Automated Visual Regression Testing with Apify, Google Gemini, and Google Drive

Overview

This workflow streamlines visual regression testing by integrating Apify, Google Gemini AI, and Google Drive. It automates the process of capturing, analyzing, and storing website screenshots to detect visual changes over time.

Key Features

• Automated Screenshot Capture: Downloads website screenshots for comparison.
• AI-Powered Analysis: Utilizes Google Gemini's vision model to detect visual differences.
• Batch Processing: Efficiently processes multiple images using split-in-batches and wait nodes.
• Structured Output Parsing: Extracts and organizes AI analysis results for actionable insights.
• Cloud Storage Integration: Uploads and updates base images in Google Drive for version control.
• Scheduling: Runs on a set schedule for continuous monitoring.

Benefits

• Early Detection: Quickly identifies unintended visual changes, reducing manual QA effort.
• Consistency: Ensures UI consistency across deployments and updates.
• Time Savings: Automates repetitive testing tasks, freeing up developer resources.
• Scalability: Handles large volumes of images and tests with batch processing.

Use Cases

• Continuous integration pipelines for web applications.
• Automated UI/UX regression testing for product teams.
• Monitoring marketing or e-commerce sites for visual consistency.

Integrations

• Google Drive: For image storage and version management.
• Google Gemini AI: For advanced vision-based comparison.
• Apify: For automated screenshot capture.

This workflow delivers robust, scalable, and intelligent visual regression testing for modern web teams.