📄 中文摘要
该项目开发了一种确定性的中间件，能够有效地将大型语言模型（LLM）的提示信息压缩 50% 到 80%。通过智能算法，该中间件在保持信息完整性的同时，显著减少了输入数据的大小。这一技术的应用前景广泛，尤其是在需要高效数据传输和存储的场景中。用户反馈表明，该中间件在实际应用中表现良好，能够提升系统的响应速度和处理效率。开发者们希望通过进一步优化算法，提升压缩率和兼容性，以满足更广泛的需求。
展示 HN：一种确定性的中间件，可将 LLM 提示压缩 50-80%
出处: Show HN: A deterministic middleware to compress LLM prompts by 50-80%
发布: 2026年3月21日
📄 English Summary
Show HN: A deterministic middleware to compress LLM prompts by 50-80%
A deterministic middleware has been developed that effectively compresses prompts for large language models (LLMs) by 50% to 80%. Utilizing intelligent algorithms, this middleware significantly reduces the size of input data while maintaining information integrity. The technology has broad applications, particularly in scenarios requiring efficient data transmission and storage. User feedback indicates that the middleware performs well in practical applications, enhancing system response speed and processing efficiency. Developers aim to further optimize the algorithms to improve compression rates and compatibility to meet wider demands.