什么是LangChain Agent
简单来说,用户像LangChain输入的内容未知。此时可以有一套工具集合(也可以自定义工具),将这套自定义工具托管给LLM,让其自己决定使用工具中的某一个(如果存在的话)
例子
首先,这里自定义了两个简单的工具
from langchain.tools import BaseTool
# 天气查询工具 ,无论查询什么都返回Sunny
class WeatherTool(BaseTool):
name = "Weather"
description = "useful for When you want to know about the weather"
def _run(self, query: str) -> str:
return "Sunny^_^"
async def _arun(self, query: str) -> str:
"""Use the tool asynchronously."""
raise NotImplementedError("BingSearchRun does not support async")
# 计算工具,暂且写死返回3
class CustomCalculatorTool(BaseTool):
name = "Calculator"
description = "useful for when you need to answer questions about math."
def _run(self, query: str) -> str:
return "3"
async def _arun(self, query: str) -> str:
raise NotImplementedError("BingSearchRun does not support async")
接下来是针对于工具的简单调用:注意,这里使用OpenAI temperature=0
需要限定为0
from langchain.agents import initialize_agent
from langchain.llms import OpenAI
from CustomTools import WeatherTool
from CustomTools import CustomCalculatorTool
llm = OpenAI(temperature=0)
tools = [WeatherTool(), CustomCalculatorTool()]
agent = initialize_agent(tools, llm, agent="zero-shot-react-description", verbose=True)
agent.run("Query the weather of this week,And How old will I be in ten years? This year I am 28")
看一下完整的响应过程:
I need to use two different tools to answer this question
Action: Weather
Action Input: This week
Observation: Sunny^_^
Thought: I need to use a calculator to answer the second part of the question
Action: Calculator
Action Input: 28 + 10
Observation: 3
Thought: I now know the final answer
Final Answer: This week will be sunny and in ten years I will be 38.
可以看到LangChain Agent 详细分析了每一个步骤,并且正确的调用了每一个可用的方法,拿到了相应的返回值,甚至在最后还修复了28+10=3这个错误。
下面看看LangChain Agent是如何做到这点的
工作原理
首先看看我输入的问题是什么:Query the weather of this week,And How old will I be in ten years? This year I am 28
查询本周天气,以及十年后我多少岁,今年我28
LangChain Agent中,有一套模板可以套用:
PREFIX = """Answer the following questions as best you can. You have access to the following tools:"""
FORMAT_INSTRUCTIONS = """Use the following format:
Question: the input question you must answer
Thought: you should always think about what to do
Action: the action to take, should be one of [{tool_names}]
Action Input: the input to the action
Observation: the result of the action
... (this Thought/Action/Action Input/Observation can repeat N times)
Thought: I now know the final answer
Final Answer: the final answer to the original input question"""
SUFFIX = """Begin!
Question: {input}
Thought:{agent_scratchpad}"""
通过这个模板,加上我们的问题以及自定义的工具,会变成下面这个样子,并且附带解释:
Answer the following questions as best you can. You have access to the following tools: # 尽可能的去回答以下问题,你可以使用以下的工具:
Calculator: Useful for when you need to answer questions about math.
