Stumbling Across SWE-agent: Simple, Yet Awesome
So, I was poking around on GitHub and found this cool project called SWE-agent. At first, I was like, “Neat, it fixes GitHub issues on its own!” Then it hit me—this is the same agent killing it on SWE-bench, a benchmark that throws real-world coding problems at AI. With a 12.5% solve rate, SWE-agent’s doing better than a lot of fancier tools out there, and it’s keeping things super simple. Less is more, right?
UPD: And now everything lights up - OpenAI updated Codex, which is the ancestor of the SWE-agent, and it’s now available for free. Ofc it’ll bind you to the OpenAI API, but it’s still a great opportunity to try it out. XMas in May, right?
What’s SWE-agent All About?
SWE-agent is this open-source tool that lets language models tackle coding tasks like a pro. It’s got this thing called an Agent-Computer Interface (ACI) that helps the AI zip through repos, tweak code, and run tests without breaking a sweat. Unlike beefy tools like Replit’s Roo or GitHub’s Copilot, SWE-agent’s vibe is minimal—basic commands, no fluff. Even its system prompt is short and sweet, which is wild for something this powerful.
And the results? Pretty darn impressive. On SWE-bench, with 2,294 tough tasks from 12 big Python repos, SWE-agent nails 12.5% of them when paired with GPT-4. Humans would crush it at 100%, but for an AI, that’s legit—especially when big shots like Claude 2 and GPT-4 barely hit 5% on their own.
Digging into the Research
I got curious and checked out the research paper by Yang et al. (2024). It’s a bit of a slog, but totally worth it. They talk about how ACIs are like IDEs for AI—giving models the right tools to shine. SWE-agent’s ACI makes file navigation and editing a breeze, so the model can focus on fixing stuff instead of wrestling with clunky bash commands.
The paper backs it up with solid numbers: SWE-agent hits a 12.5% pass@1 on SWE-bench and an 87.7% pass rate on HumanEvalFix. It’s like, yup, all those trial-and-error runs weren’t lying—smart design makes a basic model go far.
Reminds Me of Plandex
While geeking out over SWE-agent, I kept thinking of Plandex, this under-the-radar tool that’s also all about keeping things simple. Plandex is more about planning and team vibes, but it’s got that same “let’s not overcomplicate this” energy as SWE-agent. If you’re into hidden gems that get the job done, give Plandex a peek.
Why It’s a Big Deal
SWE-agent’s success on SWE-bench screams one thing: you don’t need to go overboard to get results. A simple prompt, a slick interface, and a model like GPT-4 can outshine flashier setups. For coders and tinkerers, it’s a nudge to think smart, not hard.
Wanna play around with SWE-agent or see how it stacks up? Hit up the GitHub repo or check the SWE-bench leaderboard. Fair warning: you might end up like me, staying up way too late nerding out over the future of coding.
Sources: SWE-agent GitHub, SWE-bench, Yang et al., 2024, Plandex GitHub