[PYTHON/LANGCHAIN] langserve 모듈 : langchain 모듈 체인을 REST API 서버로 배포하기

■ langserve 모듈을 사용해 langchain 모듈의 체인을 REST API 서버로 배포하는 방법을 보여준다.

▶ server.py


import os

import uvicorn

from langchain_core.prompts        import ChatPromptTemplate
from langchain_core.output_parsers import StrOutputParser
from langchain_openai              import ChatOpenAI
from fastapi                       import FastAPI
from langserve                     import add_routes

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

promptTemplate = ChatPromptTemplate.from_messages(
    [
        ("system", "Translate the following into {language} : "),
        ("user"  , "{text}"                                    )
    ]
)

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

strOutputParser = StrOutputParser()

runnableSequence = promptTemplate | chatOpenAI | strOutputParser

fastAPI = FastAPI(
  title       = "LangChain Server",
  version     = "1.0",
  description = "A simple API server using LangChain's Runnable interfaces",
)

add_routes(
    fastAPI,
    runnableSequence,
    path = "/chain",
)

if __name__ == "__main__":
    uvicorn.run(fastAPI, host = "0.0.0.0", port = 8000)

import os

import uvicorn

from langchain_core.prompts import ChatPromptTemplate

from langchain_core.output_parsers import StrOutputParser

from langchain_openai import ChatOpenAI

from fastapi import FastAPI

from langserve import add_routes

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

promptTemplate = ChatPromptTemplate.from_messages(

[

("system", "Translate the following into {language} : "),

("user" , "{text}" )

]

)

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

strOutputParser = StrOutputParser()

runnableSequence = promptTemplate | chatOpenAI | strOutputParser

fastAPI = FastAPI(

title = "LangChain Server",

version = "1.0",

description = "A simple API server using LangChain's Runnable interfaces",

)

add_routes(

fastAPI,

runnableSequence,

path = "/chain",

)

if __name__ == "__main__":

uvicorn.run(fastAPI, host = "0.0.0.0", port = 8000)

▶ client.py


from langserve import RemoteRunnable

remoteRunnable = RemoteRunnable("http://localhost:8000/chain/")

resultString = remoteRunnable.invoke({"language" : "korean", "text" : "hi"})

print(resultString)

from langserve import RemoteRunnable

remoteRunnable = RemoteRunnable("http://localhost:8000/chain/")

resultString = remoteRunnable.invoke({"language" : "korean", "text" : "hi"})

print(resultString)

▶ 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==2.4
langchain==0.2.3
langchain-core==0.2.5
langchain-openai==0.1.8
langchain-text-splitters==0.2.1
langsmith==0.1.75
multidict==6.0.5
numpy==1.26.4
openai==1.33.0
orjson==3.10.3
packaging==23.2
pydantic==2.7.3
pydantic_core==2.18.4
PyYAML==6.0.1
regex==2024.5.15
requests==2.32.3
sniffio==1.3.1
SQLAlchemy==2.0.30
tenacity==8.3.0
tiktoken==0.7.0
tqdm==4.66.4
typing_extensions==4.12.2
urllib3==2.2.1
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==2.4

langchain==0.2.3

langchain-core==0.2.5

langchain-openai==0.1.8

langchain-text-splitters==0.2.1

langsmith==0.1.75

multidict==6.0.5

numpy==1.26.4

openai==1.33.0

orjson==3.10.3

packaging==23.2

pydantic==2.7.3

pydantic_core==2.18.4

PyYAML==6.0.1

regex==2024.5.15

requests==2.32.3

sniffio==1.3.1

SQLAlchemy==2.0.30

tenacity==8.3.0

tiktoken==0.7.0

tqdm==4.66.4

typing_extensions==4.12.2

urllib3==2.2.1

yarl==1.9.4

※ pip install langchain langchain-openai langserve["all"] 명령을 실행했다.