README.md

metadata

title: GOD Simulation
emoji: 🕉️
colorFrom: indigo
colorTo: purple
sdk: docker
app_port: 7860
pinned: false
license: mit

GOD — a reincarnation-based social simulation

This is a Python project to simulate a “world engine” where a fixed pool of souls cycles through birth → life → death → rebirth, accumulating karma and experiencing scarce shared resources, social identity, and events.

The goal is not to “simulate everything”, but to build a configurable sandbox where we can run repeatable experiments and visualize emergent outcomes over many generations.

What this application is trying to answer

• Bias experiments: What happens to world stability when the population is biased toward “good nature” vs “bad nature”?
• Scarcity vs abundance: How do shared natural resources shape inequality, wellbeing, cooperation/conflict, and longevity?
• Identity dynamics: How do race/faith/beauty norms influence social networks and opportunity, and how do they compound over rebirth cycles?
• Sustainability Equilibrium: What is the ideal balance of population, resources, and moral bias to ensure world longevity?

Core Features

• Deterministic Simulation: Tick-based engine where every run is reproducible via seed.
• Sustainable Equilibrium Optimizer: An auto-tuning tool that hunts for parameters that maximize world longevity (surviving collapse).
• Run History & AI Comparison: Automatically saves all runs and allows AI to generate comparative insights between two different worlds.
• Local AI Insights: Uses Gemma 2 2b (via llama_cpp or Ollama) to quantitatively interpret simulation results and causal links.

High-level model

• Soul: immutable id; persists across lifetimes; carries karma forward.
• Person: a transient body with traits (moral bias, health, wellbeing).
• Karma: numeric score updated by actions; influences next-life initialization.
• Resources: global pool with replenishment; consumption influenced by moral bias (sharing vs hoarding).
• World Collapse: Simulation ends if resources hit 0, everyone dies, or karma reaches 0.

Running the App

The app is optimized for Hugging Face Spaces using Docker, but can be run locally:

# Run the UI (Streamlit)
uv run streamlit run src/god_sim/app/streamlit_app.py

Local LLM insights

1. Install Ollama and pull Gemma: ollama pull gemma2:2b
2. Run the app and click Generate insights.

Hugging Face Deployment

The app uses llama_cpp with GGUF for fast, serverless insights:

• Provider: llama_cpp
• Model Repo: bartowski/gemma-2-2b-it-GGUF
• Model File: gemma-2-2b-it-Q4_K_M.gguf
• Context Window: 8192 tokens.