Files
xiaoxia-saas/apps/api/app/tasks/lipsync_tts.py
T
xiaoxia 2fa6de29bc
CI/CD Pipeline / Dedup Check - skip PR tests when covered by push pipeline (pull_request) Successful in 1s
CI/CD Pipeline / Check if frontend-only change (pull_request) Successful in 2s
CI/CD Pipeline / PR Build Web Image (pull_request) Successful in 30s
CI/CD Pipeline / PR Build API Image (pull_request) Successful in 33s
CI/CD Pipeline / Frontend Lint (pull_request) Successful in 1m39s
CI/CD Pipeline / PR Build Worker Image (pull_request) Successful in 1m39s
CI/CD Pipeline / Frontend Unit Tests (pull_request) Successful in 1m47s
PR Automation / Auto Approve on CI Green (pull_request) Successful in 2m44s
Preview Deploy / Deploy Preview Environment (pull_request) Successful in 2m55s
AI Code Review / AI Code Review (pull_request) Successful in 6m31s
CI/CD Pipeline / Integration Tests (pull_request) Successful in 8m15s
CI/CD Pipeline / Unit Tests (pull_request) Successful in 8m17s
CI/CD Pipeline / Validate - Python (mypy + alembic) (pull_request) Successful in 10m28s
CI/CD Pipeline / Validate - Style (pull_request) Has been cancelled
CI/CD Pipeline / Validate - Security (pull_request) Has been cancelled
CI/CD Pipeline / Build Production API Image (pull_request) Has been cancelled
CI/CD Pipeline / Build Production Web Image (pull_request) Has been cancelled
CI/CD Pipeline / Build Production Worker Image (pull_request) Has been cancelled
CI/CD Pipeline / Deploy Production (pull_request) Has been cancelled
CI/CD Pipeline / Production Browser E2E (pull_request) Has been cancelled
CI/CD Pipeline / Canary Release to Production (pull_request) Has been cancelled
CI/CD Pipeline / CI Gate (pull_request) Has been cancelled
PR Automation / Auto Merge on CI Green + Approved (pull_request) Has been cancelled
CI/CD Pipeline / Staging API Integration Tests (pull_request) Failing after 89h23m49s
CI/CD Pipeline / Retag skipped Staging Web Image (pull_request) Failing after 89h23m53s
CI/CD Pipeline / Build Staging Web Image (pull_request) Failing after 89h23m55s
CI/CD Pipeline / Build Staging API Image (pull_request) Failing after 89h23m33s
CI/CD Pipeline / ACR Image Cleanup (pull_request) Failing after 89h23m27s
CI/CD Pipeline / Retag skipped Staging Worker Image (pull_request) Failing after 89h23m31s
CI/CD Pipeline / Build Staging Worker Image (pull_request) Failing after 89h23m33s
CI/CD Pipeline / Staging E2E Tests (pull_request) Failing after 89h23m27s
CI/CD Pipeline / Deploy Staging (Watchtower auto-deploy) (pull_request) Failing after 89h23m28s
CI/CD Pipeline / Retag skipped Staging API Image (pull_request) Failing after 89h23m31s
CI/CD Pipeline / Check push changed paths (pull_request) Failing after 89h24m9s
fix(lipsync): 修复Celery事务竞态导致job永远卡在tts_processing(P0)
根因:create_job() 先 apply_async() 发送 Celery 任务,再 db.commit() 提交事务。
worker 是独立进程+独立DB连接,任务<4ms就被消费,但此时 API 事务还未 commit,
worker 查询 job 返回 None → 静默 return 不重试 → job 永远卡在 tts_processing。

修复:
1. API侧(lipsync_service.py):先 db.commit()+db.refresh(job),再 apply_async() 发任务;
   投递失败/MediaKit提交失败分支也各自 commit,确保状态及时落库。
2. Worker侧(lipsync_tts.py):job not found 时改用 self.retry() 递增重试3次
   (1s/3s/7s退避),作为竞态场景的第二道防线;
   增加 autoretry_for=(OSError, ConnectionError) 自动重试网络抖动;
   max_retries 从2调整到5。

子agent在staging实锤:受影响job共5个,手工重投递后全部3秒内完成TTS+提交MediaKit,
证实TTS本身只需要2秒,卡顿完全是因为竞态。

单测:新增 TestCreateJobCommitOrder 验证 commit 在 apply_async 之前。
2026-09-12 21:50:02 +08:00

547 lines
20 KiB
Python
Raw Blame History

This file contains ambiguous Unicode characters
This file contains Unicode characters that might be confused with other characters. If you think that this is intentional, you can safely ignore this warning. Use the Escape button to reveal them.
