数字人生成服务怎么部署
- 环境查看
系统环境
# lsb_release -a
No LSB modules are available.
Distributor ID: Ubuntu
Description: Ubuntu 22.04.5 LTS
Release: 22.04
Codename: jammy
# uname -a
Linux AiServer003187 6.8.0-111-generic #111~22.04.1-Ubuntu SMP PREEMPT_DYNAMIC Tue Apr 14 17:13:45 UTC x86_64 x86_64 x86_64 GNU/Linux
软件环境
# uv --version
uv 0.9.2
# python --version
Python 3.10.18
# nvidia-smi
Wed Jun 24 17:05:13 2026
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 580.159.03 Driver Version: 580.159.03 CUDA Version: 13.0 |
+-----------------------------------------+------------------------+----------------------+
| GPU Name Persistence-M | Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap | Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|=========================================+========================+======================|
| 0 NVIDIA GeForce RTX 4090 Off | 00000000:18:00.0 Off | Off |
| 30% 25C P8 28W / 450W | 10924MiB / 24564MiB | 0% Default |
| | | N/A |
+-----------------------------------------+------------------------+----------------------+
| 1 NVIDIA GeForce RTX 4090 Off | 00000000:3B:00.0 Off | Off |
| 30% 25C P8 23W / 450W | 2109MiB / 24564MiB | 0% Default |
| | | N/A |
+-----------------------------------------+------------------------+----------------------+
| 2 NVIDIA GeForce RTX 4090 Off | 00000000:86:00.0 Off | Off |
| 30% 24C P8 21W / 450W | 18MiB / 24564MiB | 0% Default |
| | | N/A |
+-----------------------------------------+------------------------+----------------------+
+-----------------------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=========================================================================================|
| 0 N/A N/A 3512 G /usr/lib/xorg/Xorg 4MiB |
| 0 N/A N/A 27256 C python 906MiB |
| 0 N/A N/A 42270 C python 444MiB |
| 0 N/A N/A 42271 C python 538MiB |
| 0 N/A N/A 42357 C python 2108MiB |
| 0 N/A N/A 43393 C python 436MiB |
| 0 N/A N/A 43397 C python 538MiB |
| 0 N/A N/A 43520 C python 2098MiB |
| 0 N/A N/A 61464 C python 1916MiB |
| 0 N/A N/A 66625 C python 906MiB |
| 0 N/A N/A 73081 G ...m_detection/.venv/bin/python3 20MiB |
| 0 N/A N/A 101530 C python 902MiB |
| 1 N/A N/A 3512 G /usr/lib/xorg/Xorg 4MiB |
| 1 N/A N/A 73081 C ...m_detection/.venv/bin/python3 2086MiB |
| 2 N/A N/A 3512 G /usr/lib/xorg/Xorg 4MiB |
+-----------------------------------------------------------------------------------------+
- 下载代码
代码目录
未上传gitlab
/home/xiaoxing/data/latentsync-heygem
- 安装
安装redis
apt install redis
# 使用默认配置不添加鉴权
systemctl start redis
systemctl enable redis
安装uv不详述
设置uv虚拟环境
# 在目录之外执行
# uv init latentsync-heygem
使用uv安装python版本
# cd latentsync-heygem
# uv venv --python 3.10.18
激活进入虚拟环境
# source .venv/bin/activate
安装依赖
