Skip to content

ARIES (ArXiv Research Intelligent Efficient Summary)

License

Notifications You must be signed in to change notification settings

LAMDASZ-ML/Aries

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

19 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

♈️ Aries: ArXiv Research Intelligent Efficient Summary

Arxiv Paper to Feishu

ARIES Logo

🎉 Introduction

A tool that automatically fetches the latest LLM-related papers from arXiv and pushes them through Feishu bots. The bot uses Deepseek AI for intelligent filtering and summarization, helping you stay up-to-date with the latest research developments.


✨ Features

  • 🤖 Auto Paper Fetching: Scrapes the latest LLM-related papers from arXiv.
  • 🧠 Smart Filtering & Summarization: Uses Deepseek AI for high-quality filtering and summarization.
  • 📱 Multi-bot Support: Configure multiple Feishu bots to push to different groups.
  • Scheduled Tasks: Default push at 9 AM daily, customizable.
  • ⚙️ Flexible Configuration: Customize paper types, filtering rules, and push methods via config file.
  • 📊 History Tracking: Pushed papers are recorded in paper_history.json to avoid duplicates.

🚀 Quick Start

  1. Install dependencies:

    pip install -r requirements.txt
  2. Configure environment variables:

    • Create a .env file and fill in as follows:
      DEEPSEEK_API_KEY=your_deepseek_api_key
      WEBHOOK_URL_1=https://your_first_webhook_url
      WEBHOOK_URL_2=https://your_second_webhook_url
      
  3. Configure config.yaml to customize paper types and filtering rules.

  4. Run the script:

    python main.py

⚙️ Configuration Guide

Environment Variables

  • DEEPSEEK_API_KEY: Required, for calling Deepseek API.
  • WEBHOOK_URL_[n]: Required, Feishu bot webhook URLs, multiple can be configured.

Configuration Details:

  • paper_types: Define settings for each paper type.

    • enabled: Status, true to enable, false to disable.
    • search_query: arXiv search query, supports logical conditions and keyword combinations.
    • keywords: Keyword list for paper filtering.
    • prompt: Prompt for Deepseek to judge paper relevance, generated based on search_query and keywords. Can be modified.
    • max_papers: Maximum number of papers per push (default 5, customizable).
  • general: Global configuration.

    • max_search_results: Maximum number of papers returned by search.
    • schedule_time: Daily scheduled task time (24-hour format).

❗ Important Notes

  1. Ensure sufficient Deepseek API Key quota.
  2. Feishu Webhook URLs should be obtained from bot settings in Feishu groups.
  3. Recommended to deploy on a server for continuous operation.
  4. New paper types can be added or existing configurations adjusted via config.yaml.

❓ FAQ

  1. API Call Failure
    • Check if the Deepseek API Key is correct.
  2. Message Push Failure
    • Verify if the Webhook URL is valid.
  3. Test Push
    • Uncomment agent.run() in the main function to run directly.

📝 TODO List

  • 📚 Paper Collection & Management

    • Automatic arXiv paper fetching
    • Paper history storage
    • Related paper correlation analysis
    • Paper archiving system
  • 🔍 Intelligent Paper Processing

    • Auto Summary: Paper summarization
    • Auto Review: Paper review generation
    • Auto Survey: Field survey generation
  • 📢 Multi-platform Distribution

    • Feishu bot integration
    • WeChat bot integration
    • Xiaohongshu content publishing

📄 License

This project is licensed under the MIT License.

About

ARIES (ArXiv Research Intelligent Efficient Summary)

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages