[PYTHON/LANGCHAIN] VectorStoreRetriever 클래스 : configurable_fields 메소드에서 search_kwargs 인자를 사용해 RunnableConfigurableFields 객체 만들기

■ VectorStoreRetriever 클래스의 configurable_fields 메소드에서 search_kwargs 인자를 사용해 RunnableConfigurableFields 객체를 만드는 방법을 보여준다.

※ PINECONE_API_KEY 환경 변수 값은 .env 파일에 정의한다.

▶ main.py


from dotenv                   import load_dotenv
from langchain_openai         import OpenAIEmbeddings
from langchain_pinecone       import PineconeVectorStore
from langchain_core.runnables import ConfigurableField

load_dotenv()

openAIEmbeddings = OpenAIEmbeddings()

pineconeVectorStore = PineconeVectorStore(index_name = "test-example", embedding = openAIEmbeddings) # Pinecone 사이트에서 test-example 인덱스가 존재해야 한다.

pineconeVectorStore.add_texts(["i worked at kensho"  ], namespace = "harrison")
pineconeVectorStore.add_texts(["i worked at facebook"], namespace = "ankush"  )

vectorStoreRetriever = pineconeVectorStore.as_retriever()

runnableConfigurableFields = vectorStoreRetriever.configurable_fields(
    search_kwargs = ConfigurableField(
        id          = "search_kwargs",
        name        = "Search Kwargs",
        description = "The search kwargs to use"
    )
)

from dotenv import load_dotenv

from langchain_openai import OpenAIEmbeddings

from langchain_pinecone import PineconeVectorStore

from langchain_core.runnables import ConfigurableField

load_dotenv()

openAIEmbeddings = OpenAIEmbeddings()

pineconeVectorStore = PineconeVectorStore(index_name = "test-example", embedding = openAIEmbeddings) # Pinecone 사이트에서 test-example 인덱스가 존재해야 한다.

pineconeVectorStore.add_texts(["i worked at kensho" ], namespace = "harrison")

pineconeVectorStore.add_texts(["i worked at facebook"], namespace = "ankush" )

vectorStoreRetriever = pineconeVectorStore.as_retriever()

runnableConfigurableFields = vectorStoreRetriever.configurable_fields(

search_kwargs = ConfigurableField(

id = "search_kwargs",

name = "Search Kwargs",

description = "The search kwargs to use"

)

▶ requirements.txt


aiohttp==3.9.5
aiosignal==1.3.1
annotated-types==0.7.0
anyio==4.6.2.post1
attrs==24.2.0
certifi==2024.8.30
charset-normalizer==3.4.0
colorama==0.4.6
distro==1.9.0
frozenlist==1.5.0
h11==0.14.0
httpcore==1.0.7
httpx==0.28.0
idna==3.10
jiter==0.8.0
jsonpatch==1.33
jsonpointer==3.0.0
langchain-core==0.3.21
langchain-openai==0.2.11
langchain-pinecone==0.2.0
langsmith==0.1.147
multidict==6.1.0
numpy==1.26.4
openai==1.56.2
orjson==3.10.12
packaging==24.2
pinecone-client==5.0.1
pinecone-plugin-inference==1.1.0
pinecone-plugin-interface==0.0.7
propcache==0.2.1
pydantic==2.10.3
pydantic_core==2.27.1
python-dotenv==1.0.1
PyYAML==6.0.2
regex==2024.11.6
requests==2.32.3
requests-toolbelt==1.0.0
sniffio==1.3.1
tenacity==9.0.0
tiktoken==0.8.0
tqdm==4.67.1
typing_extensions==4.12.2
urllib3==2.2.3
yarl==1.18.3

aiohttp==3.9.5

aiosignal==1.3.1

annotated-types==0.7.0

anyio==4.6.2.post1

attrs==24.2.0

certifi==2024.8.30

charset-normalizer==3.4.0

colorama==0.4.6

distro==1.9.0

frozenlist==1.5.0

h11==0.14.0

httpcore==1.0.7

httpx==0.28.0

idna==3.10

jiter==0.8.0

jsonpatch==1.33

jsonpointer==3.0.0

langchain-core==0.3.21

langchain-openai==0.2.11

langchain-pinecone==0.2.0

langsmith==0.1.147

multidict==6.1.0

numpy==1.26.4

openai==1.56.2

orjson==3.10.12

packaging==24.2

pinecone-client==5.0.1

pinecone-plugin-inference==1.1.0

pinecone-plugin-interface==0.0.7

propcache==0.2.1

pydantic==2.10.3

pydantic_core==2.27.1

python-dotenv==1.0.1

PyYAML==6.0.2

regex==2024.11.6

requests==2.32.3

requests-toolbelt==1.0.0

sniffio==1.3.1

tenacity==9.0.0

tiktoken==0.8.0

tqdm==4.67.1

typing_extensions==4.12.2

urllib3==2.2.3

yarl==1.18.3

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