Odin 发布面向 bug 定位的搜索引擎，在 SWE-bench Lite 上文件命中率 93%
Built a search engine for debugging which is not a wrapper [P]
作者发布名为 Odin 的 bug 定位搜索引擎，粘贴公开仓库地址并关联或描述 issue 后，它会下载、解析代码并按 bug 相关度对函数排序。在 SWE-bench Lite 的 300 条真实 issue 上，正确文件进入前 10 的比例为 93.0%，精确定位到函数的比例为 79.4%。
TLDR: I built a search engine that reads a bug report (or lets you define it) and points to the exact file (93%) and to the exact function (79.4%) you need to fix.
Hey everyone,
I recently made a new project while trying to get into RAG and automation.
Odin is more than a search engine, all you have to do is paste a public repo URL and link the issue or describe the bug yourself and it downloads, parses and ranks the functions based on the mentioned bug.
Why its different than any LLM:
It runs mostly in your browser: It uses Tree-sitter (via WebAssembly) and small local models (via WebGPU) so your code isn't just blindly shipped off to a giant cloud LLM.
It punches above its weight: Evaluated on 300 real issues from the SWE-bench Lite dataset, it puts the correct file in the top 10 results 93.0% of the time, and the exact function 79.4% of the time.
It’s incredibly efficient: It matches the accuracy of heavy Claude 4.5 agents using models under 1B parameters, cutting the cost per issue to a fraction of a cent.
There’s also a GitHub Action you can drop into your repo to automatically comment on new issues with the most likely functions to fix.
I would really appreciate it if you would give it a try (it would help me with the benchmarks as well)
feedback, questions, criticism are welcome
submitted by /u/Massive_Capital9611
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来源：r/MachineLearning · reddit.com