Initial commit

Dockerfile

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+FROM nvidia/cuda:13.0.2-cudnn-devel-ubuntu24.04
+
+# Set non-interactive frontend to prevent apt prompts
+ENV DEBIAN_FRONTEND=noninteractive
+
+# CRITICAL: Allow pip to install globally on Ubuntu 24.04 without a venv
+ENV PIP_BREAK_SYSTEM_PACKAGES=1
+
+# Set the base directory environment variable
+ENV VLLM_BASE_DIR=/workspace/vllm
+
+# 1. Install System Dependencies
+# Added 'git', 'wget', and 'python3-pip' as they are required for the script steps
+RUN apt-get update && apt-get install -y \
+    cmake \
+    build-essential \
+    ninja-build \
+    python3-dev \
+    python3-pip \
+    git \
+    wget \
+    && rm -rf /var/lib/apt/lists/*
+
+# Setup Workspace
+WORKDIR $VLLM_BASE_DIR
+
+# 2. Download Tiktoken files
+RUN mkdir -p tiktoken_encodings && \
+    wget -O tiktoken_encodings/o200k_base.tiktoken "https://openaipublic.blob.core.windows.net/encodings/o200k_base.tiktoken" && \
+    wget -O tiktoken_encodings/cl100k_base.tiktoken "https://openaipublic.blob.core.windows.net/encodings/cl100k_base.tiktoken"
+
+# 3. Set Environment Variables
+# Note: TORCH_CUDA_ARCH_LIST=12.1a is very specific (Hopper/H100 usually).
+# Ensure this matches your target hardware.
+ENV TORCH_CUDA_ARCH_LIST=12.1a
+ENV TRITON_PTXAS_PATH=/usr/local/cuda/bin/ptxas
+ENV TIKTOKEN_ENCODINGS_BASE=$VLLM_BASE_DIR/tiktoken_encodings
+
+# 4. Install Python Dependencies (Using pip instead of uv)
+#RUN python3 -m pip install --upgrade pip
+
+# Install PyTorch for CUDA 13.0
+RUN pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu130
+
+# Install Helper libraries
+RUN pip install xgrammar triton
+
+# Install FlashInfer
+# Note: Using the same index URLs as provided in your script
+RUN pip install flashinfer-python --no-deps --index-url https://flashinfer.ai/whl && \
+    pip install flashinfer-cubin --index-url https://flashinfer.ai/whl && \
+    pip install flashinfer-jit-cache --index-url https://flashinfer.ai/whl/cu130
+
+# Install fast safetensors to improve loading speeds
+RUN pip install fastsafetensors>=0.1.10
+
+# 5. Clone and Build vLLM
+RUN git clone --recursive https://github.com/vllm-project/vllm.git
+WORKDIR $VLLM_BASE_DIR/vllm
+
+# Prepare build requirements
+RUN python3 use_existing_torch.py && \
+    sed -i "/flashinfer/d" requirements/cuda.txt && \
+    pip install -r requirements/build.txt
+
+# Final Build
+# Uses --no-build-isolation to respect the pre-installed Torch/FlashInfer
+# Changed -e (editable) to . (standard install) for better Docker portability
+RUN pip install --no-build-isolation . -v
+
+WORKDIR $VLLM_BASE_DIR
+# Default entrypoint (Optional: starts the server)
+CMD ["/bin/bash"]