[PYTHON/LANGCHAIN] RunnableBindable 클래스 : invoke 메소드를 사용해 모델에서 도구 호출하기

■ RunnableBindable 클래스의 invoke 메소드를 사용해 모델에서 도구를 호출하는 방법을 보여준다.

※ OPENAI_API_KEY 환경 변수 값은 .env 파일에 정의한다.

▶ main.py


import random

from dotenv               import load_dotenv
from langchain_core.tools import tool
from typing               import Tuple
from typing               import List
from langchain_openai     import ChatOpenAI

load_dotenv()

@tool(response_format = "content_and_artifact")
def generateRandomIntegerValues(minimumValue : int, maximumValue : int, count : int) -> Tuple[str, List[int]]:
    """Generate size random ints in the range [minimumValue, maximumValue]."""
    array = [random.randint(minimumValue, maximumValue) for _ in range(count)]
    content = f"Successfully generated array of {count} random ints in [{minimumValue}, {maximumValue}]."
    return content, array

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

runnableBindable = chatOpenAI.bind_tools([generateRandomIntegerValues])

responseAIMessage = runnableBindable.invoke("generate 6 positive ints less than 25")

print(responseAIMessage.tool_calls)

"""
[{'name': 'generateRandomIntegerValues', 'args': {'minimumValue': 1, 'maximumValue': 24, 'count': 6}, 'id': 'call_F9ZZFBIsd6HXz30bb0yZTWgl', 'type': 'tool_call'}]
"""

import random

from dotenv import load_dotenv

from langchain_core.tools import tool

from typing import Tuple

from typing import List

from langchain_openai import ChatOpenAI

load_dotenv()

@tool(response_format = "content_and_artifact")

def generateRandomIntegerValues(minimumValue : int, maximumValue : int, count : int) -> Tuple[str, List[int]]:

"""Generate size random ints in the range [minimumValue, maximumValue]."""

array = [random.randint(minimumValue, maximumValue) for _ in range(count)]

content = f"Successfully generated array of {count} random ints in [{minimumValue}, {maximumValue}]."

return content, array

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

runnableBindable = chatOpenAI.bind_tools([generateRandomIntegerValues])

responseAIMessage = runnableBindable.invoke("generate 6 positive ints less than 25")

print(responseAIMessage.tool_calls)

"""

[{'name': 'generateRandomIntegerValues', 'args': {'minimumValue': 1, 'maximumValue': 24, 'count': 6}, 'id': 'call_F9ZZFBIsd6HXz30bb0yZTWgl', 'type': 'tool_call'}]

"""

▶ requirements.txt


annotated-types==0.7.0
anyio==4.6.0
certifi==2024.8.30
charset-normalizer==3.3.2
distro==1.9.0
exceptiongroup==1.2.2
h11==0.14.0
httpcore==1.0.5
httpx==0.27.2
idna==3.10
jiter==0.5.0
jsonpatch==1.33
jsonpointer==3.0.0
langchain-core==0.3.6
langchain-openai==0.2.1
langsmith==0.1.129
openai==1.50.2
orjson==3.10.7
packaging==24.1
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
sniffio==1.3.1
tenacity==8.5.0
tiktoken==0.7.0
tqdm==4.66.5
typing_extensions==4.12.2
urllib3==2.2.3

annotated-types==0.7.0

anyio==4.6.0

certifi==2024.8.30

charset-normalizer==3.3.2

distro==1.9.0

exceptiongroup==1.2.2

h11==0.14.0

httpcore==1.0.5

httpx==0.27.2

idna==3.10

jiter==0.5.0

jsonpatch==1.33

jsonpointer==3.0.0

langchain-core==0.3.6

langchain-openai==0.2.1

langsmith==0.1.129

openai==1.50.2

orjson==3.10.7

packaging==24.1

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

sniffio==1.3.1

tenacity==8.5.0

tiktoken==0.7.0

tqdm==4.66.5

typing_extensions==4.12.2

urllib3==2.2.3

※ pip install langchain-openai 명령을 실행했다.