dayuan.jiang
b8b851fc5b
- A redirect followed for a custom base URL also drops the key headers of providers that do not use Authorization (x-api-key, x-goog-api-key, api-key) when it goes to another origin. - A second Enter or click while a message is being prepared (attachments read, diagram exported) no longer sends it twice. - The admin Test on the deployment's own endpoints (EdgeOne, the server's keyless Ollama, an address on the server's network) counts toward the quota like a chat; the chat and the Test share one rule for it. The Test of an Azure entry set up by AZURE_RESOURCE_NAME only goes where chat goes. - EdgeOne's function is called at the site root again, as on main: EdgeOne serves edge functions there, outside Next's base path. - MCP History: the state before a write is kept unless the browser saved no change of the user's since the last server write (draw.io's sync copy of it adds no entry), and the dedupe compares the exact text again, so a change of page size or other settings only is its own version. - MCP: an edit keeps untouched labels as draw.io shows them (a literal line break in an attribute is a space); a new document of empty pages the user named is auto-saved; load_diagram reads only regular files, so a pipe cannot hold up the other write tools; the preview does not load back its own push still on its way (an undo made meanwhile is saved). - Two overlapping saves of a new chat no longer reload the canvas from the older copy. - At most three screenshot checks per user turn, passed or failed, as documented. - Desktop: the main window navigates only within the app (draw.io stays in its frame); a presets file that is not JSON and cannot be moved aside is not overwritten. - A last self-closing cell with a raw "<" in a value is not taken for cut off output. - README: Material Design shapes load their icons from fonts.gstatic.com.
Next AI Draw.io
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!
🎁 Thanks to Atlas Cloud for sponsoring next-ai-draw-io. Its OpenAI-compatible API gives diagram workflows one provider connection for DeepSeek, Qwen, GLM, Kimi, MiniMax, and more. Budget-friendly access is available through the Coding Plan.
https://github.com/user-attachments/assets/9d60a3e8-4a1c-4b5e-acbb-26af2d3eabd1
Table of Contents
- Next AI Draw.io
Examples
Here are some example prompts and their generated diagrams:
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Animated transformer connectors Prompt: Give me a **animated connector** diagram of transformer's architecture. 
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RAG Technique Diagram Prompt: Generate a RAG architecture diagram for **chat application**. Use connected diagram for data ingestion 
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Authentication using React and AWS Prompt: Generate authentication process using React with **AWS**. Use Serverless architecture. 
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Open Innovation Prompt: Create visualization of Henry Chesbrough's Open Innovation model. 
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Cat sketch Prompt: Draw a cute cat for me. 
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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!
The MCP server includes most of the web app's drawing features:
- The same drawing rules and shape libraries (AWS, Azure, GCP, Kubernetes and more)
- A screenshot tool, so the AI can check the rendered diagram and fix it
- Version history, multi-page diagrams, and download as
.drawio,.png,.svg, or.drawio.svg - Auto-save to
~/.next-ai-drawio/, so you can continue a diagram after a restart
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:
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
Installation
- 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.
- Run the development server:
npm run dev
- 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:
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
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
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
- Atlas Cloud
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!
Special thanks to Atlas Cloud for sponsoring next-ai-draw-io and supporting its multi-provider ecosystem! Try its OpenAI-compatible LLM API through the Atlas Cloud Coding Plan.
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.