使用翻译进行意译
大型语言模型对接收到的提示方式很敏感。当提示不正确时，尽管模型拥有响应提示的信息或能力，其表现也可能大幅下降。我们可以通过执行回译来帮助找到语义相似的提示——回译是指我们将提示翻译成另一种语言再翻译回来，以鼓励重新措辞的提示更具多样性。
提示意译1. 提供了一些方法来帮助我们改进提示的措辞。
我们可以使用 instructor 来实现这一点，如下所示。
import instructor
from openai import AsyncOpenAI
from pydantic import BaseModel
import random
client = instructor.from_openai(AsyncOpenAI())
class TranslatedPrompt(BaseModel):
translation: str
async def translate_prompt(prompt: str, from_language: str, to_language: str):
return await client.chat.completions.create(
model="gpt-4o",
messages=[
{
"role": "system",
"content": f"""
You are an expert translation assistant.
You are going to be given a prompt and
asked to translate it from {from_language}
to {to_language}. Paraphrase and use
synonyms where possible, especially for
the examples.
""",
},
{"role": "user", "content": f"Prompt: {prompt}"},
],
response_model=TranslatedPrompt,
)
async def generate_permutation(prompt: str, language: str) -> str:
tranlated_prompt = await translate_prompt(prompt, "english", language)
backtranslated_prompt = await translate_prompt(
tranlated_prompt.translation, language, "english"
)
return backtranslated_prompt.translation
async def generate_prompts(
prompt: str, languages: list[str], permutations: int
) -> list[str]:
coros = [
generate_permutation(prompt, random.choice(languages))
for _ in range(permutations)
]
return await asyncio.gather(*coros)
if __name__ == "__main__":
import asyncio
prompt = """
You are an expert system that excels at Sentiment
Analysis of User Reviews.
Here are a few examples to refer to:
1. That was a fantastic experience I had! I'm
definitely recommending this to all my friends
// Positive
2. I think it was a passable evening. I don't think
there was anything remarkable or off-putting for me.
// Negative
3. I'm horrified at the state of affairs in this new
restaurant // Negative
Sentence: This was a fantastic experience!
"""
languages = ["french", "spanish", "chinese"]
permutations = 2
generated_prompts = asyncio.run(generate_prompts(prompt, languages, permutations))
for prompt in generated_prompts:
print(prompt)
"""
You are an expert system specializing in user review sentiment analysis. Here are a few examples to guide you: 1. It was an exceptional experience! I will definitely recommend it to all my friends // Positive 2. I think it was a mediocre evening. There wasn't anything outstanding or particularly bad for me // Negative 3. I am horrified by the condition of things in this new restaurant // Negative Sentence: It was an amazing experience!
"""
"""
You are an expert system that excels in User Review Sentiment Analysis.
Here are some reference examples:
1. I had an amazing experience! I will definitely recommend it to all my friends.
// Positive
2. I think it was an average evening. I don’t believe there was anything remarkable or unpleasant about it for me.
// Negative
3. I am horrified by the situation at this new restaurant.
// Negative
Sentence: This was a fantastic experience!
"""
"""
You are an expert system skilled in conducting user
review sentiment analysis.
Here are some examples for reference:
1. That was an awesome experience! I'll definitely
recommend it to all my friends // Positive
2. I think it was an okay evening. I don't find
anything particularly outstanding or unpleasant.
// Neutral
3. I am very shocked by the condition of this new
restaurant // Negative
Sentence: This was a wonderful experience!
"""