diff --git a/metagpt/roles/di/data_interpreter.py b/metagpt/roles/di/data_interpreter.py
index a8534b710..16875a42e 100644
--- a/metagpt/roles/di/data_interpreter.py
+++ b/metagpt/roles/di/data_interpreter.py
@@ -43,66 +43,66 @@ class DataInterpreter(Role):
     tool_recommender: ToolRecommender = None
     react_mode: Literal["plan_and_act", "react"] = "plan_and_act"
     max_react_loop: int = 10  # used for react mode
-
+    
     @model_validator(mode="after")
     def set_plan_and_tool(self) -> "Interpreter":
         self._set_react_mode(react_mode=self.react_mode, max_react_loop=self.max_react_loop, auto_run=self.auto_run)
         self.use_plan = (
-            self.react_mode == "plan_and_act"
+                self.react_mode == "plan_and_act"
         )  # create a flag for convenience, overwrite any passed-in value
         if self.tools:
             self.tool_recommender = BM25ToolRecommender(tools=self.tools)
         self.set_actions([WriteAnalysisCode])
         self._set_state(0)
         return self
-
+    
     @property
     def working_memory(self):
         return self.rc.working_memory
-
+    
     async def _think(self) -> bool:
         """Useful in 'react' mode. Use LLM to decide whether and what to do next."""
         user_requirement = self.get_memories()[0].content
         context = self.working_memory.get()
-
+        
         if not context:
             # just started the run, we need action certainly
             self.working_memory.add(self.get_memories()[0])  # add user requirement to working memory
             self._set_state(0)
             return True
-
+        
         prompt = REACT_THINK_PROMPT.format(user_requirement=user_requirement, context=context)
         rsp = await self.llm.aask(prompt)
         rsp_dict = json.loads(CodeParser.parse_code(block=None, text=rsp))
         self.working_memory.add(Message(content=rsp_dict["thoughts"], role="assistant"))
         need_action = rsp_dict["state"]
         self._set_state(0) if need_action else self._set_state(-1)
-
+        
         return need_action
-
+    
     async def _act(self) -> Message:
         """Useful in 'react' mode. Return a Message conforming to Role._act interface."""
         code, _, _ = await self._write_and_exec_code()
         return Message(content=code, role="assistant", cause_by=WriteAnalysisCode)
-
+    
     async def _plan_and_act(self) -> Message:
         rsp = await super()._plan_and_act()
         await self.execute_code.terminate()
         return rsp
-
+    
     async def _act_on_task(self, current_task: Task) -> TaskResult:
         """Useful in 'plan_and_act' mode. Wrap the output in a TaskResult for review and confirmation."""
         code, result, is_success = await self._write_and_exec_code()
         task_result = TaskResult(code=code, result=result, is_success=is_success)
         return task_result
-
+    
     async def _write_and_exec_code(self, max_retry: int = 3):
         counter = 0
         success = False
-
+        
         # plan info
         plan_status = self.planner.get_plan_status() if self.use_plan else ""
-
+        
         # tool info
         if self.tools:
             context = (
@@ -112,45 +112,46 @@ class DataInterpreter(Role):
             tool_info = await self.tool_recommender.get_recommended_tool_info(context=context, plan=plan)
         else:
             tool_info = ""
-
+        
         # data info
         await self._check_data()
-
+        
         while not success and counter < max_retry:
             ### write code ###
             code, cause_by = await self._write_code(counter, plan_status, tool_info)
-
+            
             self.working_memory.add(Message(content=code, role="assistant", cause_by=cause_by))
-
+            
             ### execute code ###
+            import pdb;pdb.set_trace()
             result, success = await self.execute_code.run(code)
             print(result)
-
+            
             self.working_memory.add(Message(content=result, role="user", cause_by=ExecuteNbCode))
-
+            
             ### process execution result ###
             counter += 1
-
+            
             if not success and counter >= max_retry:
                 logger.info("coding failed!")
                 review, _ = await self.planner.ask_review(auto_run=False, trigger=ReviewConst.CODE_REVIEW_TRIGGER)
                 if ReviewConst.CHANGE_WORDS[0] in review:
                     counter = 0  # redo the task again with help of human suggestions
-
+        
         return code, result, success
-
+    
     async def _write_code(
-        self,
-        counter: int,
-        plan_status: str = "",
-        tool_info: str = "",
+            self,
+            counter: int,
+            plan_status: str = "",
+            tool_info: str = "",
     ):
         todo = self.rc.todo  # todo is WriteAnalysisCode
         logger.info(f"ready to {todo.name}")
         use_reflection = counter > 0 and self.use_reflection  # only use reflection after the first trial
-
+        
         user_requirement = self.get_memories()[0].content
-
+        
         code = await todo.run(
             user_requirement=user_requirement,
             plan_status=plan_status,
@@ -158,19 +159,19 @@ class DataInterpreter(Role):
             working_memory=self.working_memory.get(),
             use_reflection=use_reflection,
         )
-
+        
         return code, todo
-
+    
     async def _check_data(self):
         if (
-            not self.use_plan
-            or not self.planner.plan.get_finished_tasks()
-            or self.planner.plan.current_task.task_type
-            not in [
-                TaskType.DATA_PREPROCESS.type_name,
-                TaskType.FEATURE_ENGINEERING.type_name,
-                TaskType.MODEL_TRAIN.type_name,
-            ]
+                not self.use_plan
+                or not self.planner.plan.get_finished_tasks()
+                or self.planner.plan.current_task.task_type
+                not in [
+            TaskType.DATA_PREPROCESS.type_name,
+            TaskType.FEATURE_ENGINEERING.type_name,
+            TaskType.MODEL_TRAIN.type_name,
+        ]
         ):
             return
         logger.info("Check updated data")
@@ -182,3 +183,6 @@ class DataInterpreter(Role):
             print(result)
             data_info = DATA_INFO.format(info=result)
             self.working_memory.add(Message(content=data_info, role="user", cause_by=CheckData))
+    
+    def get_last_cell_source(self):
+        return self.execute_code.nb.cells[-1].source