Feed it your own writing. It learns your voice. Then it writes in that voice — consistently, at scale.
Most "AI writing" tools sound like everyone else's AI writing: flat, generic, instantly recognizable. YOOS-APP solves the opposite problem. You give it a folder of texts you have written; it builds a portable profile of how you write — your sentence rhythm, your punctuation habits, your vocabulary, your openings — and then generates new content that stays in your voice.
It's built for people who have something to publish but find writing slow or hard: solo founders, bloggers, small brands, newsletter authors, anyone who needs a steady stream of on-brand content without sounding like a robot.
Writing consistently is the bottleneck. Not everyone can sit down and produce clean, on-voice copy every week — but everyone has a backlog of things worth saying. Generic LLM output doesn't help: it's correct but voiceless, and readers feel it.
YOOS-APP turns your existing writing into a reusable voice asset. Analyze once, generate forever.
- No embeddings. No vector database. No cloud lock-in. Voice is captured as plain, inspectable statistics in a portable JSON file.
- Runs fully local with Ollama, or with any major API (OpenAI, Anthropic).
- Auditable output — every generation gets a 0–100 voice-match score so you know how close it landed.
Your corpus (.txt / .pdf / .html)
│
▼
┌─────────────┐ 25+ stylometric dimensions:
│ analyze │ sentence-length distribution, first-person rate,
│ │ punctuation fingerprint, vocabulary richness,
└──────┬──────┘ paragraph rhythm, signature phrases…
│ voice profile → portable JSON
▼
┌─────────────┐ Genre templates: blog, guide, magazine,
│ generate │ news, story, column, essay, marketing
│ + backend │ Backends: OpenAI · Anthropic · Ollama (local)
└──────┬──────┘
│ draft + voice-match score (0–100)
▼
┌─────────────┐
│ export │ → file · PDF · WordPress
└─────────────┘
git clone https://github.com/yoldaolmak/YOOS-APP.git
cd YOOS-APP
pip install -r requirements.txt
# See it work end-to-end, no setup:
python -m yoos_app demo# 1. Learn your voice from a folder of your texts
yoos-app analyze --corpus ./my-articles/ --author "Me" --out my-voice.json
# 2. Generate a new piece in that voice
yoos-app generate --profile my-voice.json --type magazine \
--topic "Three days in Lisbon" --backend openai
# 3. Or run the whole pipeline at once and publish
yoos-app run --corpus ./my-articles/ --type travel_blog \
--topic "Why I keep going back to Tokyo" --dest wordpressThat's the whole loop: analyze → generate → export.
| You are… | YOOS-APP gives you… |
|---|---|
| A solo founder / indie brand | On-voice blog & marketing copy without hiring a writer |
| A blogger or newsletter author | A way to keep publishing on the weeks you can't write |
| An agency | One reusable voice profile per client, consistent across drafts |
| A non-native or reluctant writer | Your ideas, in clean prose that still sounds like you |
The opportunity is consistency at scale: capture a voice once, then produce dozens of pieces that read like the same human wrote them.
The analyzer is pure, transparent text statistics — no black-box embeddings. It measures things like:
- Sentence-length distribution (mean, spread, short/long ratio)
- First-person, question, and exclamation rates
- Paragraph rhythm (sentences per paragraph)
- Punctuation style (em-dash, semicolon, parenthesis use)
- Vocabulary richness (type–token ratio)
- Signature 2-gram phrases and typical openings
The result is a small JSON file you can read, diff, version, and reuse anywhere.
| Backend | Use it when |
|---|---|
| Ollama (local) | You want zero API cost and full privacy |
| OpenAI | You want top-tier quality out of the box |
| Anthropic | You prefer Claude models |
Set your key in .env (see .env.example). No key needed for the local Ollama path or the demo.
YOOS-APP is the accessible, bring-your-own-voice entry point: give it your texts, get consistent content in your voice.
graphova is its more advanced sibling — a voice-print engine for writing in any author's tone. YOOS-APP is the simple front door; graphova is the deep end.
MIT — see LICENSE. Use it, fork it, build on it.