Return docs most similar to the query with embedding.
Also includes the query embedding vector.
similarity_search_with_embedding(
self,
query: str,
k: int = 4,
filter: dict[str, Any] | None = None
) -> tuple[list[float], list[tuple[Document, list[float]]]]