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draw-a-ui vs OpenHands

Which should you use? A side-by-side look at what each one does, who it suits, what it costs, how hard it is to set up, and where each falls short.

draw-a-ui

Open source · MIT

Draw a rough wireframe in a canvas and get HTML/Tailwind code generated from it by GPT-4 Vision.

OpenHands

Open source · MIT

A self-hosted control panel that runs AI coding agents on your machine, in Docker, or in the cloud.

The short answer

Choose draw-a-ui if you need…

  • Developers exploring how vision models can turn sketches into HTML
  • Designers who want a quick rough draft of a page layout as code
  • People learning how to connect a canvas drawing tool to an AI API
  • Anyone who wants a starting point for a Tailwind-based page

Choose OpenHands if you need…

  • Developers who want coding agents running on a server while their laptop is off
  • Teams that want a shared agent server for tasks like code review or dependency updates
  • People who want to connect agents to Slack, GitHub, or Linear through automations
  • Users who want to choose their own LLM provider

Side-by-side

draw-a-uiOpenHands
TypeAppApp
PriceFree and open sourceFree and open source
LicenceMITMIT
GitHub stars13.6k92.5k
Setup difficultyBeginnerIntermediate
How you get itClone and build from sourceInstall with a package manager
Main languageTypeScriptTypeScript
Last code update16 months ago4 days ago

What each one is

draw-a-ui

draw-a-ui is a Next.js web app built on the tldraw drawing canvas. You sketch a wireframe, the app exports the canvas as an image, and sends it to OpenAI's gpt-4-vision API with instructions to return a single HTML file styled with Tailwind. It is a demo that shows how an image of a layout can be turned into working front-end code.

OpenHands

Agent Canvas is a self-hosted control center for AI coding agents. You start conversations with agents and set up automations, such as generating reports that publish to Slack or breaking GitHub issues into tasks. It runs on your own machine by default and can also connect to agents running in Docker, on virtual machines, or on OpenHands Cloud or Enterprise infrastructure. It can run the open source OpenHands agent or third-party agents such as Claude Code, Codex, and Gemini CLI.

Best for

draw-a-ui

  • Developers exploring how vision models can turn sketches into HTML
  • Designers who want a quick rough draft of a page layout as code
  • People learning how to connect a canvas drawing tool to an AI API
  • Anyone who wants a starting point for a Tailwind-based page

OpenHands

  • Developers who want coding agents running on a server while their laptop is off
  • Teams that want a shared agent server for tasks like code review or dependency updates
  • People who want to connect agents to Slack, GitHub, or Linear through automations
  • Users who want to choose their own LLM provider

Strengths

draw-a-ui

  • Simple idea that is easy to follow from the README
  • Built on established tools: Next.js, tldraw and the OpenAI API
  • Open source under the MIT license

OpenHands

  • Self-hosted, so you control where agents run and where your work is stored
  • Supports several agents and backends from one frontend
  • Released under the MIT license with a large public community (about 92,000 stars)

Not ideal for

draw-a-ui

  • Production deployment: the README says it is a demo with no auth, so it could run up API costs for anyone who finds it
  • Users without an OpenAI API key with GPT-4 Vision access, since the app cannot work without one
  • People needing pixel-accurate or production-ready code, since the output is generated and not reviewed

OpenHands

  • People who need strong isolation by default: the quickstart without a sandbox gives the agent full access to your filesystem
  • Non-technical users who are not comfortable with Node.js, npm, Docker, or the command line
  • Anyone who needs a fully hosted service with no setup, since the README centers on self-hosting

Trade-offs

draw-a-ui

  • Depends on a paid OpenAI API key with GPT-4 Vision access
  • README explicitly says it is a demo, not for production, and has no authentication
  • Output quality depends on the model and the sketch; the README does not describe accuracy

OpenHands

  • Running without a sandbox gives the agent full access to your filesystem, so the Docker options need careful setup
  • Multiple features depend on configuring backends, LLM keys, and integrations, which takes effort
  • The README is truncated and does not fully document security hardening or every integration; see the linked docs

Getting started

draw-a-ui

Create env file with your OpenAI key

echo "OPENAI_API_KEY=sk-your-key" > .env.local

Install dependencies

npm install
Step-by-step guide: how to use draw-a-ui

OpenHands

Install globally with npm (no sandbox)

npm install -g @openhands/agent-canvas

Start the full local stack

agent-canvas
Step-by-step guide: how to use OpenHands

Frequently asked questions

What is the difference between draw-a-ui and OpenHands?

draw-a-ui: Draw a rough wireframe in a canvas and get HTML/Tailwind code generated from it by GPT-4 Vision. OpenHands: A self-hosted control panel that runs AI coding agents on your machine, in Docker, or in the cloud. draw-a-ui suits developers exploring how vision models can turn sketches into html, while OpenHands suits developers who want coding agents running on a server while their laptop is off.

Are draw-a-ui and OpenHands free?

draw-a-ui: Free and open source. OpenHands: Free and open source.

Which is easier to set up, draw-a-ui or OpenHands?

draw-a-ui is easier to get started with (rated beginner); OpenHands is rated intermediate and usually needs more setup.

Is draw-a-ui or OpenHands more popular?

OpenHands has more GitHub stars (92.5k) than draw-a-ui (13.6k). Popularity isn't the same as fit — check which one matches your use case above.

What are other alternatives to draw-a-ui and OpenHands?

Other options people compare them with include Screenshot to Code, One API, LlamaGPT, CowAgent, LibreChat.

Keep comparing

Built from our catalogue entries for both products: open-source details come from each project's README (AI-assisted, refreshed weekly) and GitHub data; AI-tool details are editorial. Spotted something wrong? Let us know from either product's page.