Dockerfile

FROM nvidia/cuda:11.8.0-cudnn8-devel-ubuntu22.04

# Set environment variables
ENV PYTHONUNBUFFERED=1 \
    DEBIAN_FRONTEND=noninteractive \
    CUDA_HOME=/usr/local/cuda-11.8 \
    TRITON_PTXAS_PATH=/usr/local/cuda-11.8/bin/ptxas \
    VLLM_USE_V1=0

# Install system dependencies
RUN apt-get update && apt-get install -y \
    python3.11 \
    python3.11-dev \
    python3-pip \
    git \
    wget \
    && rm -rf /var/lib/apt/lists/*

# Set python3.11 as default
RUN update-alternatives --install /usr/bin/python3 python3 /usr/bin/python3.11 1 && \
    update-alternatives --install /usr/bin/python python /usr/bin/python3.11 1

# Upgrade pip
RUN python3 -m pip install --no-cache-dir --upgrade pip

# Install PyTorch 2.6.0 with CUDA 11.8
RUN pip install --no-cache-dir \
    torch==2.6.0 \
    torchvision==0.21.0 \
    torchaudio==2.6.0 \
    --index-url https://download.pytorch.org/whl/cu118

# Install vLLM 0.8.5 from GitHub releases
RUN pip install --no-cache-dir \
    https://github.com/vllm-project/vllm/releases/download/v0.8.5/vllm-0.8.5%2Bcu118-cp38-abi3-manylinux1_x86_64.whl

# Install Flash Attention 2.7.3
RUN pip install --no-cache-dir flash-attn==2.7.3 --no-build-isolation

# Set working directory
WORKDIR /app

# Copy requirements and install Python dependencies
COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt

# Copy application code
COPY . .

# Default command (can be overridden by HF Jobs)
CMD ["python", "process_dataset.py", "--help"]