[PYTHON/LANGCHAIN] InjectedToolArg 클래스 : 도구에 런타임 값 전달하기

■ InjectedToolArg 클래스를 사용해 도구에 런타임 값을 전달하는 방법을 보여준다.

※ 런타임에만 알려진 도구에 값을 바인딩해야 할 수도 있다.
※ 예를 들어, 도구 로직은 요청을 한 사용자의 ID를 사용해야 할 수 있다.
※ 대부분의 경우 이러한 값은 LLM에서 제어해서는 안 된다.
※ 사실, LLM이 사용자 ID를 제어하도록 허용하면 보안 위험이 발생할 수 있다.
※ 대신 LLM은 LLM에서 제어하도록 의도된 도구의 매개 변수만 제어해야 하며, 다른 매개 변수(예 : 사용자 ID)는 애플리케이션 로직에서 수정해야 한다.
※ 모델이 특정 도구 인수를 생성하여 런타임에 직접 주입하는 것을 방지하는 방법을 보여준다.
※ OPENAI_API_KEY 환경 변수 값은 .env 파일에 정의한다.

▶ main.py


from dotenv                   import load_dotenv
from langchain_core.tools     import tool
from typing                   import List
from typing_extensions        import Annotated
from langchain_core.tools     import InjectedToolArg
from langchain_openai         import ChatOpenAI
from langchain_core.runnables import chain
from copy                     import deepcopy

load_dotenv()

userDictionary = {}
userID         = "123"

@tool(parse_docstring = True)
def updateFavoritePets(petList : List[str], userID : Annotated[str, InjectedToolArg]) -> None:
    """Add the list of favorite pets.

    Args:
        petList : List of favorite pets to set.
        userID  : User's ID.
    """
    userDictionary[userID] = petList

@tool(parse_docstring = True)
def deleteFavoritePets(userID : Annotated[str, InjectedToolArg]) -> None:
    """Delete the list of favorite pets.

    Args:
        userID : User's ID.
    """
    if userID in userDictionary:
        del userDictionary[userID]

@tool(parse_docstring = True)
def listFavoritePets(userID : Annotated[str, InjectedToolArg]) -> None:
    """List favorite pets if any.

    Args:
        userID : User's ID.
    """
    return userDictionary.get(userID, [])

toolList = [
    updateFavoritePets,
    deleteFavoritePets,
    listFavoritePets,
]

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

runnableBindable = chatOpenAI.bind_tools(toolList)

aiMessage = runnableBindable.invoke("my favorite animals are cats and parrots")

@chain
def injectUserID(aiMessage):
    toolCallList = []
    for toolCall in aiMessage.tool_calls:
        copyToolCall = deepcopy(toolCall)
        copyToolCall["args"]["userID"] = userID
        toolCallList.append(copyToolCall)
    return toolCallList

toolMapDictionary = {tool.name : tool for tool in toolList}

@chain
def getTool(toolCall):
    return toolMapDictionary[toolCall["name"]]

runnableSquence = runnableBindable | injectUserID | getTool.map()

inputSchemaDictionary = runnableSquence.invoke("my favorite animals are cats and parrots")

print(inputSchemaDictionary)
print()
print(userDictionary)

"""
[ToolMessage(content='null', name='updateFavoritePets', tool_call_id='call_A9Bw2iMPO2uWQGnIqPnqZI2h')]
{'123': ['cats', 'parrots']}
"""

from dotenv import load_dotenv

from langchain_core.tools import tool

from typing import List

from typing_extensions import Annotated

from langchain_core.tools import InjectedToolArg

from langchain_openai import ChatOpenAI

from langchain_core.runnables import chain

from copy import deepcopy

load_dotenv()

userDictionary = {}

userID = "123"

@tool(parse_docstring = True)

def updateFavoritePets(petList : List[str], userID : Annotated[str, InjectedToolArg]) -> None:

"""Add the list of favorite pets.

Args:

petList : List of favorite pets to set.

userID : User's ID.

"""

userDictionary[userID] = petList

@tool(parse_docstring = True)

def deleteFavoritePets(userID : Annotated[str, InjectedToolArg]) -> None:

"""Delete the list of favorite pets.

Args:

userID : User's ID.

"""

if userID in userDictionary:

del userDictionary[userID]

@tool(parse_docstring = True)

def listFavoritePets(userID : Annotated[str, InjectedToolArg]) -> None:

"""List favorite pets if any.

Args:

userID : User's ID.

"""

return userDictionary.get(userID, [])

toolList = [

updateFavoritePets,

deleteFavoritePets,

listFavoritePets,

]

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

runnableBindable = chatOpenAI.bind_tools(toolList)

aiMessage = runnableBindable.invoke("my favorite animals are cats and parrots")

@chain

def injectUserID(aiMessage):

toolCallList = []

for toolCall in aiMessage.tool_calls:

copyToolCall = deepcopy(toolCall)

copyToolCall["args"]["userID"] = userID

toolCallList.append(copyToolCall)

return toolCallList

toolMapDictionary = {tool.name : tool for tool in toolList}

@chain

def getTool(toolCall):

return toolMapDictionary[toolCall["name"]]

runnableSquence = runnableBindable | injectUserID | getTool.map()

inputSchemaDictionary = runnableSquence.invoke("my favorite animals are cats and parrots")

print(inputSchemaDictionary)

print()

print(userDictionary)

"""

[ToolMessage(content='null', name='updateFavoritePets', tool_call_id='call_A9Bw2iMPO2uWQGnIqPnqZI2h')]

{'123': ['cats', 'parrots']}

"""

▶ requirements.txt


annotated-types==0.7.0
anyio==4.5.0
certifi==2024.8.30
charset-normalizer==3.3.2
colorama==0.4.6
distro==1.9.0
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==0.3.2
langchain-openai==0.2.0
langsmith==0.1.125
openai==1.46.1
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==4.5.0

certifi==2024.8.30

charset-normalizer==3.3.2

colorama==0.4.6

distro==1.9.0

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==0.3.2

langchain-openai==0.2.0

langsmith==0.1.125

openai==1.46.1

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 python-dotenv langchain-openai 명령을 실행했다.