_aembed_query() — langchain Function Reference
Architecture documentation for the _aembed_query() function in vectorstores.py from the langchain codebase.
Entity Profile
Dependency Diagram
graph TD b6daed04_d43f_da3b_07c7_c1835c32cf84["_aembed_query()"] 2d095452_70a7_4606_a1b1_4650d16b5343["Qdrant"] b6daed04_d43f_da3b_07c7_c1835c32cf84 -->|defined in| 2d095452_70a7_4606_a1b1_4650d16b5343 0bfb6a9a_e62a_ca13_35c1_984eee7bf4a4["asimilarity_search_with_score()"] 0bfb6a9a_e62a_ca13_35c1_984eee7bf4a4 -->|calls| b6daed04_d43f_da3b_07c7_c1835c32cf84 32137f96_4258_744f_9902_4d022e824899["amax_marginal_relevance_search()"] 32137f96_4258_744f_9902_4d022e824899 -->|calls| b6daed04_d43f_da3b_07c7_c1835c32cf84 style b6daed04_d43f_da3b_07c7_c1835c32cf84 fill:#6366f1,stroke:#818cf8,color:#fff
Relationship Graph
Source Code
libs/partners/qdrant/langchain_qdrant/vectorstores.py lines 2118–2137
async def _aembed_query(self, query: str) -> list[float]:
"""Embed query text asynchronously.
Used to provide backward compatibility with `embedding_function` argument.
Args:
query: Query text.
Returns:
List of floats representing the query embedding.
"""
if self.embeddings is not None:
embedding = await self.embeddings.aembed_query(query)
elif self._embeddings_function is not None:
embedding = self._embeddings_function(query)
else:
msg = "Neither of embeddings or embedding_function is set"
raise ValueError(msg)
return embedding.tolist() if hasattr(embedding, "tolist") else embedding
Domain
Subdomains
Source
Frequently Asked Questions
What does _aembed_query() do?
_aembed_query() is a function in the langchain codebase, defined in libs/partners/qdrant/langchain_qdrant/vectorstores.py.
Where is _aembed_query() defined?
_aembed_query() is defined in libs/partners/qdrant/langchain_qdrant/vectorstores.py at line 2118.
What calls _aembed_query()?
_aembed_query() is called by 2 function(s): amax_marginal_relevance_search, asimilarity_search_with_score.
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