修复因Milvus数据库初始化失败而导致整个服务无法启动的问题

bbit_ai/app/db/milvus.py

@@ -3,7 +3,7 @@ from typing import List
 
 from langchain_core.documents import Document
 
-from config.milvus import knVectorstore, memVectorstore
+from config.milvus import get_kn_vectorstore, get_mem_vectorstore
 
 
 def get_knowledge_by_key_words(key_words: str, kn_ids: List[str]) -> str:
@@ -17,7 +17,7 @@ def get_knowledge_by_key_words(key_words: str, kn_ids: List[str]) -> str:
     else:
         return "未找到相关的知识。"
 
-    result = knVectorstore.similarity_search(
+    result = get_kn_vectorstore().similarity_search(
         query=key_words, k=3, expr=expr  # 可调节返回条数
     )
 
@@ -46,7 +46,7 @@ def get_memory_by_key_words(key_words: str, ai_ids: List[str]) -> str:
     else:
         expr = ""  # 不限制 kn_id todo 实际上应该不反悔任何内容
 
-    result = memVectorstore.similarity_search(
+    result = get_mem_vectorstore().similarity_search(
         query=key_words, k=5, expr=expr  # 可调节返回条数
     )
 
@@ -65,7 +65,7 @@ def get_memory_by_key_words(key_words: str, ai_ids: List[str]) -> str:
 
 def get_knowledge_by_base_id(base_id: str):
     expr = f'kn_id == "{base_id}"'  # base_id 会被替换
-    result = knVectorstore.similarity_search(
+    result = get_kn_vectorstore().similarity_search(
         query="", k=100, expr=expr  # 如果只想用过滤条件，可以传空字符串
     )
     return [
@@ -90,7 +90,7 @@ def add_knowledge(text: str, is_active: bool, base_id: str, user_id: str):
             },
         )
     ]
-    return knVectorstore.add_documents(docs)
+    return get_kn_vectorstore().add_documents(docs)
 
 
 def add_memory(ai_id: str, mem: str, user_id: str, is_active: bool):
@@ -105,4 +105,4 @@ def add_memory(ai_id: str, mem: str, user_id: str, is_active: bool):
             },
         )
     ]
-    return memVectorstore.add_documents(docs)
+    return get_mem_vectorstore().add_documents(docs)