Dockerfile

# ── GLM-OCR — Dockerfile (Hugging Face Spaces) ────────────────────────────
#
# HF Spaces builds this automatically when you push to your Space repo.
# No local Docker needed — HF handles the build and hosting.
# ──────────────────────────────────────────────────────────────────────────

# Use plain Python slim — no CUDA needed on the free CPU tier,
# and it avoids the old PyTorch 2.2 in the pytorch/pytorch base image
# (GLM-OCR's transformers requires PyTorch >= 2.4).
FROM python:3.11-slim

# ── System deps ────────────────────────────────────────────────────────────
RUN apt-get update && apt-get install -y --no-install-recommends \
    libgl1 \
    libglib2.0-0 \
    curl \
 && rm -rf /var/lib/apt/lists/*

# ── Workdir ────────────────────────────────────────────────────────────────
WORKDIR /app

# ── Install CPU PyTorch first (must come before requirements.txt so pip
#    doesn't pull the CUDA build from PyPI and stays on >=2.4) ─────────────
RUN pip install --no-cache-dir \
    "torch>=2.4.0" \
    "torchvision>=0.19.0" \
    --index-url https://download.pytorch.org/whl/cpu

# ── Install remaining dependencies ─────────────────────────────────────────
# pip will see torch/torchvision already satisfy their constraints and skip them
COPY requirements.txt ./
RUN pip install --no-cache-dir -r requirements.txt

# ── Copy source (flat structure) ───────────────────────────────────────────
COPY main.py ocr_engine.py ./
COPY frontend/ ./frontend/

# ── Expose & run (HF Spaces requires port 7860) ────────────────────────────
EXPOSE 7860
CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "7860"]