How to overcome Rate limit error while working with GPT3 Models using Tenacity

In my situation I am trying to pass a prompt using a helper function to the actual GPT3 models, in my case text-ada-001 and then eventually applying it on a pandas column using the following code. but I am recovering the following error:

    def sentiment_prompt(text):
    return """Is the sentiment Positive, Negative or Neutral for the following text:
    
    "{}"
    """.format(text)
    def sentiment_text(text):
        response = openai.Completion.create(
           engine="text-ada-001",
           prompt=sentiment_prompt(text),
           max_tokens=1000,
           temperature=0,
           top_p=1,
           frequency_penalty=0,
           presence_penalty=0
    )
    sentiment = response.choices[0].text
    return sentiment

and then eventually applying to my pandas column:

    df['sentiment'] = df['text'].apply(lambda x :sentiment_text(x))

And the error;

    RateLimitError: Rate limit reached for default-global-with-image-limits in organization org-XXXX on requests per min. Limit: 60 / min. Please try again in 1s. Contact support@openai.com if you continue to have issues. Please add a payment method to your account to increase your rate limit. Visit https://platform.openai.com/account/billing to add a payment method.

To overcome this error I was looking into this link and found that tenacity could help resolve my issue. But I am not sure how to structure my code. I am doing the following at the moment

How do I use the code suggested in the link to overcome the Rate Limit error?

Import tenacity at the beginning of your code and then add its decoration where you are calling the OpenAI library with create. So your code would look like this:

from tenacity import (
    retry,
    stop_after_attempt,
    wait_random_exponential,
) 

@retry(wait=wait_random_exponential(min=1, max=60), stop=stop_after_attempt(6))
def sentiment_text(text):
        your_prompt = """Is the sentiment Positive, Negative or Neutral for the 
                         following text:
    
                         "{}"
                      """.format(text)
        response = openai.Completion.create(
           engine="text-ada-001",
           prompt=your_prompt ,
           max_tokens=1000,
           temperature=0,
           top_p=1,
           frequency_penalty=0,
           presence_penalty=0
        )
        sentiment = response.choices[0].text
        return sentiment