A FastAPI backend for fetching and eventually summarizing the latest research papers from arXiv.org. This project is the foundation for building a platform that provides clean, accessible summaries of academic research.

• ✅ Query arXiv API for papers submitted within a given date range
• ✅ Built with FastAPI (async, lightweight, Pythonic)
• ✅ Designed for future integration with LLM summarization

research-tldr/
├── app/
│   ├── __init__.py
│   ├── main.py         ← FastAPI app and routes
│   └── arxiv.py        ← ArXiv fetch logic
├── .venv/              ← Python virtual environment
├── requirements.txt    ← Project dependencies
└── README.md           ← You're here!

1. Clone the repo

git clone https://github.com/your-username/research-tldr.git
cd research-tldr

2. Set up virtual environment

python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt

3. Run the dev server

uvicorn main:app --reload

4. Test the API

Open in browser: http://127.0.0.1:8000/arxiv/daily

GET /arxiv/daily
Fetches papers submitted in the last 2 days using the submittedDate range from arXiv’s API. (Currently returns raw XML.)

• FastAPI
• Uvicorn
• httpx
• pydantic

(Full list available in requirements.txt)

• LLM-powered summaries (GPT or Claude)
• Tagging papers by research area
• Daily digest generation
• Simple dashboard UI

MIT — free to use, contribute, and modify.

Pull requests are welcome! For major changes, please open an issue first to discuss.