镜像自地址
https://github.com/binary-husky/gpt_academic.git
已同步 2025-12-05 22:16:49 +00:00
8042750d41
* stage academic conversation * stage document conversation * fix buggy gradio version * file dynamic load * merge more academic plugins * accelerate nltk * feat: 为predict函数添加文件和URL读取功能 - 添加URL检测和网页内容提取功能，支持自动提取网页文本 - 添加文件路径识别和文件内容读取功能，支持private_upload路径格式 - 集成WebTextExtractor处理网页内容提取 - 集成TextContentLoader处理本地文件读取 - 支持文件路径与问题组合的智能处理 * back * block unstable --------- Co-authored-by: XiaoBoAI <liuboyin2019@ia.ac.cn>
459 行
15 KiB
Python
459 行
15 KiB
Python
from typing import List, Optional, Dict, Union
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from datetime import datetime
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import aiohttp
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import asyncio
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from crazy_functions.review_fns.data_sources.base_source import DataSource, PaperMetadata
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import xml.etree.ElementTree as ET
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from urllib.parse import quote
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import json
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from tqdm import tqdm
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import random
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class PubMedSource(DataSource):
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"""PubMed API实现"""
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# 定义API密钥列表
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API_KEYS = [
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"xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx",
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"xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx",
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"xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
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]
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def __init__(self, api_key: str = None):
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"""初始化
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Args:
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api_key: PubMed API密钥，如果不提供则从预定义列表中随机选择
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"""
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self.api_key = api_key or random.choice(self.API_KEYS) # 随机选择一个API密钥
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self._initialize()
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def _initialize(self) -> None:
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"""初始化基础URL和请求头"""
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self.base_url = "https://eutils.ncbi.nlm.nih.gov/entrez/eutils"
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self.headers = {
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"User-Agent": "Mozilla/5.0 PubMedDataSource/1.0",
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"Accept": "application/json"
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}
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async def _make_request(self, url: str) -> Optional[str]:
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"""发送HTTP请求
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Args:
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url: 请求URL
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Returns:
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响应内容
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"""
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try:
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async with aiohttp.ClientSession(headers=self.headers) as session:
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async with session.get(url) as response:
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if response.status == 200:
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return await response.text()
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else:
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print(f"请求失败: {response.status}")
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return None
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except Exception as e:
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print(f"请求发生错误: {str(e)}")
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return None
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async def search(
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self,
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query: str,
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limit: int = 100,
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sort_by: str = "relevance",
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start_year: int = None
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) -> List[PaperMetadata]:
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"""搜索论文
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Args:
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query: 搜索关键词
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limit: 返回结果数量限制
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sort_by: 排序方式 ('relevance', 'date', 'citations')
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start_year: 起始年份
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Returns:
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论文列表
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"""
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try:
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# 添加年份过滤
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if start_year:
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query = f"{query} AND {start_year}:3000[dp]"
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# 构建搜索URL
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search_url = (
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f"{self.base_url}/esearch.fcgi?"
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f"db=pubmed&term={quote(query)}&retmax={limit}"
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f"&usehistory=y&api_key={self.api_key}"
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)
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if sort_by == "date":
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search_url += "&sort=date"
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# 获取搜索结果
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response = await self._make_request(search_url)
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if not response:
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return []
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# 解析XML响应
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root = ET.fromstring(response)
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id_list = root.findall(".//Id")
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pmids = [id_elem.text for id_elem in id_list]
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if not pmids:
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return []
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# 批量获取论文详情
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papers = []
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batch_size = 50
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for i in range(0, len(pmids), batch_size):
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batch = pmids[i:i + batch_size]
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batch_papers = await self._fetch_papers_batch(batch)
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papers.extend(batch_papers)
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return papers
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except Exception as e:
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print(f"搜索论文时发生错误: {str(e)}")
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return []
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async def _fetch_papers_batch(self, pmids: List[str]) -> List[PaperMetadata]:
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"""批量获取论文详情
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Args:
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pmids: PubMed ID列表
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Returns:
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论文详情列表
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"""
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try:
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# 构建批量获取URL
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fetch_url = (
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f"{self.base_url}/efetch.fcgi?"
