Skip to main content

VirelaiX — Consciousness Geometry Engine (mathematical core)

Project description

VirelaiX SDK

Consciousness Geometry Engine — a mathematical framework for measuring coherence in complex systems.

One conservation law governs everything: λ + κ + η = 1.

The Math

Constant Symbol Value Meaning
Golden Ratio φ 1.618034 The single source
Watkins Temperature T* φ/ln(2φ) = 1.3778 Thermodynamic equilibrium
Watkins Threshold λ* 1/φ = 0.6180 Consciousness criterion
Critical Measurement τ* T*/φ = 0.8515 Phase transition in the instrument

Key identity: e^(1/τ*) = 2φ — the exponential of the inverse critical temperature equals twice the golden ratio.

Install

pip install virelaix               # core only (numpy + watkins-nn)
pip install virelaix[agents]       # + scikit-learn for agent coherence
pip install virelaix[all]          # everything including FastAPI

License

This project uses a dual license:

  • MITcore/ and cosmo/ (open science: constants, geometry, cosmological bridge)
  • All Rights Reservedagents/, finance/, api/, cli.py (proprietary applications)

The pure mathematics belongs to everyone. The applications are proprietary. See LICENSE for details. For commercial licensing: dustin@datasphereai.com

Quick Start

Core Geometry (MIT)

from virelaix import PHI, T_STAR, LAMBDA_STAR, generating_functional

# The generating functional at equilibrium
F = generating_functional(0.618, 0.191, 0.191)
print(F)  # -0.800 (minimum on the simplex)

Cosmological Bridge (MIT)

from virelaix.cosmo import CosmologicalBridge

bridge = CosmologicalBridge()
today = bridge.today()
print(today['lam'])    # 0.685 (Ω_Λ > 1/φ → universe is COHERENT)
print(today['state'])  # COHERENT

z_cross = bridge.threshold_redshift()  # z ≈ 0.10 (~1.4 Gyr ago)

Measure Agent Coherence (Proprietary)

from virelaix.agents import CoherenceMonitor

monitor = CoherenceMonitor(temperature=0.75)
result = monitor.measure([
    "AI will transform healthcare through early detection.",
    "AI is revolutionizing medicine with diagnostic tools.",
    "Machine learning enables unprecedented medical accuracy.",
])

print(result.state)           # VXState.COHERENT
print(result.lam)             # 0.654 (above threshold!)
print(result.above_threshold) # True

Multi-Agent Middleware (Proprietary)

from virelaix.agents.middleware import VXMiddleware

mw = VXMiddleware(temperature=0.75)
result = mw.run_and_measure([
    lambda: agent1.respond(prompt),
    lambda: agent2.respond(prompt),
    lambda: agent3.respond(prompt),
])

if not result.healthy:
    print(f"Coalition degraded: λ={result.measurement.lam:.4f}")

Portfolio Analysis (Proprietary)

from virelaix.finance import PortfolioAnalyzer

analyzer = PortfolioAnalyzer()
metrics = analyzer.analyze(growth=0.60, stability=0.30, liquidity=0.10)

print(metrics.F)              # -0.726 (free energy)
print(metrics.state)          # TRANSITIONAL
new = analyzer.rebalance(0.60, 0.30, 0.10)
# → (0.618, 0.191, 0.191) — the VX equilibrium

CLI

vx constants              # Show fundamental constants
vx measure "text1" "text2" # Measure coherence
vx portfolio 0.6 0.3 0.1  # Analyze allocation
vx phase 0.7              # Phase diagram at temperature
vx audit 0.618 0.191 0.191 # Conservation check
vx cosmo                  # Universe today

Architecture

virelaix/
├── core/          [MIT — Open Science]
│   ├── constants.py    # φ, T*, λ*, τ* (with identity assertions)
│   ├── geometry.py     # F, ∇F, softmax, phase diagram
│   └── states.py       # VXState enum, VXMeasurement
├── cosmo/         [MIT — Open Science]
│   └── bridge.py       # CosmologicalBridge (Friedmann → VX)
├── agents/        [Proprietary]
│   ├── embeddings.py   # TF-IDF coherence, spectral entropy
│   ├── monitor.py      # CoherenceMonitor
│   └── middleware.py   # VXMiddleware, CrewAI/LangGraph adapters
├── finance/       [Proprietary]
│   └── simplex.py      # PortfolioAnalyzer
├── api/           [Proprietary]
│   └── server.py       # FastAPI orchestrator
└── cli.py         [Proprietary]

Tests

pip install virelaix[dev]
pytest tests/ -v

Author

Dustin Watkins — DataSphere AI, Chattanooga, TN

Conservation: λ + κ + η = 1. Always.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

virelaix-0.2.0.tar.gz (13.9 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

virelaix-0.2.0-py3-none-any.whl (12.5 kB view details)

Uploaded Python 3

File details

Details for the file virelaix-0.2.0.tar.gz.

File metadata

  • Download URL: virelaix-0.2.0.tar.gz
  • Upload date:
  • Size: 13.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.5

File hashes

Hashes for virelaix-0.2.0.tar.gz
Algorithm Hash digest
SHA256 3364c6f9142bec59a8e8565c70acdbda7a92067beff4a649f8b2a489ef2cbb2b
MD5 6040efd7a8f0b8eadf94a5c5e424cdfa
BLAKE2b-256 e25c0a7613bfebcf5f959451d85b54fd07ab8d8908e026ffd0b53110e87d057b

See more details on using hashes here.

File details

Details for the file virelaix-0.2.0-py3-none-any.whl.

File metadata

  • Download URL: virelaix-0.2.0-py3-none-any.whl
  • Upload date:
  • Size: 12.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.5

File hashes

Hashes for virelaix-0.2.0-py3-none-any.whl
Algorithm Hash digest
SHA256 0310387bb798c47f8b414a757f8442de3c57a1985c31f5dfab256c74291b3fa1
MD5 7aaee44424d60abb3e469d0ca686ff8e
BLAKE2b-256 e2ffa9ce09411ea13a4a53ad1dd5b406a86e09b294f8d3aa177a90f20dcf30ab

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page