feat: enhance vector database configuration handling and improve provider initialization

domain/ai/api.py

@@ -267,19 +267,24 @@ async def get_vector_db_config(request: Request, user: User = Depends(get_curren
 async def update_vector_db_config(
     request: Request, payload: VectorDBConfigPayload, user: User = Depends(get_current_active_user)
 ):
-    entry = get_provider_entry(payload.type)
+    provider_type = str(payload.type or "").strip()
+    if not provider_type:
+        raise HTTPException(status_code=400, detail="向量数据库类型不能为空")
+    normalized_config = VectorDBConfigManager.normalize_config(payload.config)
+
+    entry = get_provider_entry(provider_type)
     if not entry:
         raise HTTPException(
-            status_code=400, detail=f"未知的向量数据库类型: {payload.type}")
+            status_code=400, detail=f"未知的向量数据库类型: {provider_type}")
     if not entry.get("enabled", True):
         raise HTTPException(status_code=400, detail="该向量数据库类型暂不可用")
 
-    provider_cls = get_provider_class(payload.type)
+    provider_cls = get_provider_class(provider_type)
     if not provider_cls:
         raise HTTPException(
-            status_code=400, detail=f"未找到类型 {payload.type} 对应的实现")
+            status_code=400, detail=f"未找到类型 {provider_type} 对应的实现")
 
-    test_provider = provider_cls(payload.config)
+    test_provider = provider_cls(normalized_config)
     try:
         await test_provider.initialize()
     except Exception as exc:
@@ -293,7 +298,7 @@ async def update_vector_db_config(
             except Exception:
                 pass
 
-    await VectorDBConfigManager.save_config(payload.type, payload.config)
+    await VectorDBConfigManager.save_config(provider_type, normalized_config)
     service = VectorDBService()
     await service.reload()
     config_data = await service.current_provider()

domain/ai/service.py

@@ -1,7 +1,7 @@
 import asyncio
 import json
 from collections.abc import Iterable
-from typing import Any, Dict, List, Optional, Tuple
+from typing import Any, Dict, List, Optional, Tuple, TypeVar
 
 import httpx
 from tortoise.exceptions import DoesNotExist
@@ -28,16 +28,37 @@ OPENAI_EMBEDDING_DIMS = {
     "text-embedding-ada-002": 1536,
 }
 
+T = TypeVar("T")
+
 
 class VectorDBConfigManager:
     TYPE_KEY = "VECTOR_DB_TYPE"
     CONFIG_KEY = "VECTOR_DB_CONFIG"
     DEFAULT_TYPE = "milvus_lite"
 
+    @classmethod
+    def normalize_type(cls, provider_type: Any) -> str:
+        normalized = str(provider_type or cls.DEFAULT_TYPE).strip()
+        return normalized or cls.DEFAULT_TYPE
+
+    @classmethod
+    def normalize_config(cls, config: Dict[str, Any] | None) -> Dict[str, Any]:
+        normalized: Dict[str, Any] = {}
+        for key, value in (config or {}).items():
+            normalized_key = str(key).strip()
+            if not normalized_key:
+                continue
+            if isinstance(value, str):
+                value = value.strip()
+                if not value:
+                    continue
+            normalized[normalized_key] = value
+        return normalized
+
     @classmethod
     async def load_config(cls) -> Tuple[str, Dict[str, Any]]:
         raw_type = await ConfigService.get(cls.TYPE_KEY, cls.DEFAULT_TYPE)
-        provider_type = str(raw_type or cls.DEFAULT_TYPE)
+        provider_type = cls.normalize_type(raw_type)
 
         raw_config = await ConfigService.get(cls.CONFIG_KEY)
         config_dict: Dict[str, Any] = {}
@@ -48,12 +69,14 @@ class VectorDBConfigManager:
                 config_dict = {}
         elif isinstance(raw_config, dict):
             config_dict = raw_config
-        return provider_type, config_dict
+        return provider_type, cls.normalize_config(config_dict)
 
     @classmethod
     async def save_config(cls, provider_type: str, config: Dict[str, Any]) -> None:
-        await ConfigService.set(cls.TYPE_KEY, provider_type)
+        normalized_type = cls.normalize_type(provider_type)
-        await ConfigService.set(cls.CONFIG_KEY, json.dumps(config or {}))
+        normalized_config = cls.normalize_config(config)
+        await ConfigService.set(cls.TYPE_KEY, normalized_type)
+        await ConfigService.set(cls.CONFIG_KEY, json.dumps(normalized_config))
 
     @classmethod
     async def get_type(cls) -> str:
@@ -413,6 +436,7 @@ class VectorDBService:
             self._provider_type: Optional[str] = None
             self._provider_config: Dict[str, Any] | None = None
             self._lock = asyncio.Lock()
+            self._operation_lock = asyncio.Lock()
 
     async def _ensure_provider(self) -> BaseVectorProvider:
         if self._provider is None:
@@ -449,33 +473,38 @@ class VectorDBService:
             self._provider_config = normalized_config
             return provider
 
