Mar 26 • 💬 General
Meet LocAgent-Open Sourec
Graph-Based AI Agents Transforming Code Localization for Scalable Software Maintenance.
Some Key Takeaways from the Research on LocAgent include the following:
- LocAgent transforms codebases into heterogeneous graphs for multi-level code reasoning.
- It achieved up to 92.7% file-level accuracy on SWE-Bench-Lite with Qwen2.5-32B.
- Reduced code localization cost by approximately 86% compared to proprietary models. Introduced Loc-Bench dataset with 660 examples: 282 bugs, 203 features, 31 security, 144 performance.
- Fine-tuned models (Qwen2.5-7B, Qwen2.5-32B) performed comparably to Claude-3.5.
- Tools like TraverseGraph and SearchEntity proved essential, with accuracy drops when disabled.
- Demonstrated real-world utility by improving GitHub issue resolution rates.
- It offers a scalable, cost-efficient, and effective alternative to proprietary LLM solutions.
cud you please create a demo on this and teach us.
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Meet LocAgent-Open Sourec
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