asimilarity_search_with_score() — langchain Function Reference

Architecture documentation for the asimilarity_search_with_score() function in in_memory.py from the langchain codebase.

Function python DataProcessing VectorStores calls 1 called by 1

Entity Profile

DataProcessing→ VectorStores→ asimilarity_search_with_score() — langchain Function Reference

Dependency Diagram

graph TD
  e59dcf6a_fb2f_6e50_714b_45aedbb12988["asimilarity_search_with_score()"]
  6e491709_d60f_689d_8a1a_c760b54fd120["InMemoryVectorStore"]
  e59dcf6a_fb2f_6e50_714b_45aedbb12988 -->|defined in| 6e491709_d60f_689d_8a1a_c760b54fd120
  fe6f7064_efb9_6d58_7f4d_5704ca875b42["asimilarity_search()"]
  fe6f7064_efb9_6d58_7f4d_5704ca875b42 -->|calls| e59dcf6a_fb2f_6e50_714b_45aedbb12988
  bc9209e2_2df4_4845_6a2a_f1a745b98d88["similarity_search_with_score_by_vector()"]
  e59dcf6a_fb2f_6e50_714b_45aedbb12988 -->|calls| bc9209e2_2df4_4845_6a2a_f1a745b98d88
  style e59dcf6a_fb2f_6e50_714b_45aedbb12988 fill:#6366f1,stroke:#818cf8,color:#fff

Relationship Graph

Source Code

libs/core/langchain_core/vectorstores/in_memory.py lines 373–381

    async def asimilarity_search_with_score(
        self, query: str, k: int = 4, **kwargs: Any
    ) -> list[tuple[Document, float]]:
        embedding = await self.embedding.aembed_query(query)
        return self.similarity_search_with_score_by_vector(
            embedding,
            k,
            **kwargs,
        )