Dockerfile

FROM python:3.10-slim

WORKDIR /app

# Install system deps (libgl1-mesa-glx removed in Debian Trixie — libglib2.0-0 is all Pillow needs)
RUN apt-get update && apt-get install -y --no-install-recommends \
    libglib2.0-0 \
    && rm -rf /var/lib/apt/lists/*

# Install Python deps — CPU-only torch to keep image lean
COPY requirements.txt .
RUN pip install --no-cache-dir \
    --extra-index-url https://download.pytorch.org/whl/cpu \
    -r requirements.txt

# Pre-cache model weights at build time using huggingface-cli so cold starts
# are near-zero.  Separate RUN layers give per-model Docker cache granularity —
# changing one model default invalidates only that layer.
# HF_HOME is set explicitly so the CLI download and the transformers runtime
# both resolve to the same cache directory.
ENV HF_HOME=/root/.cache/huggingface

RUN huggingface-cli download OwensLab/commfor-model-224
# Pre-cache the timm ViT-S/16 backbone used by Community-Forensics (no pretrained weights needed, just the arch)
RUN python3 -c "import timm; timm.create_model('vit_small_patch16_224.augreg_in21k_ft_in1k', pretrained=False)" 2>/dev/null || true
RUN huggingface-cli download haywoodsloan/ai-image-detector-deploy
RUN huggingface-cli download Ateeqq/ai-vs-human-image-detector
RUN huggingface-cli download dima806/deepfake_vs_real_image_detection
RUN huggingface-cli download umm-maybe/AI-image-detector
RUN huggingface-cli download NYUAD-ComNets/NYUAD_AI-generated_images_detector
RUN python -c "from transformers import pipeline; pipeline('zero-shot-image-classification', model='openai/clip-vit-base-patch32')"

COPY app.py .

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