MiniMax-AI/skills · warning · SystemExit

Timeout after {max_wait}s. task_id={task_id}, check manually

Error message

Timeout after {max_wait}s. task_id={task_id}, check manually.

What it means

poll_task() looped until elapsed reached max_wait (default 600s) without the status becoming Success or Fail — the job is still Processing/queued. The task is NOT dead; it continues server-side and can be checked later with the task_id.

Source

Thrown at skills/frontend-dev/scripts/minimax_video.py:107

        data = resp.json()
        _check_resp(data)

        status = data.get("status", "")
        file_id = data.get("file_id", "")

        if status == "Success":
            if not file_id:
                raise SystemExit("Task succeeded but no file_id returned")
            print(f"  Done! file_id={file_id}")
            return file_id
        elif status == "Fail":
            raise SystemExit(f"Video generation failed: {json.dumps(data, indent=2)}")
        else:
            print(f"  [{elapsed}s] Status: {status}...")
            time.sleep(interval)
            elapsed += interval

    raise SystemExit(f"Timeout after {max_wait}s. task_id={task_id}, check manually.")


def download_video(file_id: str, output_path: str):
    """Retrieve download URL via file_id and save the video."""
    resp = requests.get(
        f"{API_BASE}/files/retrieve",
        headers=_headers(),
        params={"file_id": file_id},
        timeout=30,
    )
    resp.raise_for_status()
    data = resp.json()
    _check_resp(data)

    download_url = data.get("file", {}).get("download_url", "")
    if not download_url:
        raise SystemExit(f"No download_url in response: {json.dumps(data, indent=2)}")

View on GitHub (pinned to 60aaae52bb)

Solutions

1. Raise the budget: re-run with `--max-wait 1200` (or pass max_wait=1200), keeping poll interval reasonable.
2. Do NOT discard the task_id from the dumped message — re-query GET {API_BASE}/query/video_generation?task_id=... later to resume waiting without re-creating the task.
3. Lower the work: use 768P/720P and duration 6 to finish faster within the window.
4. If timeouts are routine, build a resume-capable wrapper that persists task_id and polls across runs.

Example fix

// before: fixed 600s ceiling, task lost on timeout
raise SystemExit(f"Timeout after {max_wait}s. task_id={task_id}")

// after: persist task_id and support resume, raise ceiling
import json, pathlib
pathlib.Path(".video_task").write_text(task_id)
# re-run mode: python minimax_video.py --resume <task_id>
raise TimeoutError(f"still processing; task_id={task_id} saved for resume")

import json, pathlib

def run_video_resumable(prompt, out, max_wait=1200, task_store=pathlib.Path(".video_task")):
    """Raise max_wait and persist task_id so a timeout can be resumed."""
    task_id = task_store.read_text() if task_store.exists() else None
    if not task_id:
        task_id = create_task(prompt, ...)
        task_store.write_text(task_id)
    file_id = poll_task(task_id, interval=10, max_wait=max_wait)  # may raise TimeoutError
    download_video(file_id, out)
    task_store.unlink(missing_ok=True)

def is_processing(status: str) -> bool:
    """True when the task is still in a non-terminal (non-Success/Fail) state."""
    return status not in {"Success", "Fail"}

import subprocess, sys
timeout = 1200
while True:
    r = subprocess.run([sys.executable, "minimax_video.py", prompt, "-o", out, "--max-wait", str(timeout)], capture_output=True, text=True)
    if r.returncode == 0:
        break
    if "Timeout after" in (r.stderr or r.stdout or ""):
        tid = extract_task_id(r.stdout or r.stderr)  # task_id is in the message
        timeout = 600  # shorter re-poll window; same task_id continues server-side
        continue
    raise RuntimeError(r.stderr or r.stdout)

When it happens

Trigger: Long generations (1080P, 10s duration) under load exceeding the default 600s window; high platform concurrency slowing the queue; a too-aggressive poll that exits just before completion; max_wait lowered by the caller.

Common situations: First-time 1080P/10s jobs during peak hours; account tier with lower scheduling priority; default 600s too short for the chosen quality; network hiccup making each poll slow so fewer effective checks occur.

Understand the failure class

• Timeouts: ETIMEDOUT, deadlines, and hung requests — what actually expires when a request times out.

Related errors

• Generation incomplete (status={status}): {json.dumps(data, i
• Task succeeded but no file_id returned
• No download_url in response: {json.dumps(data, indent=2)}
• API Error [{code}]: {msg}
• No task_id in response: {json.dumps(data, indent=2)}

AI-assisted analysis of MiniMax-AI/skills@60aaae52bb (2026-08-13). Data as JSON: /api/errors/91b9db4cd9d1a9e0. Report an issue: GitHub.