Dockerfile

# FLYNNCONCEIVABLE! - The Neural Network That Became a CPU
# 
# Multi-architecture Docker image (amd64, arm64)
# Works on: x86 Linux, Apple Silicon, Raspberry Pi, Jetson, etc.
#
# Build:
#   docker build -t flynnconceivable .
#
# Run:
#   docker run -it flynnconceivable
#
# Or just pull from Docker Hub:
#   docker run -it flynncomm/flynnconceivable
#

FROM python:3.11-slim

# Labels
LABEL org.opencontainers.image.title="FLYNNCONCEIVABLE!"
LABEL org.opencontainers.image.description="The Neural Network That Became a CPU"
LABEL org.opencontainers.image.vendor="FLYNNCOMM, LLC"
LABEL org.opencontainers.image.url="https://flynnconceivable.io"
LABEL org.opencontainers.image.source="https://github.com/flynncomm/flynnconceivable"
LABEL org.opencontainers.image.licenses="MIT"

# Don't buffer Python output (better for Docker logs)
ENV PYTHONUNBUFFERED=1
ENV PYTHONDONTWRITEBYTECODE=1

# Install PyTorch (CPU version - works on all architectures)
# The --index-url ensures we get CPU-only version (smaller, works everywhere)
RUN pip install --no-cache-dir torch --index-url https://download.pytorch.org/whl/cpu

# Install pytest for testing
RUN pip install --no-cache-dir pytest

# Create app directory
WORKDIR /app

# Copy only what we need (see .dockerignore)
COPY . .

# Make scripts executable
RUN chmod +x play setup quickstart test 2>/dev/null || true

# Default command: run the demo
CMD ["python", "-m", "flynnconceivable.demo"]

# Alternative entrypoints:
# Interactive shell:  docker run -it flynnconceivable /bin/bash
# Run tests:          docker run flynnconceivable python -m pytest tests/ -v
# Quick Python:       docker run -it flynnconceivable python