123 lines
3.9 KiB
Python
123 lines
3.9 KiB
Python
import json
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import requests
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from dashscope import Generation
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from requests import RequestException
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from retry import retry
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from app.core.config import QWEN_API_KEY
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# os.environ["http_proxy"] = "http://127.0.0.1:7890"
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# os.environ["https_proxy"] = "http://127.0.0.1:7890"
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# llm = ChatOpenAI(model_name=OPENAI_MODEL,
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# openai_api_key=OPENAI_API_KEY,
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# temperature=0)
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prefix_for_llama = (
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"""
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Translate everything within the brackets [] into English.
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Never translate or modify any English input.
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The input must be fully translated into coherent English sentences.
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Please only output the translated result.\n
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"""
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)
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def translate_to_en(text):
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template = (
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"""You are a translation expert, proficient in various languages.
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And can translate various languages into English.
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Please translate to grammatically correct English regardless of the input language.
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If the input is already in English, or consists of letters or numbers such as "cat", "abc", or "1",
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output the input text exactly as it is without any modifications or additions.
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If there are grammatical errors, correct them and then output the sentence."""
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)
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prefix = (
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"""
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Translate everything within the brackets [] into English.
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Never translate or modify any English input.
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The input must be fully translated into coherent English sentences.
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Never present the translation results in the format
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"The translation of \"Material suave\" into English would be \"Smooth material.\"". Instead, directly output "Smooth material".
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"""
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)
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messages = [
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# {
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# Translate the entire text and ensure the output is a complete and coherent sentence in English.
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# "content": template, # 系统message
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# "role": "system"
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# },
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{
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# "content": input('请输入：'), # 用户message
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"content": prefix + text, # 用户message
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"role": "user"
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}
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]
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first_response = get_response(messages)
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assistant_output = first_response.output.choices[0].message
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print("input : {}, translate result : {}".format(text, assistant_output.content))
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return assistant_output.content
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# llama3专用
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# data = get_translation_from_llama3(text)
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# translation = data
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# # print("Response from llama3 : " + translation)
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# return translation
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@retry(exceptions=RequestException, tries=3, delay=1)
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def get_response(messages):
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response = Generation.call(
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model='qwen-turbo',
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api_key= QWEN_API_KEY,
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messages=messages,
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# 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
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result_format='message', # 将输出设置为message形式
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enable_search='True'
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)
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return response
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def get_translation_from_llama3(text):
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url = "http://localhost:11434/api/generate"
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# url = "http://10.1.1.240:1143/api/generate"
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prompt = f"System: {prefix_for_llama}\nUser:[{text}]"
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# 创建请求的负载
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payload = {
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"model": "llama3.2",
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"prompt": prompt,
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"stream": False
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}
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# 将负载转换为 JSON 格式
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headers = {'Content-Type': 'application/json'}
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response = requests.post(url, data=json.dumps(payload), headers=headers)
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# 处理响应
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if response.status_code == 200:
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# print("Response from server:")
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# print(response.json())
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resp = json.loads(response.content).get("response")
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print("input : {}, translate result : {}".format(text, resp))
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return resp
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else:
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print(f"Request failed with status code {response.status_code}")
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print(response.text)
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def main():
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"""Main function"""
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text = translate_to_en("fire")
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print(text)
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if __name__ == "__main__":
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main()
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