python

🎧 Omi Python SDK

A pip-installable Python SDK for connecting to Omi wearable devices over Bluetooth, decoding Opus-encoded audio, and transcribing it in real time using Deepgram.

📦 Installation

Prerequisites

The Omi SDK requires the Opus audio codec library to be installed on your system:

macOS:

brew install opus

Ubuntu/Debian:

sudo apt-get install libopus0 libopus-dev

CentOS/RHEL/Fedora:

sudo yum install opus opus-devel  # CentOS/RHEL
sudo dnf install opus opus-devel  # Fedora

Option 1: Install from PyPI (when published)

pip install omi-sdk

Option 2: Install from source

git clone https://github.com/BasedHardware/omi.git
cd omi/sdks/python
pip install -e .

🚀 Quick Start

1. Set up your environment

# Get a free API key from https://deepgram.com
export DEEPGRAM_API_KEY=your_actual_deepgram_key

2. Find your Omi device

# Scan for nearby Bluetooth devices
omi-scan

Look for a device named "Omi" and copy its MAC address:

0. Omi [7F52EC55-50C9-D1B9-E8D7-19B83217C97D]

3. Use in your Python code

import asyncio
import os
from omi import listen_to_omi, OmiOpusDecoder, transcribe
from asyncio import Queue

# Configuration
OMI_MAC = "YOUR_OMI_MAC_ADDRESS_HERE"  # From omi-scan
OMI_CHAR_UUID = "19B10001-E8F2-537E-4F6C-D104768A1214"  # Standard Omi audio UUID
DEEPGRAM_API_KEY = os.getenv("DEEPGRAM_API_KEY")

async def main():
    audio_queue = Queue()
    decoder = OmiOpusDecoder()
    
    def handle_audio(sender, data):
        pcm_data = decoder.decode_packet(data)
        if pcm_data:
            audio_queue.put_nowait(pcm_data)
    
    def handle_transcript(transcript):
        # Custom transcript handling
        print(f"🎤 {transcript}")
        # Save to file, send to API, etc.
    
    # Start transcription and device connection
    await asyncio.gather(
        listen_to_omi(OMI_MAC, OMI_CHAR_UUID, handle_audio),
        transcribe(audio_queue, DEEPGRAM_API_KEY, on_transcript=handle_transcript)
    )

if __name__ == "__main__":
    asyncio.run(main())

4. Run the example

The included example demonstrates connecting to an Omi device and real-time transcription:

# 1. Set your Deepgram API key
export DEEPGRAM_API_KEY=your_actual_deepgram_key

# 2. Find your Omi device MAC address
omi-scan

# 3. Update examples/main.py with your device's MAC address
# Edit line 10: OMI_MAC = "YOUR_DEVICE_MAC_HERE"

# 4. Run the example
python examples/main.py

The example will:

• Connect to your Omi device via Bluetooth
• Decode incoming Opus audio packets to PCM
• Transcribe audio in real-time using Deepgram
• Print transcriptions to the console

📚 API Reference

Core Functions

• omi.print_devices() - Scan for Bluetooth devices
• omi.listen_to_omi(mac, uuid, handler) - Connect to Omi device
• omi.OmiOpusDecoder() - Decode Opus audio to PCM
• omi.transcribe(queue, api_key) - Real-time transcription

Command Line Tools

• omi-scan - Scan for nearby Bluetooth devices

🔧 Development

Local development setup

git clone https://github.com/BasedHardware/omi.git
cd omi/sdks/python

# Create virtual environment
python3 -m venv venv
source venv/bin/activate

# Install in editable mode
pip install -e .

# Install dev dependencies
pip install -e ".[dev]"

🧩 Troubleshooting

• Opus library error: Make sure Opus audio codec is installed (see Prerequisites section)
• Bluetooth permission errors on macOS: Go to System Preferences → Privacy & Security → Bluetooth and grant access to Terminal and Python
• Python version: Requires Python 3.10+
• Omi device: Make sure device is powered on and nearby
• WebSocket issues: SDK uses websockets>=11.0

📄 License

MIT License

🙌 Credits

Built by the Omi community using Omi hardware and Deepgram's transcription engine.