Dockerfile_5

# Step 1 — Base image with Python
FROM python:3.10-slim

# Step 2 — Install system dependencies
RUN apt-get update && apt-get install -y \
    git \
    build-essential \
    ninja-build \
    cmake \
    python3-dev \
    gcc-12 \
    g++-12 \
    g++ \
    libnuma-dev \
    && rm -rf /var/lib/apt/lists/*
    
RUN update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-12 10 --slave /usr/bin/g++ g++ /usr/bin/g++-12

# Step 3 — Environment for CPU build
ENV VLLM_TARGET_DEVICE=cpu

# Step 4 — Clone vLLM repo
WORKDIR /workspace
RUN git clone https://github.com/vllm-project/vllm.git

# Step 5 — Install Python build tools
RUN pip install --upgrade pip
RUN pip install cmake>=3.26 wheel packaging ninja "setuptools-scm>=8" numpy
RUN pip install --upgrade pip setuptools wheel packaging setuptools_scm

# Step 6 — Install PyTorch CPU before building vLLM
RUN pip install torch --extra-index-url https://download.pytorch.org/whl/cpu


# Step 7 — Install vLLM requirements for CPU
WORKDIR /workspace/vllm
RUN pip install -r requirements/cpu.txt --extra-index-url https://download.pytorch.org/whl/cpu

# Step 8 — Build and install vLLM from source
RUN python setup.py install

# Step 9 — Expose Hugging Face-friendly port
EXPOSE 7860

# Step 10 — Start API server with a model from HF Hub
CMD ["python", "-m", "vllm.entrypoints.openai.api_server", \
     "--model", "unsloth/Llama-3.2-3B-bnb-4bit", \
     "--host", "0.0.0.0", \
     "--port", "7860", \
     "--trust-remote-code"]