dayuan.jiang cd1df1eb6a feat(diagram-engine): wire up restructure_diagram + stencil catalog
Closes the loop: the model can now build and edit AWS architecture diagrams by
declaring structure, and never writes an mxCell again.

catalog.ts — 983 AWS icon and 19 group stencils as a name→style map, generated from
drawio-ai-kit's catalog (itself generated from jgraph's draw.io shape index). Styles
are verbatim, so the official category colours, connection points and aspect=fixed
come along for free and nothing is hand-assembled. An invented name is rejected with
suggestions instead of rendering as a blank square, which is what draw.io does with
an unknown resIcon today.

operations.ts — what the model actually sends: add_icon / add_container / move /
link / set_dir and so on, applied in order against the tree. Guards the things that
break a diagram quietly: duplicate ids (draw.io drops one of the two cells), edges
left pointing at a removed node, and moving a container inside itself.

index.ts — the entry point. current XML → parse → apply ops → check names → layout →
render → new XML. The tree is not stored between calls; it is re-derived from the
canvas every time, so a user's manual edits are input to the next layout rather than
state to reconcile.

Token cost, measured with Claude's tokenizer rather than estimated:
  - build a VPC diagram:  515 tok as operations vs 3180 as XML   (6.2x)
  - add one icon:          27 tok as an operation vs 3823 re-emitting (142x)
  - read current state:   216 tok as an outline vs 3180 as XML   (14.7x)

The 142x is the one that matters day to day: "add a Redis" is one operation, not a
rewrite of the whole diagram.

Routing in the system prompt sends AWS architecture through this path and leaves
flowcharts, BPMN, sequence diagrams, mind maps and Azure/GCP on display_diagram —
the layout engine's primitives (nested rows, columns, grids) do not model a sequence
diagram's lifelines or a mind map's radial spread, and pretending otherwise would
make those worse rather than better.

Also: added a NOTICE recording the MIT port and the AWS Architecture Icons terms,
and a narrow .gitignore exception so the generated catalog is tracked while the
root data/ directory (admin settings, contains secrets) stays ignored.

403 unit tests + 3 new e2e. Verified in the real app: a structural tool call renders
with real stencils and container markers; a second call adds one node and keeps
everything from the first; an invented name is refused and nothing is drawn. The 13
existing diagram e2e tests still pass.
2026-08-09 13:49:11 +09:00

Next AI Draw.io

AI-Powered Diagram Creation Tool - Chat, Draw, Visualize

English | 中文 | 日本語

TrendShift

License: Apache 2.0 Next.js React Sponsor

Live Demo

A Next.js web application that integrates AI capabilities with draw.io diagrams. Create, modify, and enhance diagrams through natural language commands and AI-assisted visualization.

Note: Thanks to ByteDance Doubao sponsorship, the demo site now uses the powerful glm-4.7 model!

https://github.com/user-attachments/assets/9d60a3e8-4a1c-4b5e-acbb-26af2d3eabd1

Table of Contents

Examples

Here are some example prompts and their generated diagrams:

Animated transformer connectors

Prompt: Give me a **animated connector** diagram of transformer's architecture.

Transformer Architecture with Animated Connectors
RAG Technique Diagram

Prompt: Generate a RAG architecture diagram for **chat application**. Use connected diagram for data ingestion

RAG Architecture Diagram
Authentication using React and AWS

Prompt: Generate authentication process using React with **AWS**. Use Serverless architecture.

Authentication Architecture Diagram
Open Innovation

Prompt: Create visualization of Henry Chesbrough's Open Innovation model.

Open Innovation Diagram
Cat sketch

Prompt: Draw a cute cat for me.

Cat Drawing

Features

  • LLM-Powered Diagram Creation: Leverage Large Language Models to create and manipulate draw.io diagrams directly through natural language commands
  • Image-Based Diagram Replication: Upload existing diagrams or images and have the AI replicate and enhance them automatically
  • PDF & Text File Upload: Upload PDF documents and text files to extract content and generate diagrams from existing documents
  • AI Reasoning Display: View the AI's thinking process for supported models (OpenAI o1/o3, Gemini, Claude, etc.)
  • Diagram History: Comprehensive version control that tracks all changes, allowing you to view and restore previous versions of your diagrams before the AI editing.
  • Interactive Chat Interface: Communicate with AI to refine your diagrams in real-time
  • Cloud Architecture Diagram Support: Specialized support for generating cloud architecture diagrams (AWS, GCP, Azure)
  • Animated Connectors: Create dynamic and animated connectors between diagram elements for better visualization

MCP Server

Use Next AI Draw.io with AI agents like Claude Desktop, Cursor, and VS Code via MCP (Model Context Protocol).

