mirror of
https://github.com/JefferyHcool/BiliNote.git
synced 2026-05-21 16:20:40 +08:00
8cd8c6f7b4
- Add /deploy_status API endpoint for system status check - Create Monitor.tsx component with real-time status display - Support CUDA, FFmpeg, Whisper model status monitoring - Auto-refresh every 30 seconds with manual refresh option
78 lines
2.1 KiB
Python
78 lines
2.1 KiB
Python
from fastapi import APIRouter, HTTPException
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from pydantic import BaseModel
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from typing import Optional
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from app.utils.response import ResponseWrapper as R
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from app.services.cookie_manager import CookieConfigManager
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from ffmpeg_helper import ensure_ffmpeg_or_raise
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router = APIRouter()
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cookie_manager = CookieConfigManager()
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class CookieUpdateRequest(BaseModel):
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platform: str
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cookie: str
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@router.get("/get_downloader_cookie/{platform}")
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def get_cookie(platform: str):
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cookie = cookie_manager.get(platform)
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if not cookie:
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return R.success(msg='未找到Cookies')
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return R.success(
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data={"platform": platform, "cookie": cookie}
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)
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@router.post("/update_downloader_cookie")
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def update_cookie(data: CookieUpdateRequest):
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cookie_manager.set(data.platform, data.cookie)
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return R.success(
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)
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@router.get("/sys_health")
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async def sys_health():
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try:
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ensure_ffmpeg_or_raise()
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return R.success()
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except EnvironmentError:
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return R.error(msg="系统未安装 ffmpeg 请先进行安装")
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@router.get("/sys_check")
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async def sys_check():
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return R.success()
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@router.get("/deploy_status")
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async def deploy_status():
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"""返回部署监控所需的所有状态信息"""
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import torch
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import os
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# CUDA 状态
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cuda_available = torch.cuda.is_available()
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cuda_info = {
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"available": cuda_available,
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"version": torch.version.cuda if cuda_available else None,
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"gpu_name": torch.cuda.get_device_name(0) if cuda_available else None,
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}
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# Whisper 模型状态
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model_size = os.getenv("WHISPER_MODEL_SIZE", "base")
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transcriber_type = os.getenv("TRANSCRIBER_TYPE", "fast-whisper")
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# FFmpeg 状态
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try:
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ensure_ffmpeg_or_raise()
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ffmpeg_ok = True
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except:
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ffmpeg_ok = False
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return R.success(data={
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"backend": {"status": "running", "port": int(os.getenv("BACKEND_PORT", 8483))},
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"cuda": cuda_info,
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"whisper": {"model_size": model_size, "transcriber_type": transcriber_type},
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"ffmpeg": {"available": ffmpeg_ok},
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}) |