From b1cf0e61e1b26dcf2a79a8c73d48f99ea4915c23 Mon Sep 17 00:00:00 2001
From: hailin <hailin@gdzx.xyz>
Date: Sun, 11 May 2025 01:49:18 +0800
Subject: [PATCH] .

---
 app/api/search.py     | 2 +-
 app/core/embedding.py | 1 +
 2 files changed, 2 insertions(+), 1 deletion(-)

diff --git a/app/api/search.py b/app/api/search.py
index b62c9df..ae12f5f 100644
--- a/app/api/search.py
+++ b/app/api/search.py
@@ -57,7 +57,7 @@ def search_docs(request: QueryRequest, user_id: str = Query(..., description="
         logger.info("VectorStoreIndex loaded successfully.")
 
         # 将用户查询通过本地模型生成嵌入向量
-        query_vector = embedder._get_query_embedding(request.query)  # 使用本地模型生成查询的嵌入向量
+        query_vector = embedder.encode([request.query])  # 使用本地模型生成查询的嵌入向量
         logger.info(f"Generated query embedding: {query_vector}")
 
         # 使用 FaissVectorStore 检索最相似的节点
diff --git a/app/core/embedding.py b/app/core/embedding.py
index 86ddb8a..e3aa4ca 100644
--- a/app/core/embedding.py
+++ b/app/core/embedding.py
@@ -28,3 +28,4 @@ class BGEEmbedding:
         return torch.sum(token_embeddings * input_mask_expanded, 1) / torch.clamp(input_mask_expanded.sum(1), min=1e-9)
 
 embedder = BGEEmbedding()
+