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AI Diagrams

AI diagram tattvas live under murali::frontend::collection::ai.

This family is for higher-level teaching visuals and model diagrams rather than generic geometric graphing.

Included tattvas​

  • AttentionMatrix - heatmap-style token-to-token attention grid
  • SignalFlow - animated pulse moving through one or more paths
  • NeuralNetworkDiagram - layered node-and-edge network diagram
  • TokenSequence - ordered token visualization
  • TransformerBlockDiagram - transformer-style block composition
  • DecisionBoundaryPlot - classifier-style 2D decision region plot
  • AgenticFlowChart - routed flow-chart style diagrams

Examples​

AttentionMatrix is useful when values matter cell-by-cell:

use murali::frontend::collection::ai::attention_matrix::AttentionMatrix;

scene.add_tattva(
    AttentionMatrix::new(
        vec![
            vec![1.0, 0.5, 0.1],
            vec![0.3, 0.9, 0.2],
            vec![0.1, 0.4, 0.8],
        ],
        Some(vec!["The".into(), "cat".into(), "sat".into()]),
    ),
    Vec3::ZERO,
);

SignalFlow is useful when motion along a route is the story:

use murali::frontend::collection::ai::signal_flow::SignalFlow;

scene.add_tattva(
    SignalFlow::new(vec![
        Vec3::new(-2.0, 0.0, 0.0),
        Vec3::new(0.0, 1.0, 0.0),
        Vec3::new(2.0, 0.0, 0.0),
    ]),
    Vec3::ZERO,
);

NeuralNetworkDiagram is useful when layer structure matters:

use murali::frontend::collection::ai::neural_network_diagram::NeuralNetworkDiagram;

scene.add_tattva(
    NeuralNetworkDiagram::new(vec![3, 5, 2])
        .with_labels(vec!["Input", "Hidden", "Output"]),
    Vec3::ZERO,
);

This section should eventually document each concrete AI tattva separately, because the authoring intent differs a lot between them. For now, this page serves as the family index so the docs match the shipped API surface.