Evalite, a TypeScript-native eval runner by Matt Pocock, offers a specialized test harness for AI applications, allowing developers to create reproducible evals with comprehensive trace capture and a user-friendly web interface. Reaching its v1 beta, Evalite aims to be the go-to testing tool for applications utilizing large language models (LLMs), similar to Vitest and Jest.
Evalite treats evals like test suites with advanced outputs, scoring each data point from .eval.ts files. It features a local dev server for real-time iteration and integrates familiar test practices. With a focus on efficiency, Evalite supports various run modes, enabling teams to track evaluation trends and customize success metrics. Recent updates include AI SDK model caching, enhancing speed and model iteration. The community has shown strong support, with the GitHub repository gaining interest. As an open-source platform under MIT, Evalite prioritizes control and flexibility, making it an invaluable tool for testing AI-driven applications.
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