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# Stage 1: Build dependencies and download models
FROM public.ecr.aws/docker/library/python:3.11.9-slim-bookworm AS builder
# Install Lambda web adapter in case you want to run with with an AWS Lamba function URL (not essential if not using Lambda)
#COPY --from=public.ecr.aws/awsguru/aws-lambda-adapter:0.8.3 /lambda-adapter /opt/extensions/lambda-adapter
# Install system dependencies
RUN apt-get update && rm -rf /var/lib/apt/lists/*
# Create directories (if needed for model download script)
RUN mkdir -p /model/rep /model/embed /install
WORKDIR /src
# Copy requirements file and install dependencies. Sentence transformers and Bertopic are installed without dependencies so that torch is not reinstalled.
COPY requirements_aws.txt .
RUN pip install torch==2.4.0+cpu --target=/install --index-url https://download.pytorch.org/whl/cpu \
&& pip install --no-cache-dir --target=/install sentence-transformers==3.0.1 --no-deps \
&& pip install --no-cache-dir --target=/install bertopic==0.16.2 --no-deps \
&& pip install --no-cache-dir --target=/install -r requirements_aws.txt \
&& pip install --no-cache-dir --target=/install gradio==4.44.0
# Add /install to the PYTHONPATH
ENV PYTHONPATH="/install:${PYTHONPATH}"
# Download models (using your download_model.py script)
COPY download_model.py /src/download_model.py
RUN python /src/download_model.py
RUN rm requirements_aws.txt download_model.py
# Stage 2: Final runtime image
FROM public.ecr.aws/docker/library/python:3.11.9-slim-bookworm
# Create a non-root user
RUN useradd -m -u 1000 user
# Copy installed packages from builder stage
COPY --from=builder /install /usr/local/lib/python3.11/site-packages/
# Create necessary directories and set ownership
RUN mkdir -p /home/user/app/output /home/user/.cache/huggingface/hub /home/user/.cache/matplotlib /home/user/app/cache \
&& chown -R user:user /home/user
# Download the quantised phi model directly with curl. Changed at it is so big - not loaded
#RUN curl -L -o /home/user/app/model/rep/Phi-3.1-mini-128k-instruct-Q4_K_M.gguf https://huggingface.co/bartowski/Phi-3.1-mini-128k-instruct-GGUF/tree/main/Phi-3.1-mini-128k-instruct-Q4_K_M.gguf
# Copy models from the builder stage
COPY --from=builder /model/rep /home/user/app/model/rep
COPY --from=builder /model/embed /home/user/app/model/embed
# Switch to the non-root user
USER user
# Set environment variables
ENV HOME=/home/user \
PATH=/home/user/.local/bin:$PATH \
PYTHONPATH=/home/user/app \
PYTHONUNBUFFERED=1 \
PYTHONDONTWRITEBYTECODE=1 \
GRADIO_ALLOW_FLAGGING=never \
GRADIO_NUM_PORTS=1 \
GRADIO_SERVER_NAME=0.0.0.0 \
GRADIO_SERVER_PORT=7860 \
GRADIO_THEME=huggingface \
AWS_STS_REGIONAL_ENDPOINT=regional \
GRADIO_OUTPUT_FOLDER='output/' \
NUMBA_CACHE_DIR=/home/user/app/cache \
SYSTEM=spaces
# Set working directory and copy application code
WORKDIR $HOME/app
COPY --chown=user . $HOME/app
# Command to run your application
CMD ["python", "app.py"] |