Typesense · Schema

Field

Full-Text SearchOpen SourceSearch EngineTypo ToleranceVector Search

Properties

Name	Type	Description
name	string	Name of the field.
type	string	Data type of the field. Supported types include string, int32, int64, float, bool, string[], int32[], int64[], float[], bool[], auto, object, object[], geopoint, geopoint[], image.
optional	boolean	Whether this field is optional in documents.
facet	boolean	Whether this field can be used for faceting.
index	boolean	Whether this field should be indexed for search.
sort	boolean	Whether this field can be used for sorting.
infix	boolean	Whether infix search is enabled for this field.
locale	string	Locale for language-specific tokenization.
reference	string	Reference to a field in another collection for JOINs.
num_dim	integer	Number of dimensions for vector fields.
store	boolean	Whether to store the field value for retrieval.
range_index	boolean	Whether to build a range index for this field.
stem	boolean	Whether stemming is enabled for this field.
stem_dictionary	string	Name of the custom stemming dictionary to use.
drop	boolean	Whether to drop this field during a schema update.
vec_dist	string	Distance metric for vector fields.
embed	object	Embedding configuration for auto-generating vector embeddings.

View JSON Schema on GitHub

JSON Schema

{
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "$id": "#/components/schemas/Field",
  "title": "Field",
  "type": "object",
  "required": [
    "name",
    "type"
  ],
  "properties": {
    "name": {
      "type": "string",
      "description": "Name of the field."
    },
    "type": {
      "type": "string",
      "description": "Data type of the field. Supported types include string, int32, int64, float, bool, string[], int32[], int64[], float[], bool[], auto, object, object[], geopoint, geopoint[], image.",
      "enum": [
        "string",
        "int32",
        "int64",
        "float",
        "bool",
        "string[]",
        "int32[]",
        "int64[]",
        "float[]",
        "bool[]",
        "auto",
        "object",
        "object[]",
        "geopoint",
        "geopoint[]",
        "image"
      ]
    },
    "optional": {
      "type": "boolean",
      "description": "Whether this field is optional in documents."
    },
    "facet": {
      "type": "boolean",
      "description": "Whether this field can be used for faceting."
    },
    "index": {
      "type": "boolean",
      "description": "Whether this field should be indexed for search."
    },
    "sort": {
      "type": "boolean",
      "description": "Whether this field can be used for sorting."
    },
    "infix": {
      "type": "boolean",
      "description": "Whether infix search is enabled for this field."
    },
    "locale": {
      "type": "string",
      "description": "Locale for language-specific tokenization."
    },
    "reference": {
      "type": "string",
      "description": "Reference to a field in another collection for JOINs."
    },
    "num_dim": {
      "type": "integer",
      "description": "Number of dimensions for vector fields."
    },
    "store": {
      "type": "boolean",
      "description": "Whether to store the field value for retrieval."
    },
    "range_index": {
      "type": "boolean",
      "description": "Whether to build a range index for this field."
    },
    "stem": {
      "type": "boolean",
      "description": "Whether stemming is enabled for this field."
    },
    "stem_dictionary": {
      "type": "string",
      "description": "Name of the custom stemming dictionary to use."
    },
    "drop": {
      "type": "boolean",
      "description": "Whether to drop this field during a schema update."
    },
    "vec_dist": {
      "type": "string",
      "description": "Distance metric for vector fields.",
      "enum": [
        "cosine",
        "ip"
      ]
    },
    "embed": {
      "type": "object",
      "description": "Embedding configuration for auto-generating vector embeddings.",
      "properties": {
        "from": {
          "type": "array",
          "description": "Field names to generate embeddings from.",
          "items": {
            "type": "string"
          }
        },
        "model_config": {
          "type": "object",
          "description": "Model configuration for embedding generation.",
          "properties": {
            "model_name": {
              "type": "string",
              "description": "Name of the embedding model."
            },
            "api_key": {
              "type": "string",
              "description": "API key for external embedding services."
            },
            "url": {
              "type": "string",
              "description": "URL of the embedding service."
            }
          }
        }
      }
    }
  }
}