Parameters
texts (List[str]) – Text data.
embedding (Embeddings) – Embedding function.
metadatas (Optional[List[dict]]) – Metadata for each text if it exists.
Defaults to None.
collection_name (str, optional) – Collection name to use. Defaults to
“LangChainCollection”.
connection_args (dict[str, Any], optional) – Connection args to use. Defaults
to DEFAULT_MILVUS_CONNECTION.
consistency_level (str, optional) – Which consistency level to use. Defaults
to “Session”.
index_params (Optional[dict], optional) – Which index_params to use. Defaults
to None.
search_params (Optional[dict], optional) – Which search params to use.
Defaults to None.
drop_old (Optional[bool], optional) – Whether to drop the collection with
that name if it exists. Defaults to False.
Returns
Milvus Vector Store
Return type
Milvus
max_marginal_relevance_search(query: str, k: int = 4, fetch_k: int = 20, lambda_mult: float = 0.5, param: Optional[dict] = None, expr: Optional[str] = None, timeout: Optional[int] = None, **kwargs: Any) → List[Document][source]¶
Perform a search and return results that are reordered by MMR.
Parameters
query (str) – The text being searched.
k (int, optional) – How many results to give. Defaults to 4.
fetch_k (int, optional) – Total results to select k from.
Defaults to 20.
lambda_mult – Number between 0 and 1 that determines the degree
of diversity among the results with 0 corresponding
to maximum diversity and 1 to minimum diversity.
Defaults to 0.5