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System Requirements

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Operating System

  • Linux (Ubuntu 20, 22, 24)
  • MacOS 12.0+

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Hardware

  • Sufficient memory to run vision and other models
  • Reliable WiFi or other networking
  • Sensors such as cameras, microphones, LIDAR units, IMUs
  • Actuators and outputs such as speakers, visual displays, and movement platforms (legs, arms, hands)
  • Hardware connected to the “central” computer via Zenoh, CycloneDDS, serial, usb, or custom APIs/libraries

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Software

Ensure you have the following installed on your machine:
  • Python >= 3.10
  • uv >= 0.6.2 as the Python package manager and virtual environment
  • portaudio for audio input and output
  • ffmpeg for video processing
  • Openmind API key

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UV (A Rust and Python package manager)

# Mac
brew install uv 

# Linux
curl -LsSf https://astral.sh/uv/install.sh | sh

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PortAudio Library

For audio functionality, install portaudio: 
# Mac
brew install portaudio

# Linux
sudo apt-get update
sudo apt-get install portaudio19-dev python-all-dev

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ffmpeg

For video functionality, install FFmpeg:
Mac
# Mac
brew install ffmpeg

# Linux
sudo apt-get update
sudo apt-get install ffmpeg

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Installation and Setup

  1. Clone the repository
Run the following commands to clone the repository and set up the environment:
clone repo
git clone https://github.com/openmind/OM1.git
cd OM1
git submodule update --init
uv venv
  1. Set the configuration variables
Locate the config folder and add your OpenMind API key to /config/spot.json (for example). If you do not already have one, you can obtain a free access key at https://portal.openmind.org/. 
# /config/spot.json
...
"api_key": "om1_live_..."
...
Note: Using the placeholder key openmind-free will generate errors. Or, create a .env file in the project directory and add the following: 
OM_API_KEY=om1_live_...
  1. Run the Spot Agent
Run the following command to start the Spot Agent: 
uv run src/run.py spot
On initial execution, this command will resolve and install project dependencies. Please allow a few minutes for this process to finish, before the system becomes active.

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WebSim to check input and output

Go to http://localhost:8000 to see real time logs along with the input and output in the terminal. For easy debugging, add --debug to see additional logging information.

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Understanding the Log Data

The log data provide insight into how the spot agent makes sense of its environment and decides on its next actions.
  • First, it detects a person using vision.
  • Communicates with an external AI API for response generation.
  • The LLM(s) decide on a set of actions (dancing and speaking).
  • The simulated robot expresses emotions via a front-facing display.
  • Logs latency and processing times to monitor system performance.
Object Detector INPUT
// START
You see a person in front of you. You also see a laptop.
// END

AVAILABLE ACTIONS:
command: move
    A movement to be performed by the agent.
    Effect: Allows the agent to move.
    Arguments: Allowed values: 'stand still', 'sit', 'dance', 'shake paw', 'walk', 'walk back', 'run', 'jump', 'wag tail'

command: speak
    Words to be spoken by the agent.
    Effect: Allows the agent to speak.
    Arguments: <class 'str'>

command: emotion
    A facial expression to be performed by the agent.
    Effect: Performs a given facial expression.
    Arguments: Allowed values: 'cry', 'smile', 'frown', 'think', 'joy'

What will you do? Command: 

INFO:httpx:HTTP Request: POST https://api.openmind.org/api/core/openai/chat/completions "HTTP/1.1 200 OK"
INFO:root:OpenAI LLM output: commands=[Command(type='move', value='wag tail'), Command(type='speak', value="Hi there! I see you and I'm excited!"), Command(type='emotion', value='joy')]

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More Examples

There are more pre-configured agents in the /config folder. They can be run with the following command: For example, to run the conversation agent: 
uv run src/run.py conversation
If you configure a custom agent, replace <agent_name> with your agent and run the below command: 
uv run src/run.py <agent_name>