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  3. Introduction to Embeddings with the OpenAI API

Exercise

Embedding more detailed descriptions

One of the last predicted labels didn't seem representative of the review; this was probably down to the lack of information being captured when we're only embedding the class labels. This time, descriptions of each class will be embedded instead, so the model better "understands" that you're classifying restaurant reviews.

The following objects are available for you to use:

sentiments = [{'label': 'Positive',
               'description': 'A positive restaurant review'},
              {'label': 'Neutral',
               'description':'A neutral restaurant review'},
              {'label': 'Negative',
               'description': 'A negative restaurant review'}]

reviews = ["The food was delicious!",
           "The service was a bit slow but the food was good",
           "Never going back!"]

Instructions

100 XP
  • Copy your API key and provide it to the OpenAI client.
  • Extract a list containing the sentiment descriptions and embed them.