langchain（6）：代理Agent

llm使用从互联网上学习的各类背景知识，同时利用你提供的新信息来帮助你回答问题、推理内容、决定下一步操作等

# 使用llm作为agent的推理引擎，其连接到其他数据和计算资源
# 所以将temperature设置为0，希望结果尽可能好和精确，消除随机性
llm = ChatOpenAI(temperature=0, model=llm_model)
# 加载工具
tools = load_tools(["llm-math","wikipedia"], llm=llm)
# 初始化代理
agent= initialize_agent(
    tools, 
    llm, 
    agent=AgentType.CHAT_ZERO_SHOT_REACT_DESCRIPTION,
    handle_parsing_errors=True,
    verbose = True)
# 提问1，agent会自主选择使用什么工具
agent("What is the 25% of 300?")
# 提问2
question = "Tom M. Mitchell is an American computer scientist \
and the Founders University Professor at Carnegie Mellon University (CMU)\
what book did he write?"
result = agent(question) 

# 查看agent的每一步过程
agent = create_python_agent(
    llm,
    tool=PythonREPLTool(),
    verbose=True
)
customer_list = [["Harrison", "Chase"], 
                 ["Lang", "Chain"],
                 ["Dolly", "Too"],
                 ["Elle", "Elem"], 
                 ["Geoff","Fusion"], 
                 ["Trance","Former"],
                 ["Jen","Ayai"]
                ]

import langchain
langchain.debug=True
agent.run(f"""Sort these customers by \
last name and then first name \
and print the output: {customer_list}""") 
langchain.debug=False

# 创建自定义工具，将其用到你需要的地方
from langchain.agents import tool
from datetime import date
# 创建一个tool，其中可以添加注释，帮助agent决定什么时候用和注意事项
@tool
def time(text: str) -> str:
    """Returns todays date, use this for any \
    questions related to knowing todays date. \
    The input should always be an empty string, \
    and this function will always return todays \
    date - any date mathmatics should occur \
    outside this function."""
    return str(date.today())
# 创建agent，并将time的tool放入工具列表
agent= initialize_agent(
    tools + [time], 
    llm, 
    agent=AgentType.CHAT_ZERO_SHOT_REACT_DESCRIPTION,
    handle_parsing_errors=True,
    verbose = True)
# 运行agent
agent.run("whats the date today?")