"""AI 数字人对口型 TTS 异步任务 — 将 TTS 合成从 HTTP 请求移至 Celery 后台执行.
优化目标:将 create_job 的 API 响应时间从 6~35s 降到 <1s。
任务流程:
1. 创建新 DB session,加载 job 记录
2. 调用 CosyVoice 合成音频
3. 下载音频并转存到自家 OSS
4. 更新 job 的 audio_url
5. 签名 URL 并提交到 MediaKit
6. 更新 job 状态为 submitted
7. 异常时标记 job 为 failed
注意:使用 @shared_task 而非绑定到某个 celery_app 实例,
确保任务能被 Worker 侧 celery_app 正确注册,同时 API 侧 send_task/apply_async 仍可正常调用。
"""
import io
import logging
from datetime import datetime, timezone
from urllib.parse import urlparse
from celery import shared_task
logger = logging.getLogger(__name__)
# MediaKit 预签名 URL 有效期(7天,秒),与 LipsyncService._sign_media_url 保持一致
_MEDIAKIT_URL_TTL_SECONDS = 7 * 24 * 3600
def _sign_media_url(url: str) -> str:
"""对自家 OSS 私有桶 URL 重签长有效期预签名.
- 自家 OSS URL → 重签 7 天有效期
- 外部临时 URL → 原样透传
- 任何异常降级原样返回,不阻断主流程
"""
if not url:
return url
try:
from packages.shared.storage import get_shared_storage_service
storage = get_shared_storage_service()
public_base = getattr(storage, "public_url", "")
if not isinstance(public_base, str) or not public_base:
return url
own_host = urlparse(public_base).netloc.lower()
host = urlparse(url).netloc.lower()
if not own_host or host != own_host:
return url
signed = storage.get_download_url(url, expires_seconds=_MEDIAKIT_URL_TTL_SECONDS)
return signed or url
except Exception as exc: # noqa: BLE001
logger.warning("[lipsync_tts] URL 重签失败,原样返回: url_prefix=%s err=%s", url[:80], exc)
return url
def _split_script_into_sentences(script_text: str) -> list[str]:
"""按句号/问号/感叹号/分号/换行分句(与前端 splitScriptIntoSentences 一致)."""
import re
text = (script_text or "").strip()
if not text:
return []
parts = re.split(r"[。!?!?;;\n\r]+", text)
return [p.strip() for p in parts if p.strip()]
def _compute_sentence_timings(audio_data: bytes, script_text: str, total_duration: float) -> list[dict]:
"""基于 TTS 音频的静音检测,精确计算每句文案的起止时间.
使用 ffmpeg silencedetect 检测静音段,将静音点与句子边界对齐。
比字数比例估算准确得多。
Args:
audio_data: TTS 音频二进制数据(MP3)
script_text: 文案全文
total_duration: 音频总时长(秒)
Returns:
list[{"index": int, "text": str, "start_time": float, "end_time": float}]
"""
import re
import subprocess
import tempfile
sentences = _split_script_into_sentences(script_text)
if not sentences:
return []
# 写入临时音频文件
with tempfile.NamedTemporaryFile(suffix=".mp3", delete=False) as tmp:
tmp.write(audio_data)
tmp_path = tmp.name
try:
# 用 ffmpeg silencedetect 检测静音段
result = subprocess.run(
[
"ffmpeg",
"-i",
tmp_path,
"-af",
"silencedetect=noise=-25dB:d=0.3",
"-f",
"null",
"-",
],
capture_output=True,
text=True,
timeout=30,
)
stderr = result.stderr or ""
# 解析静音结束时间点(silence_end: X.XXX)
silence_ends = []
for match in re.finditer(r"silence_end:\s*([\d.]+)", stderr):
t = float(match.group(1))
if 0 < t < total_duration:
silence_ends.append(t)
# 如果没有检测到足够的静音点,降级为字数比例估算
if len(silence_ends) < len(sentences) - 1:
logger.warning(
"[sentence_timings] 静音点不足(%d < %d),降级为字数比例估算",
len(silence_ends),
len(sentences) - 1,
)
return _estimate_sentence_timings_by_chars(sentences, total_duration)
# 贪心匹配:N-1 个句子边界对应 N-1 个静音点
# 按时间均匀分布期望值,选择最近的静音点
n_boundaries = len(sentences) - 1
boundaries = []
used_indices = set()
for i in range(n_boundaries):
# 期望的边界位置(按句子数量均匀分布)
expected_pos = (i + 1) / len(sentences) * total_duration
# 找最近的未使用静音点
best_idx = None
best_dist = float("inf")
for j, t in enumerate(silence_ends):
if j in used_indices:
continue
dist = abs(t - expected_pos)
if dist < best_dist:
best_dist = dist
best_idx = j
if best_idx is not None:
used_indices.add(best_idx)
boundaries.append(silence_ends[best_idx])
boundaries.sort()
# 构建 sentence_timings
timings = []
prev_end = 0.0
for i, sent in enumerate(sentences):
start = prev_end
end = boundaries[i] if i < len(boundaries) else total_duration
timings.append(
{
"index": i,
"text": sent,
"start_time": round(start, 2),
"end_time": round(end, 2),
}
)
prev_end = end
return timings
except Exception as exc:
logger.warning("[sentence_timings] 静音检测异常,降级为字数比例估算: %s", exc)
return _estimate_sentence_timings_by_chars(sentences, total_duration)
finally:
import os
try:
os.unlink(tmp_path)
except Exception:
pass
def _estimate_sentence_timings_by_chars(sentences: list[str], total_duration: float) -> list[dict]:
"""降级方案:按字数比例估算句子时间(与原前端逻辑一致)."""
