Turn an arXiv paper URL or PDF into extracted text, word frequency tables, and reference links. Create additional materials such as a two-person audio discussion, an interactive webpage, presentation slides, and a visual summary.
其他高等院校教师与数据科学家在追踪前沿学术时，当需要深度解析arXiv论文，用此技能可一键下载PDF并自动生成词频分析、双人播客、交互式网页、PPT演示与总结图，将数小时的文献阅读转化为多媒体内容，效率提升十倍！
Review the instructions the agent will receive before you install.
标准流程:
scripts/download_pdf.py 下载 arXiv PDF--url (arXiv 论文网址), --output (输出 PDF 文件路径)scripts/extract_text.py 提取纯文本--pdf (PDF 文件路径), --output (输出 txt 文件路径)scripts/analyze_word_frequency.py 进行词频统计--txt (txt 文件路径), --output (输出 csv 文件路径)scripts/text_to_speech.py 将文本转为语音--txt (txt 文件路径), --output (输出 wav 文件路径)scripts/dialogue_to_podcast.py 将对话脚本转换为语音--dialogue (对话脚本文件路径), --output (输出 wav 文件路径)scripts/generate_html.py 生成交互式网页--txt (txt 文件路径), --word_freq (词频 csv 文件路径), --output (输出 html 文件路径)scripts/generate_ppt.py 生成演示文稿--txt (txt 文件路径), --output (输出 pptx 文件路径)scripts/extract_references.py 提取引用链接--txt (txt 文件路径), --output (输出 csv 文件路径)可选分支:
# 下载 PDF
python scripts/download_pdf.py --url "https://arxiv.org/abs/2301.00001" --output ./user-data/paper.pdf
# 提取文本
python scripts/extract_text.py --pdf ./user-data/paper.pdf --output ./user-data/paper.txt
# 词频分析
python scripts/analyze_word_frequency.py --txt ./user-data/paper.txt --output ./user-data/word_freq.csv
# 语音合成
python scripts/text_to_speech.py --txt ./user-data/paper.txt --output ./user-data/paper.wav
# 播客对话（智能体生成对话脚本后）
python scripts/dialogue_to_podcast.py --dialogue ./user-data/dialogue.txt --output ./user-data/podcast.wav
# 生成网页
python scripts/generate_html.py --txt ./user-data/paper.txt --word_freq ./user-data/word_freq.csv --output ./user-data/analysis.html
# 生成 PPT
python scripts/generate_ppt.py --txt ./user-data/paper.txt --output ./user-data/presentation.pptx
# 提取引用
python scripts/extract_references.py --txt ./user-data/paper.txt --output ./user-data/references.csv
python scripts/analyze_word_frequency.py --txt ./user-data/paper.txt --output ./user-data/word_freq.csv
python scripts/extract_references.py --txt ./user-data/paper.txt --output ./user-data/references.csv
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