feat(gpu): #1978 AI数字人口型同步接入MuseTalk GPU Worker(业务侧集成) (#1991)
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This commit was merged in pull request #1991.
This commit is contained in:
@@ -325,3 +325,58 @@ class GpuLipsyncService:
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t.updated_at = now
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if stuck_tasks:
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self.db.flush()
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# ── 业务侧辅助 ──────────────────────────────────────────────────
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def has_available_worker(self) -> bool:
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"""判断是否有 Worker 在心跳新鲜窗口内可用."""
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stale_cutoff = datetime.now(UTC) - timedelta(seconds=self.settings.gpu_worker_stale_seconds)
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return (
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self.db.query(GpuWorkerModel).filter(GpuWorkerModel.last_heartbeat_at >= stale_cutoff).first() is not None
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)
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def wait_for_result(
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self,
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task_id: str,
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timeout_seconds: Optional[int] = None,
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poll_interval: Optional[float] = None,
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) -> Optional[GpuLipsyncTaskModel]:
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"""同步轮询等待 GPU 任务完成。
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Args:
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task_id: 任务 ID(由 create_task 返回)
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timeout_seconds: 总超时,默认取 settings.gpu_lipsync_wait_timeout
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poll_interval: 轮询间隔秒,默认取 settings.gpu_lipsync_poll_interval
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Returns:
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终态 task(status=done/failed);超时返回 None(此时调用方应回退 MediaKit)。
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等待期间会自动调用 _recover_timed_out_tasks 做超时回收。
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"""
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import time
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timeout = timeout_seconds if timeout_seconds is not None else self.settings.gpu_lipsync_wait_timeout
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interval = poll_interval if poll_interval is not None else self.settings.gpu_lipsync_poll_interval
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deadline = time.monotonic() + timeout
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while True:
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now = datetime.now(UTC)
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# 顺手回收超时任务
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try:
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self._recover_timed_out_tasks(now)
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self.db.commit()
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except Exception as exc: # noqa: BLE001 - 回收失败不阻塞主流程
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logger.warning("wait_for_result 回收超时任务异常: %s", exc)
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self.db.rollback()
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task = self.db.get(GpuLipsyncTaskModel, task_id)
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if task is None:
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return None
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if task.status == "done":
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return task
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if task.status == "failed":
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return task
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# pending/processing 继续等
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if time.monotonic() >= deadline:
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logger.warning("GPU 任务 %s 等待超时(%ds),回退 MediaKit", task_id, timeout)
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return None
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time.sleep(interval)
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@@ -36,6 +36,7 @@ from sqlalchemy.orm import Session
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from packages.adapters.sqlalchemy_impl.models import LipsyncJobModel
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from packages.application.cosyvoice_service import CosyVoiceError
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from packages.config import get_api_settings
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from packages.domain.sentence_timings import (
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compute_sentence_timings,
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probe_audio_duration,
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@@ -63,6 +64,7 @@ class LipsyncService:
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self.client = client or get_mediakit_client()
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self._cosyvoice = cosyvoice_service
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self._voice_clone_repo = voice_clone_repo
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self.settings = get_api_settings()
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def _get_cosyvoice(self):
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"""延迟获取 CosyVoiceService(与 tts 路由一致,含 OSS 预签名配置)."""
