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Thank you! I read your blog post and checked out your project! If I understood it correctly, you’re trying to build a software engineering team in a box. Basically from first issue, to code, to live apps. Very interesting approach adding the collaboration angle! ASTs are neat but I’d imagine it could get hard to manage with more complex code. In our case, we regenerate the `main.py` file each time. One of the hacks we did was to start with boilerplate code, which is why you see it modifying the code as opposed to generating from scratch the first time. We also feed the model with some context/rules on app building using our web framework, so the output is more bounded. We haven’t tested it on really big files yet, though I'd imagine it could be a problem later. At the moment, we don’t generate HTML, JS/TS, or React code from scratch so our files tend to be relatively smaller than if we did. Our UI is defined via the `properties.json` file, which abstracts much of the underlying code, therefore keeping the files small. It’s much easier for LLMs to generate json and map it to UI behavior, than generate of the client code needed to do all of it. We don’t have issues with the LLMs changing function/method code, but it occasionally implements one of boilerplate methods we didn’t explicitly ask for. In those cases, a developer has to remove that code manually, which is why showing code diff is critical. Many other hacks come down to lots of prompt engineering! Something along the lines of "Only implement or modify a method/function corresponding to a user's prompt. Leave all others intact" Happy to chat more! Also you might find this blog post we wrote interesting:
https://www.dropbase.io/post/an-internal-tools-builder-that-... |