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With TestMu AI (Formerly LambdaTest), you can run SmartUI visual regression tests for Storybook components across real browsers and operating systems using the @lambdatest/smartui-storybook CLI.
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Sign up on TestMu AI (Formerly LambdaTest).
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Follow the TestMu AI Documentation for the full setup walkthrough.
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Basic understanding of Storybook.
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Node.js version higher than
14.15.0. See Node.js releases. -
Storybook version higher than
6.4.0. See Storybook releases. -
A TestMu AI account — sign up here and log into TestMu AI SmartUI.
Clone the repository:
git clone https://github.com/LambdaTest/smartui-storybook
cd smartui-storybook
Install the SmartUI Storybook CLI globally:
npm install @lambdatest/smartui-storybook -g
Add the following to your .storybook/main.js:
module.exports = {
features: {
buildStoriesJson: true,
},
};Create a SmartUI project at the Projects page, then set your project token:
- For Linux/macOS:
export PROJECT_TOKEN="123456#1234abcd-****-****-****-************"
- For Windows:
set PROJECT_TOKEN="123456#1234abcd-****-****-****-************"
Generate the SmartUI configuration file:
smartui config create .smartui.json
Execute visual regression tests on your Storybook components:
smartui storybook http://localhost:6006 --config .smartui.json
When given a URL, the CLI renders the running Storybook directly from that URL. It starts a TestMu AI tunnel so the SmartUI renderer can reach a Storybook on localhost or on your internal network, and stops the tunnel once the build finishes. The URL can be a Storybook dev server started with npm run storybook (webpack or Vite builder) or any hosted build.
The tunnel needs your TestMu AI (Formerly LambdaTest) username and access key. Pass them as options or set them in the environment:
smartui storybook http://localhost:6006 --config .smartui.json --userName <LT_USERNAME> --accessKey <LT_ACCESS_KEY>
export LT_USERNAME="<your username>"
export LT_ACCESS_KEY="<your access key>"
smartui storybook http://localhost:6006 --config .smartui.json
Keep the CLI running until it reports the build result: the tunnel stays open until the build finishes or fails, or until the CLI has waited two hours, in which case it closes the tunnel and exits with a non-zero code. If the dev server is still compiling when you run the command, open the Storybook once in a browser first so that the first render does not time out.
For a Storybook URL the renderer keeps the load on your tunnel low: the stories are split into chunks of chunkSize stories (default 50 for a Storybook URL, minimum 25, maximum 100) and each chunk renders every configured browser, viewport and custom viewport one after another, reusing the assets it already fetched through the tunnel. A chunk therefore produces chunkSize × browsers × viewports screenshots; lower chunkSize in the config file for Storybooks with many browsers and viewports so that individual chunks stay short.
You can always provide a path to the storybook-static directory instead of the local Storybook URL. Use --help for more information on usage.
To test locally hosted apps, set up the TestMu AI tunnel. OS-specific guides:
This applies to a storybook-static build whose pages need a tunnel to load assets. For a Storybook URL the CLI starts its own tunnel and the tunnel block in the config file is ignored. Configure the tunnel in your SmartUI config:
{
"tunnel": true
}
Contributions are welcome. Open an issue to discuss your idea before submitting a pull request. When reporting bugs, include your Node.js version, OS, and npm version.
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On January 12, 2026, LambdaTest evolved to TestMu AI, the world's first fully autonomous Agentic AI Quality Engineering Platform.
Same team. Same infrastructure. Same customer accounts. All existing LambdaTest logins, scripts, capabilities, and integrations continue to work without change.
ð Find the new home for LambdaTest.
In 2017, we launched LambdaTest with a simple mission: make testing fast, reliable, and accessible. As LambdaTest grew, we expanded into Test Intelligence, Visual Regression Testing, Accessibility Testing, API Testing, and Performance Testing, covering the full depth of the testing lifecycle.
As software development entered the AI era, testing had to evolve, too. We rebuilt the architecture to be AI-native from the ground up, with autonomous agents that plan, author, execute, analyze, and optimize tests while keeping humans in the loop. The platform integrates with your repos, CI, IDEs, and terminals, continuously learning from every code change and development signal.
That evolution earned a new name: TestMu AI, built for an AI-first future of quality engineering. TestMu is not a new name for us. It is the name of our annual community conference, which has brought together 100,000+ quality engineers to discuss how AI would reshape testing, long before that became an industry norm.
What started as a high-performance cloud testing platform has transformed into an AI-native, multi-agent system powering a connected, end-to-end quality layer. That evolution defined a new identity: LambdaTest evolved into TestMu AI, built for an AI-first future of quality engineering.
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