uv pip install -r requirements.txt
查看安装的所有依赖
uv pip list
Using Python 3.10.18 environment at: /home/xiaoxing/data/latentsync-heygem/.venv
Package Version
------------------------ -----------
absl-py 2.3.1
accelerate 0.26.1
aiofiles 24.1.0
albucore 0.0.24
albumentations 2.0.8
amqp 5.3.1
annotated-types 0.7.0
antlr4-python3-runtime 4.9.3
anyio 4.10.0
appdirs 1.4.4
async-timeout 5.0.1
attrs 25.3.0
audioread 3.0.1
billiard 4.2.1
blinker 1.9.0
celery 5.5.1
certifi 2025.8.3
cffi 2.0.0
charset-normalizer 3.4.3
click 8.2.1
click-didyoumean 0.3.1
click-plugins 1.1.1.2
click-repl 0.3.0
coloredlogs 15.0.1
contourpy 1.3.2
cycler 0.12.1
cython 3.1.3
decorator 4.4.2
decord 0.6.0
diffusers 0.32.2
easydict 1.13
einops 0.7.0
exceptiongroup 1.3.0
face-alignment 1.4.1
fastapi 0.116.1
ffmpeg-python 0.2.0
ffmpy 0.6.1
filelock 3.19.1
flask 3.1.0
flatbuffers 25.2.10
fonttools 4.59.2
fsspec 2025.9.0
future 1.0.0
gradio 5.24.0
gradio-client 1.8.0
groovy 0.1.2
h11 0.16.0
httpcore 1.0.9
httpx 0.28.1
huggingface-hub 0.30.2
humanfriendly 10.0
idna 3.10
imageio 2.31.1
imageio-ffmpeg 0.5.1
importlib-metadata 8.7.0
insightface 0.7.3
itsdangerous 2.2.0
jax 0.6.2
jaxlib 0.6.2
jinja2 3.1.6
joblib 1.5.2
kiwisolver 1.4.9
kombu 5.5.4
kornia 0.8.0
kornia-rs 0.1.9
lazy-loader 0.4
librosa 0.10.1
llvmlite 0.44.0
lpips 0.1.4
markdown-it-py 4.0.0
markupsafe 3.0.2
matplotlib 3.10.6
mdurl 0.1.2
mediapipe 0.10.11
ml-dtypes 0.5.3
moviepy 1.0.3
mpmath 1.3.0
msgpack 1.1.1
networkx 3.4.2
numba 0.61.2
numpy 1.26.4
nvidia-cublas-cu12 12.8.4.1
nvidia-cuda-cupti-cu12 12.8.90
nvidia-cuda-nvrtc-cu12 12.8.93
nvidia-cuda-runtime-cu12 12.8.90
nvidia-cudnn-cu12 9.10.2.21
nvidia-cufft-cu12 11.3.3.83
nvidia-cufile-cu12 1.13.1.3
nvidia-curand-cu12 10.3.9.90
nvidia-cusolver-cu12 11.7.3.90
nvidia-cusparse-cu12 12.5.8.93
nvidia-cusparselt-cu12 0.7.1
nvidia-nccl-cu12 2.27.3
nvidia-nvjitlink-cu12 12.8.93
nvidia-nvtx-cu12 12.8.90
omegaconf 2.3.0
onnx 1.17.0
onnxruntime-gpu 1.21.0
opencv-contrib-python 4.11.0.86
opencv-python 4.9.0.80
opencv-python-headless 4.11.0.86
opt-einsum 3.4.0
orjson 3.11.3
packaging 25.0
pandas 2.3.2
pillow 11.3.0
platformdirs 4.4.0
pooch 1.8.2
prettytable 3.16.0
proglog 0.1.12
prompt-toolkit 3.0.52
protobuf 3.20.3
psutil 7.0.0
pycparser 2.23
pydantic 2.11.7
pydantic-core 2.33.2
pydub 0.25.1
pygments 2.19.2
pyparsing 3.2.3
python-dateutil 2.9.0.post0
python-multipart 0.0.20
python-speech-features 0.6
pytz 2025.2
pyyaml 6.0.2
redis 5.2.1
regex 2025.9.1
requests 2.32.5
rich 14.1.0
ruff 0.13.0
safehttpx 0.1.6
safetensors 0.6.2
scenedetect 0.6.1
scikit-image 0.22.0
scikit-learn 1.7.2
scipy 1.15.3
semantic-version 2.10.0
shellingham 1.5.4
simsimd 6.5.3
six 1.17.0
sniffio 1.3.1
sounddevice 0.5.2
