by jia-gao · LLM Plugin · ★ 312
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leanctx Drop-in prompt compression for production LLM applications. Cut your input-token bill by 40–60% — without changing your code. On the public LongBench v2 leaderboard's short subset, leanctx-Lingua doubles accuracy versus naive head+tail truncation (40 % vs 20 %) while removing 57 % of tokens. Open-source models, runs locally, MIT-licensed. Your prompts and user data never leave your infrastructure by default. Quickstart (60 seconds) First Lingua call loads 1.2 GB of model weigh
| Stars | 312 |
| Forks | 2 |
| Language | Python |
| Category | LLM Plugin |
| License | MIT |
| Quality Score | 64.4367355470561/100 |
| Open Issues | 1 |
| Last Updated | 2026-06-28 |
| Created | 2026-04-18 |
| Platforms | gemini, python |
| Est. Tokens | ~16k |
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leanctx is Drop-in prompt compression for production LLM apps. Cut your token bill 40-60% without changing your code. Python SDK, LLMLingua-2, MIT.. It is categorized as a LLM Plugin with 312 GitHub stars.
leanctx is primarily written in Python. It covers topics such as anthropic, cost-optimization, gemini.
You can find installation instructions and usage details in the leanctx GitHub repository at github.com/jia-gao/leanctx. The project has 312 stars and 2 forks, indicating an active community.
leanctx is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to leanctx on Agent Skills Hub include context-compressor, open-extract, flock. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.