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Gemini Tools

Gemini Embed Content

Generates text embeddings using Gemini embedding models. Converts text into numerical vectors for semantic search, similarity comparison, clustering, and classification tasks.

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Use Gemini Embed Content

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Aident LoadoutAident Playbook EditorOpen-CUAK

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Inputs

  • textstring
    Required
    The text content to generate embeddings for.
  • modelstring
    Embedding model to use. Options: 'text-embedding-004' (768 dimensions, default), 'gemini-embedding-001' (3072 dimensions, latest).
  • titlestring
    Optional title for the content. Use with task_type='RETRIEVAL_DOCUMENT' to improve embedding quality for document search.
  • task_typestring
    Specifies the intended use case to optimize the embedding. Options: 'RETRIEVAL_QUERY' (search queries), 'RETRIEVAL_DOCUMENT' (documents to be searched), 'SEMANTIC_SIMILARITY' (text similarity), 'CLASSIFICATION' (categorization), 'CLUSTERING' (grouping), 'QUESTION_ANSWERING' (que…
  • output_dimensionalityinteger
    Truncate the embedding to this number of dimensions. Only supported by 'gemini-embedding-001' model. Recommended values: 768, 1536, or 3072. Lower dimensions reduce storage but may affect quality.

Observable output

  • data
    Required
    Data from the action execution
  • errorstring
    Error if any occurred during the execution of the action
  • successfulboolean
    Required
    Whether or not the action execution was successful or not

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