14-stage Fusion Pipeline for LLM token compression — reversible compression, AST-aware code analysis, intelligent content routing. Zero LLM inference cost. MIT licensed.

Drop-in prompt compression for production LLM apps. Cut your token bill 40-60% without changing your code. Python SDK, LLMLingua-2, MIT.

Unlock 2x more Claude Code and Codex usage

Local proxy that compresses your LLM API requests so you pay less, with no change to the answers. Trims wasted tokens from prompts, history, tool output, and code before they're sent: -31% input / -74% output, measured live. Any provider, no extra model calls. Also an MCP server and embeddable library (Rust, Python, Ruby, Kotlin, Swift, JS/TS).

JavaScript/TypeScript implementation of LLMLingua-2 (Experimental)

A self-improving knowledge base about LLM agent infrastructure

Python command-line tool for interacting with AI models through the OpenRouter API/Cloudflare AI Gateway, or local self-hosted Ollama. Optionally support Microsoft LLMLingua prompt token compression

Lossless-first prompt compression for JSON, YAML, CSV, and Markdown. Library, CLI, MCP server, desktop app, and browser extension.

VL-JEPA inspired pipeline — compress images/text locally via Ollama, send compact payloads to any LLM API. Cut token costs by ~80%.

Rolling context compression for Claude Code — never hit the context wall. Auto-compresses old messages while keeping recent context verbatim. Zero config, zero latency. Works as a Claude Code plugin.

Reverse T9 for LLMs. Free, open-source prompt compressor for your AI prompts and agents.

A curated list of strategies, tools, papers, and resources for reducing LLM token costs and improving efficiency in production.

CUTIA: compress prompts while preserving quality

A Claude Code skill that shrinks massive prompts and files using LLMLingua to save tokens.

A curated list of techniques, tools, and research for reducing LLM token usage. Optimize context for Claude Code, Copilot, Cursor, and Aider.

This repository is the official implementation of Generative Context Distillation.

LLMLingua-2 prompt compression hook for Claude Code — cut token usage by ~55%

ComprExIT: context compression via explicit information transmission over frozen LLM hidden states (official implementation)

TOON for TYPO3 — a compact, human-readable, and token-efficient data format for AI prompts & LLM contexts. Perfect for ChatGPT, Gemini, Claude, Mistral, and OpenAI integrations (JSON ⇄ TOON).

Lossless-first semantic compression for LLM context windows. Shrink context 60-80% and prove nothing important was lost. Deterministic, extractive, stdlib-only, validated.