Files
NexQuant/rdagent/components/coder/factor_coder/__init__.py
T
you-n-g ffc85936f1 refactor: refactor core framework to better propogate feedbacks (#599)
* refactor: Update type annotations and remove unused class in evolving modules

* refactor: Simplify evolving agent and feedback handling in CoSTEER module

* lint & CI

* mypy

* ruff for core

* mypy

* refactor: remove unnecessary comments and update feedback handling logic

* refactor: Add prev_task_feedback parameter to evolving strategies

* feat: Clear folder before extracting zip file in DockerEnv

* fix: Correct retrieval of last experiment from history
2025-02-16 01:40:44 +08:00

32 lines
1.2 KiB
Python

from rdagent.components.coder.CoSTEER import CoSTEER
from rdagent.components.coder.CoSTEER.evaluators import CoSTEERMultiEvaluator
from rdagent.components.coder.factor_coder.config import FACTOR_COSTEER_SETTINGS
from rdagent.components.coder.factor_coder.evaluators import FactorEvaluatorForCoder
from rdagent.components.coder.factor_coder.evolving_strategy import (
FactorMultiProcessEvolvingStrategy,
)
from rdagent.core.experiment import Experiment
from rdagent.core.scenario import Scenario
class FactorCoSTEER(CoSTEER):
def __init__(
self,
scen: Scenario,
*args,
**kwargs,
) -> None:
setting = FACTOR_COSTEER_SETTINGS
eva = CoSTEERMultiEvaluator(FactorEvaluatorForCoder(scen=scen), scen=scen)
es = FactorMultiProcessEvolvingStrategy(scen=scen, settings=FACTOR_COSTEER_SETTINGS)
super().__init__(*args, settings=setting, eva=eva, es=es, evolving_version=2, scen=scen, **kwargs)
def develop(self, exp: Experiment) -> Experiment:
try:
exp = super().develop(exp)
finally:
es = self.evolve_agent.evolving_trace[-1]
exp.prop_dev_feedback = es.feedback
return exp