
evalkit
The TypeScript LLM Evaluation Library
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EvalKit is an open-source TypeScript library for evaluating and improving the performance of large language models (LLMs). It helps developers ensure the reliability, accuracy, and trustworthiness of their AI models. The library provides various metrics such as Bias Detection, Coherence, Faithfulness, Hallucination, Intent Detection, and Semantic Similarity. EvalKit is designed to be user-friendly with detailed documentation, tutorials, and recipes for different use cases and LLM providers. It requires Node.js 18+ and an OpenAI API Key for installation and usage. Contributions from the community are welcome under the Apache 2.0 License.
README:
The TypeScript LLM Evaluations Library
EvalKit is an open-source library designed for TypeScript developers to evaluate and improve the performance of large language models (LLMs) with confidence. Ensure your AI models are reliable, accurate, and trustworthy.
Click here to navigate to the Official EvalKit Documentation
In the documentation, you can find information on how to use EvalKit, its architecture, including tutorials and recipes for various use cases and LLM providers.
Feature | Availability | Docs |
---|---|---|
Bias Detection Metric | โ | ๐ |
Coherence Metric | โ | ๐ |
Dynamic Metric (G-Eval) | โ | ๐ |
Faithfulness Metric | โ | ๐ |
Hallucination Metric | โ | ๐ |
Intent Detection Metric | โ | ๐ |
Semantic Similarity Metric | โ | ๐ |
Semantic Similarity Metric | โ | ๐ |
Reporting | ๐ง | ๐ง |
Looking for a metric/feature that's not listed here? Open an issue and let us know!
- Node.js 18+
- OpenAI API Key
EvalKit currently exports a core package that includes all evaluation related functionalities. Install the package by running the following command:
npm install --save-dev @evalkit/core
We welcome contributions from the community! Please feel free to submit pull requests or create issues for bugs or feature suggestions.
This repository's source code is available under the Apache 2.0 License.
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