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2a0f699 6ea319c 2a0f699 6ea319c 2a0f699 6ea319c 2a0f699 6ea319c 2a0f699 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 | # 1. Base Image: Use a slim Python image
FROM python:3.10-slim
# 2. Set Environment Variables
# General Python/PIP settings
ENV PYTHONUNBUFFERED=1
ENV PIP_NO_CACHE_DIR=off
ENV PIP_DISABLE_PIP_VERSION_CHECK=on
# Hugging Face cache settings
ENV HF_HOME="/app/huggingface_cache"
ENV TRANSFORMERS_CACHE="/app/huggingface_cache/transformers"
# Optional: For Hugging Face token (if needed for private models, Gemma is public)
# ENV HUGGING_FACE_HUB_TOKEN="your_hf_token_here" # Pass at runtime or via secrets
# 3. Set Working Directory
WORKDIR /app
# 4. Copy requirements file and install dependencies
# This is done before copying the rest of the app to leverage Docker layer caching.
COPY requirements.txt .
RUN apt-get update && apt-get install -y --no-install-recommends \
build-essential \
&& rm -rf /var/lib/apt/lists/*
RUN pip install --no-cache-dir -r requirements.txt
# 5. Copy the rest of the application code
COPY app.py .
# 6. Create the cache directory and set permissions
RUN mkdir -p $HF_HOME && chmod -R 777 $HF_HOME
# Note: chmod 777 is permissive; for production, consider a more specific user/group.
# 7. Expose the port the app runs on
EXPOSE 8000
# 8. Command to run the application
CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "8000"] |