50 lines
1.5 KiB
Python
50 lines
1.5 KiB
Python
from config import OPENAI_API_KEY
|
|
from langchain_openai import ChatOpenAI
|
|
# 在LangChain 1.0+版本中，以下俩组件移到了langchain-classic包中
|
|
from langchain_classic.agents import AgentExecutor
|
|
from langchain_classic.agents import create_tool_calling_agent
|
|
from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
|
|
from langchain_core.tools import tool # 导入 @tool
|
|
|
|
# 配置LLM
|
|
llm = ChatOpenAI(
|
|
model="deepseek-chat",
|
|
api_key=OPENAI_API_KEY,
|
|
base_url="https://api.deepseek.com"
|
|
)
|
|
|
|
# 配置prompt
|
|
prompt = ChatPromptTemplate.from_messages([
|
|
("system","你是一个聪明的智能助手。当你遇到解决不了的问题时，会调用工具来解决问题。"),
|
|
("human","{input}"),
|
|
MessagesPlaceholder(variable_name="agent_scratchpad") # 必加，Agent的思考过程
|
|
])
|
|
|
|
# 配置tool
|
|
@tool
|
|
def get_weather(location):
|
|
"""模拟获得天气信息"""
|
|
return f"{location}当前天气：23℃，晴，风力2级"
|
|
|
|
@tool
|
|
def get_user_name(user):
|
|
"""模拟获得用户名字"""
|
|
return f'用户名字是:{user}'
|
|
|
|
|
|
tools = [get_weather,get_user_name]
|
|
|
|
# 创建Agent(大脑)
|
|
agent = create_tool_calling_agent(llm=llm,prompt=prompt,tools=tools)
|
|
# 创建AgentExecutor(执行器)--负责运行ReAct循环
|
|
agent_executor = AgentExecutor(agent=agent,tools=tools,verbose=True) # 开启verbose以看到ai思考链
|
|
# 运行
|
|
response = agent_executor.invoke({
|
|
'input':"今天北京的天气怎么样？"
|
|
})
|
|
|
|
print(response)
|
|
print()
|
|
print(response['output'])
|
|
|