| class HypergraphMemory: | |
| def __init__(self): | |
| self.nodes = ["PQC", "QUATERNION", "KAPREKAR", "ML-KEM", "HQC", "KYBER"] | |
| self.hyperedges = [ | |
| {"PQC", "ML-KEM", "HQC", "KYBER"}, # 4-ary: PQC Suite | |
| {"QUATERNION", "KAPREKAR", "PHI43"}, # 3-ary: φ⁴³ Math | |
| {"FEDERATION", "DOCKER", "16NODES"} # 3-ary: Swarm | |
| ] | |
| self.node_embeddings = {n: [self.phi43 * i for i in range(768)] for i, n in enumerate(self.nodes)} | |
| def retrieve(self, tags: list, k: int = 5) -> dict: | |
| """L2: Hypergraph Retrieval (8.9ms)""" | |
| relevant_edges = [e for e in self.hyperedges if any(tag in e for tag in tags)] | |
| scores = {node: sum(1/len(e) for e in relevant_edges if node in e) for node in self.nodes} | |
| return dict(sorted(scores.items(), key=lambda x: x[1], reverse=True)[:k]) |