Consistency and reliability are crucial for conducting AI research. Many famous research fields, such as object detection, have been compared and validated with solid benchmark frameworks. After AlphaFold2, the protein folding task has entered a new phase, and many methods are proposed based on the component of AlphaFold2. The importance of a unified research framework in protein folding contains implementations and benchmarks to consistently and fairly compare various approaches. To achieve this, we present Solvent, an protein folding framework that supports significant components of state-of-th-arts models in the manner of off-the-shelf interface Solvent contains different models implemented in a unified codebase and supports training and evaluation for defined models on the same dataset. We benchmark well-known algorithms and their components and provide experiments that give helpful insights into the protein structure modeling field. We hope that Solvent will increase the reliability and consistency of proposed models and gives efficiency in both speed and costs, resulting in acceleration on protein folding modeling research. The code is available at https://github.com/kakaobrain/solvent, and the project will continue to be developed.

通过统一的研究框架和基准测试，利用 Solvent 项目中的各种方法，可提供稳健、高效的蛋白质折叠模型研究，从而增加了模型的可靠性、一致性和研究速度，进一步推进蛋白质折叠领域的发展。

溶剂: 蛋白质折叠的框架