metadata_field: Document field that metadata is stored in. Defaults to
“metadata”.
Can be set to a special value “*” to include the entire document.
Optional Args for Approximate Search:search_type: “approximate_search”; default: “approximate_search”
boolean_filter: A Boolean filter consists of a Boolean query that
contains a k-NN query and a filter.
subquery_clause: Query clause on the knn vector field; default: “must”
lucene_filter: the Lucene algorithm decides whether to perform an exact
k-NN search with pre-filtering or an approximate search with modified
post-filtering.
Optional Args for Script Scoring Search:search_type: “script_scoring”; default: “approximate_search”
space_type: “l2”, “l1”, “linf”, “cosinesimil”, “innerproduct”,
“hammingbit”; default: “l2”
pre_filter: script_score query to pre-filter documents before identifying
nearest neighbors; default: {“match_all”: {}}
Optional Args for Painless Scripting Search:search_type: “painless_scripting”; default: “approximate_search”
space_type: “l2Squared”, “l1Norm”, “cosineSimilarity”; default: “l2Squared”
pre_filter: script_score query to pre-filter documents before identifying
nearest neighbors; default: {“match_all”: {}}
similarity_search_with_score(query: str, k: int = 4, **kwargs: Any) → List[Tuple[langchain.schema.Document, float]][source]#
Return docs and it’s scores most similar to query.
By default supports Approximate Search.
Also supports Script Scoring and Painless Scripting.
Parameters
query – Text to look up documents similar to.
k – Number of Documents to return. Defaults to 4.
rtdocs_stable/api.python.langchain.com/en/stable/reference/modules/vectorstores.html