perf: improve transaction performance in vector db

This commit is contained in:
Soulter
2025-05-30 12:59:26 +08:00
parent af934c5d09
commit 2ab5810f13
+4 -10
View File
@@ -30,19 +30,13 @@ class FaissVecDB(BaseVecDB):
async def initialize(self):
await self.document_storage.initialize()
async def insert(
self,
content: str,
metadata: dict = None,
id: str = None,
) -> int:
async def insert(self, content: str, metadata: dict = None, id: str = None) -> int:
"""
插入一条文本和其对应向量,自动生成 ID 并保持一致性。
"""
metadata = metadata or {}
str_id = id or str(uuid.uuid4()) # 使用 UUID 作为原始 ID
# 获取向量
vector = await self.embedding_provider.get_embedding(content)
vector = np.array(vector, dtype=np.float32)
async with self.document_storage.connection.cursor() as cursor:
@@ -54,9 +48,9 @@ class FaissVecDB(BaseVecDB):
result = await self.document_storage.get_document_by_doc_id(str_id)
int_id = result["id"]
# 插入向量到 FAISS
await self.embedding_storage.insert(vector, int_id)
return int_id
# 插入向量到 FAISS
await self.embedding_storage.insert(vector, int_id)
return int_id
async def retrieve(
self, query: str, k: int = 5, fetch_k: int = 20, metadata_filters: dict = None