# Minimal base image - optimized for size and build speed
FROM nvidia/cuda:11.8.0-cudnn8-runtime-ubuntu22.04

ENV DEBIAN_FRONTEND=noninteractive
ENV CUDA_HOME=/usr/local/cuda
ENV PATH=${CUDA_HOME}/bin:${PATH}
ENV LD_LIBRARY_PATH=${CUDA_HOME}/lib64:${LD_LIBRARY_PATH}

# Only build for T4 (7.5) and A100 (8.0) - HuggingFace hardware
ENV TORCH_CUDA_ARCH_LIST="7.5;8.0"

# Install minimal runtime dependencies
# Remove problematic CUDA repo and install packages
RUN rm -f /etc/apt/sources.list.d/cuda*.list /etc/apt/sources.list.d/*.list && \
    apt-get update && apt-get install -y --no-install-recommends --allow-unauthenticated \
    ca-certificates \
    && apt-get clean && rm -rf /var/lib/apt/lists/* && \
    apt-get update && apt-get install -y --no-install-recommends \
    python3.10 \
    python3-pip \
    git \
    libgl1 \
    libglib2.0-0 \
    libgomp1 \
    && rm -rf /var/lib/apt/lists/* \
    && apt-get clean

# Set python as default
RUN update-alternatives --install /usr/bin/python3 python3 /usr/bin/python3.10 1 && \
    update-alternatives --install /usr/bin/python python /usr/bin/python3.10 1

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

WORKDIR /app

# Install PyTorch (smallest CUDA 11.8 build)
RUN pip install --no-cache-dir torch==2.1.0 torchvision==0.16.0 --index-url https://download.pytorch.org/whl/cu118

# Copy and install only essential requirements
COPY requirements.txt .
RUN pip install --no-cache-dir \
    gradio>=4.0.0 \
    numpy>=1.24.0 \
    opencv-python-headless>=4.8.0 \
    Pillow>=10.0.0 \
    huggingface-hub>=0.20.0 \
    && pip cache purge

# Clone FoundationPose (but don't build yet - that's done in final stage)
RUN git clone --depth 1 https://github.com/NVlabs/FoundationPose.git /app/FoundationPose && \
    cd /app/FoundationPose/bundlesdf/mycuda && \
    sed -i 's/-std=c++14/-std=c++17/g' setup.py

# Copy application files
COPY app.py client.py estimator.py ./

# Create weights directory
RUN mkdir -p weights

EXPOSE 7860