ES|QL TEXT_EMBEDDING function
text- Text string to generate embeddings from. Must be a non-null literal string value.
inference_id- Identifier of an existing inference endpoint that will generate the embeddings. The inference endpoint must have the
text_embeddingtask type and should use the same model that was used to embed your indexed data. options-
(Optional) Options for the inference request.
Generates dense vector embeddings from text input using a specified inference endpoint. Use this function to generate query vectors for KNN searches against your vectorized data or others dense vector based operations.
| text | inference_id | options | result |
|---|---|---|---|
| keyword | keyword | named parameters | dense_vector |
timeout-
(keyword) Timeout for the inference request (e.g. "30s", "1m").
Generate text embeddings using the 'test_dense_inference' inference endpoint.
FROM dense_vector_text METADATA _score
| WHERE KNN(text_embedding_field, TEXT_EMBEDDING("be excellent to each other", "test_dense_inference"))