With our framework, if you want flexibility for
> You know exactly what goes into the prompt, how it’s parsed, what params are used or when they are changed
We provide this for you. We just give you a process that lets you try and evaluate different configurations of your LLM application layer at scale.
Frameworks are more process driven for achieving a complex task. This is like ReactJS with their component mode -- they set a process for building web application such that you can build more complex applications. At the same time, you have lots of flexibilities in the implementation details of your application. Framework should provide as much flexibilities as possible.
Similarly, we are trying to build our framework for streamlining the process for LLM development such that you can iterate on your LLM application faster. To help setup this process, we enforce very high-level interfaces for how you build(input & output schema), evaluate, deploy your application. We provide all the flexibilities to the developer for low-level implementation details and ensure it's extensible so you can also use any external tools you want within the framework.
You know exactly what goes into the prompt, how it’s parsed, what params are used or when they are changed. You can abstract away as much or as little of it as you like. Your API is going to change only when you make it so. And everything you learn about patterns in the process will be applicable to Python in general - not just one framework that may be replaced two months from now.