soundfile 0.13.1
soxr 1.0.0
starlette 0.47.3
stringzilla 4.0.7
sympy 1.14.0
threadpoolctl 3.6.0
tifffile 2025.5.10
tokenizers 0.21.4
tomlkit 0.13.3
torch 2.8.0
torchvision 0.23.0
tqdm 4.67.1
transformers 4.48.0
triton 3.4.0
typer 0.17.4
typing-extensions 4.15.0
typing-inspection 0.4.1
tzdata 2025.2
urllib3 2.5.0
uvicorn 0.35.0
vine 5.1.0
wcwidth 0.2.13
websockets 15.0.1
werkzeug 3.1.3
zipp 3.23.0
- 启动
使用tumx启动
# 启动api
tmux new -s latentsync_heygem_api
python api_server.py
# 启动队列
tmux new -s latentsync_heygem_celery
celery -A api_server.celery worker
使用systemctl管理
两个配置文件
api
# cat /usr/lib/systemd/system/latentsync_heygem_api.service
[Unit]
Description=latentsync-heygem-api
After=network.target
[Service]
Type=simple
User=root
# 工作目录
WorkingDirectory=/home/xiaoxing/data/latentsync-heygem
# 启动脚本,使用完整路径
ExecStart=/home/xiaoxing/data/latentsync-heygem/.venv/bin/python /home/xiaoxing/data/latentsync-heygem/api_server.py
Restart=always
RestartSec=5
# 防止 OOM 被 kill
LimitNOFILE=65535
LimitNPROC=65535
# GPU 环境变量（可选但建议加）
Environment="CUDA_VISIBLE_DEVICES=0"
[Install]
WantedBy=multi-user.target
celery
root@AiServer003088:/home/xiaoxing/data/latentsync-heygem# cat /usr/lib/systemd/system/latentsync_heygem_celery.service
[Unit]
Description=latentsync-heygem-celery
After=network.target
[Service]
Type=simple
User=root
# 工作目录
WorkingDirectory=/home/xiaoxing/data/latentsync-heygem
# 启动脚本,使用完整路径
ExecStart=/home/xiaoxing/data/latentsync-heygem/.venv/bin/celery -A api_server.celery worker
Restart=always
RestartSec=5
# 防止 OOM 被 kill
LimitNOFILE=65535
LimitNPROC=65535
# GPU 环境变量（可选但建议加）
Environment="CUDA_VISIBLE_DEVICES=0"
[Install]
WantedBy=multi-user.target
启动
systemctl daemon-reload
systemctl enable latentsync_heygem_api.service
systemctl enable latentsync_heygem_celery.service
systemctl start latentsync_heygem_api.service
systemctl start latentsync_heygem_celery.service
使用podman启动其他服务
安装podman
apt instal podman
pip install podman-compose
下载镜像
podman pull harbor.xiaoxingcloud.com/foundation/docker.io/guiji2025/duix.avatar
docker-compose配置文件
有两个配置文件,都需要启动
# pwd
/home/xiaoxing/data/Duix.Heygem/deploy
# cat docker-compose-linux.yml
networks:
ai_network:
driver: bridge
services:
heygem-gen-video:
image: guiji2025/duix.avatar
container_name: heygem-gen-video
restart: always
#runtime: nvidia
gpus: all
security_opt:
- label=disable
- seccomp=unconfined
volumes:
- /home/xiaoxing/data/latentsync-heygem/heygem_data/face2face:/code/data
environment:
- LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64:/host/usr/lib/nvidia:/host/usr/lib/x86_64-linux-gnu:/usr/local/lib:/usr/lib
- NVIDIA_VISIBLE_DEVICES=0
- PYTORCH_CUDA_ALLOC_CONF=max_split_size_mb:512
devices:
- /dev/nvidia0:/dev/nvidia0
