Artificial intelligence functions
Artificial intelligence (AI) functions allow you to work with large language models (LLMs), Core ML models, or regression models.
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Adds two embedding vectors and returns the result as a normalized vector. |
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Returns a JSON object containing the result of the Core ML model evaluation. |
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Returns the similarity between two embedding vectors as a number between -1 (opposite) and 1 (similar). |
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Sends input data to an embedding model and returns a vector representation as container data. |
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Converts an embedding vector from text format to binary container data. |
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Converts an embedding vector from binary container data to text format. |
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Returns a list of the fields on a layout as JSON data. |
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Returns metadata in JSON format about a named model that's currently loaded. |
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Returns information about the specified RAG space or all RAG spaces, if no space ID is specified. |
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Returns table information in Data Definition Language (DDL) format for a list of table occurrences specified as a JSON array. |
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Returns the token count for the specified text. Use for guidance only; actual counts used by models may vary. |
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Normalizes an embedding vector. If specified, the dimension parameter reduces the number of vector dimensions to use before normalizing. |
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Returns the predicted value from a trained regression model for the specified text embedding vector. |
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Subtracts embedding vector v2 from v1 and returns the result as a normalized vector. |