Ensure high-quality LLM outputs with automatic evals. Use a representative sample of user inputs to reduce subjectivity when tuning prompts. Use built-in metrics, LLM-graded evals, or define your own custom metrics. Compare prompts and model outputs side-by-side, or integrate the library into your existing test/CI workflow. Use OpenAI, Anthropic, and open-source models like Llama and Vicuna, or integrate custom API providers for any LLM API.

Features

  • Create a list of test cases
  • Set up evaluation metrics
  • Select the best prompt & model
  • Use a representative sample of user inputs to reduce subjectivity when tuning prompts
  • Use built-in metrics, LLM-graded evals, or define your own custom metrics
  • Compare prompts and model outputs side-by-side, or integrate the library into your existing test/CI workflow

Project Samples

Project Activity

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License

MIT License

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Additional Project Details

Programming Language

TypeScript

Related Categories

TypeScript Large Language Models (LLM)

Registered

2023-08-25