define a function that takes a list of problems as a text input and uses gpt-3 to return a marketing copy in python

To use GPT-3 for generating marketing copy, we can use OpenAI's GPT-3 API. Here's an example of how to define a Python function that takes a list of problem descriptions as input, and generates corresponding marketing copy using GPT-3:

main.py
import openai
openai.api_key = "INSERT YOUR API KEY HERE"

def generate_marketing_copy(problems):
    prompt = "Generate marketing copy for the following problems:\n\n"
    for problem in problems:
        prompt += f"- {problem}\n"
        
    # Set the GPT-3 parameters
    model_engine = "text-davinci-002"
    max_tokens = 256
    temperature = 0.5
    
    # Use the GPT-3 API to generate text
    response = openai.Completion.create(
        engine=model_engine,
        prompt=prompt,
        max_tokens=max_tokens,
        temperature=temperature,
    )
    
    # Extract the generated marketing copy from the API response
    marketing_copy = response.choices[0].text
    
    return marketing_copy
710 chars
26 lines

In this code, we first import the openai module and set our API key. Then we define a function generate_marketing_copy that takes a list of problem descriptions as its input.

Inside the function, we construct a prompt string which contains the problem descriptions as a bulleted list. We then set the GPT-3 parameters such as the model engine, max_tokens (the maximum number of tokens to generate), and temperature (a measure of how random the generated text is).

Finally, we use the openai.Completion.create method to generate the marketing copy using GPT-3. We extract the generated text from the API response and return it from the function.

Note that GPT-3 is an extremely powerful tool, but it can sometimes generate inappropriate or offensive text. It's important to use it responsibly and ensure that the generated text is appropriate for your intended audience.