{
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "$id": "https://raw.githubusercontent.com/api-evangelist/snowflake/main/json-schema/snowflake-embed-request-schema.json",
  "title": "EmbedRequest",
  "description": "Request to calculate text embeddings using a specified model.",
  "x-generated": "2026-10-04",
  "x-method": "derived",
  "x-generator": "derive-json-schema.py",
  "x-source": "openapi/snowflake-cortex-embed-api-openapi.yml#/components/schemas/EmbedRequest",
  "type": "object",
  "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"
  ]
}