Upload a thesis or paper draft and have it auto-formatted to a specific university's style.
Convert plain tables into academic three-line tables automatically.
Renumber figures, tables, and references consistently across a long paper.
Generate a table of contents and export the final document as Word or PDF.
| gbnb666/feiqilai | aarav90-cpu/fetchit | adammartinez271828/x4-analysis | |
|---|---|---|---|
| Stars | 10 | 10 | 10 |
| Language | Python | Python | Python |
| Setup difficulty | moderate | easy | easy |
| Complexity | 3/5 | 2/5 | 2/5 |
| Audience | researcher | developer | general |
Figures from each repo's GitHub metadata at analysis time.
Requires a DeepSeek API key and running both a Python backend and a Node frontend.
Feiqilai, whose Chinese name means AI Smart Formatting Assistant, is a tool for formatting academic papers. A user uploads a paper and the tool automatically applies formatting rules: recognizing titles, chapter structure, and reference lists using the DeepSeek AI model, then producing a properly formatted document. According to the README, the tool converts regular tables into the three line table style commonly required by academic papers in China, numbers figures and tables by chapter, renumbers references with hanging indents, and can automatically generate a table of contents. It also lets users adjust image width and alignment in bulk, fine tune fonts, font sizes, and spacing through a settings panel, and preview the formatted document as HTML before downloading. Finished documents can be downloaded in both Word and PDF formats. The project also ships several built in templates matching different Chinese university paper formats. Technically, the project has a FastAPI backend written in Python that uses SQLAlchemy and python-docx, paired with a React and TypeScript frontend styled with Tailwind CSS. The AI analysis step calls the DeepSeek API. For development, the backend is started with a standard pip install and uvicorn command while the frontend uses npm install and npm run dev, after which the app is reachable locally. The project can also be packaged into a single Windows executable using PyInstaller, producing a file that opens directly in the browser when double clicked. The README organizes the codebase into a backend with separate modules for AI analysis, file handling, the formatting engine, image formatting, job management, HTML preview, school templates, and user templates, plus a frontend split into pages, modules, and components. This is a practical tool aimed at students and researchers who need to reformat papers to match specific institutional requirements rather than a general purpose document editor.
An AI tool that automatically reformats academic papers, including tables, references, and captions, to match university formatting requirements.
Mainly Python. The stack also includes Python, FastAPI, SQLAlchemy.
Setup difficulty is rated moderate, with roughly 30min to a first successful run.
Mainly researcher.
This repo across BitVibe Labs
Verify against the repo before relying on details.