
talk2dom
Locate web elements using natural language. Powered by LLM. Works with Selenium
If you’re a QA engineer, test automation developer, or AI agent builder seeking a smarter way to interact with web elements, talk2dom is a game-changing tool that brings natural language understanding to Selenium-based workflows. By leveraging large language models (LLMs) like GPT-4 or LLaMA-3, talk2dom allows you to locate and interact with DOM elements using plain English commands, eliminating the need for brittle XPath or CSS selectors.
🔑 Key Features of talk2dom:
- Natural Language Element Location: With talk2dom, you can find elements by simply describing them. This approach reduces the complexity of writing and maintaining selectors, especially in dynamic web applications.
- ActionChain for Fluent Automation: The
ActionChain
class provides a chainable API to perform actions seamlessly and enhances readability and maintainability of test scripts. - Visual Element Highlighting: For better debugging and demo purposes, talk2dom can highlight elements it interacts with, making it easier to verify that the correct elements are targeted.
- Scoped Queries for Efficiency: You can limit the search scope to specific elements to reduce token usage and improve accuracy. This is particularly useful for complex pages with nested components.
- Model Flexibility: talk2dom supports various LLMs, including OpenAI’s GPT models and open-source alternatives like LLaMA-3, giving you flexibility based on your preferences and requirements.
🚀 Key Benefits:
- Simplified Test Creation: Write tests using natural language, reducing the learning curve for new testers.
- Reduced Maintenance: Minimize test failures due to UI changes, as talk2dom adapts to changes in the DOM structure.
- Enhanced Debugging: Visual highlights and clear error messages make it easier to identify and fix issues.
- Integration with Existing Tools: Seamlessly integrates with Selenium, allowing you to enhance existing test suites without a complete overhaul.
Tags:
SeleniumLLMMCPOpen Source