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''' |
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这个文件里的所有内容其实应该精简以后全部放在ReviewerBot下 |
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''' |
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from json import loads |
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import pandas as pd |
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import io |
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from utils.review import Reviewer |
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from utils.pubmed import PubMedFetcher |
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from utils.ris_parser import RisFile |
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from utils.pdf_parser import PdfFile |
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def get_paper_info(inputMethod, email=None, pmids=None, ris_data=None): |
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''' |
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解析文章信息准备用于解读 |
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''' |
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if inputMethod == 'PMID': |
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pmids = pmids.strip().split('\n') |
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fetcher = PubMedFetcher(email=email, pmids=pmids) |
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paper_info = pd.DataFrame(fetcher.fetch_abstract()) |
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elif inputMethod == 'RIS File': |
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fileHandle = io.StringIO(ris_data.decode('utf-8')) |
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risFile = RisFile(file=fileHandle) |
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paper_info = risFile.parse_info(kwd=['doi', 'title', 'abstract']).rename(columns={ |
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'doi': 'DOI', |
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'title': 'Title', |
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'abstract': 'Abstract' |
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}) |
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return paper_info |
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def review(task, paper_info, prompts, openai_key, review_model): |
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''' |
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调用已有函数进行文献工作: |
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1. 文献纳入判断(基于摘要) |
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2. 文献小结(基于摘要) |
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''' |
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reviewer = Reviewer(api_key=openai_key, model=review_model) |
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if task == 'Screen': |
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answers = [] |
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for _, rec in paper_info.iterrows(): |
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response = reviewer.screen(prompts, rec['Abstract']) |
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answer = loads(response['choices'][0]['message']['content']) |
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if 'PMID' in rec: |
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answers.append('\n'.join([ |
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f'**PMID: {rec["PMID"]}**', |
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f'- Title: {rec["Title"]}', |
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f'- Inclusion: {answer["Inclusion"]}', |
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'- Explanation:', |
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'\n'.join([f' + {exp}' for exp in answer["Explanation"]]) |
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])) |
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elif 'DOI' in rec: |
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answers.append('\n'.join([ |
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f'**DOI: {rec["DOI"]}**', |
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f'- Title: {rec["Title"]}', |
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f'- Inclusion: {answer["Inclusion"]}', |
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'- Explanation:', |
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'\n'.join([f' + {exp}' for exp in answer["Explanation"]]) |
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])) |
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else: |
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raise Exception('No PMID nor DOI in record.') |
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return '\n\n------------------------\n\n'.join(answers) |
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elif task == 'Summarise': |
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papers = [] |
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for _, rec in paper_info.iterrows(): |
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if 'PMID' in rec: |
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papers.append((rec['PMID'], rec['Abstract'])) |
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elif 'DOI' in rec: |
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papers.append((rec['DOI'], rec['Abstract'])) |
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else: |
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raise Exception('No PMID nor DOI in record.') |
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response = reviewer.summarise(papers, prompts) |
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return response['choices'][0]['message']['content'] |
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def parse_pdf_info(pdf_data, openai_key): |
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''' |
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调用模块解析PDF, 单独放出来, 解析只需要一次 |
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''' |
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fileHandle = io.BytesIO(pdf_data) |
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pdf = PdfFile(file=fileHandle, api_key=openai_key) |
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paper_data = pdf.parse_info() |
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return paper_data |
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def study(paper_data, prompts, openai_key, review_model): |
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''' |
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根据解析好的PDF数据进行阅读 |
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''' |
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reviewer = Reviewer(api_key=openai_key, model=review_model) |
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response = reviewer.study(prompts, paper_data) |
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return response['choices'][0]['message']['content'] |
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def query(prompts, openai_key, review_model): |
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reviewer = Reviewer(api_key=openai_key, model=review_model) |
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response = reviewer.query(prompts) |
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return response['choices'][0]['message']['content'] |
