Dockerfile

ARG BASE_IMAGE=ghcr.io/meta-pytorch/openenv-base:latest
FROM ${BASE_IMAGE} AS builder

WORKDIR /app

# Ensure git is available (required for installing dependencies from VCS)
RUN apt-get update && \
    apt-get install -y --no-install-recommends git && \
    rm -rf /var/lib/apt/lists/*

# Build argument to control whether we're building standalone or in-repo
ARG BUILD_MODE=in-repo
ARG ENV_NAME=DataDojo

# Copy environment code (always at root of build context)
COPY . /app/env

# For in-repo builds, openenv is already vendored in the build context
# For standalone builds, openenv will be installed via pyproject.toml
WORKDIR /app/env

# Ensure uv is available (for local builds where base image lacks it)
RUN if ! command -v uv >/dev/null 2>&1; then \
        curl -LsSf https://astral.sh/uv/install.sh | sh && \
        mv /root/.local/bin/uv /usr/local/bin/uv && \
        mv /root/.local/bin/uvx /usr/local/bin/uvx; \
    fi

# Install dependencies using uv sync
# If uv.lock exists, use it; otherwise resolve on the fly
RUN --mount=type=cache,target=/root/.cache/uv \
    if [ -f uv.lock ]; then \
        uv sync --frozen --no-install-project --no-editable; \
    else \
        uv sync --no-install-project --no-editable; \
    fi

RUN --mount=type=cache,target=/root/.cache/uv \
    if [ -f uv.lock ]; then \
        uv sync --frozen --no-editable; \
    else \
        uv sync --no-editable; \
    fi

# Final runtime stage
FROM ${BASE_IMAGE}

WORKDIR /app

# Copy the virtual environment from builder
COPY --from=builder /app/env/.venv /app/.venv

# Copy the environment code
COPY --from=builder /app/env /app/env

# Set PATH to use the virtual environment
ENV PATH="/app/.venv/bin:$PATH"

# Set PYTHONPATH so imports work correctly
ENV PYTHONPATH="/app/env:$PYTHONPATH"

# Health check
HEALTHCHECK --interval=30s --timeout=3s --start-period=5s --retries=3 \
    CMD curl -f http://localhost:8000/health || exit 1

# Run the FastAPI server
CMD ["uvicorn", "server.app:app", "--host", "0.0.0.0", "--port", "8000"]