WangQrkkk/PaperQuay

What it solves

PaperQuay is a local-first AI paper workspace designed to eliminate the fragmented workflow of researchers and graduate students. It replaces the need to switch between separate PDF readers, translation tools, note-taking apps, and reference managers (like Zotero) by integrating them into a single desktop application.

How it works

Built as an Electron app using React and TypeScript, PaperQuay manages a local library of PDFs stored in a configurable folder and indexed via SQLite. It uses MinerU for structural PDF parsing, allowing for block-level translation and navigation. AI capabilities are powered by OpenAI-compatible APIs, which generate structured paper overviews (summaries of methods, findings, etc.) and drive an Agent workspace for library management tasks. A Tiptap-based editor provides a rich notes environment with wiki-links and paper references.

Who it’s for

Graduate students, academic researchers, and heavy paper-reading users who need a centralized system for importing, annotating, and organizing large volumes of scientific literature.

Highlights

• Instant Block-Level Translation: Caches translated structural blocks to allow instant jumping between source and translation without reading latency.
• Integrated Notes Workspace: A Tiptap-powered editor supporting [[note]] links, #tags, and @paper references to connect ideas across the library.
• Agent-Assisted Management: An AI agent capable of batch renaming, metadata completion, smart tagging, and classification of papers.
• Fast Screening: An overview panel that surfaces AI-generated fields (e.g., research questions, limitations) for quick paper evaluation.
• Zotero Compatibility: Optional import of Zotero collections, tags, and PDFs without requiring Zotero to be a dependency.
• Reading Analytics: Tracks and visualizes time spent on specific PDF positions via reading-time charts and heat previews.