Create Index

Creates and returns a new encrypted index based on the provided configuration.

def create_index(self,
                 index_name: str,
                 index_key: bytes,
                 index_config: IndexConfig = None,
                 embedding_model: str = None,
                 metric: str = None,
                 logger: Logger = None)

Parameters

Parameter	Type	Description
index_name	str	Name of the index to create. Must be unique.
index_key	bytes	32-byte encryption key for the index, used to secure the index data.
index_config	IndexConfig	(Optional) Configuration specifying the index type and parameters. When not provided, uses IndexIVFSQ(sq_bits=16) defaults.
embedding_model	str	(Optional) Name of the SentenceTransformer model to use for automatic text embeddings.
metric	str	(Optional) Distance metric to use: “euclidean”, “cosine”, or “squared_euclidean”. Overrides the metric in index_config. Defaults to “euclidean”.
logger	Logger	(Optional) Logger instance for capturing operation logs. Defaults to None.

For more info on auto-generating embeddings, refer to Auto-Generate Embeddings.

Returns

EncryptedIndex: An instance of the newly created encrypted index.

Exceptions

ValueError

• Throws if the index name is not unique.
• Throws if the index configuration is invalid.
• Throws if the index could not be created.

Example Usage

Automatic Setup

import cyborgdb_core as cyborgdb
import secrets

index_location = cyborgdb.DBConfig(location='redis', connection_string="redis://localhost")
config_location = cyborgdb.DBConfig(location='redis', connection_string="redis://localhost")
items_location = cyborgdb.DBConfig(location='postgres', table_name="items", connection_string="host=localhost dbname=postgres")

client = cyborgdb.Client(
    api_key=api_key,
    index_location=index_location, 
    config_location=config_location, 
    items_location=items_location
)

index_name = "my_index"
index_key = secrets.token_bytes(32)  # Generate a secure 32-byte encryption key

# Create with automatic IndexIVFSQ defaults (16-bit scalar quantization)
index = client.create_index(
    index_name=index_name,
    index_key=index_key
)

Explicit Setup

import cyborgdb_core as cyborgdb
import secrets

index_location = cyborgdb.DBConfig(location='redis', connection_string="redis://localhost")
config_location = cyborgdb.DBConfig(location='redis', connection_string="redis://localhost")
items_location = cyborgdb.DBConfig(location='postgres', table_name="items", connection_string="host=localhost dbname=postgres")

client = cyborgdb.Client(
    api_key=api_key, 
    index_location=index_location, 
    config_location=config_location, 
    items_location=items_location
)

index_name = "my_index"
index_key = secrets.token_bytes(32)  # Generate a secure 32-byte encryption key
index_config = cyborgdb.IndexIVF(
    dimension=128  # n_lists will be set automatically during training
)

# Optional: Set up logging
logger = cyborgdb.Logger.instance()
logger.configure(level="info", to_file=True, file_path="index_creation.log")

index = client.create_index(
    index_name=index_name,
    index_key=index_key,
    index_config=index_config,
    metric="cosine",  # Override default metric
    logger=logger
)