Make mlops module independent of train and serving modules

Previously, MLOps orchestration was possible within a Lamber. Now with new dependencies, they are too big to fit in the lambda. The native dependencies and PyTorch explode the size of the total deployment signficantly

首先追踪 MLOps、train 和 serving 模块之间的依赖关系，然后复现 issue 中描述的 Lambda 打包大小问题。确定哪些原生依赖项和 PyTorch 被引入了 MLOps 部署中。当 MLOps 编排可以在不包含这些不必要依赖项的情况下独立打包时，即视为完成。

由索引模型根据 Issue 内容生成。