Return MongoDB documents most similar to the given query vector.
Atlas Vector Search eliminates the need to run a separate search system alongside your database.
Args: embedding: Embedding vector to search for. k: (Optional) number of documents to return. Defaults to 4. pre_filter: List of MQL match expressions comparing an indexed field post_filter_pipeline: (Optional) Pipeline of MongoDB aggregation stages to filter/process results after $vectorSearch. oversampling_factor: Multiple of k used when generating number of candidates at each step in the HNSW Vector Search. include_embeddings: If True, the embedding vector of each result will be included in metadata. kwargs: Additional arguments are specific to the search_type
