Introducing Align Evals: Streamlining LLM Application Evaluation 🚀
LangChain · 2025-07-29 · 13м 16с · 6 945 просмотров · YouTube ↗
Топики: ai-agent-orchestration
Аудио ещё не скачано.
📝 Summary
Summary ещё не сгенерён.
📜 Transcript
Transcript ещё не сделан.
⚙️ Pipeline jobs
Нет job'ов в очереди.
📄 Описание YouTube
Показать
Evaluations are a key technique for improving your application — whether you’re working on a single prompt or a complex agent. Iterating on evaluators has often involved a lot of guesswork. With Align Evals you get: - A playground-like interface to iterate on your evaluator prompt and see the evaluator’s “alignment score” - Side-by-side comparison of human-graded data and LLM-generated scores, with sorting to identify “unaligned” cases - A saved baseline alignment score in order to compare your latest changes to the previous version of your prompt Get started by heading to our developer documentation: https://docs.smith.langchain.com/evaluation/tutorials/aligning_evaluator Leave us your feedback in the LangChain community form: https://forum.langchain.com/t/introducing-align-evals-streamlining-llm-application-evaluation/817