From 0078cdc72451467c7b1af60cbb948e257059db52 Mon Sep 17 00:00:00 2001 From: hxb Date: Sun, 28 Apr 2024 16:12:23 +0800 Subject: [PATCH] =?UTF-8?q?bugfix:=20=E4=BD=BF=E7=94=A8=E5=90=91=E9=87=8F?= =?UTF-8?q?=E8=AE=A1=E7=AE=97=E6=96=B9=E5=BC=8FMETRIC=5FINNER=5FPRODUCT?= =?UTF-8?q?=E6=97=B6=E5=90=AF=E7=94=A8normalize=5FL2=E4=BC=9A=E5=AF=BC?= =?UTF-8?q?=E8=87=B4=E5=90=91=E9=87=8F=E5=8C=96=E5=A4=B1=E8=B4=A5?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- server/knowledge_base/kb_cache/faiss_cache.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/server/knowledge_base/kb_cache/faiss_cache.py b/server/knowledge_base/kb_cache/faiss_cache.py index 60c550ee..bee88fbc 100644 --- a/server/knowledge_base/kb_cache/faiss_cache.py +++ b/server/knowledge_base/kb_cache/faiss_cache.py @@ -57,7 +57,7 @@ class _FaissPool(CachePool): ) -> FAISS: embeddings = EmbeddingsFunAdapter(embed_model) doc = Document(page_content="init", metadata={}) - vector_store = FAISS.from_documents([doc], embeddings, normalize_L2=True,distance_strategy="METRIC_INNER_PRODUCT") + vector_store = FAISS.from_documents([doc], embeddings, distance_strategy="METRIC_INNER_PRODUCT") ids = list(vector_store.docstore._dict.keys()) vector_store.delete(ids) return vector_store @@ -94,7 +94,7 @@ class KBFaissPool(_FaissPool): if os.path.isfile(os.path.join(vs_path, "index.faiss")): embeddings = self.load_kb_embeddings(kb_name=kb_name, embed_device=embed_device, default_embed_model=embed_model) - vector_store = FAISS.load_local(vs_path, embeddings, normalize_L2=True,distance_strategy="METRIC_INNER_PRODUCT") + vector_store = FAISS.load_local(vs_path, embeddings, distance_strategy="METRIC_INNER_PRODUCT") elif create: # create an empty vector store if not os.path.exists(vs_path):