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/multimodal_entity_linker.py

@@ -5,7 +5,6 @@ InsightFlow Multimodal Entity Linker - Phase 7
 """
 
 import uuid
-from typing import List, Dict, Optional, Tuple, Set
 from dataclasses import dataclass
 from difflib import SequenceMatcher
 
@@ -28,7 +27,7 @@ class MultimodalEntity:
     source_id: str
     mention_context: str
     confidence: float
-    modality_features: Dict = None  # 模态特定特征
+    modality_features: dict = None  # 模态特定特征
 
     def __post_init__(self):
         if self.modality_features is None:
@@ -55,7 +54,7 @@ class AlignmentResult:
     """对齐结果"""
 
     entity_id: str
-    matched_entity_id: Optional[str]
+    matched_entity_id: str | None
     similarity: float
     match_type: str  # exact, fuzzy, embedding
     confidence: float
@@ -66,9 +65,9 @@ class FusionResult:
     """知识融合结果"""
 
     canonical_entity_id: str
-    merged_entity_ids: List[str]
-    fused_properties: Dict
-    source_modalities: List[str]
+    merged_entity_ids: list[str]
+    fused_properties: dict
+    source_modalities: list[str]
     confidence: float
 
 
@@ -117,7 +116,7 @@ class MultimodalEntityLinker:
         # 编辑距离相似度
         return SequenceMatcher(None, s1, s2).ratio()
 
-    def calculate_entity_similarity(self, entity1: Dict, entity2: Dict) -> Tuple[float, str]:
+    def calculate_entity_similarity(self, entity1: dict, entity2: dict) -> tuple[float, str]:
         """
         计算两个实体的综合相似度
 
@@ -159,8 +158,8 @@ class MultimodalEntityLinker:
         return combined_sim, "none"
 
     def find_matching_entity(
-        self, query_entity: Dict, candidate_entities: List[Dict], exclude_ids: Set[str] = None
-    ) -> Optional[AlignmentResult]:
+        self, query_entity: dict, candidate_entities: list[dict], exclude_ids: set[str] = None
+    ) -> AlignmentResult | None:
         """
         在候选实体中查找匹配的实体
 
@@ -201,11 +200,11 @@ class MultimodalEntityLinker:
     def align_cross_modal_entities(
         self,
         project_id: str,
-        audio_entities: List[Dict],
-        video_entities: List[Dict],
-        image_entities: List[Dict],
-        document_entities: List[Dict],
-    ) -> List[EntityLink]:
+        audio_entities: list[dict],
+        video_entities: list[dict],
+        image_entities: list[dict],
+        document_entities: list[dict],
+    ) -> list[EntityLink]:
         """
         跨模态实体对齐
 
@@ -259,7 +258,7 @@ class MultimodalEntityLinker:
         return links
 
     def fuse_entity_knowledge(
-        self, entity_id: str, linked_entities: List[Dict], multimodal_mentions: List[Dict]
+        self, entity_id: str, linked_entities: list[dict], multimodal_mentions: list[dict]
     ) -> FusionResult:
         """
         融合多模态实体知识
@@ -331,7 +330,7 @@ class MultimodalEntityLinker:
             confidence=min(1.0, len(linked_entities) * 0.2 + 0.5),
         )
 
-    def detect_entity_conflicts(self, entities: List[Dict]) -> List[Dict]:
+    def detect_entity_conflicts(self, entities: list[dict]) -> list[dict]:
         """
         检测实体冲突（同名但不同义）
 
@@ -380,7 +379,7 @@ 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
 
@@ -464,7 +463,7 @@ class MultimodalEntityLinker:
             confidence=confidence,
         )
 
-    def analyze_modality_distribution(self, multimodal_entities: List[MultimodalEntity]) -> Dict:
+    def analyze_modality_distribution(self, multimodal_entities: list[MultimodalEntity]) -> dict:
         """
         分析模态分布