From 898b52edcb47bcb3e9d6106e74ca73e74ea01e70 Mon Sep 17 00:00:00 2001
From: sillylaird <sillyfanboy@gmail.com>
Date: Thu, 3 Sep 2026 00:33:59 +0000
Subject: import live www.sillylaird.ca webroot

---
 .../daily-paper-generator/scripts/arxiv_search.py  | 152 +++++++++++++++++++++
 1 file changed, 152 insertions(+)
 create mode 100755 .agents/skills/daily-paper-generator/scripts/arxiv_search.py

(limited to '.agents/skills/daily-paper-generator/scripts/arxiv_search.py')

diff --git a/.agents/skills/daily-paper-generator/scripts/arxiv_search.py b/.agents/skills/daily-paper-generator/scripts/arxiv_search.py
new file mode 100755
index 0000000..65dd2d7
--- /dev/null
+++ b/.agents/skills/daily-paper-generator/scripts/arxiv_search.py
@@ -0,0 +1,152 @@
+#!/usr/bin/env python3
+"""
+arXiv 论文搜索脚本
+
+用于搜索 arXiv 上与脑电解码相关的论文。
+
+用法:
+    python arxiv_search.py --query "EEG speech decoding" --max-results 50
+    python arxiv_search.py --keywords EEG speech decoding --months 3
+"""
+
+import argparse
+import feedparser
+import re
+from datetime import datetime, timedelta
+from typing import List, Dict, Optional
+from urllib.parse import quote_plus
+
+
+def search_arxiv(
+    query: str,
+    max_results: int = 50,
+    categories: Optional[List[str]] = None,
+    months: int = 3
+) -> List[Dict]:
+    """
+    搜索 arXiv 论文
+
+    Args:
+        query: 搜索查询字符串
+        max_results: 最大结果数
+        categories: arXiv 分类列表 (如 ['cs.CV', 'cs.LG'])
+        months: 搜索最近几个月的论文
+
+    Returns:
+        论文列表，每个论文包含标题、作者、摘要、链接等信息
+    """
+    # 构建 arXiv API 查询
+    base_url = "http://export.arxiv.org/api/query?"
+
+    # 添加分类过滤
+    if categories:
+        cat_query = " OR ".join([f"cat:{cat}" for cat in categories])
+        search_query = f"search_query=({quote_plus(cat_query)})+AND+all:{quote_plus(query)}"
+    else:
+        search_query = f"search_query=all:{quote_plus(query)}"
+
+    # 其他参数
+    params = f"&start=0&max_results={max_results}&sortBy=submittedDate&sortOrder=descending"
+    url = base_url + search_query + params
+
+    print(f"正在搜索: {url}")
+
+    # 执行查询
+    feed = feedparser.parse(url)
+    papers = []
+
+    # 计算时间截止
+    cutoff_date = datetime.now() - timedelta(days=months * 30)
+
+    for entry in feed.entries:
+        # 解析日期
+        published = datetime(*entry.published_parsed[:6])
+
+        # 时间过滤
+        if published < cutoff_date:
+            continue
+
+        # 解析作者
+        authors = [author.name for author in entry.authors]
+        first_author = authors[0] if authors else "Unknown"
+
+        # 解析 arXiv ID
+        arxiv_id = entry.id.split("/abs/")[-1]
+        arxiv_link = f"https://arxiv.org/abs/{arxiv_id}"
+
+        # 解析摘要（去除多余空白）
+        summary = re.sub(r'\s+', ' ', entry.summary).strip()
+
+        paper = {
+            "title": entry.title,
+            "authors": authors,
+            "first_author": first_author,
+            "summary": summary,
+            "published": published.strftime("%Y-%m-%d"),
+            "arxiv_id": arxiv_id,
+            "arxiv_link": arxiv_link,
+            "pdf_link": f"https://arxiv.org/pdf/{arxiv_id}.pdf",
+            "categories": [tag.term for tag in entry.tags],
+        }
+        papers.append(paper)
+
+    print(f"找到 {len(papers)} 篇相关论文（最近{months}个月）")
+    return papers
+
+
+def print_papers(papers: List[Dict], limit: int = 10):
+    """打印论文列表"""
+    print(f"\n=== 最近 {min(limit, len(papers))} 篇论文 ===\n")
+    for i, paper in enumerate(papers[:limit]):
+        print(f"[{i+1}] {paper['title']}")
+        print(f"    作者: {paper['first_author']} et al.")
+        print(f"    发表: {paper['published']}")
+        print(f"    链接: {paper['arxiv_link']}")
+        print(f"    摘要: {paper['summary'][:150]}...")
+        print()
+
+
+def main():
+    parser = argparse.ArgumentParser(description="搜索 arXiv 论文")
+    parser.add_argument("--query", "-q", type=str, help="搜索查询字符串")
+    parser.add_argument("--keywords", "-k", nargs="+", help="搜索关键词列表")
+    parser.add_argument("--max-results", "-n", type=int, default=50, help="最大结果数")
+    parser.add_argument("--categories", "-c", nargs="+",
+                        default=["cs.CV", "cs.LG", "q-bio.NC"],
+                        help="arXiv 分类")
+    parser.add_argument("--months", "-m", type=int, default=3,
+                        help="搜索最近几个月的论文")
+    parser.add_argument("--output", "-o", type=str, help="输出 JSON 文件路径")
+
+    args = parser.parse_args()
+
+    # 构建查询
+    if args.query:
+        query = args.query
+    elif args.keywords:
+        query = "+".join(args.keywords)
+    else:
+        # 默认查询：脑电语音解码
+        query = "EEG+speech+decoding"
+
+    # 执行搜索
+    papers = search_arxiv(
+        query=query,
+        max_results=args.max_results,
+        categories=args.categories,
+        months=args.months
+    )
+
+    # 打印结果
+    print_papers(papers, limit=10)
+
+    # 输出 JSON
+    if args.output:
+        import json
+        with open(args.output, 'w', encoding='utf-8') as f:
+            json.dump(papers, f, ensure_ascii=False, indent=2)
+        print(f"\n结果已保存到 {args.output}")
+
+
+if __name__ == "__main__":
+    main()
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