Home / Function/ max_marginal_relevance_search_by_vector() — langchain Function Reference

max_marginal_relevance_search_by_vector() — langchain Function Reference

Architecture documentation for the max_marginal_relevance_search_by_vector() function in qdrant.py from the langchain codebase.

Entity Profile

Dependency Diagram

graph TD
  f70b258f_7085_17ed_46c4_07fbcbea68c1["max_marginal_relevance_search_by_vector()"]
  671b47a0_cdd3_a89d_e90f_0631a4bd67d3["QdrantVectorStore"]
  f70b258f_7085_17ed_46c4_07fbcbea68c1 -->|defined in| 671b47a0_cdd3_a89d_e90f_0631a4bd67d3
  6c0af82c_cb1f_821f_efa9_a3c7b1a87425["max_marginal_relevance_search()"]
  6c0af82c_cb1f_821f_efa9_a3c7b1a87425 -->|calls| f70b258f_7085_17ed_46c4_07fbcbea68c1
  365c8401_562f_37f6_22d0_d8da0ff6fb68["max_marginal_relevance_search_with_score_by_vector()"]
  f70b258f_7085_17ed_46c4_07fbcbea68c1 -->|calls| 365c8401_562f_37f6_22d0_d8da0ff6fb68
  style f70b258f_7085_17ed_46c4_07fbcbea68c1 fill:#6366f1,stroke:#818cf8,color:#fff

Relationship Graph

Source Code

libs/partners/qdrant/langchain_qdrant/qdrant.py lines 771–803

    def max_marginal_relevance_search_by_vector(
        self,
        embedding: list[float],
        k: int = 4,
        fetch_k: int = 20,
        lambda_mult: float = 0.5,
        filter: models.Filter | None = None,  # noqa: A002
        search_params: models.SearchParams | None = None,
        score_threshold: float | None = None,
        consistency: models.ReadConsistency | None = None,
        **kwargs: Any,
    ) -> list[Document]:
        """Return docs selected using the maximal marginal relevance with dense vectors.

        Maximal marginal relevance optimizes for similarity to query AND diversity
        among selected documents.

        Returns:
            List of `Document` objects selected by maximal marginal relevance.

        """
        results = self.max_marginal_relevance_search_with_score_by_vector(
            embedding,
            k=k,
            fetch_k=fetch_k,
            lambda_mult=lambda_mult,
            filter=filter,
            search_params=search_params,
            score_threshold=score_threshold,
            consistency=consistency,
            **kwargs,
        )
        return list(map(itemgetter(0), results))

Domain

Subdomains

Frequently Asked Questions

What does max_marginal_relevance_search_by_vector() do?
max_marginal_relevance_search_by_vector() is a function in the langchain codebase, defined in libs/partners/qdrant/langchain_qdrant/qdrant.py.
Where is max_marginal_relevance_search_by_vector() defined?
max_marginal_relevance_search_by_vector() is defined in libs/partners/qdrant/langchain_qdrant/qdrant.py at line 771.
What does max_marginal_relevance_search_by_vector() call?
max_marginal_relevance_search_by_vector() calls 1 function(s): max_marginal_relevance_search_with_score_by_vector.
What calls max_marginal_relevance_search_by_vector()?
max_marginal_relevance_search_by_vector() is called by 1 function(s): max_marginal_relevance_search.

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