同步合理数据库字段

rag2_0/demo/heli_db_to_excel.py

@@ -35,6 +35,46 @@ logging.basicConfig(
 )
 logger = logging.getLogger(__name__)
 
+def parse_session_tags(input_string):
+    """
+    解析sessionTag格式的字符串，支持任意数量的sessionTag
+    支持格式：sessionTagFirst, sessionTagSecond, sessionTagThird, sessionTagFourth 等
+    """
+    # 去除外层的方括号和引号
+    cleaned_string = input_string.strip('[]"')
+    
+    # 使用正则表达式匹配所有的sessionTag
+    # 匹配模式：sessionTag + 任意后缀 + = + 花括号内容
+    pattern = r'sessionTag(\w+)=\{([^}]+)\}'
+    matches = re.findall(pattern, cleaned_string)
+    
+    result = {}
+    
+    for tag_suffix, content in matches:
+        # 解析每个tag的内容
+        tag_data = {}
+        
+        # 提取键值对，支持中文和各种字符
+        kv_pattern = r'(\w+)=([^,}]+?)(?=,\s*\w+=|$|,\s*$)'
+        kv_matches = re.findall(kv_pattern, content)
+        
+        for key, value in kv_matches:
+            # 清理值的空白字符
+            cleaned_value = value.strip()
+            
+            # 尝试转换数据类型
+            if cleaned_value.isdigit():
+                tag_data[key] = int(cleaned_value)
+            elif cleaned_value.lower() in ['true', 'false']:
+                tag_data[key] = cleaned_value.lower() == 'true'
+            else:
+                tag_data[key] = cleaned_value
+        
+        # 构造完整的sessionTag键名
+        session_key = f'sessionTag{tag_suffix}'
+        result[session_key] = tag_data
+    
+    return result
 
 @dataclass
 class DatabaseConfig:
@@ -228,7 +268,23 @@ class DataProcessor:
         return clean_text.strip()
     
     @staticmethod
-    def messages_df_to_list(messages_df: pd.DataFrame) -> List[Dict[str, Any]]:
+    def get_session_tag_dict(json_data: str) -> dict:
+        """解析JSON数据获取会话标签字典"""
+        try:
+            json_data_dict = json.loads(json_data)
+            session_tag_list_str = json_data_dict.get('sessionMultiTagList', None)
+            if not session_tag_list_str:
+                return {}
+            
+            result = parse_session_tags(session_tag_list_str)   
+            return result
+                
+        except (json.JSONDecodeError, Exception) as e:
+            logger.error(f"解析会话标签时出错: {e}")
+            return {}
+    
+    @staticmethod
+    def messages_df_to_list(messages_df: pd.DataFrame, session_row) -> List[Dict[str, Any]]:
         """将消息DataFrame转换为字典列表，使用高效的向量化操作"""
         if messages_df.empty:
             return []
@@ -249,6 +305,9 @@ class DataProcessor:
             axis=1
         )
         
+        json_data = session_row['JSON']
+        session_tag_dict = DataProcessor.get_session_tag_dict(json_data)
+        
         # 处理内容
         def process_content(row):
             content = row["CONTENT"]
@@ -270,7 +329,9 @@ class DataProcessor:
             # 如果上一条消息和当前消息的发送者、创建时间、消息内容相同，则跳过
             if result and result[-1]['会话id'] == record['SESSION_ID'] and result[-1]['消息发送者'] == record['message_sender'] and result[-1]['创建时间'] == record['CREATE_TIME'] and result[-1]['消息内容'] == record['processed_content']:
                 continue
-            result.append({
+            
+            # 创建消息字典
+            message_dict = {
                 "账号id": record["ACCOUNT"],
                 "会话id": record["SESSION_ID"],
                 "消息内容": record["processed_content"],
@@ -278,7 +339,19 @@ class DataProcessor:
                 "发送者昵称": record["sender_nickname"],
                 "创建时间": record["CREATE_TIME"],
                 "SEQUENCE_ID": record["SEQUENCE_ID"],
-            })
+            }
+            
+            # 添加标签信息（如果有）
+            if session_tag_dict:
+                if 'sessionTagFirst' in session_tag_dict:
+                    first_tag = session_tag_dict['sessionTagFirst']
+                    message_dict["一级标签"] = first_tag.get('tagName', '')
+                
+                if 'sessionTagSecond' in session_tag_dict:
+                    second_tag = session_tag_dict['sessionTagSecond']
+                    message_dict["二级标签"] = second_tag.get('tagName', '')
+            
+            result.append(message_dict)
         
         return result
 
@@ -327,7 +400,7 @@ class MariaDBClient:
         """查询指定日期范围内的会话数据"""
         sql = """
         SELECT ACCOUNT, BEGIN_TIME, END_TIME, CUST_SEND_MESSAGE_COUNT, 
-               AGENT_SEND_MESSAGE_COUNT, STATUS, CHANNEL_NAME, SESSION_ID, SESSION_TAG_NAME
+               AGENT_SEND_MESSAGE_COUNT, STATUS, CHANNEL_NAME, SESSION_ID, SESSION_TAG_NAME, JSON
         FROM crm_hlyj.crm_hlyj_dsri
         WHERE BEGIN_TIME >= %s 
           AND BEGIN_TIME < %s
@@ -439,7 +512,7 @@ class SessionProcessor:
                 messages_df = self.db_client.query_messages_by_session_id(session_id)
                 
                 if messages_df is not None and not messages_df.empty:
-                    conversation = self.db_client.data_processor.messages_df_to_list(messages_df)
+                    conversation = self.db_client.data_processor.messages_df_to_list(messages_df, session_row)
                     if conversation:
                         return conversation
             except Exception as e:
@@ -494,8 +567,8 @@ def main() -> None:
         # 创建数据库客户端
         with MariaDBClient(config, max_connections=12) as db_client:
             # 查询会话数据
-            start_date = '2025-06-12 00:00:00'
+            start_date = '2025-08-01 00:00:00'
-            end_date = '2025-07-01 00:00:00'
+            end_date = '2025-08-01 23:00:00'
             
             logger.info(f"查询时间范围: {start_date} 到 {end_date}")
             # 创建会话处理器

rag2_0/intent_recognition/PromptTemplates.py

@@ -39,7 +39,7 @@ classification_info="""【垂直领域分类】：
 2. 故障排查：软件运行异常、软件报错、软件显示错误等
 
 【业务问题包括以下两类】：
-1. 专业咨询：涉及电力造价规范、工程计价规则问题、行业标准解读等
+1. 专业咨询：涉及电力造价规范、工程计价规则问题、行业标准解读、定额套用、建筑问题等
 2. 数据问题：涉及电力造价费用、造价指标的计算或构成等
 
 【安装下载注册包括以下三类】：