ML Research MCP

# Reference: https://github.com/astral-sh/uv-docker-example/blob/main/multistage.Dockerfile # Development version with UV tools and development dependencies included # Use UV image directly for development environment FROM ghcr.io/astral-sh/uv:python3.12-bookworm-slim # Set environment variables for UV ENV UV_COMPILE_BYTECODE=1 UV_LINK_MODE=copy ENV UV_PYTHON_DOWNLOADS=0 # ホストのユーザー名、ユーザーID、グループIDをビルド引数として受け取る ARG USERNAME=appuser ARG USER_ID=1000 ARG GROUP_ID=1000 # ユーザーとグループを指定されたIDで作成 RUN groupadd -g ${GROUP_ID} ${USERNAME} && \ useradd -u ${USER_ID} -g ${USERNAME} -s /bin/bash -m ${USERNAME} # Allow user to run SSH daemon without password RUN apt-get update && apt-get install -y sudo openssh-server && \ mkdir -p /run/sshd && \ sed -i 's/#PermitRootLogin prohibit-password/PermitRootLogin no/' /etc/ssh/sshd_config && \ sed -i 's/#PasswordAuthentication yes/PasswordAuthentication no/' /etc/ssh/sshd_config && \ echo "Port 2222" >> /etc/ssh/sshd_config && \ mkdir -p /etc/sudoers.d && \ echo "$USERNAME ALL=(ALL) NOPASSWD: ALL" > /etc/sudoers.d/nopasswd && \ chmod 0440 /etc/sudoers.d/nopasswd # Create cache directory with proper permissions for UV RUN mkdir -p /home/$USERNAME/.cache/uv && chown -R $USERNAME:$USERNAME /home/$USERNAME # Install additional development tools RUN apt-get update && apt-get install -y --no-install-recommends \ git \ curl \ procps \ vim \ openssh-server \ sudo \ && mkdir -p /run/sshd \ && rm -rf /var/lib/apt/lists/* WORKDIR /app # Copy the entire project for development COPY . /app # Give user ownership of virtual environment directory and project files RUN mkdir -p /app/.venv && chown -R $USERNAME:$USERNAME /app/.venv \ && chown -R $USERNAME:$USERNAME /app # Install dependencies including development dependencies RUN --mount=type=cache,target=/root/.cache/uv \ uv sync # Place executables in the environment at the front of the path ENV PATH="/app/.venv/bin:$PATH" # Set UV cache path for the user ENV UV_CACHE_DIR="/home/$USERNAME/.cache/uv" # Use non-root user for better security USER $USERNAME # No ENTRYPOINT or CMD for maximum flexibility # To run in development with code mounting: # docker run -v $(pwd):/app -p 8000:8000 ml-research-mcp-dev python -m ml_research_mcp.main # or for live reload with something like uvicorn: # docker run -v $(pwd):/app -p 8000:8000 ml-research-mcp-dev uvicorn ml_research_mcp.app:app --reload --host 0.0.0.0