3620c967b9
Three surgical import changes. No behavior change. No new semantics.
Backend decides Rust vs pure-Python transparently.
- field/propagate.py: versor_apply <- algebra.backend
- vocab/manifold.py: cga_inner <- algebra.backend
- vault/store.py: recall loop replaced with vault_recall() from
algebra.backend; public result shape preserved ({versor, score,
metadata, index}). null_project stays on algebra.cga (not the
recall hot path). store() and reproject() unchanged.
Rust path for vault_recall uses Rayon parallel scan and releases
the GIL. Python fallback is sequential and behaviorally identical.
No batching introduced; that is Commit 3+.
71 lines
2.5 KiB
Python
71 lines
2.5 KiB
Python
"""
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VaultStore — exact memory via CGA inner product scan.
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No HNSW. No approximate nearest neighbor. No index rebuild.
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Recall is exact: argmax_i { cga_inner(query, X_i) } over stored versors.
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Periodic null_project() prevents floating-point null-cone drift in long sessions.
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Hot path: recall() routes through algebra.backend.vault_recall(), which
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dispatches to a Rayon parallel scan (releases GIL) when core_rs is available
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and falls back to a sequential Python scan silently. Public result shape
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is unchanged: list of {versor, score, metadata, index}.
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null_project() remains on algebra.cga — it is not the recall hot path
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and does not benefit from the same batching pattern.
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"""
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import numpy as np
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from algebra.backend import vault_recall
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from algebra.cga import null_project
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class VaultStore:
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def __init__(self, reproject_interval: int = 100):
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self._versors: list = []
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self._metadata: list = []
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self._store_count: int = 0
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self._reproject_interval = reproject_interval
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def store(self, F: np.ndarray, metadata: dict = None) -> int:
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"""Store a versor. Returns its index. Auto-reprojects every N stores."""
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self._versors.append(np.asarray(F, dtype=np.float32).copy())
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self._metadata.append(metadata or {})
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self._store_count += 1
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if self._store_count % self._reproject_interval == 0:
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self.reproject()
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return len(self._versors) - 1
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def recall(self, query: np.ndarray, top_k: int = 5) -> list:
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"""
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Return top_k closest stored versors by CGA inner product.
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Each result: {versor, score, metadata, index}
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Routes through algebra.backend.vault_recall():
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Rust path — Rayon parallel scan, GIL released.
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Python path — sequential, behaviorally identical.
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"""
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if not self._versors:
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return []
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ranked = vault_recall(self._versors, query, top_k)
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return [
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{
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"versor": self._versors[i],
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"score": float(score),
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"metadata": self._metadata[i],
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"index": i,
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}
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for i, score in ranked
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]
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def reproject(self) -> None:
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"""
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Re-project all stored versors onto the null cone.
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Corrects floating-point drift. Run between turns or asynchronously.
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null_project stays on algebra.cga — not the recall hot path.
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"""
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self._versors = [null_project(v) for v in self._versors]
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def __len__(self) -> int:
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return len(self._versors)
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