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f"db=pubmed&id={','.join(pmids)}"
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f"&retmode=xml&api_key={self.api_key}"
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)
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response = await self._make_request(fetch_url)
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if not response:
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return []
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# 解析XML响应
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root = ET.fromstring(response)
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articles = root.findall(".//PubmedArticle")
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return [self._parse_article(article) for article in articles]
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except Exception as e:
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print(f"获取论文批次时发生错误: {str(e)}")
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return []
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def _parse_article(self, article: ET.Element) -> PaperMetadata:
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"""解析PubMed文章XML
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Args:
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article: XML元素
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Returns:
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解析后的论文数据
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"""
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try:
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# 提取基本信息
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pmid = article.find(".//PMID").text
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article_meta = article.find(".//Article")
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# 获取标题
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title = article_meta.find(".//ArticleTitle")
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title = title.text if title is not None else ""
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# 获取作者列表
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authors = []
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author_list = article_meta.findall(".//Author")
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for author in author_list:
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last_name = author.find("LastName")
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fore_name = author.find("ForeName")
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if last_name is not None and fore_name is not None:
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authors.append(f"{fore_name.text} {last_name.text}")
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elif last_name is not None:
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authors.append(last_name.text)
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# 获取摘要
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abstract = article_meta.find(".//Abstract/AbstractText")
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abstract = abstract.text if abstract is not None else ""
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# 获取发表年份
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pub_date = article_meta.find(".//PubDate/Year")
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year = int(pub_date.text) if pub_date is not None else None
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# 获取DOI
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doi = article.find(".//ELocationID[@EIdType='doi']")
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doi = doi.text if doi is not None else None
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# 获取期刊信息
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journal = article_meta.find(".//Journal")
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if journal is not None:
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journal_title = journal.find(".//Title")
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venue = journal_title.text if journal_title is not None else None
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# 获取期刊详细信息
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venue_info = {
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'issn': journal.findtext(".//ISSN"),
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'volume': journal.findtext(".//Volume"),
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'issue': journal.findtext(".//Issue"),
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'pub_date': journal.findtext(".//PubDate/MedlineDate") or
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f"{journal.findtext('.//PubDate/Year', '')}-{journal.findtext('.//PubDate/Month', '')}"
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}
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else:
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venue = None
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venue_info = {}
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# 获取机构信息
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institutions = []
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affiliations = article_meta.findall(".//Affiliation")
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for affiliation in affiliations:
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if affiliation is not None and affiliation.text:
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institutions.append(affiliation.text)
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return PaperMetadata(
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title=title,
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authors=authors,
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abstract=abstract,
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year=year,
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doi=doi,
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url=f"https://pubmed.ncbi.nlm.nih.gov/{pmid}/" if pmid else None,
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citations=None, # PubMed API不直接提供引用数据
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venue=venue,
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institutions=institutions,
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venue_type="journal",
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venue_name=venue,
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venue_info=venue_info,
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source='pubmed' # 添加来源标记
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)
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except Exception as e:
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print(f"解析文章时发生错误: {str(e)}")
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return None
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async def get_paper_details(self, pmid: str) -> Optional[PaperMetadata]:
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"""获取指定PMID的论文详情"""
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papers = await self._fetch_papers_batch([pmid])
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return papers[0] if papers else None
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async def get_related_papers(self, pmid: str, limit: int = 100) -> List[PaperMetadata]:
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"""获取相关论文
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使用PubMed的相关文章功能
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Args:
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pmid: PubMed ID
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limit: 返回结果数量限制
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Returns:
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相关论文列表
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"""
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try:
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# 构建相关文章URL
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link_url = (
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f"{self.base_url}/elink.fcgi?"
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f"db=pubmed&id={pmid}&cmd=neighbor&api_key={self.api_key}"
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)
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response = await self._make_request(link_url)
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if not response:
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return []
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# 解析XML响应
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root = ET.fromstring(response)
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related_ids = root.findall(".//Link/Id")
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pmids = [id_elem.text for id_elem in related_ids][:limit]
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if not pmids:
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return []
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# 获取相关论文详情
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return await self._fetch_papers_batch(pmids)
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except Exception as e:
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print(f"获取相关论文时发生错误: {str(e)}")
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return []
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async def search_by_author(
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self,
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author: str,
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limit: int = 100,
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start_year: int = None
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) -> List[PaperMetadata]:
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"""按作者搜索论文"""
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query = f"{author}[Author]"
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if start_year:
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query += f" AND {start_year}:3000[dp]"
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return await self.search(query, limit=limit)
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async def search_by_journal(
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self,
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journal: str,
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limit: int = 100,
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start_year: int = None
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) -> List[PaperMetadata]:
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"""按期刊搜索论文"""
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query = f"{journal}[Journal]"
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if start_year:
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query += f" AND {start_year}:3000[dp]"
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return await self.search(query, limit=limit)
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async def get_latest_papers(
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self,
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days: int = 7,
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limit: int = 100
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) -> List[PaperMetadata]:
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"""获取最新论文
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Args:
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days: 最近几天的论文
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limit: 返回结果数量限制
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Returns:
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最新论文列表
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"""
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query = f"last {days} days[dp]"
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return await self.search(query, limit=limit, sort_by="date")
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async def get_citations(self, paper_id: str) -> List[PaperMetadata]:
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"""获取引用该论文的文献
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注意：PubMed API本身不提供引用数据，此方法将返回空列表
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未来可以考虑集成其他数据源(如CrossRef)来获取引用信息
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Args:
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paper_id: PubMed ID
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Returns:
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空列表，因为PubMed不提供引用数据
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"""
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return []
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async def get_references(self, paper_id: str) -> List[PaperMetadata]:
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"""获取该论文引用的文献
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从PubMed文章的参考文献列表获取引用的文献
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Args:
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paper_id: PubMed ID
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Returns:
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引用的文献列表
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"""
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try:
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# 构建获取参考文献的URL
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refs_url = (
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f"{self.base_url}/elink.fcgi?"
