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Cosine similarity
Given two embedding vectors, return their cosine similarity. Handle a zero vector without producing NaN.
Example
a = [1, 0, 1]
b = [1, 1, 0]
output = 0.5
import numpy as npdef cosine_similarity(a, b): dot = np.dot(a, b) norms = np.linalg.norm(a) * np.linalg.norm(b) if norms == 0: return 0.0 return dot / normsPractice without watching another hour of tutorials.
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