Merge pull request 'sit' (#1) from sit into test

Reviewed-on: #1

database_init_report.json

@@ -0,0 +1,9 @@
+{
+  "init_time": "2025-12-12T13:31:25.459591",
+  "database_version": "SQLite 3.43.1",
+  "database_url": "sqlite:///tsp_assistant.db",
+  "migrations_applied": 0,
+  "tables_created": 9,
+  "initial_data_inserted": true,
+  "verification_passed": true
+}

logs/tsp_assistant.log

@@ -0,0 +1,9 @@
+2025-12-12 13:30:49,040 - src.core.database - ERROR - 数据库操作失败: 'search_frequency' is an invalid keyword argument for KnowledgeEntry
+2025-12-12 13:31:25,399 - src.vehicle.vehicle_data_manager - INFO - 添加车辆数据成功: V001 - location
+2025-12-12 13:31:25,404 - src.vehicle.vehicle_data_manager - INFO - 添加车辆数据成功: V001 - status
+2025-12-12 13:31:25,409 - src.vehicle.vehicle_data_manager - INFO - 添加车辆数据成功: V001 - battery
+2025-12-12 13:31:25,414 - src.vehicle.vehicle_data_manager - INFO - 添加车辆数据成功: V001 - engine
+2025-12-12 13:31:25,419 - src.vehicle.vehicle_data_manager - INFO - 添加车辆数据成功: V002 - location
+2025-12-12 13:31:25,424 - src.vehicle.vehicle_data_manager - INFO - 添加车辆数据成功: V002 - status
+2025-12-12 13:31:25,429 - src.vehicle.vehicle_data_manager - INFO - 添加车辆数据成功: V002 - fault
+2025-12-12 13:31:25,429 - src.vehicle.vehicle_data_manager - INFO - 示例车辆数据添加成功

src/config/config.py

@@ -10,8 +10,8 @@ class Config:
     ALIBABA_MODEL_NAME = "qwen-plus-latest"
     
     # 数据库配置
-    DATABASE_URL = "mysql+pymysql://tsp_assistant:123456@jeason.online/tsp_assistant?charset=utf8mb4"
+    DATABASE_URL = "mysql+pymysql://tsp_assistant:123456@43.134.68.207/tsp_assistant?charset=utf8mb4"
-    # DATABASE_URL = "sqlite:///local_test.db"  # 本地测试数据库
+    # DATABASE_URL = "sqlite:///tsp_assistant.db"  # 本地测试数据库
     
     # 知识库配置
     KNOWLEDGE_BASE_PATH = "data/knowledge_base"

src/core/models.py

@@ -86,6 +86,9 @@ class KnowledgeEntry(Base):
     verified_by = Column(String(100))  # 验证人
     verified_at = Column(DateTime)  # 验证时间
     vector_embedding = Column(Text)  # 向量嵌入的JSON字符串
+    search_frequency = Column(Integer, default=0)  # 搜索频率
+    last_accessed = Column(DateTime)  # 最后访问时间
+    relevance_score = Column(Float, default=0.0)  # 相关性评分
 
 class VehicleData(Base):
     """车辆实时数据模型"""