Dockerfile

# infra/hf_spaces/embedder/Dockerfile
# Bakes BAAI/bge-small-en-v1.5 weights into the image at build time.
# Cold start: ~5s (weights load from disk, not downloaded). No startup surprises.

FROM python:3.11-slim

WORKDIR /app

# HF_HOME must be set before the RUN python cache step so the model
# is written to /app/model_cache, which becomes part of this layer.
ENV HF_HOME=/app/model_cache \
    PYTHONDONTWRITEBYTECODE=1 \
    PYTHONUNBUFFERED=1

RUN pip install --no-cache-dir \
    fastapi>=0.115.0 \
    uvicorn[standard]>=0.29.0 \
    sentence-transformers>=3.0.0 \
    numpy>=1.26.0

# Download and cache model weights during build — never at runtime.
# This is the key step that makes cold starts fast on HF Spaces.
RUN python -c "\
from sentence_transformers import SentenceTransformer; \
SentenceTransformer('BAAI/bge-small-en-v1.5', cache_folder='/app/model_cache')"

COPY app.py .

EXPOSE 7860

CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860", "--workers", "1"]