fix: auto-fix code issues (cron)

- 修复重复导入/字段
- 修复异常处理
- 修复PEP8格式问题
- 添加类型注解

backend/entity_aligner.py

@@ -4,12 +4,12 @@ Entity Aligner - Phase 3
 使用 embedding 进行实体对齐
 """
 
-import os
 import json
+import os
+from dataclasses import dataclass
+
 import httpx
 import numpy as np
-from typing import List, Optional, Dict
-from dataclasses import dataclass
 
 # API Keys
 KIMI_API_KEY = os.getenv("KIMI_API_KEY", "")
@@ -21,7 +21,7 @@ class EntityEmbedding:
     entity_id: str
     name: str
     definition: str
-    embedding: List[float]
+    embedding: list[float]
 
 
 class EntityAligner:
@@ -29,9 +29,9 @@ class EntityAligner:
 
     def __init__(self, similarity_threshold: float = 0.85):
         self.similarity_threshold = similarity_threshold
-        self.embedding_cache: Dict[str, List[float]] = {}
+        self.embedding_cache: dict[str, list[float]] = {}
 
-    def get_embedding(self, text: str) -> Optional[List[float]]:
+    def get_embedding(self, text: str) -> list[float] | None:
         """
         使用 Kimi API 获取文本的 embedding
 
@@ -67,7 +67,7 @@ class EntityAligner:
             print(f"Embedding API failed: {e}")
             return None
 
-    def compute_similarity(self, embedding1: List[float], embedding2: List[float]) -> float:
+    def compute_similarity(self, embedding1: list[float], embedding2: list[float]) -> float:
         """
         计算两个 embedding 的余弦相似度
 
@@ -111,9 +111,9 @@ class EntityAligner:
         project_id: str,
         name: str,
         definition: str = "",
-        exclude_id: Optional[str] = None,
-        threshold: Optional[float] = None,
-    ) -> Optional[object]:
+        exclude_id: str | None = None,
+        threshold: float | None = None,
+    ) -> object | None:
         """
         查找相似的实体
 
@@ -175,8 +175,8 @@ class EntityAligner:
         return best_match
 
     def _fallback_similarity_match(
-        self, entities: List[object], name: str, exclude_id: Optional[str] = None
-    ) -> Optional[object]:
+        self, entities: list[object], name: str, exclude_id: str | None = None
+    ) -> object | None:
         """
         回退到简单的相似度匹配（不使用 embedding）
 
@@ -209,8 +209,8 @@ class EntityAligner:
         return None
 
     def batch_align_entities(
-        self, project_id: str, new_entities: List[Dict], threshold: Optional[float] = None
-    ) -> List[Dict]:
+        self, project_id: str, new_entities: list[dict], threshold: float | None = None
+    ) -> list[dict]:
         """
         批量对齐实体
 
@@ -257,7 +257,7 @@ class EntityAligner:
 
         return results
 
-    def suggest_entity_aliases(self, entity_name: str, entity_definition: str = "") -> List[str]:
+    def suggest_entity_aliases(self, entity_name: str, entity_definition: str = "") -> list[str]:
         """
         使用 LLM 建议实体的别名