cohere · Schema

Cohere Embedding

Represents the embedding output from the Cohere Embed API, including vector representations in multiple numeric formats.

Properties

Name Type Description
id string Unique identifier for the embedding request.
embeddings object Container for embedding vectors organized by type. Each type maps to an array of embedding vectors.
texts array The text entries for which embeddings were returned.
images array The image entries for which embeddings were returned.
View JSON Schema on GitHub

JSON Schema

cohere-embedding-schema.json Raw ↑ 
{
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "$id": "https://api.cohere.com/schemas/cohere/embedding.json",
  "title": "Cohere Embedding",
  "description": "Represents the embedding output from the Cohere Embed API, including vector representations in multiple numeric formats.",
  "type": "object",
  "properties": {
    "id": {
      "type": "string",
      "description": "Unique identifier for the embedding request."
    },
    "embeddings": {
      "type": "object",
      "description": "Container for embedding vectors organized by type. Each type maps to an array of embedding vectors.",
      "properties": {
        "float": {
          "type": "array",
          "description": "Default float embeddings for each input. Supported with all Embed models.",
          "items": {
            "type": "array",
            "items": {
              "type": "number"
            }
          }
        },
        "int8": {
          "type": "array",
          "description": "Signed int8 embeddings for each input. Supported with Embed v3.0 and newer models.",
          "items": {
            "type": "array",
            "items": {
              "type": "integer",
              "minimum": -128,
              "maximum": 127
            }
          }
        },
        "uint8": {
          "type": "array",
          "description": "Unsigned int8 embeddings for each input. Supported with Embed v3.0 and newer models.",
          "items": {
            "type": "array",
            "items": {
              "type": "integer",
              "minimum": 0,
              "maximum": 255
            }
          }
        },
        "binary": {
          "type": "array",
          "description": "Signed binary embeddings for each input. Supported with Embed v3.0 and newer models.",
          "items": {
            "type": "array",
            "items": {
              "type": "integer"
            }
          }
        },
        "base64": {
          "type": "array",
          "description": "Base64-encoded embeddings for each input. Supported with Embed v3.0 and newer models.",
          "items": {
            "type": "string",
            "pattern": "^[A-Za-z0-9+/]+=*$"
          }
        }
      }
    },
    "texts": {
      "type": "array",
      "description": "The text entries for which embeddings were returned.",
      "items": {
        "type": "string"
      }
    },
    "images": {
      "type": "array",
      "description": "The image entries for which embeddings were returned.",
      "items": {
        "type": "string"
      }
    }
  },
  "$defs": {
    "EmbeddingInputType": {
      "type": "string",
      "description": "The type of input for embedding generation. Determines how the model processes the input.",
      "enum": [
        "search_document",
        "search_query",
        "classification",
        "clustering",
        "image"
      ]
    },
    "TruncateOption": {
      "type": "string",
      "description": "How to handle inputs longer than the maximum token length.",
      "enum": ["NONE", "START", "END"]
    }
  }
}