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xiaoxia-saas/apps/api/app/schemas/gpu_lipsync.py
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xiaoxia a8f1069cd2
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fix(gpu): #1970 MuseTalk worker 推理期心跳/超时 900/重试收敛/短视频前置失败
- GPU_TASK_TIMEOUT_SECONDS 默认 300→900(base.py + env 模板),worker
  REQUEST_TIMEOUT 默认同步 300→900,RTX2060 6G 处理 720p 长视频不再超时
- worker 新增 TaskHeartbeat daemon 线程:任务处理期间每 30s POST
  /gpu/register(task_id=...) 续任务心跳,服务端只在任务心跳真正停滞
  超过 900s(崩溃/断网)或 worker 明确上报 failed 时才回退 pending,
  长推理阻塞主循环不再导致误回退
- register schema/service 支持 task_id:_touch_task_heartbeat 只刷新
  属于该 worker 且仍 processing 的任务,已完成/已被回收重派的过期心跳忽略
- worker 本地 TASK_MAX_RETRY 2→1,且仅对瞬时错误(连接失败/超时/5xx)重试;
  4xx、结果过小等确定性失败不本地重试,服务端 MAX_ATTEMPTS=3 不变,
  消除 3×3=9 次推理放大
- <3s 输入视频(MuseTalk division by zero)下载后 ffprobe 前置校验,
  直接上报 failed"视频过短",不调用推理;ffprobe 不可用时不拦截
- 新增 11 个单测(worker 独立脚本按路径加载),全量 15839 passed
2026-09-19 14:29:22 +08:00

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"""GPU MuseTalk 反向轮询 API Schema 定义.
面向部署在用户 RTX2060 本地的 GPU Worker 脚本,不面向前端用户。
Worker 用长期 GPU_WORKER_TOKEN 鉴权(不是用户 JWT)。
"""
from __future__ import annotations
from datetime import datetime
from typing import Optional
from pydantic import BaseModel, Field
# ── Worker 注册/心跳 ──────────────────────────────────────────────
class GpuWorkerRegisterRequest(BaseModel):
"""Worker 启动/心跳时上报自身信息."""
worker_id: str = Field(..., min_length=1, max_length=100, description="Worker 唯一 ID(机器名+UUID 等)")
hostname: str = Field("", max_length=200, description="主机名,用于运维排查")
gpu_name: str = Field("", max_length=200, description="GPU 型号,如 'NVIDIA GeForce RTX 2060'")
free_vram_mb: int = Field(0, ge=0, description="当前空闲显存(MB)")
capabilities: str = Field("musetalk", max_length=500, description="能力列表,逗号分隔,如 'musetalk'")
task_id: Optional[str] = Field(
None,
max_length=64,
description=(
"当前正在处理的任务 ID。Worker 推理期间定期心跳时携带,"
"服务端同步刷新该任务 last_heartbeat_at,防止长推理被误判超时;空闲时不传"
),
)
class GpuWorkerRegisterResponse(BaseModel):
ok: bool = True
server_time: datetime
message: str = "ok"
# ── 轮询任务 ────────────────────────────────────────────────────
class GpuLipsyncTaskPayload(BaseModel):
"""下发给 Worker 的任务载荷(含预签名下载 URL)."""
task_id: str
video_url: str = Field(..., description="人物视频预签名下载 URL(GET)")
audio_url: str = Field(..., description="驱动音频预签名下载 URL(GET)")
lipsync_job_id: str = ""
user_id: str = ""
project_id: str = ""
created_at: datetime
upload_url: str = Field(..., description="结果视频预签名上传 URL(PUT, video/mp4)")
upload_method: str = Field("PUT", description="上传方式,目前只支持 PUT")
expires_at: datetime
class GpuLipsyncPollResponse(BaseModel):
"""Worker poll 的返回:200 带任务,204 无任务."""
task: Optional[GpuLipsyncTaskPayload] = None
# ── Worker 上报结果 ──────────────────────────────────────────────
class GpuLipsyncResultRequest(BaseModel):
"""Worker 通过 multipart 上传结果时携带的字段(非文件字段)."""
task_id: str = Field(..., min_length=1, max_length=64)
worker_id: str = Field(..., min_length=1, max_length=100)
success: bool = Field(True, description="true=成功(此时必须上传 result 视频文件);false=失败")
duration_seconds: float = Field(0.0, ge=0, description="合成后视频时长(秒),成功时应填入")
error_msg: str = Field("", max_length=2000, description="失败原因,success=false 时必填")
class GpuLipsyncResultResponse(BaseModel):
ok: bool = True
task_id: str
status: str # done / failed
message: str = "ok"
# ── 业务侧查询任务状态 ────────────────────────────────────────────
class GpuLipsyncStatusResponse(BaseModel):
task_id: str
status: str
result_url: str = ""
result_duration: float = 0.0
error_msg: str = ""
worker_id: str = ""
attempt: int = 0
created_at: datetime
started_at: Optional[datetime] = None
finished_at: Optional[datetime] = None
# ── 创建任务(内部服务调用) ──────────────────────────────────────
class GpuLipsyncCreateRequest(BaseModel):
"""服务层内部创建 GPU 任务用(不通过 HTTP 暴露给 Worker/前端)."""
video_url: str # 已可访问的 OSS key 或公网 URL(API 侧会转预签名)
audio_url: str
lipsync_job_id: str = ""
user_id: str = ""
project_id: str = ""