What it does
Humanize-Text is an open-source Python project from the Lynote team for rewriting AI-generated text into more natural prose. The runnable code is a legacy translation-chain pipeline: two LLM rewrite passes, then two machine-translation hops through different engines, passing through Chinese, Japanese and Finnish before returning to English. You run it from the command line after adding your own keys for an LLM provider such as DeepSeek or OpenRouter and for the Niutrans translation service, or you can import the included n8n workflow. The repository also includes five worked examples that save every intermediate step. The newer method in the repository is a data pipeline for building training data for the team's own rewrite model. The repo says no weights or endpoints are shipped, so that part is documentation and code rather than a usable model. For current results the team points to its hosted Lynote.ai service and a Humanizer API billed by input word. The project is open about its limits: round-trip translation can distort technical terms and citations, detector scores are probabilistic, and it should not be used to misrepresent authorship or get around institutional rules.
Capabilities
- Four-step chain of two LLM rewrites and two translation hops
- Configurable LLM provider such as DeepSeek or OpenRouter
- Command-line entry point and an importable n8n workflow
- Showcase examples with every intermediate step saved
- Structure-first training-data pipeline included as reference
When to use it
- You want to read and run an open pipeline for AI-text rewriting
- You are polishing AI-assisted drafts for readability and will check the output carefully
- You want to experiment with LLM and translation-based rewriting in Python or n8n