{
  "mcpServers": {
    "drawio": {
      "command": "npx",
      "args": ["@next-ai-drawio/mcp-server@latest"]
    }
  }
}

Claude Code CLI

claude mcp add drawio -- npx @next-ai-drawio/mcp-server@latest

Then ask Claude to create diagrams:

"Create a flowchart showing user authentication with login, MFA, and session management"

The diagram appears in your browser in real-time!

See the MCP Server README for VS Code, Cursor, and other client configurations.

Getting Started

Try it Online

No installation needed! Try the app directly on our demo site:

Live Demo

Bring Your Own API Key: You can use your own API key to bypass usage limits on the demo site. Click the Settings icon in the chat panel to configure your provider and API key. Your key is stored locally in your browser and is never stored on the server.

Desktop Application

Download the native desktop app for your platform from the Releases page:

Supported platforms: Windows, macOS, Linux.

Run with Docker

Go to Docker Guide

Installation

  1. Clone the repository:
git clone https://github.com/DayuanJiang/next-ai-draw-io
cd next-ai-draw-io
npm install
cp env.example .env.local

See the Provider Configuration Guide for detailed setup instructions for each provider.

  1. Run the development server:
npm run dev
  1. Open http://localhost:6002 in your browser to see the application.

Deployment

Deploy to EdgeOne Pages

You can deploy with one click using Tencent EdgeOne Pages.

Deploy by this button:

Deploy to EdgeOne Pages

Check out the Tencent EdgeOne Pages documentation for more details.

Additionally, deploying through Tencent EdgeOne Pages will also grant you a daily free quota for DeepSeek models.

Deploy on Vercel

Deploy with Vercel

The easiest way to deploy is using Vercel, the creators of Next.js. Be sure to set the environment variables in the Vercel dashboard as you did in your local .env.local file.

See the Next.js deployment documentation for more details.

Deploy on Cloudflare Workers

Go to Cloudflare Deploy Guide

Multi-Provider Support

  • ByteDance Doubao
  • AWS Bedrock (default)
  • OpenAI
  • Anthropic
  • Google AI
  • Google Vertex AI
  • Azure OpenAI
  • Ollama
  • OpenRouter
  • AIHubMix
  • DeepSeek
  • SiliconFlow
  • ModelScope
  • SGLang
  • Vercel AI Gateway

All providers except AWS Bedrock and OpenRouter support custom endpoints.

📖 Detailed Provider Configuration Guide - See setup instructions for each provider.

Server-Side Multi-Model Configuration

Administrators can configure multiple server-side models that are available to all users without requiring personal API keys. Configure via AI_MODELS_CONFIG environment variable (JSON string) or ai-models.json file. For a single-provider quick setup, list comma-separated model IDs in AI_MODEL.

Admin Panel

Set the ADMIN_PASSWORD environment variable and visit /admin to manage server settings (models, access codes, features, observability, quota) from a web panel instead of hand-editing .env.

📖 Admin Panel Guide — setup, precedence rules, and notes.

Model Requirements: This task requires strong model capabilities for generating long-form text with strict formatting constraints (draw.io XML). Recommended models include Claude Sonnet 4.5, GPT-5.1, Gemini 3 Pro, and DeepSeek V3.2/R1.

Note that the claude series has been trained on draw.io diagrams with cloud architecture logos like AWS, Azure, GCP. So if you want to create cloud architecture diagrams, this is the best choice.

How It Works

The application uses the following technologies:

  • Next.js: For the frontend framework and routing
  • Vercel AI SDK (ai + @ai-sdk/*): For streaming AI responses and multi-provider support
  • react-drawio: For diagram representation and manipulation

Diagrams are represented as XML that can be rendered in draw.io. The AI processes your commands and generates or modifies this XML accordingly.

Support & Contact

Special thanks to ByteDance Doubao for sponsoring the API token usage of the demo site! Register on the ARK platform to get 500K free tokens for all models!

If you find this project useful, please consider sponsoring to help me host the live demo site!

For support or inquiries, please open an issue on the GitHub repository or contact the maintainer at:

  • Email: me[at]jiang.jp

FAQ

See FAQ for common issues and solutions.

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A next.js web application that integrates AI capabilities with draw.io diagrams. This app allows you to create, modify, and enhance diagrams through natural language commands and AI-assisted visualization.
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