BigQuery AI.Classify
AI.CLASSIFY categorizes unstructured data into a predefined set of labels.
Syntax Reference
AI.CLASSIFY(
[ input => ] 'INPUT',
[ categories => ] 'CATEGORIES'
[, connection_id => 'CONNECTION_ID' ]
[, endpoint => 'ENDPOINT' ]
[, output_mode => 'OUTPUT_MODE' ]
)Input Arguments
| Argument | Requirement | Type | Description |
|---|---|---|---|
input |
Required | String | The text content to |
| : : : : classify. : | |||
categories |
Required | Array<String> | A list of target |
| : : : : categories/labels. : | |||
| : : : : Can be : | |||
: : : : ARRAY<STRING> or : |
|||
| : : : : `ARRAY<STRUCT<STRING, : | |||
| : : : : STRING>>` (label, : | |||
| : : : : description). : | |||
connection_id |
Optional | String | The connection ID to |
| : : : : use for the LLM. : | |||
endpoint |
Optional | String | The model name, e.g., |
: : : : 'gemini-2.5-flash'. : |
|||
output_mode |
Optional | String | 'single' (default) |
: : : : or 'multi'. : |
|||
| : : : : Determines the output : | |||
| : : : : type. : |
Output Schema
The output type depends on the output_mode argument:
| Output Mode | output_mode Value | Type | Description |
|---|---|---|---|
| Single Label | NULL (Default) |
STRING |
The single category |
| : : : : that best fits the : | |||
| : : : : input. : | |||
| **Single Label | 'single' |
ARRAY<STRING> |
An array containing |
| : (Explicit)** : : : exactly one : | |||
| : : : : category string. : | |||
| Multi Label | 'multi' |
ARRAY<STRING> |
An array containing |
| : : : : zero or more : | |||
| : : : : matching : | |||
| : : : : categories. : |
Examples
Classify text into categories
SELECT
content,
AI.CLASSIFY(
content,
categories => ['Spam', 'Not Spam', 'Urgent'],
connection_id => 'my-project.us.my-connection'
) as classification
FROM `dataset.emails`;Classify text into multiple topics
SELECT
title,
body,
AI.CLASSIFY(
body,
categories => ['tech', 'sport', 'business', 'politics', 'entertainment', 'other'],
output_mode => 'multi') AS categories
FROM
`bigquery-public-data.bbc_news.fulltext`
LIMIT 100;Classify reviews by sentiment
SELECT AI.CLASSIFY( ('Classify the review by sentiment: ', review), categories
=> [('green', 'The review is positive.'), ('yellow', 'The review is neutral.'),
('red', 'The review is negative.')]) AS ai_review_rating, reviewer_rating AS
human_provided_rating, review, FROM bigquery-public-data.imdb.reviews WHERE
title = 'The English Patient'