Paper Reading List

A minimal, locally-hosted academic paper reading manager with persistent SQLite storage.

✨ Note: This project was built entirely through Vibe Coding—focusing on rapid, AI-assisted development, high-fidelity UI aesthetics, and frictionless prototyping.

Classic Light Mode

Classic Dark Mode

Features

• Classic Minimalist Design: Premium grayscale aesthetic with full Light and Dark mode support (toggle in header).
• Dual Source Support: Add papers via web URL or local file path (both open natively in your browser).
• Persistent Notes: Add and save personal notes/comments for each paper.
• Auto Title Detection: Automatically derives paper title from URL path or filename.
• Reading Progress: Seamlessly move papers between Reading List and Completed.
• Duplicate Prevention: Automatically rejects duplicate entries (by title or source) with auto-dismissing alerts.
• Export to CSV: Download your completed reading list as a CSV file for your records.
• Persistent Storage: Data is stored in a local SQLite database.

Setup

Prerequisites

• Node.js (v20+)
• uv (Python package manager)

Install dependencies

# Frontend
cd client && npm install

# Backend
cd server && uv sync

Usage

Start Services (Background)

chmod +x start.sh stop.sh
./start.sh

• Frontend: http://localhost:5187
• Backend: http://localhost:8787

Stop Services

./stop.sh

Shortcuts & Controls

• Toggle Mode: Use the ☀️/🌙 icon in the header.
• Export: Click the Export button to download your completed list as CSV.
• Open Paper: Click the paper row to quickly view the paper in a new browser tab.
• Edit Note: Click the note field or the "Add Note" text to edit; auto-saves on blur or Enter.

Project Structure

paper-reading-list/
├── client/          # React + TypeScript + Mantine frontend
│   ├── src/
│   │   ├── components/   # PaperAddInput, PaperList
│   │   ├── store/        # Zustand state
│   └── vite.config.ts
├── server/          # FastAPI + SQLAlchemy backend
│   ├── app/
│   │   ├── api/          # Route handlers (open via URL or securely serve local files)
│   │   └── models/       # SQLAlchemy models
│   ├── pyproject.toml
│   └── data/papers.db    # Persistent SQLite database
├── start.sh         # Launch both services in background
├── stop.sh          # Kill background processes
└── README.md