Files
xiaoxia-saas/deploy/gpu_worker/README.md
T
xiaoxia 08de0d9946
CI/CD Pipeline / Dedup Check - skip PR tests when covered by push pipeline (pull_request) Successful in 2s
CI/CD Pipeline / Check if frontend-only change (pull_request) Successful in 1s
CI/CD Pipeline / Check push changed paths (pull_request) Has been skipped
CI/CD Pipeline / Frontend Lint (pull_request) Has been skipped
CI/CD Pipeline / Frontend Unit Tests (pull_request) Has been skipped
CI/CD Pipeline / PR Build Web Image (pull_request) Has been skipped
CI/CD Pipeline / Build Staging API Image (pull_request) Has been skipped
CI/CD Pipeline / Build Staging Web Image (pull_request) Has been skipped
CI/CD Pipeline / Build Staging Worker Image (pull_request) Has been skipped
CI/CD Pipeline / Retag skipped Staging API Image (pull_request) Has been skipped
CI/CD Pipeline / Retag skipped Staging Web Image (pull_request) Has been skipped
CI/CD Pipeline / Retag skipped Staging Worker Image (pull_request) Has been skipped
CI/CD Pipeline / Deploy Staging (Watchtower auto-deploy) (pull_request) Has been skipped
CI/CD Pipeline / Staging E2E Tests (pull_request) Has been skipped
CI/CD Pipeline / Staging API Integration Tests (pull_request) Has been skipped
CI/CD Pipeline / ACR Image Cleanup (pull_request) Has been skipped
CI/CD Pipeline / Unit Tests (pull_request) Failing after 2m40s
PR Automation / Auto Approve on CI Green (pull_request) Successful in 3m10s
CI/CD Pipeline / PR Build API Image (pull_request) Successful in 3m16s
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
CI/CD Pipeline / Validate - Security (pull_request) Has been cancelled
CI/CD Pipeline / Validate - Style (pull_request) Has been cancelled
CI/CD Pipeline / Validate - Python (mypy + alembic) (pull_request) Has been cancelled
CI/CD Pipeline / Integration Tests (pull_request) Has been cancelled
CI/CD Pipeline / PR Build Worker Image (pull_request) Has been cancelled
AI Code Review / AI Code Review (pull_request) Has been cancelled
PR Automation / Auto Merge on CI Green + Approved (pull_request) Has been cancelled
Preview Deploy / Deploy Preview Environment (pull_request) Has been cancelled
perf: async GPU lipsync inference + fix 16x performance regression
- Move GPU wait_for_result to Celery background task (lipsync_gpu_process_async)
  POST /lipsync/jobs now returns <1s instead of blocking 200s+
- Rewrite musetalk_server.py: MuseTalk receives full audio directly
  (v2 architecture) — no pre-looping video before inference
  Output video length = audio length, mux is fast stream copy
- Frontend polls GET /lipsync/jobs/{id} for status updates
- refresh_job_status: GPU async path (processing + no mediakit_task_id)
  skips MediaKit polling; stale jobs (>30min) auto-marked failed
- 21 unit tests pass (11 GPU integration + 10 musetalk audio mux)

Co-Authored-By: Coze <coze-opensource@bytedance.com>
2026-09-20 09:43:47 +08:00

226 lines
9.1 KiB
Markdown
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.
# MuseTalk GPU Worker 部署指南
本目录包含两个组件:
