arXiv Sage: AI-Powered Research Summarizer

arXiv Sage is a desktop application that transforms complex research papers into engaging, Instagram-style summaries. Simply enter a keyword, and the app fetches the latest papers from arXiv, summarizes them using DeepSeek AI, and presents them in a beautiful feed interface.

Features

• Research Made Accessible: Search arXiv's vast repository with simple keywords
• AI-Powered Summaries: Automatically transform dense research papers into concise, engaging summaries
• Instagram-Style Feed: Browse summaries in a familiar, visually appealing format
• Desktop Application: Convenient, secure, and lightweight Tauri-based app for Windows, Mac, and Linux

Tech Stack

Frontend

• Next.js: React framework for building the user interface
• Tauri: Wraps the web app into a lightweight desktop application
• Tailwind CSS: Utility-first CSS framework for styling
• React Component Library: UI components for consistent design

Backend

• FastAPI: High-performance Python web framework
• arXiv API: Integration for fetching research papers
• PDF Processing: Extraction of text from research PDFs
• DeepSeek API: AI-powered text summarization

Getting Started

Prerequisites

• Node.js (v14+)
• Rust (latest stable version)
• Python (v3.8+)
• npm or yarn

Backend Setup

1. Create a Python virtual environment:

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

2. Install backend dependencies:

pip install -r requirements.txt

3. Set up environment variables:

# Create a .env file in the backend directory
DEEPSEEK_API_KEY=your_deepseek_api_key

4. Start the FastAPI server:

uvicorn main:app --reload

Frontend Setup

1. Install frontend dependencies (inside frontend directory):

npm install
# or
yarn install

2. Run the development server:

npm run dev
# or
yarn dev

3. For Tauri development:

npm run tauri dev
# or
yarn tauri dev

Building for Production

Package the Tauri App

npm run build
npm run tauri build
# or
yarn build
yarn tauri build

This will create distributable packages in the dist folder for your platform.

Project Structure

arXiv-sage/
├── backend/               # FastAPI backend
│   ├── pdfs/              # arXiv PDFs storage
│   ├── services/          # Business logic
│   │   ├── arxiv.py       # arXiv API integration
│   │   ├── pdf.py         # PDF processing
│   │   └── summarizer.py  # DeepSeek API integration
│   ├── binary_main.py     # pyinstaller binary for Tauri
│   ├── main.py            # Main FastAPI application
│   └── requirements.txt   # Python dependencies
├── frontend/              # Next.js + Electron frontend
│   ├── public/            # Static assets
|   ├── src/
│   |   ├── app/           # Next.js app configuration
│   |   ├── components/    # Next.js components
│   |   ├── hooks/         # Next.js hooks
│   ├── src-tauri/         # Tauri configuration
│   |   ├── binaries/      # FastAPI sidecar binary
│   |   ├── capabilities/  # Permissions for sidecar
│   |   ├── gen/           # Schema for Tauri API
│   |   ├── icons/         # Default tauri icons
│   |   ├── pdfs/          # Pdf storage
│   |   ├── src/           # Tauri app entry point
│   |   ├── Cargo.toml     # Tauri dependencies
│   |   ├── build.rs       # Tauri build script
│   |   ├── tauri.conf.json# Tauri configuration
│   └── package.json       # Node.js dependencies
└── README.md              # Project documentation

Future Extensions

• Local ML model integration for offline summarization
• Custom summarization styles (academic, ELI5, etc.)
• Citation extraction and management
• Collaborative features for research teams

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is licensed under the MIT License - see the LICENSE file for details.