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import time
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import os
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from basereal import BaseReal
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from logger import logger
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def llm_response(message,nerfreal:BaseReal):
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start = time.perf_counter()
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from openai import OpenAI
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client = OpenAI(
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# 如果您没有配置环境变量，请在此处用您的API Key进行替换
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api_key=os.getenv("DASHSCOPE_API_KEY"),
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# 填写DashScope SDK的base_url
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base_url="https://dashscope.aliyuncs.com/compatible-mode/v1",
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)
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end = time.perf_counter()
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logger.info(f"llm Time init: {end-start}s")
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completion = client.chat.completions.create(
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model="qwen-plus",
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messages=[{'role': 'system', 'content': 'You are a helpful assistant.'},
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{'role': 'user', 'content': message}],
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stream=True,
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# 通过以下设置，在流式输出的最后一行展示token使用信息
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stream_options={"include_usage": True}
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)
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result=""
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first = True
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for chunk in completion:
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if len(chunk.choices)>0:
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#print(chunk.choices[0].delta.content)
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if first:
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end = time.perf_counter()
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logger.info(f"llm Time to first chunk: {end-start}s")
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first = False
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msg = chunk.choices[0].delta.content
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lastpos=0
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#msglist = re.split('[,.!;:，。！?]',msg)
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for i, char in enumerate(msg):
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if char in ",.!;:，。！？：；" :
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result = result+msg[lastpos:i+1]
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lastpos = i+1
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if len(result)>10:
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logger.info(result)
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nerfreal.put_msg_txt(result)
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result=""
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result = result+msg[lastpos:]
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end = time.perf_counter()
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logger.info(f"llm Time to last chunk: {end-start}s")
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nerfreal.put_msg_txt(result)
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