# 计算器:当你需要回答数学计算的时候可以用到
Weather: useful for When you want to know about the weather # 天气:当你想知道天气相关的问题时可以用到
Use the following format: # 请使用以下格式(回答)
Question: the input question you must answer # 你必须回答输入的问题
Thought: you should always think about what to do
# 你应该一直保持思考,思考要怎么解决问题
Action: the action to take, should be one of [Calculator, Weather] # 你应该采取[计算器,天气]之一
Action Input: the input to the action # 动作的输入
Observation: the result of the action # 动作的结果
... (this Thought/Action/Action Input/Observation can repeat N times) # 思考-行动-输入-输出 的循环可以重复N次
T
hought: I now know the final answer # 最后,你应该知道最终结果了
Final Answer: the final answer to the original input question # 针对于原始问题,输出最终结果
Begin! # 开始
Question: Query the weather of this week,And How old will I be in ten years? This year I am 28 # 问输入的问题
Thought:
通过这个模板向openai规定了一系列的规范,包括目前现有哪些工具集,你需要思考回答什么问题,你需要用到哪些工具,你对工具需要输入什么内容,等等。
如果仅仅是这样,openAI会完全补完你的回答,中间无法插入任何内容。因此LangChain使用OpenAI的stop参数,截断了AI当前对话。"stop": ["\\nObservation: ", "\\n\\tObservation: "]
做了以上设定以后,OpenAI仅仅会给到Action
和 Action Input
两个内容就被stop早停了。
以下是OpenAI的响应内容:
I need to use the weather tool to answer the first part of the question, and the calculator to answer the second part.
Action: Weather
Action Input: This week
到这里是OpenAI的响应结果,可见,很简单就拿到了Action和Action Input。
这里从Tools中找到name=Weather
的工具,然后再将This Week传入方法。具体业务处理看详细情况。这里仅返回Sunny。
由于当前找到了Action和Action Input。 代表OpenAI认定当前任务链并没有结束。因此像请求体后拼接结果:Observation: Sunny
并且让他再次思考Thought:
开启第二轮思考:
下面是再次请求的完整请求体:
Answer the following questions as best you can. You have access to the following tools:
Calculator: Useful for when you need to answer questions about math.
Weather: useful for When you want to know about the weather
Use the following format:
Question: the input question you must answer
Thought: you should always think about what to do
Action: the action to take, should be one of [Calculator, Weather]
Action Input: the input to the action
Observation: the result of the action
... (this Thought/Action/Action Input/Observation can repeat N times)
Thought: I now know the final answer
Final Answer: the final answer to the original input question
Begin!
Question: Query the weather of this week,And How old will I be in ten years? This year I am 28
Thought: I need to use the weather tool to answer the first part of the question, and the calculator to answer the second part.
Action: Weather
Action Input: This week
Observation: Sunny^_^
Thought:
同第一轮一样,OpenAI再次进行思考,并且返回Action
和 Action Input
后,再次被早停。
I need to calculate my age in ten years
Action: Calculator
Action Input: 28 + 10
由于计算器工具只会返回3,结果会拼接出一个错误的结果,构造成了一个新的请求体
进行第三轮请求:
Answer the following questions as best you can. You have access to the following tools:
Calculator: Useful for when you need to answer questions about math.
Weather: useful for When you want to know about the weather
Use the following format:
Question: the input question you must answer
Thought: you should always think about what to do
Action: the action to take, should be one of [Calculator, Weather]
Action Input: the input to the action
Observation: the result of the action
... (this Thought/Action/Action Input/Observation can repeat N times)
Thought: I now know the final answer
Final Answer: the final answer to the original input question
Begin!
Question: Query the weather of this week,And How old will I be in ten years? This year I am 28
Thought: I need to use the weather tool to answer the first part of the question, and the calculator to answer the second part.
Action: Weather
Action Input: This week
Observation: Sunny^_^
Thought:I need to calculate my age in ten years
Action: Calculator
Action Input: 28 + 10
Observation: 3
Thought:
此时两个问题全都拿到了结果,根据开头的限定,OpenAi在完全拿到结果以后会返回I now know the final answer
。并且根据完整上下文。把多个结果进行归纳总结:下面是完整的相应结果:
I now know the final answer
Final Answer: I will be 38 in ten years and the weather this week is sunny.
可以看到。ai严格的按照设定返回想要的内容,并且还以外的把28+10=3这个数学错误给改正了文章来源:https://www.toymoban.com/news/detail-423596.html
以上,就是LangChain Agent的完整工作流程文章来源地址https://www.toymoban.com/news/detail-423596.html
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