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LLM Prompt Engineering - inferring 用 LLM 跨語言任務 翻譯 文字風格 文法檢查

back-to:: LLM Prompt Engineering MOC

簡單的翻譯​

Translate the following English text to Spanish:

語言辨識​

Tell me which language this is:

LLM-Prompt-Engineering-inferring -20230502172145

多語言 to 多語言​

將混雜的語言文本，同時翻譯多個語言

user_messages = [
  "La performance du système est plus lente que d'habitude.",
  "Mi monitor tiene píxeles que no se iluminan.",
  "Il mio mouse non funziona",
  "Mój klawisz Ctrl jest zepsuty",
  "我的屏幕在闪烁"
]
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.

語氣轉換 （轉換成商業書信）​

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)
Dear Sir/Madam,

I am writing to bring to your attention a standing lamp that I believe may be of interest to you. Please find attached the specifications for your review.

Thank you for your time and consideration.

Sincerely,

Joe

LLM-Prompt-Engineering-inferring -20230502174025

JSON 轉 html table​

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))

output:

<table>
  <caption>Restaurant Employees</caption>
  <thead>
    <tr>
      <th>Name</th>
      <th>Email</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <td>Shyam</td>
      <td>shyamjaiswal@gmail.com</td>
    </tr>
    <tr>
      <td>Bob</td>
      <td>bob32@gmail.com</td>
    </tr>
    <tr>
      <td>Jai</td>
      <td>jai87@gmail.com</td>
    </tr>
  </tbody>
</table>

拼字文法檢查​

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:

翻譯成論文架構​

proofread and correct this review. Make it more compelling. Ensure it follows APA style guide and targets an advanced reader. Output in markdown format.