from rdagent.app.kaggle.conf import KaggleBasePropSetting from rdagent.core.conf import ExtendedSettingsConfigDict class DataScienceBasePropSetting(KaggleBasePropSetting): model_config = ExtendedSettingsConfigDict(env_prefix="DS_", protected_namespaces=()) # Main components ## Scen scen: str = "rdagent.scenarios.data_science.scen.KaggleScen" """Scenario class for data mining model""" ## proposal exp_gen: str = "rdagent.scenarios.data_science.proposal.exp_gen.DSExpGen" # exp_gen_init_kwargs: dict = {"max_trace_hist": 3} # TODO: to be configurable # the two below should be used in ExpGen # hypothesis_gen: str = "rdagent.scenarios.kaggle.proposal.proposal.KGHypothesisGen" # """Hypothesis generation class""" # # hypothesis2experiment: str = "rdagent.scenarios.kaggle.proposal.proposal.KGHypothesis2Experiment" # """Hypothesis to experiment class""" ## dev/coder data_loader_coder: str = "rdagent.components.coder.data_science.raw_data_loader.DataLoaderCoSTEER" """Data Loader CoSTEER""" # feature_coder: str = "rdagent.scenarios.kaggle.developer.coder.KGFactorCoSTEER" # """Feature Coder class""" # model_feature_selection_coder: str = "rdagent.scenarios.kaggle.developer.coder.KGModelFeatureSelectionCoder" # """Model Feature Selection Coder class""" # model_coder: str = "rdagent.scenarios.kaggle.developer.coder.KGModelCoSTEER" # """Model Coder class""" ## dev/runner feature_runner: str = "rdagent.scenarios.kaggle.developer.runner.KGFactorRunner" """Feature Runner class""" model_runner: str = "rdagent.scenarios.kaggle.developer.runner.KGModelRunner" """Model Runner class""" ## feedback summarizer: str = "rdagent.scenarios.kaggle.developer.feedback.KGExperiment2Feedback" """Summarizer class""" ## Workflow Related consecutive_errors: int = 5 debug_timeout: int = 600 """The timeout limit for running on debugging data""" full_timeout: int = 3600 """The timeout limit for running on full data""" DS_RD_SETTING = DataScienceBasePropSetting()