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>
480 行
19 KiB
Python
480 行
19 KiB
Python
from typing import List, Optional
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from datetime import datetime
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from crazy_functions.review_fns.data_sources.base_source import DataSource, PaperMetadata
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import random
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class SemanticScholarSource(DataSource):
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"""Semantic Scholar API实现,使用官方Python包"""
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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: Semantic Scholar API密钥(可选)
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"""
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self.api_key = api_key
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self._initialize() # 调用初始化方法
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def _initialize(self) -> None:
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"""初始化API客户端"""
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if not self.api_key:
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# 默认API密钥列表
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default_api_keys = [
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"xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx",
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"xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
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]
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self.api_key = random.choice(default_api_keys)
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self.client = None # 延迟初始化
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self.fields = [
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"title",
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"authors",
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"abstract",
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"year",
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"externalIds",
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"citationCount",
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"venue",
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"openAccessPdf",
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"publicationVenue"
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]
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async def _ensure_client(self):
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"""确保客户端已初始化"""
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if self.client is None:
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from semanticscholar import AsyncSemanticScholar
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self.client = AsyncSemanticScholar(api_key=self.api_key)
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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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start_year: int = None
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) -> List[PaperMetadata]:
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"""搜索论文"""
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try:
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await self._ensure_client()
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# 如果指定了起始年份，添加到查询中
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if start_year:
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query = f"{query} year>={start_year}"
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# 直接使用 search_paper 的结果
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response = await self.client._requester.get_data_async(
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f"{self.client.api_url}{self.client.BASE_PATH_GRAPH}/paper/search",
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f"query={query}&limit={min(limit, 100)}&fields={','.join(self.fields)}",
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self.client.auth_header
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)
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papers = response.get('data', [])
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return [self._parse_paper_data(paper) for paper in 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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import traceback
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print(traceback.format_exc())
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return []
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async def get_paper_details(self, doi: str) -> Optional[PaperMetadata]:
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"""获取指定DOI的论文详情"""
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try:
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await self._ensure_client()
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paper = await self.client.get_paper(f"DOI:{doi}", fields=self.fields)
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return self._parse_paper_data(paper)
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except Exception as e:
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print(f"获取论文详情时发生错误: {str(e)}")
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return None
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async def get_citations(
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self,
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doi: 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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"""获取引用指定DOI论文的文献列表"""
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try:
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await self._ensure_client()
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# 构建查询参数
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fields_param = f"fields={','.join(self.fields)}"
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limit_param = f"limit={limit}"
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year_param = f"year>={start_year}" if start_year else ""
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params = "&".join(filter(None, [fields_param, limit_param, year_param]))
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response = await self.client._requester.get_data_async(
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f"{self.client.api_url}{self.client.BASE_PATH_GRAPH}/paper/DOI:{doi}/citations",
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params,
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self.client.auth_header
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)
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citations = response.get('data', [])
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return [self._parse_paper_data(citation.get('citingPaper', {})) for citation in citations]
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except Exception as e:
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print(f"获取引用列表时发生错误: {str(e)}")
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return []
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async def get_references(
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self,
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doi: 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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"""获取指定DOI论文的参考文献列表"""
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try:
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await self._ensure_client()
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# 构建查询参数
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fields_param = f"fields={','.join(self.fields)}"
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limit_param = f"limit={limit}"
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year_param = f"year>={start_year}" if start_year else ""
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params = "&".join(filter(None, [fields_param, limit_param, year_param]))
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response = await self.client._requester.get_data_async(
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f"{self.client.api_url}{self.client.BASE_PATH_GRAPH}/paper/DOI:{doi}/references",
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params,
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self.client.auth_header
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)
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references = response.get('data', [])
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return [self._parse_paper_data(reference.get('citedPaper', {})) for reference in references]
