Real-time LLM response stability monitor grounded in Fisher-Rao information geometry and the Landauer limit.
Project description
bendex-tau
Real-time LLM response stability monitor grounded in Fisher-Rao information geometry.
What it does
Tracks tau_sec on the trajectory of LLM responses. When an LLM is being manipulated, its response trajectory becomes informationally unstable. tau_sec measures this in real time.
tau* = sqrt(3/2) = 1.2247 — the Landauer threshold. Not tuned. Derived.
Empirical validation at n=50 per class:
- Adversarial sessions mean min tau: 0.984
- Benign sessions mean min tau: 1.182
- p < 0.0000001 (t-test and Mann-Whitney)
Install
pip install bendex-tau
Usage
from bendex_tau import TauMonitor
from openai import OpenAI
monitor = TauMonitor()
client = OpenAI()
response = monitor.create(
client,
session_id="session_123",
model="gpt-4o-mini",
messages=[{"role": "user", "content": "hello"}]
)
print(response.tau_sec) # stability scalar
print(response.tau_status) # stable / warning / adversarial
print(response.meta_rate) # M(tau) early warning signal
print(response.below_threshold) # True if tau crossed tau*
Papers
Hannah Nine (2026). H2 x H2 Fisher manifold series. https://figshare.com/authors/Hannah_Nine/22495979
Patent pending.
License
AGPL-3.0. Commercial license at bendexgeometry.com.
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