14-用于LLM令牌压缩的Fusion Pipeline阶段-可逆压缩、AST感知代码分析、智能内容路由。零LLM推理成本。麻省理工学院获得许可。

context-compression 开源项目推荐(396 个)
context-compression 话题在 GitHub 上没有填写简介,这里按 Star 数汇总最相关的热门仓库。
热门项目 前 20
按 Star 数排序展示前 20 个 · GitHub 共 396 个仓库压缩LLM上下文以节省代币并降低成本
在AI编码上,将你的Claude / OpenAI / Gemini账单砍70%到95%。本地代理,压缩上下文,保持提供者缓存热,并验证LLM输出(免费幻觉保护)。Cursor、Claude Code、Codex、Aider + 34 个额外和自定义服务商的直接访问 — 30 秒,代码不变
One zero-dependency MCP gateway CLI for every server and agent skill. Token optimization, tool discovery and context compression: 71,929 -> 581 tokens (-99.2%, measured), schemas stay out of context. One config for Claude Code, Codex, Cursor, every agent. 561KB, pure Python. | 零依赖 CLI:管所有 MCP 工具与技能,工具发现省 99.2% token。
The one place for the skills, keys and memory of every agent you use. Formerly OMNI.
一个统一的工具包,用于高效且有效的编码代理(Karpathy原则、Caveman、Ponytail、TEK、CodeCurve、Context-Mode)。最短设置时间不超过30秒。任何操作系统。
🦍 Memorilla: Latent Semantic Memory for LLMs
TOMC Memory: CPU context compression and task memory for Codex, Claude Code, Cursor, TRAE, WorkBuddy and other MCP clients.
Official Implementation for the ACL 2026 paper "SARA: Selective and Adaptive Retrieval-augmented Generation with Context Compression"
受CC启发的便携技能,用于内存、验证、多代理协调、上下文压缩和主动编码代理工作流程。
面向 AI Agent 的高并发、低延迟上下文治理与 Prompt Cache 守护网关 (Tree-sitter AST / Tool Delta / 50%~80% Token 削减)
Context compression for MCP. Same upstream call, exact results recoverable.
A drop-in proxy that compresses bloated code context in real-time, cutting LLM API costs by 50–80% without losing what the model actually needs to know.
The official repo for "LLoCo: Learning Long Contexts Offline"
Zed extension for Headroom — context compression for AI agents
Context compression plugin for Claude Code. Automatically trims large tool output—JSON, YAML, stack traces, and logs—before it enters the context window.
AST-Aware, Personalized-PageRank-Ranked, Token-Budgeted Codebase Compressor for LLMs
Pytorch implementation for "Compressed Context Memory For Online Language Model Interaction" (ICLR'24)
State aware knowledge compression, ingestion, and hybrid retrieval engine. Zero dependencies. Sub-100ms queries.
铃音的记忆写入协议 - an informatics protocol: fragmented, cue-based, symbolic, highly compressed information for AI agents; usable for memory writing and transmission, decodable approximately or via retrieval.
关于这个话题
- 清单取自 GitHub 话题页并按 Star 数排序,每次展示前 20 个项目;原始页面见 https://github.com/topics/context-compression。
- 该话题在 GitHub 上共有 396 个仓库, 本站收录的是其中最热门的 20 个,不是全量列表。
- Star / Fork 每日自动刷新一次,实时数据以 GitHub 为准。
- 当前 20 个项目累计 6412 Star,覆盖 4 种主要语言,数据更新于 2026-11-07。
- 中文介绍来自 GitHub 官方话题说明(github/explore)的机器翻译,可点「查看原文」对照;译文缺失时会先展示原文。