Automate Visual Regression Testing with AI and n8n
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Streamline your website's visual consistency with an automated regression testing workflow powered by n8n. This solution leverages AI to compare screenshots, detect changes, and report issues directly to your team.
About This Workflow
This n8n workflow automates the critical process of visual regression testing, ensuring your website's user interface remains consistent across deployments. It begins by downloading existing base screenshots from Google Drive. Then, it generates new screenshots of the same web pages using an external screenshotting service. These two sets of images are fed into Google's Gemini Vision model, which intelligently compares them to identify any visual discrepancies. The workflow is designed for efficiency, allowing you to update base images when necessary and automating the detection of unintended UI changes. Finally, any detected differences are compiled into a clear, actionable report that's automatically created as an issue in Linear.app, or can be easily adapted for other project management tools like Jira or Slack.
Key Features
- Automated Screenshot Comparison: Utilizes AI vision models to detect visual differences between base and current website screenshots.
- Dynamic Image Generation: Integrates with external services to capture up-to-date webpage screenshots.
- Intelligent Change Detection: Employs Google Gemini's vision capabilities for accurate and nuanced visual analysis.
- Structured AI Output: Parses AI responses into a structured JSON format for easy integration and reporting.
- Seamless Issue Reporting: Automatically creates issues in Linear.app (or alternatives) with detailed change reports.
How To Use
- Configure Google Drive: Set up credentials for accessing your Google Drive to store and retrieve base images.
- Integrate Screenshot Service: Connect to an external screenshotting service (like Apify, mentioned in the notes) to generate new webpage screenshots.
- Set Up Gemini API: Configure your Google Gemini (PaLM) API credentials to enable the AI vision model.
- Define Output Schema: Customize the
Structured Output Parsernode with the specific JSON schema required for your AI response analysis. - Specify Reporting Tool: Configure the
Linear.appnode (or swap for Jira/Slack) with your API credentials and desired settings for creating issues. - Input Webpage URLs: Provide the list of URLs to be tested, either directly or through an upstream node.
- Run and Monitor: Execute the workflow to generate base images or to perform regression tests, and monitor the generated issues for detected changes.
Apps Used
Workflow JSON
{
"id": "05296013-55fb-4c76-a722-ddce88c3e917",
"name": "Automate Visual Regression Testing with AI and n8n",
"nodes": 12,
"category": "DevOps",
"status": "active",
"version": "1.0.0"
}Note: This is a sample preview. The full workflow JSON contains node configurations, credentials placeholders, and execution logic.
Get This Workflow
ID: 05296013-55fb...
About the Author
Crypto_Watcher
Web3 Developer
Automated trading bots and blockchain monitoring workflows.
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