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>
279 行
9.4 KiB
Python
279 行
9.4 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 json
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from tqdm import tqdm
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import random
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class AdsabsSource(DataSource):
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"""ADS (Astrophysics Data System) API实现"""
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# 定义API密钥列表
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API_KEYS = [
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"xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx",
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"xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx",
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"xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
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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: ADS 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://api.adsabs.harvard.edu/v1"
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self.headers = {
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"Authorization": f"Bearer {self.api_key}",
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"Content-Type": "application/json"
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}
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async def _make_request(self, url: str, method: str = "GET", data: dict = None) -> Optional[dict]:
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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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method: HTTP方法
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data: POST请求数据
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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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if method == "GET":
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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.json()
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elif method == "POST":
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async with session.post(url, json=data) as response:
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if response.status == 200:
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return await response.json()
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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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def _parse_paper(self, doc: dict) -> PaperMetadata:
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"""解析ADS文献数据
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Args:
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doc: ADS文献数据
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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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return PaperMetadata(
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title=doc.get('title', [''])[0] if doc.get('title') else '',
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authors=doc.get('author', []),
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abstract=doc.get('abstract', ''),
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year=doc.get('year'),
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doi=doc.get('doi', [''])[0] if doc.get('doi') else None,
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url=f"https://ui.adsabs.harvard.edu/abs/{doc.get('bibcode')}/abstract" if doc.get('bibcode') else None,
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citations=doc.get('citation_count'),
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venue=doc.get('pub', ''),
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institutions=doc.get('aff', []),
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venue_type="journal",
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venue_name=doc.get('pub', ''),
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venue_info={
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'volume': doc.get('volume'),
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'issue': doc.get('issue'),
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'pub_date': doc.get('pubdate', '')
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},
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source='adsabs'
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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 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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# 构建查询
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if start_year:
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query = f"{query} year:{start_year}-"
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# 设置排序
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sort_mapping = {
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'relevance': 'score desc',
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'date': 'date desc',
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'citations': 'citation_count desc'
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}
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sort = sort_mapping.get(sort_by, 'score desc')
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# 构建搜索请求
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search_url = f"{self.base_url}/search/query"
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params = {
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"q": query,
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"rows": limit,
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"sort": sort,
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"fl": "title,author,abstract,year,doi,bibcode,citation_count,pub,aff,volume,issue,pubdate"
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}
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response = await self._make_request(f"{search_url}?{self._build_query_string(params)}")
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if not response or 'response' not in response:
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return []
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# 解析结果
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papers = []
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for doc in response['response']['docs']:
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paper = self._parse_paper(doc)
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if paper:
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papers.append(paper)
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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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def _build_query_string(self, params: dict) -> str:
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"""构建查询字符串"""
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return "&".join([f"{k}={v}" for k, v in params.items()])
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async def get_paper_details(self, bibcode: str) -> Optional[PaperMetadata]:
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"""获取指定bibcode的论文详情"""
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search_url = f"{self.base_url}/search/query"
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params = {
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"q": f"identifier:{bibcode}",
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"fl": "title,author,abstract,year,doi,bibcode,citation_count,pub,aff,volume,issue,pubdate"
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}
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response = await self._make_request(f"{search_url}?{self._build_query_string(params)}")
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if response and 'response' in response and response['response']['docs']:
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return self._parse_paper(response['response']['docs'][0])
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return None
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async def get_related_papers(self, bibcode: str, limit: int = 100) -> List[PaperMetadata]:
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"""获取相关论文"""
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url = f"{self.base_url}/search/query"
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params = {
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"q": f"citations(identifier:{bibcode}) OR references(identifier:{bibcode})",
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"rows": limit,
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"fl": "title,author,abstract,year,doi,bibcode,citation_count,pub,aff,volume,issue,pubdate"
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}
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response = await self._make_request(f"{url}?{self._build_query_string(params)}")
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if not response or 'response' not in response:
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return []
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papers = []
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for doc in response['response']['docs']:
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paper = self._parse_paper(doc)
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if paper:
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papers.append(paper)
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return papers
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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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return await self.search(query, limit=limit, start_year=start_year)
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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"pub:\"{journal}\""
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return await self.search(query, limit=limit, start_year=start_year)
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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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query = f"entdate:[NOW-{days}DAYS TO NOW]"
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return await self.search(query, limit=limit, sort_by="date")
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async def get_citations(self, bibcode: str) -> List[PaperMetadata]:
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"""获取引用该论文的文献"""
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url = f"{self.base_url}/search/query"
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params = {
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"q": f"citations(identifier:{bibcode})",
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"fl": "title,author,abstract,year,doi,bibcode,citation_count,pub,aff,volume,issue,pubdate"
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}
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response = await self._make_request(f"{url}?{self._build_query_string(params)}")
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if not response or 'response' not in response:
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return []
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papers = []
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for doc in response['response']['docs']:
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paper = self._parse_paper(doc)
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if paper:
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papers.append(paper)
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return papers
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async def get_references(self, bibcode: str) -> List[PaperMetadata]:
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"""获取该论文引用的文献"""
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url = f"{self.base_url}/search/query"
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params = {
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"q": f"references(identifier:{bibcode})",
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"fl": "title,author,abstract,year,doi,bibcode,citation_count,pub,aff,volume,issue,pubdate"
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}
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response = await self._make_request(f"{url}?{self._build_query_string(params)}")
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if not response or 'response' not in response:
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return []
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papers = []
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for doc in response['response']['docs']:
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paper = self._parse_paper(doc)
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if paper:
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papers.append(paper)
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return papers
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async def example_usage():
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"""AdsabsSource使用示例"""
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ads = AdsabsSource()
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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：搜索黑洞相关论文 ===")
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papers = await ads.search("black hole", 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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# 其他示例...
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except Exception as e:
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print(f"发生错误: {str(e)}")
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if __name__ == "__main__":
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# python -m crazy_functions.review_fns.data_sources.adsabs_source
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asyncio.run(example_usage()) |