– The OmnAIView Story –

Imagine having half a dozen sensors on your desk—an oscilloscope, two CAN probes, a weather station, maybe a Li-Io battery monitor. They all speak slightly different protocols, yet you want one window that pops open, shows every curve live, and lets you say, “Yep, that’s the spike I was hunting.”
That window is OmnAIView, and, yes, you can build it in pure Python.

At its heart, OmnAIView is a modular Angular + Electron front-end designed to receive, visualise, analyse and persist heterogeneous time-series data from multiple back-ends. Because it’s open source under the MIT licence, you can fork it, extend it, even re-skin it for your next hackathon. GitHub Key ideas:

• Backend-agnostic – talk to REST, WebSocket or custom adapters.
• Analysis-ready – hook in your own algorithms or use the built-ins with one click.
• Desktop & Web – run in the browser during development, ship as a desktop app via Electron for operators.

Join our github repository on : https://github.com/AI-Gruppe/OmnAIView 

OmnAIView is crafted by the AI Gruppe, a data-driven collective from Germany that publishes mostly everything in the open. Issues, docs and road-map discussions all live on GitHub, so contributions are welcome—whether that’s a new chart type, documentation polish or a crazy data source.

Angular isn’t everyone’s cup of coffee, and sometimes you just want a scope on a headless Pi. That’s when the beauty of the design idea sparks . 

If a server can answer two tiny endpoints…

1. 1. Get a list of devices in some format 
   2. Get timestamps and values in some format 

… and the Frontend has some DataSource interface that can 

1. 1. Read the list of devices somehow 
   2. Read the timestamps and values somehow 

You can build the frontend in any language, for all datasources. For the easy way we build you a minimal example in python.

# 1. grab the minimal demo

git clone https://github.com/AI-Gruppe/OmnAIView_python_FE_minimalExample

cd OmnAIView_python_FE_minimalExample

# 2. create & activate a virtual-env

python -m venv env

source env/bin/activate        # Windows: env\Scripts\activate 

# 3. install the only three runtime deps

pip install requests websockets matplotlib

# 4. run it

python main.py                                                                        

1. 1. A Dev-DataServer generating a sinus and rectangular wave 
   2. A real life example with the OmnAIScope→ an USB Oscilloscope as tiny as a finger 

# 1. Clone the server

git clone https://github.com/AI-Gruppe/OmnAIView-DevDataServer.git

cd OmnAIView-DevDataServer/example_python

# 2. Create & activate a virtual-env

python -m venv env

source env/bin/activate        # Windows: env\Scripts\activate

# 3. Install minimal deps

pip install aiohttp websockets

# 4. Fire it up

python main.py

# -> "Server running on port 8080 (HTTP & WebSocket)"

Back in the GUI choose DevDataServer, leave the defaults (JSON, 60 Hz), and watch the waveforms glide across the canvas.

1. Plug in your Scope via USB

2. Start the OmnAIScope DataServer :

– Download the executable for developer

– In your shell start the exe via :

 .\MiniOmni.exe -w 

In the Python GUI pick OmnAIScope DataServer, click connect and select your source.  Seconds later real life data flow over your screen . Here you can find the real life example : 

Integrate your DataSource directly into the code by adding your datasource implementing the DataSourceStrategy or clone the repo and build your own frontend. The repo is Open Source available ( as everything else ) and shows the steps needed build it yourself. 

 Further Resources for Developers

You want to go deeper into data-driven telemetry & visualisation with OmnAIView in Angular?
You’re in the right place!
Our developer blog is packed with tutorials and deep-dives that show you how to wire up modern measurement tech to any backend.

But that’s just the beginning:

• Main GitHub Repository:
  Clone the source, start the project and open pull requests—everything lives in the open.
• Dev Data Server:
  A minimal Python implementation that demonstrates the required REST / WebSocket interface.
• Issue Tracker & Roadmap:
  See what’s next, report bugs or vote for features.
• Developer Discussions:
  Join the conversation, ask questions and share best practices with the community.
• Project README:
  Quick-start commands, architecture overview and contribution guidelines—all in one place.

Ready to ship your own data source? Fork the repos, hack away and show us what you build—PRs are welcome!

Whether you’re an embedded hacker or a full-stack engineer—here you’ll find the right tools and docs to level up your telemetry game.
Our motto: If we can measure it, you can improve it!