- /dev/nvidiactl:/dev/nvidiactl
- /dev/nvidia-uvm:/dev/nvidia-uvm
- /dev/nvidia-uvm-tools:/dev/nvidia-uvm-tools
shm_size: '8g'
ports:
- '8383:8383'
command: python /code/app_local.py
networks:
- ai_network
# cat docker-compose-linux-v1.yml
networks:
ai_network_v1:
driver: bridge
services:
heygem-gen-video-v1:
image: guiji2025/duix.avatar
container_name: heygem-gen-video-v1
restart: always
#runtime: nvidia
gpus: all
security_opt:
- label=disable
- seccomp=unconfined
volumes:
- /home/xiaoxing/data/latentsync-heygem/heygem_data/face2face:/code/data
environment:
- LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64:/host/usr/lib/nvidia:/host/usr/lib/x86_64-linux-gnu:/usr/local/lib:/usr/lib
- NVIDIA_VISIBLE_DEVICES=1
- PYTORCH_CUDA_ALLOC_CONF=max_split_size_mb:512
devices:
- /dev/nvidia0:/dev/nvidia0
- /dev/nvidiactl:/dev/nvidiactl
- /dev/nvidia-uvm:/dev/nvidia-uvm
- /dev/nvidia-uvm-tools:/dev/nvidia-uvm-tools
shm_size: '8g'
ports:
- '8384:8383'
command: python /code/app_local.py
networks:
- ai_network_v1
启动podman镜像
podman-compose -f docker-compose-linux.yml up -d
podman-compose -f docker-compose-linux-v1.yml up -d
注意:原配置文件启动失败,需要修改以下配置为gpus: all
#runtime: nvidia
gpus: all
把podman设置为开机自启动
两个配置文件
heygem-gen-video
# cat /usr/lib/systemd/system/heygem-gen-video.service
[Unit]
Description=heygem-gen-video
After=network-online.target
Wants=network-online.target
[Service]
Type=oneshot
RemainAfterExit=yes
# 工作目录放置docker-compose.yml配置文件
WorkingDirectory=/home/xiaoxing/data/Duix.Heygem/deploy
ExecStart=/usr/bin/podman-compose -f docker-compose-linux.yml up -d
ExecStop=/usr/bin/podman-compose -f docker-compose-linux.yml down
[Install]
WantedBy=default.target
heygem-gen-video-v1
# cat /usr/lib/systemd/system/heygem-gen-video-v1.service
[Unit]
Description=heygem-gen-video-v1
After=network-online.target
Wants=network-online.target
[Service]
Type=oneshot
RemainAfterExit=yes
# 工作目录放置docker-compose.yml配置文件
WorkingDirectory=/home/xiaoxing/data/Duix.Heygem/deploy
ExecStart=/usr/bin/podman-compose -f docker-compose-linux-v1.yml up -d
ExecStop=/usr/bin/podman-compose -f docker-compose-linux-v1.yml down
[Install]
WantedBy=default.target
启动和设置开机自启动
systemctl daemon-reload
systemctl enable heygem-gen-video
systemctl enable heygem-gen-video-v1
systemctl start heygem-gen-video
systemctl start heygem-gen-video-v1
api默认启动端口为8009,可以修改配置文件api_server.py修改端口
5. 测试
使用curl测试
curl --location --request POST 'http://192.168.8.90:8009/create/video' \
--form 'audio_file=@"/root/test.wav"' \
--form 'avatar_id="d5ab7e81672a4ddf94d93fb1ecf2f663"' \
--form 'audio_url=""' \
--form 'callback_url=""'
传递一个音频文件作为参数,再传递一个avatar_id这个id是在目录的app.log日志文件找到的
查看接口日志
查看队列日志
如配置了域名则使用域名测试
浙公网安备 33010602011771号