mirror of
https://github.com/NicolasBohn/NexQuant.git
synced 2026-08-06 03:27:44 +00:00
Xu Yang
e0a24fb46f
* 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
52 lines
1.5 KiB
Python
52 lines
1.5 KiB
Python
from pathlib import Path
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from rdagent.components.coder.model_coder.model import (
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ModelExperiment,
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ModelFBWorkspace,
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ModelTask,
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)
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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.workspace import QlibFBWorkspace
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prompt_dict = Prompts(file_path=Path(__file__).parent / "prompts.yaml")
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class QlibModelExperiment(ModelExperiment[ModelTask, QlibFBWorkspace, ModelFBWorkspace]):
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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 / "model_template")
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class QlibModelScenario(Scenario):
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@property
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def background(self) -> str:
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return prompt_dict["qlib_model_background"]
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@property
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def source_data(self) -> str:
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raise NotImplementedError("source_data of QlibModelScenario is not implemented")
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@property
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def output_format(self) -> str:
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return prompt_dict["qlib_model_output_format"]
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@property
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def interface(self) -> str:
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return prompt_dict["qlib_model_interface"]
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@property
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def simulator(self) -> str:
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return prompt_dict["qlib_model_simulator"]
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def get_scenario_all_desc(self) -> str:
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return f"""Background of the scenario:
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{self.background}
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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 model:
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{self.simulator}
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"""
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