GenAI-DrawIO-Creator: A Framework for Automated Diagram Generation
Jinze Yu, Dayuan Jiang

TL;DR
This paper introduces GenAI-DrawIO-Creator, a framework that uses large language models to automate and improve diagram creation and editing in draw.io, reducing time and increasing accuracy.
Contribution
It presents a novel system design integrating LLMs for real-time diagram generation, with specialized prompt engineering for valid XML outputs, demonstrating practical applications.
Findings
Reduces diagram creation time significantly
Produces high-fidelity, structurally correct diagrams
Capable of generating diagrams from natural language, code, and images
Abstract
Diagrams are crucial for communicating complex information, yet creating and modifying them remains a labor-intensive task. We present GenAI-DrawIO-Creator, a novel framework that leverages Large Language Models (LLMs) to automate diagram generation and manipulation in the structured XML format used by draw.io. Our system integrates Claude 3.7 to reason about structured visual data and produce valid diagram representations. Key contributions include a high-level system design enabling real-time diagram updates, specialized prompt engineering and error-checking to ensure well-formed XML outputs. We demonstrate a working prototype capable of generating accurate diagrams (such as network architectures and flowcharts) from natural language or code, and even replicating diagrams from images. Simulated evaluations show that our approach significantly reduces diagram creation time and produces…
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Taxonomy
TopicsData Visualization and Analytics · Multimodal Machine Learning Applications · Constraint Satisfaction and Optimization
