OpenAI - Prompt Engineering (Transforming)

OpenAI 잘사용하는 방법

1. 프롬프트를 위한 지침
2. 반복 프롬프트
3. 요약하기
4. 추론하기
5. 텍스트 변환
6. 프롬프트 확장
7. 챗봇

텍스트 변환 (ipynb)

• Translation

    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 screen is flashing
    ] 
    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 Korean: ```{issue}```
    """
    response = get_completion(prompt)
    print(response, "\n")
  

    Original message (This is French.): La performance du système est plus lente que d'habitude.
    English: The system performance is slower than usual.
    Korean: 시스템 성능이 평소보다 느립니다. 
  
    Original message (This is Spanish.): Mi monitor tiene píxeles que no se iluminan.
    English: My monitor has pixels that don't light up.
    Korean: 내 모니터에는 불이 켜지지 않는 픽셀이 있습니다. 
  
    Original message (This is Italian.): Il mio mouse non funziona
    English: My mouse is not working.
    Korean: 내 마우스가 작동하지 않습니다. 
  
    Original message (This is Polish.): Mój klawisz Ctrl jest zepsuty
    English: My Ctrl key is broken.
    Korean: 제 Ctrl 키가 고장 났어요. 
  
    Original message (This is Chinese (Simplified).): 我的屏幕在闪烁
    English: My screen is flickering.
    Korean: 내 화면이 깜빡입니다. 
  

• Writing (changing tones)
  • formal vs informal
  • slang -> business
• Input / Output Formats

    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))
  

• Grammar & Spelling Check

    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))