| dozens of great ideas in here pedro. > The main feature allows specific code chunks to be referenced and edited/removed/appended to. Do you know if it works to just include in the system message something like "When editing a function, don't rewrite the whole thing, be sure to edit modules piecemeal e.g. Foo.NestedFooClass.bar_method = ..."? > imports could be auto-added when missing and unambiguous GREAT idea. You're write, tons of low hanging fruit here. A preprocess.py file should probably be added to Open Interpreter with all these ideas— what do LLMs tend to fail at that we can programmatically correct in each code block? Then just run that on each block it writes before asking the user for approval to run it. > logit warping to boost tokens corresponding to names/keywords valid in the current scope WOAH. Have you heard of outlines? (https://normal-computing.github.io/outlines/) Lets you put in any Regex you want, then as the LLM is generating, logit bias is used to conform the output to that Regex. Works for local models. I can totally imagine pairing some linting function with outlines to get models to write automatically linted code on the first pass. For my thing, I abandoned IPython since I wanted a more uniform approach to multiple programming languages. Open Interpreter keeps a single subprocess open with `python -i` to get a live Python interpreter that displays a real-time output. It's acts the same as IPython, but I can just swap out that command (for example, with `node -i`) to get different languages. I think this also gets around the issues with cell magic, which as you've said, might confuse it— instead we just ask the model to tell us what language it wants to use + the code it wants to run in a single function call. Have thought a lot about letting the user edit code. The next version of Open Interpreter = an electron app with a UI so you can edit code before it runs, better copy/paste, convo history, etc. > with a broken backspace key By the way, have you heard of this idea of training models to use a backspace key? Powerful stuff. We could think about implementing this in preprocess.py — another pass by GPT-4 or whatever to edit things it thinks isn't going to work. To the user it would just look like GPT-4 has a working backspace key. Would love to see your github on these if you're willing to share! Open Interpreter is MIT license so ideally I could make it attractive enough / similar enough to your project to simply join up / contribute some of these ideas. |