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30 lines
1.2 KiB
Python
30 lines
1.2 KiB
Python
from functions.open_application_tool import OpenApplicationInput, OpenApplicationTool
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from langchain_core.output_parsers import StrOutputParser
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from langchain_core.prompts import ChatPromptTemplate
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from tools.search_engine_tool import SearchEngineTool
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from utils.llm_util import LLM_Util
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class TestLangChain:
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def test_chain(self):
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template = """根据用户输入，提取出搜索引擎的关键字，返回该关键字:
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{input}"""
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model = LLM_Util().llm()
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prompt = ChatPromptTemplate.from_template(template)
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chain = prompt | model | StrOutputParser() | SearchEngineTool()
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search_datas = chain.invoke({"input": "谁是李一舟"})
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info = "\n".join(f"{i + 1}. {data.title}" for i, data in enumerate(search_datas))
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choice = input(f"下面是百度搜索结果，请选择你觉得有用的信息以逗号分割，如1,3,4，直接回车代表all in：\n{info}")
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choice = list(map(int, choice.split(",")))
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def test_chain(self):
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a = OpenApplicationTool()
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# a.invoke(r"C:\Users\yuruo\Desktop\HBuilder X.lnk")
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b = OpenApplicationInput.model_fields
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for c in b.keys():
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print(c)
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print(b[c].title)
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