42 lines
1.6 KiB
Python
42 lines
1.6 KiB
Python
import os
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import qianfan
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from qianfan.resources.console.data import Data
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import pandas as pd
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import re
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# 使用安全认证AK/SK鉴权，通过环境变量方式初始化；替换下列示例中参数，安全认证Access Key替换your_iam_ak，Secret Key替换your_iam_sk
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os.environ["QIANFAN_ACCESS_KEY"] = "ALTAK8Mo2gY80BAW8RjEtHX3SS"
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os.environ["QIANFAN_SECRET_KEY"] = "95f6ac794fcb45b7805d5780bec589dc"
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chat_comp = qianfan.ChatCompletion()
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question = []
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with open("/home/zhangxj/WorkFile/LCA-GPT/QA/split/question/ques0.txt","r",encoding="utf-8") as file:
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for line in file.readlines():
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question.append(line.strip())
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answers = []
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with open("/home/zhangxj/WorkFile/LCA-GPT/QA/split/answer/ans0.txt","r",encoding="utf-8") as file:
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for line in file.readlines():
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answers.append(line.strip())
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answer_new = []
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for ques,ans in zip(question,answers):
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# 指定特定模型
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content = f"你是生命周期领域富有经验和知识的专家。我会为你提供一个问题和对应的答案，根据你所掌握的知识简要补充答案内容。不要列出几点来回答，不需要换行。问题是:“{ques}”。答案是:“{ans}”"
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resp = chat_comp.do(model="ERNIE-4.0-8K", messages=[
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{
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"role": "user",
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"content": content
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}])
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ans = resp["body"]["result"]
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line = re.sub(r'\s+', '', ans)
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print("问题：",ques)
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print(line)
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answer_new.append(line)
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with open("/home/zhangxj/WorkFile/LCA-GPT/QA/filters/answer_100.txt","w",encoding="utf-8") as file:
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for ans in answer_new:
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file.write(ans+"\n")
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