Class HNSWConfig (0.2.0)

HNSWConfig(
    name: str,
    field_name: typing.Optional[str] = None,
    vector_size: int = 128,
    distance_strategy: langchain_community.vectorstores.utils.DistanceStrategy = DistanceStrategy.COSINE,
    initial_cap: int = 10000,
    m: int = 16,
    ef_construction: int = 200,
    ef_runtime: int = 10,
)

Initializes the HNSWConfig object.

Parameters
Name	Description
`name`	`str` The unique name for the vector index, serving as an identifier within the vector store or database system.
`field_name`	`str` The name of the field in the dataset that holds the vector data to be indexed. This specifies which part of the data structure is used for indexing and searching.
`vector_size`	`int` The dimensionality of the vectors that the index will accommodate. All vectors must match this specified size.
`distance_strategy`	`DistanceStrategy` The metric used for calculating distances or similarities between vectors, influencing how search results are ranked.
`initial_cap`	`int` Specifies the initial capacity of the index in terms of the number of vectors it can hold, impacting the initial memory allocation.
`m`	`int` Determines the maximum number of outgoing edges each node in the index graph can have, directly affecting the graph's connectivity and search performance.
`ef_construction`	`int` Controls the size of the dynamic candidate list during the construction of the index, influencing the index build time and quality.
`ef_runtime`	`int` Sets the size of the dynamic candidate list during search queries, balancing between search speed and accuracy.

Class HNSWConfig (0.2.0)

Parameters