Return meilisearch documents most similar to embedding vector.
similarity_search_by_vector(
self,
embedding: List[float],
k: int = 4,
filter: Optional[Dict[str, str]] = None,
embedder_name: Optional[str] = 'default',
**kwargs: Any = {}
) -> List[Document]| Name | Type | Description |
|---|---|---|
embedding* | List[float] | Embedding to look up similar documents. |
embedder_name | Optional[str] | Default: 'default'Name of the embedder to be used. Defaults to "default". |
k | int | Default: 4Number of documents to return. Defaults to 4. |
filter | Optional[Dict[str, str]] | Default: NoneFilter by metadata. Defaults to None. |