Dockerfile

FROM python:3.11-slim

WORKDIR /app

# Install system dependencies
# libgomp1 is needed for some ML libraries
RUN apt-get update && apt-get install -y \
    build-essential \
    curl \
    libgomp1 \
    && rm -rf /var/lib/apt/lists/*

# Install uv for fast package management
COPY --from=ghcr.io/astral-sh/uv:latest /uv /bin/uv

# Copy dependency files
COPY pyproject.toml uv.lock ./

# Install dependencies
# We use --system to install into the system python, avoiding venv complexity in container
RUN uv sync --frozen --no-dev

# Copy application code
COPY . .

# Create directory for ML artifacts
RUN mkdir -p app/models/artifacts

# Expose port
EXPOSE 8000

# Run the application
# We use the python directly from the .venv created by uv sync, or just rely on system path if we used --system
# uv sync creates a .venv by default. Let's use it.
ENV PATH="/app/.venv/bin:$PATH"

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