mirror of
https://github.com/NicolasBohn/NexQuant.git
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you-n-g
7fc53940fd
* OAI api * more comments * llm utils * RD-Framework for dynamic scen * remove useless code * auto lint * fix dynamic scennario * Add parameter * auto lint * remove abstractmethod * fix lint
76 lines
2.6 KiB
Python
76 lines
2.6 KiB
Python
from copy import deepcopy
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from pathlib import Path
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from rdagent.components.coder.factor_coder.factor import (
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FactorExperiment,
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FactorFBWorkspace,
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FactorTask,
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)
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from rdagent.core.experiment import Task
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from rdagent.core.prompts import Prompts
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from rdagent.core.scenario import Scenario
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from rdagent.scenarios.qlib.experiment.utils import get_data_folder_intro
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from rdagent.scenarios.qlib.experiment.workspace import QlibFBWorkspace
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prompt_dict = Prompts(file_path=Path(__file__).parent / "prompts.yaml")
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class QlibFactorExperiment(FactorExperiment[FactorTask, QlibFBWorkspace, FactorFBWorkspace]):
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def __init__(self, *args, **kwargs) -> None:
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super().__init__(*args, **kwargs)
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self.experiment_workspace = QlibFBWorkspace(template_folder_path=Path(__file__).parent / "factor_template")
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class QlibFactorScenario(Scenario):
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def __init__(self) -> None:
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super().__init__()
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self._background = deepcopy(prompt_dict["qlib_factor_background"])
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self._source_data = deepcopy(get_data_folder_intro())
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self._output_format = deepcopy(prompt_dict["qlib_factor_output_format"])
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self._interface = deepcopy(prompt_dict["qlib_factor_interface"])
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self._strategy = deepcopy(prompt_dict["qlib_factor_strategy"])
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self._simulator = deepcopy(prompt_dict["qlib_factor_simulator"])
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self._rich_style_description = deepcopy(prompt_dict["qlib_factor_rich_style_description"])
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self._experiment_setting = deepcopy(prompt_dict["qlib_factor_experiment_setting"])
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@property
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def background(self) -> str:
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return self._background
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def get_source_data_desc(self, task: Task | None = None) -> str:
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return self._source_data
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@property
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def output_format(self) -> str:
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return self._output_format
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@property
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def interface(self) -> str:
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return self._interface
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@property
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def simulator(self) -> str:
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return self._simulator
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@property
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def rich_style_description(self) -> str:
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return self._rich_style_description
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@property
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def experiment_setting(self) -> str:
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return self._experiment_setting
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def get_scenario_all_desc(self, task: Task | None = None) -> str:
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"""A static scenario describer"""
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return f"""Background of the scenario:
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{self.background}
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The source data you can use:
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{self.get_source_data_desc(task)}
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The interface you should follow to write the runnable code:
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{self.interface}
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The output of your code should be in the format:
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{self.output_format}
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The simulator user can use to test your factor:
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{self.simulator}
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"""
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