aiko_services

Aiko Services

Distributed system framework supporting AIoT, Machine Learning, Media streaming and Robotics

See Wiki for Glossary (concepts), Roadmap for v1.0, Work In Progress (WIP) and Reference pages

Features

• Supports multi-nodal Machine Learning streaming pipelines ... that span from edge (embedded) devices all the way through to the data centre systems and back again

• Consistent distributed system approach integrating best-of-breed technology choices

  • Supports the Actor Model
  • Provides HyperSpace (example), a unified distributed network graph for everything !
  • Supports Flow based programming via distributed pipeline graphs
  • Low-latency performance with fully asynchronous function / method calls via message passing

• Ease of visualization and diagnosis for systems with many interconnected components via the Aiko Dashboard

• Light-weight core design, i.e a micro-controller reference implementation, e.g ESP32 running microPython

• Flexible deployment choices when deciding which components should run in the same process (for performance) or across different processes and/or hosts (for flexibility)

• Aiming to make the difficult parts ... much easier !

Documention

• Aiko Services Concepts guide and Design overview

Uses the Open Knowledge Format ... and is immediately useable by your favorite A.I coding assistant 🤖

Installation

Installing from PyPI (Python Package Index)

Recommended when simply trying Aiko Services by using existing examples and tools. Installs the Aiko Services package from PyPI

pip install aiko_services

Installing from GitHub

Recommended when using Aiko Services as a framework for development

git clone https://github.com/geekscape/aiko_services.git
cd aiko_services
python3 -m venv venv      # Once only
source venv/bin/activate  # Each terminal session
pip install -U pip        # Install latest pip
pip install -e .          # Install Aiko Services for development

Installing for package maintainers

Recommended when making an Aiko Services release to PyPI After installing from GitHub (above), perform these additional commands

pip install -U hatch  # Install latest Hatch build and package manager
hatch shell           # Run shell using Hatch to manage dependencies
# hatch test          # Run local tests (to be completed)
hatch build           # Publish Aiko Services package to PyPI

Quick start

After installing from GitHub (above), choose whether to use a public MQTT server ... or to install and run your own MQTT server

It is easier to start by using a public remotely hosted MQTT server to tryout a few examples. For the longer term, it is better and more secure to install and run your own MQTT server.

Running your own mosquitto (MQTT) server

• Install the mosquitto (MQTT) server on Linux, Mac OS X or Windows

On Linux or Mac OS X: Start mosquitto, aiko_registrar and aiko_dashboard

./scripts/system_start.sh  # default AIKO_MQTT_HOST=localhost

Examples

• Aloha Honua examples (hello world)

To Do

See GitHub Issues

Presentations

• An open-source framework for creating awesome Machine Learning applications

  • Slide deck (Google slides)
  • Everything Open conference January 2025: Adelaide, Australia

• microPython distributed, embedded services (YouTube)

  • Slide deck (Google slides)
  • microPython meet-up November 2023: Melbourne, Australia

• Using Python to stream media using GStreamer for RTSP and WebRTC applications (YouTube)

  • Slide deck (Google slides)
  • PyCon AU conference August 2023: Adelaide, Australia

• Building an open framework combining AIoT, Media, Robotics & Machine Learning (YouTube)

  • Slide deck (Google slides)
  • Everything Open conference March 2023: Melbourne, Australia