vector_search_stage#
- langchain_mongodb.pipelines.vector_search_stage(query_vector: List[float], search_field: str, index_name: str, top_k: int = 4, filter: Dict[str, Any] | None = None, oversampling_factor: int = 10, **kwargs: Any) Dict[str, Any] [source]#
Vector Search Stage without Scores.
Scoring is applied later depending on strategy. vector search includes a vectorSearchScore that is typically used. hybrid uses Reciprocal Rank Fusion.
- Parameters:
query_vector (List[float]) – List of embedding vector
search_field (str) – Field in Collection containing embedding vectors
index_name (str) – Name of Atlas Vector Search Index tied to Collection
top_k (int) – Number of documents to return
oversampling_factor (int) – this times limit is the number of candidates
filter (Dict[str, Any] | None) – MQL match expression comparing an indexed field. Some operators are not supported. See vectorSearch filter docs
kwargs (Any) –
- Returns:
Dictionary defining the $vectorSearch
- Return type:
Dict[str, Any]