Perform a similarity search against the query string.
similarity_search_by_vector(
self,
embedding: List[float],
k: int = 4,
param: Optional[dict] = None,
expr: Optional[str] = None,
timeout: Optional[float] = None,
**kwargs: Any = {}
) -> List[Document]| Name | Type | Description |
|---|---|---|
embedding* | List[float] | The embedding vector to search. |
k | int | Default: 4How many results to return. Defaults to 4. |
param | dict | Default: NoneThe search params for the index type. Defaults to None. |
expr | str | Default: NoneFiltering expression. Defaults to None. |
timeout | int | Default: NoneHow long to wait before timeout error. Defaults to None. |
kwargs | Any | Default: {}Collection.search() keyword arguments. |