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epicormic

Provider drift detection and containment for pollard-governed AI systems.

Epicormic shoots sprout from dormant buds after a tree is pollarded: growth that reappears after the cut. epicormic watches for model behaviour that reappears, or changes, after a baseline has been pinned.

Status: pre-release, under construction. The 0.0.1 release on PyPI is a name claim: it installs and reports its version and nothing more. The specification is docs/PLAN.md, and the first functional release will be 0.1.0.

What it will do

  • Record repeated observations of a pinned canary panel inside a pollard execution tree, so every observation is content-addressed, budgeted, sealed, and replayable.
  • Reduce each observation to value-free signals through an extensible scorer protocol.
  • Test whether the current window differs from the baseline beyond sampling variance, per probe and pooled, and run anytime-valid sequential change detection across windows.
  • Drive pollard's fail-closed levers from the drift state: a meter that refuses dispatch, a policy that forces confirmation of side-effectful tools, and a gate on unacknowledged execution fingerprint changes.

What it will not do

It does not prevent a provider from changing a model. It observes the consequence, records evidence, and contains the effect.

Installation

python -m pip install epicormic

Development install from a checkout:

python -m pip install -e ".[dev]"

License

MIT.

Metadata

Release files for epicormic 0.0.1

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Source distribution for epicormic 0.0.1
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Total release size: 32.7 kB

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