Class VectorIndexConfig (0.2.0)

VectorIndexConfig(
    name: str,
    field_name: str,
    type: str,
    distance_strategy: langchain_community.vectorstores.utils.DistanceStrategy,
    vector_size: int,
    data_type: str = "FLOAT32",
)

Initializes the VectorIndexConfig object.

Parameters
Name	Description
`name`	`str` The unique name for the vector index. This name is used to identify and reference the index within the vector storage system.
`field_name`	`str` The name of the field in the data structure that contains the vector data to be indexed. This specifies the target data for indexing.
`type`	`str` The type of vector index. This parameter determines the indexing algorithm or structure to be used (e.g., "FLAT", "HNSW").
`distance_strategy`	`DistanceStrategy` Enum specifying the metric used to calculate the distance or similarity between vectors. Supported strategies include COSINE, EUCLIDEAN_DISTANCE (L2), and MAX_INNER_PRODUCT (IP), influencing how search results are ranked and returned.
`vector_size`	`int` The dimensionality of the vectors that will be stored and indexed. All vectors must conform to this specified size.
`data_type`	`str, optional` The data type of the vector elements (e.g., "FLOAT32"). This specifies the precision and format of the vector data, affecting storage requirements and possibly search performance.

Class VectorIndexConfig (0.2.0)

Parameters