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
- 修复缺失的urllib.parse导入

backend/multimodal_entity_linker.py

@@ -14,6 +14,7 @@ try:
 except ImportError:
     NUMPY_AVAILABLE = False
 
+
 @dataclass
 class MultimodalEntity:
     """多模态实体"""
@@ -32,6 +33,7 @@ class MultimodalEntity:
         if self.modality_features is None:
             self.modality_features = {}
 
+
 @dataclass
 class EntityLink:
     """实体关联"""
@@ -46,6 +48,7 @@ class EntityLink:
     confidence: float
     evidence: str
 
+
 @dataclass
 class AlignmentResult:
     """对齐结果"""
@@ -56,6 +59,7 @@ class AlignmentResult:
     match_type: str  # exact, fuzzy, embedding
     confidence: float
 
+
 @dataclass
 class FusionResult:
     """知识融合结果"""
@@ -66,11 +70,17 @@ class FusionResult:
     source_modalities: list[str]
     confidence: float
 
+
 class MultimodalEntityLinker:
     """多模态实体关联器 - 跨模态实体对齐和知识融合"""
 
     # 关联类型
-    LINK_TYPES = {"same_as": "同一实体", "related_to": "相关实体", "part_of": "组成部分", "mentions": "提及关系"}
+    LINK_TYPES = {
+        "same_as": "同一实体",
+        "related_to": "相关实体",
+        "part_of": "组成部分",
+        "mentions": "提及关系",
+    }
 
     # 模态类型
     MODALITIES = ["audio", "video", "image", "document"]
@@ -123,7 +133,9 @@ class MultimodalEntityLinker:
             (相似度, 匹配类型)
         """
         # 名称相似度
-        name_sim = self.calculate_string_similarity(entity1.get("name", ""), entity2.get("name", ""))
+        name_sim = self.calculate_string_similarity(
+            entity1.get("name", ""), entity2.get("name", "")
+        )
 
         # 如果名称完全匹配
         if name_sim == 1.0:
@@ -142,7 +154,9 @@ class MultimodalEntityLinker:
             return 0.95, "alias_match"
 
         # 定义相似度
-        def_sim = self.calculate_string_similarity(entity1.get("definition", ""), entity2.get("definition", ""))
+        def_sim = self.calculate_string_similarity(
+            entity1.get("definition", ""), entity2.get("definition", "")
+        )
 
         # 综合相似度
         combined_sim = name_sim * 0.7 + def_sim * 0.3
@@ -301,7 +315,9 @@ class MultimodalEntityLinker:
                 fused_properties["contexts"].append(mention.get("mention_context"))
 
         # 选择最佳定义（最长的那个）
-        best_definition = max(fused_properties["definitions"], key=len) if fused_properties["definitions"] else ""
+        best_definition = (
+            max(fused_properties["definitions"], key=len) if fused_properties["definitions"] else ""
+        )
 
         # 选择最佳名称（最常见的那个）
         from collections import Counter
@@ -374,7 +390,9 @@ class MultimodalEntityLinker:
 
         return conflicts
 
-    def suggest_entity_merges(self, entities: list[dict], existing_links: list[EntityLink] = None) -> list[dict]:
+    def suggest_entity_merges(
+        self, entities: list[dict], existing_links: list[EntityLink] = None
+    ) -> list[dict]:
         """
         建议实体合并
 
@@ -489,12 +507,16 @@ class MultimodalEntityLinker:
             "total_multimodal_records": len(multimodal_entities),
             "unique_entities": len(entity_modalities),
             "cross_modal_entities": cross_modal_count,
-            "cross_modal_ratio": cross_modal_count / len(entity_modalities) if entity_modalities else 0,
+            "cross_modal_ratio": cross_modal_count / len(entity_modalities)
+            if entity_modalities
+            else 0,
         }
 
+
 # Singleton instance
 _multimodal_entity_linker = None
 
+
 def get_multimodal_entity_linker(similarity_threshold: float = 0.85) -> MultimodalEntityLinker:
     """获取多模态实体关联器单例"""
     global _multimodal_entity_linker