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except Exception as e:
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print(f"获取参考文献列表时发生错误: {str(e)}")
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return []
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async def get_recommended_papers(self, doi: str, limit: int = 100) -> List[PaperMetadata]:
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"""获取论文推荐
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根据一篇论文获取相关的推荐论文
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Args:
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doi: 论文的DOI
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limit: 返回结果数量限制，最大500
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Returns:
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推荐论文列表
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"""
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try:
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await self._ensure_client()
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papers = await self.client.get_recommended_papers(
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f"DOI:{doi}",
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fields=self.fields,
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limit=min(limit, 500)
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)
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return [self._parse_paper_data(paper) for paper in papers]
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except Exception as e:
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print(f"获取论文推荐时发生错误: {str(e)}")
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return []
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async def get_recommended_papers_from_lists(
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self,
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positive_dois: List[str],
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negative_dois: List[str] = None,
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limit: int = 100
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) -> List[PaperMetadata]:
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"""基于正负例论文列表获取推荐
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Args:
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positive_dois: 正例论文DOI列表（想要获取类似的论文）
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negative_dois: 负例论文DOI列表（不想要类似的论文）
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limit: 返回结果数量限制，最大500
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Returns:
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推荐论文列表
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"""
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try:
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await self._ensure_client()
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positive_ids = [f"DOI:{doi}" for doi in positive_dois]
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negative_ids = [f"DOI:{doi}" for doi in negative_dois] if negative_dois else None
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papers = await self.client.get_recommended_papers_from_lists(
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positive_paper_ids=positive_ids,
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negative_paper_ids=negative_ids,
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fields=self.fields,
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limit=min(limit, 500)
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)
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return [self._parse_paper_data(paper) for paper in papers]
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except Exception as e:
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print(f"获取论文推荐列表时发生错误: {str(e)}")
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return []
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async def search_author(self, query: str, limit: int = 100) -> List[dict]:
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"""搜索作者"""
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try:
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await self._ensure_client()
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# 直接使用 API 请求而不是 search_author 方法
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response = await self.client._requester.get_data_async(
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f"{self.client.api_url}{self.client.BASE_PATH_GRAPH}/author/search",
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f"query={query}&fields=name,paperCount,citationCount&limit={min(limit, 1000)}",
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self.client.auth_header
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)
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authors = response.get('data', [])
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return [
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{
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'author_id': author.get('authorId'),
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'name': author.get('name'),
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'paper_count': author.get('paperCount'),
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'citation_count': author.get('citationCount'),
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}
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for author in authors
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]
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except Exception as e:
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print(f"搜索作者时发生错误: {str(e)}")
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return []
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async def get_author_details(self, author_id: str) -> Optional[dict]:
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"""获取作者详细信息"""
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try:
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await self._ensure_client()
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# 直接使用 API 请求
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response = await self.client._requester.get_data_async(
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f"{self.client.api_url}{self.client.BASE_PATH_GRAPH}/author/{author_id}",
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"fields=name,paperCount,citationCount,hIndex",
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self.client.auth_header
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)
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return {
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'author_id': response.get('authorId'),
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'name': response.get('name'),
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'paper_count': response.get('paperCount'),
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'citation_count': response.get('citationCount'),
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'h_index': response.get('hIndex'),
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}
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except Exception as e:
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print(f"获取作者详情时发生错误: {str(e)}")
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return None
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async def get_author_papers(self, author_id: str, limit: int = 100) -> List[PaperMetadata]:
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"""获取作者的论文列表"""
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try:
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await self._ensure_client()
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# 直接使用 API 请求
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response = await self.client._requester.get_data_async(
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f"{self.client.api_url}{self.client.BASE_PATH_GRAPH}/author/{author_id}/papers",
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f"fields={','.join(self.fields)}&limit={min(limit, 1000)}",
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self.client.auth_header
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)
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papers = response.get('data', [])
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return [self._parse_paper_data(paper) for paper in papers]
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except Exception as e:
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print(f"获取作者论文列表时发生错误: {str(e)}")
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return []
