gpt.py

import openai
from dotenv import load_dotenv

# api_key = "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"

load_dotenv()  # Load secrets


api_key = "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"


class GPT_3:
    def __init__(self, api_key):
        openai.api_key = api_key

        self.completion = openai.Completion
        self.options = {
            'engine': 'text-davinci-002',
            'temperature': 0.25,
            'top_p': 1,
            'frequency_penalty': 0,
            'presence_penalty': 0,
            'max_tokens': 512
        }

    def __call__(self, prompt, options=None):
        return self.prediction(prompt, options)

    def prediction(self, prompt, options=None):
        if not options:
            options = self.options

        return self.completion.create(prompt=prompt, **options)['choices'][0]['text']

    def teach(self, text, words):
        prompt = f'explain the following topic to a UG student in a conventional way in about {words}.\n\n Topic: {text}'
        return self.prediction(prompt=prompt)

    def resources2(self, text):
        prompt = f'Tell me resources to learn about {text} in the form of a list '
        return self.prediction(prompt=prompt)

    def translate(self, text, l):
        prompt = f'Translate provided text into the {l} language !\n\n text: {text}'
        return self.prediction(prompt=prompt)

    format = '''["question": "Question 1","options": ["Option 1", "Option 2", "Option 3", "Option 4"], "correct_answer": "Option 1" ]"'''

    def QuizMe(self, text, num):
        prompt = f'please make an MCQ quiz  of {num} questions related to {text} with all correct answers in a different line "'
        return self.prediction(prompt=prompt)

    # def prediction2(self, prompt, options=None):
    #     if not options:
    #         options = self.options

    #     return self.completion.create(prompt=prompt, **options)['choices'][0]['json']
    # def script(self , text ):
    #     prompt = f'Provide script to create a short and crisp video to explain about : {text}'
    #     return self.prediction(prompt=prompt)

    # def resources(self, text , videoNo = 0 , bookNo = 0 , articleNo = 0 , podcastNo = 0 ):
    #     prompt = f'Tell me resources to learn about {text} in the form of a list of {videoNo} yt video , {bookNo} book , {articleNo} article , {podcastNo} podcast'

    #     return self.prediction(prompt=prompt)

    # def topics(self, text):
    #     prompt = f'Mention all the topics included in this piece of text !\n\n text: {text}'
    #     # time.sleep(1)
    #     return self.prediction(prompt=prompt)