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A StreamLit-based web application to visualize GPU inventory and AI capabilities on the Livepeer network.

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Livepeer AI GPU and Capabilities Dashboard

A Streamlit-based web application to visualize GPU inventory and AI capabilities across orchestrators in the Livepeer AI network using the Gateway /capabilities endpoint.

Features

  • GPU Type Distribution: View the distribution of GPU types across orchestrators.
  • Orchestrator GPU Distribution: Analyze GPU availability per orchestrator.
  • Capabilities Distribution: Explore AI capabilities provided by the orchestrators.
  • Interactive Filters: Filter data by GPU models and AI models.
  • Data Table: View detailed GPU and orchestrator data in a tabular format.

How to Run

  1. Clone the repository:

    git clone https://github.com/rickstaa/ai-compute-visualizer
    cd ai-compute-visualizer
  2. Install dependencies:

    pip install -r requirements.txt
  3. Set the required environment variable:

    export CAPABILITIES_DATA_URL="<GATEWAY_CAPABILITIES_URL>"
  4. Run the application:

    streamlit run gpu_dashboard.py
  5. Open your web browser and navigate to http://localhost:8501 to view the dashboard.

Deployment

To deploy the application on Streamlit Community Cloud:

  1. Push the code to a GitHub repository.
  2. Link the repository to Streamlit Community Cloud.
  3. Set the environment variable CAPABILITIES_DATA_URL in the Streamlit Cloud settings to the appropriate gateway capabilities URL.

Limitations

  • Data represents a snapshot of orchestrators and capabilities at the time of parsing.
  • Only GPUs ready to take jobs are shown.
  • Data is collected from a single gateway and may not include all orchestrators and GPUs.
  • Realtime AI GPUs are excluded as they are still in beta and not discoverable on chain.

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A StreamLit-based web application to visualize GPU inventory and AI capabilities on the Livepeer network.

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