The ML_EMBED_ROW
routine uses the specified
embedding model to encode the specified text or query into a
vector embedding. The routine returns a
VECTOR
that contains a numerical
representation of the specified text.
mysql> select sys.ML_EMBED_ROW('Text', [options]);
options: {
JSON_OBJECT('key','value'[,'key','value'] ...)
'key','value': {
['model_id', {'all_minilm_l12_v2'|'multilingual-e5-small'|'cohere.embed-english-v3.0'|'cohere.embed-multilingual-v3.0'}]
['truncate', {true|false}]
}
}
Following are ML_EMBED_ROW
parameters:
Text
: specifies the text to encode.-
options
: specifies optional parameters as key-value pairs in JSON format. It can include the following parameters:-
model_id
: specifies the embedding model to use for encoding the text. Default value isall_minilm_l12_v2
. Possible values are:all_minilm_l12_v2
: for encoding English text.multilingual-e5-small
: for encoding text in supported languages other than English (en
). This embedding model is available in HeatWave9.0.1-u1
and later versions.cohere.embed-english-v3.0
: for encoding English text. This embedding model is available in HeatWave9.0.1-u1
and later versions.cohere.embed-multilingual-v3.0
: for encoding text in supported languages other than English. This embedding model is available in HeatWave9.0.1-u1
and later versions.
To view the lists of supported models, see HeatWave In-Database Embedding Models and OCI Generative AI Service Embedding Models. To view the list of supported languages, see Languages.
truncate
: specifies whether to truncate inputs longer than the maximum token size. Default value istrue
.
-