kestrel-feature-parametric-self 0.1.0

Owned parametric self for Kestrel Sovereign agents — a per-agent local model nightly-finetuned on the agent's own experience

kestrel-feature-parametric-self

The agent's owned parametric self for Kestrel Sovereign.

A per-agent local model (target: Gemma 4 31B, 4-bit MLX) that is nightly-finetuned during the sleep cycle on the agent's own experience, and — once proven — consulted in the agent's reasoning loop as a disposition prior and on-demand oracle alongside the frontier model.

Slogan: rent intelligence, own identity. This is the parametric counterpart to reflection's symbolic self-model (the weights, not a trait dict). It is not memory — RAG remains the factual layer.

Design: docs/research/TWO_BRAIN_ARCHITECTURE.md in kestrel-sovereign. Build plan: epic #1.

Status: P0 scaffold. The feature loads and registers; the MLX trainer, reflection-derived corpus, fidelity gate, and in-loop integration land in later phases. The Apple-Silicon trainer is imported lazily, so the package installs and CI-validates on any platform.

Installation

uv pip install kestrel-feature-parametric-self

The package registers ParametricSelfFeature through the kestrel_sovereign.features entry point group.

Development

uv sync --extra test
uv run --extra test pytest