lambda_mult: Number between 0 and 1 determining the degree of diversity.
                0 corresponds to max diversity and 1 to min diversity. Defaults to 0.5.
            exec_option (str): DeepLakeVectorStore supports 3 ways for searching.
                Could be "python", "compute_engine" or "tensor_db". Defaults to
                "python".
                - "python" - Pure-python implementation running on the client.
                    Can be used for data stored anywhere. WARNING: using this
                    option with big datasets is discouraged due to potential
                    memory issues.
                - "compute_engine" - Performant C++ implementation of the Deep
                    Lake Compute Engine. Runs on the client and can be used for
                    any data stored in or connected to Deep Lake. It cannot be used
                    with in-memory or local datasets.
                - "tensor_db" - Performant, fully-hosted Managed Tensor Database.
                    Responsible for storage and query execution. Only available for
                    data stored in the Deep Lake Managed Database. To store datasets
                    in this database, specify `runtime = {"db_engine": True}`
                    during dataset creation.
            **kwargs: Additional keyword arguments.
        Returns:
            List[Documents] - A list of documents.
        """
        return self._search(
            embedding=embedding,
            k=k,
            fetch_k=fetch_k,
            use_maximal_marginal_relevance=True,
            lambda_mult=lambda_mult,
            exec_option=exec_option,
            **kwargs,
        )
[docs]    def max_marginal_relevance_search(
        self,
        query: str,
        k: int = 4,
        fetch_k: int = 20,
        lambda_mult: float = 0.5,