+    async def _run_provider_call(self, provider: BaseVectorProvider, method_name: str, *args, **kwargs) -> T:
+        method = getattr(provider, method_name)
+        async with self._operation_lock:
+            return await asyncio.to_thread(method, *args, **kwargs)
+
     async def ensure_collection(self, collection_name: str, vector: bool = True, dim: int = DEFAULT_VECTOR_DIMENSION) -> None:
         provider = await self._ensure_provider()
-        provider.ensure_collection(collection_name, vector, dim)
+        await self._run_provider_call(provider, "ensure_collection", collection_name, vector, dim)
 
     async def upsert_vector(self, collection_name: str, data: Dict[str, Any]) -> None:
         provider = await self._ensure_provider()
-        provider.upsert_vector(collection_name, data)
+        await self._run_provider_call(provider, "upsert_vector", collection_name, data)
 
     async def delete_vector(self, collection_name: str, path: str) -> None:
         provider = await self._ensure_provider()
-        provider.delete_vector(collection_name, path)
+        await self._run_provider_call(provider, "delete_vector", collection_name, path)
 
     async def search_vectors(self, collection_name: str, query_embedding, top_k: int = 5):
         provider = await self._ensure_provider()
-        return provider.search_vectors(collection_name, query_embedding, top_k)
+        return await self._run_provider_call(provider, "search_vectors", collection_name, query_embedding, top_k)
 
     async def search_by_path(self, collection_name: str, query_path: str, top_k: int = 20):
         provider = await self._ensure_provider()
-        return provider.search_by_path(collection_name, query_path, top_k)
+        return await self._run_provider_call(provider, "search_by_path", collection_name, query_path, top_k)
 
     async def get_all_stats(self) -> Dict[str, Any]:
         provider = await self._ensure_provider()
-        return provider.get_all_stats()
+        return await self._run_provider_call(provider, "get_all_stats")
 
     async def clear_all_data(self) -> None:
         provider = await self._ensure_provider()
-        provider.clear_all_data()
+        await self._run_provider_call(provider, "clear_all_data")
 
     async def current_provider(self) -> Dict[str, Any]:
         provider_type, provider_config = await VectorDBConfigManager.load_config()

domain/ai/vector_providers/milvus_lite.py

@@ -1,3 +1,4 @@
+import asyncio
 from pathlib import Path
 from typing import Any, Dict, List, Optional
 
@@ -23,12 +24,14 @@ class MilvusLiteProvider(BaseVectorProvider):
 
     def __init__(self, config: Dict[str, Any] | None = None):
         super().__init__(config)
-        self.db_path = Path(self.config.get("db_path") or "data/db/milvus.db")
+        raw_db_path = self.config.get("db_path")
+        db_path = str(raw_db_path).strip() if raw_db_path is not None else ""
+        self.db_path = Path(db_path or "data/db/milvus.db")
         self.client: MilvusClient | None = None
 
     async def initialize(self) -> None:
         try:
-            self.client = MilvusClient(str(self.db_path))
+            self.client = await asyncio.to_thread(MilvusClient, str(self.db_path))
         except Exception as exc:  # pragma: no cover - depends on local environment
             raise RuntimeError(f"Failed to open Milvus Lite at {self.db_path}: {exc}") from exc
 

domain/ai/vector_providers/milvus_server.py

@@ -1,3 +1,4 @@
+import asyncio
 from typing import Any, Dict, List, Optional
 
 from pymilvus import CollectionSchema, DataType, FieldSchema, MilvusClient
@@ -32,11 +33,14 @@ class MilvusServerProvider(BaseVectorProvider):
         self.client: MilvusClient | None = None
 
     async def initialize(self) -> None:
-        uri = self.config.get("uri")
+        uri = str(self.config.get("uri") or "").strip()
         if not uri:
             raise RuntimeError("Milvus Server URI is required")
+        token = self.config.get("token")
+        if isinstance(token, str):
+            token = token.strip() or None
         try:
-            self.client = MilvusClient(uri=uri, token=self.config.get("token"))
+            self.client = await asyncio.to_thread(MilvusClient, uri=uri, token=token)
         except Exception as exc:  # pragma: no cover - depends on remote availability
             raise RuntimeError(f"Failed to connect to Milvus Server {uri}: {exc}") from exc
 

domain/ai/vector_providers/qdrant.py

@@ -1,3 +1,4 @@
+import asyncio
 from typing import Any, Dict, List, Optional, Sequence
 from uuid import NAMESPACE_URL, uuid5
 
@@ -40,7 +41,7 @@ class QdrantProvider(BaseVectorProvider):
         api_key = (self.config.get("api_key") or None) or None
         try:
             client = QdrantClient(url=url, api_key=api_key)
-            client.get_collections()
+            await asyncio.to_thread(client.get_collections)
             self.client = client
         except Exception as exc:  # pragma: no cover - 依赖外部服务
             raise RuntimeError(f"Failed to connect to Qdrant at {url}: {exc}") from exc