move configs to configs.model_config

configs/config.py

@@ -1,12 +0,0 @@
-SQLALCHEMY_DATABASE_URI = "sqlite:///./langchain_chat_glm.db"
-kbs_config = {
-    "faiss": {
-    },
-    "milvus": {
-        "host": "127.0.0.1",
-        "port": "19530",
-        "user": "",
-        "password": "",
-        "secure": False,
-    }
-}

configs/model_config.py.example

@@ -239,8 +239,10 @@ if not os.path.exists(LOG_PATH):
 # 知识库默认存储路径
 KB_ROOT_PATH = os.path.join(os.path.dirname(os.path.dirname(__file__)), "knowledge_base")
 
-# 数据库默认存储路径
+# 数据库默认存储路径。
+# 如果使用sqlite，可以直接修改DB_ROOT_PATH；如果使用其它数据库，请直接修改SQLALCHEMY_DATABASE_URI。
 DB_ROOT_PATH = os.path.join(KB_ROOT_PATH, "info.db")
+SQLALCHEMY_DATABASE_URI = f"sqlite://{DB_ROOT_PATH}"
 
 # 缓存向量库数量
 CACHED_VS_NUM = 1
@@ -278,3 +280,14 @@ BING_SEARCH_URL = "https://api.bing.microsoft.com/v7.0/search"
 # 是因为服务器加了防火墙，需要联系管理员加白名单，如果公司的服务器的话，就别想了GG
 BING_SUBSCRIPTION_KEY = ""
 
+kbs_config = {
+    "faiss": {
+    },
+    "milvus": {
+        "host": "127.0.0.1",
+        "port": "19530",
+        "user": "",
+        "password": "",
+        "secure": False,
+    }
+}

server/db/base.py

@@ -2,7 +2,7 @@ from sqlalchemy import create_engine
 from sqlalchemy.ext.declarative import declarative_base
 from sqlalchemy.orm import sessionmaker
 
-from configs.config import SQLALCHEMY_DATABASE_URI
+from configs.model_config import SQLALCHEMY_DATABASE_URI
 
 engine = create_engine(SQLALCHEMY_DATABASE_URI)
 

server/knowledge_base/kb_service/base.py

@@ -8,9 +8,9 @@ from langchain.embeddings import HuggingFaceEmbeddings
 from langchain.embeddings.base import Embeddings
 from langchain.docstore.document import Document
 
-from configs.config import kbs_config
 from configs.model_config import (VECTOR_SEARCH_TOP_K,
-                                  embedding_model_dict, EMBEDDING_DEVICE, EMBEDDING_MODEL)
+                                  embedding_model_dict, EMBEDDING_DEVICE, EMBEDDING_MODEL,
+                                  kbs_config)
 
 from server.db.repository.knowledge_base_repository import add_kb_to_db, delete_kb_from_db, list_kbs_from_db, kb_exists
 from server.db.repository.knowledge_file_repository import add_doc_to_db, delete_file_from_db, doc_exists, \

server/knowledge_base/kb_service/default_kb_service.py

@@ -22,15 +22,9 @@ class DefaultKBService(KBService):
     def vs_type(self) -> str:
         return "default"
 
-    def do_create_kbs(self):
-        pass
-
     def do_init(self):
         pass
 
-    def do_drop_kbs(self):
-        pass
-
     def do_search(self):
         pass
 

server/knowledge_base/kb_service/milvus_kb_service.py

@@ -4,8 +4,7 @@ from langchain.embeddings.base import Embeddings
 from langchain.schema import Document
 from langchain.vectorstores import Milvus
 
-from configs.config import kbs_config
-from configs.model_config import EMBEDDING_DEVICE
+from configs.model_config import EMBEDDING_DEVICE, kbs_config
 from server.knowledge_base import KnowledgeFile
 from server.knowledge_base.kb_service.base import KBService, SupportedVSType, load_embeddings