[PYTHON/LANGCHAIN] AgentExecutor 클래스 : 생성자에서 early_stopping_method/max_iterations 인자를 사용해 반복 제한/시간 제한 중단 문자열 반환하기

■ AgentExecutor 클래스의 생성자에서 early_stopping_method/max_iterations 인자를 사용해 반복 제한/시간 제한 중단 문자열을 반환하는 방법을 보여준다.

※ OPENAI_API_KEY 환경 변수 값은 .env 파일에 정의한다.

▶ main.py


from dotenv                 import load_dotenv
from langchain_openai       import ChatOpenAI
from langchain_core.tools   import tool
from langchain_core.prompts import ChatPromptTemplate
from langchain.agents       import create_tool_calling_agent
from langchain.agents       import AgentExecutor

load_dotenv()

chatOpenAI = ChatOpenAI(model = "gpt-4o")

@tool
def magicFunction(input : int) -> int:
    """Applies a magic function to an input."""
    return input + 2

toolList = [magicFunction]

chatPromptTemplate = ChatPromptTemplate.from_messages(
    [
        ("system"     , "You are a helpful assistant. Respond only in Korean."),
        ("human"      , "{input}"                                             ),
        ("placeholder", "{agent_scratchpad}"                                  )
    ]
)

runnableSequence = create_tool_calling_agent(chatOpenAI, toolList, chatPromptTemplate)

agentExecutor = AgentExecutor(
    agent                 = runnableSequence,
    tools                 = toolList,
    early_stopping_method = "force",
    max_iterations        = 1,
    verbose               = False
)

query = "what is the value of magicFunction(3)?"

responseDictionary = agentExecutor.invoke({"input" : query})

print(responseDictionary)

"""
{'input': 'what is the value of magicFunction(3)?', 'output': 'Agent stopped due to max iterations.'}
"""

from dotenv import load_dotenv

from langchain_openai import ChatOpenAI

from langchain_core.tools import tool

from langchain_core.prompts import ChatPromptTemplate

from langchain.agents import create_tool_calling_agent

from langchain.agents import AgentExecutor

load_dotenv()

chatOpenAI = ChatOpenAI(model = "gpt-4o")

@tool

def magicFunction(input : int) -> int:

"""Applies a magic function to an input."""

return input + 2

toolList = [magicFunction]

chatPromptTemplate = ChatPromptTemplate.from_messages(

[

("system" , "You are a helpful assistant. Respond only in Korean."),

("human" , "{input}" ),

("placeholder", "{agent_scratchpad}" )

]

)

runnableSequence = create_tool_calling_agent(chatOpenAI, toolList, chatPromptTemplate)

agentExecutor = AgentExecutor(

agent = runnableSequence,

tools = toolList,

early_stopping_method = "force",

max_iterations = 1,

verbose = False

)

query = "what is the value of magicFunction(3)?"

responseDictionary = agentExecutor.invoke({"input" : query})

print(responseDictionary)

"""

{'input': 'what is the value of magicFunction(3)?', 'output': 'Agent stopped due to max iterations.'}

"""

▶ requirements.txt


aiohappyeyeballs==2.4.3
aiohttp==3.10.10
aiosignal==1.3.1
annotated-types==0.7.0
anyio==4.6.2
async-timeout==4.0.3
attrs==24.2.0
certifi==2024.8.30
charset-normalizer==3.4.0
distro==1.9.0
exceptiongroup==1.2.2
frozenlist==1.4.1
greenlet==3.1.1
h11==0.14.0
httpcore==1.0.6
httpx==0.27.2
idna==3.10
jiter==0.6.1
jsonpatch==1.33
jsonpointer==3.0.0
langchain==0.3.3
langchain-core==0.3.10
langchain-openai==0.2.2
langchain-text-splitters==0.3.0
langsmith==0.1.134
multidict==6.1.0
numpy==1.26.4
openai==1.51.2
orjson==3.10.7
packaging==24.1
propcache==0.2.0
pydantic==2.9.2
pydantic_core==2.23.4
python-dotenv==1.0.1
PyYAML==6.0.2
regex==2024.9.11
requests==2.32.3
requests-toolbelt==1.0.0
sniffio==1.3.1
SQLAlchemy==2.0.35
tenacity==8.5.0
tiktoken==0.8.0
tqdm==4.66.5
typing_extensions==4.12.2
urllib3==2.2.3
yarl==1.15.2

aiohappyeyeballs==2.4.3

aiohttp==3.10.10

aiosignal==1.3.1

annotated-types==0.7.0

anyio==4.6.2

async-timeout==4.0.3

attrs==24.2.0

certifi==2024.8.30

charset-normalizer==3.4.0

distro==1.9.0

exceptiongroup==1.2.2

frozenlist==1.4.1

greenlet==3.1.1

h11==0.14.0

httpcore==1.0.6

httpx==0.27.2

idna==3.10

jiter==0.6.1

jsonpatch==1.33

jsonpointer==3.0.0

langchain==0.3.3

langchain-core==0.3.10

langchain-openai==0.2.2

langchain-text-splitters==0.3.0

langsmith==0.1.134

multidict==6.1.0

numpy==1.26.4

openai==1.51.2

orjson==3.10.7

packaging==24.1

propcache==0.2.0

pydantic==2.9.2

pydantic_core==2.23.4

python-dotenv==1.0.1

PyYAML==6.0.2

regex==2024.9.11

requests==2.32.3

requests-toolbelt==1.0.0

sniffio==1.3.1

SQLAlchemy==2.0.35

tenacity==8.5.0

tiktoken==0.8.0

tqdm==4.66.5

typing_extensions==4.12.2

urllib3==2.2.3

yarl==1.15.2

※ pip install python-dotenv langchain langchain-openai 명령을 실행했다.