Classifiers are used to label a text with a specific category. For example, you can use a classifier to label a text as positive or negative.

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Response signature

Each classifier model returns an object with the detected label and the respective scores. This object is added to the API response under the model’s key.
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label
string
required
The most probable label. This will always be the label with the highest score. Returns null if the analyzer fails.
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score
number
required
The score of the label. From 0-1 score with 1 meaning a high probability of being correct.
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label_scores
object
required
An object containing all the label scores.

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Pre-built text classifiers

Toxicity

Detects toxic content.

NSFW

Detects NSFW content.

Propriety

Detects inappropriate content.

Sentiment

Positive, negative, or neutral.

Spam

Detects spam.

Language

Detects the language.

Sexual

Detects sexual content.

Discrimination

Detects discriminating content.

Self harm

Detects content related to self harm.

Violence

Detects content related to violence.