Files
NexQuant/rdagent/scenarios/qlib/experiment/factor_experiment.py
T
Xu Yang 90d9cdd0e9 feat(kaggle): several update in kaggle scenarios (#476)
* udpate plot

* log and reduce token

* trace tag

* add simple_background parameter to get_scenario_all_desc

* update trace

* update first version code

* chat model map

* add annotation for stack index

* add annotation

* reformatted by black

* several update on kaggle scenarios

* update some new change

* fix CI

* fix CI

* fix a bug

* fix bugs in graph RAG

---------

Co-authored-by: Tim <illking@foxmail.com>
2024-11-06 13:14:35 +08:00

81 lines
2.7 KiB
Python

from copy import deepcopy
from pathlib import Path
from rdagent.components.coder.factor_coder.factor import (
FactorExperiment,
FactorFBWorkspace,
FactorTask,
)
from rdagent.core.experiment import Task
from rdagent.core.prompts import Prompts
from rdagent.core.scenario import Scenario
from rdagent.scenarios.qlib.experiment.utils import get_data_folder_intro
from rdagent.scenarios.qlib.experiment.workspace import QlibFBWorkspace
prompt_dict = Prompts(file_path=Path(__file__).parent / "prompts.yaml")
class QlibFactorExperiment(FactorExperiment[FactorTask, QlibFBWorkspace, FactorFBWorkspace]):
def __init__(self, *args, **kwargs) -> None:
super().__init__(*args, **kwargs)
self.experiment_workspace = QlibFBWorkspace(template_folder_path=Path(__file__).parent / "factor_template")
class QlibFactorScenario(Scenario):
def __init__(self) -> None:
super().__init__()
self._background = deepcopy(prompt_dict["qlib_factor_background"])
self._source_data = deepcopy(get_data_folder_intro())
self._output_format = deepcopy(prompt_dict["qlib_factor_output_format"])
self._interface = deepcopy(prompt_dict["qlib_factor_interface"])
self._strategy = deepcopy(prompt_dict["qlib_factor_strategy"])
self._simulator = deepcopy(prompt_dict["qlib_factor_simulator"])
self._rich_style_description = deepcopy(prompt_dict["qlib_factor_rich_style_description"])
self._experiment_setting = deepcopy(prompt_dict["qlib_factor_experiment_setting"])
@property
def background(self) -> str:
return self._background
def get_source_data_desc(self, task: Task | None = None) -> str:
return self._source_data
@property
def output_format(self) -> str:
return self._output_format
@property
def interface(self) -> str:
return self._interface
@property
def simulator(self) -> str:
return self._simulator
@property
def rich_style_description(self) -> str:
return self._rich_style_description
@property
def experiment_setting(self) -> str:
return self._experiment_setting
def get_scenario_all_desc(
self, task: Task | None = None, filtered_tag: str | None = None, simple_background: bool | None = None
) -> str:
"""A static scenario describer"""
if simple_background:
return f"""Background of the scenario:
{self.background}"""
return f"""Background of the scenario:
{self.background}
The source data you can use:
{self.get_source_data_desc(task)}
The interface you should follow to write the runnable code:
{self.interface}
The output of your code should be in the format:
{self.output_format}
The simulator user can use to test your factor:
{self.simulator}
"""