■ CacheBackedEmbeddings 클래스의 from_bytes_store 정적 메소드를 사용해 CacheBackedEmbeddings 객체를 만드는 방법을 보여준다.
※ OPENAI_API_KEY 환경 변수 값은 .env 파일에 정의한다.
▶ main.py
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from dotenv import load_dotenv from langchain_openai import OpenAIEmbeddings from langchain.storage import LocalFileStore from langchain.embeddings import CacheBackedEmbeddings load_dotenv() openAIEmbeddings = OpenAIEmbeddings() localFileStore = LocalFileStore("./cache/") cacheBackedEmbeddings = CacheBackedEmbeddings.from_bytes_store(openAIEmbeddings, localFileStore, namespace = openAIEmbeddings.model) |
▶ requirements.txt
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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==3.0.0 langchain==0.2.6 langchain-core==0.2.10 langchain-openai==0.1.13 langchain-text-splitters==0.2.2 langsmith==0.1.82 multidict==6.0.5 numpy==1.26.4 openai==1.35.7 orjson==3.10.5 packaging==24.1 pydantic==2.7.4 pydantic_core==2.18.4 python-dotenv==1.0.1 PyYAML==6.0.1 regex==2024.5.15 requests==2.32.3 sniffio==1.3.1 SQLAlchemy==2.0.31 tenacity==8.4.2 tiktoken==0.7.0 tqdm==4.66.4 typing_extensions==4.12.2 urllib3==2.2.2 yarl==1.9.4 |
※ pip install python-dotenv langchain langchain-openai 명령을 실행했다.