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/ai_manager.py

@@ -291,7 +291,7 @@ class AIManager:
             return self._row_to_custom_model(row)
 
     def list_custom_models(
-        self, tenant_id: str, model_type: ModelType | None = None, status: ModelStatus | None = None
+        self, tenant_id: str, model_type: ModelType | None = None, status: ModelStatus | None = None,
     ) -> list[CustomModel]:
         """列出自定义模型"""
         query = "SELECT * FROM custom_models WHERE tenant_id = ?"
@@ -311,7 +311,7 @@ class AIManager:
             return [self._row_to_custom_model(row) for row in rows]
 
     def add_training_sample(
-        self, model_id: str, text: str, entities: list[dict], metadata: dict = None
+        self, model_id: str, text: str, entities: list[dict], metadata: dict = None,
     ) -> TrainingSample:
         """添加训练样本"""
         sample_id = f"ts_{uuid.uuid4().hex[:16]}"
@@ -638,7 +638,7 @@ class AIManager:
             }
 
     def get_multimodal_analyses(
-        self, tenant_id: str, project_id: str | None = None
+        self, tenant_id: str, project_id: str | None = None,
     ) -> list[MultimodalAnalysis]:
         """获取多模态分析历史"""
         query = "SELECT * FROM multimodal_analyses WHERE tenant_id = ?"
@@ -721,7 +721,7 @@ class AIManager:
             return self._row_to_kg_rag(row)
 
     def list_kg_rags(
-        self, tenant_id: str, project_id: str | None = None
+        self, tenant_id: str, project_id: str | None = None,
     ) -> list[KnowledgeGraphRAG]:
         """列出知识图谱 RAG 配置"""
         query = "SELECT * FROM kg_rag_configs WHERE tenant_id = ?"
@@ -738,7 +738,7 @@ class AIManager:
             return [self._row_to_kg_rag(row) for row in rows]
 
     async def query_kg_rag(
-        self, rag_id: str, query: str, project_entities: list[dict], project_relations: list[dict]
+        self, rag_id: str, query: str, project_entities: list[dict], project_relations: list[dict],
     ) -> RAGQuery:
         """基于知识图谱的 RAG 查询"""
         start_time = time.time()
@@ -1123,7 +1123,7 @@ class AIManager:
         """获取预测模型"""
         with self._get_db() as conn:
             row = conn.execute(
-                "SELECT * FROM prediction_models WHERE id = ?", (model_id,)
+                "SELECT * FROM prediction_models WHERE id = ?", (model_id,),
             ).fetchone()
 
             if not row:
@@ -1132,7 +1132,7 @@ class AIManager:
             return self._row_to_prediction_model(row)
 
     def list_prediction_models(
-        self, tenant_id: str, project_id: str | None = None
+        self, tenant_id: str, project_id: str | None = None,
     ) -> list[PredictionModel]:
         """列出预测模型"""
         query = "SELECT * FROM prediction_models WHERE tenant_id = ?"
@@ -1149,7 +1149,7 @@ class AIManager:
             return [self._row_to_prediction_model(row) for row in rows]
 
     async def train_prediction_model(
-        self, model_id: str, historical_data: list[dict]
+        self, model_id: str, historical_data: list[dict],
     ) -> PredictionModel:
         """训练预测模型"""
         model = self.get_prediction_model(model_id)
@@ -1369,7 +1369,7 @@ class AIManager:
         predicted_relations = [
             {"type": rel_type, "likelihood": min(count / len(relation_history), 0.95)}
             for rel_type, count in sorted(
-                relation_counts.items(), key=lambda x: x[1], reverse=True
+                relation_counts.items(), key=lambda x: x[1], reverse=True,
             )[:5]
         ]
 
@@ -1394,7 +1394,7 @@ class AIManager:
             return [self._row_to_prediction_result(row) for row in rows]
 
     def update_prediction_feedback(
-        self, prediction_id: str, actual_value: str, is_correct: bool
+        self, prediction_id: str, actual_value: str, is_correct: bool,
     ) -> None:
         """更新预测反馈（用于模型改进）"""
         with self._get_db() as conn: