Muse Glimmer MLX playground

# Muse Glimmer Playground

A local Muse Glimmer 30B vision-and-reasoning chat app tuned for a 128 GB Apple M5 Max. Inference runs through ExecuTorch, MLX/Metal, and DFlash on this Mac; the server listens only on `127.0.0.1`, and conversations are not persisted to disk.

![Muse Glimmer Playground](docs/screenshot.png)

## Quick start

Requirements:

- An Apple silicon Mac. This preset is sized for a high-memory M5 Max; other Macs are not tested.
- Xcode, Node.js 20.19+ or 22.12+, npm, an internet connection, and at least 30 GB of free disk space.

Download and unzip the repository, then run this from the project folder:

```bash
./setup.sh
```

Setup prepares a project-local Python environment, builds the pinned ExecuTorch MLX worker, downloads the approximately 21 GB model and vision data, builds the browser app, and creates **Muse Glimmer.command** locally. Downloads and completed build work are reused later.

After setup, double-click **Muse Glimmer.command** in Finder and keep its Terminal window open. The launcher starts the server at [http://127.0.0.1:3939](http://127.0.0.1:3939) and opens the app in the default browser. Press Control-C in that Terminal window to stop the server and release the model.

To preserve setup errors or launch without Finder, run:

```bash
./Muse\ Glimmer.command
```

## Playground

- Live answer streaming with Muse Glimmer's thinking shown separately in an automatic collapsible disclosure
- Text and vision chat; attach one PNG or JPEG of up to 20 MB per conversation
- Edit or copy any prompt or response, regenerate responses, and stop active generation
- Markdown, tables, task lists, code, and links in responses
- A four-stop reasoning-effort slider for Low, Medium, High, or XHigh
- Temperature, Top P, Top K, and maximum-output-token controls
- Light, system, and dark themes with desktop and mobile layouts
- Time to first token, duration, throughput, thinking/output/input token usage, context usage, and runtime details

The recommended defaults are temperature `1.0`, Top P `0.95`, Top K `64`, High reasoning effort, and the full 131,072-token output ceiling. Prompt and output share that context window: before generation, the server subtracts the rendered prompt and gives the model the exact remaining room. The **Max** shortcut restores the full ceiling. Editing an earlier turn replaces that point in the conversation and remove