charturbo - v0.1.0
    Preparing search index...

    Interface HighDimEmbeddingOptions

    interface HighDimEmbeddingOptions {
        clusters?: Uint16Array<ArrayBufferLike>;
        dimensions: number;
        kNeighbors?: number;
        projection?: EmbeddingProjectionMode;
        similarityThreshold?: number;
        spaceRadius?: number;
        umapWarmupTicks?: number;
    }
    Index
    clusters?: Uint16Array<ArrayBufferLike>

    Optional pre-assigned cluster IDs (length = N). If omitted, Rust runs Spherical K-Means in D-dim space

    dimensions: number

    Embedding vector dimension D (supports any D >= 3, e.g., 64, 128, 384, 768, 1024, 1536, 3072, 4096+)

    kNeighbors?: number

    Number of top cosine-similar neighbors to connect as edges per vector (default: 5)

    Dimensionality reduction mode from R^D -> R^3 (default: 'pca-umap')

    similarityThreshold?: number

    Minimum cosine similarity in [-1, 1] required to create an edge (default: 0.35)

    spaceRadius?: number

    Target 3D bounding sphere radius (default: 85)

    umapWarmupTicks?: number

    Physics warmup ticks when projection is 'pca-umap' (default: 35)