| import json | |
| from sentence_transformers import SentenceTransformer | |
| from tqdm import tqdm | |
| model = SentenceTransformer('thenlper/gte-large') | |
| embed = lambda text: model.encode(text).tolist() | |
| def parse_data(file_path): | |
| papers = [] | |
| with open(file_path, 'r') as file: | |
| paper = {} | |
| for line in tqdm(file, desc="Parsing data"): | |
| if line.startswith('#*'): | |
| paper['title'] = line[2:].strip() | |
| elif line.startswith('#@'): | |
| paper['authors'] = line[2:].strip().split(',') | |
| elif line.startswith('#t'): | |
| paper['year'] = int(line[2:].strip()) | |
| elif line.startswith('#c'): | |
| paper['venue'] = line[2:].strip() | |
| elif line.startswith('#index'): | |
| paper['index'] = int(line[6:].strip()) | |
| elif line.startswith('#%'): | |
| if 'references' not in paper: | |
| paper['references'] = [] | |
| paper['references'].append(int(line[2:].strip())) | |
| elif line.startswith('#!'): | |
| paper['abstract'] = line[2:].strip() | |
| paper['embedding'] = embed(line[2:].strip()) | |
| if 'references' not in paper: paper['references'] = [] | |
| papers.append(paper) | |
| paper = {} | |
| elif line.strip() == '': | |
| continue | |
| return papers | |
| file_path = '/home/ppxscal/Projects/kellis/neuralmaps/papers.txt' | |
| papers = parse_data(file_path) | |
| with open('papers.json', 'w') as json_file: | |
| json.dump(papers, json_file) | |
| with open('papers_formatted.json', 'w') as json_file: | |
| json.dump(papers, json_file, indent=1) |