I built ell based on some ideas during my time as a research scientist at OpenAI around language model programming, with the aim of building the PyTorch of prompt engineering. AI engineering needs good, open-source and free tooling, so we've built a tensorboard-like visualization tool (studio) packaged along side ell to fully leverage this new library.
really excited about this, and would love some feedback!
How would you say this compares to DSPy? At first glance, ell is very application developer focused, while DSPy is more designed as a lower level framework on top of which others can build. Curious to see how this evolves for ell. Also, prompt "optimization" as per the docs is a fuzzy term - what is being optimized exactly? Basically, if I want to minimize my time doing prompt engineering (which I hate), is ell the framework for me?
