DocArrayHnswSearch는 Docarray에서 제공하는 경량 Document Index 구현으로, 완전히 로컬에서 실행되며 소규모에서 중규모 데이터셋에 가장 적합합니다. 벡터는 hnswlib에 디스크에 저장하고, 다른 모든 데이터는 SQLite에 저장합니다.
이 integration을 사용하려면 pip install -qU langchain-community로 langchain-community를 설치해야 합니다 이 notebook은 DocArrayHnswSearch와 관련된 기능을 사용하는 방법을 보여줍니다.

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Setup

아직 설치하지 않았다면 아래 셀의 주석을 해제하여 docarray를 설치하고 OpenAI api key를 가져오거나 설정하세요. 
pip install -qU  "docarray[hnswlib]"

# Get an OpenAI token: https://platform.openai.com/account/api-keys

# import os
# from getpass import getpass

# OPENAI_API_KEY = getpass()

# os.environ["OPENAI_API_KEY"] = OPENAI_API_KEY

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DocArrayHnswSearch 사용하기

from langchain_community.document_loaders import TextLoader
from langchain_community.vectorstores import DocArrayHnswSearch
from langchain_openai import OpenAIEmbeddings
from langchain_text_splitters import CharacterTextSplitter

documents = TextLoader("../../how_to/state_of_the_union.txt").load()
text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0)
docs = text_splitter.split_documents(documents)

embeddings = OpenAIEmbeddings()

db = DocArrayHnswSearch.from_documents(
    docs, embeddings, work_dir="hnswlib_store/", n_dim=1536
)

query = "What did the president say about Ketanji Brown Jackson"
docs = db.similarity_search(query)

print(docs[0].page_content)

Tonight. I call on the Senate to: Pass the Freedom to Vote Act. Pass the John Lewis Voting Rights Act. And while you’re at it, pass the Disclose Act so Americans can know who is funding our elections.

Tonight, I’d like to honor someone who has dedicated his life to serve this country: Justice Stephen Breyer—an Army veteran, Constitutional scholar, and retiring Justice of the United States Supreme Court. Justice Breyer, thank you for your service.

One of the most serious constitutional responsibilities a President has is nominating someone to serve on the United States Supreme Court.

And I did that 4 days ago, when I nominated Circuit Court of Appeals Judge Ketanji Brown Jackson. One of our nation’s top legal minds, who will continue Justice Breyer’s legacy of excellence.

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Similarity search with score

반환되는 distance score는 cosine distance입니다. 따라서 낮은 score가 더 좋습니다. 
docs = db.similarity_search_with_score(query)

docs[0]

(Document(page_content='Tonight. I call on the Senate to: Pass the Freedom to Vote Act. Pass the John Lewis Voting Rights Act. And while you’re at it, pass the Disclose Act so Americans can know who is funding our elections. \n\nTonight, I’d like to honor someone who has dedicated his life to serve this country: Justice Stephen Breyer—an Army veteran, Constitutional scholar, and retiring Justice of the United States Supreme Court. Justice Breyer, thank you for your service. \n\nOne of the most serious constitutional responsibilities a President has is nominating someone to serve on the United States Supreme Court. \n\nAnd I did that 4 days ago, when I nominated Circuit Court of Appeals Judge Ketanji Brown Jackson. One of our nation’s top legal minds, who will continue Justice Breyer’s legacy of excellence.', metadata={}),
 0.36962226)

import shutil

# delete the dir
shutil.rmtree("hnswlib_store")
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