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The Cypher query implemented in llamaindex FalkorDBPropertyGraphStore.vector_query seems to calculate the similarity directly against all nodes, which, if there are many nodes, may have poor performance.
MATCH (e:`__Entity__`)
WHERE e.embedding IS NOT NULL AND ({filters})
WITH e, vec.euclideanDistance(e.embedding, vecf32($embedding)) AS score
ORDER BY score LIMIT $limit
RETURN e.id AS name,
[l in labels(e) WHERE l <> '__Entity__' | l][0] AS type,
e{{.* , embedding: Null, name: Null, id: Null}} AS properties,
score
The text was updated successfully, but these errors were encountered:
The Cypher query implemented in llamaindex
FalkorDBPropertyGraphStore.vector_query
seems to calculate the similarity directly against all nodes, which, if there are many nodes, may have poor performance.The text was updated successfully, but these errors were encountered: