Use Translation for Paraphrasing

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!
        """