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[ARTICLE · art-28721] src=discuss.huggingface.co ↗ pub= topic=large-language-models verified=true sentiment=↑ positive

Open Source: llmslim – Semantic Prompt Compression for LLM Applications

Developer released llmslim, an open-source Python package that compresses prompts, chat histories, and RAG contexts using semantic chunking and extractive ranking, achieving up to 60% token reduction. The tool aims to reduce costs and latency for LLM applications.

read1 min views1 publishedJun 15, 2026

Published my first open-source Python package: llmslim.

It compresses prompts, chat histories, and RAG contexts using semantic chunking + extractive ranking before sending them to an LLM.

Example:

2847 tokens → 1138 tokens (60% reduction)

Looking for feedback from the HF community on:

Contributions and criticism welcome.

source & further reading
discuss.huggingface.co — original article Rakarrack-0.6.1 port making progress! ( AI assisted ) Cloud Storage Poll Welcome to Haiku basic(Haiku Docs, Haiku slide and Haiku sheets)
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