Dev Tools · 4h ago
LLMSlim cuts LLM prompt tokens by 60% without losing info
A developer built LLMSlim, a Python library that compresses RAG context prompts by up to 60% using extractive methods. The tool reduces token costs and improves LLM performance by removing filler while preserving critical information. It uses TF-IDF and LexRank to score sentence importance and runs entirely offline.
Meridian48 take
The library addresses a real pain point, but its reliance on extractive compression may struggle with nuanced or highly technical content where every sentence matters.
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Why Your LLM Pipeline Is Burning 60% of Its Token Budget on Noise (and How to Fix It) →
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llm-prompt-compressionrag-optimization