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Model

Used to predict emotion based on feature text

URL : /api/model/predict

Method : POST

Auth required : NO

Data constraints

{
    "feature": "[random feature text in plain text]"
}

Data example

{
    "feature": "I am feeling pumped"
}

Success Response

Code : 200 OK

Content example

{
  "emotion": 2,
  "emotion-classes": "{0: 'anger', 1: 'fear', 2: 'happiness', 3: 'sadness'}",
  "prediction": "[0.05598123 0.00394219 0.6793236  0.26075292]",
  "salience": "0.6793236",
  "success": true
}

  • emotion refers to the predicted emotion based on the emotion class

  • emotion clases represents the indices of the emotion in the prediction array.

  • salience represent the probability of the predicted emotion.

  • Notes:

    • Since the emotify-model has a web dyno, and when the web dyno receives no traffic in a 30 minute period, the web dyno will sleep. As such the initial call after a while without trafic will take a while (~30s).