This commit is contained in:
墨梓柒
2025-07-15 15:33:30 +08:00
160 changed files with 8429 additions and 12578 deletions

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@@ -62,7 +62,7 @@ EMBEDDING_SIM_THRESHOLD = 0.99
def cosine_similarity(a, b):
# 计算余弦相似度
dot = sum(x * y for x, y in zip(a, b))
dot = sum(x * y for x, y in zip(a, b, strict=False))
norm_a = math.sqrt(sum(x * x for x in a))
norm_b = math.sqrt(sum(x * x for x in b))
if norm_a == 0 or norm_b == 0:
@@ -288,7 +288,7 @@ class EmbeddingStore:
distances = list(distances.flatten())
result = [
(self.idx2hash[str(int(idx))], float(sim))
for (idx, sim) in zip(indices, distances)
for (idx, sim) in zip(indices, distances, strict=False)
if idx in range(len(self.idx2hash))
]