[PYTHON/LANGCHAIN] RunnableSequence 클래스 : with_fallbacks 메소드를 사용해 체인 오류시 다른 체인으로 대체하는 RunnableWithFallbacks 객체 만들기

■ RunnableSequence 클래스의 with_fallbacks 메소드를 사용해 체인 오류시 다른 체인으로 대체하는 RunnableWithFallbacks 객체를 만드는 방법을 보여준다.

※ OPENAI_API_KEY 환경 변수 값은 .env 파일에 정의한다.

▶ main.py


from dotenv                        import load_dotenv
from langchain_core.prompts        import ChatPromptTemplate
from langchain_openai              import ChatOpenAI
from langchain_core.output_parsers import StrOutputParser
from langchain_core.prompts        import PromptTemplate
from langchain_openai              import OpenAI

load_dotenv()

badChatPromptTemplate = ChatPromptTemplate.from_messages(
    [
        (
            "system",
            "You're a nice assistant who always includes a compliment in your response",
        ),
        ("human", "Why did the {animal} cross the road?")
    ]
)

badChatOpenAI = ChatOpenAI(model = "gpt-fake")

badRunnableSequence = badChatPromptTemplate | badChatOpenAI | StrOutputParser()

goodPromptTemplateString = """Instructions : You should always include a compliment in your response.

Question : Why did the {animal} cross the road?"""

goodPromptTemplate = PromptTemplate.from_template(goodPromptTemplateString)

goodOpenAI = OpenAI()

goodRunnableSequence = goodPromptTemplate | goodOpenAI | StrOutputParser()

runnableWithFallbacks = badRunnableSequence.with_fallbacks([goodRunnableSequence])

responseString = runnableWithFallbacks.invoke({"animal" : "turtle"})

print(responseString)

"""
Response : That's a great question! You always come up with the most interesting and thought-provoking questions.
"""

from dotenv import load_dotenv

from langchain_core.prompts import ChatPromptTemplate

from langchain_openai import ChatOpenAI

from langchain_core.output_parsers import StrOutputParser

from langchain_core.prompts import PromptTemplate

from langchain_openai import OpenAI

load_dotenv()

badChatPromptTemplate = ChatPromptTemplate.from_messages(

[

(

"system",

"You're a nice assistant who always includes a compliment in your response",

("human", "Why did the {animal} cross the road?")

]

)

badChatOpenAI = ChatOpenAI(model = "gpt-fake")

badRunnableSequence = badChatPromptTemplate | badChatOpenAI | StrOutputParser()

goodPromptTemplateString = """Instructions : You should always include a compliment in your response.

Question : Why did the {animal} cross the road?"""

goodPromptTemplate = PromptTemplate.from_template(goodPromptTemplateString)

goodOpenAI = OpenAI()

goodRunnableSequence = goodPromptTemplate | goodOpenAI | StrOutputParser()

runnableWithFallbacks = badRunnableSequence.with_fallbacks([goodRunnableSequence])

responseString = runnableWithFallbacks.invoke({"animal" : "turtle"})

print(responseString)

"""

Response : That's a great question! You always come up with the most interesting and thought-provoking questions.

"""

▶ 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==0.2.9
langchain-openai==0.1.9
langsmith==0.1.81
openai==1.35.3
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
tenacity==8.4.1
tiktoken==0.7.0
tqdm==4.66.4
typing_extensions==4.12.2
urllib3==2.2.2

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==0.2.9

langchain-openai==0.1.9

langsmith==0.1.81

openai==1.35.3

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

tenacity==8.4.1

tiktoken==0.7.0

tqdm==4.66.4

typing_extensions==4.12.2

urllib3==2.2.2

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