EmbeddingList

An EmbeddingList instance represents a list of vector embeddings. You can use an EmbeddingList instance to build the query vectors in a search against a vector field in an Array of Structs field.

Request Syntax

python

class pymilvus.EmbeddingList

PARAMETERS:

• embeddings (np.ndarray, List[np.ndarray) -

  A list of vector embeddings, which can be either of the following types: np.ndarray with shape (n, dim): , indicating a list of multiple vector embeddings. np.ndarray with shape (dim,): , indicating a single vector embedding. List[np.ndarray], indicating a list of vector embedding arrays:.

• dim (int) -

  The dimensionality of the vector embeddings that are specified in the embedding parameter, for validation purposes. If provided, all specified vector embeddings must adhere to the dimensionality restriction.

• dtype (np.dtype, str, DataType) -

  • np.dtype, such as np.float32, np.float16, or np.unit8.

  • string, such as 'float32', 'float16', or 'uint8'.

  • DataType, such as DataType.FLOAT_VECTOR, DataType.FLOAT16_VECTOR, DataType.BFLOAT16_VECTOR, DataType.INT8_VECTOR, or DataType.BINARY_VECTOR.

RETURN TYPE:

EmbeddingList

RETURNS:

An EmbeddingList instance.

Examples

python

from pymilvus import EmbeddingList

# create an empty embedding list
embeddingList1 = EmbeddingList()

# create an embedding list with a single vector embedding of 5 dimensions
embeddingList2 = EmbeddingList(
    embeddings=[0.1, 0.2, 0.3, 0.4, 0.5],
    dim=5
)

# create an embedding list with two vector embeddings, each having five dimensions
embeddingList3 = EmbeddingList(
    embeddings= [[0.1, 0.2, 0.3, 0.4, 0.5], [0.5, 0.4, 0.3, 0.2, 0.1]],
    dim=5
)