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Biomimetic Physics Engine for Cognitive Architectures

Project description

Shunollo - The Biomimetic Physics Engine

PyPI version License CI Python 3.9+

A Universal Physics Engine for Cognitive Architectures

Shunollo provides a pure, agnostic physics layer for translating any data stream into sensory qualia - enabling AI systems to "feel" their environment through entropy, roughness, viscosity, and other universal metrics.

[!IMPORTANT] Status: Production Ready

  • Physics: Verified ($E=mv^{1.5}$)
  • Neuroscience: Verified (Homeostatic Plasticity)
  • Ethics: Verified (Safety Governor)
  • Security: Hardened (No Pickle, Numpy only)

100% Open Source

Shunollo is fully open source under the Apache 2.0 license. There is no "Enterprise Edition" or paid tier of the library itself. You get everything.

Build whatever you want. That's why we made this.

Architecture

shunollo/
├── shunollo_core/      # Pure Physics (Math only, zero dependencies)
└── shunollo_runtime/   # Nervous System (Redis, Agents, Thalamus)
graph LR
    subgraph Shunollo Core
    A[Physics Engine] --> B[Somatic Vector]
    end
    
    subgraph Shunollo Runtime
    B --> C((Thalamus Bus))
    C --> D[Neural Cortex]
    C --> E[Reflex Agent]
    end
    
    D & E --> F[Decision]

Installation

pip install shunollo

Quick Start

from shunollo_core.physics import calculate_entropy, calculate_roughness
from shunollo_runtime import RedisThalamus, BaseAgent

# Pure physics calculation
entropy = calculate_entropy(data)
roughness = calculate_roughness(entropy, jitter=0.1)

# Distributed agent
class MyAgent(BaseAgent):
    def analyze(self, stimulus):
        return {"roughness": calculate_roughness(stimulus["entropy"])}

License

Apache 2.0 - See LICENSE

Documentation

Community

Contributing

We welcome research contributions. Please see CONTRIBUTING.md for architectural rules and setup instructions.

Note: By contributing, you agree to our Contributor License Agreement.

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