todo_chatbot / src /Dockerfile
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Deploy FastAPI backend with MCP and OpenAI agents
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# syntax=docker/dockerfile:1
# ----------- Base image (for both build and final) -----------
FROM python:3.13-slim AS base
# ----------- Builder stage: install dependencies and venv -----------
FROM base AS builder
WORKDIR /app
# Install uv (fast Python package manager) from official container
COPY --from=ghcr.io/astral-sh/uv:latest /uv /bin/uv
# Copy dependency files first for better cache utilization
COPY --link pyproject.toml ./
# If you have a lock file, copy it too (but not .env or secrets)
COPY --link ../uv.lock ./uv.lock
# Create virtual environment and install dependencies
ENV UV_CACHE_DIR=/root/.cache/uv
RUN --mount=type=cache,target=$UV_CACHE_DIR \
uv venv .venv && \
uv pip install --system --no-cache --compile -r pyproject.toml
# ----------- Final stage: minimal runtime image -----------
FROM base AS final
WORKDIR /app
# Create non-root user for security
RUN groupadd --gid 1000 appgroup && \
useradd --uid 1000 --gid appgroup --shell /bin/bash --create-home appuser
# Copy virtual environment from builder
COPY --from=builder /app/.venv /app/.venv
# Copy application code (src/ directory and entrypoint)
COPY --link . ./
# Set environment variables
ENV PATH="/app/.venv/bin:$PATH" \
PYTHONUNBUFFERED=1 \
PYTHONDONTWRITEBYTECODE=1 \
PORT=8000
# Switch to non-root user
USER appuser
# Expose port
EXPOSE 8000
# Healthcheck (optional, FastAPI default health endpoint is /health)
HEALTHCHECK --interval=30s --timeout=10s --start-period=5s --retries=3 \
CMD curl -f http://localhost:${PORT:-8000}/health || exit 1
# Start the FastAPI app with uvicorn
CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8000"]