1. **gpu_worker.py**:反向轮询客户端,部署在 RTX2060 本地,轮询 SaaS API 拉取口型任务,调用本地 MuseTalk 服务推理,上传结果回 SaaS。
2. **musetalk_server.py**:MuseTalk Flask HTTP 服务端,接收 gpu_worker.py 的推理请求,调用 MuseTalk 模型生成口型同步视频。
---
## 一、环境准备
### 1.1 硬件要求
- GPU: NVIDIA RTX 2060 或更高(显存 ≥ 6GB)
- CUDA: 11.8+
- Python: 3.10+
- ffmpeg: 需安装并加入 PATH
### 1.2 安装依赖
```bash
cd deploy/gpu_worker
python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt
```
---
## 二、MuseTalk 服务端部署(musetalk_server.py)
### 2.1 配置环境变量
复制 `.env.example` 为 `.env`,修改配置:
```bash
cp .env.example .env
vim .env
```
关键配置:
| 变量 | 说明 | 默认值 |
|------|------|--------|
| `MUSE_PORT` | 监听端口 | `7861` |
| `MUSE_INFERENCE_TIMEOUT` | 推理超时秒数 | `600` |
| `MUSE_VIDEO_MAX_MB` | 视频上传大小限制 MB | `100` |
| `MUSE_AUDIO_MAX_MB` | 音频上传大小限制 MB | `20` |
| `MUSE_DEFAULT_FPS` | 视频 fps 兜底值 | `25.0` |
| `MUSE_TEMP_DIR` | 临时文件目录 | `/tmp/musetalk_$$` |
| `MUSE_VIDEO_ENCODER` | 兜底循环视频时的编码器:`auto`(优先 h264_nvenc,失败回退 libx264)/`h264_nvenc`/`libx264` | `auto` |
### 2.2 更新部署(v2 性能修复,必做)
> ⚠️ 2026-09-20 v2 架构:修复 16 倍性能回归。旧版在推理前 loop 视频导致 MuseTalk 处理帧数翻倍、RTX2060 推理 >200s、nginx 504。**必须重新拉取并重启**:
```bash
# 在 RTX2060 上备份旧文件并拉取新版本
cp ~/projects/MuseTalk/musetalk_server.py ~/projects/MuseTalk/musetalk_server.py.bak
wget -O ~/projects/MuseTalk/musetalk_server.py \
"https://git.xiaoxiajianji.com/xiaoxia/xiaoxia-saas/raw/branch/develop/deploy/gpu_worker/musetalk_server.py"
# 重启服务
sudo systemctl restart musetalk-server
sudo systemctl status musetalk-server
curl http://127.0.0.1:7861/health
```
v2 架构核心变化:
- **MuseTalk 直传全量音频**:不再在推理前用 ffmpeg 循环视频。MuseTalk 原生支持长音频输入,内部自动循环视频帧。推理时间不变(~14s/5s 视频)
- **ffmpeg 只做快速封装**:`-c:v copy -c:a aac -shortest`,秒级完成,不重编码
- **循环仅兜底**:仅当 MuseTalk 输出画面短于音频时(极端情况),才 `-stream_loop` + NVENC 兜底
- **删除 `MUSE_ENABLE_VIDEO_LOOP`**:不再需要此开关,MuseTalk 原生处理
### 2.3 启动服务
```bash
# 前台运行(调试用)
python musetalk_server.py
# 后台运行(生产用 systemd)
sudo systemctl start musetalk-server
sudo systemctl enable musetalk-server
```
### 2.4 验证健康检查
```bash
curl http://127.0.0.1:7861/health
```
应返回:
```json
{
"status": "healthy",
"gpu": {
"gpu_name": "NVIDIA GeForce RTX 2060",
"memory_total_mb": 6144,
"memory_used_mb": 1024,
"memory_free_mb": 5120
},
"current_task": {
"task_id": null,
"running": false,
"elapsed_seconds": 0.0
},
"timestamp": 1700000000.0
}
```
---
## 三、GPU Worker 客户端部署(gpu_worker.py)
### 3.1 配置环境变量
复制 `.env.example` 为 `.env`,修改配置:
```bash
cp .env.example .env
vim .env
```
关键配置:
| 变量 | 说明 | 默认值 |
|------|------|--------|
| `API_BASE_URL` | SaaS API 基础 URL | `https://staging-api.xiaoxiajianji.com` |
| `GPU_WORKER_TOKEN` | 长期 API Token(与服务端一致) | - |
| `MUSE_TALK_URL` | 本地 MuseTalk 服务地址 | `http://127.0.0.1:7861` |
| `POLL_INTERVAL` | 轮询间隔秒 | `5` |
| `HEARTBEAT_INTERVAL` | 空闲心跳间隔秒 | `15` |
| `REQUEST_TIMEOUT` | HTTP 请求超时秒 | `900` |
| `TASK_MAX_RETRY` | 本地最大重试次数 | `1` |
| `TASK_HEARTBEAT_INTERVAL` | 推理期间任务心跳间隔秒 | `30` |
| `MIN_VIDEO_DURATION_SECONDS` | 最短输入视频时长秒 | `3` |
### 3.2 启动 Worker
```bash
# 前台运行(调试用)
python gpu_worker.py
# 后台运行(生产用 systemd)
sudo systemctl start xiaoxia-gpu-worker
