FROM nvidia/cuda:12.9.1-base-ubuntu22.04 RUN apt-get update -y \ && apt-get install -y python3-pip curl \ && curl -LsSf https://astral.sh/uv/install.sh | sh ENV PATH="/root/.local/bin:$PATH" RUN ldconfig /usr/local/cuda-12.9/compat/ # Install vLLM with FlashInfer - use CUDA 12.9 PyTorch wheels RUN uv pip install --system "packaging>=24.2" && \ uv pip install --system "vllm[flashinfer]==0.19.1" --extra-index-url https://download.pytorch.org/whl/cu129 # Install additional Python dependencies (after vLLM to avoid PyTorch version conflicts) COPY builder/requirements.txt /requirements.txt RUN --mount=type=cache,target=/root/.cache/uv \ uv pip install --system -r /requirements.txt # Setup for Option 2: Building the Image with the Model included ARG MODEL_NAME="" ARG TOKENIZER_NAME="" ARG BASE_PATH="/runpod-volume" ARG QUANTIZATION="" ARG MODEL_REVISION="" ARG TOKENIZER_REVISION="" ARG VLLM_NIGHTLY="false" ENV MODEL_NAME=$MODEL_NAME \ MODEL_REVISION=$MODEL_REVISION \ TOKENIZER_NAME=$TOKENIZER_NAME \ TOKENIZER_REVISION=$TOKENIZER_REVISION \ BASE_PATH=$BASE_PATH \ QUANTIZATION=$QUANTIZATION \ HF_DATASETS_CACHE="${BASE_PATH}/huggingface-cache/datasets" \ HUGGINGFACE_HUB_CACHE="${BASE_PATH}/huggingface-cache/hub" \ HF_HOME="${BASE_PATH}/huggingface-cache/hub" \ HF_HUB_ENABLE_HF_TRANSFER=0 \ # Suppress Ray metrics agent warnings (not needed in containerized environments) RAY_METRICS_EXPORT_ENABLED=0 \ RAY_DISABLE_USAGE_STATS=1 \ # Prevent rayon thread pool panic in containers where ulimit -u < nproc # (tokenizers uses Rust's rayon which tries to spawn threads = CPU cores) TOKENIZERS_PARALLELISM=false \ RAYON_NUM_THREADS=4 ENV PYTHONPATH="/:/vllm-workspace" RUN if [ "${VLLM_NIGHTLY}" = "true" ]; then \ uv pip install --system -U vllm --pre --index-url https://pypi.org/simple --extra-index-url https://wheels.vllm.ai/nightly && \ apt-get update && apt-get install -y git && rm -rf /var/lib/apt/lists/* && \ uv pip install --system git+https://github.com/huggingface/transformers.git; \ fi COPY src /src RUN chmod +x /src/start.sh RUN --mount=type=secret,id=HF_TOKEN,required=false \ if [ -f /run/secrets/HF_TOKEN ]; then \ export HF_TOKEN=$(cat /run/secrets/HF_TOKEN); \ fi && \ if [ -n "$MODEL_NAME" ]; then \ python3 /src/download_model.py; \ fi # Start the handler CMD ["/bin/bash", "/src/start.sh"]