■ InMemoryVectorStore 클래스의 as_retriever 메소드를 사용해 VectorStoreRetriever 객체를 만드는 방법을 보여준다.
▶ main.py
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from langchain_core.documents import Document from langchain_openai import OpenAIEmbeddings from langchain_core.vectorstores import InMemoryVectorStore documentList = [ Document(page_content = "Dogs are great companions, known for their loyalty and friendliness."), Document(page_content = "Cats are independent pets that often enjoy their own space." ) ] openAIEmbeddings = OpenAIEmbeddings() inMemoryVectorStore = InMemoryVectorStore.from_documents( documentList, embedding = openAIEmbeddings ) vectorStoreRetriever = inMemoryVectorStore.as_retriever( search_type = "similarity", search_kwargs = {"k" : 1} ) |
※ pip install langchain-openai 명령을 실행했다.