Dockerfile

# Use an official Python runtime with a specific version for stability
FROM python:3.11-slim

# Set environment variables for Hugging Face cache
ENV TRANSFORMERS_CACHE=/app/cache
ENV HF_HOME=/app/cache
ENV XDG_CACHE_HOME=/app/cache
ENV HF_HUB_DISABLE_SYMLINKS_WARNING=1
ENV PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True

# Install system dependencies required for some Python packages
RUN apt-get update && apt-get install -y \
    gcc \
    g++ \
    make \
    && rm -rf /var/lib/apt/lists/*

# Set the working directory
WORKDIR /app

# Create a non-root user first to avoid permission issues
RUN adduser --disabled-password --gecos '' myuser

# --- ADD THIS LINE ---
# Give the new user ownership of the working directory
RUN chown -R myuser:myuser /app

# Create cache directory with proper permissions
RUN mkdir -p /app/cache && chown myuser:myuser /app/cache

# Copy requirements first to leverage Docker cache
COPY --chown=myuser:myuser requirements.txt .

# Install Python dependencies as non-root user
USER myuser
RUN pip install --no-cache-dir --user -r requirements.txt

# Add user's local bin to PATH
ENV PATH="/home/myuser/.local/bin:${PATH}"

# Pre-download models during build to avoid runtime issues
RUN python -c "\
from sentence_transformers import SentenceTransformer; \
SentenceTransformer('sentence-transformers/all-MiniLM-L6-v2'); \
from transformers import AutoModelForSequenceClassification, AutoTokenizer; \
AutoModelForSequenceClassification.from_pretrained('MoritzLaurer/DeBERTa-v3-base-mnli-fever-anli', cache_dir='/app/cache'); \
from transformers import T5Tokenizer, T5ForConditionalGeneration; \
T5ForConditionalGeneration.from_pretrained('google/flan-t5-base', cache_dir='/app/cache'); \
from transformers import pipeline; \
pipeline('image-classification', model='umm-maybe/AI-image-detector'); \
"

# Copy the rest of your application code
COPY --chown=myuser:myuser . .

# Set up environment variable for Google Vision API
ENV GOOGLE_VISION_API=""

# Expose the port the app runs on
EXPOSE 7860

# Run the FastAPI server when the container launches
CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]