Getting Started with LangChain (8) - Customize the tools used in the agent

Table of contents

1. Description

Two, examples

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1. Description

There is an interesting part in the custom tool. The weight of which tool is used is realized by  工具中描述内容 , which is completely different from our previous programming that relies on numerical values ​​to control the weight.

For example, Calculator wrote in the description that if you ask questions about mathematics, use him as a tool. We can see in the above execution process that he chose the Calculator tool for calculation in the mathematics part of the prompt we requested.

Two, examples

import os

from langchain.agents import initialize_agent, Tool
from langchain.agents import AgentType
from langchain.tools import BaseTool
from langchain.llms import OpenAI
from langchain import LLMMathChain, SerpAPIWrapper

# openAI的Key
os.environ["OPENAI_API_KEY"] = '**************'
# 谷歌搜索的Key
os.environ["SERPAPI_API_KEY"] = '**************'

llm = OpenAI(temperature=0)

# 初始化搜索链和计算链
search = SerpAPIWrapper()

llm_math_chain = LLMMathChain(llm=llm, verbose=True)

# 创建一个功能列表，指明这个 agent 里面都有哪些可用工具，agent 执行过程可以看必知概念里的 Agent 那张图
tools = [
    Tool(
        name="Search",
        func=search.run,
        description="useful for when you need to answer questions about current events"
    ),
    Tool(
        name="Calculator",
        func=llm_math_chain.run,
        description="useful for when you need to answer questions about math"
    )
]

# 初始化 agent
agent = initialize_agent(tools, llm, agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION, verbose=True)

# 执行 agent
run = agent.run("杜兰特进入NBA多少年了，年份的三次方是多少？")
print("结果：", run)