---
title: "Chapter 06: Serve and Automate"
description: "Serve the tuned model over the OpenAI-compatible API and wrap the entire loop in a Makefile you'll use for the rest of the course."
type: lesson
order: 6
chapter: "02-the-pipeline"
---

# Chapter 06: Serve and Automate

## Serving

```bash
mlx_lm.server --model ./models/gemma-json-1b --port 8080
```

Now anything that speaks the OpenAI chat-completions API can hit `http://localhost:8080/v1/chat/completions`. This endpoint is what Part 3's harness talks to. Same protocol, one URL — which is also why the final scale-up in Part 5 is a one-line change.

## Deliverable: The Makefile

A `Makefile` or `justfile`:

```
make data     # regenerate JSONL from source
make train    # mlx_lm.lora
make overfit  # the 10-example check
make fuse     # merge
make serve    # mlx_lm.server
make eval     # generate on held-out prompts, print results
```

This is not busywork. Part 3 changes *only the JSONL content* and reruns everything. Part 5 runs this loop hundreds of times unattended. The Makefile is the pipeline.

## Exit Criteria

- `make data && make train && make serve` from clean, in under fifteen minutes
- The served model always returns valid JSON
- You have swapped the dataset at least twice **without touching any other file**

That last one is the real test. If swapping data requires edits elsewhere, the pipeline isn't done.

---

[← Chapter 05](/fine-tune-local-agent/02-the-pipeline/05-train-and-check/) · [Next: Part 3 →](/fine-tune-local-agent/03-trajectories/)