Announcing Eval Protocol
Blog post from Fireworks AI
Eval Protocol (EP) is an open-source library and SDK designed to bring software development lifecycle rigor to the development of large language model (LLM) applications, providing a standardized method for evaluating these models akin to unit testing and CI/CD automation. EP addresses the challenges developers face with LLMs by standardizing evaluations from initial model selection to production deployment, offering immediate benefits such as automated CI/CD checks to prevent regressions. It supports both single-turn and multi-turn evaluations, allowing developers to optimize and customize their models over time. EP facilitates seamless integration into existing workflows through tools like GitHub Actions and provides resources to help developers transition from basic quality checks to advanced model customization, effectively bridging the gap between quick wins and long-term improvements in LLM application development.
| Trend | Post Mentions | Total Month Mentions | Posts | Companies | MoM |
|---|---|---|---|---|---|
| LLM | 7 | 3,922 | 600 | 189 | -6% |
| MCP | 5 | 3,840 | 275 | 112 | +19% |
| AI Model Fine-tuning | 2 | 568 | 107 | 59 | -14% |
| Observability | 1 | 1,883 | 347 | 119 | -9% |
| Reinforcement learning | 1 | 98 | 39 | 26 | -36% |
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