Skip to main content
To create an encrypted index, you need to specify an index name (must be unique) and an index key: 
import cyborgdb_core as cyborgdb
import secrets

# Get your API key
api_key = "your_api_key_here"  # Replace with your CyborgDB API key

# Create a client (in-memory backing store for this example)
client = cyborgdb.Client(api_key, cyborgdb.StorageConfig.memory())

# Generate an encryption key for the index
index_key = secrets.token_bytes(32)

# Create an encrypted index
index = client.create_index("my_index", index_key)
This creates a new DiskIVF encrypted index. The vector dimension is auto-detected from the first upsert (or derived from an embedding_model); you can also set it explicitly with the keyword-only dimension parameter. Other optional parameters include metric ("euclidean" default, "cosine", or "squared_euclidean") and storage_precision (float32 default, or float16 to halve the on-disk rerank-vector footprint).
The example above creates a random 32 byte (256-bit) index key. This is fine for evaluation purposes, but for production use, we recommend that you use an HSM or KMS solution. For more details, see Managing Encryption Keys.

​
Automatic Embedding Generation

This feature is only available in Python. To use it, use pip install cyborgdb-core[embeddings]
In the Python version of CyborgDB, you can enable automatic embedding generation for the encrypted index by setting embedding_model in create_index():
Python
import cyborgdb_core as cyborgdb
import secrets

# Get your API key
api_key = "your_api_key_here"  # Replace with your CyborgDB API key

# Create a client (in-memory backing store for this example)
client = cyborgdb.Client(api_key, cyborgdb.StorageConfig.memory())

# Generate an encryption key for the index
index_key = secrets.token_bytes(32)

# Create an encrypted index with managed embedding generation (model from HuggingFace)
index = client.create_index(
    "my_index",
    index_key,
    embedding_model="all-MiniLM-L6-v2"
)

​
API Reference

For more information on creating encrypted indexes, refer to the API reference:

Python API Reference

API reference for create_index() in Python

C++ API Reference

API reference for CreateIndex() in C++