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 (E302, E305, E501)
- 修复行长度超过100字符的问题
- 修复F821未定义名称错误

backend/entity_aligner.py

@@ -15,6 +15,7 @@ import numpy as np
 KIMI_API_KEY = os.getenv("KIMI_API_KEY", "")
 KIMI_BASE_URL = os.getenv("KIMI_BASE_URL", "https://api.kimi.com/coding")
 
+
 @dataclass
 class EntityEmbedding:
     entity_id: str
@@ -22,6 +23,7 @@ class EntityEmbedding:
     definition: str
     embedding: list[float]
 
+
 class EntityAligner:
     """实体对齐器 - 使用 embedding 进行相似度匹配"""
 
@@ -64,7 +66,7 @@ class EntityAligner:
             self.embedding_cache[cache_key] = embedding
             return embedding
 
-        except Exception as e:
+        except (httpx.HTTPError, json.JSONDecodeError, KeyError) as e:
             print(f"Embedding API failed: {e}")
             return None
 
@@ -311,12 +313,14 @@ class EntityAligner:
             if json_match:
                 data = json.loads(json_match.group())
                 return data.get("aliases", [])
-        except Exception as e:
+        except (httpx.HTTPError, json.JSONDecodeError, KeyError) as e:
             print(f"Alias suggestion failed: {e}")
 
         return []
 
 # 简单的字符串相似度计算（不使用 embedding）
+
+
 def simple_similarity(str1: str, str2: str) -> float:
     """
     计算两个字符串的简单相似度
@@ -347,6 +351,7 @@ def simple_similarity(str1: str, str2: str) -> float:
 
     return SequenceMatcher(None, s1, s2).ratio()
 
+
 if __name__ == "__main__":
     # 测试
     aligner = EntityAligner()