Several update on the repo (see desc) (#76)

* ignore result csv file

* fix app scripts

* rename taskgenerator to developer and generate to develop

* fix a config bug in coder

* fix a small bug in factor coder evaluators

* remove a single logger in factor coder evaluators

* fix a small bug in model coder main.py

* rename Implementation to Workspace

* move the prepare the inject_code into FBWorkspace to align all the behavior

* fix a small bug in model feedback

* remove debug lines for multi processing and simplify evaluators multi proc

* add a copy function to workspace to freeze the workspace && add config prefix to speed up debugging

* make hypothesisgen a abc class

* use Qlib***Experiment

* fix a small bug

* rename Imp to Ws

* rename sub_implementations to sub_workspace_list

* fix a bug in feedback not presented as content in prompts

* move proposal pys to proposal folder

* reformat the folder

* align factor and model qlib workspace and use template to handle the workspace

* add a filter to evoagent to filter out false evo

* align multi_proc_n into RDAGENT seeting

* handle when runner gets empty experiment

* fix logger merge remaining problems

* fix black and isort automatically

rdagent/components/coder/model_coder/CoSTEER/knowledge_management.py

@@ -9,7 +9,7 @@ from rdagent.core.evolving_framework import (
     QueriedKnowledge,
     RAGStrategy,
 )
-from rdagent.core.experiment import Implementation
+from rdagent.core.experiment import Workspace
 from rdagent.oai.llm_utils import calculate_embedding_distance_between_str_list
 
 
@@ -17,7 +17,7 @@ class ModelKnowledge(Knowledge):
     def __init__(
         self,
         target_task: ModelTask,
-        implementation: Implementation,
+        implementation: Workspace,
         feedback: ModelCoderFeedback,
     ) -> None:
         """
@@ -30,7 +30,7 @@ class ModelKnowledge(Knowledge):
             None
         """
         self.target_task = target_task
-        self.implementation = implementation
+        self.implementation = implementation.copy()
         self.feedback = feedback
 
     def get_implementation_and_feedback_str(self) -> str:
@@ -87,7 +87,7 @@ class ModelRAGStrategy(RAGStrategy):
                 for task_index in range(len(implementations.sub_tasks)):
                     target_task = implementations.sub_tasks[task_index]
                     target_task_information = target_task.get_task_information()
-                    implementation = implementations.sub_implementations[task_index]
+                    implementation = implementations.sub_workspace_list[task_index]
                     single_feedback = feedback[task_index]
                     if single_feedback is None:
                         continue
@@ -121,9 +121,9 @@ class ModelRAGStrategy(RAGStrategy):
         for target_model_task in evo.sub_tasks:
             target_model_task_information = target_model_task.get_task_information()
             if target_model_task_information in self.knowledgebase.success_task_info_set:
-                queried_knowledge.success_task_to_knowledge_dict[target_model_task_information] = (
-                    self.knowledgebase.implementation_trace[target_model_task_information][-1]
-                )
+                queried_knowledge.success_task_to_knowledge_dict[
+                    target_model_task_information
+                ] = self.knowledgebase.implementation_trace[target_model_task_information][-1]
             elif (
                 len(
                     self.knowledgebase.implementation_trace.setdefault(
@@ -135,12 +135,14 @@ class ModelRAGStrategy(RAGStrategy):
             ):
                 queried_knowledge.failed_task_info_set.add(target_model_task_information)
             else:
-                queried_knowledge.working_task_to_former_failed_knowledge_dict[target_model_task_information] = (
-                    self.knowledgebase.implementation_trace.setdefault(
-                        target_model_task_information,
-                        [],
-                    )[-query_former_trace_limit:]
-                )
+                queried_knowledge.working_task_to_former_failed_knowledge_dict[
+                    target_model_task_information
+                ] = self.knowledgebase.implementation_trace.setdefault(
+                    target_model_task_information,
+                    [],
+                )[
+                    -query_former_trace_limit:
+                ]
 
                 knowledge_base_success_task_list = list(
                     self.knowledgebase.success_task_info_set,
@@ -161,7 +163,7 @@ class ModelRAGStrategy(RAGStrategy):
                     )[-1]
                     for index in similar_indexes
                 ]
-                queried_knowledge.working_task_to_similar_successful_knowledge_dict[target_model_task_information] = (
-                    similar_successful_knowledge
-                )
+                queried_knowledge.working_task_to_similar_successful_knowledge_dict[
+                    target_model_task_information
+                ] = similar_successful_knowledge
         return queried_knowledge