# geometry_rag_demo.py → UPGRADE NOW (Copy this)
from scipy.sparse.linalg import eigsh
import numpy as np
import networkx as nx

class AqarionGeometry:
    def spectral_gap_production(self):
        """10K node production scale"""
        if len(self.G.nodes) <= 250:  # A15 fast path
            L = nx.laplacian_matrix(self.G).todense()
            return float(np.sort(np.real(np.linalg.eigvals(L)))[1])
        
        # 🔴 PRODUCTION: Lanczos → 10K nodes
        L_sparse = nx.laplacian_matrix(self.G, format='csr')
        eigenvalues = eigsh(L_sparse, k=3, which='SM', return_eigenvectors=False)
        return float(eigenvalues[1])  # λ₂

# TEST 1K NODES NOW
G = nx.barabasi_albert_graph(1000, 3)  # Real graph
aq = AqarionGeometry()
aq.G = G
print(f"🔥 1K nodes → λ₂={aq.spectral_gap_production():.3f}")