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Stop vibe-debugging.
Plug Claude into your app's actual errors.
AppSignal's MCP server hands Claude, Cursor, or Zed your real errors, traces, and the deploy that shipped them. AI writes the fix; you review the diff.
The lightweight PyTorch wrapper for high-performance AI research
Scale your models, not your boilerplate with PyTorch Lightning! PyTorch Lightning is the ultimate PyTorch research framework that allows you to focus on the research while it takes care of everything else. It's designed to decouple the science from the engineering in your PyTorch code, simplifying complex network coding and giving you maximum flexibility. PyTorch Lightning can be used for just about any type of research, and was built for the fast inference needed in AI research and production. ...
This project provide a framework for general coding style checker's process:
1, Support different adapter plugin for different programming language syntax
2, Support incremental scanning
3, Support customize criteria rules.
4, Generate report for scanning result.
A C/C++ adapter was also implemented based on clang library as example.