This template includes a real-time data processing pipeline with the following services:
demo-data-source
: A car telemetry data source for demonstration purposes.starter-visualization
: A simple template that reads from a Kafka topic and sends data to a web page. This page can be customized via ChatGPT to create various visualizations.
%%{ init: { 'flowchart': { 'curve': 'monotoneX' } } }%%
graph LR;
demo-data-source[fa:fa-rocket demo-data-source ‍] --> f1-data{{ fa:fa-arrow-right-arrow-left f1-data ‍}}:::topic;
f1-data{{ fa:fa-arrow-right-arrow-left f1-data ‍}}:::topic --> starter-visualization[fa:fa-rocket starter-visualization ‍];
classDef default font-size:110%;
classDef topic font-size:80%;
classDef topic fill:#3E89B3;
classDef topic stroke:#3E89B3;
classDef topic color:white;
This application receives data from a Kafka topic and sends it to a WebSocket connection without any transformation. The same application serves an HTML webpage located at ./templates/index.html
, which reads from the WebSocket and creates a real-time visualization.
- Run the visualization application: Ensure your data source is running.
- View initial visualization: The time-series data will be displayed on the screen.
- Customize the visualization:
- Copy the content of
./templates/index.html
and paste it into ChatGPT, describing how you want your visualization to be customized. - Use the modified code provided by ChatGPT to replace the content in
./templates/index.html
. - Refresh the webpage to see the updated visualization.
- Copy the content of
- Iterate: Repeat this process until you achieve the desired visualization.
-
Initial visualization: This is the default visualization provided by the template.
-
ChatGPT conversation: View Conversation
-
Improved visualization: After a few iterations with ChatGPT, the visualization was enhanced. However, there's potential to achieve even more with additional creativity and imagination.