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from test import TestCase, generate_random_vector
import struct
import redis.exceptions
class DimensionValidation(TestCase):
def getname(self):
return "[regression] Dimension Validation with Projection"
def estimated_runtime(self):
return 0.5
def test(self):
# Test scenario 1: Create a set with projection
original_dim = 100
reduced_dim = 50
# Create the initial vector and set with projection
vec1 = generate_random_vector(original_dim)
vec1_bytes = struct.pack(f'{original_dim}f', *vec1)
# Add first vector with projection
result = self.redis.execute_command('VADD', self.test_key,
'REDUCE', reduced_dim,
'FP32', vec1_bytes, f'{self.test_key}:item:1')
assert result == 1, "First VADD with REDUCE should return 1"
# Check VINFO returns the correct projection information
info = self.redis.execute_command('VINFO', self.test_key)
info_map = {k.decode('utf-8'): v for k, v in zip(info[::2], info[1::2])}
assert 'vector-dim' in info_map, "VINFO should contain vector-dim"
assert info_map['vector-dim'] == reduced_dim, f"Expected reduced dimension {reduced_dim}, got {info['vector-dim']}"
assert 'projection-input-dim' in info_map, "VINFO should contain projection-input-dim"
assert info_map['projection-input-dim'] == original_dim, f"Expected original dimension {original_dim}, got {info['projection-input-dim']}"
# Test scenario 2: Try adding a mismatched vector - should fail
wrong_dim = 80
wrong_vec = generate_random_vector(wrong_dim)
wrong_vec_bytes = struct.pack(f'{wrong_dim}f', *wrong_vec)
# This should fail with dimension mismatch error
try:
self.redis.execute_command('VADD', self.test_key,
'REDUCE', reduced_dim,
'FP32', wrong_vec_bytes, f'{self.test_key}:item:2')
assert False, "VADD with wrong dimension should fail"
except redis.exceptions.ResponseError as e:
assert "Input dimension mismatch for projection" in str(e), f"Expected dimension mismatch error, got: {e}"
# Test scenario 3: Add a correctly-sized vector
vec2 = generate_random_vector(original_dim)
vec2_bytes = struct.pack(f'{original_dim}f', *vec2)
# This should succeed
result = self.redis.execute_command('VADD', self.test_key,
'REDUCE', reduced_dim,
'FP32', vec2_bytes, f'{self.test_key}:item:3')
assert result == 1, "VADD with correct dimensions should succeed"
# Check VSIM also validates input dimensions
wrong_query = generate_random_vector(wrong_dim)
try:
self.redis.execute_command('VSIM', self.test_key,
'VALUES', wrong_dim, *[str(x) for x in wrong_query],
'COUNT', 10)
assert False, "VSIM with wrong dimension should fail"
except redis.exceptions.ResponseError as e:
assert "Input dimension mismatch for projection" in str(e), f"Expected dimension mismatch error in VSIM, got: {e}"
class ReduceDimConstraintValidation(TestCase):
def getname(self):
return "[regression] VADD enforces reduce_dim <= dim"
def estimated_runtime(self):
return 0.1
def test(self):
import struct
dim = 16
reduce_dim = dim + 1 # Intentionally larger than dim
# Build a simple FP32 vector of the given dimension.
vec = [0.0] * dim
vec_bytes = struct.pack(f'{dim}f', *vec)
try:
self.redis.execute_command(
'VADD', self.test_key,
'REDUCE', reduce_dim,
'FP32', vec_bytes,
f'{self.test_key}:item:reducemismatch')
assert False, "VADD with reduce_dim > dim should fail"
except redis.exceptions.ResponseError as e:
# Same generic validation error path as other vector spec problems.
assert "invalid vector specification" in str(e), (
f"Expected invalid vector error, got: {e}")