Dockerfile

# 1. Base Image
FROM python:3.11-slim

# 2. Set the working directory
WORKDIR /app

# 3. Install PyTorch FIRST
RUN pip install --no-cache-dir torch torchvision --index-url https://download.pytorch.org/whl/cpu

# 4. Install API dependencies SECOND
RUN pip install --no-cache-dir fastapi uvicorn transformers pillow pydantic requests

# 5. THE FIX: Pre-download the Plant weights AND forcefully load the Google processor
RUN python -c "from transformers import pipeline; pipeline('image-classification', model='linkanjarad/mobilenet_v2_1.0_224-plant-disease-identification', image_processor='google/mobilenet_v2_1.0_224')"

# 6. Copy code and set path
COPY app.py /app/app.py
ENV PYTHONPATH=/app

# 7. Expose port
EXPOSE 7860

# 8. Start the node
CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]