evidently vs llm-action
A neutral, constraint-first comparison - live GitHub stats and typed relationships, not marketing.
| evidently | llm-action | |
|---|---|---|
| Tagline | Evidently is an open-source ML and LLM observability framework. | 分享大模型技术原理与实战经验，涵盖工程化和应用落地 |
| Stars | 7.7k | 25k |
| Forks | 874 | 2.8k |
| Open issues | 285 | 18 |
| Language | Jupyter Notebook | HTML |
| License | Apache-2.0 | Apache-2.0 |
| Last pushed | May 2, 2026 | Jul 1, 2026 |
| Categories | Evaluation & Observability | Inference & Serving, Evaluation & Observability, Model Training, LLM Frameworks, Developer Tools |
evidently
Evidently is a Python library for evaluating, testing, and monitoring machine learning (ML) and large language model (LLM) systems from experiments to production. It supports a wide range of evaluation metrics and can be used both offline and in live environments.
Jupyter Notebook
llm-action
该项目针对各种大规模语言模型提供技术细节及实践指导，包括训练、推理优化以及其他相关领域的知识。内容涉及LLM的高效微调、分布式训练并行技术、推理框架以及性能测评等。
HTML