Snowflake · Schema

EmbedRequest

Request to calculate text embeddings using a specified model.

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Properties

Name Type Description
model string Identifier of the model to use for generating embeddings. Refer to Snowflake documentation for the list of supported models. Examples: - `snowflake-arctic-embed-m` - `snowflake-arctic-embed-m-v1.5`
text array An array of input texts for which vector embeddings will be calculated. Example: ["Hello world", "Machine learning is fascinating"]
provisioned_throughput_id stringnull The provisioned throughput ID to be used with the request.
View JSON Schema on GitHub

JSON Schema

cortex-embed-embed-request-schema.json Raw ↑
{
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "title": "EmbedRequest",
  "type": "object",
  "description": "Request to calculate text embeddings using a specified model.",
  "properties": {
    "model": {
      "type": "string",
      "description": "Identifier of the model to use for generating embeddings.\nRefer to Snowflake documentation for the list of supported models.\n\nExamples:\n  - `snowflake-arctic-embed-m`\n  - `snowflake-arctic-embed-m-v1.5`\n"
    },
    "text": {
      "type": "array",
      "items": {
        "type": "string"
      },
      "description": "An array of input texts for which vector embeddings will be calculated.\nExample: [\"Hello world\", \"Machine learning is fascinating\"]",
      "minItems": 1
    },
    "provisioned_throughput_id": {
      "type": [
        "string",
        "null"
      ],
      "description": "The provisioned throughput ID to be used with the request."
    }
  },
  "required": [
    "model",
    "text"
  ]
}

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