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# First stage: build dependencies
FROM public.ecr.aws/docker/library/python:3.11.9-slim-bookworm
# Install Lambda web adapter
COPY --from=public.ecr.aws/awsguru/aws-lambda-adapter:0.8.3 /lambda-adapter /opt/extensions/lambda-adapter
# Install wget, git, curl
RUN apt-get update && \
apt-get install -y wget git curl && \
apt-get clean && rm -rf /var/lib/apt/lists/*
WORKDIR /src
COPY requirements.txt .
# Optimized dependency installation
RUN pip install --no-cache-dir -r requirements.txt && \
pip install --no-cache-dir gradio==4.36.0
# Create a directory for the models and switch to user
RUN mkdir /model && \
useradd -m -u 1000 user && \
chown -R user:user /model
USER user
WORKDIR /home/user
# Download the GGUF model to local model/phi directory:
ENV REPO_ID "QuantFactory/Phi-3-mini-128k-instruct-GGUF"
ENV MODEL_FILE "Phi-3-mini-128k-instruct.Q4_K_M.gguf"
RUN python -c "from huggingface_hub import hf_hub_download; \
hf_hub_download(repo_id='$REPO_ID', filename='$MODEL_FILE', local_dir='/model/phi')"
# Download the transformers-based models
RUN curl -s https://packagecloud.io/install/repositories/github/git-lfs/script.deb.sh | bash && \
apt-get install -y git-lfs && \
git lfs install
RUN git clone https://huggingface.co/stacked-summaries/flan-t5-large-stacked-samsum-1024 /model/stacked_t5 && \
rm -rf /model/stacked_t5/.git && \
git clone https://huggingface.co/pszemraj/long-t5-tglobal-base-16384-book-summary /model/long_t5 && \
rm -rf /model/long_t5/.git
ENV HOME=/home/user \
PATH=/home/user/.local/bin:$PATH \
PYTHONPATH=$HOME/app \
PYTHONUNBUFFERED=1 \
GRADIO_ALLOW_FLAGGING=never \
GRADIO_NUM_PORTS=1 \
GRADIO_SERVER_NAME=0.0.0.0 \
GRADIO_SERVER_PORT=7860 \
GRADIO_THEME=huggingface \
SYSTEM=spaces
# Switch back to root to copy the app files
USER root
WORKDIR /home/user/app
# Copy the current directory contents into the container at $HOME/app setting the owner to the user
COPY --chown=user . $HOME/user/app
# Switch back to the user to run the app
USER user
CMD ["python", "app.py"] |