1. Hardware & Muse Bridge

Raspberry Pi 5 + SPI LCD
Ready. Hardware pipeline initialized.

2. Live Hardware Screen & Bus Simulation

240 x 240 px
MUSE_HW_PI5 // /dev/fb0
SPI Refresh Rate 58.4 FPS
Audio Latency 42 ms
Muse State STREAMING
Pi RAM Used 184 MB / 4 GB
# Generating daemon code...

Open Source Meta Muse Architecture for Hardware

Meta open-sourced the protocol and client runtime bindings for Muse, allowing engineers and makers to bridge custom sensors, microdisplays, and companion hardware directly to Muse AI capabilities.

  • Bi-directional Streaming: High-bandwidth audio and frame buffers stream over a single low-overhead WebSocket tunnel directly from Raspberry Pi hardware.
  • Direct Framebuffer Rendering: Draw animated emotional avatars, status indicators, and streaming token responses via Linux /dev/fb0, SPI ST7789, or ILI9488 drivers with minimal overhead.
  • Hardware Interrupts: Physical pushbuttons and rotary encoders trigger GPIO callbacks that seamlessly interrupt or steer Muse speech generation.

Hardware Deployment Instructions

Get your physical gadget running in under 5 minutes on Raspberry Pi OS:

  • sudo apt-get update && sudo apt-get install -y python3-pip python3-spidev python3-pygame libportaudio2
  • pip3 install meta-muse-sdk gpiozero pillow websockets
  • Export your Muse API token: export MUSE_API_KEY="your-key-here"
  • Download the compiled muse_gadget_daemon.py from this workbench and run: python3 muse_gadget_daemon.py
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