> ## Documentation Index
> Fetch the complete documentation index at: https://arkor-92aeef0e-eng-615.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Mental model

> The mental model behind Arkor: project layout, trainer, lifecycle callbacks, and Studio.

This section gives you the mental model you need before diving into the [SDK reference](/sdk/overview) or [CLI reference](/cli/overview). Read these in order; each builds on the previous.

## What to read

* [**Project structure**](/concepts/project-structure). Where Arkor expects code to live (`src/arkor/index.ts`, `src/arkor/trainer.ts`), what `.arkor/` and `~/.arkor/` are for, and what `arkor.config.ts` does (and does not) do today.
* [**Trainer**](/concepts/trainer). The shape of `createTrainer`: required fields, dataset sources, LoRA settings, and the `Trainer.start / wait / cancel` lifecycle.
* [**Lifecycle callbacks**](/concepts/lifecycle). The five callbacks (`onStarted`, `onLog`, `onCheckpoint`, `onCompleted`, `onFailed`), their argument shapes, and when each fires. This is where most of the value of doing fine-tuning in TypeScript lives.
* [**Studio**](/concepts/studio). What the local web UI is for, why it runs on loopback, and how it fits into the dev loop.

## The one-paragraph version

You define a `Trainer` with `createTrainer({ name, model, dataset, ... })` in `src/arkor/trainer.ts` and register it through `createArkor({ trainer })` in `src/arkor/index.ts`. `arkor dev` opens a local Studio in the browser; clicking **Run training** in Studio spawns `arkor start`, which calls `trainer.start()` and `trainer.wait()`. While `wait()` is open, callbacks dispatch from the SSE event stream, training streams from Arkor's managed GPUs, and the same view is reflected back into Studio.