Dockerfile

FROM python:3.12.2-slim

ENV PYTHONDONTWRITEBYTECODE=1 \
PYTHONUNBUFFERED=1 \
PIP_NO_CACHE_DIR=1

# build-essential covers the few deps with C extensions (numpy/pandas wheels
# are usually prebuilt for 3.12, but this is cheap insurance).
RUN apt-get update && apt-get install -y --no-install-recommends \
build-essential \
&& rm -rf /var/lib/apt/lists/*

WORKDIR /app

# Deps first so editing app.py doesn't reinstall torch on every rebuild.
COPY requirements.txt .
RUN pip install --extra-index-url https://download.pytorch.org/whl/cpu -r requirements.txt

# Source next.
COPY src/ ./src/
COPY app.py ./

# Weights last — biggest layer, changes least often, so cache stays warm
# when you iterate on app.py.
COPY model/ ./model/

# torch.load on tokenizer.pt unpickles a `Tokenizer` instance that was
# saved from the module path `tokenizer` (src/tokenizer.py). Making /app/src
# importable lets the unpickler find that class.
ENV PYTHONPATH=/app/src

# HF Spaces routes external traffic to $PORT; 7860 is the convention.
# Single worker — the model lives in process memory and multiple workers
# would multiply the ~1.5 GB RSS.
EXPOSE 7860
CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860", "--workers", "1"]