March 2026
Intermediate
504 pages
11h 26m
Korean
Content preview from 파이토치로 배우는 LLM & AI
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454
2
부
모델 사용
벡터 저장소를 만들었으니 유사도 검색을 어떻게 수행하는지 알아보겠습니다.
18.2.3
유사도 검색 수행하기
벡터 저장소를 준비하면 유사도 검색은 쉽습니다.
다음은 벡터 저장소로 유사도 검색을 수행하는 간단한 함수입니다.
def search_vectorstore(vectorstore, query, k=3):
results = vectorstore.similarity_search(query, k=k)
return results
여기서 보듯이 정말 간단합니다. 다음과 같은 매개변수를 사용해 일부 기능을 재정의하거나 확
장할 수 있습니다.
•
search_type
: 기본값이
similarity
이지만
MMR
maximum
marginal
relevance
을 위해
mmr
로 지정할 수 있습니
다. 제품 시스템을 구축할 때 실험해 볼 가치가 있습니다.
MMR
은 중복 결과를 피하고 싶을 때 특히 유용
합니다.
•
distance_metric
: 기본값이
cosine
이지만 임베딩 공간상의 두 벡터 사이의 직선 거리를 의미하는
l2
로
지정할 수도 있습니다. 또는 내적
inner
product
을 의미하는
ip
로 지정할 수 있습니다. 계산이 빠르지만 정확도
가 낮아질 수 있습니다.
•
lambda_mult
: 거리 측정의 엄격성을 제어하는
0
과
1
사이의 값입니다. ...
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