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async def get_paper_autocomplete(self, query: str) -> List[dict]:
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"""论文标题自动补全"""
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try:
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await self._ensure_client()
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# 直接使用 API 请求
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response = await self.client._requester.get_data_async(
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f"{self.client.api_url}{self.client.BASE_PATH_GRAPH}/paper/autocomplete",
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f"query={query}",
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self.client.auth_header
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)
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suggestions = response.get('matches', [])
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return [
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{
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'title': suggestion.get('title'),
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'paper_id': suggestion.get('paperId'),
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'year': suggestion.get('year'),
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'venue': suggestion.get('venue'),
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}
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for suggestion in suggestions
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]
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except Exception as e:
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print(f"获取标题自动补全时发生错误: {str(e)}")
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return []
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def _parse_paper_data(self, paper) -> PaperMetadata:
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"""解析论文数据"""
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# 获取DOI
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doi = None
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external_ids = paper.get('externalIds', {}) if isinstance(paper, dict) else paper.externalIds
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if external_ids:
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if isinstance(external_ids, dict):
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doi = external_ids.get('DOI')
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if not doi and 'ArXiv' in external_ids:
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doi = f"10.48550/arXiv.{external_ids['ArXiv']}"
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else:
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doi = external_ids.DOI if hasattr(external_ids, 'DOI') else None
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if not doi and hasattr(external_ids, 'ArXiv'):
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doi = f"10.48550/arXiv.{external_ids.ArXiv}"
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# 获取PDF URL
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pdf_url = None
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pdf_info = paper.get('openAccessPdf', {}) if isinstance(paper, dict) else paper.openAccessPdf
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if pdf_info:
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pdf_url = pdf_info.get('url') if isinstance(pdf_info, dict) else pdf_info.url
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# 获取发表场所详细信息
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venue_type = None
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venue_name = None
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venue_info = {}
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venue = paper.get('publicationVenue', {}) if isinstance(paper, dict) else paper.publicationVenue
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if venue:
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if isinstance(venue, dict):
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venue_name = venue.get('name')
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venue_type = venue.get('type')
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# 提取更多venue信息
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venue_info = {
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'issn': venue.get('issn'),
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'publisher': venue.get('publisher'),
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'url': venue.get('url'),
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'alternate_names': venue.get('alternate_names', [])
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}
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else:
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venue_name = venue.name if hasattr(venue, 'name') else None
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venue_type = venue.type if hasattr(venue, 'type') else None
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venue_info = {
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'issn': getattr(venue, 'issn', None),
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'publisher': getattr(venue, 'publisher', None),
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'url': getattr(venue, 'url', None),
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'alternate_names': getattr(venue, 'alternate_names', [])
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}
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# 获取标题
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title = paper.get('title', '') if isinstance(paper, dict) else getattr(paper, 'title', '')
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# 获取作者
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authors = paper.get('authors', []) if isinstance(paper, dict) else getattr(paper, 'authors', [])
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author_names = []
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for author in authors:
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if isinstance(author, dict):
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author_names.append(author.get('name', ''))
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else:
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author_names.append(author.name if hasattr(author, 'name') else str(author))
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# 获取摘要
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abstract = paper.get('abstract', '') if isinstance(paper, dict) else getattr(paper, 'abstract', '')
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# 获取年份
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year = paper.get('year') if isinstance(paper, dict) else getattr(paper, 'year', None)
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# 获取引用次数
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citations = paper.get('citationCount') if isinstance(paper, dict) else getattr(paper, 'citationCount', None)
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return PaperMetadata(
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title=title,
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authors=author_names,
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abstract=abstract,
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year=year,
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doi=doi,
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url=pdf_url or (f"https://doi.org/{doi}" if doi else None),
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citations=citations,
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venue=venue_name,
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institutions=[],
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venue_type=venue_type,
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venue_name=venue_name,
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venue_info=venue_info,
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source='semantic' # 添加来源标记
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)
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async def example_usage():
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"""SemanticScholarSource使用示例"""
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semantic = SemanticScholarSource()
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try:
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# 示例1：使用DOI直接获取论文
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print("\n=== 示例1：通过DOI获取论文 ===")
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doi = "10.18653/v1/N19-1423" # BERT论文
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print(f"获取DOI为 {doi} 的论文信息...")