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f"dbfrom=pubmed&db=pubmed&id={paper_id}"
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f"&cmd=neighbor_history&linkname=pubmed_pubmed_refs"
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f"&api_key={self.api_key}"
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)
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response = await self._make_request(refs_url)
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if not response:
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return []
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# 解析XML响应
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root = ET.fromstring(response)
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ref_ids = root.findall(".//Link/Id")
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pmids = [id_elem.text for id_elem in ref_ids]
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if not pmids:
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return []
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# 获取参考文献详情
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return await self._fetch_papers_batch(pmids)
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except Exception as e:
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print(f"获取参考文献时发生错误: {str(e)}")
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return []
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async def example_usage():
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"""PubMedSource使用示例"""
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pubmed = PubMedSource()
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try:
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# 示例1：基本搜索
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print("\n=== 示例1：搜索COVID-19相关论文 ===")
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papers = await pubmed.search("COVID-19", limit=3)
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for i, paper in enumerate(papers, 1):
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print(f"\n--- 论文 {i} ---")
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print(f"标题: {paper.title}")
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print(f"作者: {', '.join(paper.authors)}")
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print(f"发表年份: {paper.year}")
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print(f"DOI: {paper.doi}")
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if paper.abstract:
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print(f"摘要: {paper.abstract[:200]}...")
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# 示例2：获取论文详情
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if papers:
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print("\n=== 示例2：获取论文详情 ===")
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paper_id = papers[0].url.split("/")[-2]
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paper = await pubmed.get_paper_details(paper_id)
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if paper:
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print(f"标题: {paper.title}")
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print(f"期刊: {paper.venue}")
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print(f"机构: {', '.join(paper.institutions)}")
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# 示例3：获取相关论文
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if papers:
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print("\n=== 示例3：获取相关论文 ===")
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related = await pubmed.get_related_papers(paper_id, limit=3)
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for i, paper in enumerate(related, 1):
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print(f"\n--- 相关论文 {i} ---")
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print(f"标题: {paper.title}")
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print(f"作者: {', '.join(paper.authors)}")
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# 示例4：按作者搜索
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print("\n=== 示例4：按作者搜索 ===")
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author_papers = await pubmed.search_by_author("Fauci AS", limit=3)
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for i, paper in enumerate(author_papers, 1):
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print(f"\n--- 论文 {i} ---")
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print(f"标题: {paper.title}")
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print(f"发表年份: {paper.year}")
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# 示例5：按期刊搜索
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print("\n=== 示例5：按期刊搜索 ===")
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journal_papers = await pubmed.search_by_journal("Nature", limit=3)
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for i, paper in enumerate(journal_papers, 1):
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print(f"\n--- 论文 {i} ---")
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print(f"标题: {paper.title}")
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print(f"发表年份: {paper.year}")
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# 示例6：获取最新论文
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print("\n=== 示例6：获取最新论文 ===")
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latest = await pubmed.get_latest_papers(days=7, limit=3)
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for i, paper in enumerate(latest, 1):
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print(f"\n--- 最新论文 {i} ---")
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print(f"标题: {paper.title}")
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print(f"发表日期: {paper.venue_info.get('pub_date')}")
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# 示例7：获取论文的参考文献
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if papers:
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print("\n=== 示例7：获取论文的参考文献 ===")
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paper_id = papers[0].url.split("/")[-2]
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references = await pubmed.get_references(paper_id)
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for i, paper in enumerate(references[:3], 1):
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print(f"\n--- 参考文献 {i} ---")
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print(f"标题: {paper.title}")
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print(f"作者: {', '.join(paper.authors)}")
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print(f"发表年份: {paper.year}")
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# 示例8：尝试获取引用信息（将返回空列表）
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if papers:
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print("\n=== 示例8：获取论文的引用信息 ===")
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paper_id = papers[0].url.split("/")[-2]
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citations = await pubmed.get_citations(paper_id)
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print(f"引用数据：{len(citations)} (PubMed API不提供引用信息)")
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except Exception as e:
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print(f"发生错误: {str(e)}")
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import traceback
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print(traceback.format_exc())
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if __name__ == "__main__":
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asyncio.run(example_usage())
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