From a35c39c71f2cd7258e6aba60bf71983c46cc8bbe Mon Sep 17 00:00:00 2001 From: Stefano Fiorucci Date: Thu, 1 Feb 2024 14:56:17 +0100 Subject: [PATCH] Update integrations/pgvector/src/haystack_integrations/components/retrievers/pgvector/embedding_retriever.py Co-authored-by: Massimiliano Pippi --- .../components/retrievers/pgvector/embedding_retriever.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/integrations/pgvector/src/haystack_integrations/components/retrievers/pgvector/embedding_retriever.py b/integrations/pgvector/src/haystack_integrations/components/retrievers/pgvector/embedding_retriever.py index fbd9704f4..2540eaf5a 100644 --- a/integrations/pgvector/src/haystack_integrations/components/retrievers/pgvector/embedding_retriever.py +++ b/integrations/pgvector/src/haystack_integrations/components/retrievers/pgvector/embedding_retriever.py @@ -32,7 +32,7 @@ def __init__( :param filters: Filters applied to the retrieved Documents. Defaults to None. :param top_k: Maximum number of Documents to return, defaults to 10. :param vector_function: The similarity function to use when searching for similar embeddings. - Defaults to the PgvectorDocumentStore's vector_function. + Defaults to the one set in the `document_store` instance. "cosine_similarity" and "inner_product" are similarity functions and higher scores indicate greater similarity between the documents. "l2_distance" returns the straight-line distance between vectors,