Vector Encryption API

from mirror_sdk.core.models import VectorData

vector_data = VectorData(
    vector=[1.0, 2.0, 3.0],
    id="vector_1",
    metadata={"source": "user_embedding"}
)

encrypted = sdk.vectax.encrypt(vector_data)

decrypted = sdk.vectax.decrypt(encrypted_vector)

vectors = [
    VectorData(vector=v, id=f"vec_{i}")
    for i, v in enumerate(vectors)
]
encrypted_vectors = sdk.vectax.batch_encrypt(vectors)

# 1. Create vector data
vector = [1.0, 2.0, 3.0, 4.0]
data = VectorData(
    vector=vector,
    id="example_vector",
    metadata={"type": "embedding"}
)

# 2. Encrypt vector
encrypted = sdk.vectax.encrypt(data)

# 3. Store encrypted vector
# (Using ChromaDB as example)
collection.add(
    ids=[data.id],
    embeddings=[encrypted.ciphertext],
    metadatas=[{
        "iv": encrypted.iv,
        "auth_hash": encrypted.auth_hash
    }]
)

# 4. Later: Decrypt vector
decrypted = sdk.vectax.decrypt(encrypted)