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<h1>PaperBanana</h1>
<p><strong>Automated Academic Illustration for AI Scientists</strong></p>
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<a href="https://github.com/llmsresearch/paperbanana/actions/workflows/ci.yml"><img src="https://github.com/llmsresearch/paperbanana/actions/workflows/ci.yml/badge.svg" alt="CI"/></a>
<a href="https://pypi.org/project/paperbanana/"><img src="https://img.shields.io/pypi/dm/paperbanana?label=PyPI%20downloads&logo=pypi&logoColor=white" alt="PyPI Downloads"/></a>
<a href="https://huggingface.co/spaces/llmsresearch/paperbanana"><img src="https://img.shields.io/badge/Demo-HuggingFace-yellow?logo=huggingface&logoColor=white" alt="Demo"/></a>
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<a href="https://www.python.org/downloads/"><img src="https://img.shields.io/badge/python-3.10%2B-blue?logo=python&logoColor=white" alt="Python 3.10+"/></a>
<a href="https://arxiv.org/abs/2601.23265"><img src="https://img.shields.io/badge/arXiv-2601.23265-b31b1b?logo=arxiv&logoColor=white" alt="arXiv"/></a>
<a href="LICENSE"><img src="https://img.shields.io/badge/license-MIT-green?logo=opensourceinitiative&logoColor=white" alt="License: MIT"/></a>
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<a href="https://pydantic.dev"><img src="https://img.shields.io/badge/Pydantic-v2-e92063?logo=pydantic&logoColor=white" alt="Pydantic v2"/></a>
<a href="https://typer.tiangolo.com"><img src="https://img.shields.io/badge/CLI-Typer-009688?logo=gnubash&logoColor=white" alt="Typer"/></a>
<a href="https://ai.google.dev/"><img src="https://img.shields.io/badge/Gemini-Free%20Tier-4285F4?logo=google&logoColor=white" alt="Gemini Free Tier"/></a>
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Disclaimer: This is an unofficial, community-driven open-source implementation of the paper
"PaperBanana: Automating Academic Illustration for AI Scientists" by Dawei Zhu, Rui Meng, Yale Song,
Xiyu Wei, Sujian Li, Tomas Pfister, and Jinsung Yoon (arXiv:2601.23265).
This project is not affiliated with or endorsed by the original authors or Google Research.
The implementation is based on the publicly available paper and may differ from the original system.
An agentic framework for generating publication-quality academic diagrams and statistical plots from text descriptions. Supports OpenAI (GPT-5.2 + GPT-Image-1.5), Azure OpenAI / Foundry, and Google Gemini providers.
- Two-phase multi-agent pipeline with iterative refinement
- Multiple VLM and image generation providers (OpenAI, Azure, Gemini)
- Input optimization layer for better generation quality
- Auto-refine mode and run continuation with user feedback
- CLI, Python API, and MCP server for IDE integration
- Batch generation from a manifest file (YAML/JSON) for multiple diagrams in one run
- Batch plots —
paperbanana plot-batch runs many statistical plots from one manifest (CSV/JSON per item)
- PDF inputs for methodology context (optional
paperbanana[pdf] / PyMuPDF), with per-page selection
- PaperBanana Studio — local Gradio web UI (
paperbanana studio) for diagrams, plots, evaluation, batch, and run browser
- Claude Code skills for
/generate-diagram, /generate-plot, and /evaluate-diagram
<p align="center">
<img src="assets/img/hero_image.png" alt="PaperBanana takes paper as input and provide diagram as output" style="max-width: 960px; width: 100%; height: auto;"/>
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Quick Start
Prerequisites
... View full README on GitHub
