mirror of
https://github.com/NicolasBohn/NexQuant.git
synced 2026-07-28 07:57:44 +00:00
Xu Yang
d5a6a08210
* 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
53 lines
1.7 KiB
Python
53 lines
1.7 KiB
Python
from pathlib import Path
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from typing import Literal, Union
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from pydantic_settings import BaseSettings
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SELECT_METHOD = Literal["random", "scheduler"]
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class FactorImplementSettings(BaseSettings):
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class Config:
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env_prefix = "FACTOR_CODER_" # Use FACTOR_CODER_ as prefix for environment variables
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coder_use_cache: bool = False
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data_folder: str = str(
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(Path().cwd() / "git_ignore_folder" / "factor_implementation_source_data").absolute(),
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)
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data_folder_debug: str = str(
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(Path().cwd() / "git_ignore_folder" / "factor_implementation_source_data_debug").absolute(),
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)
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cache_location: str = str(
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(Path().cwd() / "git_ignore_folder" / "factor_implementation_execution_cache").absolute(),
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)
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enable_execution_cache: bool = True # whether to enable the execution cache
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# TODO: the factor implement specific settings should not appear in this settings
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# Evolving should have a method specific settings
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# evolving related config
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fail_task_trial_limit: int = 20
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v1_query_former_trace_limit: int = 5
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v1_query_similar_success_limit: int = 5
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v2_query_component_limit: int = 1
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v2_query_error_limit: int = 1
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v2_query_former_trace_limit: int = 1
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v2_error_summary: bool = False
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v2_knowledge_sampler: float = 1.0
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file_based_execution_timeout: int = 120 # seconds for each factor implementation execution
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select_method: SELECT_METHOD = "random"
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select_ratio: float = 0.5
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max_loop: int = 10
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knowledge_base_path: Union[str, None] = None
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new_knowledge_base_path: Union[str, None] = None
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python_bin: str = "python"
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FACTOR_IMPLEMENT_SETTINGS = FactorImplementSettings()
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