fix: fix a bug in proposal (add last loop's exception to last task desc) (#596)

* fix a bug in proposal (add last loop's exception to last task desc)

* fix

rdagent/scenarios/data_science/proposal/exp_gen.py

@@ -198,15 +198,7 @@ class DSExpGen(ExpGen):
             if len(trace.hist) > 0 and trace.hist[-1] is not last_successful_exp
             else None
         )
-        resp_dict = self._init_task_gen(
-            targets=component,
-            scenario_desc=scenario_desc,
-            spec=last_successful_exp.experiment_workspace.file_dict[spec_file] if spec_file else None,
-            task_output_format=T(f".prompts:output_format.{component_prompt_key or component.lower()}").r(),
-            former_task=former_task_desc,
-        )
 
-        # Create task instance
         exp_and_feedback = trace.hist[-1] if len(trace.hist) > 0 else None
         if (
             exp_and_feedback
@@ -217,10 +209,15 @@ class DSExpGen(ExpGen):
                 and component == "Model"
             )
         ):  # Assumption: when completing missing component, using component name as task name
-            resp_dict["description"] = (
-                str(resp_dict.get("description", ""))
-                + f"\n\nYou have tried to implement the same component and got the following exception: \n{exp_and_feedback[1].exception}\n Please try different methods to avoid the same errors and results in an infinite loop"
-            )
+            former_task_desc += f"\n\nYou have tried to implement the same component and got the following exception: \n{exp_and_feedback[1].exception}\n Please try different methods to avoid the same errors and results in an infinite loop"
+
+        resp_dict = self._init_task_gen(
+            targets=component,
+            scenario_desc=scenario_desc,
+            spec=last_successful_exp.experiment_workspace.file_dict[spec_file] if spec_file else None,
+            task_output_format=T(f".prompts:output_format.{component_prompt_key or component.lower()}").r(),
+            former_task=former_task_desc,
+        )
 
         task = task_cls(
             name=component if component != "Model" else resp_dict.pop("model_name"),

rdagent/scenarios/data_science/proposal/prompts.yaml

@@ -342,7 +342,6 @@ output_format:
           },
         },
     }
-    Usually, a larger model works better than a smaller one. Hence, the parameters should be larger.
   ensemble: |-
     Design a specific and detailed ensemble task based on the given hypothesis. The output should be detailed enough to directly implement the corresponding code.
     The output should follow JSON format. The schema is as follows:

rdagent/scenarios/kaggle/prompts.yaml

@@ -173,7 +173,6 @@ model_experiment_output_format: |-
       "model_type": "Please select only **one** model type from the following four options: XGBoost, RandomForest, LightGBM, or NN. The selected model must be unique and used as the **primary model**. You may choose an auxiliary model for support or optimization on specific tasks if necessary, but the primary model must come from the provided options."
 
   }
-  Usually, a larger model works better than a smaller one. Hence, the parameters should be larger.
 
 kg_feedback_generation_user: |-
   We are in a process of finding and validating hypotheses to build a powerful model. Each round aims to confirm or reject hypotheses based on results.