Gpt 3 keywords extractor

Question

I'm getting accustomed to gpt and want to build a keywords extractor for book summaries. Can someone point me to the references that'd help for my use case ?

Answer 1

For extracting the keywords from the text you can use OpenAI GPT-3 model's Keyword extraction example

import os
import openai

openai.api_key = os.getenv("OPENAI_API_KEY")

response = openai.Completion.create(
  model="text-davinci-002",
  prompt="Extract keywords from this text:\n\nBlack-on-black ware is a 20th- and 21st-century pottery tradition developed by the Puebloan Native American ceramic artists in Northern New Mexico. Traditional reduction-fired blackware has been made for centuries by pueblo artists. Black-on-black ware of the past century is produced with a smooth surface, with the designs applied through selective burnishing or the application of refractory slip. Another style involves carving or incising designs and selectively polishing the raised areas. For generations several families from Kha'po Owingeh and P'ohwhóge Owingeh pueblos have been making black-on-black ware with the techniques passed down from matriarch potters. Artists from other pueblos have also produced black-on-black ware. Several contemporary artists have created works honoring the pottery of their ancestors.",
  temperature=0.3,
  max_tokens=60,
  top_p=1.0,
  frequency_penalty=0.8,
  presence_penalty=0.0
)

Some references:

• Extract Keywords
• Keyword Extraction with BERT
• Minimal keyword extraction with BERT
• Keyword Extraction: from TF-IDF to BERT