mirror of
https://github.com/NicolasBohn/NexQuant.git
synced 2026-08-01 17:37:43 +00:00
Tim
46dec7b624
* custom data * fix: simplify competition check and log local description file * no sample data * feat: add test evaluation module with error handling support * fix: update eval path to use eval_sub_dir and add valid_check TODO * refactor: add MLETestEval check to conditionally run grading steps * avoid blank stdout * valid in testeval * rename test.csv to avoid conflict * Support Disabling sample submission * refactoring * fix: remove DS_KAGGLE_DATA and update prompt instructions * add try for grade * ignore submission * fix: remove tee from eval command and warn about pipeline exit code detection * optional to use raw description * support old data * add execution result to stdout * add metric to raw description * custom data explain * add debug_path * rst update --------- Co-authored-by: Young <afe.young@gmail.com>
70 lines
2.1 KiB
Python
70 lines
2.1 KiB
Python
from typing import Literal
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from pydantic_settings import SettingsConfigDict
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from rdagent.app.kaggle.conf import KaggleBasePropSetting
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class DataScienceBasePropSetting(KaggleBasePropSetting):
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# TODO: Kaggle Setting should be the subclass of DataScience
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model_config = SettingsConfigDict(env_prefix="DS_", protected_namespaces=())
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# Main components
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## Scen
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scen: str = "rdagent.scenarios.data_science.scen.KaggleScen"
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"""Scenario class for data mining model"""
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## Workflow Related
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consecutive_errors: int = 5
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## Coding Related
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coding_fail_reanalyze_threshold: int = 3
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debug_timeout: int = 600
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"""The timeout limit for running on debugging data"""
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full_timeout: int = 3600
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"""The timeout limit for running on full data"""
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### specific feature
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#### enable specification
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spec_enabled: bool = True
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#### proposal related
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proposal_version: str = "v1"
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coder_on_whole_pipeline: bool = False
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max_trace_hist: int = 3
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coder_max_loop: int = 10
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runner_max_loop: int = 1
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rule_base_eval: bool = False
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sample_data: bool = True
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use_raw_description: bool = False
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#### model dump
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enable_model_dump: bool = False
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enable_doc_dev: bool = False
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model_dump_check_level: Literal["medium", "high"] = "medium"
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### knowledge base
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enable_knowledge_base: bool = False
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knowledge_base_version: str = "v1"
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knowledge_base_path: str | None = None
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idea_pool_json_path: str | None = None
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### archive log folder after each loop
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enable_log_archive: bool = True
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log_archive_path: str | None = None
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log_archive_temp_path: str | None = (
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None # This is to store the mid tar file since writing the tar file is preferred in local storage then copy to target storage
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)
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#### Evaluation on Test related
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eval_sub_dir: str = "eval" # TODO: fixme, this is not a good name
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"""We'll use f"{DS_RD_SETTING.local_data_path}/{DS_RD_SETTING.eval_sub_dir}/{competition}"
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to find the scriipt to evaluate the submission on test"""
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DS_RD_SETTING = DataScienceBasePropSetting()
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