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paper = await semantic.get_paper_details(doi)
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if paper:
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print("\n--- 论文信息 ---")
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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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print(f"URL: {paper.url}")
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if paper.abstract:
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print(f"\n摘要:")
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print(paper.abstract)
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print(f"\n引用次数: {paper.citations}")
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print(f"发表venue: {paper.venue}")
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# 示例2：搜索论文
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print("\n=== 示例2：搜索论文 ===")
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query = "BERT pre-training"
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print(f"搜索关键词 '{query}' 相关的论文...")
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papers = await semantic.search(query=query, limit=3)
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for i, paper in enumerate(papers, 1):
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print(f"\n--- 搜索结果 {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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if paper.abstract:
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print(f"\n摘要:")
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print(paper.abstract)
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print(f"\nDOI: {paper.doi}")
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print(f"引用次数: {paper.citations}")
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# 示例3：获取论文推荐
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print("\n=== 示例3：获取论文推荐 ===")
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print(f"获取与论文 {doi} 相关的推荐论文...")
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recommendations = await semantic.get_recommended_papers(doi, limit=3)
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for i, paper in enumerate(recommendations, 1):
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print(f"\n--- 推荐论文 {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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# 示例4：基于多篇论文的推荐
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print("\n=== 示例4：基于多篇论文的推荐 ===")
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positive_dois = ["10.18653/v1/N19-1423", "10.18653/v1/P19-1285"]
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print(f"基于 {len(positive_dois)} 篇论文获取推荐...")
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multi_recommendations = await semantic.get_recommended_papers_from_lists(
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positive_dois=positive_dois,
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limit=3
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)
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for i, paper in enumerate(multi_recommendations, 1):
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print(f"\n--- 推荐论文 {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5：搜索作者
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print("\n=== 示例5：搜索作者 ===")
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author_query = "Yann LeCun"
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print(f"搜索作者: '{author_query}'")
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authors = await semantic.search_author(author_query, limit=3)
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for i, author in enumerate(authors, 1):
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print(f"\n--- 作者 {i} ---")
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print(f"姓名: {author['name']}")
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print(f"论文数量: {author['paper_count']}")
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print(f"总引用次数: {author['citation_count']}")
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# 示例6：获取作者详情
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print("\n=== 示例6：获取作者详情 ===")
|
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if authors: # 使用第一个搜索结果的作者ID
|
||
author_id = authors[0]['author_id']
|
||
print(f"获取作者ID {author_id} 的详细信息...")
|
||
author_details = await semantic.get_author_details(author_id)
|
||
if author_details:
|
||
print(f"姓名: {author_details['name']}")
|
||
print(f"H指数: {author_details['h_index']}")
|
||
print(f"总引用次数: {author_details['citation_count']}")
|
||
print(f"发表论文数: {author_details['paper_count']}")
|
||
|
||
# 示例7：获取作者论文
|
||
print("\n=== 示例7：获取作者论文 ===")
|
||
if authors: # 使用第一个搜索结果的作者ID
|
||
author_id = authors[0]['author_id']
|
||
print(f"获取作者 {authors[0]['name']} 的论文列表...")
|
||
author_papers = await semantic.get_author_papers(author_id, limit=3)
|
||
for i, paper in enumerate(author_papers, 1):
|
||
print(f"\n--- 论文 {i} ---")
|
||
print(f"标题: {paper.title}")
|
||
print(f"发表年份: {paper.year}")
|
||
print(f"引用次数: {paper.citations}")
|
||
|
||
# 示例8：论文标题自动补全
|
||
print("\n=== 示例8：论文标题自动补全 ===")
|
||
title_query = "Attention is all"
|
||
print(f"搜索标题: '{title_query}'")
|
||
suggestions = await semantic.get_paper_autocomplete(title_query)
|
||
for i, suggestion in enumerate(suggestions[:3], 1):
|
||
print(f"\n--- 建议 {i} ---")
|
||
print(f"标题: {suggestion['title']}")
|
||
print(f"发表年份: {suggestion['year']}")
|
||
print(f"发表venue: {suggestion['venue']}")
|
||
|
||
except Exception as e:
|
||
print(f"发生错误: {str(e)}")
|
||
import traceback
|
||
print(traceback.format_exc())
|
||
|
||
if __name__ == "__main__":
|
||
import asyncio
|
||
asyncio.run(example_usage()) |