query. (as a string or a weighted) – 
k (int, optional) – The number of documents to return. Defaults to 4.
Returns
k documents ordered from best to worst match.
Return type
List[Document]
similarity_search_by_vector(embedding: List[float], k: int = 4, **kwargs: Any) → List[Document]¶
Return docs most similar to embedding vector.
Parameters
embedding – Embedding to look up documents similar to.
k – Number of Documents to return. Defaults to 4.
Returns
List of Documents most similar to the query vector.
similarity_search_with_relevance_scores(query: str, k: int = 4, **kwargs: Any) → List[Tuple[Document, float]]¶
Return docs and relevance scores in the range [0, 1].
0 is dissimilar, 1 is most similar.
Parameters
query – input text
k – Number of Documents to return. Defaults to 4.
**kwargs – kwargs to be passed to similarity search. Should include:
score_threshold: Optional, a floating point value between 0 to 1 to
filter the resulting set of retrieved docs
Returns
List of Tuples of (doc, similarity_score)
similarity_search_with_score(query: Union[str, Dict[str, float]], k: int = 4) → List[Tuple[Document, float]][source]¶
Return documents from Marqo that are similar to the query as well
as their scores.
Parameters
query (str) – The query to search with, either as a string or a weighted
query. – 
k (int, optional) – The number of documents to return. Defaults to 4.
Returns
The matching documents and their scores,
ordered by descending score.
Return type
List[Tuple[Document, float]]