Prompt-refiner – Lightweight optimization for LLM inputs and RAG
Hi HN, While building RAG agents, I noticed a lot of token budget was wasted on formatting overhead (HTML tags, JSON structure, whitespace). Existing solutions felt too heavy (often requiring torch/transformers), so I wrote this lightweight, zero-dependency library to solve it. It includes strategies for context packing, PII redaction, and tool output compression. Benchmarks show it can save ~15% of tokens with negligible latency overhead (<0.5ms). Happy to answer any questions!
Prompt-refiner – Lightweight optimization for LLM inputs and RAG launched on December 17, 2025 with 7 votes, #1,248 of 11,628 launches that month and more than 75% of that year's launches.
What it does
🚀 Lightweight Python library for building production LLM applications with smart context management and automatic token optimization. Save 10-20% on API costs while fitting RAG docs, chat history, and prompts into your token budget. - JacobHuang91/prompt-refiner
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