Dockerfile

# Use a Python image with uv pre-installed
FROM ghcr.io/astral-sh/uv:python3.12-bookworm-slim

# Install the project into `/app`
WORKDIR /app

# Install system dependencies needed for LightGBM
RUN apt-get update && apt-get install -y libgomp1 && rm -rf /var/lib/apt/lists/*

# Enable bytecode compilation
ENV UV_COMPILE_BYTECODE=1

# Copy from the cache instead of linking since it's a mounted volume
ENV UV_LINK_MODE=copy

# Install the project's dependencies using the lockfile and settings
# RUN --mount=type=cache,target=/root/.cache/uv \
#     --mount=type=bind,source=uv.lock,target=uv.lock \
#     --mount=type=bind,source=pyproject.toml,target=pyproject.toml \
#     uv sync --locked --no-install-project --no-dev

# Then, add the rest of the project source code and install it
# Installing separately from its dependencies allows optimal layer caching
COPY pyproject.toml uv.lock mlflow.db ./
COPY src/ ./src/
COPY mlruns/ ./mlruns/

RUN --mount=type=cache,target=/root/.cache/uv \
    uv sync --locked --no-dev --no-install-project

# Place executables in the environment at the front of the path
ENV PATH="/app/.venv/bin:$PATH"

# Reset the entrypoint, don't invoke `uv`
ENTRYPOINT []

CMD ["uvicorn", "src.app:app", "--host", "0.0.0.0", "--port", "8000"]