if not sentences or total_duration <= 0:
return []
total_chars = sum(len(s.replace(r"\s", "")) for s in sentences)
if total_chars == 0:
return []
timings = []
acc = 0
for i, sent in enumerate(sentences):
chars = len(sent.replace(r"\s", ""))
start = (acc / total_chars) * total_duration
end = ((acc + chars) / total_chars) * total_duration
timings.append(
{
"index": i,
"text": sent,
"start_time": round(start, 2),
"end_time": round(end, 2),
}
)
acc += chars
return timings
@shared_task(
bind=True,
name="lipsync_tts.synthesize_and_submit",
max_retries=5, # 事务竞态重试3次(job not found)+ TTS偶发错误2次
default_retry_delay=30,
autoretry_for=(OSError, ConnectionError), # 网络/连接错误自动重试
retry_backoff=True,
retry_backoff_max=30,
soft_time_limit=180,
time_limit=200,
)
def tts_synthesize_and_submit(
self,
job_id: str,
user_id: str,
voice_id: str,
script_text: str,
speed: float,
emotion: str,
):
"""异步执行 TTS 合成 + OSS 转存 + MediaKit 提交.
在 Celery worker 中运行,不阻塞 HTTP 请求。
"""
from app.services.mediakit_client import MediaKitError, get_mediakit_client
from sqlalchemy.orm import Session as DBSession
from packages.adapters.sqlalchemy_impl.models import LipsyncJobModel
from packages.application.cosyvoice_service import CosyVoiceError, CosyVoiceService
from packages.shared.url_security import safe_download_bytes
# SessionLocal 获取:
# - API 容器:app.db.SessionLocal(环境变量完整,导入即建引擎)
# - Worker 容器:worker_app.db.SessionLocal(Worker 自己的 settings 初始化引擎)
# API 侧没有 worker_app 模块 → ImportError 直接回退;
# Worker 侧 app.db 会因缺少 API 专有环境变量抛 pydantic ValidationError,
# 此时也要回退到 worker_app.db。
try:
from worker_app.db import SessionLocal # type: ignore
except Exception: # noqa: BLE001
from app.db import SessionLocal # type: ignore
db: DBSession = SessionLocal()
try:
job = (
db.query(LipsyncJobModel)
.filter(
LipsyncJobModel.id == job_id,
LipsyncJobModel.user_id == user_id,
)
.first()
)
if job is None:
# 事务竞态防御:API 在 commit 前投递了任务,worker 消费时事务尚未提交。
# Celery 内置 autoretry_for 不支持"业务条件重试",这里手动 retry 3 次,
# 间隔递增(1s/3s/7s),让 API 事务有时间提交。
# max_retries 由 self.request(retries) 维护;默认 self.max_retries=3 由装饰器 soft_time_limit 下方指定。
retries = getattr(self.request, "retries", 0)
max_retries = 3
if retries < max_retries:
backoff = (2 ** retries) + (retries * 1) # 1s, 3s, 7s
logger.warning(
"[lipsync_tts] Job not found yet (retry %d/%d, backoff %ds): job_id=%s",
retries + 1,
max_retries,
backoff,
job_id,
)
self.db.close()
raise self.retry(countdown=backoff, max_retries=max_retries)
logger.error(
"[lipsync_tts] Job not found after %d retries, giving up: job_id=%s",
max_retries,
job_id,
)
return
# 已取消的任务不再处理
if job.status == "cancelled":
logger.info("[lipsync_tts] Job already cancelled, skipping: job_id=%s", job_id)
return
# 1. TTS 合成
logger.info(
"[lipsync_tts] 开始 TTS 合成: job_id=%s voice_id=%s text_len=%d speed=%.2f",
job_id,
voice_id,
len(script_text),
speed,
)
try:
cosyvoice = CosyVoiceService()
result = cosyvoice.submit_synthesize_task(
text=script_text,
voice_id=voice_id,
speed=speed,
emotion=emotion,
)
except CosyVoiceError as exc:
logger.error("[lipsync_tts] TTS 合成失败: job_id=%s err=%s", job_id, exc)
job.status = "failed"