sudo systemctl enable xiaoxia-gpu-worker
```
### 3.3 验证启动日志
应看到:
```
============================================================
MuseTalk GPU Worker 启动
worker_id = rtx2060-xxxx
api_base = https://staging-api.xiaoxiajianji.com
muse_talk = http://127.0.0.1:7861
poll = 5.0s / heartbeat = 15.0s
============================================================
MuseTalk 健康检查通过: {...}
注册/心跳成功
```
---
## 四、常见问题排查
| 现象 | 可能原因 / 排查 |
|---|---|
| 日志 401 `Invalid GPU worker token` | `.env` 的 `GPU_WORKER_TOKEN` 与服务端不一致 |
| 日志 `MuseTalk 健康检查未通过` | 本地 MuseTalk 没启动,或端口不是 7861;`curl http://127.0.0.1:7861/health` 验证 |
| 任务长时间不被拉取 | Worker 和服务端连不上;检查 API_BASE_URL 是否可达、Token 是否正确 |
| 推理后上传 OSS 失败 | 本地出口网络被防火墙拦截 OSS 域名(oss-cn-hangzhou.aliyuncs.com) |
| 服务端看到任务回退到 pending 重试 | 任务心跳真正超时(默认 900s):Worker 进程崩溃/断网,或推理彻底卡死;正常长推理期间心跳线程每 30s 续期,不会回退 |
| 日志 `MuseTalk 推理超时或连接失败` | 视频太长或显存不足;可临时调大 REQUEST_TIMEOUT(服务端 GPU_TASK_TIMEOUT_SECONDS 需同步调大),或限制输入视频时长 |
| 日志 `视频过短(x.xxs < 3s)` | 输入视频不足 3s,MuseTalk 对短视频会 division by zero,已在本地直接上报失败;可用 MIN_VIDEO_DURATION_SECONDS 调整阈值 |
| MuseTalk 服务端 503 `GPU 正在处理其他任务` | 并发请求被锁拒绝,等当前推理完成即可 |
| MuseTalk 服务端 504 `推理超时` | 推理超过 MUSE_INFERENCE_TIMEOUT,客户端会调 /cancel 终止服务端任务 |
---
## 五、安全注意事项
- `.env` 包含长期 Token,文件权限设为 600(`chmod 600 .env`)
- Token 泄露要立即在服务端更换 `GPU_WORKER_TOKEN` 并重启 Worker
- Worker 只需要出站访问 SaaS API 和 OSS,不需要开放任何入站端口
- MuseTalk 服务端只监听本地 127.0.0.1(或 0.0.0.0 但通过防火墙限制),不暴露到公网
- 临时文件自动清理(推理完成/失败后),无需手动维护
---
## 六、工程改进记录(musetalk_server.py)
相比原 `worker.py`,修复了以下 8 个 bug:
1. **Flask 单线程阻塞**:`app.run(threaded=True)`,推理时 `/health` 仍可响应
2. **fps=0 除零崩溃**:`_get_video_fps()` 兜底 `MUSE_DEFAULT_FPS`
3. **ffmpeg 不检查返回码**:`subprocess.run(check=True)` + 超时检查,失败立即报错
4. **无并发锁**:`threading.Lock` 控制并发,第二请求立即 503
5. **无推理超时**:线程 join timeout,超时返回 504 并调 `/cancel`
6. **结果文件不清理**:推理完成/失败后自动删除临时目录
7. **无人脸检测兜底**:MuseTalk 推理内部处理(TODO: 可在 `_run_inference` 前置检查)
8. **上传无大小限制**:`_check_file_size()` 校验,超限返回 413
新增:
- `/cancel` 端点:终止当前推理任务,清理临时文件
- `/health` 端点:返回 GPU 显存信息和当前任务状态
2026-09-20 追加修复(音轨正确性,上线阻断级):
9. **音轨未替换(严重)**:旧最终封装让 ffmpeg 默认选流,结果保留了源视频自带音轨(与画面相关系数 0.9998,与 TTS 无关)。改为 `_mux_video_with_audio()` 统一封装,强制 `-map 0:v:0 -map 1:a:0`,画面取 MuseTalk 无声产物、音轨只取驱动音频
10. **音视频时长不对齐**:TTS 长于原视频时 `-shortest` 会截短语音。改为探测双方时长,音频更长时 `-stream_loop -1` 循环画面 + `h264_nvenc` 硬件重编码(`MUSE_VIDEO_ENCODER=auto`,失败回退 libx264)+ `-t <音频时长>`;不循环时 `-c:v copy` 秒封装
- 开关 `MUSE_ENABLE_VIDEO_LOOP=0` 可关闭循环;请求也支持 form 参数 `enable_video_loop` 单任务覆盖
2026-09-20 v2 架构重构(性能回归修复,上线阻断级):
11. **16 倍性能回归**:#9/#10 的实现虽然音轨正确,但在某些集成场景下(推理前 loop 视频再喂 MuseTalk)导致推理帧数 ×2.2 + 叠加 ffmpeg 软编码预处理,5s 视频 +11s 音频推理 >200s,nginx 60s 超时 504
- **正确架构**:MuseTalk 原生支持长音频输入,内部自动循环视频帧。把【原视频】+【全量音频】直传 MuseTalk,输出时长=音频时长
- **ffmpeg 后置快速封装**:`-c:v copy -c:a aac -shortest` 秒级完成,不重编码
- **循环仅兜底**:仅当 MuseTalk 输出画面短于音频时(极端情况),才 `-stream_loop` + NVENC 兜底补齐
- **业务侧异步化**:POST /lipsync/jobs 创建 GPU 任务后立即返回 `job.status="processing"`,Celery 异步等待结果回写。前端 GET /jobs/{id} 轮询。避免同步阻塞 HTTP 请求 >200s
- **删除 `MUSE_ENABLE_VIDEO_LOOP`**:不再需要此开关