PaperBanana is an open-source, AI-powered platform that converts text descriptions into publication-ready academic illustrations, including methodology diagrams, statistical charts, and infographics, using a five-agent collaborative architecture.
What is PaperBanana?
PaperBanana is an AI-powered tool that automates the creation of publication-ready academic illustrations from natural language text descriptions. It takes text input and produces images such as methodology diagrams, statistical plots, system architectures, flow charts, and poster assets. The platform is web-based, with a credit-based freemium model, and is developed by researchers at Peking University (as indicated by the GitHub repository owner dwzhu-pku). It is open source and available on GitHub, with a related research paper.
Key Features
- Multi-agent architecture: Employs a closed-loop five-agent system (Planner, Visualizer, etc.) to ensure precise, logically accurate diagrams.
- Code-based statistical plots: Generates executable Python Matplotlib code for charts, eliminating numerical hallucination and ensuring mathematical precision.
- Nano-Banana-Pro model: A built-in model optimized for rendering scientific icons, shapes, and connectors with high aesthetic quality.
- Sketch refinement: Accepts rough hand-drawn sketches or whiteboard notes and transforms them into publication-quality figures.
- Multiple diagram types: Supports methodology diagrams, statistical charts, system architectures, flow charts, educational infographics, and poster assets.
- Style and aspect ratio control: Offers dropdown selection for visual style (e.g., Methodology Diagrams, Statistical Plots) and aspect ratio (Auto, square, etc.).
- Credit-based generation: Each generation costs 5 credits; users must sign in to generate images (freemium model with limited free credits likely).
