How to use GPT-3 in Python With the OpenAI API

Here’s a step-by-step tutorial on how to use the OpenAI API to generate text using GPT-3 and save the results to a pandas DataFrame:

  1. Import the required libraries: To get started, you’ll need to import the following libraries: “openai”, “pandas”, and “numpy”.
  2. Set up your OpenAI API key: You’ll need to create an account with OpenAI and obtain an API key to use their language models. Once you have your API key, you can store it in an environment variable or in a file on your local machine. In this tutorial, we’ll assume that you’ve stored your API key as an environment variable called “OPENAI_API_KEY”.
  3. Create an empty pandas DataFrame: Before generating any text, you’ll need to create an empty pandas DataFrame to store the results. You can create an empty DataFrame with two columns named “Text” and “Correction”
  4. Define the input prompt: In this tutorial, we’ll use the input prompt “Correct this to standard English:mum not school back” as an example. You can define your own input prompt as a string variable.
  5. Generate the text: To generate the corrected text, you’ll use the “openai.Completion.create()” method from the OpenAI API. This method takes several parameters, including the “engine” to use, the “prompt” to provide to the language model, and various parameters that control the behavior of the language model.
  6. Extract the generated text: Once the text has been generated, you can extract it from the response using the “text” attribute of the first choice in the response.
  7. Add the prompt and generated text to the DataFrame: Finally, you can add the input prompt and the generated text as a new row in the pandas DataFrame using the “append” method.
GPT-3 PYTHON

That’s it! You can repeat steps 5-7 with different input prompts to generate more text and add it to the DataFrame. You can also use the various parameters in step 5 to control the behavior of the language model and experiment with different settings.