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    Interface RunClusterAnalysisInput

    Input for the RunClusterAnalysis GraphQL mutation.

    Mirrors the server-side RunClusterAnalysisInput (MJServer RunClusterAnalysisResolver). All fields are optional; the server applies defaults for any that are omitted.

    interface RunClusterAnalysisInput {
        Algorithm?: string;
        ColorBy?: "cluster" | "entity";
        Dimensions?: number;
        DistanceMetric?: string;
        EntityDocumentID?: string;
        EntityDocumentIDs?: string[];
        EntityID?: string;
        EntityName?: string;
        Epsilon?: number;
        Filter?: string;
        K?: number;
        MaxRecords?: number;
        MinPoints?: number;
        NameClusters?: boolean;
        PersistName?: string;
    }
    Index

    Properties

    Algorithm? ColorBy? Dimensions? DistanceMetric? EntityDocumentID? EntityDocumentIDs? EntityID? EntityName? Epsilon? Filter? K? MaxRecords? MinPoints? NameClusters? PersistName?

    Properties

    Algorithm?: string

    Clustering algorithm: 'kmeans' or 'dbscan'.

    ColorBy?: "cluster" | "entity"

    Legend mode: color points by 'cluster' (default) or 'entity'.

    Dimensions?: number

    Number of dimensions for the projected layout (2 or 3). Defaults to 2.

    DistanceMetric?: string

    Distance metric: 'cosine', 'euclidean' or 'dotproduct'.

    EntityDocumentID?: string

    Specific Entity Document ID supplying the vectors. Blank => the server chooses.

    EntityDocumentIDs?: string[]

    Multi-entity clustering: one or more Entity Document IDs whose vectors are merged into one analysis. Takes precedence over EntityDocumentID when non-empty. The server hard-blocks documents that use different embedding models.

    EntityID?: string

    Entity ID — persisted to the top-level EntityID column when available.

    EntityName?: string

    Entity name whose records are being clustered.

    Epsilon?: number

    Epsilon neighbourhood radius for DBSCAN.

    Filter?: string

    Optional SQL-style filter applied by the vector source.

    K?: number

    Number of clusters for K-Means.

    MaxRecords?: number

    Maximum number of records to fetch for clustering.

    MinPoints?: number

    Minimum points to form a dense region in DBSCAN.

    NameClusters?: boolean

    When true, runs the optional LLM cluster-naming step server-side.

    PersistName?: string

    When supplied, the result is persisted as an MJ: Cluster Analysis row with this Name and the returned AnalysisID is populated.

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