arXiv Tools - Intelligent Literature Workflow Manager

Author: Ansatz Gong
Version: 0.1.0 | Last Updated: 2025-02-23

Background & Motivation

Problem Statement

arXiv daily submissions may update article tags post-publication. Traditional workflows face two challenges:

1. Metadata Synchronization Gap: Local reading history (via browser clicks) isn't synced with arXiv accounts
2. Version Drift Detection: No native mechanism to detect newly added/updated articles in historical submissions

Solution Overview

This toolset bridges arXiv metadata with Zotero reference management and Obsidian knowledge workflows by:

graph LR
    A[arXiv Daily Query] --> B[Zotero Sync Check]
    B --> C{New/Updated?}
    C -->|Yes| D[Markdown Report]
    C -->|No| E[Version Archive]
    D --> F[Obsidian Processing]

Loading

Installation & Setup

Prerequisites

Zotero Configuration:

Enable API access: Settings > Advanced > Miscellaneous > Allow other applications on this computer to communicate with Zotero ......

Python Environment:

pip install .

Obsidian Setup (Optional):

install and activate plugins : MetaEdit Dataview

Core Features

Intelligent Metadata Pipeline

arxiv_update.py

import time
from ArXiv_Tools.report import filter_arxiv_to_md
from ArXiv_Tools.arxiv_index_fetch import query_args

# get time 
localtime = time.localtime()
year = localtime.tm_year
month = localtime.tm_mon
# Example: Generate quantum physics report for 2025-02
filter_arxiv_to_md(
    year=year,
    month=month,
    md_folder=r'/path/to/obsidian/vault/arxiv_datas/quant-ph',
    query_args=query_args  # Customize arXiv categories
)

you may write a schedule job to update data everyday.

30 7 * * * conda run -n arxiv  arxiv_update.py

It means that this command will be executed at 7:30 everyday/

TO-DO

1. update function and remind

2. add AI reading and sorting function