The core shift here is the "discovery" phase. Instead of hardcoding #username-field-v2
, you find an element and Vibium gives you a temporary reference like @e1
. You then act on that reference. It's a much more interactive, agentic way to handle the browser.
Getting Started from Scratch #
Setting this up is straightforward since it handles the browser binaries for you.
- Install the CLI via npm:
npm install -g vibium
- Test the connection:
vibium go https://example.com
(This will automatically pull a Chrome for Testing build if you don't have one).## Practical Tutorial: Automating a Login
I tested this on the OrangeHRM demo site to see if it actually removes the friction of selector management. Here is the raw workflow:
vibium record start
vibium go "https://opensource-demo.orangehrmlive.com"
vibium map
vibium fill "@e1" "Admin"
vibium fill "@e2" "admin123"
vibium click "@e3"
vibium record stop
By using vibium map
, the tool identifies elements using semantic signals—labels, placeholders, and the accessibility tree—rather than just brittle XPaths.
Vibium vs. Playwright vs. Selenium #
I'm naturally skeptical of "simpler" tools because they usually sacrifice power for ease of use. Here is how they stack up:
Setup Overhead: Vibium is the fastest (CLI based) vs. Playwright/Selenium (Framework based).Element Targeting: Vibium uses semantic references (@e1) vs. Playwright/Selenium using CSS/XPath.Workflow: Vibium is designed for agentic/CLI usage andMCPservers vs. the others being designed for structured test suites.Stability: Playwright is the gold standard for enterprise CI/CD; Vibium is better for rapid prototyping and LLM-driven AI workflows.
If you're building a massive regression suite, stick to Playwright. But if you're building an LLM agent or need a quick hands-on guide to scrape/automate a site without writing a full project scaffold, this CLI approach is significantly faster.
Next OpenAI vs Hugging Face: The Open-Source Tension →