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from test import TestCase
class BasicSimilarity(TestCase):
def getname(self):
return "VSIM reported distance makes sense with 4D vectors"
def test(self):
# Add two very similar vectors, one different
vec1 = [1, 0, 0, 0]
vec2 = [0.99, 0.01, 0, 0]
vec3 = [0.1, 1, -1, 0.5]
# Add vectors using VALUES format
self.redis.execute_command('VADD', self.test_key, 'VALUES', 4,
*[str(x) for x in vec1], f'{self.test_key}:item:1')
self.redis.execute_command('VADD', self.test_key, 'VALUES', 4,
*[str(x) for x in vec2], f'{self.test_key}:item:2')
self.redis.execute_command('VADD', self.test_key, 'VALUES', 4,
*[str(x) for x in vec3], f'{self.test_key}:item:3')
# Query similarity with vec1
result = self.redis.execute_command('VSIM', self.test_key, 'VALUES', 4,
*[str(x) for x in vec1], 'WITHSCORES')
# Convert results to dictionary
results_dict = {}
for i in range(0, len(result), 2):
key = result[i].decode()
score = float(result[i+1])
results_dict[key] = score
# Verify results
assert results_dict[f'{self.test_key}:item:1'] > 0.99, "Self-similarity should be very high"
assert results_dict[f'{self.test_key}:item:2'] > 0.99, "Similar vector should have high similarity"
assert results_dict[f'{self.test_key}:item:3'] < 0.8, "Not very similar vector should have low similarity"
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