#Prompt-compression
Showing 9 of 9 repositories tagged #prompt-compression, ranked by stars
14-stage Fusion Pipeline for LLM token compression — reversible compression, AST-aware code analysis, intelligent content routing. Zero LLM inference cost. MIT licensed.
Unlock 2x more Claude Code and Codex usage
Drop-in prompt compression for production LLM apps. Cut your token bill 40-60% without changing your code. Python SDK, LLMLingua-2, MIT.
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).
HEWN 2.0 2026: AI Output Router for Precision Summaries & Polished Code
JavaScript/TypeScript implementation of LLMLingua-2 (Experimental)
A self-improving knowledge base about LLM agent infrastructure
A curated list of strategies, tools, papers, and resources for reducing LLM token costs and improving efficiency in production.
Reverse T9 for LLMs. Free, open-source prompt compressor for your AI prompts and agents.