similarity_search_by_vector() — langchain Function Reference
Architecture documentation for the similarity_search_by_vector() function in in_memory.py from the langchain codebase.
Entity Profile
Dependency Diagram
graph TD f029e9d2_7f4e_370f_644b_6396cf0bc134["similarity_search_by_vector()"] 6e491709_d60f_689d_8a1a_c760b54fd120["InMemoryVectorStore"] f029e9d2_7f4e_370f_644b_6396cf0bc134 -->|defined in| 6e491709_d60f_689d_8a1a_c760b54fd120 e9dc5486_451a_3994_08cf_b19dc6c55850["asimilarity_search_by_vector()"] e9dc5486_451a_3994_08cf_b19dc6c55850 -->|calls| f029e9d2_7f4e_370f_644b_6396cf0bc134 bc9209e2_2df4_4845_6a2a_f1a745b98d88["similarity_search_with_score_by_vector()"] f029e9d2_7f4e_370f_644b_6396cf0bc134 -->|calls| bc9209e2_2df4_4845_6a2a_f1a745b98d88 style f029e9d2_7f4e_370f_644b_6396cf0bc134 fill:#6366f1,stroke:#818cf8,color:#fff
Relationship Graph
Source Code
libs/core/langchain_core/vectorstores/in_memory.py lines 384–395
def similarity_search_by_vector(
self,
embedding: list[float],
k: int = 4,
**kwargs: Any,
) -> list[Document]:
docs_and_scores = self.similarity_search_with_score_by_vector(
embedding,
k,
**kwargs,
)
return [doc for doc, _ in docs_and_scores]
Domain
Subdomains
Called By
Source
Frequently Asked Questions
What does similarity_search_by_vector() do?
similarity_search_by_vector() is a function in the langchain codebase, defined in libs/core/langchain_core/vectorstores/in_memory.py.
Where is similarity_search_by_vector() defined?
similarity_search_by_vector() is defined in libs/core/langchain_core/vectorstores/in_memory.py at line 384.
What does similarity_search_by_vector() call?
similarity_search_by_vector() calls 1 function(s): similarity_search_with_score_by_vector.
What calls similarity_search_by_vector()?
similarity_search_by_vector() is called by 1 function(s): asimilarity_search_by_vector.
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