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HyperspaceDB Embeddings

HyperspaceDB Native Hyperbolic Embeddings

HyperspaceDB Embeddings

AI-generated

Summary

Configure the spatial metric for generating native hyperbolic embeddings using the selected HyperspaceDB metric.

Inputs

  • Metric / Geometry (required) — Selects the spatial metric used for embedding calculations; options are Lorentz (Hyperbolic), Poincaré (Hyperbolic), Cosine Similarity, or Euclidean (L2).

Output shape

a single embedding object representing the vectorized form based on the chosen metric

This operation outputs the embeddings as a workflow data output with the AiEmbedding type. It does not take input data via node inputs but rather provides embedding functionality using the configured metric parameter.

Examples

Example 1: Use the node to obtain embeddings for a text query or documents with the selected metric for downstream vector search or similarity tasks in the workflow.

Set the 'Metric / Geometry' parameter to the desired spatial metric (default is 'Lorentz (Hyperbolic)').

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