Active-inference metacognitive controller kit for agent runtimes, with Hermes Agent adapter support.
Project description
Dionysus MetaCog
Dionysus MetaCog is an active-inference metacognitive controller kit for agent runtimes.
It provides a public Python package, dionysus-metacognition, with import root
dionysus_metacog. The package is designed to expose metacognitive control
primitives, model provenance, attractor-aware state tracking, and adapter seams
for systems such as Hermes Agent, Autonoesis, Elume, Sakshi, and
linoss-dynamics.
Install
pip install dionysus-metacognition
Import
import dionysus_metacog
from dionysus_metacog.core import MetaCogSignal, PromotionLabel
For local code that wants a shorter alias:
import dionysus_metacog as metacog
Scope
Dionysus MetaCog is not a generic utils package and is not the ontology owner
for phenomenological self-modeling. It is the applied metacognitive controller
layer: the place where active-inference control signals, POMDP-style model
records, Markov blanket boundaries, attractor-aware runtime observations, and
adapter seams can be assembled without polluting host projects.
Autonoesis should remain the self-model and computational-phenomenology kernel. Elume should remain the deterministic replay and competition substrate. Sakshi should remain the witness and verification layer. linoss-dynamics should remain the oscillator dynamics toolkit. Hermes Agent should remain a first-class runtime adapter target, not a hard dependency.
Package Layout
dionysus_metacog/
core/ # controller signals, traces, promotion labels
models/ # active-inference, POMDP, Markov blanket records
attractors/ # attractor-state interfaces
adapters/ # optional integration seams
provenance/ # source attribution and model lineage
Status
This is the initial public package skeleton. The API is intentionally small and typed so that the package name can be claimed cleanly before deeper model extraction lands.
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