app.post("/rig")
def rig(inp: RigIn):
    os.makedirs("/tmp/in", exist_ok=True)
    mesh_path = os.path.join("/tmp/in", os.path.basename(inp.mesh_url))

    # 1️⃣ 입력 파일 다운로드
    with requests.get(inp.mesh_url, stream=True) as r:
        r.raise_for_status()
        with open(mesh_path, "wb") as f:
            for chunk in r.iter_content(chunk_size=8192):
                if chunk:
                    f.write(chunk)

    # 2️⃣ Puppeteer 실행
    workdir = "/app/Puppeteer"
    cmd = ["bash", "demo_rigging.sh", mesh_path]
    try:
        subprocess.run(cmd, cwd=workdir, check=True)
    except subprocess.CalledProcessError as e:
        return {"status": "error", "detail": str(e)}

    # 3️⃣ 결과 목록 반환
    result_dir = os.path.join(workdir, "results")
    files = []
    for rootdir, _, filenames in os.walk(result_dir):
        for fn in filenames:
            files.append(os.path.join(rootdir, fn))
            if len(files) >= 20: break
    return {"status": "ok", "result_dir": result_dir, "files_preview": files[:10]}