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| from src.Surveyor import Surveyor | |
| import logging | |
| logging.basicConfig() | |
| logging.getLogger().setLevel(logging.ERROR) | |
| if __name__ == '__main__': | |
| import argparse | |
| parser = argparse.ArgumentParser(description='Generate a survey just from a query !!') | |
| parser.add_argument('query', metavar='query_string', type=str, | |
| help='your research query/keywords') | |
| parser.add_argument('--max_search', metavar='max_metadata_papers', type=int, default=None, | |
| help='maximium number of papers to gaze at - defaults to 100') | |
| parser.add_argument('--num_papers', metavar='max_num_papers', type=int, default=None, | |
| help='maximium number of papers to download and analyse - defaults to 25') | |
| parser.add_argument('--pdf_dir', metavar='pdf_dir', type=str, default=None, | |
| help='pdf paper storage directory - defaults to arxiv_data/tarpdfs/') | |
| parser.add_argument('--txt_dir', metavar='txt_dir', type=str, default=None, | |
| help='text-converted paper storage directory - defaults to arxiv_data/fulltext/') | |
| parser.add_argument('--img_dir', metavar='img_dir', type=str, default=None, | |
| help='image storage directory - defaults to arxiv_data/images/') | |
| parser.add_argument('--tab_dir', metavar='tab_dir', type=str, default=None, | |
| help='tables storage directory - defaults to arxiv_data/tables/') | |
| parser.add_argument('--dump_dir', metavar='dump_dir', type=str, default=None, | |
| help='all_output_dir - defaults to arxiv_dumps/') | |
| parser.add_argument('--models_dir', metavar='save_models_dir', type=str, default=None, | |
| help='directory to save models (> 5GB) - defaults to saved_models/') | |
| parser.add_argument('--title_model_name', metavar='title_model_name', type=str, default=None, | |
| help='title model name/tag in hugging-face, defaults to \'Callidior/bert2bert-base-arxiv-titlegen\'') | |
| parser.add_argument('--ex_summ_model_name', metavar='extractive_summ_model_name', type=str, default=None, | |
| help='extractive summary model name/tag in hugging-face, defaults to \'allenai/scibert_scivocab_uncased\'') | |
| parser.add_argument('--ledmodel_name', metavar='ledmodel_name', type=str, default=None, | |
| help='led model(for abstractive summary) name/tag in hugging-face, defaults to \'allenai/led-large-16384-arxiv\'') | |
| parser.add_argument('--embedder_name', metavar='sentence_embedder_name', type=str, default=None, | |
| help='sentence embedder name/tag in hugging-face, defaults to \'paraphrase-MiniLM-L6-v2\'') | |
| parser.add_argument('--nlp_name', metavar='spacy_model_name', type=str, default=None, | |
| help='spacy model name/tag in hugging-face (if changed - needs to be spacy-installed prior), defaults to \'en_core_sci_scibert\'') | |
| parser.add_argument('--similarity_nlp_name', metavar='similarity_nlp_name', type=str, default=None, | |
| help='spacy downstream model(for similarity) name/tag in hugging-face (if changed - needs to be spacy-installed prior), defaults to \'en_core_sci_lg\'') | |
| parser.add_argument('--kw_model_name', metavar='kw_model_name', type=str, default=None, | |
| help='keyword extraction model name/tag in hugging-face, defaults to \'distilbert-base-nli-mean-tokens\'') | |
| parser.add_argument('--refresh_models', metavar='refresh_models', type=str, default=None, | |
| help='Refresh model downloads with given names (needs atleast one model name param above), defaults to False') | |
| parser.add_argument('--high_gpu', metavar='high_gpu', type=str, default=None, | |
| help='High GPU usage permitted, defaults to False') | |
| args = parser.parse_args() | |
| surveyor = Surveyor( | |
| pdf_dir=args.pdf_dir, | |
| txt_dir=args.txt_dir, | |
| img_dir=args.img_dir, | |
| tab_dir=args.tab_dir, | |
| dump_dir=args.dump_dir, | |
| models_dir=args.models_dir, | |
| title_model_name=args.title_model_name, | |
| ex_summ_model_name=args.ex_summ_model_name, | |
| ledmodel_name=args.ledmodel_name, | |
| embedder_name=args.embedder_name, | |
| nlp_name=args.nlp_name, | |
| similarity_nlp_name=args.similarity_nlp_name, | |
| kw_model_name=args.kw_model_name, | |
| refresh_models=args.refresh_models, | |
| high_gpu=args.high_gpu | |
| ) | |
| surveyor.survey(args.query, max_search=args.max_search, num_papers=args.num_papers, | |
| debug=False, weigh_authors=False) | |