[PYTHON/LANGCHAIN] CompiledStateGraph 클래스 : asyncio 모듈의 create_task/wait_for 함수를 사용해 최대 실행 시간 설정하기

■ CompiledStateGraph 클래스에서 asyncio 패키지의 create_task/wait_for 함수를 사용해 최대 실행 시간을 설정하는 방법을 보여준다.

※ OPENAI_API_KEY 환경 변수 값은 .env 파일에 정의한다.

▶ main.py


import asyncio
import time

from dotenv               import load_dotenv
from langchain_openai     import ChatOpenAI
from langchain_core.tools import tool
from langgraph.prebuilt   import create_react_agent

load_dotenv()

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

@tool
def magicFunction(input : int) -> int:
    """Applies a magic function to an input."""
    time.sleep(2.5)
    return input + 2

toolList = [magicFunction]

compiledStateGraph = create_react_agent(chatOpenAI, tools = toolList)

async def stream(compiledStateGraph, inputDictionary):
    async for addableValuesDict in compiledStateGraph.astream(inputDictionary):
        print(addableValuesDict)
        print("-" * 100)

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

async def main():
    try:
        task = asyncio.create_task(stream(compiledStateGraph, {"messages": [("human", query)]}))
        await asyncio.wait_for(task, timeout = 3)
    except asyncio.exceptions.TimeoutError:
        print("Task Cancelled.")

asyncio.run(main())

import asyncio

import time

from dotenv import load_dotenv

from langchain_openai import ChatOpenAI

from langchain_core.tools import tool

from langgraph.prebuilt import create_react_agent

load_dotenv()

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

@tool

def magicFunction(input : int) -> int:

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

time.sleep(2.5)

return input + 2

toolList = [magicFunction]

compiledStateGraph = create_react_agent(chatOpenAI, tools = toolList)

async def stream(compiledStateGraph, inputDictionary):

async for addableValuesDict in compiledStateGraph.astream(inputDictionary):

print(addableValuesDict)

print("-" * 100)

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

async def main():

try:

task = asyncio.create_task(stream(compiledStateGraph, {"messages": [("human", query)]}))

await asyncio.wait_for(task, timeout = 3)

except asyncio.exceptions.TimeoutError:

print("Task Cancelled.")

asyncio.run(main())

▶ 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
langgraph==0.2.35
langgraph-checkpoint==2.0.1
langsmith==0.1.134
msgpack==1.1.0
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

langgraph==0.2.35

langgraph-checkpoint==2.0.1

langsmith==0.1.134

msgpack==1.1.0

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 langgraph 명령을 실행했다.