InMemoryVectorstoreWithSearch Class — langchain Architecture

Architecture documentation for the InMemoryVectorstoreWithSearch class in test_base.py from the langchain codebase.

Class python

Entity Profile

Dependency Diagram

graph TD
  8a79270f_42fb_7a57_0a40_e13f5b02878f["InMemoryVectorstoreWithSearch"]
  6e491709_d60f_689d_8a1a_c760b54fd120["InMemoryVectorStore"]
  8a79270f_42fb_7a57_0a40_e13f5b02878f -->|extends| 6e491709_d60f_689d_8a1a_c760b54fd120
  d1736cc5_5d04_ec6a_a15a_4a8a730c63dd["test_base.py"]
  8a79270f_42fb_7a57_0a40_e13f5b02878f -->|defined in| d1736cc5_5d04_ec6a_a15a_4a8a730c63dd
  bfc3db68_2a96_682f_d606_0fcf9e00f190["similarity_search()"]
  8a79270f_42fb_7a57_0a40_e13f5b02878f -->|method| bfc3db68_2a96_682f_d606_0fcf9e00f190

Relationship Graph

Source Code

libs/langchain/tests/unit_tests/retrievers/self_query/test_base.py lines 64–75

class InMemoryVectorstoreWithSearch(InMemoryVectorStore):
    @override
    def similarity_search(
        self,
        query: str,
        k: int = 4,
        **kwargs: Any,
    ) -> list[Document]:
        res = self.store.get(query)
        if res is None:
            return []
        return [res]