FROM python:3.11-slim

ENV HF_HOME=/srv/.hf_cache \
    TRANSFORMERS_CACHE=/srv/.hf_cache \
    HF_HUB_DISABLE_TELEMETRY=1 \
    PIP_NO_CACHE_DIR=1 \
    PYTHONUNBUFFERED=1 \
    OMP_NUM_THREADS=1

# Runtime-Libs für NumPy/SciPy/Sklearn/Torch
RUN apt-get update && apt-get install -y --no-install-recommends \
    libgomp1 libstdc++6 libgfortran5 ca-certificates wget && \
    rm -rf /var/lib/apt/lists/*

WORKDIR /srv

# 1) Pip & feste Numerik/Torch (CPU)
RUN python -m pip install --upgrade pip && \
    pip install --no-cache-dir --index-url https://download.pytorch.org/whl/cpu "torch==2.2.2" && \
    pip install --no-cache-dir "numpy==1.26.4" "scipy==1.11.4" "scikit-learn==1.3.2"

# 2) App-Dependencies (ziehen KEIN numpy-Upgrade mehr)
RUN pip install --no-cache-dir \
    fastapi==0.111.0 \
    uvicorn[standard]==0.30.1 \
    sentence-transformers==3.0.1

# 3) App-Code
COPY ../app/embed_server.py /srv/embed_server.py

# 4) Build-Time-Sanity-Check (bricht Build ab, falls was nicht stimmt)
RUN python - <<'PY'
from sentence_transformers import SentenceTransformer
m = SentenceTransformer("sentence-transformers/all-MiniLM-L6-v2")
e = m.encode(["ping","hallo welt"], normalize_embeddings=False)
assert len(e)==2 and len(e[0])==384, "embedding shape mismatch"
print("Sanity OK: shape", len(e), len(e[0]))
PY

EXPOSE 8990
CMD ["uvicorn", "embed_server:app", "--host", "0.0.0.0", "--port", "8990"]