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# Use Ubuntu as the base image
FROM ubuntu:22.04
# Set the working directory in the container
WORKDIR /app
# Install system dependencies and Python
RUN apt-get update && apt-get install -y \
python3 \
python3-pip \
curl \
git \
build-essential \
cmake \
ninja-build \
wget \
&& rm -rf /var/lib/apt/lists/*
# Set Python3 as the default
RUN ln -s /usr/bin/python3 /usr/bin/python
# Copy the requirements file and install dependencies
COPY requirements.txt ./
RUN pip install --no-cache-dir -r requirements.txt
# Install llama.cpp using CMake
RUN git clone https://github.com/ggerganov/llama.cpp.git /app/llama.cpp && \
cd /app/llama.cpp && \
mkdir build && cd build && \
cmake .. -G Ninja && ninja install
# Ensure llama.cpp binaries are in the system path
ENV PATH="/usr/local/bin:$PATH"
# Copy the Llama model into the Docker image
COPY Meta-Llama-3-8B-Instruct.Q4_0.gguf /app/
# Copy the application files
COPY . .
# Expose the FastAPI default port
EXPOSE 8000
# Start llama.cpp server, then start FastAPI
CMD ["sh", "-c", "/usr/local/bin/server -m /app/Meta-Llama-3-8B-Instruct.Q4_0.gguf & sleep 5 && uvicorn main:app --host 0.0.0.0 --port 8000"]
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