liujuntao123/smart-excalidraw-next

A smart, powerful, and beautiful excalidraw drawing tool.Draw Professional Charts with Natural Language

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Summary Information

Updated 9 minutes ago
Added to GitGenius on September 19th, 2026
Created on October 30th, 2025
Open Issues & Pull Requests: 28 (+0)
GitHub issues: Enabled
Number of forks: 431
Total Stargazers: 3,517 (+0)
Total Subscribers: 17 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 26.2 hours
Mean response time: 10.9 days
90th percentile: 18.1 days
Tracked items: 13

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Issue Activity (beta)

Open issues: 20
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 273 days
Stale 30+ days: 20
Stale 90+ days: 19

Recent activity

Opened in 7 days: 0
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

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Detailed Description

Smart Excalidraw is a drawing tool that generates professional diagrams from natural language descriptions using AI.

The tool solves the problem of creating structured, well-laid-out diagrams quickly without manual design effort. It uses large language models to interpret text descriptions and generate diagrams in Excalidraw format, which can then be freely edited and refined on the canvas. The project includes a proprietary arrow optimization algorithm designed to automatically calculate optimal connection points between elements, reducing visual clutter and improving diagram clarity.

The tool supports over twenty diagram types including flowcharts, architecture diagrams, sequence diagrams, entity-relationship diagrams, and mind maps, with AI capable of selecting appropriate diagram types based on user descriptions. It requires only an AI API key to begin use, with all configuration stored locally in the browser. Users can either provide their own API key from OpenAI or Anthropic, or use a server-side configuration via an access password if the administrator has set one up. The generated diagrams are fully editable within Excalidraw, allowing users to combine AI generation with manual refinement.

Development activity shows consistent engagement with the codebase through regular commits and updates to core functionality. The project maintains active documentation in multiple languages and includes example screenshots demonstrating various diagram types and use cases. Recent work has focused on expanding diagram type support and refining the AI integration workflow.