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write LLM evals like you write software tests (pytest/vitest/jest) writing software tests is standard practice. writing evals for LLMs is equally important, but we don't see it as common place yet we hope this helps bridge the gap! https://t.co/GZozKNbOw0
pretty cool - bring your LLM evals into your code (pytest) and then they are auto synced with langsmith https://t.co/ygiDMoZ3nv
🎉 Easier evals are here! Evals are a vital part of bringing LLM apps into production, but are often ignored because they are tedious to set up. This new DX with Pytest/Vitest reduces that friction! Really excited to ship this w/ @baga_tur! Let us know what you think. https://t.co/IO1dy689aV
LangChainAI has announced a new integration that allows developers to test their large language model (LLM) applications using familiar test frameworks such as Pytest, Vitest, and Jest. This initiative aims to simplify the evaluation process for LLM apps, which are often overlooked due to the tedious setup involved. The integration enables users to curate datasets of example inputs and outputs, facilitating easier evaluations. Developers expressed enthusiasm for this development, highlighting its potential to bridge the gap between software testing and LLM evaluations, which are becoming increasingly important in production environments.
