import openai import os from dotenv import load_dotenv, find_dotenv _ = load_dotenv(find_dotenv()) # read local .env file openai.api_key = os.getenv('OPENAI_API_KEY') def get_completion(prompt, model="gpt-3.5-turbo"): messages = [{"role": "user", "content": prompt}] response = openai.ChatCompletion.create( model=model, messages=messages, temperature=0, # this is the degree of randomness of the model's output ) return response.choices[0].message["content"] prompt = f""" Translate the following English text to Gujrati: \ ```Hi, I would like to order a blender``` """ response = get_completion(prompt) print(response) prompt = f""" Tell me which language this is: ```Combien coûte le lampadaire?``` """ response = get_completion(prompt) print(response) prompt = f""" Translate the following text to French and Spanish and English pirate: \ ```I want to order a basketball``` """ response = get_completion(prompt) print(response) prompt = f""" Translate the following text to Spanish in both the \ formal and informal forms: 'Would you like to order a pillow?' """ response = get_completion(prompt) print(response) print("=======================") user_messages = [ "La performance du système est plus lente que d'habitude.", # System performance is slower than normal "Mi monitor tiene píxeles que no se iluminan.", # My monitor has pixels that are not lighting "Il mio mouse non funziona", # My mouse is not working "Mój klawisz Ctrl jest zepsuty", # My keyboard has a broken control key "我的屏幕在闪烁", "My name is Vivek Dabhi" ] for issue in user_messages: prompt = f"Tell me what language this is: ```{issue}```" lang = get_completion(prompt) print(f"Original message ({lang}): {issue}") prompt = f""" Translate the following text to English \ and Gujrati: ```{issue}``` """ response = get_completion(prompt) print(response, "\n") print("=======================") prompt = f""" Translate the following from slang to a business letter: 'Dude, This is Joe, check out this spec on this standing lamp.' """ response = get_completion(prompt) print(response) data_json = { "resturant employees" :[ {"name":"Shyam", "email":"shyamjaiswal@gmail.com"}, {"name":"Bob", "email":"bob32@gmail.com"}, {"name":"Jai", "email":"jai87@gmail.com"} ]} prompt = f""" Translate the following python dictionary from JSON to an HTML \ table with column headers and title: {data_json} """ response = get_completion(prompt) print(response) from IPython.display import display, Markdown, Latex, HTML, JSON display(HTML(response)) text = [ "The girl with the black and white puppies have a ball.", # The girl has a ball. "Yolanda has her notebook.", # ok "Its going to be a long day. Does the car need it’s oil changed?", # Homonyms "Their goes my freedom. There going to bring they’re suitcases.", # Homonyms "Your going to need you’re notebook.", # Homonyms "That medicine effects my ability to sleep. Have you heard of the butterfly affect?", # Homonyms "This phrase is to cherck chatGPT for speling abilitty" # spelling ] for t in text: prompt = f"""Proofread and correct the following text and rewrite the corrected version. If you don't find and errors, just say "No errors found". Don't use any punctuation around the text: ```{t}```""" response = get_completion(prompt) print(response) text = f""" Got this for my daughter for her birthday cuz she keeps taking \ mine from my room. Yes, adults also like pandas too. She takes \ it everywhere with her, and it's super soft and cute. One of the \ ears is a bit lower than the other, and I don't think that was \ designed to be asymmetrical. It's a bit small for what I paid for it \ though. I think there might be other options that are bigger for \ the same price. It arrived a day earlier than expected, so I got \ to play with it myself before I gave it to my daughter. """ prompt = f"proofread and correct this review: ```{text}```" response = get_completion(prompt) print(response) from redlines import Redlines diff = Redlines(text,response) display(Markdown(diff.output_markdown)) prompt = f""" proofread and correct this review. Make it more compelling. Ensure it follows APA style guide and targets an advanced reader. Output in markdown format. Text: ```{text}``` """ response = get_completion(prompt) display(Markdown(response))