{
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "$id": "#/components/schemas/EmbedRequest",
  "title": "EmbedRequest",
  "type": "object",
  "required": [
    "model",
    "input_type"
  ],
  "properties": {
    "model": {
      "type": "string",
      "description": "The name of the embedding model to use.",
      "example": "embed-english-v3.0"
    },
    "texts": {
      "type": "array",
      "description": "An array of strings for the model to embed. Maximum number of texts per call depends on the model.",
      "items": {
        "type": "string"
      }
    },
    "images": {
      "type": "array",
      "description": "An array of image data for the model to embed. Used with models that support image embedding.",
      "items": {
        "type": "string"
      }
    },
    "input_type": {
      "type": "string",
      "enum": [
        "search_document",
        "search_query",
        "classification",
        "clustering",
        "image"
      ],
      "description": "Specifies the type of input passed to the model. Required for embedding models v3 and higher. Use search_document for embeddings stored in a vector database, search_query for search queries, classification for text classifiers, clustering for clustering tasks, and image for image inputs."
    },
    "embedding_types": {
      "type": "array",
      "description": "Specifies the types of embeddings to return. Can include one or more of float, int8, uint8, binary, and base64.",
      "items": {
        "type": "string",
        "enum": [
          "float",
          "int8",
          "uint8",
          "binary",
          "base64"
        ]
      }
    },
    "truncate": {
      "type": "string",
      "enum": [
        "NONE",
        "START",
        "END"
      ],
      "description": "Specifies how the API handles inputs longer than the maximum token length. START discards the beginning, END discards the end. NONE returns an error if the input is too long."
    }
  }
}