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https://github.com/NicolasBohn/NexQuant.git
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Linlang
ea85d5efc8
* fix PR template * subfolders of the log displayed on the web page * fix code error * add health check * reformat with isort * reformat with black * update README * fix bug && experience confusing * reformat with black & update health check code * reformat with isort * reformat with black * update README.md * Removed duplicates in documentation and health_check && Upgraded code for filtering folders * update docs * reformat with black
49 lines
1.6 KiB
Python
49 lines
1.6 KiB
Python
import fire
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from rdagent.components.coder.model_coder.task_loader import (
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ModelExperimentLoaderFromPDFfiles,
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)
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from rdagent.components.document_reader.document_reader import (
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extract_first_page_screenshot_from_pdf,
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)
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from rdagent.log import rdagent_logger as logger
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from rdagent.scenarios.general_model.scenario import GeneralModelScenario
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from rdagent.scenarios.qlib.developer.model_coder import QlibModelCoSTEER
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def extract_models_and_implement(report_file_path: str) -> None:
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"""
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This is a research copilot to automatically implement models from a report file or paper.
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It extracts models from a given PDF report file and implements the necessary operations.
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Parameters:
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report_file_path (str): The path to the report file. The file must be a PDF file.
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Example URLs of PDF reports:
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- https://arxiv.org/pdf/2210.09789
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- https://arxiv.org/pdf/2305.10498
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- https://arxiv.org/pdf/2110.14446
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- https://arxiv.org/pdf/2205.12454
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- https://arxiv.org/pdf/2210.16518
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Returns:
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None
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"""
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with logger.tag("init"):
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scenario = GeneralModelScenario()
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logger.log_object(scenario, tag="scenario")
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with logger.tag("r"):
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# Save Relevant Images
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img = extract_first_page_screenshot_from_pdf(report_file_path)
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logger.log_object(img, tag="pdf_image")
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exp = ModelExperimentLoaderFromPDFfiles().load(report_file_path)
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logger.log_object(exp, tag="load_experiment")
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with logger.tag("d"):
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exp = QlibModelCoSTEER(scenario).develop(exp)
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logger.log_object(exp, tag="developed_experiment")
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if __name__ == "__main__":
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fire.Fire(extract_models_and_implement)
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