Return docs most similar to embedding vector.
similarity_search_by_vector(
self,
embedding: Optional[List[float]] = None,
k: int = DEFAULT_TOPN,
text_in_page_content: Optional[str] = None,
meta_filter: Optional[dict] = None,
not_include_fields_in_metadata: Optional[Set[str]] = None,
**kwargs: Any = {}
) -> List[Document]| Name | Type | Description |
|---|---|---|
embedding | Optional[List[float]] | Default: NoneEmbedding to look up documents similar to. |
k | int | Default: DEFAULT_TOPNNumber of Documents to return. Defaults to 4. |
text_in_page_content | Optional[str] | Default: NoneFilter by the text in page_content of Document. |
meta_filter | Optional[dict] | Default: NoneFilter by metadata. Defaults to None. |
not_incude_fields_in_metadata* | unknown | Not include meta fields of each document. |