Dockerfile

FROM nvidia/cuda:12.1.0-cudnn8-devel-ubuntu22.04
ENV DEBIAN_FRONTEND=noninteractive \
    PATH=/opt/conda/bin:$PATH \
    CUDA_HOME=/usr/local/cuda

# Install system dependencies
RUN apt-get update && apt-get install -y \
    wget git libgl1-mesa-glx libgl1-mesa-dri xvfb ffmpeg build-essential \
    && rm -rf /var/lib/apt/lists/*

# Install Miniconda
RUN wget --quiet https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O /tmp/miniconda.sh && \
    bash /tmp/miniconda.sh -b -p /opt/conda && \
    rm /tmp/miniconda.sh && \
    conda clean -afy

# Configure conda to avoid Anaconda TOS prompt
RUN conda config --remove channels defaults && \
    conda config --add channels conda-forge && \
    conda config --set channel_priority strict

# Create conda environment with Python + ffmpeg from conda-forge
RUN conda create -n appenv python=3.10 ffmpeg=7 -y && conda clean -afy
SHELL ["conda", "run", "-n", "appenv", "/bin/bash", "-c"]

# Copy requirements first for layer caching
WORKDIR /workspace
COPY requirements.txt .

# Install Python dependencies (flash-attn will compile since we have nvcc)
RUN pip install --upgrade pip && pip install --no-cache-dir -r requirements.txt

# Copy remaining code
COPY . .

CMD ["conda", "run", "--no-capture-output", "-n", "appenv", "python", "finetune/app.py"]