■ BM25Retriever 클래스의 from_texts 정적 메소드를 사용해 BM25Retriever 객체를 만드는 방법을 보여준다.
▶ main.py
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from langchain_community.retrievers import BM25Retriever stringList = [ "I like apples", "I like oranges", "Apples and oranges are fruits" ] bm25Retriever = BM25Retriever.from_texts(stringList, metadatas = [{"source" : 1}] * len(stringList1)) bm25Retriever.k = 2 |
▶ requirements.txt
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aiohappyeyeballs==2.4.0 aiohttp==3.10.5 aiosignal==1.3.1 annotated-types==0.7.0 anyio==4.4.0 attrs==24.2.0 certifi==2024.8.30 charset-normalizer==3.3.2 dataclasses-json==0.6.7 frozenlist==1.4.1 greenlet==3.1.0 h11==0.14.0 httpcore==1.0.5 httpx==0.27.2 idna==3.8 jsonpatch==1.33 jsonpointer==3.0.0 langchain==0.2.16 langchain-community==0.2.16 langchain-core==0.2.39 langchain-text-splitters==0.2.4 langsmith==0.1.120 marshmallow==3.22.0 multidict==6.1.0 mypy-extensions==1.0.0 numpy==1.26.4 orjson==3.10.7 packaging==24.1 pydantic==2.9.1 pydantic_core==2.23.3 PyYAML==6.0.2 rank-bm25==0.2.2 requests==2.32.3 sniffio==1.3.1 SQLAlchemy==2.0.34 tenacity==8.5.0 typing-inspect==0.9.0 typing_extensions==4.12.2 urllib3==2.2.3 yarl==1.11.1 |
※ install langchain-community rank_bm25 명령을 실행했다.