From f8fd86f3fbc0669eb61843c03eb48e943956a0cb Mon Sep 17 00:00:00 2001 From: shaohuzhang1 Date: Mon, 4 Mar 2024 10:26:05 +0800 Subject: [PATCH] =?UTF-8?q?fix:=20=E3=80=90=E5=BA=94=E7=94=A8=E3=80=91?= =?UTF-8?q?=E5=BA=94=E7=94=A8=E4=B8=8D=E5=85=B3=E8=81=94=E7=9F=A5=E8=AF=86?= =?UTF-8?q?=E5=BA=93=EF=BC=8C=E8=BF=9B=E8=A1=8C=E5=91=BD=E4=B8=AD=E6=B5=8B?= =?UTF-8?q?=E8=AF=95=E6=8A=A5=E9=94=99?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- apps/embedding/vector/pg_vector.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/apps/embedding/vector/pg_vector.py b/apps/embedding/vector/pg_vector.py index fd5378aea..2b65c2344 100644 --- a/apps/embedding/vector/pg_vector.py +++ b/apps/embedding/vector/pg_vector.py @@ -64,6 +64,8 @@ class PGVector(BaseVectorStore): def hit_test(self, query_text, dataset_id_list: list[str], exclude_document_id_list: list[str], top_number: int, similarity: float, embedding: HuggingFaceEmbeddings): + if dataset_id_list is None or len(dataset_id_list) == 0: + return [] exclude_dict = {} embedding_query = embedding.embed_query(query_text) query_set = QuerySet(Embedding).filter(dataset_id__in=dataset_id_list, is_active=True)