[PYTHON/LANGCHAIN] ChatOpenAI 클래스 : with_structured_output 메소드에서 Union 객체를 정의한 Pydantic 객체를 전달해 여러 스키마 중에서 구조화된 데이터 받기

■ ChatOpenAI 클래스의 with_structured_output 메소드에서 Union 객체를 정의한 Pydantic 객체를 전달해 여러 스키마 중에서 구조화된 데이터를 받는 방법을 보여준다.

▶ main.py


import os

from typing import Optional
from typing import Union

from langchain_core.pydantic_v1 import BaseModel, Field
from langchain_openai           import ChatOpenAI

os.environ["OPENAI_API_KEY"] = "<OPENAI_API_KEY>"

class Joke(BaseModel):
    """Joke to tell user."""

    setup     : str           = Field(description = "The setup of the joke"              )
    punchline : str           = Field(description = "The punchline to the joke"          )
    rating    : Optional[int] = Field(description = "How funny the joke is, from 1 to 10")

class ConversationalResponse(BaseModel):
    """Respond in a conversational manner. Be kind and helpful."""

    response : str = Field(description = "A conversational response to the user's query")

class Response(BaseModel):
    output : Union[Joke, ConversationalResponse]

chatOpenAI = ChatOpenAI(model = "gpt-3.5-turbo-0125")

runnableSequence = chatOpenAI.with_structured_output(Response)

response1 = runnableSequence.invoke("Tell me a joke about cats")

print(response1)

"""
output=Joke(setup='Why was the cat sitting on the computer?', punchline='To keep an eye on the mouse!', rating=8)
"""

response2 = runnableSequence.invoke("How are you today?")

print(response2)

"""
output=ConversationalResponse(response="I'm just a virtual assistant, so I don't have feelings, but I'm here to help you with anything you need. How can I assist you today?")
"""

import os

from typing import Optional

from typing import Union

from langchain_core.pydantic_v1 import BaseModel, Field

from langchain_openai import ChatOpenAI

os.environ["OPENAI_API_KEY"] = "<OPENAI_API_KEY>"

class Joke(BaseModel):

"""Joke to tell user."""

setup : str = Field(description = "The setup of the joke" )

punchline : str = Field(description = "The punchline to the joke" )

rating : Optional[int] = Field(description = "How funny the joke is, from 1 to 10")

class ConversationalResponse(BaseModel):

"""Respond in a conversational manner. Be kind and helpful."""

response : str = Field(description = "A conversational response to the user's query")

class Response(BaseModel):

output : Union[Joke, ConversationalResponse]

chatOpenAI = ChatOpenAI(model = "gpt-3.5-turbo-0125")

runnableSequence = chatOpenAI.with_structured_output(Response)

response1 = runnableSequence.invoke("Tell me a joke about cats")

print(response1)

"""

output=Joke(setup='Why was the cat sitting on the computer?', punchline='To keep an eye on the mouse!', rating=8)

"""

response2 = runnableSequence.invoke("How are you today?")

print(response2)

"""

output=ConversationalResponse(response="I'm just a virtual assistant, so I don't have feelings, but I'm here to help you with anything you need. How can I assist you today?")

"""

▶ requirements.txt


annotated-types==0.7.0
anyio==4.4.0
certifi==2024.6.2
charset-normalizer==3.3.2
distro==1.9.0
exceptiongroup==1.2.1
h11==0.14.0
httpcore==1.0.5
httpx==0.27.0
idna==3.7
jsonpatch==1.33
jsonpointer==3.0.0
langchain-core==0.2.7
langchain-openai==0.1.8
langsmith==0.1.77
openai==1.34.0
orjson==3.10.5
packaging==24.1
pydantic==2.7.4
pydantic_core==2.18.4
PyYAML==6.0.1
regex==2024.5.15
requests==2.32.3
sniffio==1.3.1
tenacity==8.3.0
tiktoken==0.7.0
tqdm==4.66.4
typing_extensions==4.12.2
urllib3==2.2.1

annotated-types==0.7.0

anyio==4.4.0

certifi==2024.6.2

charset-normalizer==3.3.2

distro==1.9.0

exceptiongroup==1.2.1

h11==0.14.0

httpcore==1.0.5

httpx==0.27.0

idna==3.7

jsonpatch==1.33

jsonpointer==3.0.0

langchain-core==0.2.7

langchain-openai==0.1.8

langsmith==0.1.77

openai==1.34.0

orjson==3.10.5

packaging==24.1

pydantic==2.7.4

pydantic_core==2.18.4

PyYAML==6.0.1

regex==2024.5.15

requests==2.32.3

sniffio==1.3.1

tenacity==8.3.0

tiktoken==0.7.0

tqdm==4.66.4

typing_extensions==4.12.2

urllib3==2.2.1

※ pip install langchain-openai 명령을 실행했다.