The problem: We've all been there, you find an interesting AI model or project on GitHub, try to run it, and spend hours wrestling with Python versions, CUDA toolkit mismatches, missing dependencies, and vague README instructions. Most people give up before seeing the code actually work.
How it works:
- You give it a GitHub repo URL
- It analyzes the entire codebase using gitingest compression - Spins up the right environment (local or cloud GPU if needed)
- An AI agent debugs setup issues in real-time, retrying failed commands with fixes
- Handles API key collection, system compatibility checks, and sudo permissions
- You end up with a working environment where you can actually run the code
What makes it different: Unlike general coding assistants (Cursor, etc.) that are built for writing code, this is laser-focused on the specific task of repository setup. It never stops until everything works, it's like having a persistent developer who won't give up on getting your environment running.
Current status: CLI tool working, tested on various ML repositories. Working on improving the success rate and adding web interface.
rs545837•5mo ago