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View All on GitHubEnd-to-End Testing with AI for Agents and Engineers
End-to-End Testing with AI for Agents and Engineers
End-to-End Testing with AI for Agents and Engineers
End-to-End Testing with AI for Agents and Engineers
End-to-End Testing with AI for Agents and Engineers
End-to-End Testing with AI for Agents and Engineers
End-to-End Testing with AI for Agents and Engineers
End-to-End Testing with AI for Agents and Engineers
End-to-End Testing with AI for Agents and Engineers
End-to-End Testing with AI for Agents and Engineers
End-to-End Testing with AI for Agents and Engineers
AI Summary: This issue requests the ability to configure a custom base URL for Ollama, allowing it to connect to remote deployments instead of being limited to local instances. The proposed solution involves using an environment variable, `ALUMNIUM_OLLAMA_BASE_URL`, to specify the remote endpoint, similar to how other cloud service integrations handle base URLs.
End-to-End Testing with AI for Agents and Engineers
AI Summary: Modify the Alumnium AI-powered test automation library to capture screenshots of specific areas (defined by selectors) instead of full-page screenshots when using `area.get` or `area.check` with `vision=True`. This improvement aims to enhance stability and reduce data sent to LLMs.
End-to-End Testing with AI for Agents and Engineers
AI Summary: Integrate the ability to use Mistral large language models (LLMs), specifically the Mistral-small 3.1 24B model accessed via an API, within the Alumnium AI-powered test automation framework. This requires adding API interaction capabilities to Alumnium to handle requests to the Mistral API and integrating the LLM responses into the existing test automation workflow.
End-to-End Testing with AI for Agents and Engineers