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from langchain_core . messages import HumanMessage
from langchain_core . prompts import ChatPromptTemplate , MessagesPlaceholder , \
FewShotChatMessagePromptTemplate
from langchain_openai import ChatOpenAI
from env_util import DASHSCOPE_API_KEY , DASHSCOPE_BASE_URL
# llm对象就是调用大模型的对象
llm = ChatOpenAI (
model = " qwen-plus " ,
base_url = DASHSCOPE_BASE_URL ,
api_key = DASHSCOPE_API_KEY ,
temperature = 0.8 ,
) ;
# 示例
examples = [
{ " input " : " 2 😫 3 " , " output " : " 6 " } ,
{ " input " : " 2 😫 4 " , " output " : " 8 " } ,
] ;
# 示例格式（给大模型学习的）
example_prompt = ChatPromptTemplate . from_messages (
[
( ' human ' , " {input} " ) ,
( ' ai ' , " {output} " )
]
) ;
# 组装ICL模板
icl_template = FewShotChatMessagePromptTemplate (
examples = examples ,
example_prompt = example_prompt ,
) ;
# 聊天模板，
prompt_template = ChatPromptTemplate . from_messages ( [
( " system " , " 你是一个智能助手 " ) ,
icl_template ,
MessagesPlaceholder ( " ques " )
] ) ;
# 组装执行
chain = prompt_template | llm
resp = chain . invoke (
# 课程里说可以不加[]，但是测试得出，[]必须要有。。。。
{ " ques " : [ HumanMessage ( content = " 2 😫 67 " ) ] }
) ;
print ( resp )
