翻译

ChatGPT使用多种语言的源代码进行训练。这使模型能够进行翻译。以下是一些如何使用此功能的示例。

prompt = f"""
Translate the following English text to Spanish: \
```Hi, I would like to order a blender```
"""
response = get_completion(prompt)
print(response)

执行结果：

Hola, me gustaría ordenar una licuadora.

另外三个案例：

prompt = f"""
Tell me which language this is:
```Combien coûte le lampadaire?```
"""
response = get_completion(prompt)
print(response)

执行结果：

This is French.

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)

执行结果：

French pirate: ```Je veux commander un ballon de basket```
Spanish pirate: ```Quiero pedir una pelota de baloncesto```
English pirate: ```I want to order a basketball```

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)

执行结果：

Formal: ¿Le gustaría ordenar una almohada?
Informal: ¿Te gustaría ordenar una almohada?

通用翻译器

想象一下，您负责大型跨国电子商务公司。用户在其所有母语中都向您发送IT问题。您的员工来自世界各地，只会说他们的母语。您需要一个通用翻译器！

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")

执行结果

音调转换

写作可以根据预期受众的不同而有所不同。ChatGPT可以产生不同的音调。

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)

执行结果

格式转换

ChatGPT可以在不同格式之间进行转换。提示应该描述输入和输出格式。

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)

<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>

显示HTML：

from IPython.display import display, Markdown, Latex, HTML, JSON
display(HTML(response))

输出结果

拼写检查/语法检查

以下是一些常见语法和拼写问题的例子以及LLM的回应。

为了向LLM发出信号，表示您希望它校对您的文本，您指示模型“proofread”或“proofread and correct”。

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)

执行结果

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)

执行结果：

批改模式：

from redlines import Redlines

diff = Redlines(text,response)
display(Markdown(diff.output_markdown))

执行结果
补充：Redlines生成一个Markdown文本，显示两个字符串/文本之间的差异。这些更改用删除线和下划线表示，看起来类似于Microsoft Word的跟踪更改。这种显示变化的方法对律师来说更为熟悉，对长系列的角色来说更为紧凑。
pip install redlines

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))