并行工具使用
在带有多个工具的链条指南中,我们看到了如何构建函数调用链,这些链可以在多个工具之间进行选择。一些模型,比如2023年秋季发布的OpenAI模型,还支持并行函数调用,这使得你可以在单个模型调用中调用多个函数(或多次调用同一个函数)。我们在多个工具指南中的先前链条实际上已经支持了这一点,我们只需要使用一个支持并行函数调用的OpenAI模型即可。
设置
为了完成本指南,我们需要安装以下包:
%pip install --upgrade --quiet langchain langchain-openai
并设置以下环境变量:
import getpass
import os
os.environ["OPENAI_API_KEY"] = getpass.getpass()
# 如果你想使用LangSmith,请取消下面的注释
# os.environ["LANGCHAIN_TRACING_V2"] = "true"
# os.environ["LANGCHAIN_API_KEY"] = getpass.getpass()
工具
from langchain_core.tools import tool
@tool
def multiply(first_int: int, second_int: int) -> int:
"""Multiply two integers together."""
return first_int * second_int
@tool
def add(first_int: int, second_int: int) -> int:
"Add two integers."
return first_int + second_int
@tool
def exponentiate(base: int, exponent: int) -> int:
"Exponentiate the base to the exponent power."
return base**exponent
链条
请注意,我们使用了一个-1106
型号的模型,截至本文撰写时,这是唯一支持并行函数调用的类型:
from operator import itemgetter
from typing import Union
from langchain.output_parsers import JsonOutputToolsParser
from langchain_core.runnables import (
Runnable,
RunnableLambda,
RunnableMap,
RunnablePassthrough,
)
from langchain_openai import ChatOpenAI
model = ChatOpenAI(model="gpt-3.5-turbo-1106")
tools = [multiply, exponentiate, add]
model_with_tools = model.bind_tools(tools)
tool_map = {tool.name: tool for tool in tools}
def call_tool(tool_invocation: dict) -> Union[str, Runnable]:
"""Function for dynamically constructing the end of the chain based on the model-selected tool."""
tool = tool_map[tool_invocation["type"]]
return RunnablePassthrough.assign(output=itemgetter("args") | tool)
# .map() allows us to apply a function to a list of inputs.
call_tool_list = RunnableLambda(call_tool).map()
chain = model_with_tools | JsonOutputToolsParser() | call_tool_list
chain.invoke(
"What's 23 times 7, and what's five times 18 and add a million plus a billion and cube thirty-seven"
)
[{'type': 'multiply',
'args': {'first_int': 23, 'second_int': 7},
'output': 161},
{'type': 'add', 'args': {'first_int': 5, 'second_int': 18}, 'output': 23},
{'type': 'add',
'args': {'first_int': 1000000, 'second_int': 1000000000},
'output': 1001000000},
{'type': 'exponentiate',
'args': {'base': 37, 'exponent': 3},
'output': 50653}]