The code defines two functions, `set_open_params` and `get_completion`. `set_open_params` takes...

March 28, 2023 at 03:57 PM

def set_open_params( model="text-davinci-003", temperature=0.7, max_tokens=256, top_p=1, frequency_penalty=0, presence_penalty=0, ): """ set openai parameters""" openai_params = {} openai_params['model'] = model openai_params['temperature'] = temperature openai_params['max_tokens'] = max_tokens openai_params['top_p'] = top_p openai_params['frequency_penalty'] = frequency_penalty openai_params['presence_penalty'] = presence_penalty return openai_params def get_completion(params, prompt): """ GET completion from openai api""" response = openai.Completion.create( engine = params['model'], prompt = prompt, temperature = params['temperature'], max_tokens = params['max_tokens'], top_p = params['top_p'], frequency_penalty = params['frequency_penalty'], presence_penalty = params['presence_penalty'], ) return response

The code defines two functions, set_open_params and get_completion.

set_open_params takes in several parameters with default values for OpenAI's GPT-3 language model, and returns a dictionary containing these parameters with their specified values. These parameters include the model to use, the temperature of the model's output (which controls randomness), the maximum number of tokens to generate, and penalties for word frequency and presence.

get_completion takes in the dictionary of parameters returned by set_open_params as well as a prompt (a partial sentence or topic to continue) and uses the OpenAI API to generate text completion based on the input prompt using the specified model and parameters. The response is then returned.

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