diff --git a/.dockerignore b/.dockerignore index 1d319f0..ddd8b94 100644 --- a/.dockerignore +++ b/.dockerignore @@ -54,6 +54,4 @@ examples/ assets/ docs/ tests/ -README.md README.docker.md -LICENSE diff --git a/Dockerfile b/Dockerfile index d5d2ef8..9268cdf 100644 --- a/Dockerfile +++ b/Dockerfile @@ -1,5 +1,5 @@ -# Use NVIDIA CUDA base image with Python 3.10 (CUDA 12.8 for RTX 5080) -FROM nvidia/cuda:12.8.0-cudnn-runtime-ubuntu22.04 +# Use NVIDIA CUDA base image with Python 3.12 (CUDA 12.8 for RTX 5080) +FROM nvidia/cuda:12.8.0-base-ubuntu24.04 # Set environment variables ENV DEBIAN_FRONTEND=noninteractive \ @@ -8,27 +8,33 @@ ENV DEBIAN_FRONTEND=noninteractive \ PIP_NO_CACHE_DIR=1 \ CUDA_VISIBLE_DEVICES=0 -# Install Python 3.10 and system dependencies +# Configure apt to use Tsinghua mirror (清华源) +RUN sed -i 's@//archive.ubuntu.com@//mirrors.tuna.tsinghua.edu.cn@g' /etc/apt/sources.list.d/ubuntu.sources && \ + sed -i 's@//security.ubuntu.com@//mirrors.tuna.tsinghua.edu.cn@g' /etc/apt/sources.list.d/ubuntu.sources + +# Install Python and system dependencies (Ubuntu 24.04 uses Python 3.12) RUN apt-get update && apt-get install -y \ - python3.10 \ - python3.10-dev \ + python3 \ python3-pip \ + python3-venv \ git \ libglib2.0-0 \ libsm6 \ libxext6 \ libxrender-dev \ libgomp1 \ - libgl1-mesa-glx \ wget \ && rm -rf /var/lib/apt/lists/* -# Set Python 3.10 as default -RUN update-alternatives --install /usr/bin/python3 python3 /usr/bin/python3.10 1 && \ - update-alternatives --install /usr/bin/python python /usr/bin/python3.10 1 +# Create symlink for python command +RUN ln -sf /usr/bin/python3 /usr/bin/python -# Upgrade pip -RUN python3 -m pip install --upgrade pip setuptools wheel +# Configure pip to use Tsinghua mirror (清华源) and allow system-wide installs +RUN python3 -m pip config set global.index-url https://pypi.tuna.tsinghua.edu.cn/simple && \ + python3 -m pip config set global.break-system-packages true + +# Upgrade pip (ignore system-installed packages) +RUN pip install --upgrade --ignore-installed pip setuptools wheel # Set working directory WORKDIR /app @@ -37,9 +43,12 @@ WORKDIR /app COPY . /app/ # Install PyTorch with CUDA support first (cu124 is compatible with CUDA 12.8) -RUN pip install torch==2.6.0 torchvision==0.21.0 --index-url https://download.pytorch.org/whl/cu124 +# Note: PyTorch uses official mirror as Tsinghua doesn't host CUDA builds +RUN pip install torch torchvision # Install the package and dependencies +# Set version manually since .git is excluded by .dockerignore +ENV SETUPTOOLS_SCM_PRETEND_VERSION=1.0.0 RUN pip install -e . # Install additional dependencies for server @@ -56,5 +65,5 @@ HEALTHCHECK --interval=30s --timeout=10s --start-period=5s --retries=3 \ CMD python3 -c "import requests; requests.get('http://localhost:8001/', timeout=5)" || exit 1 # Default command to start the server (port 8001) -CMD ["texteller", "launch", "server", "-p", "8001"] +CMD ["texteller", "launch", "-p", "8001"] diff --git a/deploy.sh b/deploy.sh index 5e05e4c..2f72476 100755 --- a/deploy.sh +++ b/deploy.sh @@ -59,7 +59,7 @@ check_docker() { # Check if NVIDIA Container Toolkit is installed check_nvidia_docker() { print_info "Checking NVIDIA Container Toolkit..." - if ! docker run --rm --gpus all nvidia/cuda:12.1.0-base-ubuntu22.04 nvidia-smi &> /dev/null; then + if ! docker run --rm --gpus all nvidia/cuda:12.8.0-base-ubuntu24.04 nvidia-smi &> /dev/null; then print_error "NVIDIA Container Toolkit not working properly." print_info "Please install it with:" echo " sudo apt-get install -y nvidia-container-toolkit" @@ -113,8 +113,12 @@ start_container() { --name $CONTAINER_NAME \ --gpus '"device=0"' \ -p $PORT:8001 \ - -v "$MODEL_PATH:/root/.cache/huggingface/hub/models--OleehyO--TexTeller:ro" \ + --shm-size=2g \ + -v "$HOME/.cache/huggingface:/root/.cache/huggingface:ro" \ -e CUDA_VISIBLE_DEVICES=0 \ + -e HF_HOME=/root/.cache/huggingface \ + -e HF_HUB_OFFLINE=1 \ + -e TRANSFORMERS_OFFLINE=1 \ -e RAY_NUM_REPLICAS=1 \ -e RAY_NCPU_PER_REPLICA=4 \ -e RAY_NGPU_PER_REPLICA=1 \