reorder import

metagpt/ext/sela/experimenter/experimenter.py

@@ -6,8 +6,8 @@ import numpy as np
 import pandas as pd
 
 from metagpt.ext.sela.evaluation.evaluation import evaluate_score
-from metagpt.ext.sela.search.tree_search import create_initial_state
 from metagpt.ext.sela.research_assistant import ResearchAssistant
+from metagpt.ext.sela.search.tree_search import create_initial_state
 from metagpt.ext.sela.utils import DATA_CONFIG, save_notebook
 
 

metagpt/ext/sela/experimenter/mcts.py

@@ -6,7 +6,7 @@ from metagpt.ext.sela.evaluation.evaluation import (
 )
 from metagpt.ext.sela.evaluation.visualize_mcts import get_tree_text
 from metagpt.ext.sela.experimenter.experimenter import Experimenter
-from metagpt.ext.sela.search.search_algorithm import Greedy, Random, MCTS
+from metagpt.ext.sela.search.search_algorithm import MCTS, Greedy, Random
 
 
 class MCTSExperimenter(Experimenter):

metagpt/ext/sela/research_assistant.py

@@ -6,9 +6,9 @@ import os
 
 from pydantic import model_validator
 
-from metagpt.ext.sela.utils import mcts_logger, save_notebook
 from metagpt.actions.di.write_analysis_code import WriteAnalysisCode
 from metagpt.const import SERDESER_PATH
+from metagpt.ext.sela.utils import mcts_logger, save_notebook
 from metagpt.roles.di.data_interpreter import DataInterpreter
 from metagpt.schema import Message, Task, TaskResult
 from metagpt.utils.common import CodeParser, write_json_file

metagpt/ext/sela/run_experiment.py

@@ -2,12 +2,12 @@ import argparse
 import asyncio
 
 from metagpt.ext.sela.data.custom_task import get_mle_is_lower_better, get_mle_task_id
-from metagpt.ext.sela.experimenter.random_search import RandomSearchExperimenter
 from metagpt.ext.sela.experimenter.autogluon import GluonExperimenter
 from metagpt.ext.sela.experimenter.autosklearn import AutoSklearnExperimenter
 from metagpt.ext.sela.experimenter.custom import CustomExperimenter
 from metagpt.ext.sela.experimenter.experimenter import Experimenter
 from metagpt.ext.sela.experimenter.mcts import MCTSExperimenter
+from metagpt.ext.sela.experimenter.random_search import RandomSearchExperimenter
 
 
 def get_args(cmd=True):

metagpt/ext/sela/search/search_algorithm.py

@@ -1,4 +1,5 @@
 import numpy as np
+
 from metagpt.ext.sela.search.tree_search import BaseTreeSearch, Node
 
 

metagpt/ext/sela/search/tree_search.py

@@ -6,8 +6,14 @@ import shutil
 import numpy as np
 import pandas as pd
 
-from metagpt.ext.sela.data.custom_task import get_mle_bench_requirements, get_mle_task_id
-from metagpt.ext.sela.data.dataset import generate_task_requirement, get_split_dataset_path
+from metagpt.ext.sela.data.custom_task import (
+    get_mle_bench_requirements,
+    get_mle_task_id,
+)
+from metagpt.ext.sela.data.dataset import (
+    generate_task_requirement,
+    get_split_dataset_path,
+)
 from metagpt.ext.sela.evaluation.evaluation import evaluate_score
 from metagpt.ext.sela.insights.instruction_generator import InstructionGenerator
 from metagpt.ext.sela.research_assistant import ResearchAssistant, TimeoutException
@@ -57,9 +63,9 @@ def create_initial_state(task: str, start_task_id: int, data_config: dict, args)
     Args:
         task (str): The task to be performed.
         start_task_id (int): The ID of the starting task.
-        data_config (dict): The configuration of the data. 
+        data_config (dict): The configuration of the data.
             Expected keys: 'datasets', 'work_dir', 'role_dir'.
-        args (Namespace): The arguments passed to the program. 
+        args (Namespace): The arguments passed to the program.
             Expected attributes: 'external_eval', 'custom_dataset_dir', 'special_instruction', 'name', 'low_is_better', 'role_timeout'.
 
     Returns:
@@ -104,6 +110,7 @@ def create_initial_state(task: str, start_task_id: int, data_config: dict, args)
     os.makedirs(initial_state["node_dir"], exist_ok=True)
     return initial_state
 
+
 class Node:
     state: dict = {}
     action: str = None
@@ -113,7 +120,9 @@ class Node:
     normalized_reward: dict = {"train_score": 0, "dev_score": 0, "test_score": 0}
     parent = None
 
-    def __init__(self, parent=None, state: dict = None, action: str = None, value: float = 0, max_depth: int = 4, **kwargs):
+    def __init__(
+        self, parent=None, state: dict = None, action: str = None, value: float = 0, max_depth: int = 4, **kwargs
+    ):
         self.state = state
         self.action = action
         self.value = value
@@ -306,8 +315,6 @@ class Node:
         return score_dict, result_dict
 
 
-
-
 class BaseTreeSearch:
     # data_path
     root_node: Node = None