Typesense · Schema
EmbedConfig
Configuration for automatic embedding generation from source fields.
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Properties
| Name | Type | Description |
|---|---|---|
| from | array | Field names to generate embeddings from. Typesense concatenates these fields and generates an embedding vector. |
| model_config | object | Model configuration for embedding generation. |
JSON Schema
{
"$schema": "https://json-schema.org/draft/2020-12/schema",
"$id": "#/components/schemas/EmbedConfig",
"title": "EmbedConfig",
"type": "object",
"description": "Configuration for automatic embedding generation from source fields.",
"properties": {
"from": {
"type": "array",
"description": "Field names to generate embeddings from. Typesense concatenates these fields and generates an embedding vector.",
"items": {
"type": "string"
}
},
"model_config": {
"type": "object",
"description": "Model configuration for embedding generation.",
"properties": {
"model_name": {
"type": "string",
"description": "Name of the embedding model. Supports built-in models like ts/all-MiniLM-L12-v2 or external models via OpenAI, Google, and other providers."
},
"api_key": {
"type": "string",
"description": "API key for external embedding services such as OpenAI."
},
"url": {
"type": "string",
"description": "URL of an external embedding service endpoint."
},
"access_token": {
"type": "string",
"description": "Access token for embedding service authentication."
},
"client_id": {
"type": "string",
"description": "Client ID for OAuth-based embedding services."
},
"client_secret": {
"type": "string",
"description": "Client secret for OAuth-based embedding services."
},
"project_id": {
"type": "string",
"description": "Project ID for cloud-based embedding services."
}
}
}
}
}