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>
106 行
3.5 KiB
Python
106 行
3.5 KiB
Python
from typing import List, Dict, Any
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from .base_handler import BaseHandler
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from crazy_functions.review_fns.query_analyzer import SearchCriteria
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import asyncio
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class Arxiv最新论文推荐功能(BaseHandler):
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"""最新论文推荐处理器"""
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def __init__(self, arxiv, semantic, llm_kwargs=None):
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super().__init__(arxiv, semantic, llm_kwargs)
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async def handle(
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self,
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criteria: SearchCriteria,
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chatbot: List[List[str]],
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history: List[List[str]],
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system_prompt: str,
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llm_kwargs: Dict[str, Any],
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plugin_kwargs: Dict[str, Any],
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) -> str:
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"""处理最新论文推荐请求"""
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# 获取搜索参数
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search_params = self._get_search_params(plugin_kwargs)
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# 获取最新论文
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papers = []
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for category in criteria.arxiv_params["categories"]:
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latest_papers = await self.arxiv.get_latest_papers(
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category=category,
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debug=False,
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batch_size=50
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)
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papers.extend(latest_papers)
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if not papers:
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return self._generate_apology_prompt(criteria)
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# 使用embedding模型对论文进行排序
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self.ranked_papers = self.paper_ranker.rank_papers(
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query=criteria.original_query,
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papers=papers,
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search_criteria=criteria
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)
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# 构建最终的prompt
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current_time = self._get_current_time()
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final_prompt = f"""Current time: {current_time}
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Based on your interest in {criteria.main_topic}, here are the latest papers from arXiv in relevant categories:
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{', '.join(criteria.arxiv_params["categories"])}
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Latest papers available:
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{self._format_papers(self.ranked_papers)}
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Please provide:
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1. A clear list of latext papers, organized by themes or approaches
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2. Group papers by sub-topics or themes if applicable
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3. For each paper:
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- Publication time
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- The key contributions and main findings
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- Why it's relevant to the user's interests
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- How it relates to other latest papers
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- The paper's citation count and citation impact
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- The paper's download link
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4. A suggested reading order based on:
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- Paper relationships and dependencies
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- Difficulty level
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- Significance
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5. Future Directions
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- Emerging venues and research streams
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- Novel methodological approaches
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- Cross-disciplinary opportunities
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- Research gaps by publication type
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IMPORTANT:
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- Focus on explaining why each paper is interesting
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- Highlight the novelty and potential impact
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- Consider the credibility and stage of each publication
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- Use the provided paper titles with their links when referring to specific papers
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- Base recommendations ONLY on the explicitly provided paper information
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- Do not make ANY assumptions about papers beyond the given data
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- When information is missing or unclear, acknowledge the limitation
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- Never speculate about:
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* Paper quality or rigor not evidenced in the data
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* Research impact beyond citation counts
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* Implementation details not mentioned
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* Author expertise or background
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* Future research directions not stated
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- For each paper, cite only verifiable information
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- Clearly distinguish between facts and potential implications
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- Each paper includes download links in its 📥 PDF Downloads section
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Format your response in markdown with clear sections.
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Language requirement:
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- If the query explicitly specifies a language, use that language
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- Otherwise, match the language of the original user query
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"""
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return final_prompt |