Fun with Chrome Extensions
In my previous post, I worked on leveraging an LLM to generate test cases based on a Github Diff. I wanted to take this a step further, so I built a Chrome Extension to accomplish this process in 3 clicks.
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In my previous post, I worked on leveraging an LLM to generate test cases based on a Github Diff. I wanted to take this a step further, so I built a Chrome Extension to accomplish this process in 3 clicks.
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A while ago I found myself in an unfavorable situation: Testing a branch with numerous changes and limited time to validate each one. Having used GeminiAI in the past to resolve flaky locators in Playwright, I began to wonder if I could leverage an LLM to review the diff retreived from Github and generate test cases specific to the changes in the merge request.
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I was intrigued by the idea of leveraging the capabilities of a cloud-based LLM to resolve failures encountered by Playwright tests. In this article, I share the approach I took to integrate Google Gemini into a Playwright setup, along with some of the benefits and challenges I encountered along the way.
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Writing API Layer tests in a shared environment can present a number of challenges; Rate limits, Downtime and loss of test data to name a few. Using a mock backend service may help overcome these roadblocks in the test automation process.
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A few weeks ago I set up a local LLM environment using Ollama, Qwen2.5-Coder and Open WebUI...
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