update docker (#324)

Dockerfile

@@ -7,10 +7,10 @@ ENV LANG=C.UTF-8
 ENV LC_ALL=C.UTF-8
 ENV LD_LIBRARY_PATH=/usr/local/lib/x86_64-linux-gnu:$LD_LIBRARY_PATH
 
-RUN apt-get update && apt-get install -y vim tmux zip unzip wget git build-essential libibverbs-dev ca-certificates \
+RUN apt-get update && apt-get install -y vim tmux zip unzip wget git git-lfs build-essential libibverbs-dev ca-certificates \
     curl iproute2 libsm6 libxext6 kmod ccache libnuma-dev libssl-dev flex bison libgtk-3-dev libpango1.0-dev \
     libsoup2.4-dev libnice-dev libopus-dev libvpx-dev libx264-dev libsrtp2-dev libglib2.0-dev libdrm-dev\
-    && apt-get clean && rm -rf /var/lib/apt/lists/*
+    && apt-get clean && rm -rf /var/lib/apt/lists/* && git lfs install
 
 RUN pip install --no-cache-dir packaging ninja cmake scikit-build-core uv meson ruff pre-commit fastapi uvicorn requests -U
 
@@ -22,9 +22,9 @@ RUN git clone https://github.com/sgl-project/sglang.git && cd sglang/sgl-kernel
     && make build && make clean
 
 RUN pip install --no-cache-dir diffusers transformers tokenizers accelerate safetensors opencv-python numpy imageio \
-    imageio-ffmpeg einops loguru qtorch ftfy easydict
+    imageio-ffmpeg einops loguru qtorch ftfy easydict av
 
-RUN conda install conda-forge::ffmpeg=8.0.0 -y && ln -s /opt/conda/bin/ffmpeg /usr/bin/ffmpeg
+RUN conda install conda-forge::ffmpeg=8.0.0 -y && ln -s /opt/conda/bin/ffmpeg /usr/bin/ffmpeg && conda clean -all -y
 
 RUN git clone https://github.com/Dao-AILab/flash-attention.git --recursive
 
@@ -41,7 +41,10 @@ RUN git clone https://github.com/KONAKONA666/q8_kernels.git
 RUN cd q8_kernels && git submodule init && git submodule update && python setup.py install && rm -rf build
 
 # cloud deploy
-RUN pip install --no-cache-dir aio-pika asyncpg>=0.27.0 aioboto3>=12.0.0 PyJWT alibabacloud_dypnsapi20170525==1.2.2 redis==6.4.0 tos -U
+RUN pip install --no-cache-dir aio-pika asyncpg>=0.27.0 aioboto3>=12.0.0 PyJWT alibabacloud_dypnsapi20170525==1.2.2 redis==6.4.0 tos
+
+RUN curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh -s -- -y --default-toolchain stable
+ENV PATH=/root/.cargo/bin:$PATH
 
 RUN cd /opt \
     && wget https://mirrors.tuna.tsinghua.edu.cn/gnu//libiconv/libiconv-1.15.tar.gz \
@@ -49,10 +52,8 @@ RUN cd /opt \
     && cd libiconv-1.15 \
     && ./configure \
     && make \
-    && make install
-
-RUN curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh -s -- -y --default-toolchain stable
-ENV PATH=/root/.cargo/bin:$PATH
+    && make install \
+    && rm -rf /opt/libiconv-1.15
 
 RUN cd /opt \
     && git clone https://github.com/GStreamer/gstreamer.git -b 1.24.12 --depth 1 \
@@ -60,13 +61,15 @@ RUN cd /opt \
     && meson setup builddir \
     && meson compile -C builddir \
     && meson install -C builddir \
-    && ldconfig
+    && ldconfig \
+    && rm -rf /opt/gstreamer
 
 RUN cd /opt \
     && git clone https://github.com/GStreamer/gst-plugins-rs.git -b gstreamer-1.24.12 --depth 1 \
     && cd gst-plugins-rs \
     && cargo build --package gst-plugin-webrtchttp --release \
-    && install -m 644 target/release/libgstwebrtchttp.so $(pkg-config --variable=pluginsdir gstreamer-1.0)/
+    && install -m 644 target/release/libgstwebrtchttp.so $(pkg-config --variable=pluginsdir gstreamer-1.0)/ \
+    && rm -rf /opt/gst-plugins-rs
 
 RUN ldconfig
 

Dockerfile_deploy

-FROM lightx2v/lightx2v:25091903-cu128 AS base
+FROM lightx2v/lightx2v:25092201-cu128 AS base
 
 RUN mkdir /workspace/LightX2V
 WORKDIR /workspace/LightX2V

docs/EN/source/getting_started/quickstart.md

@@ -27,10 +27,10 @@ We strongly recommend using the Docker environment, which is the simplest and fa
 
 #### 1. Pull Image
 
-Visit LightX2V's [Docker Hub](https://hub.docker.com/r/lightx2v/lightx2v/tags), select a tag with the latest date, such as `25091903-cu128`:
+Visit LightX2V's [Docker Hub](https://hub.docker.com/r/lightx2v/lightx2v/tags), select a tag with the latest date, such as `25092201-cu128`:
 
 ```bash
-docker pull lightx2v/lightx2v:25091903-cu128
+docker pull lightx2v/lightx2v:25092201-cu128
 ```
 
 We recommend using the `cuda128` environment for faster inference speed. If you need to use the `cuda124` environment, you can use image versions with the `-cu124` suffix:
@@ -51,7 +51,7 @@ For mainland China, if the network is unstable when pulling images, you can pull
 
 ```bash
 # cuda128
-docker pull registry.cn-hangzhou.aliyuncs.com/yongyang/lightx2v:25091903-cu128
+docker pull registry.cn-hangzhou.aliyuncs.com/yongyang/lightx2v:25092201-cu128
 
 # cuda124
 docker pull registry.cn-hangzhou.aliyuncs.com/yongyang/lightx2v:25091903-cu124

docs/ZH_CN/source/getting_started/quickstart.md

@@ -27,10 +27,10 @@
 
 #### 1. 拉取镜像
 
-访问 LightX2V 的 [Docker Hub](https://hub.docker.com/r/lightx2v/lightx2v/tags)，选择一个最新日期的 tag，比如 `25091903-cu128`：
+访问 LightX2V 的 [Docker Hub](https://hub.docker.com/r/lightx2v/lightx2v/tags)，选择一个最新日期的 tag，比如 `25092201-cu128`：
 
 ```bash
-docker pull lightx2v/lightx2v:25091903-cu128
+docker pull lightx2v/lightx2v:25092201-cu128
 ```
 
 我们推荐使用`cuda128`环境，以获得更快的推理速度，若需要使用`cuda124`环境，可以使用带`-cu124`后缀的镜像版本：
@@ -51,7 +51,7 @@ docker run --gpus all -itd --ipc=host --name [容器名] -v [挂载设置] --ent
 
 ```bash
 # cuda128
-docker pull registry.cn-hangzhou.aliyuncs.com/yongyang/lightx2v:25091903-cu128
+docker pull registry.cn-hangzhou.aliyuncs.com/yongyang/lightx2v:25092201-cu128
 
 # cuda124
 docker pull registry.cn-hangzhou.aliyuncs.com/yongyang/lightx2v:25091903-cu124