Stop “vibe testing” your LLMs. It's time for real evals.

Stax is an experimental developer tool designed to streamline the evaluation of large language models (LLMs) by offering a structured approach to move beyond subjective "vibe testing." Built with insights from Google DeepMind and Google Labs, Stax addresses the non-deterministic nature of AI models by providing a framework for creating custom evaluations tailored to specific use cases. It facilitates data-driven testing by allowing developers to upload or create datasets and employ pre-built or custom autoraters to assess outputs for coherence, factuality, and other criteria. This tool emphasizes real, repeatable evaluations using both human input and LLMs as judges, enabling developers to define their unique standards and rigorously test AI systems for their specific needs. Stax aims to transform AI evaluation from a guesswork-driven process into one that is robust and metric-based, encouraging developers to treat AI components with the same scrutiny as other production stack elements.

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