docker启动项目环境搭建

app.py

@@ -95,7 +95,7 @@ def txt_to_audio(text_):
                 text_,
                 gspeaker,
                 "zh-cn", #en args.language,
-                "http://localhost:9000", #args.server_url,
+                "http://192.168.1.3:9000", #args.server_url,
                 "20" #args.stream_chunk_size
             ),
             nerfreal

llm/Dockerfile

@@ -0,0 +1,56 @@
+# 使用NVIDIA的CUDA基础镜像
+#FROM nvidia/cuda:11.3.0-cudnn8-runtime-ubuntu18.04
+#FROM m11007322/cuda11.3.0-cudnn8-devel-ubuntu20.04-jupyterlab
+FROM nvidia/cuda:11.3.1-cudnn8-devel-ubuntu20.04
+# 安装Python和pip
+RUN apt-get update && apt-get install -y --no-install-recommends \
+        python3 \
+        python3-pip \
+    && rm -rf /var/lib/apt/lists/*
+
+# 安装Jupyter
+RUN pip3 install --no-cache-dir jupyter
+
+# 安装基础工具
+RUN apt-get update -yq --fix-missing \
+ && DEBIAN_FRONTEND=noninteractive apt-get install -yq --no-install-recommends \
+    pkg-config \
+    wget \
+    cmake \
+    curl \
+    git \
+    vim
+
+# 创建一个新的Conda环境
+RUN apt-get update && apt-get install -y wget \
+    && wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh \
+    && /bin/bash Miniconda3-latest-Linux-x86_64.sh -b -p /opt/conda \
+    && rm Miniconda3-latest-Linux-x86_64.sh \
+    && apt-get remove --purge --auto-remove -y wget \
+    && apt-get clean \
+    && ln -s /opt/conda/bin/conda /usr/bin/conda \
+    && conda update -n base -c defaults conda 
+
+SHELL ["/bin/bash","-ic"]
+# 增加cuda全局变量
+RUN echo "export CUDA_HOME=/usr/local/cuda" >> ~/.bashrc \
+    && echo "export PATH=${CUDA_HOME}/bin:$PATH" >> ~/.bashrc \
+    && echo "export LD_LIBRARY_PATH=${CUDA_HOME}/lib64:$LD_LIBRARY_PATH" >> ~/.bashrc \
+    && source ~/.bashrc
+    
+    #&& echo "nameserver 8.8.8.8" >> /etc/resolv.conf
+
+# 安装cv2依赖，修复libGL.so.1错误
+RUN apt-get update
+RUN apt-get install ffmpeg libsm6 libxext6  -y
+
+# 配置Jupyter
+ENV JUPYTER_ENABLE_LAB=yes
+ENV USER=root
+ENV HOME=/home/$USER
+
+# 设置工作目录
+WORKDIR /root
+
+# 设置启动命令
+CMD ["jupyter", "lab", "--ip='*'", "--port=8888", "--no-browser", "--allow-root"]

llm/Read.me.txt

@@ -0,0 +1,74 @@
+一、cuda11.3容器启动过程
+1、拷贝Dockerfile文件到任意磁盘目录，然后执行下面的命令
+docker build -t nvidia/cuda:11.3.1-cudnn8-devel-ubuntu20.04-jupyter-conda .
+
+docker images
+
+2、启动容器
+打开镜像（常规模式--支持使用GPU）
+docker run -i -t --gpus all nvidia/cuda:11.3.1-cudnn8-devel-ubuntu20.04-jupyter-conda  /bin/bash
+
+
+打开镜像（增强模式--支持使用GPU、映射目录、设置内存）
+docker run -i -t -v /home/liguopu/:/guopu:rw --gpus all --shm-size 16G nvidia/cuda:11.3.1-cudnn8-devel-ubuntu20.04  /bin/bash
+
+测试环境（使用端口映射，把服务映射出去）
+docker run -i -td --name metehuman --gpus -p 8000:8000 all nvidia/cuda:11.3.1-cudnn8-devel-ubuntu20.04-jupyter-conda  /bin/bash
+
+正式使用（8000端口为业务对外的服务端口，根据情况可以自行增加）
+docker run -it --rm -p 8886:8888 -p 8000:8000 --gpus all nvidia/cuda:11.3.1-cudnn8-devel-ubuntu20.04-jupyter-conda
+docker run -itd -p 8886:8888 -p 8000:8000 --gpus all nvidia/cuda:11.3.1-cudnn8-devel-ubuntu20.04-jupyter-conda
+docker run -itd --name metehuman -p 8886:8888 -p 8000:8000 --gpus all nvidia/cuda:11.3.1-cudnn8-devel-ubuntu20.04-jupyter-conda
+
+docker run --gpus '"device=vgpu,id=0"' -it --rm nvidia/cuda:11.0-base nvidia-smi
+
+docker run -itd --name metehuman \
+-p 8885:8888 -p 8001:8000 \
+-e GRANT_SUDO=yes \
+-e JUPYTER_ENABLE_LAB=yes \
+--user root \
+--gpus all \
+nvidia/cuda:11.3.1-cudnn8-devel-ubuntu20.04-jupyter-conda
+
+3、查看token
+token=$(docker exec -it metehuman jupyter server list | grep -oP '(?<=token=)[a-zA-Z0-9]+')
+echo $token
+
+二、启动默认测试镜像
+docker pull m11007322/cuda11.3.0-cudnn8-devel-ubuntu20.04-jupyterlab
+docker run -it \
+    -d \
+    --gpus all \
+    -p 8887:8888 \
+    -p 8001:8000 \
+    --name metehuman2 \
+    --user root \
+    -e NB_USER="ubuntu" \
+    -e CHOWN_HOME=yes \
+    -e GRANT_SUDO=yes \
+    -w "/home/${NB_USER}" \
+    -v "$PWD":"/home/$USER/work" \
+    m11007322/cuda11.3.0-cudnn8-devel-ubuntu20.04-jupyterlab
+
+三、启动jupter镜像测试
+docker run -itd --name test \
+-p 8886:8888 -p 8000:8000 \
+-e GRANT_SUDO=yes \
+-e JUPYTER_ENABLE_LAB=yes \
+--user root \
+--gpus '"device=vgpu,id=0"' \
+nvidia/cuda:11.3.1-cudnn8-devel-ubuntu20.04-jupyter-conda
+
+docker run -it --name test --network=host --dns 8.8.8.8 --dns 8.8.4.4 --rm ubuntu
+docker run -it --gpus all  --network=host --rm  registry.cn-hangzhou.aliyuncs.com/lipku/nerfstream:v1.3
+
+四、查看容器IP
+docker inspect bceda087524e | grep IPAddress
+
+curl https://openai.api2d.net/v1/chat/completions \
+  -H 'Content-Type: application/json' \
+  -H 'Authorization: Bearer fk193752-RlcPi2mBQqPOU5u1F8SFkG2z0gtxD0HS' \
+  -d '{
+  "model": "gpt-3.5-turbo",
+  "messages": [{"role": "user", "content": "你好！给我讲个笑话。"}]
+}'