Return docs selected using the maximal marginal relevance.
Maximal marginal relevance optimizes for similarity to query AND diversity among selected documents.
amax_marginal_relevance_search(
self,
query: str,
k: int = 4,
fetch_k: int = 20,
lambda_mult: float = 0.5,
filter: Optional[Dict[str, Any]] = None,
**kwargs: Any = {}
) -> List[Document]| Name | Type | Description |
|---|---|---|
query* | str | Query to look up documents similar to. |
k | int | Default: 4Number of Documents to return. |
fetch_k | int | Default: 20Number of Documents to fetch to pass to MMR algorithm. |
lambda_mult | float | Default: 0.5Number between 0 and 1 that determines the degree of diversity among the results with 0 corresponding to maximum diversity and 1 to minimum diversity. |
filter | Optional[Dict[str, Any]] | Default: NoneFilter on the metadata to apply. |