mirror of
https://github.com/NicolasBohn/NexQuant.git
synced 2026-07-29 00:17:44 +00:00
Linlang
32a29a7479
* feat: parameterize cache paths with USER to avoid conflicts * guide for missing training_hyperparameters * guidance for KeyError: 'concise_reason' * fixed three bugs in the test * fix general_model task bug * fixed some bugs in the med_model scenario * delete comments * format with black * fix mypy error * fix ruff error * fix isort error * sync code * revert cache_path code * revert cache_path code * delete data mining scenario * fix factor report loop * fix LiteLLMAPIBackend log_llm_chat_content setting * refine fin factor report scenario * remove unused LogColors * fix UI * remove medical scenario docs * change **kaggle** to **data_science** * remove default dataset_path in create_debug_data * remove KAGGLE_SETTINGS in kaggle_crawler * limit litellm versions * reformat with black * change README * fix_data_science_docs * make hypothesis observations string * Hiding old versions of kaggle docs * hidding kaggle agent docs --------- Co-authored-by: Young <afe.young@gmail.com> Co-authored-by: Bowen Xian <xianbowen@outlook.com> Co-authored-by: yuanteli <1957922024@qq.com>
64 lines
2.5 KiB
Python
64 lines
2.5 KiB
Python
import json
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from pathlib import Path
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from rdagent.components.benchmark.eval_method import TestCase, TestCases
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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.components.loader.experiment_loader import FactorExperimentLoader
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from rdagent.core.experiment import Experiment, Loader
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from rdagent.scenarios.qlib.experiment.factor_experiment import QlibFactorExperiment
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class FactorExperimentLoaderFromDict(FactorExperimentLoader):
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def load(self, factor_dict: dict) -> QlibFactorExperiment:
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"""Load data from a dict."""
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task_l = []
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for factor_name, factor_data in factor_dict.items():
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task = FactorTask(
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factor_name=factor_name,
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factor_description=factor_data["description"],
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factor_formulation=factor_data["formulation"],
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variables=factor_data["variables"],
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)
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task_l.append(task)
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exp = QlibFactorExperiment(sub_tasks=task_l)
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return exp
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class FactorExperimentLoaderFromJsonFile(FactorExperimentLoader):
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def load(self, json_file_path: Path) -> list:
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with open(json_file_path, "r") as file:
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factor_dict = json.load(file)
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return FactorExperimentLoaderFromDict().load(factor_dict)
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class FactorExperimentLoaderFromJsonString(FactorExperimentLoader):
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def load(self, json_string: str) -> list:
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factor_dict = json.loads(json_string)
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return FactorExperimentLoaderFromDict().load(factor_dict)
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# TODO loader only supports generic of task or experiment, testcase might cause CI error here
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# class FactorTestCaseLoaderFromJsonFile(Loader[TestCases]):
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class FactorTestCaseLoaderFromJsonFile:
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def load(self, json_file_path: Path) -> TestCases:
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with open(json_file_path, "r") as file:
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factor_dict = json.load(file)
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test_cases = TestCases()
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for factor_name, factor_data in factor_dict.items():
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task = FactorTask(
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factor_name=factor_name,
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factor_description=factor_data["description"],
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factor_formulation=factor_data["formulation"],
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variables=factor_data["variables"],
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)
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gt = FactorFBWorkspace(task, raise_exception=False)
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code = {"factor.py": factor_data["gt_code"]}
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gt.inject_files(**code)
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test_cases.test_case_l.append(TestCase(task, gt))
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return test_cases
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