job.error_message = f"TTS 合成失败: {exc}"
job.error_code = "TTSSynthesisFailed"
job.updated_at = datetime.now(timezone.utc)
db.commit()
return
except ValueError as exc:
logger.error("[lipsync_tts] TTS 参数错误: job_id=%s err=%s", job_id, exc)
job.status = "failed"
job.error_message = f"TTS 参数错误: {exc}"
job.error_code = "TTSInvalidParam"
job.updated_at = datetime.now(timezone.utc)
db.commit()
return
temp_url = result.get("audio_url", "")
if not temp_url:
logger.error("[lipsync_tts] TTS 未返回音频 URL: job_id=%s", job_id)
job.status = "failed"
job.error_message = "TTS 未返回音频 URL"
job.error_code = "TTSNoAudio"
job.updated_at = datetime.now(timezone.utc)
db.commit()
return
# 2. 下载 TTS 音频到内存(用于 2.5 静音检测;不转存自家 OSS,直接使用 CosyVoice 临时 URL)
audio_data: bytes | None = None
_st_tmp_path: str | None = None
try:
audio_data = safe_download_bytes(
temp_url,
purpose="lipsync_tts_audio",
allowed_mime_types={
"audio/mpeg",
"audio/mp3",
"audio/wav",
"audio/x-wav", # CosyVoice 部分接口返回 audio/x-wav,与 audio/wav 等价(RIFF/WAVE)
"audio/mp4",
"audio/x-m4a",
},
timeout=60.0,
)
logger.info(
"[lipsync_tts] TTS 音频已下载到内存: job_id=%s size=%d",
job_id,
len(audio_data) if audio_data else 0,
)
except Exception as exc:
# 下载失败:audio_data 保持 None,2.5 静音检测会跳过;后续仍用 temp_url 提交 MediaKit
logger.warning(
"[lipsync_tts] TTS 音频下载失败,跳过静音检测,直接使用临时 URL 提交: job_id=%s err=%s",
job_id,
exc,
)
# TTS 音频使用 CosyVoice 临时 URL,跳过自家 OSS 转存(加速,步骤⑥)
job.audio_url = temp_url
logger.info("[lipsync_tts] TTS 音频使用 CosyVoice 临时 URL(跳过 OSS 转存): job_id=%s", job_id)
db.commit()
# 2.5 计算精确句子时间戳(基于 TTS 音频静音检测)
# 直接复用步骤 2 已下载到内存的 audio_data,避免重新下载
import os as _os
try:
import subprocess as _sp
import tempfile as _tmpf
if not audio_data:
logger.warning("[lipsync_tts] 无音频数据,跳过句子时间戳计算: job_id=%s", job_id)
else:
# 写入临时文件供 ffprobe/ffmpeg 使用
with _tmpf.NamedTemporaryFile(suffix=".mp3", delete=False) as _atmp:
_atmp.write(audio_data)
_st_tmp_path = _atmp.name
# ffprobe 获取音频时长
_probe_result = _sp.run(
[
"ffprobe",
"-v",
"error",
"-show_entries",
"format=duration",
"-of",
"default=noprint_wrappers=1:nokey=1",
_st_tmp_path,
],
capture_output=True,
text=True,
timeout=10,
)
_audio_duration = float(_probe_result.stdout.strip()) if _probe_result.stdout.strip() else 0.0
logger.info(
"[lipsync_tts] 音频时长探测: job_id=%s duration=%.2f probe_stdout=%s probe_stderr=%s",
job_id,
_audio_duration,
_probe_result.stdout.strip()[:50],
_probe_result.stderr.strip()[:100] if _probe_result.stderr else "",
)
if _audio_duration > 0:
_timings = _compute_sentence_timings(audio_data, script_text, _audio_duration)
if _timings:
job.sentence_timings = _timings
logger.info(
"[lipsync_tts] 句子时间戳已计算: job_id=%s sentences=%d duration=%.1f",
job_id,
len(_timings),
_audio_duration,
)
else:
logger.warning("[lipsync_tts] 句子时间戳计算返回空结果: job_id=%s", job_id)
else:
logger.warning(
"[lipsync_tts] ffprobe 未获取到有效时长,跳过句子时间戳: job_id=%s stdout=%s stderr=%s",
job_id,
_probe_result.stdout.strip()[:100],
_probe_result.stderr.strip()[:200] if _probe_result.stderr else "",
)
db.commit()
except Exception as _st_err:
logger.warning(
"[lipsync_tts] 句子时间戳计算失败(不影响主流程): job_id=%s err=%s", job_id, _st_err, exc_info=True
)
