AiDA_Python/app/service/prompt_generation/chatgpt_for_translation.py

import json


import requests
from dashscope import Generation
from requests import RequestException
from retry import retry

from app.core.config import QWEN_API_KEY


# os.environ["http_proxy"] = "http://127.0.0.1:7890"
# os.environ["https_proxy"] = "http://127.0.0.1:7890"


# llm = ChatOpenAI(model_name=OPENAI_MODEL,
#                  openai_api_key=OPENAI_API_KEY,
#                  temperature=0)

prefix_for_llama = (
        """
        Translate everything within the brackets [] into English.
        Never translate or modify any English input.
        The input must be fully translated into coherent English sentences.
        Please only output the translated result.\n
        """
    )


def translate_to_en(text):
    template = (
        """You are a translation expert, proficient in various languages.
        And can translate various languages into English.
        Please translate to grammatically correct English regardless of the input language.
        If the input is already in English, or consists of letters or numbers such as "cat", "abc", or "1", 
        output the input text exactly as it is without any modifications or additions.
        If there are grammatical errors, correct them and then output the sentence."""
    )

    prefix = (
        """
        Translate everything within the brackets [] into English.
        Never translate or modify any English input.
        The input must be fully translated into coherent English sentences.
        Never present the translation results in the format 
        "The translation of \"Material suave\" into English would be \"Smooth material.\"". Instead, directly output "Smooth material".
        """
    )
    messages = [
        # {
        # Translate the entire text and ensure the output is a complete and coherent sentence in English.
        #     "content": template,  # 系统message
        #     "role": "system"
        # },
        {
            # "content": input('请输入：'),  # 用户message
            "content": prefix + text,  # 用户message
            "role": "user"
        }
    ]
    first_response = get_response(messages)
    assistant_output = first_response.output.choices[0].message
    print("input : {}, translate result : {}".format(text, assistant_output.content))
    return assistant_output.content

    # llama3专用
    # data = get_translation_from_llama3(text)
    # translation = data
    # # print("Response from llama3 : " + translation)
    # return translation


@retry(exceptions=RequestException, tries=3, delay=1)
def get_response(messages):
    response = Generation.call(
        model='qwen-turbo',
        api_key= QWEN_API_KEY,
        messages=messages,
        # seed=random.randint(1, 10000),  # 设置随机数种子seed，如果没有设置，则随机数种子默认为1234
        result_format='message',  # 将输出设置为message形式
        enable_search='True'
    )
    return response


def get_translation_from_llama3(text):
    url = "http://localhost:11434/api/generate"
    # url = "http://10.1.1.240:1143/api/generate"

    prompt = f"System: {prefix_for_llama}\nUser:[{text}]"

    # 创建请求的负载
    payload = {
        "model": "llama3.2",
        "prompt": prompt,
        "stream": False
    }

    # 将负载转换为 JSON 格式
    headers = {'Content-Type': 'application/json'}
    response = requests.post(url, data=json.dumps(payload), headers=headers)

    # 处理响应
    if response.status_code == 200:
        # print("Response from server:")
        # print(response.json())
        resp = json.loads(response.content).get("response")
        print("input : {}, translate result : {}".format(text, resp))
        return resp
    else:
        print(f"Request failed with status code {response.status_code}")
        print(response.text)


def main():
    """Main function"""
    text = translate_to_en("fire")
    print(text)


if __name__ == "__main__":
    main()