缓存上下文，表结构添加

service/cus_vanna_srevice.py

@@ -1,3 +1,4 @@
+from dataclasses import field
 from email.policy import default
 from typing import List, Union, Any, Optional
 import time
@@ -76,10 +77,10 @@ class OpenAICompatibleLLM(VannaBase):
 
         def run_sql_damengsql(sql: str) -> Union[pd.DataFrame, None]:
             logger.info(f"start to run_sql_damengsql")
-            if not is_connection_alive(conn=self.conn):
-                logger.info("connection is not alive, reconnecting..........")
-                reconnect()
             try:
+                if not is_connection_alive(conn=self.conn):
+                    logger.info("connection is not alive, reconnecting..........")
+                    reconnect()
                 # conn.ping(reconnect=True)
                 cs = self.conn.cursor()
                 cs.execute(sql)
@@ -203,7 +204,7 @@ class OpenAICompatibleLLM(VannaBase):
 
         return response.choices[0].message.content
 
-    def generate_sql_2(self, question: str, allow_llm_to_see_data=False, **kwargs) -> dict:
+    def generate_sql_2(self, question: str, cache=None,user_id=None, allow_llm_to_see_data=False, **kwargs) -> dict:
         try:
             logger.info("Start to generate_sql_2 in cus_vanna_srevice")
             question_sql_list = self.get_similar_question_sql(question, **kwargs)
@@ -215,15 +216,19 @@ class OpenAICompatibleLLM(VannaBase):
             template = get_base_template()
             sql_temp = template['template']['sql']
             char_temp = template['template']['chart']
+            history = None
+            if user_id and cache:
+                history = cache.get(id=user_id, field="data")
             # --------基于提示词，生成sql以及图表类型
             sys_temp = sql_temp['system'].format(engine=config("DB_ENGINE", default='mysql'), lang='中文',
                                                  schema=ddl_list, documentation=[train_ddl.train_document],
-                                                 retrieved_examples_data=question_sql_list,
+                                                 history=history,retrieved_examples_data=question_sql_list,
                                                  data_training=question_sql_list,)
-            logger.info(f"sys_temp:{sys_temp}")
+
             user_temp = sql_temp['user'].format(question=question,
                                                 current_time=datetime.now().strftime('%Y-%m-%d %H:%M:%S'))
             logger.info(f"user_temp:{user_temp}")
+            logger.info(f"sys_temp:{sys_temp}")
             llm_response = self.submit_prompt(
                 [{'role': 'system', 'content': sys_temp}, {'role': 'user', 'content': user_temp}], **kwargs)
             logger.info(f"llm_response:{llm_response}")