finally:
if _st_tmp_path:
try:
_os.unlink(_st_tmp_path)
except Exception:
pass
# 3. 签名 URL 并提交到 MediaKit(复用模块内 _sign_media_url,避免对 LipsyncService 的耦合)
audio_url = _sign_media_url(job.audio_url)
video_url = _sign_media_url(job.video_url)
client = get_mediakit_client()
try:
mk_result = client.submit_lipsync(
video_url=video_url,
audio_url=audio_url,
enable_video_loop=job.enable_video_loop,
client_token=job_id,
)
job.mediakit_task_id = mk_result["task_id"]
job.status = "submitted"
job.submitted_at = datetime.now(timezone.utc)
logger.info(
"[lipsync_tts] 已提交 MediaKit: job_id=%s task_id=%s",
job_id,
mk_result["task_id"],
)
except MediaKitError as exc:
job.status = "failed"
job.error_message = str(exc)
job.error_code = exc.code
logger.error("[lipsync_tts] 提交 MediaKit 失败: job_id=%s err=%s", job_id, exc)
db.commit()
except Exception:
logger.exception("[lipsync_tts] 未预期的异常: job_id=%s", job_id)
try:
job = db.query(LipsyncJobModel).filter(LipsyncJobModel.id == job_id).first()
if job and job.status not in ("cancelled", "failed", "completed"):
job.status = "failed"
job.error_message = "TTS 异步任务执行异常"
job.error_code = "AsyncTaskError"
job.updated_at = datetime.now(timezone.utc)
db.commit()
except Exception:
logger.exception("[lipsync_tts] 回写失败状态时异常: job_id=%s", job_id)
finally:
db.close()
@shared_task(
name="lipsync_tts.persist_output_video",
max_retries=2,
default_retry_delay=30,
)
def persist_output_video_task(job_id: str, user_id: str, temp_url: str):
"""异步转存对口型输出视频到自家 OSS(步骤⑦ — 将同步阻塞挪到后台,加速前端响应).
- MediaKit 返回 completed 后先以 temp_url 回前端(前端可立即播放临时 URL)
- Celery 后台下载 temp_url 并转存 OSS,成功后更新 job.output_video_url 为永久 URL
- 失败则保留 temp_url,不阻断主流程
"""
try:
from worker_app.db import SessionLocal # type: ignore
except Exception: # noqa: BLE001
from app.db import SessionLocal # type: ignore
from packages.adapters.sqlalchemy_impl.models import LipsyncJobModel
from packages.shared.storage import get_shared_storage_service
db = SessionLocal()
try:
job = db.query(LipsyncJobModel).filter(LipsyncJobModel.id == job_id, LipsyncJobModel.user_id == user_id).first()
if job is None:
logger.error("[lipsync_tts.persist] Job not found: job_id=%s", job_id)
return
if not temp_url:
logger.warning("[lipsync_tts.persist] temp_url 为空,跳过转存: job_id=%s", job_id)
return
try:
import httpx
with httpx.Client(timeout=180.0, follow_redirects=True) as client:
resp = client.get(temp_url)
resp.raise_for_status()
data = resp.content
storage = get_shared_storage_service()
storage_key = f"lipsync-outputs/{user_id}/{job_id}.mp4"
permanent_url = storage.upload_file(io.BytesIO(data), storage_key, content_type="video/mp4")
# 对自家 OSS URL 重签 7 天有效期预签名,供前端播放
final_url = _sign_media_url(permanent_url) if permanent_url else temp_url
job.output_video_url = final_url
job.updated_at = datetime.now(timezone.utc)
db.commit()
logger.info("[lipsync_tts.persist] 输出视频已转存 OSS: job_id=%s key=%s", job_id, storage_key)
except Exception as exc:
logger.warning(
"[lipsync_tts.persist] 输出视频转存失败,保留临时 URL: job_id=%s err=%s",
job_id,
exc,
)
except Exception:
logger.exception("[lipsync_tts.persist] 未预期异常: job_id=%s", job_id)
finally:
db.close()