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# DataForge Studio
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<img width="2172" height="724" alt="dataforge" src="https://github.com/user-attachments/assets/52b25641-16ed-4a2f-b799-c7ff6905eb24" />
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# ⚒️ Dataforge Studio v2
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A workbench for building LLM fine-tuning datasets. Import data from anywhere, edit it in a proper grid, check its quality, generate synthetic examples, and export ready-to-train packages for the frameworks people actually use in 2026.
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Everything runs in your browser. There is no server, no account, no upload. Your training data never leaves your machine.
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**Live app:** https://natekali.github.io/dataforge/
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![DataForge Studio workbench](docs/screenshot-workbench.png)
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## What it does
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pnpm build # production build to dist/
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```
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## Deploy your own
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The repo ships with a GitHub Actions workflow that deploys to GitHub Pages on every push to `main`.
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1. Fork or push this repo to GitHub
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2. Repo Settings, then Pages, set Source to "GitHub Actions"
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3. Push to `main`
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That's it. The app appears at `https://<you>.github.io/dataforge/`. If your repo has a different name, set `DATAFORGE_BASE=/your-repo-name/` in the build step or edit `vite.config.ts`.
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## Privacy
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This is a static site. Datasets live in IndexedDB, in your browser, on your disk. API keys are stored locally and only ever sent to the provider you configured. There is no telemetry, no analytics, no third-party scripts.

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