Product Selector

Fusion 5.11
    Fusion 5.11

    Use a deep learning model to encode and clusterize queries into fixed dense vector space

    skip - boolean

    Set to true to skip this stage.

    Default: false

    label - string

    A unique label for this stage.

    <= 255 characters

    condition - string

    Define a conditional script that must result in true or false. This can be used to determine if the stage should process or not.

    modelId - stringrequired

    The ID of the DL encoder model bundled to the MLeap format and stored in the Fusion blob store.

    >= 1 characters

    queryFeatureField - stringrequired

    Name of the query field to feed into the encoder.

    >= 1 characters

    Default: q

    vectorContextKey - stringrequired

    Context key used to store query encoded vector.

    >= 1 characters

    Default: query_vector

    clustersContextKey - stringrequired

    Context key used to store query clusters.

    >= 1 characters

    Default: query_clusters

    distancesContextKey - stringrequired

    Context key used to store distances to the clusters.

    >= 1 characters

    Default: query_distances

    numClusters - integerrequired

    Number of query clusters to be used for additional Filter Query. Can be overwritten by `num_clusters` query parameter. Should be less or equal to the amount of clusters from the encoder model. Set to 0 to disable clusters.

    Default: 0

    documentsClustersField - stringrequired

    Document clusters Solr field name. Filter Query with query cluster(s) are constructed against this field.

    >= 1 characters

    Default: document_clusters_ss

    failOnError - boolean

    Flag to indicate if this stage should throw an exception if an error occurs.

    Default: false

    storeInContext - booleanrequired

    Flag to indicate that the encoded query vector and clusters should be stored in the context for later use by downstream query pipeline stages

    Default: true