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/
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