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33 changes: 33 additions & 0 deletions docs/reference/query-languages/query-dsl/query-dsl-knn-query.md
Original file line number Diff line number Diff line change
Expand Up @@ -227,6 +227,39 @@ A sample query can look like below:
```


## Knn query on a semantic_text field [knn-query-with-semantic-text]

Elasticsearch supports knn queries over a [
`semantic_text` field](/reference/elasticsearch/mapping-reference/semantic-text.md).

Here is an example using the `query_vector_builder`:

```json
{
"query": {
"knn": {
"field": "inference_field",
"k": 10,
"num_candidates": 100,
"query_vector_builder": {
"text_embedding": {
"model_text": "test"
}
}
}
},
"_source": {
"exclude": "inference_field.inference.chunks"
}
}
```

Note that for `semantic_text` fields, the `model_id` does not have to be
provided as it can be inferred from the `semantic_text` field mapping.

Knn search using query vectors over `semantic_text` fields is also supported,
with no change to the API.

## Knn query with aggregations [knn-query-aggregations]

`knn` query calculates aggregations on top `k` documents from each shard. Thus, the final results from aggregations contain `k * number_of_shards` documents. This is different from the [top level knn section](docs-content://solutions/search/vector/knn.md) where aggregations are calculated on the global top `k` nearest documents.