As it is, the apparent reliance on github & github actions/apps, and the lack of openness where I can't run the LLM magic myself in an environment I control makes it A) impossible to use in a corporate environment and B) not entirely well aligned with my own FOSS values to use privately.
Edit: to expand, this is the "getting started" section.
- Add the Sweep GitHub app to desired repos
- Create new issue in repo, like "Sweep: Write tests". [...]
- Watch the magic happen
Right now only GPT-3.5 and GPT-4 seem to be capable of this sort of "code editing" task. But aider has support for connecting to other/local LLMs and an active community of folks experimenting with them.
Also, the onboarding flow for GitHub Apps is significantly smoother and is a familiar interface for many people. We built a CLI-installed tool previously and there were a ton of versioning and environment-related problems etc, with 3 OS's to support. Unfortunately, it becomes harder to focus on building the best tool for our users if our focus is too broad.
To your last point, you can pry into our codebase and our blogs to see what we do under the hood; "Watch the magic happen" is just referring to the simplicity of our installation process. Also, we only store the logs for debugging and they only get persisted 30 days (which is also how long OpenAI stores them for). We gave a lot of thought to designing our search engine that doesn't store any code in plaintext. Check it out here: https://docs.sweep.dev/blogs/search-infra
I'm really interested if there is any software or open source projects that make this type of thing easier- specifically the idea of creating multiple "phases" or "tasks" that each has their own LLM prompt and validation rules (like each node in the flowchart.) I think something like that could be very helpful!