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@@ -215,7 +217,52 @@ class LipsyncService:
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if timings:
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job.sentence_timings = timings
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# 4. 签名 URL 并提交 MediaKit
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# 4. 检查是否走 GPU 路径:开关打开 + 有可用 Worker
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use_gpu = False
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if self.settings.use_gpu_lipsync:
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try:
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from app.services.gpu_lipsync_service import GpuLipsyncService
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gpu_svc = GpuLipsyncService(self.db)
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if gpu_svc.has_available_worker():
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use_gpu = True
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logger.info("[lipsync] 检测到可用 GPU Worker,优先走 MuseTalk 本地推理: job_id=%s", job.id)
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else:
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logger.info("[lipsync] GPU 开关已开但无可用 Worker(心跳过期),回退 MediaKit: job_id=%s", job.id)
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except Exception as exc:
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logger.warning("[lipsync] GPU 服务初始化失败,回退 MediaKit: job_id=%s err=%s", job.id, exc)
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if use_gpu:
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try:
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gpu_task = self._submit_to_gpu(job=job, gpu_svc=gpu_svc)
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if gpu_task is not None:
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# GPU 任务完成:直接把结果写入 job,标为 completed
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job.mediakit_task_id = "" # GPU 路径不走 MediaKit
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job.status = STATUS_COMPLETED
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job.output_video_url = gpu_task.result_url
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job.output_duration = gpu_task.result_duration or 0.0
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job.completed_at = datetime.now(UTC)
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job.updated_at = datetime.now(UTC)
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self.db.commit()
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logger.info(
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"[lipsync] GPU MuseTalk 推理完成: job_id=%s gpu_task=%s duration=%.2f",
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job.id,
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gpu_task.id,
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job.output_duration,
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)
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# 转存到持久 OSS 路径(GPU 结果已在 gpu-lipsync/results/ 下,直接签短链)
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return
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# wait_for_result 返回 None 表示超时/最终失败 → 继续走 MediaKit 兜底
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logger.warning("[lipsync] GPU 任务等待超时或失败,回退 MediaKit: job_id=%s", job.id)
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self.db.rollback() # 回滚可能的中间状态
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except Exception as exc:
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logger.exception("[lipsync] GPU 路径异常,回退 MediaKit: job_id=%s err=%s", job.id, exc)
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try:
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self.db.rollback()
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except Exception:
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pass
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# 5. 签名 URL 并提交 MediaKit(兜底路径)
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video_url = self._sign_media_url(job.video_url)
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signed_audio_url = self._sign_media_url(job.audio_url)
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job.audio_url = signed_audio_url
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@@ -244,6 +291,51 @@ class LipsyncService:
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self.db.commit()
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raise
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# ── GPU MuseTalk 路径 ────────────────────────────────────────────────
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def _submit_to_gpu(self, *, job, gpu_svc) -> Optional[object]:
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"""创建 GPU 任务并同步等待结果。
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成功返回终态 task 对象(status=done);超时或 GPU 最终失败返回 None,
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调用方回退 MediaKit。
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注意:job.video_url / job.audio_url 可能是:
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- 自家 OSS 存储 key(storage.is_own_url 判断,gpu_svc.create_task 内部
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get_download_url 会自动签预签名 URL 给 Worker)
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- 外部公网 URL(CosyVoice 临时链接等):poll 返回时原样透传给 Worker,
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Worker 可直接 GET 下载。
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"""
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# 创建 GPU 任务
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gpu_task = gpu_svc.create_task(
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video_url=job.video_url,
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audio_url=job.audio_url,
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lipsync_job_id=job.id,
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user_id=job.user_id,
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project_id=job.project_id,
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)
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logger.info(
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"[lipsync] 已创建 GPU 任务: job_id=%s gpu_task=%s",
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job.id,
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gpu_task.id,
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)
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# 同步等待 Worker 处理完成(轮询 DB)
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final_task = gpu_svc.wait_for_result(gpu_task.id)
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if final_task is None:
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logger.warning("[lipsync] GPU 任务等待超时,回退 MediaKit: gpu_task=%s", gpu_task.id)
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return None
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if final_task.status != "done":
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logger.warning(
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"[lipsync] GPU 任务失败: gpu_task=%s status=%s err=%s",
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gpu_task.id,
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final_task.status,
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final_task.error_msg,
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)
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return None
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# result_url 是 OSS 存储 key;签一个长有效期 URL 写回 job.output_video_url
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result_signed = self._sign_media_url(final_task.result_url)
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final_task.result_url = result_signed or final_task.result_url
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return final_task
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# ── 创建任务 ──────────────────────────────────────────────────────────
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def create_job(
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