# CUDA + cudnn + PyTorch 2.5.1 (CUDA 12.4)
FROM pytorch/pytorch:2.5.1-cuda12.4-cudnn9-devel

# Sistema y build tools
RUN apt-get update && apt-get install -y --no-install-recommends \
    git openssh-client sshpass build-essential cmake ninja-build kmod curl ca-certificates && \
    rm -rf /var/lib/apt/lists/*

# CUDA env
ENV CUDA_HOME=/usr/local/cuda
ENV PATH=$CUDA_HOME/bin:$PATH
ENV LD_LIBRARY_PATH=/usr/local/cuda/lib64:${LD_LIBRARY_PATH}

# Evitar reinstall de torch/torchvision ya presentes y asegurar numpy
RUN pip install --no-cache-dir -U pip && pip install --no-cache-dir numpy

# Código app
WORKDIR /app
COPY . /app

# Sistema y build tools (añade paquetes de Cairo)
RUN apt-get update && apt-get install -y --no-install-recommends \
    git openssh-client sshpass build-essential cmake ninja-build kmod \
    pkg-config libcairo2-dev python3-dev libffi-dev \
 && rm -rf /var/lib/apt/lists/*

# Instalar el proyecto (usa pyproject del repo)
RUN pip install --no-cache-dir -e .

# Sustituir vLLM oficial por el fork de StarVector
RUN git clone https://github.com/starvector/vllm.git /app/vllm && \
    pip install --no-cache-dir -e /app/vllm

# Crear usuario no root después de instalar dependencias
RUN useradd -m -u 1000 user && chown -R user:user /app
USER user

# Permisos y arranque
RUN chmod +x ./start.sh
CMD ["./start.sh"]