"""PALIMPSESTE — Un Cortex Hypervectoriel Auto-Référentiel.

A self-referential, append-only, hypervectorial memory substrate where:

  - there is no stored weight matrix ``W`` — the "parameters" are *reconstructed*
    at each instant by associative retrieval from memory;
  - learning is an ``O(1)`` append to an LSH-indexed knowledge base (no gradient,
    no GPU, no retraining epoch);
  - the system is driven by autonomous minimization of its own predictive
    surprise (active inference);
  - the read-back kernel ``Phi`` is itself encoded in a reserved meta-subspace
    ``H_meta`` of the same memory, and may rewrite itself only under a
    Lyapunov (energy-decreasing) constraint.

See ``docs/architecture.md`` and the module docstrings for the full formalism.

Public API:

    from palimseste import HV, random_hv, bind, bundle, similarity
"""

from __future__ import annotations

__version__ = "0.1.0"

# Core primitives re-exported for convenience. Heavy submodules (memory, phi,
# loop) are imported lazily by users to avoid pulling numpy/extra deps at
# package-import time when only primitives are needed.
from .hv import (
    HV,
    DEFAULT_D,
    random_hv,
    constant_hv,
    bind,
    unbind,
    bundle,
    hamming,
    similarity,
    bits_to_signs,
    signs_to_bits,
)

__all__ = [
    "HV",
    "DEFAULT_D",
    "random_hv",
    "constant_hv",
    "bind",
    "unbind",
    "bundle",
    "hamming",
    "similarity",
    "bits_to_signs",
    "signs_to_bits",
    "__version__",
]