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arxiv_summarizer

Python tool to automatically extract and summarize arXiv research papers.

#automation
#Python
#arXiv
#Paper abstract
#Gemini API
arxiv_summarizer

Product Details

The product is a Python script that leverages the Gemini API to fetch and summarize research papers from arXiv. It helps researchers, students, and enthusiasts quickly extract key information, saving time from reading lengthy literature. This tool is not only suitable for individual users, but can also automate daily literature searches and improve research efficiency. The product is available free of charge and is easy to install and configure.

Main Features

1
Single URL summary: Provide the URL of an arXiv paper to quickly generate a summary.
2
Batch URL summarization: Read multiple arXiv paper URLs from text files and generate summaries in batches.
3
Keyword batch summary: Extract and summarize relevant papers based on specified keywords and date ranges.
4
Automated daily extraction: Daily extraction and summarization of documents can be automated via Google Apps Script.
5
Gemini API integration: Leverage the free Gemini API for high-quality summary generation.
6
Simple installation: Use Conda and pip for simple installation and configuration.

How to Use

1
Clone the repository locally: git clone https://github.com/Shaier/arxiv_summarizer.git.
2
Enter the repository directory: cd arxiv_summarizer.
3
Create and activate the Conda environment: conda create -n arxiv_summarizer python=3.11, conda activate arxiv_summarizer.
4
Install required dependencies: pip install -r requirements.txt.
5
Configure Gemini API key: Replace YOUR_GEMINI_API_KEY in the url_summarize.py file with your actual API key.
6
Run the script to summarize a single paper: python url_summarize.py, selecting input 1 and providing the arXiv URL.
7
Batch process multiple papers: Add multiple URLs in links.txt, run the script and choose input 2.

Target Users

This product is suitable for researchers, students and document workers who need to quickly access the core content of research documents. Through the automated document summarization function, they can save time and improve work efficiency.

Examples

A graduate student uses the tool to quickly access the latest research advances in a specific field.

A research team used batch summarization to quickly analyze commonalities and trends across multiple papers.

A teacher uses automated daily extraction to organize emerging and relevant literature into Google Docs.

Quick Access

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Categories

🎓 educate
› research tools
› AI information platform

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