# Hugging Face Space — Docker SDK
# FastAPI latent-diffusion server (DC-AE + distilled TinyCLIP + from-scratch
# UNet) on the Keras TensorFlow CPU backend (graph-compiled UNet), port 7860.

FROM python:3.12-slim

# OpenMP runtime for tensorflow; slim images don't ship it. git is needed to
# pip-install the keras-hub fork from GitHub.
RUN apt-get update && apt-get install -y --no-install-recommends \
        libgomp1 git \
    && rm -rf /var/lib/apt/lists/*

# HF Spaces runs the container as a non-root user with UID 1000.
# Create it so model/tokenizer caches land in a writable home dir.
RUN useradd -m -u 1000 user
USER user
ENV HOME=/home/user \
    PATH=/home/user/.local/bin:$PATH \
    # caches for keras / keras-hub / HF downloads + the Kaggle presets
    KERAS_HOME=/home/user/.keras \
    HF_HOME=/home/user/.cache/huggingface \
    PRESET_CACHE=/home/user/.cache/ldm_presets \
    # Keras runs on the TensorFlow CPU backend (graph-compiled UNet); quiet TF's
    # startup logging.
    KERAS_BACKEND=tensorflow \
    TF_CPP_MIN_LOG_LEVEL=2

WORKDIR $HOME/app

# Install deps first so this layer caches across code changes. TensorFlow (CPU)
# is the compute backend, so no torch wheel is needed.
COPY --chown=user requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt

# App code + sprites + static (gallery images).
COPY --chown=user . .

EXPOSE 7860
CMD ["uvicorn", "server:app", "--host", "0.0.0.0", "--port", "7860"]