Hora 0.1，可能是最快的AI搜索算法库

import numpy as np from horapy import HNSWIndex dimension = 50 n = 1000 # init index instance index = HNSWIndex(dimension, "usize") samples = np.float32(np.random.rand(n, dimension)) for i in range( 0, len(samples)): # 添加节点 index.add(np.float32(samples[i]), i) index.build("euclidean") # 构建索引 target = np.random.randint(0, n) # 410 in Hora ANNIndex <HNSWIndexUsize> (dimension: 50, dtype: usize, max_item: 1000000, n_neigh: 32, n_neigh0: 64, ef_build: 20, ef_search: 500, has_deletion: [731, 有邻居: [731] # 65, 36, 631, 83, 111, 254, 990, 161] print("{} in {} 有邻居：{}".format( target, index, index.search(samples[target], 10))) ＃ 搜索