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fix(backend): 部署韧性——模型自愈/就绪门禁/全局代理/启动诊断
- whisper: model.bin 截断/损坏时删目录重下重试一次,修「Unable to
open file model.bin」死循环;mlx 同样按 config.json 判完整性
- /generate_note 加就绪门禁:本地转写引擎模型没下好直接拦截,返回
reason=transcriber_model_not_ready,不让任务静默卡在首次下载
- 全局代理:新增 ProxyConfigManager(JSON 配置 + HTTP_PROXY env 兜底)
+ build_openai_client,统一注入代理到 LLM/Groq 客户端;yt-dlp 与
youtube-transcript-api 也走代理
- build_openai_client 校验 api_key 非空,空 key 给「xxx 的 API Key
未配置」而不是天书般的 Illegal header value b'Bearer '
- universal_gpt: 模型拒绝自定义 temperature(o1/o3/gpt-5 系列)时
就地去掉参数重试,不消耗重试预算
- connect_test 改用真实 chat completion 而非 /v1/models 探测
- main.py: lifespan 拆 [startup 1/5..5/5] 分段日志 + 异常清晰定位
- /sys_health 重构为结构化返回 {backend,ffmpeg,db,whisper_model}
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
This commit is contained in:
co-authored by
Claude Opus 4.7
parent
88d25f8cc1
commit
41f17592c2
@@ -61,3 +61,54 @@ class TranscriberConfigManager:
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def get_whisper_model_size(self) -> str:
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return self.get_config()["whisper_model_size"]
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def is_model_ready(self) -> Dict[str, Any]:
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"""当前转写器是否就绪可用。
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返回 {ready, transcriber_type, model_size, downloading, reason}:
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- 在线引擎 (groq/bcut/kuaishou):永远 ready(不需要本地模型)
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- fast-whisper:检查 whisper-{size}/model.bin 落盘
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- mlx-whisper:检查 {repo_id}/config.json 落盘
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给 /generate_note 入口做「开始视频前先确认模型下载好」的门禁用。
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"""
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cfg = self.get_config()
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ttype = cfg["transcriber_type"]
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size = cfg["whisper_model_size"]
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result = {
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"ready": True,
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"transcriber_type": ttype,
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"model_size": size,
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"downloading": False,
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"reason": "",
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}
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if ttype not in ("fast-whisper", "mlx-whisper"):
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return result # 在线引擎无需本地模型
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# 延迟 import 避免与 routers.config 的循环依赖;只取纯函数,不触发路由副作用
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try:
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from app.routers.config import (
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_check_whisper_model_exists,
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_check_mlx_whisper_model_exists,
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_downloading,
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)
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except Exception as e:
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# 拿不到检查函数时保守放行,不要把用户卡死
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result["reason"] = f"无法检查模型状态: {e}"
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return result
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if ttype == "fast-whisper":
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downloaded = _check_whisper_model_exists(size, "whisper")
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downloading = _downloading.get(size) == "downloading"
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else: # mlx-whisper
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downloaded = _check_mlx_whisper_model_exists(size)
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downloading = _downloading.get(f"mlx-{size}") == "downloading"
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result["downloading"] = downloading
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if downloaded:
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return result
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result["ready"] = False
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result["reason"] = (
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f"转写模型 {ttype} / {size} 尚未下载就绪"
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+ (",正在下载中,请稍候" if downloading else ",请先在「设置 → 音频转写配置」页下载")
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)
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return result
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