arxiv_ai_weather

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arxiv_ai_weather

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A Python tool for searching, filtering, and summarizing arXiv papers in atmospheric science with AI applications.

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# ArXiv AI Weather Research Tool

A Python tool for searching, filtering, and summarizing arXiv papers in atmospheric science with AI applications.

## Why This Project?

AI is being used more and more in weather and climate research. With this trend, most new papers in the AI-for-atmospheric-science field now appear first on arXiv. This leads to a few key observations:

- There are too many papers on arXiv for one person to read them all.
- But, the number isn't so large that an AI can't process them quickly.
- Most of these papers are tagged with the physics.ao-ph category.

So, it's a perfect use case for a Language Model to help us digest the latest progress. This project aims to:

- Fetch all physics.ao-ph papers from a recent period (up to a month).
- Have an LLM select the ones related to both atmospheric science and AI.
- Summarize them.

That's the "why" behind this project. For now, it's just a simple script that runs from top to bottom. It's not interactive, doesn't take natural language commands, and it's not an MCP. But it was very fast to build (especially with the help of Copilot). I might add more features in the future, and I'd love for you to join in and help make it better. Stay tuned!

## Features

- Search arXiv papers in atmospheric and oceanic physics category
- AI-powered filtering for papers relevant to weather/climate research with deep learning
- Automatic PDF download
- AI-generated summaries for each paper
- A comprehensive report for all papers

The `data` directory contains examples of a paper summary and a comprehensive report.

## Installation

1. Clone the repository
2. Install dependencies:
   ```bash
   pip install -r requirements.txt
   ```

3. Set up environment variables:
   
   Create a `.env` file in the project root:
   ```bash
   cp .env.example .env
   ```
   
   Add your OpenRouter API key to the `.env` file:
   ```bash
   OPENROUTER_API_KEY=your_actual_api_key_here
   ```

**⚠️ NOTE:** Currently, it only supports the OpenRouter API.

## Usage

```bash
PYTHONPATH=$(pwd) python main.py --start-date 2025-05-01 --end-date 2025-05-31
```

Please note that you may select a different model; however, the project currently employs the [Structured Outputs](https://openrouter.ai/docs/features/structured-outputs) feature. If you encounter any issues, please try using an OpenAI model.

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