index_name

@property
index_name: str
Returns the name of the encrypted index.

Returns

str: The unique name identifier of the index.

Example Usage

index_name = index.index_name
print(f'Index name: {index_name}')
# Output: "my-vectors"

index_type

@property
index_type: str
Returns the type of the index (for example, 'ivf', 'ivfpq', or 'ivfflat').

Returns

str: The index type.

Example Usage

index_type = index.index_type
print(f'Index type: {index_type}')
# Output: "ivf"

if index_type == 'ivfpq':
    print('Using IVFPQ index for memory efficiency')
elif index_type == 'ivfflat':
    print('Using IVFFlat index for high accuracy')

is_trained

def is_trained() -> bool
Returns whether the index has been trained. Training is required for optimal query performance on IVF-based indexes.

Returns

bool: True if the index has been trained, False otherwise.

Example Usage

trained = index.is_trained()
print(f'Index trained: {trained}')

if not trained:
    print('Index needs training for optimal performance')
    index.train()

is_training

def is_training() -> bool
Returns whether the index is currently in the process of training.

Returns

bool: True if the index is currently training, False otherwise.

Example Usage

import time

index.train()  # Start training

while index.is_training():
    print('Index is still training...')
    time.sleep(5)  # Wait before checking again
print('Index training complete')


index_config

@property
index_config: Dict[str, Any]
Returns the index configuration object as a dictionary. The structure depends on the index type.

Returns

Dict[str, Any]: Configuration dictionary containing index parameters.

Example Usage

config = index.index_config
print(f'Index configuration: {config}')

# Access common properties
print(f"Dimension: {config.get('dimension')}")
print(f"Metric: {config.get('metric')}")
print(f"Number of lists: {config.get('n_lists')}")

# Type-specific properties
if config.get('type') == 'ivfpq':
    print(f"PQ dimension: {config.get('pq_dim')}")
    print(f"PQ bits: {config.get('pq_bits')}")

Configuration Properties

Common Properties (All Index Types)

PropertyTypeDescription
typestrIndex type ('ivf', 'ivfflat', or 'ivfpq')
dimensionintVector dimensionality
metricstrDistance metric ('cosine', 'euclidean', etc.)
n_listsintNumber of inverted lists for clustering

IVFPQ-Specific Properties

PropertyTypeDescription
pq_dimintProduct quantization dimension
pq_bitsintNumber of bits for quantization