Dockerfile

FROM pytorch/pytorch:2.6.0-cuda12.4-cudnn9-devel

# Create user for HF Spaces (runs as uid 1000)
RUN useradd -m -u 1000 user || true
ENV HOME=/home/user
ENV PATH=/home/user/.local/bin:$PATH

# Set working directory
WORKDIR /app

# Copy requirements and install
# requirements.txt already pins python-docx>=1.1 and hypothesis>=6.100
# which are required by Dataset v2 tooling (document_cutter, PBT tests).
COPY requirements.txt .
RUN pip install --no-cache-dir --upgrade pip && \
    pip install --no-cache-dir -r requirements.txt

# Copy all files (training/* plus scripts/* when the build context is the
# repo root). entrypoint.sh lands at /app/entrypoint.sh.
COPY . .

# Make the dispatch entrypoint executable. The script selects between
# serve / train / train_v2 / filter_dataset_v2 / evaluate based on the
# ENTRYPOINT_MODE environment variable (see training/entrypoint.sh for
# details). Default is "serve" to preserve the existing HF Space
# inference behaviour.
RUN chmod +x /app/entrypoint.sh

# Fix permissions
RUN chown -R 1000:1000 /app /home/user
USER 1000

# Set cache dirs to writable locations
ENV HF_HOME=/home/user/.cache/huggingface
ENV TORCH_HOME=/home/user/.cache/torch

# Default to the inference server. Override by setting
# ENTRYPOINT_MODE=train_v2 (or another supported value) on the HF Space.
CMD ["/app/entrypoint.sh"]