I just published SuperCompress to PyPI! 🎉

pip install supercompress — that's all it takes.

What is it?

A tiny ~5K parameter CPU policy that scores every line of context for relevance before sending to the LLM. It keeps only what matters for the answer.

The Numbers

• 65% fewer tokens → same answers
• 100% oracle recall → never drops the answer line
• ~60ms CPU latency → no GPU needed
• Open source → MIT with non-commercial clause

Quick Start

pip install supercompress

from supercompress import compress
result = compress(context, question)
print(f"Saved {result['kv_savings_pct']}% tokens")

Live Demo

Try the interactive comparison tool: https://supercompress.vercel.app/compare

Or read the technical deep-dive: https://dev.to/arjunkshah/how-i-built-a-prompt-compressor-that-saves-65-on-llm-costs-3m80

GitHub: https://github.com/arjunkshah/supercompress
PyPI: https://pypi.org/project/supercompress/