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More repeatable embeddings

As you continue to work with embeddings, you'll find yourself making repeated calls to OpenAI's embedding model. To make these calls in a more repeatable and modular way, it would be better to define a custom function called create_embeddings() that would output embeddings for any number of text inputs. In this exercise, you'll do just that!

Questo esercizio fa parte del corso

Introduction to Embeddings with the OpenAI API

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Istruzioni dell'esercizio

  • Define a create_embeddings() function that sends an input, texts, to the embedding model, and returns a list containing the embeddings for each input text.
  • Embed short_description using create_embeddings(), and extract and print the embeddings in a single list.
  • Embed list_of_descriptions using create_embeddings() and print.

Esercizio pratico interattivo

Prova a risolvere questo esercizio completando il codice di esempio.

# Define a create_embeddings function
def create_embeddings(texts):
  response = client.____(
    model="text-embedding-3-small",
    input=____
  )
  response_dict = response.model_dump()
  
  return [data['____'] for data in ____['data']]

# Embed short_description and print
print(____)

# Embed list_of_descriptions and print
print(____)
Modifica ed esegui il codice