Return docs most similar to embedding vector.
similarity_search_by_vector(
self,
embedding: List[float],
k: int = 4,
metadata_keys: Optional[List[str]] = None,
index_name: Optional[str] = None,
**kwargs: Any = {}
) -> List[Document]| Name | Type | Description |
|---|---|---|
embedding* | List[float] | Embedding to look up documents similar to. |
k | int | Default: 4Number of Documents to return. Defaults to 4. |
metadata_keys | Optional[List[str]] | Default: NoneList of metadata keys to return with the documents. If None, all metadata keys will be returned. Defaults to None. |
index_name | Optional[str] | Default: NoneName of the index to search. Overrides the default index_name. |
kwargs | Any | Default: {}Additional keyword arguments to pass to the search method. |