[PYTHON/LANGCHAIN] JsonOutputParser 클래스 : 체인에서 구조화된 데이터 구하기

■ JsonOutputParser 클래스를 사용해 체인에서 구조화된 데이터를 구하는 방법을 보여준다.

※ OPENAI_API_KEY 환경 변수 값은 .env 파일에 정의한다.

▶ main.py


from dotenv                        import load_dotenv
from langchain_core.pydantic_v1    import BaseModel
from langchain_core.pydantic_v1    import Field
from langchain_core.prompts        import PromptTemplate
from langchain_openai              import OpenAI
from langchain_core.output_parsers import JsonOutputParser

load_dotenv()

class Joke(BaseModel):
    setup     : str = Field(description = "question to set up a joke" )
    punchline : str = Field(description = "answer to resolve the joke")

jsonOutputParser = JsonOutputParser(pydantic_object = Joke)

promptTemplate = PromptTemplate(
    template          = "Answer the user query.\n{format_instructions}\n{query}\n",
    input_variables   = ["query"],
    partial_variables = {"format_instructions" : jsonOutputParser.get_format_instructions()},
)

openAI = OpenAI(model_name = "gpt-3.5-turbo-instruct", temperature = 0.0)

runnableSequence = promptTemplate | openAI | jsonOutputParser

responseDictionary = runnableSequence.invoke({"query" : "Tell me a joke."})

print(responseDictionary)

"""
{'setup' : 'Why did the tomato turn red?', 'punchline' : 'Because it saw the salad dressing!'}
"""

from dotenv import load_dotenv

from langchain_core.pydantic_v1 import BaseModel

from langchain_core.pydantic_v1 import Field

from langchain_core.prompts import PromptTemplate

from langchain_openai import OpenAI

from langchain_core.output_parsers import JsonOutputParser

load_dotenv()

class Joke(BaseModel):

setup : str = Field(description = "question to set up a joke" )

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

jsonOutputParser = JsonOutputParser(pydantic_object = Joke)

promptTemplate = PromptTemplate(

template = "Answer the user query.\n{format_instructions}\n{query}\n",

input_variables = ["query"],

partial_variables = {"format_instructions" : jsonOutputParser.get_format_instructions()},

)

openAI = OpenAI(model_name = "gpt-3.5-turbo-instruct", temperature = 0.0)

runnableSequence = promptTemplate | openAI | jsonOutputParser

responseDictionary = runnableSequence.invoke({"query" : "Tell me a joke."})

print(responseDictionary)

"""

{'setup' : 'Why did the tomato turn red?', 'punchline' : 'Because it saw the salad dressing!'}

"""

▶ requirements.txt


aiohttp==3.9.5
aiosignal==1.3.1
annotated-types==0.7.0
anyio==4.4.0
async-timeout==4.0.3
attrs==23.2.0
certifi==2024.6.2
charset-normalizer==3.3.2
distro==1.9.0
exceptiongroup==1.2.1
frozenlist==1.4.1
greenlet==3.0.3
h11==0.14.0
httpcore==1.0.5
httpx==0.27.0
idna==3.7
jsonpatch==1.33
jsonpointer==3.0.0
langchain==0.2.6
langchain-core==0.2.10
langchain-openai==0.1.10
langchain-text-splitters==0.2.2
langsmith==0.1.82
multidict==6.0.5
numpy==1.26.4
openai==1.35.4
orjson==3.10.5
packaging==24.1
pydantic==2.7.4
pydantic_core==2.18.4
python-dotenv==1.0.1
PyYAML==6.0.1
regex==2024.5.15
requests==2.32.3
sniffio==1.3.1
SQLAlchemy==2.0.31
tenacity==8.4.2
tiktoken==0.7.0
tqdm==4.66.4
typing_extensions==4.12.2
urllib3==2.2.2
yarl==1.9.4

aiohttp==3.9.5

aiosignal==1.3.1

annotated-types==0.7.0

anyio==4.4.0

async-timeout==4.0.3

attrs==23.2.0

certifi==2024.6.2

charset-normalizer==3.3.2

distro==1.9.0

exceptiongroup==1.2.1

frozenlist==1.4.1

greenlet==3.0.3

h11==0.14.0

httpcore==1.0.5

httpx==0.27.0

idna==3.7

jsonpatch==1.33

jsonpointer==3.0.0

langchain==0.2.6

langchain-core==0.2.10

langchain-openai==0.1.10

langchain-text-splitters==0.2.2

langsmith==0.1.82

multidict==6.0.5

numpy==1.26.4

openai==1.35.4

orjson==3.10.5

packaging==24.1

pydantic==2.7.4

pydantic_core==2.18.4

python-dotenv==1.0.1

PyYAML==6.0.1

regex==2024.5.15

requests==2.32.3

sniffio==1.3.1

SQLAlchemy==2.0.31

tenacity==8.4.2

tiktoken==0.7.0

tqdm==4.66.4

typing_extensions==4.12.2

urllib3==2.2.2

yarl==1.9.4

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