core/README.md

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# CORE-AI: Versor Engine
A cognitive field system built on Cl(4,1) Conformal Geometric Algebra.
**Core invariant:** `||F * reverse(F) - 1||_F < 1e-6` at all times.
All state is a versor. All transitions are versor products.
Coherence is algebraic by construction — not monitored, not corrected.
## Quick Start
```bash
pip install -e ".[dev]"
pytest tests/test_versor_closure.py # must pass before anything else
pytest tests/
```
## Architecture
```
raw input -> ingest/gate.py (normalize once)
-> field/propagate.py (versor_apply every step)
-> generate/stream.py (nearest by cga_inner)
-> vault/store.py (store and recall by cga_inner)
-> persona/motor.py (rigid motor, not weight overlay)
```
## The Two Primitives
- `versor_apply(V, F) = V * F * reverse(V)` — the only field transition
- `cga_inner(X, Y) = -d^2 / 2` — the only distance metric
## Layers
| Layer | Purpose |
|---|---|
| `algebra/` | Cl(4,1) multivector math, versor ops, CGA, holonomy |
| `ingest/` | Single injection gate — the only normalization site |
| `field/` | FieldState dataclass and propagation loop |
| `vocab/` | Word-to-versor manifold, edge rotors |
| `vault/` | Exact CGA inner product memory store |
| `persona/` | Persona as CGA motor (screw motion) |
| `generate/` | Token streaming loop |
| `session/` | Session binding: field + vault + vocab + persona |
## Signature
Cl(4,1): `(+, +, +, +, -)` — conformal model of 3D Euclidean space.
Multivectors: `float32` arrays of shape `(32,)`, ordered by grade.